**Meet the editor**

Dr Xavier Perpiñà was born in Almenar, Spain, in 1976. He received the B.S. degree in physics, the M.Phil. degree in electronic engineering, and the Ph.D. degree from the Universitat Autònoma de Barcelona, Bellaterra, Spain, in 1999, 2002, and 2005, respectively. In 1999, he was with the Institut de Microelectrònica de Barcelona-Centre Nacional de Microelectrònica (IMB-CNM),

Spanish Research Council (CSIC), Bellaterra, Spain, where he worked in the clean room and, then until 2005, he began his research activity with the Power Devices and Systems Group, IMB-CNM. From 2005 to 2007, he was with Alstom Transport, where he developed studies on thermal management and power-converters reliability. He is currently a Contracted Researcher with IMB-CNM and his research deals with thermal investigations and reliability studies in power devices and packaging. He has authored and coauthored more than 60 research papers in international conferences and refereed journals. He also belongs to the scientific committee of EUROSIME conference and THERMINIC workshop.

Contents

**Preface IX** 

Chapter 1 **The Role of Light Railway in** 

**Part 1 Railway Systems in the World 1** 

Hassan A. Abdel-Mawla

Chapter 2 **Topological Analysis of Tokyo** 

Takeshi Ozeki

Zhao Zhisu

Hamid Yaghoubi,

Chapter 7 **Power System Modelling for** 

Chapter 6 **Maglev 123** 

**Part 2 Modelling for** 

**Sugarcane Transport in Egypt 3** 

**Metropolitan Railway System 25** 

Chapter 4 **Competitiveness and Sustainability of Railways 69**  Dave van der Meulen and Fienie Möller

Nariman Barazi and Mohammad Reza Aoliaei

**Urban Massive Transportation Systems 179** 

Johan Wiberg, Raid Karoumi and Costin Pacoste

Chapter 8 **Optimized Model Updating of a Railway Bridge for** 

Mario A. Ríos and Gustavo Ramos

**the Atacama Desert Railway – An Interpretation 51** 

Chapter 5 **Structural and Kinematic Analysis of EMS Maglev Trains 95** 

**Railway Infrastructure Design and Characterization 177** 

**Increased Accuracy in Moving Load Simulations 203** 

Chapter 3 **Privatization Versus Public Funding on** 

Jose Antonio Gonzalez-Pizarro

## Contents

### **Preface XIII**

	- **Part 2 Modelling for Railway Infrastructure Design and Characterization 177**

X Contents


Contents VII

Chapter 19 **Special Tunnel Blasting Techniques for Railway Projects 479** 

**the Railway Electromagnetic Environment 503**

Chapter 20 **Susceptibility of the GSM-R Transmissions to** 

Stephen Dudoyer, Virginie Deniau, Nedim Ben Slimen and Ricardo Adriano

More Ramulu


VI Contents

Chapter 9 **Controlling and Simulation of** 

Chapter 10 **Cellular Automaton Modeling of** 

Chapter 11 **Gaming Simulations for Railways:** 

Chapter 12 **Application of 3D Simulation Methods to** 

Elżbieta Szychta, Leszek Szychta, Mirosław Luft and Kamil Kiraga

Akiyasu Tomoeda

Sebastiaan Meijer

Chapter 13 **EMC Analysis of Railway Power** 

**Part 3 Signalling, Security and** 

Inmculada Gallego,

Chapter 15 **Influence of the Phreatic Level on** 

Anatoly Levchenkov,

Chapter 17 **Study and Design of an Electro** 

Chapter 18 **General Principles Regarding** 

Clavel Edith, Meunier Gérard, Bellon Marc and Frugier Didier

Petzek Edward and Radu Băncilă

Shodolapo Oluyemi Franklin and Gbenga Matthew Ayininuola

**Stray Currents in DC Railway by** 

**Passenger Transport Systems 255**

**Considering the Effects of Collection Mats 225** Mohammad Ali Sandidzadeh and Amin Shafipour

**Lessons Learned from Modeling Six Games for the Dutch Infrastructure Management 275** 

S. Baranowski, H. Ouaddi, L. Kone and N. Idir

**Infrastructure Construction in Railway 353** 

Chapter 14 **Criteria for Improving the Embankment-Structure Transition Design in Railway Lines 355**

Santos Sánchez-Cambronero and Ana Rivas

**the Stability of Earth Embankments 375** 

Chapter 16 **Evolutionary Algorithms in Embedded Intelligent Devices** 

Mikhail Gorobetz and Andrew Mor-Yaroslavtsev

**Using Satellite Navigation for Railway Transport 395** 

**Technical Device for Safety on Railway Network 421**

**the Rehabilitation of Existing Railway Bridges 447** 

**the Process of Induction Heating of Rail Turnouts 295** 

**Substation Modeling and Measurements Aspects 333** 

Preface

Railway transportation has become one of the main technological advances of our society. Since the first railway system used to carry coal from a mine in Shropshire (England, 1600), a lot of efforts have been made to improve this transportation concept. One of its milestones was the invention and development of the steam locomotive, but commercial rail travels became practical two hundred years later. Currently; electric railway traction chains have become a better solution than the traction systems with generating power on board (e.g., diesel or steam-based systems). This could not be possible without the advances experienced throughout the years in power electronics, mechanics and materials engineering. In terms of performances, ERTCs show the highest power-to-weight ratio, fastest acceleration and highest traction effort on steep gradients of the railway traction scenario. Other of their advantages includes less noise, lower maintenance requirements of the traction units, and a higher rational use of energy respecting and preserving the environment (e.g., energy harvesting systems as regenerative brakes or no greenhouse gasses' emissions). Obviously, their main disadvantages are the capital cost of the electrification line, depending on a trade-off between the distance and traffic volume of the service line.

In fact, the evolution of railway transportation could not be possible without the simultaneous growth of railway infrastructures, signalling and security. They are responsible for supporting, controlling and coordinating railway traffic. The high number of railway commercial lines around the most important cities in the world, as well as the requirements of the current business market, has made of them a key factor for the development of many commercial activities. Obviously, their design and characterization is not easy at all, becoming a much more complex procedure than

This book provides the reader an overview of railway systems from several countries, some details on modelling for railway infrastructure design and characterisation, and finally the implementation of signalling procedures, security protocols and infrastructures. Besides, it reports on research progress on these issues. During the preparation of this book, I asked the authors to add recent research findings and future works in this area and cite latest references in the chapter. For this reason, a variety of novel approaches in the covered topic are detailed in this book. Insightful and readerfriendly descriptions are presented to nourish readers of any level, from practicing and

those performed in the railway earlier stages.

## Preface

Railway transportation has become one of the main technological advances of our society. Since the first railway system used to carry coal from a mine in Shropshire (England, 1600), a lot of efforts have been made to improve this transportation concept. One of its milestones was the invention and development of the steam locomotive, but commercial rail travels became practical two hundred years later. Currently; electric railway traction chains have become a better solution than the traction systems with generating power on board (e.g., diesel or steam-based systems). This could not be possible without the advances experienced throughout the years in power electronics, mechanics and materials engineering. In terms of performances, ERTCs show the highest power-to-weight ratio, fastest acceleration and highest traction effort on steep gradients of the railway traction scenario. Other of their advantages includes less noise, lower maintenance requirements of the traction units, and a higher rational use of energy respecting and preserving the environment (e.g., energy harvesting systems as regenerative brakes or no greenhouse gasses' emissions). Obviously, their main disadvantages are the capital cost of the electrification line, depending on a trade-off between the distance and traffic volume of the service line.

In fact, the evolution of railway transportation could not be possible without the simultaneous growth of railway infrastructures, signalling and security. They are responsible for supporting, controlling and coordinating railway traffic. The high number of railway commercial lines around the most important cities in the world, as well as the requirements of the current business market, has made of them a key factor for the development of many commercial activities. Obviously, their design and characterization is not easy at all, becoming a much more complex procedure than those performed in the railway earlier stages.

This book provides the reader an overview of railway systems from several countries, some details on modelling for railway infrastructure design and characterisation, and finally the implementation of signalling procedures, security protocols and infrastructures. Besides, it reports on research progress on these issues. During the preparation of this book, I asked the authors to add recent research findings and future works in this area and cite latest references in the chapter. For this reason, a variety of novel approaches in the covered topic are detailed in this book. Insightful and readerfriendly descriptions are presented to nourish readers of any level, from practicing and

#### X Preface

knowledgeable electrical engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters. This book includes twenty chapters that were authored by world-wide well-known researchers. Each chapter was written in an introductory style beginning with the fundamentals, describing approaches to the hottest issues and concluding with a comprehensive discussion. The content in each chapter is taken from many publications in prestigious journals and conferences and followed by fruitful insights. The chapters in this book also provide many recent references for relevant topics, and interested readers will find these references helpful when exploring these topics in further detail.

This book is divided into three parts. Part 1 consists of six chapters devoted to describe how the railway systems have been developed in several countries and their socioeconomical impact. Part 2 consists of seven chapters devoted to providing some ideas on safety and reliability issues. Finally, part 3 consists of seven chapters devoted to parameters monitoring in railway scenario for safety and reliability purposes.

We hope that this book will fulfill the need for publication on infrastructure design, signalling, and security in railway, as well as being useful for engineers and scientists interested in learning about or developing any system related to this topic. Furthermore, this can be used as a text book for engineering advanced undergraduate and graduate students interested in learning about the topics raised in this book.

> **Xavier Perpinya**  Institut de Microelectronica de Barcelona, Campus Universitat Autónoma de Barcelona, Barcelona, Spain

X Preface

knowledgeable electrical engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters. This book includes twenty chapters that were authored by world-wide well-known researchers. Each chapter was written in an introductory style beginning with the fundamentals, describing approaches to the hottest issues and concluding with a comprehensive discussion. The content in each chapter is taken from many publications in prestigious journals and conferences and followed by fruitful insights. The chapters in this book also provide many recent references for relevant topics, and interested readers will

This book is divided into three parts. Part 1 consists of six chapters devoted to describe how the railway systems have been developed in several countries and their socioeconomical impact. Part 2 consists of seven chapters devoted to providing some ideas on safety and reliability issues. Finally, part 3 consists of seven chapters devoted to

We hope that this book will fulfill the need for publication on infrastructure design, signalling, and security in railway, as well as being useful for engineers and scientists interested in learning about or developing any system related to this topic. Furthermore, this can be used as a text book for engineering advanced undergraduate and graduate students interested in learning about the topics raised in this book.

**Xavier Perpinya** 

Spain

Institut de Microelectronica de Barcelona,

Campus Universitat Autónoma de Barcelona, Barcelona,

find these references helpful when exploring these topics in further detail.

parameters monitoring in railway scenario for safety and reliability purposes.

**Part 1** 

**Railway Systems in the World** 

**Part 1** 

**Railway Systems in the World** 

**1** 

*Egypt* 

**The Role of Light Railway in** 

Hassan A. Abdel-Mawla

**Sugarcane Transport in Egypt** 

*Department of Ag. Engineering, Al-Azhar University, Assiut,* 

The first section of the Egyptian standard railway for public transport service started at 1854. Fifteen years later, the first light railway network established to serve sugar industry southern Egypt. A light railway network initiated through the area considered for sugarcane production whenever a modern sugar mill established. The light railway represented the mechanism that continuously convey and feed each sugar factory with raw material of

As a principle transport system, the light railway networks started transport service simultaneously with the beginning operation of each sugar mill. Whenever a modern sugar mill constructed, a light railway net established for its own cane transport service. The first light railway network started service at the west bank of Nile at 1869 when the first modern sugar mill started operation at Armant (Ar. 691 *km* south Cairo). At 1896 the second oldest light railway was initiates at the west bank of Nile to serve cane transport to Nagaa-Hamadi factory (N. H. 553 *km* south Cairo). At the early stage of the 20th century, two light railway networks started cane transport service in Abo-Qurkas (AQ. 267 *km* south Cairo) in 1904 and in Kom-Ombo (KO. 834 *km* south Cairo) in 1912 when two sugar factories begin operation at these two locations. Other four light railway networks were established within the period from 1963 to 1987 in Edfo (Ed. 776 *km* south Cairo), Quse (Qu. 573 *km* south Cairo), Dishna, (Di. 573 *km* south Cairo) and Gerga (Ge. 502 *km* south Cairo) when the sugar mills started

Based on the data of the annual report of the Sugar Counsel 2010 and former reports, continuous change of the role of narrow railway system has been recorded over the last two decades. Figure 1 shows the development of the light railway system contribution to the transport of vegetative cane delivered as row material to sugar industry. Road transport strongly competes as cane transport mean due to constant improvement of infield roads and the availability of road vehicles. On the other hand, the decline of the narrow railway system contribution may partially refer to the expansion of cane plantations outside the light railway net. The chapter discusses the existing conditions and the expected future of the role of light railway initiated for cane transport in Egypt. Alternative road transport vehicles may replace the narrow railway because of availability in addition to transport cost. It seems like the conditions of narrow railway system of cane transport in Egypt has some similar

sugarcane produced in wide farm areas around the mill.

**1. Introduction** 

there **(Afifi 1988).** 

## **The Role of Light Railway in Sugarcane Transport in Egypt**

Hassan A. Abdel-Mawla *Department of Ag. Engineering, Al-Azhar University, Assiut, Egypt* 

### **1. Introduction**

The first section of the Egyptian standard railway for public transport service started at 1854. Fifteen years later, the first light railway network established to serve sugar industry southern Egypt. A light railway network initiated through the area considered for sugarcane production whenever a modern sugar mill established. The light railway represented the mechanism that continuously convey and feed each sugar factory with raw material of sugarcane produced in wide farm areas around the mill.

As a principle transport system, the light railway networks started transport service simultaneously with the beginning operation of each sugar mill. Whenever a modern sugar mill constructed, a light railway net established for its own cane transport service. The first light railway network started service at the west bank of Nile at 1869 when the first modern sugar mill started operation at Armant (Ar. 691 *km* south Cairo). At 1896 the second oldest light railway was initiates at the west bank of Nile to serve cane transport to Nagaa-Hamadi factory (N. H. 553 *km* south Cairo). At the early stage of the 20th century, two light railway networks started cane transport service in Abo-Qurkas (AQ. 267 *km* south Cairo) in 1904 and in Kom-Ombo (KO. 834 *km* south Cairo) in 1912 when two sugar factories begin operation at these two locations. Other four light railway networks were established within the period from 1963 to 1987 in Edfo (Ed. 776 *km* south Cairo), Quse (Qu. 573 *km* south Cairo), Dishna, (Di. 573 *km* south Cairo) and Gerga (Ge. 502 *km* south Cairo) when the sugar mills started there **(Afifi 1988).** 

Based on the data of the annual report of the Sugar Counsel 2010 and former reports, continuous change of the role of narrow railway system has been recorded over the last two decades. Figure 1 shows the development of the light railway system contribution to the transport of vegetative cane delivered as row material to sugar industry. Road transport strongly competes as cane transport mean due to constant improvement of infield roads and the availability of road vehicles. On the other hand, the decline of the narrow railway system contribution may partially refer to the expansion of cane plantations outside the light railway net. The chapter discusses the existing conditions and the expected future of the role of light railway initiated for cane transport in Egypt. Alternative road transport vehicles may replace the narrow railway because of availability in addition to transport cost. It seems like the conditions of narrow railway system of cane transport in Egypt has some similar

The Role of Light Railway in Sugarcane Transport in Egypt 5

Fig. 2. Light railway expansion areas in the Nile Valley.

may currently exceed 60% of the daily mill capacity.

Infield roads on which the narrow railway lines constructed may be expanded on a side of an irrigation or drainage channel may cross several bridges and may cross the main railway line of Upper Egypt. Double light railway lines may be expanded on the main roads to maintain easy motion of cane trains travel to or coming from several infield lines connected to the main lines by unions. The sub branches of the narrow railways may be double lines that include a main rail line on which the loaded train move and an auxiliary line for the travel of empty train coming from the mill. This arraignment of auxiliary rail line for the travel of empty train may be limited to certain locations to maintain smooth motion on the light railway lines.

Figure 3 shows a map of the second oldest narrow railway network (1896) that established to feed Naga-Hammady mill with row cane. The 115 years old cane transport narrow railway network of 420 km long still efficiently working by the help of seasonal maintenance. In this particular region, the contribution of narrow railway transport system

Infield railway lines are single lines on which a train moves either empty or loaded.

aspects of that of South Africa as reported by **Abdel-Mawla (2001)**. **Malelane (2000)**  concluded that the economics of each cane transport system establish the optimum mix of transport mode in South Africa. The availability of road transport given the limitations of fixed rail siding placement and infield haulage distances.

Fig. 1. Development of the role of light railway system for feeding row materials to sugar industry.

### **2. Light railways line expansion**

The narrow railway network and whole stalk wagons represented the principle cane delivery system especially for the old constructed sugar industry. The regions at which the narrow railway expanded for sugarcane transport occupy continuous areas along both sides of the Nile. Sugar factories located at the both Nile banks where narrow railway and whole stalk wagons receive the cane transported cross Nile by the help of a crane at certain ports. The railway lines started at the back and side gates of the sugar mill and branched along the infield roads through the cane production area. The main narrow railway lines near the mill gates include several grand unions and large number of switches.

Over 2200 km of the narrow gauge railways expanded to maintain feeding sugar industry with the raw materials that represented in sugarcane produced from the adjacent areas on both sides of the Nile as shown on the map Figure (2).

aspects of that of South Africa as reported by **Abdel-Mawla (2001)**. **Malelane (2000)**  concluded that the economics of each cane transport system establish the optimum mix of transport mode in South Africa. The availability of road transport given the limitations of

Fig. 1. Development of the role of light railway system for feeding row materials to sugar

The narrow railway network and whole stalk wagons represented the principle cane delivery system especially for the old constructed sugar industry. The regions at which the narrow railway expanded for sugarcane transport occupy continuous areas along both sides of the Nile. Sugar factories located at the both Nile banks where narrow railway and whole stalk wagons receive the cane transported cross Nile by the help of a crane at certain ports. The railway lines started at the back and side gates of the sugar mill and branched along the infield roads through the cane production area. The main narrow railway lines near the mill gates include several grand unions and large number of

Over 2200 km of the narrow gauge railways expanded to maintain feeding sugar industry with the raw materials that represented in sugarcane produced from the adjacent areas on

fixed rail siding placement and infield haulage distances.

industry.

switches.

**2. Light railways line expansion** 

both sides of the Nile as shown on the map Figure (2).

Fig. 2. Light railway expansion areas in the Nile Valley.

Infield roads on which the narrow railway lines constructed may be expanded on a side of an irrigation or drainage channel may cross several bridges and may cross the main railway line of Upper Egypt. Double light railway lines may be expanded on the main roads to maintain easy motion of cane trains travel to or coming from several infield lines connected to the main lines by unions. The sub branches of the narrow railways may be double lines that include a main rail line on which the loaded train move and an auxiliary line for the travel of empty train coming from the mill. This arraignment of auxiliary rail line for the travel of empty train may be limited to certain locations to maintain smooth motion on the light railway lines. Infield railway lines are single lines on which a train moves either empty or loaded.

Figure 3 shows a map of the second oldest narrow railway network (1896) that established to feed Naga-Hammady mill with row cane. The 115 years old cane transport narrow railway network of 420 km long still efficiently working by the help of seasonal maintenance. In this particular region, the contribution of narrow railway transport system may currently exceed 60% of the daily mill capacity.

The Role of Light Railway in Sugarcane Transport in Egypt 7

The narrow railway lines established for cane transport initiated with similar gauge of 2 feet (61 cm) that represent the inside width between the rails (Figure 4). The narrow track sleepers are fabricated from cold formed steel plates of 2 m width. The ballast-less narrow track constructed by arranging the steel sleepers 0.75 to 1 m apart directly on the road soil

(Figure 5). The two feet spaced rails are fixed to the sleepers with bolts and clamps.

Fig. 4. Size (gauge) of the Egyptian light railway for cane transport

Fig. 5. A balastless narrow railway expanded on a bank of an irrigation channel

**3. Light railway system transport elements** 

**3.1 Light railway lines** 

Fig. 3. A map of light railway network of NH. sugar factory established 1896 (Courtsy, Sugar & Int. Idustry Company)

### **3. Light railway system transport elements**

### **3.1 Light railway lines**

6 Infrastructure Design, Signalling and Security in Railway

Fig. 3. A map of light railway network of NH. sugar factory established 1896 (Courtsy,

Sugar & Int. Idustry Company)

The narrow railway lines established for cane transport initiated with similar gauge of 2 feet (61 cm) that represent the inside width between the rails (Figure 4). The narrow track sleepers are fabricated from cold formed steel plates of 2 m width. The ballast-less narrow track constructed by arranging the steel sleepers 0.75 to 1 m apart directly on the road soil (Figure 5). The two feet spaced rails are fixed to the sleepers with bolts and clamps.

Fig. 4. Size (gauge) of the Egyptian light railway for cane transport

Fig. 5. A balastless narrow railway expanded on a bank of an irrigation channel

The Role of Light Railway in Sugarcane Transport in Egypt 9



Since all the sugar factories followed one company, the light railway wagons fabricated for cane transport size variation is very limited. The wagons designed to be whole stalk loaded parallel to the longitudinal axel of the wagon. Unlike the Australian cane bins described by

The wagon has two bogies each of four steel wheels on which a rectangular steel flat surface is fixed. Steel columns are bolted vertically to the outer side of the rectangular flat surface that form a basket that hold cane parallel to the longitudinal axle of the wagon. The ground clearance to the bottom surface of the wagon around 60 cm. The wheel diameter may be 32 cm from the flange side and 24 cm from the wheel trade side. The light railway wagon flat load surface may be 6 to 7 m in length and 1.5 to 1.8 m in width and the side columns are 1.4 to 1.6 m in height. Wheel base from the center of the rear wheel of the rear bogie to the

**Lynn (2008)** show large variation of wagons size that carry chopped cane.

centre of front wheel of the front bogie ranged from 5 to 5.7 m.

lines to save more room for the trains coming from the fields.

Fig. 7. A narrow gauge locomotive on the way to the field

**3.3 Light railway whole-stalk cane wagons** 

train to the departure line.

Fishplates are used to connect the ends of rails along the track. A short space is left between the ends of the rails for thermal expansion. Since this sort of rail lines are ballast-less expanded on dirt roads with considerably wide interval between sleepers, the alignment of the rail ends at the point of fishplate connection is not always secured. To overcome the probable vertical misalignment at the expansion gap, a short single bolt rail plate is used. Figure 6 show the single bolt alignment short rail piece. Whenever the train is coming from any direction, the near end of the plate is aligned to the end of the rail, carrying the train wheel and turn around the pin to be aligned to the front rail. This simple arrangement largely reduces hard sudden impact, reduces rapid wear and breakdowns of the rail wagons undercarriage.

Fig. 6. Rail ends connection

### **3.2 Light railway locomotives**

Variable sizes of locomotive are available to pull the light railway sugarcane train. Locomotives of variable types have been imported mainly from Germany, Romania, Japan, and Slovakia. Based on the statistics, old and new German and Romanian types represent the major numbers of locomotives belong to the sugarcane transport system. The sizes and function of locomotives of the narrow railway cane transport system may be:


Fishplates are used to connect the ends of rails along the track. A short space is left between the ends of the rails for thermal expansion. Since this sort of rail lines are ballast-less expanded on dirt roads with considerably wide interval between sleepers, the alignment of the rail ends at the point of fishplate connection is not always secured. To overcome the probable vertical misalignment at the expansion gap, a short single bolt rail plate is used. Figure 6 show the single bolt alignment short rail piece. Whenever the train is coming from any direction, the near end of the plate is aligned to the end of the rail, carrying the train wheel and turn around the pin to be aligned to the front rail. This simple arrangement largely reduces hard sudden

Variable sizes of locomotive are available to pull the light railway sugarcane train. Locomotives of variable types have been imported mainly from Germany, Romania, Japan, and Slovakia. Based on the statistics, old and new German and Romanian types represent the major numbers of locomotives belong to the sugarcane transport system. The sizes and


function of locomotives of the narrow railway cane transport system may be:

impact, reduces rapid wear and breakdowns of the rail wagons undercarriage.

Fig. 6. Rail ends connection

**3.2 Light railway locomotives** 


Fig. 7. A narrow gauge locomotive on the way to the field

### **3.3 Light railway whole-stalk cane wagons**

Since all the sugar factories followed one company, the light railway wagons fabricated for cane transport size variation is very limited. The wagons designed to be whole stalk loaded parallel to the longitudinal axel of the wagon. Unlike the Australian cane bins described by **Lynn (2008)** show large variation of wagons size that carry chopped cane.

The wagon has two bogies each of four steel wheels on which a rectangular steel flat surface is fixed. Steel columns are bolted vertically to the outer side of the rectangular flat surface that form a basket that hold cane parallel to the longitudinal axle of the wagon. The ground clearance to the bottom surface of the wagon around 60 cm. The wheel diameter may be 32 cm from the flange side and 24 cm from the wheel trade side. The light railway wagon flat load surface may be 6 to 7 m in length and 1.5 to 1.8 m in width and the side columns are 1.4 to 1.6 m in height. Wheel base from the center of the rear wheel of the rear bogie to the centre of front wheel of the front bogie ranged from 5 to 5.7 m.

The Role of Light Railway in Sugarcane Transport in Egypt 11

Figures 10 and 11 show the trains while transporting sugarcane. The operation of the light railway system for cane supply to the mill has to be performed according to a pre-defined schedule. The mill seasonal operation period should be approximately estimated based on the daily capacity of the mill, cane production area and average production of the unit area.

The size of the railway wagons fleet required for a sugar mill may be determined according to variable conditions. The mill daily capacity represents the total mass of raw materials has to be supplied to the mill around 24 hours. Row cane delivery Schedule plan should determine the quantities of sugarcane to be transported by road vehicles. General estimation of the average rail wagon capacity should be estimated based on the past season data. Cycle time of the rail wagon transport trip should also be clear and specified. In addition to several other factors related to harvesting, infield transport and loading, the rate of the rail

The rate of row materials delivered by the light railway wagons around the day should be managed by the mill administration to reduce the waiting time at the unloading queue. The mill administration may have to consider the following steps to estimate the numbers of the





**Androw and Ian (2005)** reported that several mill regions within the Australian sugar industry are currently exploring long-term scenarios to reduce costs in the harvesting and rail transport of sugarcane. These efficiencies can be achieved through extending the time window of harvesting, reducing the number of harvesters, and investing in new or

certain region and then pulls the loaded wagons back at specific time.

diurnal operated trains and the overnight operated trains.

The principle objectives of railway wagons operation schedule may include:

2. To reduce the probability of loaded wagons delivery delay. 3. To face the overload transport due to accidental conditions.

1. To secure uniform diurnal arrival of the current of railway wagons to the mill.

The average data of the recent juicing seasons would be helpful in that concern.

wagons breakdowns occurred during the season should be considered.

rail wagons, pull locomotives and operation team around the day:

to the morning and evening shifts.

the light railway system.

**3.4 Light railways system operation schedule** 

4. To secure overnight operation of the mill.

The loading volume inside the wagon may be ranged from 14 to 18 m3. The cane is loaded parallel to the longitudinal axle of the wagon. The load may be expanded up to 1 m over the wagon side columns to permit higher capacity of the wagon.

Transverse steel channels welded to the loading surface of the wagon to permit passing the chains under the load while unloading the wagon in the mill. Figures (8) and (9) shows isometric and projection drawings of the light railway cane transport wagon.

Fig. 8. Isometric of the cane transport light rail-wagon

Fig. 9. Common dimensions of the cane transport light railway wagon

### **3.4 Light railways system operation schedule**

10 Infrastructure Design, Signalling and Security in Railway

The loading volume inside the wagon may be ranged from 14 to 18 m3. The cane is loaded parallel to the longitudinal axle of the wagon. The load may be expanded up to 1 m over the

Transverse steel channels welded to the loading surface of the wagon to permit passing the chains under the load while unloading the wagon in the mill. Figures (8) and (9) shows

isometric and projection drawings of the light railway cane transport wagon.

wagon side columns to permit higher capacity of the wagon.

Fig. 8. Isometric of the cane transport light rail-wagon

Fig. 9. Common dimensions of the cane transport light railway wagon

The principle objectives of railway wagons operation schedule may include:


Figures 10 and 11 show the trains while transporting sugarcane. The operation of the light railway system for cane supply to the mill has to be performed according to a pre-defined schedule. The mill seasonal operation period should be approximately estimated based on the daily capacity of the mill, cane production area and average production of the unit area. The average data of the recent juicing seasons would be helpful in that concern.

The size of the railway wagons fleet required for a sugar mill may be determined according to variable conditions. The mill daily capacity represents the total mass of raw materials has to be supplied to the mill around 24 hours. Row cane delivery Schedule plan should determine the quantities of sugarcane to be transported by road vehicles. General estimation of the average rail wagon capacity should be estimated based on the past season data. Cycle time of the rail wagon transport trip should also be clear and specified. In addition to several other factors related to harvesting, infield transport and loading, the rate of the rail wagons breakdowns occurred during the season should be considered.

The rate of row materials delivered by the light railway wagons around the day should be managed by the mill administration to reduce the waiting time at the unloading queue. The mill administration may have to consider the following steps to estimate the numbers of the rail wagons, pull locomotives and operation team around the day:


**Androw and Ian (2005)** reported that several mill regions within the Australian sugar industry are currently exploring long-term scenarios to reduce costs in the harvesting and rail transport of sugarcane. These efficiencies can be achieved through extending the time window of harvesting, reducing the number of harvesters, and investing in new or

The Role of Light Railway in Sugarcane Transport in Egypt 13

Fig. 10. A narrow rail train is loaded with cane and ready for pull

Fig. 11. Train loaded with on the way back to the mill

upgraded infrastructures. As part of a series of integrated models to conduct the analysis, we developed a capacity planning model for transport to estimate the (1) number of locomotives and shifts required; (2) the number of bins required; and (3) the delays to harvesting operations resulting from harvesters waiting for bin deliveries. The schedule developed to operate the Egyptian system may have similar objectives **(Abdel-Mawla 2011)**. For example, the second oldest sugar mill (N. H.) started operation in 1896, the light railway system used to transport almost 100% of the cane delivered to the mill. At present, the light railway wagons deliver only 50% of the mill daily capacity. The mill holds the most long light railway network (410 km) expanded through the cane fields. The mill also has 1700 light railway wagons ready for operation. Large amount of field data concerning crop, field, environment and labors required for the proper design of the light railway operation schedule. Concerning the determination of the rail wagon numbers, the basic data presented in Table 1 may be necessary.


Table 1. Basic data required to estimate the number of light rail wagons.

Table 2 presents estimation of the narrow railway wagons fleet size required to secure adequate supply of the mill daily capacity of cane row materials.


Table 2. Estimation of the railway wagon fleet size

The efficiency of the narrow railway cane transport system may be largely improved by reducing transport cycle time as follow:


upgraded infrastructures. As part of a series of integrated models to conduct the analysis, we developed a capacity planning model for transport to estimate the (1) number of locomotives and shifts required; (2) the number of bins required; and (3) the delays to harvesting operations resulting from harvesters waiting for bin deliveries. The schedule developed to operate the Egyptian system may have similar objectives **(Abdel-Mawla 2011)**. For example, the second oldest sugar mill (N. H.) started operation in 1896, the light railway system used to transport almost 100% of the cane delivered to the mill. At present, the light railway wagons deliver only 50% of the mill daily capacity. The mill holds the most long light railway network (410 km) expanded through the cane fields. The mill also has 1700 light railway wagons ready for operation. Large amount of field data concerning crop, field, environment and labors required for the proper design of the light railway operation schedule. Concerning the determination of the rail wagon numbers, the basic data presented

in Table 1 may be necessary.

Shift Shift

Morning 7 am

Evening 15 pm

reducing transport cycle time as follow:


Night 23 pm

Diurnal

duration

Table 2. Estimation of the railway wagon fleet size

Item Value

Estimated season duration = 140 days

Required hourly supply = 500 tons/h Average rail wagon load = 9 tons

Mill capacity = 1.7 million ton/season

Daily supply = 12000 tons/day, approximately

Table 1. Basic data required to estimate the number of light rail wagons.

adequate supply of the mill daily capacity of cane row materials.

Required cane supply ton


Table 2 presents estimation of the narrow railway wagons fleet size required to secure

Light railway

15 pm 4000 50 2000 223 7

7 am 4000 90 3600 400 <sup>19</sup>

The efficiency of the narrow railway cane transport system may be largely improved by

23 pm 4000 10 400 45


contribution Required

wagons

% ton From To Fro

Departure time

> 16 pm

00 am

am

pm

Return time

m

12 am

23 pm

Mill yard waiting

6-10

10

To h

19 pm

6 am

Fig. 10. A narrow rail train is loaded with cane and ready for pull

Fig. 11. Train loaded with on the way back to the mill

The Role of Light Railway in Sugarcane Transport in Egypt 15

Few mechanical cane loaders were available till the Aswan Mechanization Company established at 1980. At that time large number of Bell type cane loaders imported and operated. Even though, the company stops purchasing new loaders and the majority of their loaders become old, the farmers bought those old loaders, rebuild them and bring them to operation again **(Abdel-Mawla 2010)**. Recently, other tractor mounted loaders may be locally developed and operated for cane loading. Figure (13) shows mechanical loading of

Light railway system also designed to handle the cross Nile transported cane. The system depends on the similarity in design and size of the cane holding bins fixed on the ship to that of the light railway wagons. Actually, light rail wagon frames fixed on the ship each of them have certain code number. Farmers load their cane each in certain frames on the ship. After the ship load complete, it travels across Nile to the unloading crane. A light railway line passes opposite to the crane. The crane lift the load conserving its dimension and structure and place it into a wagon (taking the same code number) waiting on the rail line. As soon as the rail wagon receives the load it pulled away waiting for pull to the mill.

the light rail-wagons using a tractor mounted loader developed by the author 2011.

Another light rail wagon pulled to the crane loading area as indicated in Figure (14).

Fig. 13. Mechanical loading of light railway wagons using a tractor mounted loader

The mechanism of unloading the light rail-wagons to the mill conveyor may vary from mill to another. A crane that carry the loaded wagon up then inverse the wagon to discharge the load over the conveyor may be found in Kom-Ombo mill. The empty wagon then returned back to the rail line and pulled away to give the chance to another wagon to be unloaded. The other common unloading mechanism may include a crane that left the wagons load with help of chains and place it over the conveyor. The unloaded wagon then moved and another one advanced toward the crane. Figure 15 show the chain un-loader which

**4.3 Mechanical loading** 

commonly used in sugar mills.

(developed by the author).

### **4. Light railway wagons loading and unloading**

### **4.1 Loading**

The cane transport administration of the mill distributes the empty light railway wagons according to the schedule. The driver of the locomotive leaves the wagons in the transloading site scheduled for cane delivery. Farmers bring the cane from inside fields to the location at which the wagons loaded. The common activity is to start loading the wagons in the morning. Loading may be done manually or mechanically according to the availability of mechanical loaders.

### **4.2 Manual loading**

The light railway of loading surface 60 to 70 cm high from the ground surface may be loaded manually (Figure 12). Two labors start carrying cane bundles, climb a ladder and place them inside the wagon. Even though the manual loading is considered adverse operation, it may permit some important advantages to obtain a higher density load such as:


Fig. 12. Labor loading of rail-wagons with sugarcane

### **4.3 Mechanical loading**

14 Infrastructure Design, Signalling and Security in Railway

The cane transport administration of the mill distributes the empty light railway wagons according to the schedule. The driver of the locomotive leaves the wagons in the transloading site scheduled for cane delivery. Farmers bring the cane from inside fields to the location at which the wagons loaded. The common activity is to start loading the wagons in the morning. Loading may be done manually or mechanically according to the availability

The light railway of loading surface 60 to 70 cm high from the ground surface may be loaded manually (Figure 12). Two labors start carrying cane bundles, climb a ladder and place them inside the wagon. Even though the manual loading is considered adverse operation, it may permit some important advantages to obtain a higher density load such as: - The labor loaders may fit the cane bundles tightly to ensure efficient use the whole



**4. Light railway wagons loading and unloading** 

**4.1 Loading** 

of mechanical loaders.

**4.2 Manual loading** 

field.

of the wagon.

Fig. 12. Labor loading of rail-wagons with sugarcane

volume of the wagon.

Few mechanical cane loaders were available till the Aswan Mechanization Company established at 1980. At that time large number of Bell type cane loaders imported and operated. Even though, the company stops purchasing new loaders and the majority of their loaders become old, the farmers bought those old loaders, rebuild them and bring them to operation again **(Abdel-Mawla 2010)**. Recently, other tractor mounted loaders may be locally developed and operated for cane loading. Figure (13) shows mechanical loading of the light rail-wagons using a tractor mounted loader developed by the author 2011.

Light railway system also designed to handle the cross Nile transported cane. The system depends on the similarity in design and size of the cane holding bins fixed on the ship to that of the light railway wagons. Actually, light rail wagon frames fixed on the ship each of them have certain code number. Farmers load their cane each in certain frames on the ship. After the ship load complete, it travels across Nile to the unloading crane. A light railway line passes opposite to the crane. The crane lift the load conserving its dimension and structure and place it into a wagon (taking the same code number) waiting on the rail line. As soon as the rail wagon receives the load it pulled away waiting for pull to the mill. Another light rail wagon pulled to the crane loading area as indicated in Figure (14).

The mechanism of unloading the light rail-wagons to the mill conveyor may vary from mill to another. A crane that carry the loaded wagon up then inverse the wagon to discharge the load over the conveyor may be found in Kom-Ombo mill. The empty wagon then returned back to the rail line and pulled away to give the chance to another wagon to be unloaded. The other common unloading mechanism may include a crane that left the wagons load with help of chains and place it over the conveyor. The unloaded wagon then moved and another one advanced toward the crane. Figure 15 show the chain un-loader which commonly used in sugar mills.

Fig. 13. Mechanical loading of light railway wagons using a tractor mounted loader (developed by the author).

The Role of Light Railway in Sugarcane Transport in Egypt 17

According to **Abdel-Mawla (2000)**, the narrow railway network faces breakdown problems due to the wear of long parts of the rail track. Currently, the light railway transport around 40% of the total cane delivered to sugar mills as general average for the

As previously explained some of the light railway systems started about 140 years ago. The old narrow railway expanded on the infield roads have been facing problems of steel components worn out. In spite of continuous seaseonal maintenance, the railway network have several corroded parts. Some of the narrow railway tracks constructed on the clay soil of the infield roads which is in the same level of the neighbor fields. The sleepers, bolts, fishplats and other parts of the rail track gradually covered by the road dirt. Moisture of underground water as well as moisture infeltrated from irrigation water may reach the rail track. The clay soil preservs moisture around the buried track causing

In the routin maintenance, the labors uncover the rail and change the wear-out parts that are easily to descover. Figure 16 show the rusted steel sleepers of the narrow railroad

Some parts of the old light railway network may become out of service because of the intensive breakdowns due to wear out. In most cases the track should be completely replaced otherwice several accedents expected due to loaded wagons turn a side or track climb where intensive losses may be occurred . Whenever such accedents repeated, the farmers abstain from transporting by the light railway and go for road transport even

Fig. 16. Balastless narrow rail track showing intensive ruste of sleepers buried in the clay soil

**5. Light railway problems** 

intensive rust of th steel parts.

though it is more costly.

eight sugar mills.

track.

**5.1 Problems related to rail track wear out** 

Fig. 14. Light railway system handle cane transported cross Nile

Fig. 15. Unloading light rail wagons.

### **5. Light railway problems**

16 Infrastructure Design, Signalling and Security in Railway

Fig. 14. Light railway system handle cane transported cross Nile

Fig. 15. Unloading light rail wagons.

### **5.1 Problems related to rail track wear out**

According to **Abdel-Mawla (2000)**, the narrow railway network faces breakdown problems due to the wear of long parts of the rail track. Currently, the light railway transport around 40% of the total cane delivered to sugar mills as general average for the eight sugar mills.

As previously explained some of the light railway systems started about 140 years ago. The old narrow railway expanded on the infield roads have been facing problems of steel components worn out. In spite of continuous seaseonal maintenance, the railway network have several corroded parts. Some of the narrow railway tracks constructed on the clay soil of the infield roads which is in the same level of the neighbor fields. The sleepers, bolts, fishplats and other parts of the rail track gradually covered by the road dirt. Moisture of underground water as well as moisture infeltrated from irrigation water may reach the rail track. The clay soil preservs moisture around the buried track causing intensive rust of th steel parts.

In the routin maintenance, the labors uncover the rail and change the wear-out parts that are easily to descover. Figure 16 show the rusted steel sleepers of the narrow railroad track.

Some parts of the old light railway network may become out of service because of the intensive breakdowns due to wear out. In most cases the track should be completely replaced otherwice several accedents expected due to loaded wagons turn a side or track climb where intensive losses may be occurred . Whenever such accedents repeated, the farmers abstain from transporting by the light railway and go for road transport even though it is more costly.

Fig. 16. Balastless narrow rail track showing intensive ruste of sleepers buried in the clay soil

The Role of Light Railway in Sugarcane Transport in Egypt 19

The narrow railroad has to be doublicated at several locations. The main track is for the loaded train travel from the field to the mill. The auxilary track established at certain locations for the travel of the empty train coming from the factory to the field. The additional track also maintain the manuver of the locomotives while collecting the loaded wagons together and the manuver of the pull locomotive to turn in front of the loaded train before pulling it back to the mill. It has been observed that intensive herbs may grow on the auxiliary patrs of the railroad

Fig. 18. The narrow railroad constructed on the middle of an infield road with parts covered

Figure 19. Intinsive herbs may cause wagon wheels climb off the track.

Fig. 19. Herbs intensively grow and harm the auxiliary railroad

with dirt

### **5.2 Problems related to system operation**

The light railway system employed for cane transport may be considered a slow system where the loaded vehicle wait for long time to be pulled back to the mill. The empty rail wagons distributed to several fields by a distribution locomotive. After these wagons been loaded with cane, the distribution locomotive move them to certain location where the stuff responsible for the train operation attach the loaded rail wagons together. The train loaded with can attached to the pull locomotive and start move back to the mill. Therefore it may last for long time before the train reach the mill. Actually, the train has to travel at limited speed (10-15 km/h) to avoid the accedents may occure at the intersections of the railroad and infield roads. Also train has to stop at the railroad switches where the locomotive driver or his helper has to swich it himself. The railroad swiches may be abused by young farmers, so that the locomotive driver himself should be sure about its position before cross.

The longer duration from the time of loading to the time of weighing the wagon load in the mill is critical for the farmer. The moisture losses from the vegitative load may be of high rate specially in such hot dry weather. Science the mony value of the load will be determined according to its weight, farmers may prefer to go for faster transport system to avoid vehicle load weight losses.

### **5.3 Problems related to farmers behaviour and road conditions**

Some other railroad tracks may be constructed on the irrigation channel banks. In such cases, water pipes passes under the railroad track to convey irrigation water from the channel to the field. Intensive soil erosion may occurred under the rail track because of the repeated activities while opening and closing the irrigation pipes as shown in Figure17. Some other farmers may park their animals on the railroad whenever they are out of the season which may be a reason of soil erosion under the railroad and/or the loosen of the track and sleepers. In several cases, the narrow railroad trak expanded on the same infield road on which farmers, animals and equipment move. Therefore, some parts of the track may be covered with dirt Figure 18. Also, some equipment drivers do not maintain the safety of the narrow railroad track while moving.

Fig. 17. Soil Erosion under the railroad.

The light railway system employed for cane transport may be considered a slow system where the loaded vehicle wait for long time to be pulled back to the mill. The empty rail wagons distributed to several fields by a distribution locomotive. After these wagons been loaded with cane, the distribution locomotive move them to certain location where the stuff responsible for the train operation attach the loaded rail wagons together. The train loaded with can attached to the pull locomotive and start move back to the mill. Therefore it may last for long time before the train reach the mill. Actually, the train has to travel at limited speed (10-15 km/h) to avoid the accedents may occure at the intersections of the railroad and infield roads. Also train has to stop at the railroad switches where the locomotive driver or his helper has to swich it himself. The railroad swiches may be abused by young farmers, so that the locomotive driver

The longer duration from the time of loading to the time of weighing the wagon load in the mill is critical for the farmer. The moisture losses from the vegitative load may be of high rate specially in such hot dry weather. Science the mony value of the load will be determined according to its weight, farmers may prefer to go for faster transport system to

Some other railroad tracks may be constructed on the irrigation channel banks. In such cases, water pipes passes under the railroad track to convey irrigation water from the channel to the field. Intensive soil erosion may occurred under the rail track because of the repeated activities while opening and closing the irrigation pipes as shown in Figure17. Some other farmers may park their animals on the railroad whenever they are out of the season which may be a reason of soil erosion under the railroad and/or the loosen of the track and sleepers. In several cases, the narrow railroad trak expanded on the same infield road on which farmers, animals and equipment move. Therefore, some parts of the track may be covered with dirt Figure 18. Also, some equipment drivers do not maintain the

**5.2 Problems related to system operation** 

himself should be sure about its position before cross.

safety of the narrow railroad track while moving.

Fig. 17. Soil Erosion under the railroad.

**5.3 Problems related to farmers behaviour and road conditions** 

avoid vehicle load weight losses.

The narrow railroad has to be doublicated at several locations. The main track is for the loaded train travel from the field to the mill. The auxilary track established at certain locations for the travel of the empty train coming from the factory to the field. The additional track also maintain the manuver of the locomotives while collecting the loaded wagons together and the manuver of the pull locomotive to turn in front of the loaded train before pulling it back to the mill. It has been observed that intensive herbs may grow on the auxiliary patrs of the railroad Figure 19. Intinsive herbs may cause wagon wheels climb off the track.

Fig. 18. The narrow railroad constructed on the middle of an infield road with parts covered with dirt

Fig. 19. Herbs intensively grow and harm the auxiliary railroad

The Role of Light Railway in Sugarcane Transport in Egypt 21

Fig. 21. Replacing the corroded steel sleepers of the rail track

Fig. 22. Balancing the level of the rail track

### **6. Light railways transport system maintenance**

### **6.1 Equipment maintenance**

Routine maintenance of Locomotives has been continuously done during the operation season. After the operation season end (in June), seasonal inspection of the locomotives started at the mill workshop. Important repair should be accomplished to make the total locomotive power ready before the next operation season start at the end of December. Some locomotives purchased during 1960's still working by the help of continuous maintenance and repair. The rail wagons maintenance also take place at the end of the season. Replacing old were up or broken bearings, gracing, replacing the twisted columns, and welding broken parts may be the major activities done to rail wagons. Replacing wear out wheels, broken springs and repair damaged bogies are also common activities of the rail wagons maintenance. Some old wagons may become out of service, the staff may decide to consider them salvage and forward a report to replace them. The new rail wagons for cane transport fabricated in the heavy equipment assembly factory belongs to the sugar company in Cairo to replace the salvage wagons.

### **6.2 Rail track maintenance**

Maintenance of the rail track start after the operation season end in June and should be finished at December before the new season start. Technicians walk over the rail track inspecting the type and location of the breakdowns (Figure 20). After localizing breakdowns, technicians uncover the wear out parts of the track to perform maintenance and repair activities. The operation of railway network maintenance may include clear dirt or weeds that cover the track, tightening loose bolts and nuts and replace wear parts. Replace wear up sleepers may be the most common activity during the maintenance season Figure 21. The rails parallelism and rail gage should be also inspected and adjusted. The final step of the narrow railroad maintenance is to test and adjust the rail level Figure 22. A monthly report has to be forward to the narrow railway engineering administration showing the completed job.

Fig. 20. Two technicians inspect the probable breakdowns of the rail track

Routine maintenance of Locomotives has been continuously done during the operation season. After the operation season end (in June), seasonal inspection of the locomotives started at the mill workshop. Important repair should be accomplished to make the total locomotive power ready before the next operation season start at the end of December. Some locomotives purchased during 1960's still working by the help of continuous maintenance and repair. The rail wagons maintenance also take place at the end of the season. Replacing old were up or broken bearings, gracing, replacing the twisted columns, and welding broken parts may be the major activities done to rail wagons. Replacing wear out wheels, broken springs and repair damaged bogies are also common activities of the rail wagons maintenance. Some old wagons may become out of service, the staff may decide to consider them salvage and forward a report to replace them. The new rail wagons for cane transport fabricated in the heavy equipment

assembly factory belongs to the sugar company in Cairo to replace the salvage wagons.

Fig. 20. Two technicians inspect the probable breakdowns of the rail track

Maintenance of the rail track start after the operation season end in June and should be finished at December before the new season start. Technicians walk over the rail track inspecting the type and location of the breakdowns (Figure 20). After localizing breakdowns, technicians uncover the wear out parts of the track to perform maintenance and repair activities. The operation of railway network maintenance may include clear dirt or weeds that cover the track, tightening loose bolts and nuts and replace wear parts. Replace wear up sleepers may be the most common activity during the maintenance season Figure 21. The rails parallelism and rail gage should be also inspected and adjusted. The final step of the narrow railroad maintenance is to test and adjust the rail level Figure 22. A monthly report has to be forward to the narrow railway engineering administration

**6. Light railways transport system maintenance** 

**6.1 Equipment maintenance** 

**6.2 Rail track maintenance** 

showing the completed job.

Fig. 21. Replacing the corroded steel sleepers of the rail track

Fig. 22. Balancing the level of the rail track

The Role of Light Railway in Sugarcane Transport in Egypt 23

future of the sugarcane light railway of Australia, **John Browning (2007)** stated that "Cane railways will continue to surprise and to interest, and they will remain "special" to the men who operate them, to the many visitors to the areas in which they run, and to those who simply love railways". It has been recommended that, some of the modern techniques developed in countries such as Australia to control the light railway sugarcane transport

Finally, the light railway for sugarcane transport represents the backbone of the raw material feeding system for sugar industry in Egypt. The system has several advantages compared to road transport such as lower transport cost, higher reliability, higher stability and minimum accidents occurred. Application of the advanced techniques for minimizing transport cycle duration expected to help for regaining the pioneer role of the light railway transport system. Practical ideas to increase wagons capacity and to improve mill yard management have been currently developed to speed up the system. Light railway transport system will continue being the familiar lovely transport system for

Fig. 23. Cost of light railway transport compared to road transport

The author wishes to announce that part of the data was collected through a project financed by the Egyptian Science and Technology Development Fund. The help of the

members of the Sugar and Integrated Industry Company is also acknowledged.

cycle time should be considered.

sugarcane farmers.

**8. Acknowledgements** 

### **7. Light railways future**

As previously discussed, each narrow railway network constructed and started operation simultaneously with the sugar factory initiation. The light railway networks belong to the old sugar factories initiated during the 19th century and those initiated at the early period of the 20th century used to supply 100% of the mill daily capacity. The narrow railway network expansion has been very limited compared to the expansion of sugar cane production area. According to **Soltan and Mohammed (2008)**, the area of sugarcane has been increased from less than 200,000 acres at 1980's to about 350,000 acres at 2008. Therefore the light railway of sugarcane transport stay constant and the cane area expanded more than 40 % outside the network. Since the role of the narrow railway sugarcane transport system declined from about 90% to about 40%. Considering the 40% decline because of cane area expansion outside the network, therefore declined of the light railway system transport may only be about 10%. Actually the percent contribution of the cane transported may be decreased but the total tonnage transported by the narrow railway system may be increased because the average unit area production increased and the mills now working at their full capacities.

The change of some farms to road vehicle may be because of the availability of their own vehicles or the advantages offered by road transport. The most important advantage offered by road transport is the short duration of transport cycle that save the excessive moisture losses that reduces the total weight and money value of the wagon load. In contrast, applications have been forward from several farmer groups to expand the light railway sugarcane transport network to their plantations. The light railway network of sugarcane transport may grow parallel to the cane production area whenever narrow rail tracks expanded according to the applications forward to the sugar company from farmers.

The sugar company has been developing experiences of light railway track maintenance, wagon fabrication and locomotive repair to maintain long life and efficient operation of the system. Constant efforts have been exerted by the company to replace locomotives and rail wagons which become out of service. The sugar mills may have hundreds of locomotives most of them compatible to the 2 feet rail gauge and more than 10,000 railway wagon for whole stalk loading. The company has been improving the level of locomotive maintenance and the design of the railway wagons to facilitate better role of the system.

The light railway sugarcane transport system was always able to transport cane with lower cost as indicated in Figure 23. Finally it may be concluded that the role of the light railway sugarcane transport system did not actually declined but remain constant while the mill capacity and the cane production increased. Since the alternative transport represented in road transport operated diurnal and it is difficult to use the road vehicles as storage bin, a minimum contribution of the narrow railway transport have to be conserved. The minimum role of the light railway system transport may be equivalent to the percent of daily capacity of the mill required for night shift. Reference to Figure 1 it could be observed that the role of railway transport system is not expected to show more decline. The sugar company organized special administration for narrow railway engineering that construct the rail track, fabricate wagons and been responsible for the system maintenance.

Australia may be considered as one of the countries achieved the most important development in the field of light railway transport of sugarcane. In his comment to the

As previously discussed, each narrow railway network constructed and started operation simultaneously with the sugar factory initiation. The light railway networks belong to the old sugar factories initiated during the 19th century and those initiated at the early period of the 20th century used to supply 100% of the mill daily capacity. The narrow railway network expansion has been very limited compared to the expansion of sugar cane production area. According to **Soltan and Mohammed (2008)**, the area of sugarcane has been increased from less than 200,000 acres at 1980's to about 350,000 acres at 2008. Therefore the light railway of sugarcane transport stay constant and the cane area expanded more than 40 % outside the network. Since the role of the narrow railway sugarcane transport system declined from about 90% to about 40%. Considering the 40% decline because of cane area expansion outside the network, therefore declined of the light railway system transport may only be about 10%. Actually the percent contribution of the cane transported may be decreased but the total tonnage transported by the narrow railway system may be increased because the average unit area production increased and

The change of some farms to road vehicle may be because of the availability of their own vehicles or the advantages offered by road transport. The most important advantage offered by road transport is the short duration of transport cycle that save the excessive moisture losses that reduces the total weight and money value of the wagon load. In contrast, applications have been forward from several farmer groups to expand the light railway sugarcane transport network to their plantations. The light railway network of sugarcane transport may grow parallel to the cane production area whenever narrow rail tracks

expanded according to the applications forward to the sugar company from farmers.

and the design of the railway wagons to facilitate better role of the system.

track, fabricate wagons and been responsible for the system maintenance.

The sugar company has been developing experiences of light railway track maintenance, wagon fabrication and locomotive repair to maintain long life and efficient operation of the system. Constant efforts have been exerted by the company to replace locomotives and rail wagons which become out of service. The sugar mills may have hundreds of locomotives most of them compatible to the 2 feet rail gauge and more than 10,000 railway wagon for whole stalk loading. The company has been improving the level of locomotive maintenance

The light railway sugarcane transport system was always able to transport cane with lower cost as indicated in Figure 23. Finally it may be concluded that the role of the light railway sugarcane transport system did not actually declined but remain constant while the mill capacity and the cane production increased. Since the alternative transport represented in road transport operated diurnal and it is difficult to use the road vehicles as storage bin, a minimum contribution of the narrow railway transport have to be conserved. The minimum role of the light railway system transport may be equivalent to the percent of daily capacity of the mill required for night shift. Reference to Figure 1 it could be observed that the role of railway transport system is not expected to show more decline. The sugar company organized special administration for narrow railway engineering that construct the rail

Australia may be considered as one of the countries achieved the most important development in the field of light railway transport of sugarcane. In his comment to the

**7. Light railways future** 

the mills now working at their full capacities.

future of the sugarcane light railway of Australia, **John Browning (2007)** stated that "Cane railways will continue to surprise and to interest, and they will remain "special" to the men who operate them, to the many visitors to the areas in which they run, and to those who simply love railways". It has been recommended that, some of the modern techniques developed in countries such as Australia to control the light railway sugarcane transport cycle time should be considered.

Finally, the light railway for sugarcane transport represents the backbone of the raw material feeding system for sugar industry in Egypt. The system has several advantages compared to road transport such as lower transport cost, higher reliability, higher stability and minimum accidents occurred. Application of the advanced techniques for minimizing transport cycle duration expected to help for regaining the pioneer role of the light railway transport system. Practical ideas to increase wagons capacity and to improve mill yard management have been currently developed to speed up the system. Light railway transport system will continue being the familiar lovely transport system for sugarcane farmers.

Fig. 23. Cost of light railway transport compared to road transport

### **8. Acknowledgements**

The author wishes to announce that part of the data was collected through a project financed by the Egyptian Science and Technology Development Fund. The help of the members of the Sugar and Integrated Industry Company is also acknowledged.

**2** 

Takeshi Ozeki

*Japan* 

**Topological Analysis of Tokyo** 

**Metropolitan Railway System** 

*Faculty of Science and Technology, Sophia University* 

Leading concept of the topological analysis of railway network systems is based on the fact that the topology of railway networks reflects the real world. It is believed because strong mutual interactions between railway systems and real worlds continue through longer periods of their growth: An eventual growth in a regional economy due to opening such a new shopping plaza may require extension of a railway system, verves, a scheduled extension of a railway may result in a growth in regional economy due to rapid increase in town population, for instance. In this way, the growth of railway system and regional activity affects their growth mutually. In context, the railway system topology reflects the

This leading concept agrees with that of Brin and Page, co-founders of Google: they reported, in their first paper on "Google"(Page and et al, 1990), that it was a great surprise the PageRank is obtained purely mechanically from the topology of Web page links. Their surprise is the discovery of the fact that the network is entangled with real world. The "Google" approximates a Web surfer as a random walker in Markov process and combines the dominant eigenvector of Markov process with a list of coincidence for a inquiry as the

This leading concept grows up as a mathematical platform using multimodal non-linear Markov process approximation so that it is applied to analyse Tokyo Metropolitan Railway

It is no doubt that there have been established platforms to analyse the dynamics of railway network systems based on growing supercomputer power. On contrary, our platform can be said as providing abstractive viewpoint based only on network topology so that it is

Network topologies have been discussed as scale free networks mainly in a field of complex systems from the end of the previous century. The scale free network science is expected to provide potential methods to analyse various network characteristics of complex systems.

expected to illustrate different new worlds for the railway system engineers.

**1. Introduction** 

**1.1 Railway system reflects the real world** 

real world: In other words, they "entangle" each other.

**1.2 Family network approximation: Rosary network** 

PageRank (Langville-Mayer, 2006)

System.

### **9. References**


## **Topological Analysis of Tokyo Metropolitan Railway System**

Takeshi Ozeki *Faculty of Science and Technology, Sophia University Japan* 

### **1. Introduction**

24 Infrastructure Design, Signalling and Security in Railway

Abdel-Mawla (2011) Expert system for selecting cane transport system. *Egyptian Sugar* 

Abdel-Mawla (2010) Efficiency of mechanical cane loading in Egypt. *Sugar Tech. 2010, vol.* 

Abdel-Mawla H A. (2000) Analysis of cane delay of traditional delivery systems: *Paper* 

Andrew H. and Ian D. (2005) A simulation model for capacity planning in sugarcane

John Browning (2007) Queensland sugar cane railways today. Light Railway Research

Malelane, M. (2000) Evaluation of Cane Transport Modes From Loading Zone to Mill to

Africa 23-28 July, 2000. *http://issct.intnet.mu/past-workshops/agriabs3.html#i*  Lynn Z. (2008): An Introduction to Modeling Queensland's Sugar Cane Railways . *1* 

Sugar Crops Council (1990-2010) Annual reports: The percent cane transported by light rail

Soltan F. H. and Mohammed I. N. (2008) Sugar industry in Egypt. *Sugar Tech*. *10 (3): 204-209* 

transport. Computers and Electronics in Agriculture. Elsevier Science Publishers B*.* 

Minimize Transport Costs. ISSCT Agricultural Engineering Workshop. South

Abdel-Mawla H A. (2001) Alternative cane to mill delivery systems*. MJAE 18 (3): 647-662.*  Affifi, F. (1988) ) Sugar production in Egypt. Central Council for Sugar Crops. Ministry of

**9. References** 

*Journal. Vol. 4, June 2011: 161-178* 

*12, no2, pp. 108-114 [7 page(s) (article)]* 

Agriculture and Land Reclamation.

*www.zelmeroz.com/canesig* 

wagons compared road transport: 64-74.

*presented to the MSAE, Menofia Univ.:25-26 October 2000.*

*V. Amsterdam, The Netherlands Volume 47 Issue 2, May, 2005* 

Society of Australia. *http://www.lrrsa.org.au/LRR\_SGRb.htm*

### **1.1 Railway system reflects the real world**

Leading concept of the topological analysis of railway network systems is based on the fact that the topology of railway networks reflects the real world. It is believed because strong mutual interactions between railway systems and real worlds continue through longer periods of their growth: An eventual growth in a regional economy due to opening such a new shopping plaza may require extension of a railway system, verves, a scheduled extension of a railway may result in a growth in regional economy due to rapid increase in town population, for instance. In this way, the growth of railway system and regional activity affects their growth mutually. In context, the railway system topology reflects the real world: In other words, they "entangle" each other.

This leading concept agrees with that of Brin and Page, co-founders of Google: they reported, in their first paper on "Google"(Page and et al, 1990), that it was a great surprise the PageRank is obtained purely mechanically from the topology of Web page links. Their surprise is the discovery of the fact that the network is entangled with real world. The "Google" approximates a Web surfer as a random walker in Markov process and combines the dominant eigenvector of Markov process with a list of coincidence for a inquiry as the PageRank (Langville-Mayer, 2006)

This leading concept grows up as a mathematical platform using multimodal non-linear Markov process approximation so that it is applied to analyse Tokyo Metropolitan Railway System.

It is no doubt that there have been established platforms to analyse the dynamics of railway network systems based on growing supercomputer power. On contrary, our platform can be said as providing abstractive viewpoint based only on network topology so that it is expected to illustrate different new worlds for the railway system engineers.

### **1.2 Family network approximation: Rosary network**

Network topologies have been discussed as scale free networks mainly in a field of complex systems from the end of the previous century. The scale free network science is expected to provide potential methods to analyse various network characteristics of complex systems.

Topological Analysis of Tokyo Metropolitan Railway System 27

The Watts-Strogatz's small world evolves from regular lattice networks to the Erdos-Renyi's random networks(Erdos, 1960) by random rewiring links with a given probability (Watts, 1998). The Watts-Strogatz's small world having fixed number of nodes is discussed as a static network. On the other hand, the scale-free network of Barabasi-Albert (BA model) introduces the concept of growing networks with preferential attachment (Barabashi, 1999). One of characterizations of networks is given by the connectivity distribution of *P* (*k*), which is the probability that a node has *k* degrees (or, number of links). In the scale free networks based on BA model, the connectivity distribution follows the power law, in which *P* (*k*) is

analysed to find various scale free networks having various exponents, which are covered in references (Newman, 2006). For an example, it is well known that social infrastructure networks, such as power grids, as egalitarian networks, follow the power law with exponent 4 (Barabasi, 2002). There were many trials reported to generate models with larger exponents for fitting these real-world networks (Newman, 2006): Dorogovtsev *et al* (Dorogovtsev, 2000) modified the preferential attachment probability and derived the exact asymptotic solution of the connectivity distribution showing the wide range of exponents

*a* 2 , where *a* is the attractiveness. However, there was no network generation model

In context, "the evolutional family networks" generated by "a group entry growth mechanism" with the preferential attachment was proposed in ICCS2006 (Ozeki, 2006): growth mechanism employed is group entry having constituent family connected in fullmesh, line and loop. This is suitable to simulate the railway system: as shown in Fig.1.1, a graph in the bottom looks like a railway system; We call it "Rosary network approximation" that will be discussed in the case of Tokyo metropolitan railway system in section 2. Various characteristics will be analysed based on the Multi-modal Markov transition approximation

We point out that nonlinear effects are inevitable in the passenger flow analysis. Since the Google is an infrastructure in daily life same as railway system, we refer the Google: the Google is characterized by a single dominant mode: In linear Markov transition, the asymptotic state is always the dominant mode. However, a Japanese adage: "people wish to get together to the place where people get together" or "Birds with a feather flock together" is important in real world to determine such PageRanking. The Google assumes such tendency is reflected in the page link network. Here, we point out it is not always sufficient, and demonstrate a Markov engine with the third-order nonlinear interaction reflecting such

We demonstrated the new engine to retrieve *the largest three stations* in respect of number of

We discuss "key stations of railway network dynamics" by analogy with "Tsubo in

=3. The real world complex networks are

approximated to *k*

in section 3.

Shiatsu".

suitable for analysing railway systems.

**1.3 Birds with a feather flock together** 

tendency to retrieve a real world, correctly.

**1.4 TSUBO: Impulse response of network** 

passengers in Tokyo Metropolitan Railway Network, in section 4.

, having the exponent

However, there is no network model suitable for analysing railway systems. Then, the rosary network in series of family the network was proposed as suitable one for railway system networks as shown in Fig.1.1 (Ozeki, 2006).

Fig. 1.1. Family network Series including Rosary Networks

Historical flows of complex systems are very interesting competitions between abstraction and computation: Origin of complex systems was introduced by Prigogine based on coupled nonlinear differential equations and sophisticated chemical experiments (Prigogine, 1981). It was followed by distributed agent model supported by rapidly growing computational power. However, for analysis of huge network systems the distributed agent model was suffered by computational complexity explosion in 1990'. Then, abstractive approaches such as scale free networks become to share exploring complex network systems. Topological analysis of railway network is backed by these historical flows.

However, there is no network model suitable for analysing railway systems. Then, the rosary network in series of family the network was proposed as suitable one for railway

system networks as shown in Fig.1.1 (Ozeki, 2006).

Fig. 1.1. Family network Series including Rosary Networks

historical flows.

Historical flows of complex systems are very interesting competitions between abstraction and computation: Origin of complex systems was introduced by Prigogine based on coupled nonlinear differential equations and sophisticated chemical experiments (Prigogine, 1981). It was followed by distributed agent model supported by rapidly growing computational power. However, for analysis of huge network systems the distributed agent model was suffered by computational complexity explosion in 1990'. Then, abstractive approaches such as scale free networks become to share exploring complex network systems. Topological analysis of railway network is backed by these The Watts-Strogatz's small world evolves from regular lattice networks to the Erdos-Renyi's random networks(Erdos, 1960) by random rewiring links with a given probability (Watts, 1998). The Watts-Strogatz's small world having fixed number of nodes is discussed as a static network. On the other hand, the scale-free network of Barabasi-Albert (BA model) introduces the concept of growing networks with preferential attachment (Barabashi, 1999). One of characterizations of networks is given by the connectivity distribution of *P* (*k*), which is the probability that a node has *k* degrees (or, number of links). In the scale free networks based on BA model, the connectivity distribution follows the power law, in which *P* (*k*) is approximated to *k* , having the exponent =3. The real world complex networks are analysed to find various scale free networks having various exponents, which are covered in references (Newman, 2006). For an example, it is well known that social infrastructure networks, such as power grids, as egalitarian networks, follow the power law with exponent 4 (Barabasi, 2002). There were many trials reported to generate models with larger exponents for fitting these real-world networks (Newman, 2006): Dorogovtsev *et al* (Dorogovtsev, 2000) modified the preferential attachment probability and derived the exact asymptotic solution of the connectivity distribution showing the wide range of exponents *a* 2 , where *a* is the attractiveness. However, there was no network generation model suitable for analysing railway systems.

In context, "the evolutional family networks" generated by "a group entry growth mechanism" with the preferential attachment was proposed in ICCS2006 (Ozeki, 2006): growth mechanism employed is group entry having constituent family connected in fullmesh, line and loop. This is suitable to simulate the railway system: as shown in Fig.1.1, a graph in the bottom looks like a railway system; We call it "Rosary network approximation" that will be discussed in the case of Tokyo metropolitan railway system in section 2. Various characteristics will be analysed based on the Multi-modal Markov transition approximation in section 3.

### **1.3 Birds with a feather flock together**

We point out that nonlinear effects are inevitable in the passenger flow analysis. Since the Google is an infrastructure in daily life same as railway system, we refer the Google: the Google is characterized by a single dominant mode: In linear Markov transition, the asymptotic state is always the dominant mode. However, a Japanese adage: "people wish to get together to the place where people get together" or "Birds with a feather flock together" is important in real world to determine such PageRanking. The Google assumes such tendency is reflected in the page link network. Here, we point out it is not always sufficient, and demonstrate a Markov engine with the third-order nonlinear interaction reflecting such tendency to retrieve a real world, correctly.

We demonstrated the new engine to retrieve *the largest three stations* in respect of number of passengers in Tokyo Metropolitan Railway Network, in section 4.

### **1.4 TSUBO: Impulse response of network**

We discuss "key stations of railway network dynamics" by analogy with "Tsubo in Shiatsu".

Topological Analysis of Tokyo Metropolitan Railway System 29

(a) Constituents of Rosary network "tsubo"map

(b) A small rosary network generated. (c) Power law

Fig. 2.1. Rosary network model suitable for analyzing railway systems.

In Japan, "Shiatsu" is a popular therapy by pressing "shiatsu point" to enhance the body's natural healing ability and prevent the progression of disease. Shiatsu points are called "Tsubo", in Japanese. Their locations and effects are based on understanding of modern anatomy and physiology. The concept of "Tsubo" has been used as a strategy in reactivation of an old city, such as Padova, Italy (Horiike, 2000). He calls it "the Point Stimulus". The "Point Stimulus Response" corresponds to the impulse response of the network system, that is, the temporal state variation in the Markov transition to the deltafunction with negative sign of initial state. We can evaluate the node activity by its response to the point stimulus.

We will discuss "Tsubo" of Tokyo metropolitan railway system in session 5.

### **2. Scale free characteristics of railway network**

We show here a large railway system, such as Tokyo metropolitan railway system, that indicates characteristics of scale free networks: "station" corresponds to "node", and "track" to "link". This section is based on our paper presented in ICCS 2006. (Ozeki 2006)

### **2.1 Growth mechanism of Rosary**

A growth step of a railway network is modelled as illustrated in Fig.2.1 (a): a rosary that consists of M stations connected in a shape like a rosary is added to an old railway network. There are two cases of its constituent: one is like a rosary having two jointing links as shown in Fig.2.1 (a) left, the other is like a snake having one jointing link as shown in Fig.2-1right. Fig.2.1 (b) is a rosary network generated this growth mechanism: assuming the fraction of snakes in constituent groups to be 10% and growth step 11 for convenience to grapes its perspective. This topology is drawn by a free-software: Cytoscape (http://www.cytoscape.org/download.html). The initial constituent is a group #0~#8 and the total number of stations is 65. The degree distribution is illustrated in Fig.2.1(c) (the "degree" denotes the number of links of a node). The degree distribution follows the power law with exponent of –4 as shown in Fig.2.1 (c).

### **2.2 Multimodal analysis of Rosary network**

Before analysing Tokyo Metropolitan Railway System, it seems better to analyse this small rosary network. We assume a passenger in the rosary railway network as "a random walker", that is equivalent to multimodal Markov transition approximation (refer Appendix 1). The dominant mode of the multimodal Markov transition corresponds to the stationary state of passenger distribution that is illustrated in Fig.2.2 (c). The eigenvector of dominant mode has a peak at station #2, and mountains in the dominant eigenvector are illustrated in Fig.4.3 (a): the original station group #0~#8 corresponds to the first mountain in the figure, and the followings are illustrated in blue rosaries. The eigenvalue of the rosary network is shown in Fig.2.2 (a): The #64 eigenvalue of 2.773 corresponds to the dominant mode. The 2nd mode has negative largest eigenvalue. The mode competition among these modes in nonlinear multimodal Markov transition is discussed in section 4.

This rosary network has no real world so that it is difficult to show the substructure analysis. Next we discuss a actual rosary network.

In Japan, "Shiatsu" is a popular therapy by pressing "shiatsu point" to enhance the body's natural healing ability and prevent the progression of disease. Shiatsu points are called "Tsubo", in Japanese. Their locations and effects are based on understanding of modern anatomy and physiology. The concept of "Tsubo" has been used as a strategy in reactivation of an old city, such as Padova, Italy (Horiike, 2000). He calls it "the Point Stimulus". The "Point Stimulus Response" corresponds to the impulse response of the network system, that is, the temporal state variation in the Markov transition to the deltafunction with negative sign of initial state. We can evaluate the node activity by its response

We show here a large railway system, such as Tokyo metropolitan railway system, that indicates characteristics of scale free networks: "station" corresponds to "node", and "track"

A growth step of a railway network is modelled as illustrated in Fig.2.1 (a): a rosary that consists of M stations connected in a shape like a rosary is added to an old railway network. There are two cases of its constituent: one is like a rosary having two jointing links as shown in Fig.2.1 (a) left, the other is like a snake having one jointing link as shown in Fig.2-1right. Fig.2.1 (b) is a rosary network generated this growth mechanism: assuming the fraction of snakes in constituent groups to be 10% and growth step 11 for convenience to grapes its perspective. This topology is drawn by a free-software: Cytoscape (http://www.cytoscape.org/download.html). The initial constituent is a group #0~#8 and the total number of stations is 65. The degree distribution is illustrated in Fig.2.1(c) (the "degree" denotes the number of links of a node). The degree distribution follows the power

Before analysing Tokyo Metropolitan Railway System, it seems better to analyse this small rosary network. We assume a passenger in the rosary railway network as "a random walker", that is equivalent to multimodal Markov transition approximation (refer Appendix 1). The dominant mode of the multimodal Markov transition corresponds to the stationary state of passenger distribution that is illustrated in Fig.2.2 (c). The eigenvector of dominant mode has a peak at station #2, and mountains in the dominant eigenvector are illustrated in Fig.4.3 (a): the original station group #0~#8 corresponds to the first mountain in the figure, and the followings are illustrated in blue rosaries. The eigenvalue of the rosary network is shown in Fig.2.2 (a): The #64 eigenvalue of 2.773 corresponds to the dominant mode. The 2nd mode has negative largest eigenvalue. The mode competition among these modes in

This rosary network has no real world so that it is difficult to show the substructure

We will discuss "Tsubo" of Tokyo metropolitan railway system in session 5.

to "link". This section is based on our paper presented in ICCS 2006. (Ozeki 2006)

**2. Scale free characteristics of railway network** 

to the point stimulus.

**2.1 Growth mechanism of Rosary** 

law with exponent of –4 as shown in Fig.2.1 (c).

**2.2 Multimodal analysis of Rosary network** 

nonlinear multimodal Markov transition is discussed in section 4.

analysis. Next we discuss a actual rosary network.

Fig. 2.1. Rosary network model suitable for analyzing railway systems.

Topological Analysis of Tokyo Metropolitan Railway System 31

(a) Map of Tokyo Metropolitan Railway System (b) Map of Edo in Tokugawa Era of 18th

A distorted hexagonal in Fig.3.1 (a) is "*Yamanote* Circular Line" which includes several well-known stations such as Tokyo, Shinbashi, Shinagawa, Shibuya, Shinjuku and

Fig.3.2 summarizes the mode structures of the network. In a list of eigenvalues illustrated in the right, we focus on the following two modes; the dominant mode #733 with eigenvalue +4.738 has larger probability at *Shinagawa* (station number #8), *Shinbash*i (#11) and *Tokyo* (#13) as shown in middle left panel of Fig.3.2. The constituent stations of the dominant

The second mode #735, having negative largest eigenvalue of -4.271, has larger probability at *Shinjuku* (#0), *Shibuya* (#3) and *Ikebukuro* (#25) as illustrated in middle right panel of Fig.3.2. The constituent stations of mode #735 are also illustrated by *italic character* on the

It is interesting that the dominant mode #733 extracts the central structure of business and government of Metropolitan Tokyo. This area also corresponds to the main structure in Edo

(http://onjweb.com/netbakumaz/edomap/edomap.html) Fig. 3.1. Tokyo Metropolitan Railway Network System

mode are illustrated in Fig.3.1 (a) on the *Yamanote* circular Line.

Ikebukuro etc.

*Yamanote* circular line, in Fig.3.1 (a).

**3.2 Orthogonal features of substructures** 

metropolitan area. (Tokyo was called *Edo* in 18th century.)

Century

Fig. 2.2. Mode Structure of Rosary Network

### **3. Analysis of Tokyo metropolitan railway system**

Tokyo metropolitan railway system is illustrated in Fig.3.1: (a) denotes the Map of contemporary Tokyo metropolitan railway system (Rail Map of Tokyo Area, 2004) and (b) denotes the map of Edo in 18th century. The central part of Tokyo metropolitan railway is truncated to have the number of total stations of 736. The total number of links is 1762. The number of links is counted topologically: for instance, we count the number of links between Tokyo and Kanda as 1, even though there are three double railways between them. Fig.3.2 (a) depicts degree distribution of a central part of Tokyo Metropolitan Railway System. The excellent fit in degree distribution suggests that the growth mechanism of Tokyo railway system is coincident with the growth mechanism of rosary network. The exponent measured to be 4, which is coincident with those of the small rosary network shown in Fig.2.1 (c) and the power grids of North America (Barabasi, 1999). It is surprising to find that the number of nodes in constituent rosary networks is *M*=3, which is reasonable in the central part of Tokyo with respect to its complexity. A real world railway network is well approximated by our rosary network model.

### **3.1 Substructures of Tokyo**

The main issue is the extraction of an authentic centre (Tokyo, Shinbashi, Shinagawa) and a new metropolitan centre (Shinjuku, Ikebukuro, Shibuya). The later corresponds to the centre and the outskirts of Edo as shown Fig.3.1 (b).

Tokyo metropolitan railway system is illustrated in Fig.3.1: (a) denotes the Map of contemporary Tokyo metropolitan railway system (Rail Map of Tokyo Area, 2004) and (b) denotes the map of Edo in 18th century. The central part of Tokyo metropolitan railway is truncated to have the number of total stations of 736. The total number of links is 1762. The number of links is counted topologically: for instance, we count the number of links between Tokyo and Kanda as 1, even though there are three double railways between them. Fig.3.2 (a) depicts degree distribution of a central part of Tokyo Metropolitan Railway System. The excellent fit in degree distribution suggests that the growth mechanism of Tokyo railway system is coincident with the growth mechanism of rosary network. The exponent measured to be 4, which is coincident with those of the small rosary network shown in Fig.2.1 (c) and the power grids of North America (Barabasi, 1999). It is surprising to find that the number of nodes in constituent rosary networks is *M*=3, which is reasonable in the central part of Tokyo with respect to its complexity. A real world railway network is well approximated by our rosary network

The main issue is the extraction of an authentic centre (Tokyo, Shinbashi, Shinagawa) and a new metropolitan centre (Shinjuku, Ikebukuro, Shibuya). The later corresponds to the centre

Fig. 2.2. Mode Structure of Rosary Network

model.

**3.1 Substructures of Tokyo** 

and the outskirts of Edo as shown Fig.3.1 (b).

**3. Analysis of Tokyo metropolitan railway system** 

(a) Map of Tokyo Metropolitan Railway System (b) Map of Edo in Tokugawa Era of 18th Century (http://onjweb.com/netbakumaz/edomap/edomap.html)

Fig. 3.1. Tokyo Metropolitan Railway Network System

A distorted hexagonal in Fig.3.1 (a) is "*Yamanote* Circular Line" which includes several well-known stations such as Tokyo, Shinbashi, Shinagawa, Shibuya, Shinjuku and Ikebukuro etc.

Fig.3.2 summarizes the mode structures of the network. In a list of eigenvalues illustrated in the right, we focus on the following two modes; the dominant mode #733 with eigenvalue +4.738 has larger probability at *Shinagawa* (station number #8), *Shinbash*i (#11) and *Tokyo* (#13) as shown in middle left panel of Fig.3.2. The constituent stations of the dominant mode are illustrated in Fig.3.1 (a) on the *Yamanote* circular Line.

The second mode #735, having negative largest eigenvalue of -4.271, has larger probability at *Shinjuku* (#0), *Shibuya* (#3) and *Ikebukuro* (#25) as illustrated in middle right panel of Fig.3.2. The constituent stations of mode #735 are also illustrated by *italic character* on the *Yamanote* circular line, in Fig.3.1 (a).

### **3.2 Orthogonal features of substructures**

It is interesting that the dominant mode #733 extracts the central structure of business and government of Metropolitan Tokyo. This area also corresponds to the main structure in Edo metropolitan area. (Tokyo was called *Edo* in 18th century.)

Topological Analysis of Tokyo Metropolitan Railway System 33

railway network map of the project, which shows *Az* for *Azamino* and *Sy* for *Shinyokohama*. *Nagatusuda* marked by *Na* was not recognized as key stations of the Newtown, but presently "*Yokohama* city plans" includes it as the *Yokohama Silicon valley*: It is well known that *Nagatsuda* includes the campus of Tokyo Institute of Technology. This network analysing engine points out the importance of *Nagatsuda* to provide TIT as Stanford University of

Unfortunately, the network graph, used hitherto, does not include the *Blueline* subway that is one of the main constructions in the *Kouhoku* Newtown project. In next, we will discuss

(a) The eigenvector #200 coherently excited (b) Kohoku Newtown Project:Kohoku Newtown encircled

Here we would like to introduce an interesting application of our network analysis platform: it is a blind evaluation method of network modification project. As introduced in the previous subsection, we try to evaluate the project of "Blueline". The method is the variation of node entropy before and after *Blueline* inauguration, as illustrated in Fig.3.4 (a). The station group with increasing in their node entropy includes *Totsuka* (#94), *Sakuragicho*(#84) and *Kannai* (#85). On the contrary, the station group with decreasing node

We can show a supporting data for this evaluation in Fig.3.4 (b). The number of annual passengers of *Hodogaya* station shows abrupt drop in 1999 when the *Blueline* service was started. This blind-evaluation method presently only provides the variation of passenger flow of modified network, but it seems a powerful tool for network system design in

by the #200 eigen–mode:Sy=Shin-Yokohama, Ok=Ohkura yam, Az=Azamino

(http://www.yk.rim.or.jp/~harujun/ntown/ntftr.html.)

entropy includes *Hodogaya*(#104) and *Kita-Kamakura*(#106).

Fig. 3.3. Eigenvector of *Kohoku* Newtown.

**3.4 Evaluation of a new subway project** 

future.

Silicon valley.

the evaluation of *Blueline* project.

Left: Degree distribution, Middle left: dominant mode; Shinagawa (8), Shinbashi (11), Tokyo (13); Middle right: second mode: Shinjuku (0), Shibuya (3),Ikebukuro(25) Right: List of eigenvalues

Fig. 3.2. Multimodal Analysis of Tokyo Metropolitan Railway System

The bridge of *Nihonbashi* is the original point of national roads including the *Tokaido* (presently *root 1*) in Edo era as shown in Fig.3.1 (b). The main business was blooming along the *Tokaido*, and the political organization was concentrated between the *Edo castle* and the *root 1*. It can be said that the central structure of contemporary Tokyo succeeds the main structure of the *Edo* metropolitan of which population was exceed one million in 18th century.

On the other hand, the second mode #735 is successor of the *Edo* outskirt villages located in the lower part of Fig.3.1 (b). The eigenmode effectively extracts orthogonal substructures in variety of viewpoints: The dominant mode retrieves the dominant political and business area of present Tokyo metropolitan. The second mode retrieves its most growing area that was the outskirt of *Edo*.

It is suggestive that the probability amplitude of the second mode, illustrated in the middle right panel of Fig.3.2, is positive at *Shinjuku* (station number #0) and negative at *Shibuya* (#3) and *Ikebukuro* (#25). Historically, *Shinjuku*, as the fourth hosting station of *Edo,* leads the others in this outskirt area. It is interesting because this mode profile has strong relations with mode competition in nonlinear Markov transition, as will be discussed in section4.

The further interpretation of probability amplitude remains in being unexplored. The data mining technology may be useful to reveal it.

### **3.3 An interesting eigenmode extracts the** *Kohoku* **new town project**

The study of the Kohoku Newtown project is an old graduation thesis of our laboratory, when a different definition of transition matrix was used in Markov transition (Ozeki, 2009). Fig.3.3 (a) denotes the eigenvector of the 200th eigenmode of Tokyo Metropolitan Railway system. It consists of three station groups, named *Azamino / Nagtsuda* group (*Denentoshi* line), *Shin-yokohama* group (*Yokohama* line) and *Kikuna / Ohkurayama* group (*Toyokyu* line). Those are excited coherently and simultaneously in the same phase, as shown in Fig.3.3 (a) A speculation suggests that a zone, encircled by three lines, might be successfully developed as a triangle business park. It is our great surprise to find that "the *Kouhoku* Newtown project" was promoted from 1965 to 1996, exactly in this zone. Fig.3.3 (b) denotes the

Left: Degree distribution, Middle left: dominant mode; Shinagawa (8), Shinbashi (11), Tokyo (13); Middle right: second mode: Shinjuku (0), Shibuya (3),Ikebukuro(25) Right: List of eigenvalues

The bridge of *Nihonbashi* is the original point of national roads including the *Tokaido* (presently *root 1*) in Edo era as shown in Fig.3.1 (b). The main business was blooming along the *Tokaido*, and the political organization was concentrated between the *Edo castle* and the *root 1*. It can be said that the central structure of contemporary Tokyo succeeds the main structure of the *Edo* metropolitan of which population was exceed one million in 18th

On the other hand, the second mode #735 is successor of the *Edo* outskirt villages located in the lower part of Fig.3.1 (b). The eigenmode effectively extracts orthogonal substructures in variety of viewpoints: The dominant mode retrieves the dominant political and business area of present Tokyo metropolitan. The second mode retrieves its most growing area that

It is suggestive that the probability amplitude of the second mode, illustrated in the middle right panel of Fig.3.2, is positive at *Shinjuku* (station number #0) and negative at *Shibuya* (#3) and *Ikebukuro* (#25). Historically, *Shinjuku*, as the fourth hosting station of *Edo,* leads the others in this outskirt area. It is interesting because this mode profile has strong relations with mode competition in nonlinear Markov transition, as will be

The further interpretation of probability amplitude remains in being unexplored. The data

The study of the Kohoku Newtown project is an old graduation thesis of our laboratory, when a different definition of transition matrix was used in Markov transition (Ozeki, 2009). Fig.3.3 (a) denotes the eigenvector of the 200th eigenmode of Tokyo Metropolitan Railway system. It consists of three station groups, named *Azamino / Nagtsuda* group (*Denentoshi* line), *Shin-yokohama* group (*Yokohama* line) and *Kikuna / Ohkurayama* group (*Toyokyu* line). Those are excited coherently and simultaneously in the same phase, as shown in Fig.3.3 (a) A speculation suggests that a zone, encircled by three lines, might be successfully developed as a triangle business park. It is our great surprise to find that "the *Kouhoku* Newtown project" was promoted from 1965 to 1996, exactly in this zone. Fig.3.3 (b) denotes the

**3.3 An interesting eigenmode extracts the** *Kohoku* **new town project** 

Fig. 3.2. Multimodal Analysis of Tokyo Metropolitan Railway System

century.

was the outskirt of *Edo*.

discussed in section4.

mining technology may be useful to reveal it.

railway network map of the project, which shows *Az* for *Azamino* and *Sy* for *Shinyokohama*. *Nagatusuda* marked by *Na* was not recognized as key stations of the Newtown, but presently

"*Yokohama* city plans" includes it as the *Yokohama Silicon valley*: It is well known that *Nagatsuda* includes the campus of Tokyo Institute of Technology. This network analysing engine points out the importance of *Nagatsuda* to provide TIT as Stanford University of Silicon valley.

Unfortunately, the network graph, used hitherto, does not include the *Blueline* subway that is one of the main constructions in the *Kouhoku* Newtown project. In next, we will discuss the evaluation of *Blueline* project.

(a) The eigenvector #200 coherently excited (b) Kohoku Newtown Project:Kohoku Newtown encircled by the #200 eigen–mode:Sy=Shin-Yokohama, Ok=Ohkura yam, Az=Azamino (http://www.yk.rim.or.jp/~harujun/ntown/ntftr.html.)

Fig. 3.3. Eigenvector of *Kohoku* Newtown.

### **3.4 Evaluation of a new subway project**

Here we would like to introduce an interesting application of our network analysis platform: it is a blind evaluation method of network modification project. As introduced in the previous subsection, we try to evaluate the project of "Blueline". The method is the variation of node entropy before and after *Blueline* inauguration, as illustrated in Fig.3.4 (a). The station group with increasing in their node entropy includes *Totsuka* (#94), *Sakuragicho*(#84) and *Kannai* (#85). On the contrary, the station group with decreasing node entropy includes *Hodogaya*(#104) and *Kita-Kamakura*(#106).

We can show a supporting data for this evaluation in Fig.3.4 (b). The number of annual passengers of *Hodogaya* station shows abrupt drop in 1999 when the *Blueline* service was started. This blind-evaluation method presently only provides the variation of passenger flow of modified network, but it seems a powerful tool for network system design in future.

Topological Analysis of Tokyo Metropolitan Railway System 35

"curious bystander" because the transition probability from node j to i increases when ( )( ) *kn mn q q* is positive. In other words, XPM expresses "Birds with a feather flock together".

To make our intention of introduction of SPM and XPM clear, we show their import

Final target is discussion of mode competition between the authentic centre and the new growing metropolitan centre. And the third-order non-linear interaction is inevitable to show that the largest three stations are those in the new growing metropolitan region in

It seems better to introduce "Emergence" in the small rosary network discussed in session 2, before we discuss more complicated Metropolitan Tokyo railway system. Fig.4.1 illustrates the temporal variation of mode probability (the squared mode amplitude) of the nonlinear Markov transition based on Eq.4.1 applied to the small rosary network shown in Fig.2.2. The initial condition is a random distribution of node probability amplitude. SPM with medium 0.1

leads to the dominant mode as the stationary state of the rosary network. It should be noted that the right panel illustrates the temporal variation of the mode amplitudes: The 2nd and 3rd order modes have negative eigenvalues so that the mode amplitudes change their sign at each

Left diagram indicates mode probability (squared mode amplitudes) and the right diagram denotes the

Fig. 4.1. Temporal variation of modes in SPM nonlinear Markov transition from random

Markov transition. The dominant mode having positive eigenvalue does not oscillate.

, ( ) ( ) (1 ( )( )) *in i j j <sup>n</sup> ik im k n m n*

( )( ) *ik im k n m n*

(2)

*AA q q* might be recognized as effect of

1 , , ,

,

*k m*

In this expression, the nonlinear term , ,

differences in network dynamics:

**4.1 Emergence of instability** 

temporal variation of mode amplitudes.

mode amplitude distribution as initial condition.

Metropolitan Tokyo.

*j k m q A q AA q q* 

### **4. Nonlinear phenomena in passenger flow in Tokyo metropolitan railway system**

Here we would like to point out that nonlinear phenomena are important in passenger flow analysis. First of all, it should be noted that there are two types of nonlinear phenomena in the third order nonlinear interaction (Agrawal, 1989): one is SFM (Self Phase Modulation) that is equivalent to "Like Button" in Facebook, that is, transition probability to a node having the same opinion increases. (Please refer Appendix to find details including notations.)

This nonlinear Markov transition process is expressed mathematically by the following;

$$(q\_i)\_{n+1} = \sum\_j A\_{i,j} (q\_j)\_n (1 + \gamma(q\_i)\_n (q\_j)\_n) \tag{1}$$

In this expression, the nonlinear term ( )( ) *i n <sup>j</sup> <sup>n</sup> q q* might be recognized as "like button": in case of the state ( )*i n q* of node #*i* having the same sign with ( )*i n q* , the transition probability from node j to i increases when the nonlinear coefficient is positive. In other words, "like button" is a tool to express our personal opinion that controls routing of information in Facebook. It might be reasonable that nonlinear phenomenon in rush hours is recognized as SPM because most of passengers in rush hours have more sharp intention to reach their destinations.

The other is called XPM (Cross Phase Modulation) that is equivalent to "curious bystanders", that is, the transition probability to a node having many "curious bystanders" increases. It is shown mathematically as following:

Fig. 3.4. Eigenvector Variation due to the Blueline.:(a) Node Entropy Change due to Blueline. (d) Evolution of Hodogaya Traffic Customers. Operation of Blueline was 1999.

$$(q\_i)\_{n+1} = \sum\_j A\_{i,j} (q\_j)\_n (1 + \gamma \sum\_{k,m} A\_{i,k} A\_{i,m} (q\_k)\_n (q\_m)\_n) \tag{2}$$

In this expression, the nonlinear term , , , ( )( ) *ik im k n m n k m AA q q* might be recognized as effect of

"curious bystander" because the transition probability from node j to i increases when ( )( ) *kn mn q q* is positive. In other words, XPM expresses "Birds with a feather flock together".

To make our intention of introduction of SPM and XPM clear, we show their import differences in network dynamics:

Final target is discussion of mode competition between the authentic centre and the new growing metropolitan centre. And the third-order non-linear interaction is inevitable to show that the largest three stations are those in the new growing metropolitan region in Metropolitan Tokyo.

### **4.1 Emergence of instability**

34 Infrastructure Design, Signalling and Security in Railway

Here we would like to point out that nonlinear phenomena are important in passenger flow analysis. First of all, it should be noted that there are two types of nonlinear phenomena in the third order nonlinear interaction (Agrawal, 1989): one is SFM (Self Phase Modulation) that is equivalent to "Like Button" in Facebook, that is, transition probability to a node having the same opinion increases. (Please refer Appendix to find details including

**4. Nonlinear phenomena in passenger flow in Tokyo metropolitan railway** 

This nonlinear Markov transition process is expressed mathematically by the following;

*j*

In this expression, the nonlinear term ( )( ) *i n <sup>j</sup> <sup>n</sup>*

increases. It is shown mathematically as following:

from node j to i increases when the nonlinear coefficient

1 , ( ) ( ) (1 ( ) ( ) ) *in i j j n in <sup>j</sup> <sup>n</sup>*

case of the state ( )*i n q* of node #*i* having the same sign with ( )*i n q* , the transition probability

button" is a tool to express our personal opinion that controls routing of information in Facebook. It might be reasonable that nonlinear phenomenon in rush hours is recognized as SPM because most of passengers in rush hours have more sharp intention to reach their

The other is called XPM (Cross Phase Modulation) that is equivalent to "curious bystanders", that is, the transition probability to a node having many "curious bystanders"

Fig. 3.4. Eigenvector Variation due to the Blueline.:(a) Node Entropy Change due to Blueline. (d) Evolution of Hodogaya Traffic Customers. Operation of Blueline was 1999.

(1)

*q q* might be recognized as "like button": in

is positive. In other words, "like

*q Aq q q*

**system** 

notations.)

destinations.

It seems better to introduce "Emergence" in the small rosary network discussed in session 2, before we discuss more complicated Metropolitan Tokyo railway system. Fig.4.1 illustrates the temporal variation of mode probability (the squared mode amplitude) of the nonlinear Markov transition based on Eq.4.1 applied to the small rosary network shown in Fig.2.2. The initial condition is a random distribution of node probability amplitude. SPM with medium 0.1 leads to the dominant mode as the stationary state of the rosary network. It should be noted that the right panel illustrates the temporal variation of the mode amplitudes: The 2nd and 3rd order modes have negative eigenvalues so that the mode amplitudes change their sign at each Markov transition. The dominant mode having positive eigenvalue does not oscillate.

Left diagram indicates mode probability (squared mode amplitudes) and the right diagram denotes the temporal variation of mode amplitudes.

Fig. 4.1. Temporal variation of modes in SPM nonlinear Markov transition from random mode amplitude distribution as initial condition.

Topological Analysis of Tokyo Metropolitan Railway System 37

However, it should be noted that there are many intuitive samples of oscillations in the real world. This oscillation has strong relation with the network controllability and stability .

Since available data of the passenger flow analysis in Tokyo railway system are dairy data average over a year, it is reasonable to use the average of probability distribution of Markov

One of the targets is to extract outstanding patterns from huge network system: In linear systems, the dominant mode corresponds to such an outstanding pattern. This understanding coincides with that of the basic Google in which one assumes that passengers in Tokyo railway system can be approximated as random walkers in the linear Markov

The real world data, however, tell us that the largest three stations, in respect of passenger number, are *Shinjuku, Ikebukuro* and *Shibuya*: *Shinjuku* had 3.2 millions per a day as its number of passengers, *Ikebukuro* 2.6 millions, and *Shibuya* 2.3 millions, in 2006. This pattern

First we introduce SPM Markov transition of Eq.4.1 to analyse the passenger distribution pattern. The initial condition of probability amplitude is a uniformly random distribution normalized by Euclidean norm. Fig.4.5 (a) depicts temporal variation of mode probability to reach dominant mode. The passenger distribution obtained is shown in Fig.4-5 (b), that corresponds to the authentic (political and business) centre of Tokyo: *Shinbashi, Shinagawa*

a) Temporal variation of mode amplitude (b) The stationary state corresponds to the

Fig. 4.5. SPM Markov Transition of Tokyo Metropolitan Railway System.

dominant mode.

These issues are discussed in Appendix C.

**4.2 The largest three stations of Tokyo metropolitan railway** 

process. Its stationary state is the dominant mode.

does not coincide with the dominant mode.

We should overcome this discrepancy

and *Tokyo* are the dominant stations.

transition approximation.

The light panel denotes the temporal variation of mode amplitudes. The middle panel denotes the temporal variation of mode probabilities. The right panel denotes two phase of probability amplitude.(the red race inverted in sign for clearness.)

Fig. 4.2. XPM Markov transition of the Rosary network:

On the other hand, Fig.4.2 illustrates the temporal variation of mode amplitudes in the case of XPM nonlinear Markov transition based on Eq.4.2. In this case the rosary network shows

"emergence" of a kind of instability: The temporal variation of mode amplitude oscillates as shown in left panel of Fig.4.2. At stationary state, two phases are shown in the right panel of Fig.4.2. At"in-phase"denoted by red, the passengers gather on node #2 and #4 . In "out-ofphase"denoted by blue, the passengers shift to node #1,#3,#9,#22 and #39 coloured by yellow in the map of Fig.4.3 left. Those nodes can be reached from node #2 or #4 within one step. The oscillation is recognized to be sustainable transition between two groups of nodes.

This kind of oscillation has not been reported in real world, yet. One of convenient interpretation is that average of two states is assumed to be observable; that is, we assume the average state corresponds to observable phenomenon in the real world. Fig.4.4 (b) illustrates the average state corresponds to the instability in the XPM Markov transition. Markov transition approximation of a large-scale network has a limitation due to delay time to obtain information of nodes connected to a node, at each transition, so that it might be reasonable to take average of oscillating states, just mentioned above.

Fig. 4.3. (a) Sustainable oscillation between two groups of nodes (b) Average probability distribution

The light panel denotes the temporal variation of mode amplitudes. The middle panel denotes the temporal variation of mode probabilities. The right panel denotes two phase of probability

On the other hand, Fig.4.2 illustrates the temporal variation of mode amplitudes in the case of XPM nonlinear Markov transition based on Eq.4.2. In this case the rosary network shows "emergence" of a kind of instability: The temporal variation of mode amplitude oscillates as shown in left panel of Fig.4.2. At stationary state, two phases are shown in the right panel of Fig.4.2. At"in-phase"denoted by red, the passengers gather on node #2 and #4 . In "out-ofphase"denoted by blue, the passengers shift to node #1,#3,#9,#22 and #39 coloured by yellow in the map of Fig.4.3 left. Those nodes can be reached from node #2 or #4 within one step. The oscillation is recognized to be sustainable transition between two groups of nodes. This kind of oscillation has not been reported in real world, yet. One of convenient interpretation is that average of two states is assumed to be observable; that is, we assume the average state corresponds to observable phenomenon in the real world. Fig.4.4 (b) illustrates the average state corresponds to the instability in the XPM Markov transition. Markov transition approximation of a large-scale network has a limitation due to delay time to obtain information of nodes connected to a node, at each transition, so that it might be

amplitude.(the red race inverted in sign for clearness.)

distribution

Fig. 4.2. XPM Markov transition of the Rosary network:

reasonable to take average of oscillating states, just mentioned above.

Fig. 4.3. (a) Sustainable oscillation between two groups of nodes (b) Average probability

However, it should be noted that there are many intuitive samples of oscillations in the real world. This oscillation has strong relation with the network controllability and stability . These issues are discussed in Appendix C.

Since available data of the passenger flow analysis in Tokyo railway system are dairy data average over a year, it is reasonable to use the average of probability distribution of Markov transition approximation.

### **4.2 The largest three stations of Tokyo metropolitan railway**

One of the targets is to extract outstanding patterns from huge network system: In linear systems, the dominant mode corresponds to such an outstanding pattern. This understanding coincides with that of the basic Google in which one assumes that passengers in Tokyo railway system can be approximated as random walkers in the linear Markov process. Its stationary state is the dominant mode.

The real world data, however, tell us that the largest three stations, in respect of passenger number, are *Shinjuku, Ikebukuro* and *Shibuya*: *Shinjuku* had 3.2 millions per a day as its number of passengers, *Ikebukuro* 2.6 millions, and *Shibuya* 2.3 millions, in 2006. This pattern does not coincide with the dominant mode.

We should overcome this discrepancy

First we introduce SPM Markov transition of Eq.4.1 to analyse the passenger distribution pattern. The initial condition of probability amplitude is a uniformly random distribution normalized by Euclidean norm. Fig.4.5 (a) depicts temporal variation of mode probability to reach dominant mode. The passenger distribution obtained is shown in Fig.4-5 (b), that corresponds to the authentic (political and business) centre of Tokyo: *Shinbashi, Shinagawa* and *Tokyo* are the dominant stations.

a) Temporal variation of mode amplitude (b) The stationary state corresponds to the dominant mode.

Fig. 4.5. SPM Markov Transition of Tokyo Metropolitan Railway System.

Topological Analysis of Tokyo Metropolitan Railway System 39

"Tsubo therapy" inspired us to study "Impulse response" in network dynamics: The impulse response in electrical circuit theory provides "frequency response function", through the Fourier Transform, that makes it possible to analyse various dynamics of the circuit system. We named "an impulse applied at a node" as "point stimulus", after professor H. Horiike, architect: winner of Grand Prix of the Dedalo-Minosse International Award'02, Italy. (Horiike, 2000); The point stimulus is expressed as the initial condition

where the impulse is applied. So far, this study is at dawn and a lot of unexplored remains. This section is based on our paper presented at KDIR2010 (International conference on

Here we would like to show examples of point stimulus responses in Tokyo Metropolitan Railway System as illustrared in Fig.5.1: the upper row denotes those of "*Shinjuku"*, "*Harajuku*" and "*Shibuya*". These point stimulus responses are dumping oscillations having fairly large amplitude of #735 mode. As discussed in subsection 4.2, since *Shinjuku* and *Shibuya* are the two of largest stations in Tokyo Metropolitan Railway System, and their degrees are sufficiently large, it is reasonable that they have larger point stimulus responses. On the contrary, "Harajuku" shows fairly large point stimulus response, but is a small station from viewpoint of its degree. The degree of *Harajuku* is only two compared to 11 of *Shinjuku*. In real world, "*Harajuku*" is a small station, but a famous down of youths and fashions. It can be said that the larger point stimulus response of "Harajiku" suggests that the point stimulus response is a reasonable tool to

The lower row denotes point stimulus responses of "*Shinagawa*","*Yurakucho*" and "*Tokyo*". As discussed in subsection 4.2, those stations belong to the group of "authentic centre of Metropolitan Tokyo". The dumping oscillations occur in eigenmode #734 that is the mode having negative second largest eigenvalue of -3.947. "Shinagawa" and "Tokyo" are fairly large station but the point stimulus responses are not so large that may reflect declining of those areas in 2006. Recently it can be said there are many successful projects to refresh these areas, such as *Shinagawa* intercity project. On the contrary, *Yurakucho* shows a relatively larger point stimulus response compared to small degree of 4. It can be said that the point

Fig.5.2 denotes the cases that point stimulus responses reflect the miscellaneous station activities. The cases of "*Akihabara*" with degree of 7, "*Megro*" with degree of 4 and "*Otsuka*" with degree of 2 are illustrated.: The point stimulus response well reflects the declining activity of "*Akihabara*" in spite of various projects for actiovation. "Meguro" and "*Otsuka*" seem to have larger point stimulus responses than their actual activities. It requires further studies whether these discrepancies suggest the chance of investments for town activation or not. We demonstrate the point stimulus response as one of interesting tool of checking the activity of node. It is expected that the point stimulus response is a clue to find the real

(..) is the kronecker delta, and *p* denotes the node

**5.1 Point stimulus response of Tokyo metropolitan railway system** 

**5. "Tsubo" of network system** 

(, ) *i p* of the Markov transition, where

evaluate station activity.

affects of networking on a node.

Knowledge Discovery and Information Retrieval 2010).

stimulus response well reflects the town activity of *Yurakucho*.

Secondary, we introduce XPM Markov transition of Eq.4.2 to analyse the passenger distribution pattern. Fig.4.6 (a) depicts temporal variation of mode probability obtained for XPM. Mode #735 (N-1) having negative eigenvalue of –4.271 oscillates continuously and Mode #732 (N-4) having positive eigenvalue of +4.423 reaches to stationary state of –0.612. This instability corresponds to sustainable commuting of random walkers between the two phases as shown in the middle panel of Fig.4.6.

Left: Temporal variation of mode amplitude, Middle: Two phase of oscillation. Right: Average Probability Distribution.

Fig. 4.6. XPM Markov transition of Tokyo Metropolitan Railway System

According to the discussion on the rosary network in subsection 4.1, the average observable state corresponds to three largest stations of Tokyo Metropolitan Railway system, as shown in the right panel of Fig.4.6. This pattern of passenger distribution might be recognized as a central zone of entertainments or young people's activity, comparing to the authentic centre of Tokyo discussed in SPM Markov transition.

These analyses suggest the importance of nonlinear interaction in passenger distribution of railway network systems. This non-linearity of passenger flow reflects a human nature such as "Birds with a feather flog together".

### **4.3 Network dynamics and Markov process**

The most basic assumption of the nonlinear Markov transition is the synchronous transition among all of the nodes in the network. The probability amplitude of higher-order mode varies in sign at nodes so that the superposition in transition causes complicated interferences among various routes of transition.

These multiple path interference may cause oscillation and dominates dynamics of network system. The multiple path interference may have relation with chromatic number in local structure.

The possibility of sustainable oscillations, including relation of chromatic number, was reported in the ICCS (International Conference of Complex System) in Boston, July 2011. However, no experimental evidence is reported yet. (Ozeki, 2011)

### **5. "Tsubo" of network system**

38 Infrastructure Design, Signalling and Security in Railway

Secondary, we introduce XPM Markov transition of Eq.4.2 to analyse the passenger distribution pattern. Fig.4.6 (a) depicts temporal variation of mode probability obtained for XPM. Mode #735 (N-1) having negative eigenvalue of –4.271 oscillates continuously and Mode #732 (N-4) having positive eigenvalue of +4.423 reaches to stationary state of –0.612. This instability corresponds to sustainable commuting of random walkers between the two

Left: Temporal variation of mode amplitude, Middle: Two phase of oscillation. Right: Average

According to the discussion on the rosary network in subsection 4.1, the average observable state corresponds to three largest stations of Tokyo Metropolitan Railway system, as shown in the right panel of Fig.4.6. This pattern of passenger distribution might be recognized as a central zone of entertainments or young people's activity, comparing to the authentic centre

These analyses suggest the importance of nonlinear interaction in passenger distribution of railway network systems. This non-linearity of passenger flow reflects a human nature such

The most basic assumption of the nonlinear Markov transition is the synchronous transition among all of the nodes in the network. The probability amplitude of higher-order mode varies in sign at nodes so that the superposition in transition causes complicated

These multiple path interference may cause oscillation and dominates dynamics of network system. The multiple path interference may have relation with chromatic number in local

The possibility of sustainable oscillations, including relation of chromatic number, was reported in the ICCS (International Conference of Complex System) in Boston, July 2011.

Fig. 4.6. XPM Markov transition of Tokyo Metropolitan Railway System

phases as shown in the middle panel of Fig.4.6.

of Tokyo discussed in SPM Markov transition.

**4.3 Network dynamics and Markov process** 

interferences among various routes of transition.

However, no experimental evidence is reported yet. (Ozeki, 2011)

as "Birds with a feather flog together".

Probability Distribution.

structure.

"Tsubo therapy" inspired us to study "Impulse response" in network dynamics: The impulse response in electrical circuit theory provides "frequency response function", through the Fourier Transform, that makes it possible to analyse various dynamics of the circuit system. We named "an impulse applied at a node" as "point stimulus", after professor H. Horiike, architect: winner of Grand Prix of the Dedalo-Minosse International Award'02, Italy. (Horiike, 2000); The point stimulus is expressed as the initial condition (, ) *i p* of the Markov transition, where (..) is the kronecker delta, and *p* denotes the node where the impulse is applied. So far, this study is at dawn and a lot of unexplored remains. This section is based on our paper presented at KDIR2010 (International conference on Knowledge Discovery and Information Retrieval 2010).

### **5.1 Point stimulus response of Tokyo metropolitan railway system**

Here we would like to show examples of point stimulus responses in Tokyo Metropolitan Railway System as illustrared in Fig.5.1: the upper row denotes those of "*Shinjuku"*, "*Harajuku*" and "*Shibuya*". These point stimulus responses are dumping oscillations having fairly large amplitude of #735 mode. As discussed in subsection 4.2, since *Shinjuku* and *Shibuya* are the two of largest stations in Tokyo Metropolitan Railway System, and their degrees are sufficiently large, it is reasonable that they have larger point stimulus responses. On the contrary, "Harajuku" shows fairly large point stimulus response, but is a small station from viewpoint of its degree. The degree of *Harajuku* is only two compared to 11 of *Shinjuku*. In real world, "*Harajuku*" is a small station, but a famous down of youths and fashions. It can be said that the larger point stimulus response of "Harajiku" suggests that the point stimulus response is a reasonable tool to evaluate station activity.

The lower row denotes point stimulus responses of "*Shinagawa*","*Yurakucho*" and "*Tokyo*". As discussed in subsection 4.2, those stations belong to the group of "authentic centre of Metropolitan Tokyo". The dumping oscillations occur in eigenmode #734 that is the mode having negative second largest eigenvalue of -3.947. "Shinagawa" and "Tokyo" are fairly large station but the point stimulus responses are not so large that may reflect declining of those areas in 2006. Recently it can be said there are many successful projects to refresh these areas, such as *Shinagawa* intercity project. On the contrary, *Yurakucho* shows a relatively larger point stimulus response compared to small degree of 4. It can be said that the point stimulus response well reflects the town activity of *Yurakucho*.

Fig.5.2 denotes the cases that point stimulus responses reflect the miscellaneous station activities. The cases of "*Akihabara*" with degree of 7, "*Megro*" with degree of 4 and "*Otsuka*" with degree of 2 are illustrated.: The point stimulus response well reflects the declining activity of "*Akihabara*" in spite of various projects for actiovation. "Meguro" and "*Otsuka*" seem to have larger point stimulus responses than their actual activities. It requires further studies whether these discrepancies suggest the chance of investments for town activation or not. We demonstrate the point stimulus response as one of interesting tool of checking the activity of node. It is expected that the point stimulus response is a clue to find the real affects of networking on a node.

Topological Analysis of Tokyo Metropolitan Railway System 41

We demonstrate a new network analysis based only on network topology of Tokyo Metropolitan Railway System. It is in highly abstractive and seems like a metaphor without any rigorous physical approval. However, many of analysis seem to illustrate the truth of

Rene Descartes wished all of the world could be described mathematically, then, as his first step, the analytical geometry was innovated. Prigogine, the originator complex systems, declared a "new alliance" between natural sciences and human sciences to solve global

Here, we report a tiny effort of topological analysis of railway systems in this context. It is our wish to explore the horizon of our new mathematical platform as a tool for supporting

The multimodal analysis based non-linear Markov transition approximation is still in its

This section is based on our paper presented in ICCS (International Conference on Complex

After the complex systems was originated by Ilya Prigogine from various foundations including irreversibility and self-organization in nonlinear dynamics (Prigogine, 1996), Barabasi introduced scale free networks for describing interaction between structures or constituents of complex network systems (Barabasi2002). On the other hand, Brin and Page simulated a web surfer by Markov transition through network linking web pages (Brin, 1998). Then they found with their surprise, in spite of personal inherence of the Page Rank, that the web-network graph can rank the page importance mechanically by its dominant eigenvector (Brin, 1998, Langville 2006). We were inspired from theses historical flows to construct a multi-modal platform of Markov transition with nonlinear interaction for

dawn. There are the vast amounts of works unexplored for the future.

Fig. 5.2. Miscellaneous "point stimulus response"

railway system from abstractive viewpoint.

intuitive power of railway system designers.

**7. Appendix1 – Mathematical platform** 

**7.1 A new rule introduced in mathematical platform** 

**6. Conclusion** 

issues of human beings.

Systems) 2011.

analysing complex networks.

Fig. 5.1. Reasonable correlations of "point stimulus responses" with station activities.

Fig. 5.2. Miscellaneous "point stimulus response"

### **6. Conclusion**

40 Infrastructure Design, Signalling and Security in Railway

Fig. 5.1. Reasonable correlations of "point stimulus responses" with station activities.

We demonstrate a new network analysis based only on network topology of Tokyo Metropolitan Railway System. It is in highly abstractive and seems like a metaphor without any rigorous physical approval. However, many of analysis seem to illustrate the truth of railway system from abstractive viewpoint.

Rene Descartes wished all of the world could be described mathematically, then, as his first step, the analytical geometry was innovated. Prigogine, the originator complex systems, declared a "new alliance" between natural sciences and human sciences to solve global issues of human beings.

Here, we report a tiny effort of topological analysis of railway systems in this context. It is our wish to explore the horizon of our new mathematical platform as a tool for supporting intuitive power of railway system designers.

The multimodal analysis based non-linear Markov transition approximation is still in its dawn. There are the vast amounts of works unexplored for the future.

### **7. Appendix1 – Mathematical platform**

This section is based on our paper presented in ICCS (International Conference on Complex Systems) 2011.

### **7.1 A new rule introduced in mathematical platform**

After the complex systems was originated by Ilya Prigogine from various foundations including irreversibility and self-organization in nonlinear dynamics (Prigogine, 1996), Barabasi introduced scale free networks for describing interaction between structures or constituents of complex network systems (Barabasi2002). On the other hand, Brin and Page simulated a web surfer by Markov transition through network linking web pages (Brin, 1998). Then they found with their surprise, in spite of personal inherence of the Page Rank, that the web-network graph can rank the page importance mechanically by its dominant eigenvector (Brin, 1998, Langville 2006). We were inspired from theses historical flows to construct a multi-modal platform of Markov transition with nonlinear interaction for analysing complex networks.

Topological Analysis of Tokyo Metropolitan Railway System 43

respect to the Euclidean norm|| || ˆ *A qn* after each transition step. This mathmatical idea used in the power method assures the stablity and also assures the linear properties of the

Furthermore, this idea lead us to read the state vector ( )*i n q* as a probability amplitude. The probability is defined by <sup>2</sup> ( ) |( ) | *in in p q* for finding a random walker at the node "*i "*, because

is its eigenvector. The eigenvectors can be coincident with the asymptotic solution of

It is essential for the network analysis platform to be capable to analyse nonlinear phenomena. We introduce a non-linear Markov transition as follows: the nonlinear interaction in Markov transition means that transition from node "*j"* to node" *i"* is *affected* by

> 1 , , , , () () ()( ) *in i j j <sup>n</sup> <sup>j</sup> i ki <sup>j</sup> n kn*

 is a measure of nonlinear interaction. Eq.A.3 includes implicitly the normalization process as shown in EqA.2. This expression agrees with the definition of the Markov process, that is, the transition is determined only by the states at the present step *n.* The 3rd

*A A q q* (A3)

*j j k*

**8. Appendix 2 – Variety of topological parameters in family networks** 

The family network series, visualized in Table A1, provides variety of topological parameters of networks, such as degree correlations, clustering coefficients, and network entropies. These parameters are plotted in Fig.A.1 to understand details. The red line in the figure denotes a typical variation of the degree Pearson correlations depending on the constituent family size *M* of family network series. A" typical variation" means that the degree correlations shown in Fig.A.1 is the mean value of those calculated for 10 samples of networks, having about 100 total nodes, for each. The BA network is known as a disassortative network, that is, nodes with low degrees are more likely to be connected to the nodes with high degrees, and vice versa. The family networks with larger size *M* of constituent family become to be assortative, that is, nodes with a given degree are more likely to have links with nodes of similar degree. These Pearson coefficients of degree correlation (Soramaki, 2007) are illustrated in Fig.A.1 as a

the sum of probability ( )*i n p* over all nodes is normalized to unity as shown in Eq.A2.

*nq* is the state vector at the nth transition step. The state vector is nomalized with

*<sup>m</sup>* is the eigenvalue of mode " *m* ", and

where ˆ

( ) *m i* 

where

red line.

Markov transition.

The eigen-equation is () () *m m A*

Eq.A2 in the power method.

**7.4 Markov transition with weak non-linearity** 

*i i <sup>m</sup>* where

the probability amplitude ( ) *k n q* at node" *k"* linked to the node *i* , that is

*q A q*

order nonlinear Markov transition is introduced in section 4.

A new rule of Euclidian norm, introduced in normalization in Markov transition approximation, provides us a new multi-modal description of complex systems: The Markov transition approximation of Page-Ranking in Google uses only the dominant mode, because their elements of the eigenvector are positive semi-definitive, and so, can be recognized as the probability finding a web surfer on a web page.

However, the elements of the eigenvectors of higher order modes are not positive semidefinitive, so that a new rule is necessary for defining the probability to find the web surfer on the page in higher order mode. It is well known that, in the power method for analysing eigenmode of such an adjacency matrix, the state vector at each transition is normalized by its Euclidian norm to prevent divergence. Since the sum of squared elements of the state vector is normalized to unity, the squared elements of the state vector can be recognized as the probability finding the web surfer on each node, just analogous to the quantum physics. In this way, we can describe the multi-modal behaviours of complex network systems employing the nonlinear Markov transition approximation (Ozeki, 2009)**.** 

### **7.2 Topology dependent characteristics of various networks**

For analysing topology dependent characteristics, it is necessary to generate scale free networks having different topological characteristics, as references. Here we employ the Granvetter's family network series [Ozeki2006:]. Using family network series, various topology dependent characteristics of scale free networks can be reviewed, in terms of chromatic number, degree correlation, clustering coefficient, and network entropy. Among these reviews, we report a sustainable oscillation caused by the unique eigenmode structure of BA-network. This topology dependent instability, which arises from mode competition in a special mode structure, named "skew degenerate modes", is observed in the most popular BA networks (Barabasi, 2002). The skew mode is discussed more in A.3.

### **7.3 A mathematical platform of network multimodal analysis**

Now we summarize a mathematical platform for network analysis in multi-modal scheme. The platform is based on the Markov transition to approximate the variation of network state: A symmetric adjacency matrix, providing an orthogonal eigenvector set, is suitable for multi-modal analysis of a network system. However, divergence in the Markov transition using the adjacency matrix as the transition matrix is a serious problem. Here, we apply a mathematical procedure, being used in "the power method" (Langville, 2006), for preventing the divergence: In Markov process approximation, the variation of network state given by

$$
\hat{q}\_{n+1} = A \cdot \hat{q}\_n \tag{A1}
$$

is described explicitly in the power method by

$$
\hat{q}\_{n+1} = A \cdot \hat{q}\_n / \parallel A \cdot \hat{q}\_n \parallel \tag{A2}
$$

A new rule of Euclidian norm, introduced in normalization in Markov transition approximation, provides us a new multi-modal description of complex systems: The Markov transition approximation of Page-Ranking in Google uses only the dominant mode, because their elements of the eigenvector are positive semi-definitive, and so, can be

However, the elements of the eigenvectors of higher order modes are not positive semidefinitive, so that a new rule is necessary for defining the probability to find the web surfer on the page in higher order mode. It is well known that, in the power method for analysing eigenmode of such an adjacency matrix, the state vector at each transition is normalized by its Euclidian norm to prevent divergence. Since the sum of squared elements of the state vector is normalized to unity, the squared elements of the state vector can be recognized as the probability finding the web surfer on each node, just analogous to the quantum physics. In this way, we can describe the multi-modal behaviours of complex network systems employing the nonlinear Markov transition

For analysing topology dependent characteristics, it is necessary to generate scale free networks having different topological characteristics, as references. Here we employ the Granvetter's family network series [Ozeki2006:]. Using family network series, various topology dependent characteristics of scale free networks can be reviewed, in terms of chromatic number, degree correlation, clustering coefficient, and network entropy. Among these reviews, we report a sustainable oscillation caused by the unique eigenmode structure of BA-network. This topology dependent instability, which arises from mode competition in a special mode structure, named "skew degenerate modes", is observed in the most popular BA networks (Barabasi, 2002). The skew mode is discussed

Now we summarize a mathematical platform for network analysis in multi-modal scheme. The platform is based on the Markov transition to approximate the variation of network state: A symmetric adjacency matrix, providing an orthogonal eigenvector set, is suitable for multi-modal analysis of a network system. However, divergence in the Markov transition using the adjacency matrix as the transition matrix is a serious problem. Here, we apply a mathematical procedure, being used in "the power method" (Langville, 2006), for preventing the divergence: In Markov process approximation, the variation of network state

<sup>1</sup> ˆ ˆ

<sup>1</sup> *q Aq Aq* ˆˆˆ

*n n q A q* (A1)

*nnn* /|| || (A2),

recognized as the probability finding a web surfer on a web page.

**7.2 Topology dependent characteristics of various networks** 

**7.3 A mathematical platform of network multimodal analysis** 

is described explicitly in the power method by

approximation (Ozeki, 2009)**.** 

more in A.3.

given by

where ˆ *nq* is the state vector at the nth transition step. The state vector is nomalized with respect to the Euclidean norm|| || ˆ *A qn* after each transition step. This mathmatical idea used in the power method assures the stablity and also assures the linear properties of the Markov transition.

Furthermore, this idea lead us to read the state vector ( )*i n q* as a probability amplitude. The probability is defined by <sup>2</sup> ( ) |( ) | *in in p q* for finding a random walker at the node "*i "*, because the sum of probability ( )*i n p* over all nodes is normalized to unity as shown in Eq.A2.

The eigen-equation is () () *m m A i i <sup>m</sup>* where *<sup>m</sup>* is the eigenvalue of mode " *m* ", and ( ) *m i* is its eigenvector. The eigenvectors can be coincident with the asymptotic solution of Eq.A2 in the power method.

#### **7.4 Markov transition with weak non-linearity**

It is essential for the network analysis platform to be capable to analyse nonlinear phenomena. We introduce a non-linear Markov transition as follows: the nonlinear interaction in Markov transition means that transition from node "*j"* to node" *i"* is *affected* by the probability amplitude ( ) *k n q* at node" *k"* linked to the node *i* , that is

$$\mathbf{u}(q\_i)\_{n+1} = \sum\_j A\_{i,j} \cdot (q\_j)\_n + \sum\_{j,k} \nu \cdot A\_{j,i} \cdot A\_{k,i} (q\_j)\_n \cdot (q\_k)\_n \tag{A3}$$

where is a measure of nonlinear interaction. Eq.A.3 includes implicitly the normalization process as shown in EqA.2. This expression agrees with the definition of the Markov process, that is, the transition is determined only by the states at the present step *n.* The 3rd order nonlinear Markov transition is introduced in section 4.

### **8. Appendix 2 – Variety of topological parameters in family networks**

The family network series, visualized in Table A1, provides variety of topological parameters of networks, such as degree correlations, clustering coefficients, and network entropies. These parameters are plotted in Fig.A.1 to understand details. The red line in the figure denotes a typical variation of the degree Pearson correlations depending on the constituent family size *M* of family network series. A" typical variation" means that the degree correlations shown in Fig.A.1 is the mean value of those calculated for 10 samples of networks, having about 100 total nodes, for each. The BA network is known as a disassortative network, that is, nodes with low degrees are more likely to be connected to the nodes with high degrees, and vice versa. The family networks with larger size *M* of constituent family become to be assortative, that is, nodes with a given degree are more likely to have links with nodes of similar degree. These Pearson coefficients of degree correlation (Soramaki, 2007) are illustrated in Fig.A.1 as a red line.

Topological Analysis of Tokyo Metropolitan Railway System 45

The variety of topological parameters of the family network provides a possibility of better approximation for a given network topology: We can approximate a network topology generated by the family network growth mechanism, with selecting the size *M* of constituent family randomly at the entry to meet its statistics, such as size of household

Red line denotes the degree correlation using Pearson's formula and Blue dotted line denotes the clustering coefficient. Black line with diamonds denotes the network entropy with the right-hand scale.

In Table A1, family network series are illustrated with the smallest number of colours: the chromatic number of a graph, in the third row in Table A1, is the smallest number of colours such that no two adjacent nodes share the same colour (http://mathworld.wolfram.com/chromaticNumber.html). This chromatic number is

The BA network has the same chromatic number as the coupled harmonic oscillators, which consist of a long chain of masses and springs. Dyson analysed the coupled oscillators in 1953 to find mode pairs having the same eigenvalue in absolute value but different in sign

Degeneracy generally refers to objects having the same eigenvalue but different in eigenvectors, whereas the skew degeneracy, we named, refers to objects having different eigenvalues with respect to the sign of the eigenvalue but having the same probability distribution, that is the

For an example, Fig.A.3.1 (1) shows the eigenvalue of the adjacency matrix of the BA network *M*=1 illustrated in Table A1, that includes two pairs of skew degeneracy modes. Fig.A.3.1 (2) illustrates the eigenvectors corresponding to a skew degenerate mode pair: Blue line denotes the dominant mode #8 having eigenvalue of +2.853, and Red line with circles denotes the mode amplitude of mode #9 having eigenvalue of –2.853. Fig.A.3.1. (3) denotes

Fig. A.1.1. Topological parameter variation of family network series

square of the eigenvectors normalized with respect to the Euclidean norm.

their probability distributions of mode #8 and #9 that coincides with each other.

**9. Appendix 3 – Skew degeneracy** 

strongly related to the symmetry of the graph.

(Ozeki, 2009).

(Dyson, 1953).


Table A.1. Topology Dependent Network Dynamics

A clustering coefficient of a node is defined by the ratio of the actual number of links among neighbours of the node over the number of potential links among them. The clustering coefficient of the network is the mean clustering coefficient over all of nodes. The blue line in Fig.A.1 denotes the clustering coefficients of family networks. The family network with larger *M* has higher clustering coefficient.

Three kinds of entropy can be defined in multimodal description:

The first one is the node entropy *NEi* that is defined by the sum of Shannon entropies over all of modes, that is,

$$NE\_i = -\sum\_m p\_i^{(m)} \ln p\_i^{(m)}\,. \tag{A4}$$

The second is the mode entropy *MEm* that is defined by the sum of Shannon entropies over all of nodes, that is,

$$ME\_m = -\sum\_i p\_i^{(m)} \ln p\_i^{(m)} \,. \tag{A5}$$

The third is the network entropy that is defined by the sum of node (or mode) entropies over all of nodes (or modes), that is,

$$\text{NetE} = \sum\_{i} \text{NE}\_{i} = \sum\_{m} \text{ME}\_{m} \,. \tag{A6}$$

The network entropy is plotted by black line with diamonds in Fig.A.1, corresponding the family network shown in Table A1.

Chromatic Number 2 2 or 3 More than 3 Morethan4

A clustering coefficient of a node is defined by the ratio of the actual number of links among neighbours of the node over the number of potential links among them. The clustering coefficient of the network is the mean clustering coefficient over all of nodes. The blue line in Fig.A.1 denotes the clustering coefficients of family networks. The family network with

The first one is the node entropy *NEi* that is defined by the sum of Shannon entropies over

*i i i m*

The second is the mode entropy *MEm* that is defined by the sum of Shannon entropies over

*m i i i*

The third is the network entropy that is defined by the sum of node (or mode) entropies

*i m*

The network entropy is plotted by black line with diamonds in Fig.A.1, corresponding the

() () ln *m m*

() () ln *m m*

*i m*

*NE p p* . (A4)

*ME p p* . (A5)

*NetE NE ME* . (A6)

Entropy 1.0 1.9 2.0 2.0 Degree Correlation -0.30 -0.10 0.11 0.15 Clustering Coefficient 0 0 0.24 0.37 Asymptotic Exponent 3 4 5 6

Table A.1. Topology Dependent Network Dynamics

Three kinds of entropy can be defined in multimodal description:

larger *M* has higher clustering coefficient.

all of modes, that is,

all of nodes, that is,

over all of nodes (or modes), that is,

family network shown in Table A1.

Family Network Topology

(ref. ICCS2006,id405)

Temporal Response (Non-linear Markov) p gy p y

BA Network (M=1) Pair Network (M=2) Trio Network(M=3) Quartet Net (M=4)

The variety of topological parameters of the family network provides a possibility of better approximation for a given network topology: We can approximate a network topology generated by the family network growth mechanism, with selecting the size *M* of constituent family randomly at the entry to meet its statistics, such as size of household (Ozeki, 2009).

Red line denotes the degree correlation using Pearson's formula and Blue dotted line denotes the clustering coefficient. Black line with diamonds denotes the network entropy with the right-hand scale.

Fig. A.1.1. Topological parameter variation of family network series

### **9. Appendix 3 – Skew degeneracy**

In Table A1, family network series are illustrated with the smallest number of colours: the chromatic number of a graph, in the third row in Table A1, is the smallest number of colours such that no two adjacent nodes share the same colour (http://mathworld.wolfram.com/chromaticNumber.html). This chromatic number is strongly related to the symmetry of the graph.

The BA network has the same chromatic number as the coupled harmonic oscillators, which consist of a long chain of masses and springs. Dyson analysed the coupled oscillators in 1953 to find mode pairs having the same eigenvalue in absolute value but different in sign (Dyson, 1953).

Degeneracy generally refers to objects having the same eigenvalue but different in eigenvectors, whereas the skew degeneracy, we named, refers to objects having different eigenvalues with respect to the sign of the eigenvalue but having the same probability distribution, that is the square of the eigenvectors normalized with respect to the Euclidean norm.

For an example, Fig.A.3.1 (1) shows the eigenvalue of the adjacency matrix of the BA network *M*=1 illustrated in Table A1, that includes two pairs of skew degeneracy modes. Fig.A.3.1 (2) illustrates the eigenvectors corresponding to a skew degenerate mode pair: Blue line denotes the dominant mode #8 having eigenvalue of +2.853, and Red line with circles denotes the mode amplitude of mode #9 having eigenvalue of –2.853. Fig.A.3.1. (3) denotes their probability distributions of mode #8 and #9 that coincides with each other.

Topological Analysis of Tokyo Metropolitan Railway System 47

The node patterns illustrated by red and blue lines coincide with the chromatic groups

On the other hand, the family networks with 3 *M* show quicker transition to the stationary

It is shown the following; the topology dependent instability dominates the temporal response in controlling the network system so that the network topology determines the

The session 2 of reference(Ozeki, 2006) should be read as follows: The asymptotic connectivity distributions of the full-mesh family networks are derived by the method reported by Dorogovtsev et al. At initial time t=1, the number of constituent family is one so that the number of nodes is *M*. We assume the node attractiveness is given by A+*M*-1 where the number of links is *M*-1, so that the total attractiveness is M(A+M-1). At time t=t, the total attractiveness of the network is M(A+M-1)t+M(t-1), where the last term M(t-1) is the contribution of the weak ties. By replacing these in equations *pkst* ( , , 1) , then the

> 1 (2 2 1) ( ) ( ) 2 ( ) ( 2 1) *<sup>M</sup> A kA p k MA kM A*

The network dynamics such as stability of the network system depends on the topology of the network system. Family network series gives us typical dynamics variations, as shown in TableA.1, as a reference. These understanding seem helpful to design network such as

So far there is no experimental evidence showing these transient behaviours of networks

a BA network with 100 nodes is illustrated in Fig.A.4.1 (1). The node # 0, and #1 and #2 are larger hubs. We might assume it as an ancestry of a family struggle, or an organization map just after consolidation of three small consanguineous companies. This topology consists of 26 pairs of skew degenerate modes and shows sustainable oscillation from an initial condition of random probability amplitude distribution as shown in Fig.A.4.1 (2). This

An intuitive method to prevent these troubles is to span a new link between two hubs, node #1 and #2 as shown in Fig.A.4.1 (3). This method is confirmed to be effective to convert the sustainable oscillation to quicker transition to stable state, by the non-linear Markov

might correspond to longer periods of struggles or troubles in this network system.

*M* 1 *A* .

**10.2 Network stabilization by topological improvement** 

yet, but we can imagine several examples intuitively as follow:

transition simulation, as shown in Fig.A.4.1 (4).

(A10)

state corresponding to the dominant mode, as shown in the second row of Table A.1.

shown in the first row of Table A.1.

dependability of the system, in a sense.

connectivity distribution p(k) is given by

We obtain the asymptotic exponent

railway system.

**10. Appendix 4 – Family network series as reference** 

**10.1 Network growth mechanism of family network** 

(1)Eigenvalue (2) Mode amplitudes: Blue line denotes the dominant mode (#8) having eigenvalue of 2.853 Red line with circles denotes the mode amplitude of mode #9 having eigenvalue of –2.853 (3)Probability Distribution :Both of skew modes coincide.

Fig. A.3.1. Skew Degenerate Mode Pair of BA network (M=1)

The family network with M=2 has a possibility having mode pairs of skew degeneracy. However, the other family networks with larger M than 3 do not show the skew degeneracy.

#### **9.1 Temporal response of skew degenerate modes in nonlinear Markov transition**

The nonlinear Markov transition of Eq.A.3 can be converted to the description of the nonlinear interaction of mode amplitudes for getting clearer image, as the following:

$$(a\_m)\_{n+1} = \mathbb{A}\_m \cdot (a\_m)\_n + \sum\_{i,m',m''} \nu \cdot \mathbb{A}\_{m'} \cdot \mathbb{A}\_{m''} \cdot \phi\_i^{m'} \cdot \phi\_i^{m''} \cdot \phi\_i^{m} \cdot (a\_{m'})\_n \cdot (a\_{m''})\_n \tag{A7}$$

where the modes are defined by the linear adjacency matrix. It should be noted that the equivalency of Eq.A.3 and Eq.A.4 is limited only for the case of very weak non-linearity considered.

The transient response of the network having the skew degeneracy shows the sustainable oscillation in the nonlinear Markov transition as shown in the second row of Table A.1. The initial conditions are the modes with the negative largest eigenvalue. The skew mode pair survives in mode competition so that the random walker continues to commutate between two states that are the superposed states of the skew degenerate modes with in-phase and out-of-phase, respectively. The two states correspond to the group of the black and the red nodes in the BA –network, so that the random walker commutes between the node groups of red and black.

Fig.A.3.2 illustrates these situations clearly; the probability amplitude distribution is given by ( ) () ( ) *<sup>m</sup> in mn i m q a* , that corresponds to the superposition of two competing modes #8 and #9 illustrated in Fig.A.3.2 (2): The mode amplitude <sup>9</sup> ( )*<sup>n</sup> a* in red of Fig.A.3.2 (1) continues to oscillate between 1/ 2 and 1/ 2 whereas 8 ( )*<sup>n</sup> a* in blue grows up to 1/ 2 so that the superposition of two competing modes corresponds to red line of in-phase and blue line of out-of-phase as shown in Fig.A.3.2 (2).

(1) (2) (3) (1)Eigenvalue (2) Mode amplitudes: Blue line denotes the dominant mode (#8) having eigenvalue of 2.853 Red line with circles denotes the mode amplitude of mode #9 having eigenvalue of –2.853

The family network with M=2 has a possibility having mode pairs of skew degeneracy. However, the other family networks with larger M than 3 do not show the skew degeneracy.

The nonlinear Markov transition of Eq.A.3 can be converted to the description of the

() () ( )( ) *mm m mn m mn m m i i i mn m n*

where the modes are defined by the linear adjacency matrix. It should be noted that the equivalency of Eq.A.3 and Eq.A.4 is limited only for the case of very weak non-linearity

The transient response of the network having the skew degeneracy shows the sustainable oscillation in the nonlinear Markov transition as shown in the second row of Table A.1. The initial conditions are the modes with the negative largest eigenvalue. The skew mode pair survives in mode competition so that the random walker continues to commutate between two states that are the superposed states of the skew degenerate modes with in-phase and out-of-phase, respectively. The two states correspond to the group of the black and the red nodes in the BA –network, so that the random walker commutes between the node groups

Fig.A.3.2 illustrates these situations clearly; the probability amplitude distribution is given

and #9 illustrated in Fig.A.3.2 (2): The mode amplitude <sup>9</sup> ( )*<sup>n</sup> a* in red of Fig.A.3.2 (1) continues to oscillate between 1/ 2 and 1/ 2 whereas 8 ( )*<sup>n</sup> a* in blue grows up to 1/ 2 so that the superposition of two competing modes corresponds to red line of in-phase and blue line

, that corresponds to the superposition of two competing modes #8

 *a a*

(A7),

**9.1 Temporal response of skew degenerate modes in nonlinear Markov transition** 

nonlinear interaction of mode amplitudes for getting clearer image, as the following:

, ,

*im m*

(3)Probability Distribution :Both of skew modes coincide.

1

considered.

of red and black.

by ( ) () ( ) *<sup>m</sup> in mn i m q a*

of out-of-phase as shown in Fig.A.3.2 (2).

*a a* 

Fig. A.3.1. Skew Degenerate Mode Pair of BA network (M=1)

The node patterns illustrated by red and blue lines coincide with the chromatic groups shown in the first row of Table A.1.

On the other hand, the family networks with 3 *M* show quicker transition to the stationary state corresponding to the dominant mode, as shown in the second row of Table A.1.

It is shown the following; the topology dependent instability dominates the temporal response in controlling the network system so that the network topology determines the dependability of the system, in a sense.

### **10. Appendix 4 – Family network series as reference**

### **10.1 Network growth mechanism of family network**

The session 2 of reference(Ozeki, 2006) should be read as follows: The asymptotic connectivity distributions of the full-mesh family networks are derived by the method reported by Dorogovtsev et al. At initial time t=1, the number of constituent family is one so that the number of nodes is *M*. We assume the node attractiveness is given by A+*M*-1 where the number of links is *M*-1, so that the total attractiveness is M(A+M-1). At time t=t, the total attractiveness of the network is M(A+M-1)t+M(t-1), where the last term M(t-1) is the contribution of the weak ties. By replacing these in equations *pkst* ( , , 1) , then the connectivity distribution p(k) is given by

$$p(k) = \frac{1}{2} \frac{\Gamma(2M + 2A + 1)}{\Gamma(M + A)} \frac{\Gamma(k + A)}{\Gamma(k + M + 2A + 1)}\tag{A10}$$

We obtain the asymptotic exponent *M* 1 *A* .

#### **10.2 Network stabilization by topological improvement**

The network dynamics such as stability of the network system depends on the topology of the network system. Family network series gives us typical dynamics variations, as shown in TableA.1, as a reference. These understanding seem helpful to design network such as railway system.

So far there is no experimental evidence showing these transient behaviours of networks yet, but we can imagine several examples intuitively as follow:

a BA network with 100 nodes is illustrated in Fig.A.4.1 (1). The node # 0, and #1 and #2 are larger hubs. We might assume it as an ancestry of a family struggle, or an organization map just after consolidation of three small consanguineous companies. This topology consists of 26 pairs of skew degenerate modes and shows sustainable oscillation from an initial condition of random probability amplitude distribution as shown in Fig.A.4.1 (2). This might correspond to longer periods of struggles or troubles in this network system.

An intuitive method to prevent these troubles is to span a new link between two hubs, node #1 and #2 as shown in Fig.A.4.1 (3). This method is confirmed to be effective to convert the sustainable oscillation to quicker transition to stable state, by the non-linear Markov transition simulation, as shown in Fig.A.4.1 (4).

Topological Analysis of Tokyo Metropolitan Railway System 49

(1) (2)

Mode amplitude

(3) (4)

(1) BA network with 100 nodes, (2) Sustainable oscillation of skew degenerate mode pair, (3) Topological improvement by connecting #1 and #2, (4) The topological improvement can convert the

sustainable oscillation to quicker transition to stable state.

Fig. A.4.1. Topological Improvement of Network System Stability

.

0 20 40

steps

n

family1c+1

1

0.5

0

an 98 an 99 0.5

(1) mode amplitude <sup>9</sup> ( )*<sup>n</sup> a* in red and <sup>8</sup> ( )*<sup>n</sup> a* in blue, (2) the state amplitude of superposition.

Fig. A.3.3. In-Phase and Out-of-Phase Superposition of Skew Degenerate Mode Pair

(1) (2)

(1) mode amplitude <sup>9</sup> ( )*<sup>n</sup> a* in red and <sup>8</sup> ( )*<sup>n</sup> a* in blue, (2) the state amplitude of superposition.

Fig. A.3.3. In-Phase and Out-of-Phase Superposition of Skew Degenerate Mode Pair

(1) BA network with 100 nodes, (2) Sustainable oscillation of skew degenerate mode pair, (3) Topological improvement by connecting #1 and #2, (4) The topological improvement can convert the sustainable oscillation to quicker transition to stable state.

#### Fig. A.4.1. Topological Improvement of Network System Stability

**3** 

*Chile* 

Jose Antonio Gonzalez-Pizarro

*Universidad Católica del Norte, Antofagasta,* 

**Privatization Versus Public Funding on the** 

**Atacama Desert Railway – An Interpretation** 

Before the arrival of railways at the Atacama desert, there were only paths and tracks inherited by caravans exchanging products – the complimentarity of John Murra's ecological ground – between the Cordillera puna and the Pacific coast. The cart roads of mining prospectors from the time of the manure and copper cycles corresponding to the republican beginnings in the plateau would be added to this pre-Hispanic sequence. But, with the discovery of potassium and silver nitrate in the middle plateau during the 1860s-1870s, the multi-ethnic population settlement of Europeans and Latin Americans could be possible, the Chilean one being the most numerous. Human settlement started on the coast; Tocopilla and Mejillones in the 1840s, preceded by Cobija in 1825; then, Antofagasta in 1866. These were seaports prepared for merchandise shipping and traffic to Bolivia. Further south, that is, from parallel 24, settlement occurred in Taltal in 1858 and Paposo small port in 1865. It was the need of connectivity among the productive mining sites of the desert and communication with Potosi from the coast what made it possible to visualize a more modern and efficient means of transport in terms of capacity, speed, and safety: the railway. As any history of techniques and means of transport, railways fall within a space and time framework connected to the well-known history of the desert geography: a process marked by landmarks, opportunities, and a long-lasting process, to use French historian Fernand Braudel's categories (Braudel, 1970). In this historic context, the Atacama desert railway is the reflection of various aspects of the social, economic, political, and natural resource history of this territory. But, at the same time, the railway together with the telegraph symbolized the keen desire for progress, science potencial, and Comte's positivistic philosophy for contemporary people, as expressed by engineer Matias Rojas-Delgado, the first Antofagasta Mayor in 1872, that is, that science should lead to the rationality of mining work and railways would open the frontiers of the unknown. "Order and Progress" was a motto that triggered private ventures and set the basis for organizing a new society in this place (Gonzalez-Pizarro, 2002). This changed the image that had been inherited from Spanish chroniclers and the first republican travellers. Science and technology that poured on the desert owing to the changes made to the nitrate leaching system thought of in

1This paper is part of Fondecyt Project 1100074 and Nucleo Milenio "Ciencia Regional y Políticas Públicas",

**1. Introduction1**

2011.

### **11. References**

Agrawal ,G.P,(1989)"Nonlinear Fiber Optics", Academic Press, San Diego.


## **Privatization Versus Public Funding on the Atacama Desert Railway – An Interpretation**

Jose Antonio Gonzalez-Pizarro *Universidad Católica del Norte, Antofagasta, Chile* 

### **1. Introduction1**

50 Infrastructure Design, Signalling and Security in Railway

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**11. References** 

Before the arrival of railways at the Atacama desert, there were only paths and tracks inherited by caravans exchanging products – the complimentarity of John Murra's ecological ground – between the Cordillera puna and the Pacific coast. The cart roads of mining prospectors from the time of the manure and copper cycles corresponding to the republican beginnings in the plateau would be added to this pre-Hispanic sequence. But, with the discovery of potassium and silver nitrate in the middle plateau during the 1860s-1870s, the multi-ethnic population settlement of Europeans and Latin Americans could be possible, the Chilean one being the most numerous. Human settlement started on the coast; Tocopilla and Mejillones in the 1840s, preceded by Cobija in 1825; then, Antofagasta in 1866. These were seaports prepared for merchandise shipping and traffic to Bolivia. Further south, that is, from parallel 24, settlement occurred in Taltal in 1858 and Paposo small port in 1865. It was the need of connectivity among the productive mining sites of the desert and communication with Potosi from the coast what made it possible to visualize a more modern and efficient means of transport in terms of capacity, speed, and safety: the railway.

As any history of techniques and means of transport, railways fall within a space and time framework connected to the well-known history of the desert geography: a process marked by landmarks, opportunities, and a long-lasting process, to use French historian Fernand Braudel's categories (Braudel, 1970). In this historic context, the Atacama desert railway is the reflection of various aspects of the social, economic, political, and natural resource history of this territory. But, at the same time, the railway together with the telegraph symbolized the keen desire for progress, science potencial, and Comte's positivistic philosophy for contemporary people, as expressed by engineer Matias Rojas-Delgado, the first Antofagasta Mayor in 1872, that is, that science should lead to the rationality of mining work and railways would open the frontiers of the unknown. "Order and Progress" was a motto that triggered private ventures and set the basis for organizing a new society in this place (Gonzalez-Pizarro, 2002). This changed the image that had been inherited from Spanish chroniclers and the first republican travellers. Science and technology that poured on the desert owing to the changes made to the nitrate leaching system thought of in

<sup>1</sup>This paper is part of Fondecyt Project 1100074 and Nucleo Milenio "Ciencia Regional y Políticas Públicas", 2011.

Privatization Versus Public Funding on the Atacama Desert Railway – An Interpretation 53

The Ceasefire Agreement between Chile and Bolivia in 1866 and 1874 moved the border to parallel 24 S latitude: Chile owned the land to the south and Bolivia to the north, as long as we are interested in noting, without putting emphasis on articles regarding custom's rights or the absence of taxes to Chilean nitrate activity during 25 years. This situation would change as a result of the Pacific War, 1879-1883, in which Chile took over the territory in

The geographic sector for the main railway activity was the one connecting Mejillones-Antofagasta axis to the hinterland, where the main nitrate mines are located (the central or Bolivian canton) with a northeast orientation, that is, the interconnection among Carmen Alto nitrate mine, Salinas station, Caracoles mine – currently located in Sierra Gorda county - and the extension to Calama, where the network was expanded to connect with Bolivia. The beginning of the railway in this area mixes unsuccesful projects, proposals accepted but not implemented, and outlines that became real. In 1872, the French explorer André Bresson (Bresson, 1997: 180) stated that the railway would change a five-day long and deadly journey from the coast to Potosi by a comfortable five-hour one. Exactly so, the Atacama desert, in being dominated by mining techniques and the introduction of the railway became, from a "naturalistic-deterministic" nature under a colonial perspective, a nature

The exploitation of Mejillones manure and Cobija commercial activity stimulated Bolivia to do a public bid to build a railway connecting Cobija and Calama during Jorge Cordoba's administration in 1856. This, along with other projects such as Gibbson's and Arrieta's in September 1863 to build a railway to Mejillones, or Roberto Brown's in August 1868 to build a railway from Cobija to Potosi, were projects discussed in La Paz government, but did not turn out successful. It is important to highlight Avelino Aramayo's project presented in 1861: "Connection of the Pacific Ocean and some point in Bolivia" with Mejillones railway, which would be supported by the government in 1863. Aramayo would get a loan in London by being a partner of Mr. Samuel Morton-Petto-Barnett and Mr. Edward Ladol-Betts, based on a study of the German engineer Hugo Reck, giving Mejillones manure companies as a guarantee. Avelino Aramayo's partners broke in 1871, the Bolivian government keeping its interest in the route starting in Mejillones. So, they made a bid for this purpose in the same year. Twenty-seven projects were put forward, but none of them was successful, including Gustavo Bordes's and partners' and that of José Manuel Brown, Marcial Martinez, and Enrique Meiggs (Bravo, 2000:53-58). According to Gomez-Zubiela, another Aramayo's project had been passed by the government through a resolution passed on May 22, 1872. This fact would be the obstacle for the "famous railway constructors" appearing during Melgarejo's government, Milbourne Clark and Carlos Watson, among them. The suspension of the railway construction in 1874 affected the whole mining and commercial area (Gomez-Zubiela, 1999; Perez, 1997). It was the time of the great Caracoles silver ore deposit discovery in 1870, so that Mejillones railway could connect this small port to this small place and its mines. However, Aramayo's project sponsored by La Paz government became an obstacle for other projects such as the concession requested by Milbourne Clark & Co. on January 14, 1873, for a Mejillones-Caracoles railway, or by Felipe

Iturriche to connect Cobija and Calama in March 1873 (Gonzalez-Pizarro, 2010: 919).

The big British investments in the nitrate industry, along with the Chilean ones, would influence the *de facto* orientation of railway policies. Milbourne Clark & Co., created on March 19, 1869, was funded by Chilean capitals - Jose Santos Ossa, Francisco Puelma,

dispute (Lagos-Carmona, 1981; Gonzalez-Pizarro, 2005).

viewed from a "pragmatic-utilitarian" optics (Gonzalez-Pizarro, 2008).

England by James Shanks and introduced by Santiago Humberstone in the sodium nitrate industry, along with the demand for locomotives and wagons made in Europe, opened a new positivistic reading of the desert (Gonzalez-Pizarro, 2009).

Geography and scientific knowledge influenced the design of railway communication. We must remember that this geographic knowledge, including its maps, has its landmark in the explorations of Rodolfo A. Philippi, a German scientist hired by the Chilean government to travel in the desert from 1853 to 1854. His conclusions contained a certain geographic determinism: "it is extremely difficult, not to say impossible, to build railways or electric telegraphs in the desert… the many ravines, 150 to 200 m deep, that constantly cut through the current road… these ravines would be avoided by a line located further west, but no water would be found in it" (Philippi, 2008: 132). Philippi added that important findings related to mining wealth could change his assumptions. This geographic conditioning of the desert considered the world's most arid remained as a barrier that would demand more accurate topographic studies since it would be affected by the presence of phenomena resulting from the climate, such as *camanchaca*, the *optical illusion* that made man be lost in this huge space. The Chilean government sponsored other studies of the desert, in both the middle plateau, as entrusted to the French geographer Pedro A. Pissis, and along the coast to its Navy Captain, Francisco Vidal-Gormaz in the 1870s, before the war. The increase of geographic knowledge became outstanding in Alejandro Bertrand's (Bertrand, 1885) and Francisco San Román's work in the Atacama Desert Exploration Commission (San Román, 1896). The physical description, mapping, mining potentiality studies, and fundamental toponymy of the desert were Bertrand's and San Roman's main contributions.

Thanks to San Roman's effort, scientific work could show that the Atacama desert nomenclature had narrowed regarding the colonial territory. In his work **Desierto y Cordilleras de Atacama** (1896), he established a close relation between what was understood as the Atacama desert and what was known from the towns and industries established in the plateau:

 "The long stretch of Chilean territory running from the wild valley of Huayco to the nitrate pampas where the Loa river runs, encompassing between both extreme borders in all Chile's width, which extends from the Pacific coast to the Andes crest, is what was properly taken as the *Atacama Desert* until the beginning of this century. This denomination has been more and more restricted to the north as general progress and mining findings were populated or made exploration in this territory accesible, founding towns and creating industries in them. However, as a mere geographic title and, above all, as significant of an arid zone and production exclusively due to the mineral kingdom, traditions and customs still keep that denomination for all the territory that includes two Chilean provinces today, Atacama and Antofagasta" (San Román, 1896: III-IV).

The geographic knowledge and naming of ravines, mountains, and other territory accidents made it possible to conquer the land. Let's say that the Antofagasta-Bolivia Railway Company (A.B.R.C or F.C.A.B, for its acronym in Spanish) was a reference for Santiago Astronomy Observatory until 1910 to localize parallels 23º and 24º south latitude in the Antofagasta province *hinterland*.

The expansion of the Atacama desert railways shows that they were connected to nitrate findings in 1866 and silver in 1870, when the territory was divided in terms of sovereigneity.

England by James Shanks and introduced by Santiago Humberstone in the sodium nitrate industry, along with the demand for locomotives and wagons made in Europe, opened a

Geography and scientific knowledge influenced the design of railway communication. We must remember that this geographic knowledge, including its maps, has its landmark in the explorations of Rodolfo A. Philippi, a German scientist hired by the Chilean government to travel in the desert from 1853 to 1854. His conclusions contained a certain geographic determinism: "it is extremely difficult, not to say impossible, to build railways or electric telegraphs in the desert… the many ravines, 150 to 200 m deep, that constantly cut through the current road… these ravines would be avoided by a line located further west, but no water would be found in it" (Philippi, 2008: 132). Philippi added that important findings related to mining wealth could change his assumptions. This geographic conditioning of the desert considered the world's most arid remained as a barrier that would demand more accurate topographic studies since it would be affected by the presence of phenomena resulting from the climate, such as *camanchaca*, the *optical illusion* that made man be lost in this huge space. The Chilean government sponsored other studies of the desert, in both the middle plateau, as entrusted to the French geographer Pedro A. Pissis, and along the coast to its Navy Captain, Francisco Vidal-Gormaz in the 1870s, before the war. The increase of geographic knowledge became outstanding in Alejandro Bertrand's (Bertrand, 1885) and Francisco San Román's work in the Atacama Desert Exploration Commission (San Román, 1896). The physical description, mapping, mining potentiality studies, and fundamental

toponymy of the desert were Bertrand's and San Roman's main contributions.

established in the plateau:

Antofagasta province *hinterland*.

Atacama and Antofagasta" (San Román, 1896: III-IV).

Thanks to San Roman's effort, scientific work could show that the Atacama desert nomenclature had narrowed regarding the colonial territory. In his work **Desierto y Cordilleras de Atacama** (1896), he established a close relation between what was understood as the Atacama desert and what was known from the towns and industries

 "The long stretch of Chilean territory running from the wild valley of Huayco to the nitrate pampas where the Loa river runs, encompassing between both extreme borders in all Chile's width, which extends from the Pacific coast to the Andes crest, is what was properly taken as the *Atacama Desert* until the beginning of this century. This denomination has been more and more restricted to the north as general progress and mining findings were populated or made exploration in this territory accesible, founding towns and creating industries in them. However, as a mere geographic title and, above all, as significant of an arid zone and production exclusively due to the mineral kingdom, traditions and customs still keep that denomination for all the territory that includes two Chilean provinces today,

The geographic knowledge and naming of ravines, mountains, and other territory accidents made it possible to conquer the land. Let's say that the Antofagasta-Bolivia Railway Company (A.B.R.C or F.C.A.B, for its acronym in Spanish) was a reference for Santiago Astronomy Observatory until 1910 to localize parallels 23º and 24º south latitude in the

The expansion of the Atacama desert railways shows that they were connected to nitrate findings in 1866 and silver in 1870, when the territory was divided in terms of sovereigneity.

new positivistic reading of the desert (Gonzalez-Pizarro, 2009).

The Ceasefire Agreement between Chile and Bolivia in 1866 and 1874 moved the border to parallel 24 S latitude: Chile owned the land to the south and Bolivia to the north, as long as we are interested in noting, without putting emphasis on articles regarding custom's rights or the absence of taxes to Chilean nitrate activity during 25 years. This situation would change as a result of the Pacific War, 1879-1883, in which Chile took over the territory in dispute (Lagos-Carmona, 1981; Gonzalez-Pizarro, 2005).

The geographic sector for the main railway activity was the one connecting Mejillones-Antofagasta axis to the hinterland, where the main nitrate mines are located (the central or Bolivian canton) with a northeast orientation, that is, the interconnection among Carmen Alto nitrate mine, Salinas station, Caracoles mine – currently located in Sierra Gorda county - and the extension to Calama, where the network was expanded to connect with Bolivia.

The beginning of the railway in this area mixes unsuccesful projects, proposals accepted but not implemented, and outlines that became real. In 1872, the French explorer André Bresson (Bresson, 1997: 180) stated that the railway would change a five-day long and deadly journey from the coast to Potosi by a comfortable five-hour one. Exactly so, the Atacama desert, in being dominated by mining techniques and the introduction of the railway became, from a "naturalistic-deterministic" nature under a colonial perspective, a nature viewed from a "pragmatic-utilitarian" optics (Gonzalez-Pizarro, 2008).

The exploitation of Mejillones manure and Cobija commercial activity stimulated Bolivia to do a public bid to build a railway connecting Cobija and Calama during Jorge Cordoba's administration in 1856. This, along with other projects such as Gibbson's and Arrieta's in September 1863 to build a railway to Mejillones, or Roberto Brown's in August 1868 to build a railway from Cobija to Potosi, were projects discussed in La Paz government, but did not turn out successful. It is important to highlight Avelino Aramayo's project presented in 1861: "Connection of the Pacific Ocean and some point in Bolivia" with Mejillones railway, which would be supported by the government in 1863. Aramayo would get a loan in London by being a partner of Mr. Samuel Morton-Petto-Barnett and Mr. Edward Ladol-Betts, based on a study of the German engineer Hugo Reck, giving Mejillones manure companies as a guarantee. Avelino Aramayo's partners broke in 1871, the Bolivian government keeping its interest in the route starting in Mejillones. So, they made a bid for this purpose in the same year. Twenty-seven projects were put forward, but none of them was successful, including Gustavo Bordes's and partners' and that of José Manuel Brown, Marcial Martinez, and Enrique Meiggs (Bravo, 2000:53-58). According to Gomez-Zubiela, another Aramayo's project had been passed by the government through a resolution passed on May 22, 1872. This fact would be the obstacle for the "famous railway constructors" appearing during Melgarejo's government, Milbourne Clark and Carlos Watson, among them. The suspension of the railway construction in 1874 affected the whole mining and commercial area (Gomez-Zubiela, 1999; Perez, 1997). It was the time of the great Caracoles silver ore deposit discovery in 1870, so that Mejillones railway could connect this small port to this small place and its mines. However, Aramayo's project sponsored by La Paz government became an obstacle for other projects such as the concession requested by Milbourne Clark & Co. on January 14, 1873, for a Mejillones-Caracoles railway, or by Felipe Iturriche to connect Cobija and Calama in March 1873 (Gonzalez-Pizarro, 2010: 919).

The big British investments in the nitrate industry, along with the Chilean ones, would influence the *de facto* orientation of railway policies. Milbourne Clark & Co., created on March 19, 1869, was funded by Chilean capitals - Jose Santos Ossa, Francisco Puelma,

Privatization Versus Public Funding on the Atacama Desert Railway – An Interpretation 55

Bolivian city, together with tin exploitation. It was even stated that civilization was measured in railway kilometers (Mendieta-Parada, 2006: 211). Liberalism years in Bolivia had led to a huge influence of British capitals on the railway network and the connection of the railway with the Pacific Ocean, where "Playa Blanca Metallurgical Installations" was located, connected to Huanchaca Co. built between 1888 and 1892 and in operation until 1902 (Ahumada, 1999; Mitre, 1981; Calderon, 2003). The disappearance of Huanchaca Co. let Antofagasta-Oruro railway under the administration of only the A.B.R.C. in 1903. It is important to note that the arrival of the railway at Calama influenced work usually done by mule packs and alfalfa pasture grounds

The prowess of extending the railway from Antofagasta to Bolivia is also shown in the

**Km from Altitude RailwayBranches Antofagasta Stations** 

35 561 O'HigginsOf.Savona,Pissis y

117 1,231 El BuitreOf.Sgto.Aldea.

133 1,369 PeinetaOf.Ausonia, Cecilia 136 1,383 CentralOf.A.Edwards.

148 1,431 PlacillaOf.María, Curicó

162 1,534 La NoriaOf.Aconcagua

435 3,696 OllagüeA Collahuasi

144 1,414 UniónOf.Anita,Candelaria,Luisis

154 1,470 SolitarioOf.Filomena, Perseverancia

238 2,265 CalamaA Chuquicamata y El Abra

170 1,623 Sierra Gorda Arranque para Caracoles

21 408 La NegraArranque hacia cantón A. Blancas

96 1,014 BaquedanoOf.Ercilla,Astoreca,J.F.Vergara

122 1,285 Carmen Alto Of.F.Puelma,Condell, Celia 128 1,341 Salinas Of.Lastenia,Aurelia,Carmela

Blanco Encalada.

Angamos, Araucana.

Domeyko Arranque hacia Boquete.

dedicated to cart transport in the nitrate pampa (Nuñez, 1992).

various railway stations that had to be built along its way:

0 34 Antofagasta 4 60 Playa Blanca 14 295 Sgto.Aldea

29 554 Portezuelo

48 573 Uribe 59 682 Prat 70 783 Latorre 83 893 Cuevitas

109 1,164 Cerrillos

120 1,279 Santa Rosa

179 1,727 Cochrane 205 2,142 Cerritos Bayos

269 2,641 Cere 299 3,015 Conchi 312 3,223 San Pedro 340 3,772 Polapi 360 3,955 Ascotán 387 3,729 Cebollar 412 3,692 San Martín

Agustin Edwards - and British investments - Milbourne Clark, George Laborer, and Casa Gibbs from Valparaíso. The official negation to Milbourne Clark & Co. did not prevent it from continuing with its railway project, changing its beginning from Antofagasta to its hinterland. Under the name "Nitrate Company and Antofagasta Railway" established in October 1872, its railway arrives at Salar del Carmen on December 1, 1873; Salinas in 1877; Pampa Central in 1881; and Pampa Alta in 1883. At this time, it was estimated that the railway construction from Antofagasta, the establishment of the big nitrate treatment plant in this port, and manure exhaustion would result in the abandonment of the Mejillones railway (Mandiola & Castillo, 1894: 3vta). The consequences of the Mejillones-Caracoles railway failure affected its workers negatively due to the high transport costs resulting from operations with the Antofagasta railway company (Bravo, 2000). For Bowman, the future of the Antofagasta port was determined by the railway construction (Bowman, 1924: 81).

### **2. The appearance of the Atacama desert railway giant: The Antofagasta and Bolivia Railway Company Ltd.**

The thriving nitrate activity in the Antofagasta province was slowed down at the south of parallel 24º after the war because of the government tax legislation that favored Tarapaca and affected the economic activities of the zone (Gonzalez-Pizarro, 2009a). At that time, the ideology of political liberalism prevailed in Chile, thus being reflected in economic policies, which would influence concessions to foreign companies.

At the beginning of the 1870s, Huanchaca Company had been established in Bolivia with the participation of Chilean investors, Melchor Concha y Toro, among others and Bolivians such as Aniceto Arce, all of them interested in the exploitation of silver from Pulacayo and Huanchaca. The ceasefire between Chile and Bolivia in 1884 again brought under discussion the mining production export from Huanchaca via Calama to Antofagasta port. Economic interests, mainly in mining, became powerful in outlining new railways.

Blakemore suggests that at the beginning of 1887, the Nitrate Co. and Antofagasta Railway had sold its railway and other rights to Huanchaca Company (Blakemore, 1996: 49). Nevertheless, the first Antofagasta Railway Co. Report shows 1886 as the exact date and gives details about the contribution to the merger between Nitrate Co. and Huanchaca Co., more particularly regarding the amount corresponding to the railway: 2,600,000 pesos distributed in: Permanent Rails: 1,600,000 pesos; Rolling Stock: 740,000 pesos, Antofagasta Machine Shop: 150,000 pesos; Dock: 50,000 pesos; and Antofagasta Real Estate: 60,000 pesos, according to Gomez-Zubiela.

 The merger between Antofagasta Nitrate Co. and Huanchaca Co. gave rise to the most important and trascendental railway company of the Atacama desert on November 28, 1888: *The Antofagasta and Bolivia Railway Company Ltd.* (A.B.R.C), legalized by the Chilean government on April 2, 1889 and the Bolivian Congress on December 8, 1888. The demands of the preandean topography made engineering work essential in order to overcome natural barriers. This was done by the English engineer Josiah Harding who, between 1883 and 1887, lay the rails from Pampa Alta to Ascotan lake, the bridge reaching 3,956 m.a.s.l. It was November 1883. The famous Conchi duct was in operation until 1918, when a similar one was built (Greve, 1944: 507). The newly established town of Uyuni in Bolivia received the first engine from the brand new company on October 30, 1889. The railway extension from Antofagasta to Oruro on May 15, 1892, under Arce's government, also stimulated the modernizing boom process of the

Agustin Edwards - and British investments - Milbourne Clark, George Laborer, and Casa Gibbs from Valparaíso. The official negation to Milbourne Clark & Co. did not prevent it from continuing with its railway project, changing its beginning from Antofagasta to its hinterland. Under the name "Nitrate Company and Antofagasta Railway" established in October 1872, its railway arrives at Salar del Carmen on December 1, 1873; Salinas in 1877; Pampa Central in 1881; and Pampa Alta in 1883. At this time, it was estimated that the railway construction from Antofagasta, the establishment of the big nitrate treatment plant in this port, and manure exhaustion would result in the abandonment of the Mejillones railway (Mandiola & Castillo, 1894: 3vta). The consequences of the Mejillones-Caracoles railway failure affected its workers negatively due to the high transport costs resulting from operations with the Antofagasta railway company (Bravo, 2000). For Bowman, the future of the Antofagasta port was determined by the railway construction (Bowman, 1924: 81).

**2. The appearance of the Atacama desert railway giant: The Antofagasta and** 

The thriving nitrate activity in the Antofagasta province was slowed down at the south of parallel 24º after the war because of the government tax legislation that favored Tarapaca and affected the economic activities of the zone (Gonzalez-Pizarro, 2009a). At that time, the ideology of political liberalism prevailed in Chile, thus being reflected in economic policies,

At the beginning of the 1870s, Huanchaca Company had been established in Bolivia with the participation of Chilean investors, Melchor Concha y Toro, among others and Bolivians such as Aniceto Arce, all of them interested in the exploitation of silver from Pulacayo and Huanchaca. The ceasefire between Chile and Bolivia in 1884 again brought under discussion the mining production export from Huanchaca via Calama to Antofagasta port. Economic

Blakemore suggests that at the beginning of 1887, the Nitrate Co. and Antofagasta Railway had sold its railway and other rights to Huanchaca Company (Blakemore, 1996: 49). Nevertheless, the first Antofagasta Railway Co. Report shows 1886 as the exact date and gives details about the contribution to the merger between Nitrate Co. and Huanchaca Co., more particularly regarding the amount corresponding to the railway: 2,600,000 pesos distributed in: Permanent Rails: 1,600,000 pesos; Rolling Stock: 740,000 pesos, Antofagasta Machine Shop: 150,000 pesos; Dock: 50,000 pesos; and Antofagasta Real Estate: 60,000 pesos,

 The merger between Antofagasta Nitrate Co. and Huanchaca Co. gave rise to the most important and trascendental railway company of the Atacama desert on November 28, 1888: *The Antofagasta and Bolivia Railway Company Ltd.* (A.B.R.C), legalized by the Chilean government on April 2, 1889 and the Bolivian Congress on December 8, 1888. The demands of the preandean topography made engineering work essential in order to overcome natural barriers. This was done by the English engineer Josiah Harding who, between 1883 and 1887, lay the rails from Pampa Alta to Ascotan lake, the bridge reaching 3,956 m.a.s.l. It was November 1883. The famous Conchi duct was in operation until 1918, when a similar one was built (Greve, 1944: 507). The newly established town of Uyuni in Bolivia received the first engine from the brand new company on October 30, 1889. The railway extension from Antofagasta to Oruro on May 15, 1892, under Arce's government, also stimulated the modernizing boom process of the

**Bolivia Railway Company Ltd.** 

according to Gomez-Zubiela.

which would influence concessions to foreign companies.

interests, mainly in mining, became powerful in outlining new railways.

Bolivian city, together with tin exploitation. It was even stated that civilization was measured in railway kilometers (Mendieta-Parada, 2006: 211). Liberalism years in Bolivia had led to a huge influence of British capitals on the railway network and the connection of the railway with the Pacific Ocean, where "Playa Blanca Metallurgical Installations" was located, connected to Huanchaca Co. built between 1888 and 1892 and in operation until 1902 (Ahumada, 1999; Mitre, 1981; Calderon, 2003). The disappearance of Huanchaca Co. let Antofagasta-Oruro railway under the administration of only the A.B.R.C. in 1903. It is important to note that the arrival of the railway at Calama influenced work usually done by mule packs and alfalfa pasture grounds dedicated to cart transport in the nitrate pampa (Nuñez, 1992).

The prowess of extending the railway from Antofagasta to Bolivia is also shown in the various railway stations that had to be built along its way:


Privatization Versus Public Funding on the Atacama Desert Railway – An Interpretation 57

Huanchaca Co. had purchased the water rights owned by Enrique Villegas, an entrepreneur and regional politician, in 1887. For this reason, when Huanchaca Co. transferred its rights to *The Antofagasta and Bolivia Railway Co. Ltd.*, it was not only connected to railway materials, but also to its water rights. In addition, a law passed on January 21, 1888, allowed Huanchaca Co. to "provide the city of Antofagasta and other territories that can be supplied by the Loa River with tap water" (Anguita, 1912: 64-65). Also, Huanchaca could extend the time to do the necessary work for supplying Antofagasta with water. By a law passed on September 23, 1890, the deadline was extended until October 1, 1892. But it was not known that Huanchaca had become *The Antofagasta and Bolivia Railway Co. Ltd* in 1889. In this way, a situation similar to Tarapaca, concerning John T. North's activities, arose during Balmaceda's government, that is, the direct or indirect monopoly of natural resources, nitrate and water, railway control, or what historian Hernan Ramírez-Necochea would call, the danger of "northification" (Ramirez, 2007: 81). When travelling to Antofagasta in March 1889, Balmaceda visited some railway stations of the central network and promised "the expropriation of all private railways in the whole Republic" (Sagredo, 2001: 144), something probably expressed at the warmth of welcome in every northern City Hall, but these ideas, as many others, did not come true (Blakemore, 1991).

A.B.R.C. tap water supply included industries, nitrate mines at special prices, and the cities of Antofagasta and Calama, among others. The water price and mainly free supply to public services were the focus of a permanent struggle between the company and the Antofagasta City Hall. By a decree on July 30, 1904, the company could "use and enjoy Palpana waters and then obtained the concession of Ujuna Grande, Puquios , and Siloli waters" (Arce: 1930: 263). In addition, it established a policy to fight for free water resources in favor of Antofagasta public services and City Hall (Blakemore, 1996: 104). Antofagasta water supply was criticized because of the tariff charged for houses and the government negation for allowing the company to increase tariffs (Recabarren, 2002). This was a recurrent issue until the late 1960s. The basic issue for Calama City Hall was the discrepancy between real estate and the valuation established by A.B.R.C and the amount of tax to pay, an issue analyzed from 1915 to 1936 since it strongly affected the City Hall budget ( Mondaca, Segovia & Sanchez, 2011). For mining activity, the basic issues were the railway breach with the liabilities agreed on with nitrate companies, particularly Antofagasta Nitrate Co., the most important Chilean company in this line of business until 1907. Among complaints detailed by Isaac Arce, Pampa Alta administrator, in 1906 are: the towing machine service because its itinerary affected work; the negation to transport workers; the demand for loading wagons in the least possible time; the prohibition to use own cars in the railway; the transport of rails and crossbeams by the nitrate company; placing switches and habilitating by-ways; storage and wagon charges for transporting forage; and excess charges for transporting merchandise,

The placement of nitrate company rails in the central canton, which finally reached the railway, was hindered by the broad concession given to Milbourne Clark. Nevertheless, since 1887 attempts had been made to build railways independent of A.B.R.C , such as the one between Pampa Alta and San Pedro de Atacama in December 1887. In October 1893, Carlos A. Watters is allowed to build a railway, taking kilometer 20 of the current A.B.R.C. as a starting point. In August 1899, Enrique Barra made a request to build a steam engine railway from Chuquicamata copper mine to Antofagasta-Bolivia railway, being approved in

materials, coal, and gunpowder (Archivo, 1906).

December (Gonzalez-Pizarro, 2008).

Altitudes referring to railway stations close to the Chile-Bolivia border demanded hiring qualified manpower that attracted Bolivian immigration (Gonzalez-Pizarro, 2008a).

The railway hired many technical and non-technical workers and was not far from the problems between capital and work, proper of political liberalism and the so-called local "social matter". As Blakemore states, A.B.R.C. hired manpower, clearly distinguishing the laborer segment (heads of gang, boatmen, port loaders, firemen, trackwalkers, and service personnel) from employees, who enjoyed a higher social status (railway station chiefs, foremen, inspectors and office personnel) (Blakemore, 1996: 155).

Some specific facts hurt the company's reputation in the regional community. Indeed, there was criticism regarding its operations because wagons used to run off the rails and put workers' safety in risk due to lack of personnel or victimization affecting men who built Pampa Alta railway station telegraph line, as dennounced by the local newspaper *La Mañana* on October 1, 1902. Although the railway company contributed to the city with the creation of a Fire Department, "Bomba Ferrocarril", in September 1902, its expansion in the province, such as the petition of land in Mejillones at the end of 1903, was criticized in the National Congress. However, when the government asked engineer Emilio de Vidts to study Mejillones opening in 1905, A.B.R.C. started its greatest investment: The construction of Mejillones machine shop, considered South America's greatest one, with a 300-house camp (Panades, 1990)

The most complex social situation affecting *The Antofagasta and Bolivia Railway Co. Ltd* was the rejection to the petitionary on January 29, 1906, through which the so-called "Mancomunal Obrera de Antofagasta" representing the laborers of the main companies in the city, including the railway, requested one hour and a half for lunch. This request was accepted by all companies, except the English A.B.C.R. administration. The boatmen and Orchard Industry and Smelter workers supported the railway laborers. The strike committee called for a meeting on Febrary 6; while the government sent naval forces and the A.B.R.C administration provided foreigners with guns. Bishop Luis Silva-Lezaeta's eclesiastic mediation was not accepted by the company. The strike ended in a laborers' massacre in Colon Square on February 6, 1906. Two days after, under the pressure of the news, the National Congress passed the first social law: the law of housing for laborers (Gonzalez-Pizarro, 2009b)

The importance of A.B.R.C. in the zone was enormous, particularly when the Peace and Friendship Treaty between Bolivia and Chile was signed in 1904. On the one hand, the treaty stated that the Atacama desert, which was part of the Antofagasta province, would belong to Chile and, on the other hand, Chile would have to build a railway to connect Arica and La Paz, along with allowing free transport from the altiplanic country to Pacific ports. The Antofagasta-Oruro railway perfectly met the requirements stated in the treaty. If, for Bolivia, *The Antofagasta and Bolivia Railway Co. Ltd.* was so important due to railway policy control, obtaining advantages for mineral exports and mechandise imports (Aramayo, 1959; Gómez Zubiela, 1999, Informe, 1959), what was observed in Antofagasta regional economy was as important. Three issues were controversial for Antofagasta and Calama City Halls and mining companies: water supply and its cost for consumers, real estate valuation, and the price for transporting cargo and passengers.

Water supply in the desert was essential for productive activities and also for the feasibility of the railway company since it used steam engines. The problem was the monopoly concerning water rights and its distribution to the urban cities and insdustries in the nitrate pampa.

Altitudes referring to railway stations close to the Chile-Bolivia border demanded hiring

The railway hired many technical and non-technical workers and was not far from the problems between capital and work, proper of political liberalism and the so-called local "social matter". As Blakemore states, A.B.R.C. hired manpower, clearly distinguishing the laborer segment (heads of gang, boatmen, port loaders, firemen, trackwalkers, and service personnel) from employees, who enjoyed a higher social status (railway station chiefs,

Some specific facts hurt the company's reputation in the regional community. Indeed, there was criticism regarding its operations because wagons used to run off the rails and put workers' safety in risk due to lack of personnel or victimization affecting men who built Pampa Alta railway station telegraph line, as dennounced by the local newspaper *La Mañana* on October 1, 1902. Although the railway company contributed to the city with the creation of a Fire Department, "Bomba Ferrocarril", in September 1902, its expansion in the province, such as the petition of land in Mejillones at the end of 1903, was criticized in the National Congress. However, when the government asked engineer Emilio de Vidts to study Mejillones opening in 1905, A.B.R.C. started its greatest investment: The construction of Mejillones machine shop,

The most complex social situation affecting *The Antofagasta and Bolivia Railway Co. Ltd* was the rejection to the petitionary on January 29, 1906, through which the so-called "Mancomunal Obrera de Antofagasta" representing the laborers of the main companies in the city, including the railway, requested one hour and a half for lunch. This request was accepted by all companies, except the English A.B.C.R. administration. The boatmen and Orchard Industry and Smelter workers supported the railway laborers. The strike committee called for a meeting on Febrary 6; while the government sent naval forces and the A.B.R.C administration provided foreigners with guns. Bishop Luis Silva-Lezaeta's eclesiastic mediation was not accepted by the company. The strike ended in a laborers' massacre in Colon Square on February 6, 1906. Two days after, under the pressure of the news, the National Congress passed the first social

The importance of A.B.R.C. in the zone was enormous, particularly when the Peace and Friendship Treaty between Bolivia and Chile was signed in 1904. On the one hand, the treaty stated that the Atacama desert, which was part of the Antofagasta province, would belong to Chile and, on the other hand, Chile would have to build a railway to connect Arica and La Paz, along with allowing free transport from the altiplanic country to Pacific ports. The Antofagasta-Oruro railway perfectly met the requirements stated in the treaty. If, for Bolivia, *The Antofagasta and Bolivia Railway Co. Ltd.* was so important due to railway policy control, obtaining advantages for mineral exports and mechandise imports (Aramayo, 1959; Gómez Zubiela, 1999, Informe, 1959), what was observed in Antofagasta regional economy was as important. Three issues were controversial for Antofagasta and Calama City Halls and mining companies: water supply and its cost for consumers, real estate valuation, and

Water supply in the desert was essential for productive activities and also for the feasibility of the railway company since it used steam engines. The problem was the monopoly concerning water rights and its distribution to the urban cities and insdustries in the nitrate pampa.

qualified manpower that attracted Bolivian immigration (Gonzalez-Pizarro, 2008a).

considered South America's greatest one, with a 300-house camp (Panades, 1990)

foremen, inspectors and office personnel) (Blakemore, 1996: 155).

law: the law of housing for laborers (Gonzalez-Pizarro, 2009b)

the price for transporting cargo and passengers.

Huanchaca Co. had purchased the water rights owned by Enrique Villegas, an entrepreneur and regional politician, in 1887. For this reason, when Huanchaca Co. transferred its rights to *The Antofagasta and Bolivia Railway Co. Ltd.*, it was not only connected to railway materials, but also to its water rights. In addition, a law passed on January 21, 1888, allowed Huanchaca Co. to "provide the city of Antofagasta and other territories that can be supplied by the Loa River with tap water" (Anguita, 1912: 64-65). Also, Huanchaca could extend the time to do the necessary work for supplying Antofagasta with water. By a law passed on September 23, 1890, the deadline was extended until October 1, 1892. But it was not known that Huanchaca had become *The Antofagasta and Bolivia Railway Co. Ltd* in 1889. In this way, a situation similar to Tarapaca, concerning John T. North's activities, arose during Balmaceda's government, that is, the direct or indirect monopoly of natural resources, nitrate and water, railway control, or what historian Hernan Ramírez-Necochea would call, the danger of "northification" (Ramirez, 2007: 81). When travelling to Antofagasta in March 1889, Balmaceda visited some railway stations of the central network and promised "the expropriation of all private railways in the whole Republic" (Sagredo, 2001: 144), something probably expressed at the warmth of welcome in every northern City Hall, but these ideas, as many others, did not come true (Blakemore, 1991).

A.B.R.C. tap water supply included industries, nitrate mines at special prices, and the cities of Antofagasta and Calama, among others. The water price and mainly free supply to public services were the focus of a permanent struggle between the company and the Antofagasta City Hall. By a decree on July 30, 1904, the company could "use and enjoy Palpana waters and then obtained the concession of Ujuna Grande, Puquios , and Siloli waters" (Arce: 1930: 263). In addition, it established a policy to fight for free water resources in favor of Antofagasta public services and City Hall (Blakemore, 1996: 104). Antofagasta water supply was criticized because of the tariff charged for houses and the government negation for allowing the company to increase tariffs (Recabarren, 2002). This was a recurrent issue until the late 1960s.

The basic issue for Calama City Hall was the discrepancy between real estate and the valuation established by A.B.R.C and the amount of tax to pay, an issue analyzed from 1915 to 1936 since it strongly affected the City Hall budget ( Mondaca, Segovia & Sanchez, 2011).

For mining activity, the basic issues were the railway breach with the liabilities agreed on with nitrate companies, particularly Antofagasta Nitrate Co., the most important Chilean company in this line of business until 1907. Among complaints detailed by Isaac Arce, Pampa Alta administrator, in 1906 are: the towing machine service because its itinerary affected work; the negation to transport workers; the demand for loading wagons in the least possible time; the prohibition to use own cars in the railway; the transport of rails and crossbeams by the nitrate company; placing switches and habilitating by-ways; storage and wagon charges for transporting forage; and excess charges for transporting merchandise, materials, coal, and gunpowder (Archivo, 1906).

The placement of nitrate company rails in the central canton, which finally reached the railway, was hindered by the broad concession given to Milbourne Clark. Nevertheless, since 1887 attempts had been made to build railways independent of A.B.R.C , such as the one between Pampa Alta and San Pedro de Atacama in December 1887. In October 1893, Carlos A. Watters is allowed to build a railway, taking kilometer 20 of the current A.B.R.C. as a starting point. In August 1899, Enrique Barra made a request to build a steam engine railway from Chuquicamata copper mine to Antofagasta-Bolivia railway, being approved in December (Gonzalez-Pizarro, 2008).

Privatization Versus Public Funding on the Atacama Desert Railway – An Interpretation 59

Changes made in May 1931 did not greatly affect schedules in the nitrate mines, but they highlighted the importance of Salinas railway station for mixed trains, both regular and

So, on Monday, the regular mixed train went up to Salinas at 1:15 p.m. and down to the same railway station at 11:15 a.m., following the usual itinerary; on Tuesday, the regular mixed train did not go up, but went down to the station at 11: 15 a.m.; while the international train went up at 1: 15 a.m., making connections between Salinas and Union stations; on Wednesday, the regular mixed train went up at 1:15 p.m. and did not go down, following the usual itinerary; the mixed train from Calama went down on this day and the international train went down, arriving at 6:20 p.m., making the connection above. On Thursday, there were no trains going up and down. On Friday, the regular mixed train did not go up, but 11:15-a.m. train went down, following the usual itinerary; the international train made a stop at Salinas at 11:15 a.m., making the usual connection. On Saturday, the regular mixed train went up at 1:15 p.m. and did not go down; the international train passed by Salinas at 6:20 p.m. On Sunday, only the regular mixed train ran, making a stop at Salinas at 1:15 p.m., when going up, and at 11:15 a.m., when going

International train trips from Antofagasta to Bolivia underwent difficulties when making a stop at Salinas station. Complaints included passengers' delay and change of second-class wagons from the mixed train arriving from Calama to add them to the international train. An service of "auto-gondolas" (small old buses) with a capacity of about 25 passengers from "María Elena" and "Chacabuco" nitrate mines was the only means for arriving at Salinas

The American administrators of Chuquicamata copper ore deposit signed an agreement with A.B.R.C. to use the railway for exporting the metal resource to international markets. The Chuquicamata train inaugurated in 1914 was connected to the main A.B.R.C. branch. The so-called Chuquicamata branch started from San Salvador station located to the north of Calama and arrived at Punta de Rieles, in a 10-km trip. In addition, A.B.R.C. built Conchi Viejo- El Abra branch in 1906 with a 19-km length to give service to the copper and silver exploitations existing to the north of Calama (Thomson-Angerstein, 1997; Castro 1984). The company profits depended on production levels which, in turn, depended on the copper pound quotation in the London stockmarket. However, *Chile Exploration Company,* the American company exploiting Chuquicamata mine, established *The Chile Exploration Co. Railway* to connect Chuquicamata and San Salvador, providing electricity in 1925. The first Chuquicamata general manager, Fred Hellman, built a railway inside the mine to transport materials and workers. It remained active until the appearance of big trucks in the early

In the 1970s, *The Antofagasta and Bolivia Railway Co.Ltd.* was involved in the difficulties affecting the Chilean politics and economics, until purchased by the Chilean entrepreneur with Croatian ancestors, Andronico Luksic, at the end of 1979 (Blakemore, 1996). In the 1980s, the frequency of the international train was once a week. At present, its acivities focus on commerce to and from Bolivia, along with CODELCO copper

special, and also the internacional train.

down (Archivo Historico, 1929).

1950s ( Monterrey, 2009).

shipping.

station.

In general, the nitrate companies of the central canton had to operate with A.B.R.C. to export their production through Antofagasta port. Nitrate companies usually had private trains inside their premises, between nitrate concessions and supply yards, using locomotives and wagons. One of the most important companies, the Antofagasta Nitrate Co., was equipped with 41 80-250 h.p. steam engines; 8 90-150 h.p. electric engines; 250 6m3 nitrate wagons; and 540 1-2 m3 nitrate wagons, apart form 470 other wagons, all of which shows a panorama of the thriving activity in the desert (Gonzalez-Pizarro, 2003: 135).

The expansion of American capital, mainly Guggenheim Brothers', not only in Chuquicamata connected to Huanchaca Co. from 1899 until its shut-down -, but also in the powerful nitrate industry, when purchasing *Anglo-Chilean Nitrate Company* and *Lautaro Nitrate Company* in the 1920s and 1930s, led to a better planning between A.B.R.C. and the railway stations in the pampa and nitrate mines. Schedules allowed identifying railway stations and the type of railway machinery in use. In 1929, A.B.R.C. took charge of all the nitrate railways, committing to the conservation and repair of the existing ones. The railways became A.B.R.C. property and nitrate companies agreed on a monthly pay for each crossing and meters run.

A.B.R:C. and Chile North Railway established a new train service in 1929 (Thompson, 2003). Two mixed trains weekly covered the distance between Baquedano and El Toco and viceversa so as to give better service to nitrate mine inhabitants. The trains stopped in Baquedano to make connections with passenger trains travelling between Mejillones and Calama. In this way, passengers could arrive at Antofagasta at 3 p.m. In addition, passengers travelling to Baquedano sorroundings could make different combinations to move throughout the pampa and railway stations until arriving at Calama since a direct train to this city was available.

In the mid-1931, A.B.R.C changed the train schedule to Calama, affecting the itinerary of the train running downward, which was scheduled for Wednesday, Thursday, and Saturday. This made *Lautaro Nitrate* organize its own transport service for mail and workers' transport.

To have an impression of the railway service and how it connected different places in the nitrate pampa, let's take a look at the schedule in 1929:


In general, the nitrate companies of the central canton had to operate with A.B.R.C. to export their production through Antofagasta port. Nitrate companies usually had private trains inside their premises, between nitrate concessions and supply yards, using locomotives and wagons. One of the most important companies, the Antofagasta Nitrate Co., was equipped with 41 80-250 h.p. steam engines; 8 90-150 h.p. electric engines; 250 6m3 nitrate wagons; and 540 1-2 m3 nitrate wagons, apart form 470 other wagons, all of which shows a panorama of

The expansion of American capital, mainly Guggenheim Brothers', not only in Chuquicamata connected to Huanchaca Co. from 1899 until its shut-down -, but also in the powerful nitrate industry, when purchasing *Anglo-Chilean Nitrate Company* and *Lautaro Nitrate Company* in the 1920s and 1930s, led to a better planning between A.B.R.C. and the railway stations in the pampa and nitrate mines. Schedules allowed identifying railway stations and the type of railway machinery in use. In 1929, A.B.R.C. took charge of all the nitrate railways, committing to the conservation and repair of the existing ones. The railways became A.B.R.C. property and

A.B.R:C. and Chile North Railway established a new train service in 1929 (Thompson, 2003). Two mixed trains weekly covered the distance between Baquedano and El Toco and viceversa so as to give better service to nitrate mine inhabitants. The trains stopped in Baquedano to make connections with passenger trains travelling between Mejillones and Calama. In this way, passengers could arrive at Antofagasta at 3 p.m. In addition, passengers travelling to Baquedano sorroundings could make different combinations to move throughout the pampa and railway stations until arriving at Calama since a direct train to this city was available.

In the mid-1931, A.B.R.C changed the train schedule to Calama, affecting the itinerary of the train running downward, which was scheduled for Wednesday, Thursday, and Saturday. This made *Lautaro Nitrate* organize its own transport service for mail and workers' transport. To have an impression of the railway service and how it connected different places in the

UPWARD TRIP DOWNWARD

Baquedano ---- 13:45 Toco ---- 7:00 La Rioja 15:01 15:05 Chacance 8:02 8:07 Deseada 16:01 16:20 Miraje 8:26 8:31

Lynch 17:18 17:32 Lynch 9:35 9:36

Toco 20:12 --- Baquedano 12:05 ---- Antofagasta 15:04 ----

Los Dones 18:02 18:05 Los Dones 9:48 9:56 Miraje 18:29 18:40 Deseada 10:15 10:20

Arrival Departure Arrival Departure

Sunday & Thursday Monday & Friday

Railway stations Train 83 Railway

Chacance 18:57 19:10 La Rioja 11:10

Los Dones 16:43 17:00 B. Astoreca y

TRIP

Stations Train 84

Los Dones 8:59 9:01

the thriving activity in the desert (Gonzalez-Pizarro, 2003: 135).

nitrate pampa, let's take a look at the schedule in 1929:

Antofagasta ---- 9:35

B. Astoreca y

nitrate companies agreed on a monthly pay for each crossing and meters run.

Changes made in May 1931 did not greatly affect schedules in the nitrate mines, but they highlighted the importance of Salinas railway station for mixed trains, both regular and special, and also the internacional train.

So, on Monday, the regular mixed train went up to Salinas at 1:15 p.m. and down to the same railway station at 11:15 a.m., following the usual itinerary; on Tuesday, the regular mixed train did not go up, but went down to the station at 11: 15 a.m.; while the international train went up at 1: 15 a.m., making connections between Salinas and Union stations; on Wednesday, the regular mixed train went up at 1:15 p.m. and did not go down, following the usual itinerary; the mixed train from Calama went down on this day and the international train went down, arriving at 6:20 p.m., making the connection above. On Thursday, there were no trains going up and down. On Friday, the regular mixed train did not go up, but 11:15-a.m. train went down, following the usual itinerary; the international train made a stop at Salinas at 11:15 a.m., making the usual connection. On Saturday, the regular mixed train went up at 1:15 p.m. and did not go down; the international train passed by Salinas at 6:20 p.m. On Sunday, only the regular mixed train ran, making a stop at Salinas at 1:15 p.m., when going up, and at 11:15 a.m., when going down (Archivo Historico, 1929).

International train trips from Antofagasta to Bolivia underwent difficulties when making a stop at Salinas station. Complaints included passengers' delay and change of second-class wagons from the mixed train arriving from Calama to add them to the international train. An service of "auto-gondolas" (small old buses) with a capacity of about 25 passengers from "María Elena" and "Chacabuco" nitrate mines was the only means for arriving at Salinas station.

The American administrators of Chuquicamata copper ore deposit signed an agreement with A.B.R.C. to use the railway for exporting the metal resource to international markets. The Chuquicamata train inaugurated in 1914 was connected to the main A.B.R.C. branch. The so-called Chuquicamata branch started from San Salvador station located to the north of Calama and arrived at Punta de Rieles, in a 10-km trip. In addition, A.B.R.C. built Conchi Viejo- El Abra branch in 1906 with a 19-km length to give service to the copper and silver exploitations existing to the north of Calama (Thomson-Angerstein, 1997; Castro 1984). The company profits depended on production levels which, in turn, depended on the copper pound quotation in the London stockmarket. However, *Chile Exploration Company,* the American company exploiting Chuquicamata mine, established *The Chile Exploration Co. Railway* to connect Chuquicamata and San Salvador, providing electricity in 1925. The first Chuquicamata general manager, Fred Hellman, built a railway inside the mine to transport materials and workers. It remained active until the appearance of big trucks in the early 1950s ( Monterrey, 2009).

In the 1970s, *The Antofagasta and Bolivia Railway Co.Ltd.* was involved in the difficulties affecting the Chilean politics and economics, until purchased by the Chilean entrepreneur with Croatian ancestors, Andronico Luksic, at the end of 1979 (Blakemore, 1996). In the 1980s, the frequency of the international train was once a week. At present, its acivities focus on commerce to and from Bolivia, along with CODELCO copper shipping.

Privatization Versus Public Funding on the Atacama Desert Railway – An Interpretation 61

Coloso-Aguas Blancas railway history is one of the most intricate of the type. Since 1880, nitrate people had been asking the government the construction of a railway for Aguas Blancas nitrate mines and were fighting for an extension of what had been accepted for Juan Besterrica, Juan Vera, and Francisco Mirada to build the rails for a steam train between Antofagasta and Aguas Blancas (Rojas, 1883). In January 1884, the Congress discussed a railway from Antofagasta to Aguas Blancas since the previous one had been rejected. In 1896, Rafael Barazarte was given permission to build a railway between Paposo and Desierto ore deposit. In 1886, Arturo Prat Mining Co. and Taltal Railway Co. received the approval to build a railway between the port and the company's mining installations. On the next year, they were allowed to extend the railway to Cachinal. This issue was again dealt with in August 1889 by J. Phillips in order to build a steam railway between these two places. On September 1, 1897, approval was given to Jose Antonio Moreno to build and exploit a railway between Paposo and Desierto ore deposit (Gonzalez-Pizarro, 2008: 37-38). But the most relevant railway connecting Aguas Blancas nitrate mines was the one requested on November 28, 1898 by the firm "Granja & Domínguez", which would build a railway between Antofagasta and Aguas Blancas. Permission was given a month later, the construction beginning in March 1899. Work done in 1900 showed that the firm was not using Antofagasta piers, but the habilitation of a site to the south of Antofagasta, a fact that revealed the firm strategy to avoid the opposition of the City Hall, boatmen unions, and A.B.R.C. On January 1, 1902, Coloso was ranked as a minor port. In March 1902, the railway connected "Pepita" nitrate mine with Coloso. Carrizo, La Negra, and Varillas stations were built between Coloso and Pepita. At Barazarte station, the branch to the east led to Yungay station with two branches including 90% of the canton nitrate mines. To the SE, it led to Rosario nitrate mine. The railway was open to the public for passenger transport. When Baltazar Dominguez died in 1902, his heirs sold the railway and nitrate belongings to Matias Granja. When this one died, Coloso-Aguas Blancas railway became involved in one of the most commented scandals of the time, mixing business and politics, which in turn involved the government at that time - 1907. This is what some authors have called "the famous affair of Granja house" (Recabarren, Obilinovic, Panades, 1989: 61-67). Finally, the transfer of the railway from Granja to W.R. Grace in 1908 ended in the railway being in the hands of *The Antofagasta (Chili) and Bolivia Railway Company Ltd*. It was 1909. In this way, all the private railways in the province were in the hands of English A.B.R.C. capitals. The train continued operations as long as nitrate mines working with the Shanks system could be profitable. In 1932, some branches were dismantled and it

In the nitrate pampa, the mines operating with private trains ruled railway jobs. Each nitrate mine had a Traffic Chief in charge of keeping the rails in good state and do necessary repairs. He was the direct boss of the engine driver, whose main job was to keep the boiler water at the right level and check the good state of all the engine keys and valves; firemen, dedicated to keep the engine throroughly clean, manage fire, and burn the coal or oil; and lastly, brakemen, in charge of taking care of the brakes of the train in motion. Railroad workers worked in the rails. There were also the so-called engine starters in charge of the lamps of trains in motion and lighting the engine fire at dawn. ( Macuer, 1930: 170-172;

definitely disappeared in 1961.

Gonzalez-Pizarro, 2003:312-314).

### **3. Nitrate railways of El Toco, Aguas Blancas, and Taltal cantons: Private interests**

El Toco canton was located between parallels 21° and 23° and meridians 70° and 69° , including 14 nitrate mines. It was the only canton using Shanks and Guggenheim systems since "Pedro de Valdivia" and "María Elena" nitrate mines were located in it, the latter being the last nitrate mine in operation.

Aguas Blancas canton was located between parallels 23° and 24° and meridians 70° and 69°, including 22 nitrate mines.

Taltal canton, below parallel 25° and between meridians 70° and 69°, included 26 nitrate mines.

In the mid-1833, the English man, Edward Squire, built a railway in El Toco canton to connect El Toco nitrate mines with a port between Loa river and Cobija, as established by a law passed on January 23, 1888, which legalized this branch. The railway purchased by *Anglo-Chilian Nitrate and Railway Co. Ltd.* was inaugurated in 1890. *Anglo-Chilian* connected Jose Francisco Vergara nitrate mine in 1910. In 1927, this company was purchased by Guggenheim who could build branches to Pedro de Valdivia and María Elena nitrate mines. This led to the appearance of other stations between Maria Elena and Tocopilla: Tupiza, Cerrillos, Colupito, Central, Barriles, and Tigres. The Central station railway branched off to provide service to nitrate mines located to the SE: Maria Elena, J.F. Vergara, Coya up to Miraje station, and also to the NE to arrive at Ojeda, Puntillas, and El Toco stations, where it branched off again to include other nitrate mines.

Steam engines operated until 1958, being replaced by diesel engines. Their itinerary in the 1950s was scheduled on a weekly basis for passengers and cargo. This itinerary has the most curves and gradients, operating until today and owned by the Chile Chemical and Mining Society which, established in 1968 as a mixed company and then belonging to the State, is now in private hands.

The history of Taltal canton nitrate railway is related to the government decision in 1878 to make prospections for a railway connecting nitrate productive activity with the port. In 1880, the proposal presented by Alfredo Quaet- Faslem was accepted. He transferred his rights to Jorge Stevenson, who established *Taltal Railway Company Ltd.*,. Supported by John Meiggs, Stevenson could build the railway to Refresco in a short time. Between 1887 and 1928, the network enlarged, its shareholders making big profits. Canchas station railway branched off to the NW, in the direction of Santa Luisa and Alemania stations up to Lautaro. To the E, there was a group of five nitrate mines, Flor de Chile being the most notable, whose branch located in Ovalo station branched off again to the NW to connect Caupolican and Bascunan nitrate mines. After the 1930-1931 crisis, the company determined the destiny of the Shanks system nitrate mines, getting rid of, as Ian Thomson states, rolling stock in 1940, *Taltal Railway Company Ltd.* being sold to the Chilean company "Rumie & Sons" in 1960. This company provided service to the last three nitrate mines. Alemania nitrate mine ended operations and the nitrate train was dismantled between 1977 and 1979 (Thomson, 2003).

El Toco canton was located between parallels 21° and 23° and meridians 70° and 69° , including 14 nitrate mines. It was the only canton using Shanks and Guggenheim systems since "Pedro de Valdivia" and "María Elena" nitrate mines were located in it, the latter

Aguas Blancas canton was located between parallels 23° and 24° and meridians 70° and 69°,

Taltal canton, below parallel 25° and between meridians 70° and 69°, included 26 nitrate

In the mid-1833, the English man, Edward Squire, built a railway in El Toco canton to connect El Toco nitrate mines with a port between Loa river and Cobija, as established by a law passed on January 23, 1888, which legalized this branch. The railway purchased by *Anglo-Chilian Nitrate and Railway Co. Ltd.* was inaugurated in 1890. *Anglo-Chilian* connected Jose Francisco Vergara nitrate mine in 1910. In 1927, this company was purchased by Guggenheim who could build branches to Pedro de Valdivia and María Elena nitrate mines. This led to the appearance of other stations between Maria Elena and Tocopilla: Tupiza, Cerrillos, Colupito, Central, Barriles, and Tigres. The Central station railway branched off to provide service to nitrate mines located to the SE: Maria Elena, J.F. Vergara, Coya up to Miraje station, and also to the NE to arrive at Ojeda, Puntillas, and El Toco stations, where it branched off again to include other nitrate

Steam engines operated until 1958, being replaced by diesel engines. Their itinerary in the 1950s was scheduled on a weekly basis for passengers and cargo. This itinerary has the most curves and gradients, operating until today and owned by the Chile Chemical and Mining Society which, established in 1968 as a mixed company and then belonging to the

The history of Taltal canton nitrate railway is related to the government decision in 1878 to make prospections for a railway connecting nitrate productive activity with the port. In 1880, the proposal presented by Alfredo Quaet- Faslem was accepted. He transferred his rights to Jorge Stevenson, who established *Taltal Railway Company Ltd.*,. Supported by John Meiggs, Stevenson could build the railway to Refresco in a short time. Between 1887 and 1928, the network enlarged, its shareholders making big profits. Canchas station railway branched off to the NW, in the direction of Santa Luisa and Alemania stations up to Lautaro. To the E, there was a group of five nitrate mines, Flor de Chile being the most notable, whose branch located in Ovalo station branched off again to the NW to connect Caupolican and Bascunan nitrate mines. After the 1930-1931 crisis, the company determined the destiny of the Shanks system nitrate mines, getting rid of, as Ian Thomson states, rolling stock in 1940, *Taltal Railway Company Ltd.* being sold to the Chilean company "Rumie & Sons" in 1960. This company provided service to the last three nitrate mines. Alemania nitrate mine ended operations and the nitrate train was dismantled between 1977 and 1979

**3. Nitrate railways of El Toco, Aguas Blancas, and Taltal cantons: Private** 

**interests** 

mines.

mines.

being the last nitrate mine in operation.

including 22 nitrate mines.

State, is now in private hands.

(Thomson, 2003).

Coloso-Aguas Blancas railway history is one of the most intricate of the type. Since 1880, nitrate people had been asking the government the construction of a railway for Aguas Blancas nitrate mines and were fighting for an extension of what had been accepted for Juan Besterrica, Juan Vera, and Francisco Mirada to build the rails for a steam train between Antofagasta and Aguas Blancas (Rojas, 1883). In January 1884, the Congress discussed a railway from Antofagasta to Aguas Blancas since the previous one had been rejected. In 1896, Rafael Barazarte was given permission to build a railway between Paposo and Desierto ore deposit. In 1886, Arturo Prat Mining Co. and Taltal Railway Co. received the approval to build a railway between the port and the company's mining installations. On the next year, they were allowed to extend the railway to Cachinal. This issue was again dealt with in August 1889 by J. Phillips in order to build a steam railway between these two places. On September 1, 1897, approval was given to Jose Antonio Moreno to build and exploit a railway between Paposo and Desierto ore deposit (Gonzalez-Pizarro, 2008: 37-38). But the most relevant railway connecting Aguas Blancas nitrate mines was the one requested on November 28, 1898 by the firm "Granja & Domínguez", which would build a railway between Antofagasta and Aguas Blancas. Permission was given a month later, the construction beginning in March 1899. Work done in 1900 showed that the firm was not using Antofagasta piers, but the habilitation of a site to the south of Antofagasta, a fact that revealed the firm strategy to avoid the opposition of the City Hall, boatmen unions, and A.B.R.C. On January 1, 1902, Coloso was ranked as a minor port. In March 1902, the railway connected "Pepita" nitrate mine with Coloso. Carrizo, La Negra, and Varillas stations were built between Coloso and Pepita. At Barazarte station, the branch to the east led to Yungay station with two branches including 90% of the canton nitrate mines. To the SE, it led to Rosario nitrate mine. The railway was open to the public for passenger transport. When Baltazar Dominguez died in 1902, his heirs sold the railway and nitrate belongings to Matias Granja. When this one died, Coloso-Aguas Blancas railway became involved in one of the most commented scandals of the time, mixing business and politics, which in turn involved the government at that time - 1907. This is what some authors have called "the famous affair of Granja house" (Recabarren, Obilinovic, Panades, 1989: 61-67). Finally, the transfer of the railway from Granja to W.R. Grace in 1908 ended in the railway being in the hands of *The Antofagasta (Chili) and Bolivia Railway Company Ltd*. It was 1909. In this way, all the private railways in the province were in the hands of English A.B.R.C. capitals. The train continued operations as long as nitrate mines working with the Shanks system could be profitable. In 1932, some branches were dismantled and it definitely disappeared in 1961.

In the nitrate pampa, the mines operating with private trains ruled railway jobs. Each nitrate mine had a Traffic Chief in charge of keeping the rails in good state and do necessary repairs. He was the direct boss of the engine driver, whose main job was to keep the boiler water at the right level and check the good state of all the engine keys and valves; firemen, dedicated to keep the engine throroughly clean, manage fire, and burn the coal or oil; and lastly, brakemen, in charge of taking care of the brakes of the train in motion. Railroad workers worked in the rails. There were also the so-called engine starters in charge of the lamps of trains in motion and lighting the engine fire at dawn. ( Macuer, 1930: 170-172; Gonzalez-Pizarro, 2003:312-314).

Privatization Versus Public Funding on the Atacama Desert Railway – An Interpretation 63

The North Longitudinal Railway administration was transferred to A.B.R.C. in 1919 under the name *Chilian Northern*, a situation that remained until October 1957, when the government decided to transfer *Chilian Northern* to the State Railway Co., authorizing A.B.R.C. to administrate it until May 1961. The most popular Atacama dersert train operated

The northern novelist Hernan Rivera-Letelier would strongly evoque the famous *Longino* in

**5. The Antofagasta-salta railway: From citizen initiative to bi-state concretion**  One of the railways having the greatest support by citizens, after Antofagasta-Salinas and

In November 1966, *En Viaje* magazine director, Manuel Jofre, wrote that this venture had started in Argentina, by naming a study commission, but it soon found opposition on both sides because "some sectors considered that it was against the interest of farmers in the south of both Chile and Argentina. For this reason, the project was delayed" (Jofre,

It was precisely the A.B.R.C. – *The Antofagasta and Bolivia Railway Co. Ltd* – which made the first studies in 1888 to connect the Argentinian northeast with the Chilean north, through a group of engineers. One of them, Luis Abd- El Kader, with Italian-Arab ancestors, was greatly influencial in the urban planning of Antofagasta, where, as Thomson & Angerstein state, a connection with *Argentina Grand Central Railway* would be looked for with a design starting from Sierra Gorda station, going through Caracoles mine, San Pedro de Atacama, and Aguas Calientes and then arriving at the Argentinian territory through Huaytiquina. These authors conclude that this study had great advantages, a steady income from local transport because the railway crossed an area very rich in minerals, among others (Thomson- Angerstein, 1997: 172-173). The project did not succeed probably owing to the

territory dispute, solved in 1899, of the Atacama puna between Chile and Argentina.

in June 1911(Sociedad Nacional de Agricultura, 1922: 5-6).

A new impulse to this venture came from the coincidence between Mejillones re-foundation efforts made by the government and A.B.R.C. request for land to install its machine shop bewteen 1904 and 1906, on the one hand, and the Argentinian renewed effort made by engineer Manuel Sola who, in 1905, called the government attention to the huge advantages Mejillones offered to export the agricultural and cattle production from Salta and the new Andes territory through its port. According to Sola, "All the input for men and animal survival easily find a market in this province. Cattle is imported from Salta (Argentinian Republic) and the south of Chile; flower, from California; rice, sugar, and fruits, from Peru; tobacco, from La Habana and Bolivia; wine, beer, cereals, beans, vegetables, barley, dry grass, and another hundred products from the south of Chile" (Solá, 1906:19). Sola's ideas were supported by other Argentinian reports such as Dr. Arturo S. Torino's in 1906 and exposed to the Argentinian Congress by the Minister of Foreign Affairs at that time, Estanislao Zeballos. On the following year, July 1907, Horacio Fabres, Manuel Maira, and Santiago Zanelli requested the government authorization to build a transandean railway to connect Mejillones and Salta. After putting it off several times, the railway was inaugurated

until June 9, 1975.

1966:17).

his work **Trains go to Purgatory.** 

Caracoles, was the Antofagasta-Salta railway.

### **4. The Noth longitudinal railway: The state intervention**

The construction of the North Longitudinal Railway started when the government decided to extend the fiscal railway from Pueblo Hundido, in Copiapo province, to Pintados, in Tarapaca. Reasons of national safety and territory integration lay behind this venture. A public bid, after some failures, was awarded to *Chilian Northern Railway Co. Ltd* in 1910.

The well-known North Longitudinal, the famous *Longino,* was finally inaugurated on January 10, 1919 (Thomson, 2003), although the definite exploitation of de journey between Iquique and Calera started on March 19, 1930 (En Viaje, 1960: Nº 325).

The North Longitudinal was connected to Santiago and Valparaíso trains. It included several stations, starting in Pueblo Hundido, followed by Altamira, Catalina, Balmaceda, Los Vientos, Lacalle, Agua Buena, Aguas Blancas, Oriente, Palestina, Desierto, Baquedano, (to Antofagasta and Calama), Rioja, Deseada, Los Dones, Lynch, Miraje, Chacabuco, El Toco, Santa Fe, and Quillagua. In 1966, the trip from Calera to Iquique was scheduled for Sunday (with a connection to and from Antofagasta) using first-class, second-class, and buffet wagons, the latter being the most complete; on Thursday, there was a trip from Baquedano to Calama, with second-class and buffet wagons; on Saturday, the train arrived at Antofagasta, with the same wagons as on Thursday; on Tuesday, there was a train with second-class and buffet wagons arriving at El Toco. The trip from Iquique to Calera was scheduled for Monday and Thursday; the trip from Antofagasta to El Toco, Tuesday and Saturday (En Viaje, 1966: N° 388)

Unlike what happened to A.B.R.C., which would later add Chuquicamata copper mining production to its load transported to Antofagasta, the North Longitudinal had to overcome economic difficulties in time. Ian Thomson, the English railway specialist, only slightly states the adverse picture of the Longitudinal crossing the desert: "A longitudinal railway to travel along one of the world's most arid zones had been built; (i) where agricultural production is practically none; (ii) where population is non-existing, except for a very limited number of small cities; (iii) where mining production is also scarce, and; (iv) which would have very limited expectations to make long journeys to and from the country's central and south zones" (Thomson, 2003:48). In the 1950s, its material had not been replaced and maintainance costs were high. The accelerated disappearance of Shanks system nitrate mines involved passenger and cargo loss. Only in the mid-1950s, the State Railway Co. considered connecting appealing desert locations to its tourist agenda. It was the beginning of a tourist massification boom in the Chilean north, supported by the railway as a non-elitist popular means of transport, as experimented in the U.S.A. (Sheffer, 2001). This happening helped discovering the northern geography as a tourist landscape, together with a State policy to support northern cities. In 1934, the State Railway Co. started publishing a *Tourist Guide* which did not strongly stimulated visits to northern "tourist" attractions, but those in the south. Nevertheless, another State Railway Co. publication, *En Viaje*, included places located in the preandean locations and the city of Antofagasta in its pages in the late 1940s. Paradoxically, the North Logitudinal did not arrive at these places (except the city of Antofagasta, where A.B.R.C. had built a railway branch between Baquedano and the port, based on an agreement with *The Chilian Northern* in 1921). In this way, the main cities could be known and a "leisure and winter tourism" could be institutionalized in the northern zone, where the railway and roads made recreation possible (Gonzalez-Pizarro, Ms).

The construction of the North Longitudinal Railway started when the government decided to extend the fiscal railway from Pueblo Hundido, in Copiapo province, to Pintados, in Tarapaca. Reasons of national safety and territory integration lay behind this venture. A public bid, after some failures, was awarded to *Chilian Northern Railway Co. Ltd* in 1910.

The well-known North Longitudinal, the famous *Longino,* was finally inaugurated on January 10, 1919 (Thomson, 2003), although the definite exploitation of de journey between

The North Longitudinal was connected to Santiago and Valparaíso trains. It included several stations, starting in Pueblo Hundido, followed by Altamira, Catalina, Balmaceda, Los Vientos, Lacalle, Agua Buena, Aguas Blancas, Oriente, Palestina, Desierto, Baquedano, (to Antofagasta and Calama), Rioja, Deseada, Los Dones, Lynch, Miraje, Chacabuco, El Toco, Santa Fe, and Quillagua. In 1966, the trip from Calera to Iquique was scheduled for Sunday (with a connection to and from Antofagasta) using first-class, second-class, and buffet wagons, the latter being the most complete; on Thursday, there was a trip from Baquedano to Calama, with second-class and buffet wagons; on Saturday, the train arrived at Antofagasta, with the same wagons as on Thursday; on Tuesday, there was a train with second-class and buffet wagons arriving at El Toco. The trip from Iquique to Calera was scheduled for Monday and Thursday; the trip from Antofagasta to El Toco, Tuesday and

Unlike what happened to A.B.R.C., which would later add Chuquicamata copper mining production to its load transported to Antofagasta, the North Longitudinal had to overcome economic difficulties in time. Ian Thomson, the English railway specialist, only slightly states the adverse picture of the Longitudinal crossing the desert: "A longitudinal railway to travel along one of the world's most arid zones had been built; (i) where agricultural production is practically none; (ii) where population is non-existing, except for a very limited number of small cities; (iii) where mining production is also scarce, and; (iv) which would have very limited expectations to make long journeys to and from the country's central and south zones" (Thomson, 2003:48). In the 1950s, its material had not been replaced and maintainance costs were high. The accelerated disappearance of Shanks system nitrate mines involved passenger and cargo loss. Only in the mid-1950s, the State Railway Co. considered connecting appealing desert locations to its tourist agenda. It was the beginning of a tourist massification boom in the Chilean north, supported by the railway as a non-elitist popular means of transport, as experimented in the U.S.A. (Sheffer, 2001). This happening helped discovering the northern geography as a tourist landscape, together with a State policy to support northern cities. In 1934, the State Railway Co. started publishing a *Tourist Guide* which did not strongly stimulated visits to northern "tourist" attractions, but those in the south. Nevertheless, another State Railway Co. publication, *En Viaje*, included places located in the preandean locations and the city of Antofagasta in its pages in the late 1940s. Paradoxically, the North Logitudinal did not arrive at these places (except the city of Antofagasta, where A.B.R.C. had built a railway branch between Baquedano and the port, based on an agreement with *The Chilian Northern* in 1921). In this way, the main cities could be known and a "leisure and winter tourism" could be institutionalized in the northern zone, where the railway and roads made recreation

**4. The Noth longitudinal railway: The state intervention** 

Iquique and Calera started on March 19, 1930 (En Viaje, 1960: Nº 325).

Saturday (En Viaje, 1966: N° 388)

possible (Gonzalez-Pizarro, Ms).

The North Longitudinal Railway administration was transferred to A.B.R.C. in 1919 under the name *Chilian Northern*, a situation that remained until October 1957, when the government decided to transfer *Chilian Northern* to the State Railway Co., authorizing A.B.R.C. to administrate it until May 1961. The most popular Atacama dersert train operated until June 9, 1975.

The northern novelist Hernan Rivera-Letelier would strongly evoque the famous *Longino* in his work **Trains go to Purgatory.** 

### **5. The Antofagasta-salta railway: From citizen initiative to bi-state concretion**

One of the railways having the greatest support by citizens, after Antofagasta-Salinas and Caracoles, was the Antofagasta-Salta railway.

In November 1966, *En Viaje* magazine director, Manuel Jofre, wrote that this venture had started in Argentina, by naming a study commission, but it soon found opposition on both sides because "some sectors considered that it was against the interest of farmers in the south of both Chile and Argentina. For this reason, the project was delayed" (Jofre, 1966:17).

It was precisely the A.B.R.C. – *The Antofagasta and Bolivia Railway Co. Ltd* – which made the first studies in 1888 to connect the Argentinian northeast with the Chilean north, through a group of engineers. One of them, Luis Abd- El Kader, with Italian-Arab ancestors, was greatly influencial in the urban planning of Antofagasta, where, as Thomson & Angerstein state, a connection with *Argentina Grand Central Railway* would be looked for with a design starting from Sierra Gorda station, going through Caracoles mine, San Pedro de Atacama, and Aguas Calientes and then arriving at the Argentinian territory through Huaytiquina. These authors conclude that this study had great advantages, a steady income from local transport because the railway crossed an area very rich in minerals, among others (Thomson- Angerstein, 1997: 172-173). The project did not succeed probably owing to the territory dispute, solved in 1899, of the Atacama puna between Chile and Argentina.

A new impulse to this venture came from the coincidence between Mejillones re-foundation efforts made by the government and A.B.R.C. request for land to install its machine shop bewteen 1904 and 1906, on the one hand, and the Argentinian renewed effort made by engineer Manuel Sola who, in 1905, called the government attention to the huge advantages Mejillones offered to export the agricultural and cattle production from Salta and the new Andes territory through its port. According to Sola, "All the input for men and animal survival easily find a market in this province. Cattle is imported from Salta (Argentinian Republic) and the south of Chile; flower, from California; rice, sugar, and fruits, from Peru; tobacco, from La Habana and Bolivia; wine, beer, cereals, beans, vegetables, barley, dry grass, and another hundred products from the south of Chile" (Solá, 1906:19). Sola's ideas were supported by other Argentinian reports such as Dr. Arturo S. Torino's in 1906 and exposed to the Argentinian Congress by the Minister of Foreign Affairs at that time, Estanislao Zeballos. On the following year, July 1907, Horacio Fabres, Manuel Maira, and Santiago Zanelli requested the government authorization to build a transandean railway to connect Mejillones and Salta. After putting it off several times, the railway was inaugurated in June 1911(Sociedad Nacional de Agricultura, 1922: 5-6).

Privatization Versus Public Funding on the Atacama Desert Railway – An Interpretation 65

In 1949, the Antofagasta-Salta railway was scheduled on a weekly basis, the journey taking two days: the train included regular and buffet wagons. It started from Antofagasta on

Nevertheless, high transport costs, exceeded by truck competente in time, did not meet the expectations of both regions. A.B.R.C. operated the railway, as contrated with the government in the 1920s, and as stated by Ian Thomson, assigned "old engines left over from other operations to cargo trains (and) in the mid-1950s, assigned relatively modern steam engines for passengers' service" (Thomson, 2006: 145) until 1964. In the 1960s, the State Railway Co. started operations on the rails. At the end of 1970, passengers' trips were cancelled. In 1990, it was transferred to Ferronor S.A., a Production-Fostering Corporation (CORFO, for its acronym in Spanish) company, privatized in 1996. At present, the railway operates only sporadically.

Ahumada, María T. 1999. El Establecimiento Industrial de Playa Blanca en Antofagasta.

Anguita, Ricardo. 1912. Leyes promulgadas en Chile desde 1810 hasta el 1° de junio de 1913. Santiago de Chile: Imprenta, Litografía i Encuadernación Barcelona, Tomo III. Aramayo, Cesáreo. 1959. Ferrocarriles bolivianos. Pasado, presente y futuro. La Paz:

Arce, Isaac. 1930. Narraciones Históricas de Antofagasta. Antofagasta: Imprenta Moderna. Archivo Escuela de Derecho, Universidad Católica del Norte. 1906. Archivo de Isaac Arce.

Archivo historico, Universidad Católica del Norte. 1929. Archivo Salitrero Oficina Chacabuco:

Benedetti, Alejandro. 2005. "El ferrocarril Huaytiquina, entre el progreso y el fracaso.

Blakemore, Harold. 1991. "¿Nacionalismo frustrado? Chile y el salitre, 1870-1895" en Harold

Blakemore, Harold.1996. Historia del Ferrocarril de Antofagasta a Bolivia 1888-1988.

Bresson, André. 1997 [1886]. Una visión francesa del Litoral Boliviano (1886). La Paz:

Bowman, Isaiah. 1924. Desert Trails of Atacama. New York: American Geographical Society. Braudel, Fernando, 1970. La historia y las ciencias sociales. Madrid: Alianza Editorial. Bravo Quezada, Carmen G. 2000. La Flor del Desierto. El mineral de Caracoles y su impacto

de la Administración del F.C.A.B, Antofagasta, 29 de mayo de 1929.

http://wwwscielo.org.ar/scielo.php?script=sci\_arttext&pid=S1669- 90412005000100007&ing=es&nrm=iso. Consulta el 14 de agosto de 2011. Bertrand, Alejandro. 1885. Memoria sobre las cordilleras del desierto de Atacama i rejiones

limítrofes. Santiago de Chile: Imprenta Nacional.

Caja "Medios de Transporte. Años 1920-1939.Transporte y Comunicaciones". Circular

Aproximaciones desde la geografía histórica del territorio de los Andes", Revista Escuela de Historia, Salta, enero-diciembre, N° 4, 123-165. Disponible en

Blakemore, Dos estudios sobre salitre y política en Chile (1870-1895). Editado por Luis Ortega. Santiago de Chile. Departamento de Historia. Universidad de

Traducción de Juan Ricardo Couyoumdjian y Beatríz Kase. Santiago de Chile:

en la economía chilena. Santiago de Chile: Dibam, Lom Ediciones, Centro de

Sunday and arrived at Salta on Tuesday.

Antofagasta: Ediciones Santos Ossa.

Carpeta varia "Personal y Salitrera".

Imprenta Nacional.

Santiago de Chile.

Impresos Universitarios S.A.

Stampa Grafica Digital.

Investigaciones Diego Barros Arana.

**6. References** 

But there was also another issue in this connectivity: the Chilean government authorization for the construction of a new Antofagasta port based on Law N° 2390, passed on September 7, 1910, which was fruitful in 1913 when the Port Commission reported the connectivity – Antofagasta natural attraction zone - of the Mejillones-Salta projected railway, which should take advantage of the new installations in the future (Gonzalez-Pizarro, 2010ª).

This proposal was supported by citizens - laborers' unions, political parties, and commercial and industrial associations –; disseminated in Open City Hall Meetings; and also supported by the establishment of the Salta Pro-Railway Executive Commission. Since April 5, 1920, multitudinal meetings in the form of Open City Hall Meetings were organized in favor of the proposal. For mayor Maximiliano Poblete-Cortes, the railway was of "national conveniente because it will help in the development of one of the country's most important regions; it will attract a big part of Argentinian commerce to the Pacific; and, therefore, there will be an increase in freight and cargo for our merchant marine; some of our industries, such as the nitrate one, will increase their production to fertilize land producing sugar cane, cotton, etc. Other industries such as shoe-making, canned food, and maybe other ones will have a safe market. Concerning regional coexistence, we believe no one can deny it. At present, the life and progress of Antofagasta and the whole region are closely related to the development and prosperity of nitrate and copper industries (Gonzalez-Pizarro, 1994, 1995, 1999, 2002).

The same response was given by Argentina, where a Pro-Pacific Railway Commission was established in 1921, its director being Luis de los Rios. This commission organized "various acts that gave prestige and widely disseminated Salta population's mood". The railway construction also lead to a geopolitical mistrust view from the military prism, while in Antofagasta, civilians reaffirmed their conviction of the integration with the Argentinian northeast" (Benedeti, 2005).

Government actions from both sides led to the investment budget agenda agreed on by the Chilean Minister of Foreign Affairs, Ernesto Barros Jarpa, and the Argentinian Envoy Extraordinary and Minister Plenipotentiary in Chile, Carlos M. Noel, on April 25, 1922. The project, however, could only be improved in 1928. In 1930, Argentina had already built the railway from Salta to San Antonio de los Cobres. Finally, the railway was constructed in Augusta Victoria station sector in 1937, after recovering from the 1930-1932 world crisis (Thomson, 2003, 2006).

During the early 1940s, the government increased its contribution to speed up the railway construction. Curiously enough, as stated by Alejandro Benedetti, the railway that had been thought of by Argentina to improve the Andes Territory would arrive late, when the territory had disappeared in 1943 to favor Salta, Jujuy, and Tucuman provinces. This was a bad sign. The Chilean north still cherished hopes for the railway, months before being inaugurated because, apart from the work of many people, "the cost of living in the northern provinces will be cheaper… it will avoid the current supply difficulties and complications due to the scarcity of cargo ships… The railway does not only have an economic mission, but it also takes the torch of progress, culture, mutual knowledge and, therefore, people's physical and spiritual welfare everywhere" (Szigethy, 1948: 67-68).

On February 20, 1948, the President of Argentina, Juan D. Peron, inaugurated the railway in the Argentinian sector, with the presence of Antofagasta Mayor, Juan de Dios Carmona.

In 1949, the Antofagasta-Salta railway was scheduled on a weekly basis, the journey taking two days: the train included regular and buffet wagons. It started from Antofagasta on Sunday and arrived at Salta on Tuesday.

Nevertheless, high transport costs, exceeded by truck competente in time, did not meet the expectations of both regions. A.B.R.C. operated the railway, as contrated with the government in the 1920s, and as stated by Ian Thomson, assigned "old engines left over from other operations to cargo trains (and) in the mid-1950s, assigned relatively modern steam engines for passengers' service" (Thomson, 2006: 145) until 1964. In the 1960s, the State Railway Co. started operations on the rails. At the end of 1970, passengers' trips were cancelled. In 1990, it was transferred to Ferronor S.A., a Production-Fostering Corporation (CORFO, for its acronym in Spanish) company, privatized in 1996. At present, the railway operates only sporadically.

### **6. References**

64 Infrastructure Design, Signalling and Security in Railway

But there was also another issue in this connectivity: the Chilean government authorization for the construction of a new Antofagasta port based on Law N° 2390, passed on September 7, 1910, which was fruitful in 1913 when the Port Commission reported the connectivity – Antofagasta natural attraction zone - of the Mejillones-Salta projected railway, which should

This proposal was supported by citizens - laborers' unions, political parties, and commercial and industrial associations –; disseminated in Open City Hall Meetings; and also supported by the establishment of the Salta Pro-Railway Executive Commission. Since April 5, 1920, multitudinal meetings in the form of Open City Hall Meetings were organized in favor of the proposal. For mayor Maximiliano Poblete-Cortes, the railway was of "national conveniente because it will help in the development of one of the country's most important regions; it will attract a big part of Argentinian commerce to the Pacific; and, therefore, there will be an increase in freight and cargo for our merchant marine; some of our industries, such as the nitrate one, will increase their production to fertilize land producing sugar cane, cotton, etc. Other industries such as shoe-making, canned food, and maybe other ones will have a safe market. Concerning regional coexistence, we believe no one can deny it. At present, the life and progress of Antofagasta and the whole region are closely related to the development and

take advantage of the new installations in the future (Gonzalez-Pizarro, 2010ª).

prosperity of nitrate and copper industries (Gonzalez-Pizarro, 1994, 1995, 1999, 2002).

northeast" (Benedeti, 2005).

(Thomson, 2003, 2006).

The same response was given by Argentina, where a Pro-Pacific Railway Commission was established in 1921, its director being Luis de los Rios. This commission organized "various acts that gave prestige and widely disseminated Salta population's mood". The railway construction also lead to a geopolitical mistrust view from the military prism, while in Antofagasta, civilians reaffirmed their conviction of the integration with the Argentinian

Government actions from both sides led to the investment budget agenda agreed on by the Chilean Minister of Foreign Affairs, Ernesto Barros Jarpa, and the Argentinian Envoy Extraordinary and Minister Plenipotentiary in Chile, Carlos M. Noel, on April 25, 1922. The project, however, could only be improved in 1928. In 1930, Argentina had already built the railway from Salta to San Antonio de los Cobres. Finally, the railway was constructed in Augusta Victoria station sector in 1937, after recovering from the 1930-1932 world crisis

During the early 1940s, the government increased its contribution to speed up the railway construction. Curiously enough, as stated by Alejandro Benedetti, the railway that had been thought of by Argentina to improve the Andes Territory would arrive late, when the territory had disappeared in 1943 to favor Salta, Jujuy, and Tucuman provinces. This was a bad sign. The Chilean north still cherished hopes for the railway, months before being inaugurated because, apart from the work of many people, "the cost of living in the northern provinces will be cheaper… it will avoid the current supply difficulties and complications due to the scarcity of cargo ships… The railway does not only have an economic mission, but it also takes the torch of progress, culture, mutual knowledge and, therefore, people's physical and spiritual welfare everywhere" (Szigethy, 1948: 67-68).

On February 20, 1948, the President of Argentina, Juan D. Peron, inaugurated the railway in the Argentinian sector, with the presence of Antofagasta Mayor, Juan de Dios Carmona.


90412005000100007&ing=es&nrm=iso. Consulta el 14 de agosto de 2011.


Privatization Versus Public Funding on the Atacama Desert Railway – An Interpretation 67

Gonzalez Pizarro, José A. 2009a. "The province of Antofagasta. Creation and consolidation

Gonzalez Pizarro, José A. 2009b. "La huelga/masacre de la Plaza Colón: 6 de febrero de 1906

Gonzalez Pizarro, José A. 2010. "La influencia de la legislación municipal boliviana en

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Greve, Ernesto. 1944. Historia de la Ingeniería en Chile. Santiago de Chile: Imprenta

Informe Económico Ferrocarril de Antofagasta a Bolivia. 1959. The Bolivia Railway

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Macuer Llaña, Horacio. 1930. Manual Práctico de los trabajos en la Pampa Salitrera.

Mandiola, Juan-Castillo, Pedro. 1894. Guía de Antofagasta. Antofagasta: Imprenta El

Mendieta Parada, Pilar. 2006. "Oruro: ciudad moderna y cosmopolita 1892-1930" en Ximena

Mitre, Antonio. 1981. Los Patriarcas de la Plata. Estructura socioeconómica de la minería

Mondaca R. Carlos- Segovia B. Wilson-Sánchez G. Elizabeth. 2011. Historia y Sociedad del

Monterrey C. Nancy. 2009. Chuquicamata. Otras voces te recuerdan. Antofagasta: Sergraf Ltda. Nuñez Atencio, Lautaro.1992. Cultura y conflicto en los oasis de San Pedro de Atacama.

Panades, Juan. 1990. "La maestranza del Ferrocarril Antofagasta a Bolivia en Mejillones".

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noviembre, Número 397.


**4** 

*South Africa* 

**Competitiveness and Sustainability of Railways** 

The world's railway population spans many outcome variations between failure and success. The study of differences is of course the foundation of scientific research: The ability to understand what drives such differences facilitates cognitive positioning of railways for success, or more specifically, competitiveness and sustainability. The authors have pioneered research that contributed some understanding, on a journey that commenced with research to describe the global railway setting, and ultimately applied multivariate statistical analysis to discover how railways adapted to their particular settings. The findings were published piecemeal as they emerged (e.g. International Heavy Haul Association 1997, 2007, and 2009; Railway Gazette International, 2006; Transport Research Arena 2012; and World Congress on Railway Research, 2003, 2006, and 2008), and have been integrated for the first time in this chapter to present a global overview of the railway industry. As put forward here, the research foundation is still evident, but only sufficient detail to support the storyline has been retained. The present objective is to emphasize interpretation and significance of the findings for future railway positioning, within the available page limit. Reference will of course be made to the

The research stream originated in a need to redress South Africa's colonial railway heritage of narrow track gauge, light axle load, low speed, small vehicle profile, steep gradients, and monolithic state ownership, which attributes posed many challenges. Some were amenable to technological solution—for example it developed successful heavy haul operations—but others remained endemic. Solutions to similar challenges emerged around the world during railway renaissance and ensuing railway reform. However, the need to control for many differences among such solutions and their settings deterred research to understand which interventions work and which do not. It will become evident, for example, that debating the merits of vertical integration and vertical separation can miss the point that either can work if a railway is inherently competitive, while neither will work if it is inherently uncompetitive. Unlike other more or less homogeneous modes such as airlines, which are challenged to differentiate their offerings, rail's attributes are so heterogeneous that their variance boggles the unaided human mind. Gradually awareness dawned that only high-

**1.1 Failure and success: Competitiveness and sustainability** 

**1.2 Building a foundation for research into railway positioning** 

**1. Introduction** 

underlying research where appropriate.

level numerate research would make progress.

Dave van der Meulen and Fienie Möller

*Railway Corporate Strategy CC* 

Bolivia y América Latina. La Paz: IFEA-Embajada de Francia- Coordinadora de Historia, Muela del Diablo Editores.


Dave van der Meulen and Fienie Möller

*Railway Corporate Strategy CC South Africa* 

### **1. Introduction**

68 Infrastructure Design, Signalling and Security in Railway

Philippi, Rodulfo .A. 2008 [1860]. Viaje al desierto de Atacama. Estudio Preliminar de Augusto

Biblioteca Nacional de Chile- Cámara Chilena de la Construcción), Tomo 39. Ramirez N. Hernán. 2007. Balmaceda y la contrarrevolución de 1891. En Hernán Ramírez

Recabarren R. Floreal-Obilinovic A. Antonio-Panades V. Juan. 1989 [ 1983 1° Ed).Coloso.

Rojas D. Matías. 1883. El Desierto de Atacama i el Territorio Reivindicado. Antofagasta:

Sagredo Baeza, Rafael. 2001. La gira del presidente Balmaceda al norte. El inicio del "crudo y

San Roman, Francisco. J. 1896. Desierto y Cordilleras de Atacama. Santiago de Chile:

Sheffer, M. 2001. See America First. Tourism and National Identity, 1880-1940*.* Washington:

Sociedad Nacional De Agricultura, 1922. Ferrocarril trasandino de Antofagasta a Salta.

Solá, Manuel. 1906. Ferrocarril Trasandino de Salta a Mejillones o Antofagasta. Salta:

Szigethy, Teodoro de. 1948. "El Ferrocarril de Salta a Antofagasta y su importancia", Revista

Thompson, Ian. 2003. Red Norte: La historia de los ferrocarriles del norte chileno. Santiago de

Thomson, Ian Thomson. 2006. "Los ferrocarriles del Capricornio Andino", en Angel

Thomson, Ian- Angerstein, Dietrich. 1997. Historia del ferrocarril en Chile. Santiago: Dibam-

Chile: Publicación patrocinada por el Instituto de Ingenieros de Chile, Imprenta Silva.

Cabezas, María Isabel Hernández, Lautaro Núñez, Mario Vásquez, Comité Editor, Las Rutas del Capricornio Andino. Huellas milenarias de Antofagasta, San Pedro de Atacama, Jujuy y Salta. Santiago de Chile: Consejo de Monumentos Nacionales,

Historia, Muela del Diablo Editores.

Antofagasta- Universidad Católica del Norte.

Imprenta de El Industrial.

Imprenta Nacional. 2 tomos.

Laborersonian Institute Press.

Imprenta y Tipografía El Cívico.

Santiago de Chile, pp. 137-149.

En Viaje, febrero, Número 172, pp. 66-68.

Centro de Investigaciones Diego Barros Arana.

Santiago de Chile: s.p.i.

Una aventura histórica. Antofagasta: Imprenta Atelier.

Bolivia y América Latina. La Paz: IFEA-Embajada de Francia- Coordinadora de

Bruna-Andrea Larroucau. Santiago de Chile: Biblioteca Fundamentos de la Construcción de Chile (Facultad de Historia, Geografía y Ciencia Política, Pontificia Universidad Católica de Chile-Fundación RA Philippi de Estudios Naturales-

Necochea, Obras Escogidas. Selección, edición y estudio preliminar Julio Pinto. Santiago de Chile: Lom Ediciones- Consejo Nacional de la Cultura y las Artes. Recabarren R. Floreal. 2002. Episodios de la vida regional. Antofagasta: Corporación Pro

riguroso invierno de su quinquenio", (verano de 1889). Santiago de Chile: Lom Ediciones-Universidad Arturo Prat- Centro de Investigaciones Diego Barros Arana.

### **1.1 Failure and success: Competitiveness and sustainability**

The world's railway population spans many outcome variations between failure and success. The study of differences is of course the foundation of scientific research: The ability to understand what drives such differences facilitates cognitive positioning of railways for success, or more specifically, competitiveness and sustainability. The authors have pioneered research that contributed some understanding, on a journey that commenced with research to describe the global railway setting, and ultimately applied multivariate statistical analysis to discover how railways adapted to their particular settings. The findings were published piecemeal as they emerged (e.g. International Heavy Haul Association 1997, 2007, and 2009; Railway Gazette International, 2006; Transport Research Arena 2012; and World Congress on Railway Research, 2003, 2006, and 2008), and have been integrated for the first time in this chapter to present a global overview of the railway industry. As put forward here, the research foundation is still evident, but only sufficient detail to support the storyline has been retained. The present objective is to emphasize interpretation and significance of the findings for future railway positioning, within the available page limit. Reference will of course be made to the underlying research where appropriate.

### **1.2 Building a foundation for research into railway positioning**

The research stream originated in a need to redress South Africa's colonial railway heritage of narrow track gauge, light axle load, low speed, small vehicle profile, steep gradients, and monolithic state ownership, which attributes posed many challenges. Some were amenable to technological solution—for example it developed successful heavy haul operations—but others remained endemic. Solutions to similar challenges emerged around the world during railway renaissance and ensuing railway reform. However, the need to control for many differences among such solutions and their settings deterred research to understand which interventions work and which do not. It will become evident, for example, that debating the merits of vertical integration and vertical separation can miss the point that either can work if a railway is inherently competitive, while neither will work if it is inherently uncompetitive. Unlike other more or less homogeneous modes such as airlines, which are challenged to differentiate their offerings, rail's attributes are so heterogeneous that their variance boggles the unaided human mind. Gradually awareness dawned that only highlevel numerate research would make progress.

Stack (Supporting, Guiding, and Coupling). All three have demonstrated robust

The fourth market space is potentially weak—light axle load combined with low speed exploits neither Supporting nor Guiding genetic technology. Failure to exploit the remaining genetic technology, Coupling, in general freight- and classic long-distance passenger rail applications exacerbates their weakness, hence competitors erode their markets. Depending on whether economic-, political-, or social objectives determine their destiny, such railways

Human passengers as payload do not achieve high axle load by railway standards, even in double deck vehicles. Furthermore, the comfort criteria and physical laws pertaining to acceleration, coasting, retardation, and station dwell time, maximize the capacity function at around 80km/h. Therefore urban rail cannot maximally exploit either the Supporting- or the Guiding genetic technology: It is confined to a potentially weak market space, in which it can exploit only the Coupling genetic technology. By forming vehicles into trains, it can achieve shorter mean headways than would be attainable by the same number of autonomous vehicles, thereby maximizing passenger capacity per direction per unit time. However, where urban rail does not exploit that one and only genetic technology to realize its capacity potential, it is vulnerable to competition from the rubber-tyred modes Automated Guided Transit, Bus Rapid Transit, and Monorail. The maximum speed of all urban guided transit modes is similar, so winners must leverage headway to maximize capacity. With no pretence at high axle load, rubber tyred modes exploit their consistent

From bleak prospects in the first decade after World War II, railways in many countries have learned to exploit the competitive strengths that inhere in rail's genetic technologies.

In 1964, Japan introduced the world's first commercial high-speed intercity trains (Japanese Railway, 1964); they exploited the Guiding genetic technology to reach speeds of 210km/h, and leveraged high capacity by exploiting the Coupling genetic technology. Today, high-

sustainability in competition with other transport modes.

Fig. 1. Railway market spaces by Axle Load and Speed

are respectively eliminated, protected, or subsidized.

high adhesion to encroach on rail's eminent domain.

The following events mark the course of their learning:

**2.2 The special case of urban rail** 

**2.3 The railway renaissance** 

The field of corporate strategy is a well established major in business administration and business leadership. It addresses the total enterprise and how various functions interact to achieve objectives. Thus while all enterprises encompass several common functions, e.g. human capital, information technology, and so on, they must also manage their distinct core business, whether that be banking, mining, whatever, or in the case of railways, moving goods and people to support their logistics and mobility needs. However, googling *railway corporate strategy* returned items dominated by the authors' enterprise and their publications. The unique contribution of the present research stream is therefore a grounded understanding of corporate strategy with respect to the core business of railways.

### **2. Railway positioning**

### **2.1 Competitiveness fundamentals**

To comprehend railway positioning, it is helpful to examine railway competitiveness vis-àvis that of other transport modes by considering their degrees-of-freedom-of-movability. Three degrees-of-freedom-of-movability (e.g. aerial- and submarine transport) offer high, spatial movability, but at relatively high cost. Next, two degrees-of-freedom-of-movability (e.g. unguided surface transport) offer lower, surface movability at lower cost. Last, one degree-of-freedom–of-movability (e.g. guided surface transport) offers only limited, linear movability, back and forth on its guideway. To the extent that limited movability reduces the value of their offering, guided surface transport modes such as railways must offer compensating advantages to compete effectively against other modes that offer higher movability, including door-to-door transport.

Axiomatically, such compensating advantages should inhere in technologies that differentiate guided surface transport from other transport modes. A vehicle-guideway pair ensures precise application of vertical loads, and safe application of lateral loads: Wheel-rail contact mechanics develop vertical- and lateral force components, technologies named *Supporting* and *Guiding* by Vuchic (2007: 449), which can sustain respectively heavy axle load and high speed. One may leverage Supporting and Guiding by combining two or many vehicles, to scale capacity as required, a technology the authors named *Coupling*. Supporting, Guiding, and Coupling are the three *genetic technologies* that distinguish guided surface transport from all other transport modes: *Inherent competitiveness* is defined here, and is measurable as, the extent to which such modes exploit their genetic technologies.

Note that the preceding two paragraphs have been generalized to guided surface transport, of which railways is a subset. Other guided surface transport modes also exist, which do not use steel-wheel-on-steel rail. We shall return to them in the context of urban guided transit in §3.3 and §3.5. Until then, this chapter addresses railways.

Cross-breaking Bearing and Guiding, in Figure 1, yields four railway market spaces. For this purpose, speed in tens of km/h is low speed, speed in hundreds of km/h is high speed; axle load above 25 tonnes is heavy. Three market spaces feature high competitiveness, by exploiting two or more of rail's genetic technologies—namely Heavy Haul (Supporting and Coupling), High-speed Intercity (Guiding and Coupling), and Heavy Intermodal1 or Double

 1Heavy intermodal traffic has heavy axle load: It is distinct from light traffic that simply transfers from one mode to another.

The field of corporate strategy is a well established major in business administration and business leadership. It addresses the total enterprise and how various functions interact to achieve objectives. Thus while all enterprises encompass several common functions, e.g. human capital, information technology, and so on, they must also manage their distinct core business, whether that be banking, mining, whatever, or in the case of railways, moving goods and people to support their logistics and mobility needs. However, googling *railway corporate strategy* returned items dominated by the authors' enterprise and their publications. The unique contribution of the present research stream is therefore a grounded

To comprehend railway positioning, it is helpful to examine railway competitiveness vis-àvis that of other transport modes by considering their degrees-of-freedom-of-movability. Three degrees-of-freedom-of-movability (e.g. aerial- and submarine transport) offer high, spatial movability, but at relatively high cost. Next, two degrees-of-freedom-of-movability (e.g. unguided surface transport) offer lower, surface movability at lower cost. Last, one degree-of-freedom–of-movability (e.g. guided surface transport) offers only limited, linear movability, back and forth on its guideway. To the extent that limited movability reduces the value of their offering, guided surface transport modes such as railways must offer compensating advantages to compete effectively against other modes that offer higher

Axiomatically, such compensating advantages should inhere in technologies that differentiate guided surface transport from other transport modes. A vehicle-guideway pair ensures precise application of vertical loads, and safe application of lateral loads: Wheel-rail contact mechanics develop vertical- and lateral force components, technologies named *Supporting* and *Guiding* by Vuchic (2007: 449), which can sustain respectively heavy axle load and high speed. One may leverage Supporting and Guiding by combining two or many vehicles, to scale capacity as required, a technology the authors named *Coupling*. Supporting, Guiding, and Coupling are the three *genetic technologies* that distinguish guided surface transport from all other transport modes: *Inherent competitiveness* is defined here, and

is measurable as, the extent to which such modes exploit their genetic technologies.

in §3.3 and §3.5. Until then, this chapter addresses railways.

Note that the preceding two paragraphs have been generalized to guided surface transport, of which railways is a subset. Other guided surface transport modes also exist, which do not use steel-wheel-on-steel rail. We shall return to them in the context of urban guided transit

Cross-breaking Bearing and Guiding, in Figure 1, yields four railway market spaces. For this purpose, speed in tens of km/h is low speed, speed in hundreds of km/h is high speed; axle load above 25 tonnes is heavy. Three market spaces feature high competitiveness, by exploiting two or more of rail's genetic technologies—namely Heavy Haul (Supporting and Coupling), High-speed Intercity (Guiding and Coupling), and Heavy Intermodal1 or Double

1Heavy intermodal traffic has heavy axle load: It is distinct from light traffic that simply transfers from

understanding of corporate strategy with respect to the core business of railways.

**2. Railway positioning** 

one mode to another.

**2.1 Competitiveness fundamentals** 

movability, including door-to-door transport.

Stack (Supporting, Guiding, and Coupling). All three have demonstrated robust sustainability in competition with other transport modes.

Fig. 1. Railway market spaces by Axle Load and Speed

The fourth market space is potentially weak—light axle load combined with low speed exploits neither Supporting nor Guiding genetic technology. Failure to exploit the remaining genetic technology, Coupling, in general freight- and classic long-distance passenger rail applications exacerbates their weakness, hence competitors erode their markets. Depending on whether economic-, political-, or social objectives determine their destiny, such railways are respectively eliminated, protected, or subsidized.

### **2.2 The special case of urban rail**

Human passengers as payload do not achieve high axle load by railway standards, even in double deck vehicles. Furthermore, the comfort criteria and physical laws pertaining to acceleration, coasting, retardation, and station dwell time, maximize the capacity function at around 80km/h. Therefore urban rail cannot maximally exploit either the Supporting- or the Guiding genetic technology: It is confined to a potentially weak market space, in which it can exploit only the Coupling genetic technology. By forming vehicles into trains, it can achieve shorter mean headways than would be attainable by the same number of autonomous vehicles, thereby maximizing passenger capacity per direction per unit time. However, where urban rail does not exploit that one and only genetic technology to realize its capacity potential, it is vulnerable to competition from the rubber-tyred modes Automated Guided Transit, Bus Rapid Transit, and Monorail. The maximum speed of all urban guided transit modes is similar, so winners must leverage headway to maximize capacity. With no pretence at high axle load, rubber tyred modes exploit their consistent high adhesion to encroach on rail's eminent domain.

### **2.3 The railway renaissance**

From bleak prospects in the first decade after World War II, railways in many countries have learned to exploit the competitive strengths that inhere in rail's genetic technologies. The following events mark the course of their learning:

In 1964, Japan introduced the world's first commercial high-speed intercity trains (Japanese Railway, 1964); they exploited the Guiding genetic technology to reach speeds of 210km/h, and leveraged high capacity by exploiting the Coupling genetic technology. Today, high-

such as airlines and logistics service providers. Corporate citizenship therefore provided a sensible perspective on which to found the research reported here. It supports a social

Railway countries have adapted themselves for competitiveness and sustainability to varying degrees in a globalized industry. Hence, in addition to rail's genetic technologies, which address their inherent competitiveness, it is necessary to control for setting variables, which influence their positioning. The research design must seamlessly compare railways in command economies with those in free economies, open access with vertical integration, heavy haul with transnational operators, and so on. It must also compare monolithic national railways, which may publish comprehensive statistics, with entities whose data are

Corporate citizenship is by definition an ongoing process that requires observations over time. Behaviour implicitly includes a time scale—snapshot data cannot observe it. A behavioural approach can naturally support the foregoing requirements. One of the authors developed a methodology for longitudinal railway corporate strategy research using large samples in a doctoral dissertation (Van der Meulen, 1994), which methodology underlies the

Fortuitously, the global population of cities and countries with railways is sufficiently small to avoid sampling, yet, using longitudinal research, at the same time sufficiently large to support multivariate statistical analysis. It has been mentioned that line haul- and urban rail are positioned differently, i.e. in respectively inherently competitive- and inherently weak market spaces. They were therefore researched separately, first line haul and thereafter urban rail. The necessary methodological distinctions start immediately below, and have

The authors formulated their research questions within the context of an enterprise's corporate citizenship, as represented by its Contribution to Society, Core Business, Social Investment, and Engagement in Public Policy, as well as resources deployed to set about its task. In respect of the three market spaces that demarcate line-haul railways, they hypothesized the existence of some number of underlying longitudinal, or time-dependent, relations among variables associated with positioning line haul railways. The research question was therefore: *Can one* 

In respect of urban rail, the market space is somewhat different. A subsidy is generally present, so the responsible authority tends to deal directly with public policy aspects. Furthermore, multiple guided transit modes in a city are not unusual, so urban transit solutions tend to be more complex. The authors therefore hypothesized that positioning the various urban guided transit modes in particular cities reflected attributes of their ever changing economic- and social setting vis-à-vis attributes of the various transit modes. Their research question was therefore *Which country- and city green- and socio-economic attributes and* 

been maintained throughout the rest of this chapter as appropriate.

*identify archetypal railway corporate citizenships within the global setting*?

*relations fit guided transit solutions to particular cities?* 

consolidated at a higher level, and with small operators whose data are confidential.

sciences behavioural approach, because human behaviour drives enterprises.

**3.2 Research in a dynamic, global setting** 

research reported here.

**3.3 The research questions** 

speed trains attain average speeds in excess of 300km/h, and move 20 000 passengers per hour per direction.

In 1972, a landmark article (Tracks to, 1972) recognized heavy haul as a distinct market space. By then, Supporting and Coupling technologies and equipment to Association of American Railroads specifications had spread abroad to dedicated railways conveying bulkcommodities. Today, heavy haul lines can move 400 million tonnes per year in trains of 300 cars or more.

In 1980, the United States' Staggers Act deregulated its railways: The ensuing wave of innovation among other triggered introduction of double stack container trains (Levinson, 2006). They enhanced inherent competitiveness through increasing axle load despite conveying low-density high-value freight in containers, and leveraged it further with the Guiding and Coupling genetic technologies.

In 1989, the fall of the Berlin Wall tipped the balance of power across the world toward those advocating democratic, consensual, free-market-oriented governance (Friedman, 2006), an ongoing process that stimulated economic globalization. In the railway supply industry, the resultant increased competition and trade rationalized many nationallyfragmented system integrators into fewer strong global brands. Concurrently, accelerating agglomeration in developing economies has expanded the urban rail market. The number of cities has proliferated by some seventy in the last decade.

Economic globalization has of course been transforming all four abovementioned railway market spaces: As examples, the *Global Rail Freight Conference 2007* in New Delhi reflected that transformation in its title, and World Congress on Railway Research 2008 reflected it in its theme *Towards a global railway.*

The foregoing four events revitalized railways in those countries that appreciated the imperative to enter as many of rail's inherently competitive market spaces as applied to them. Their accumulation across all railway countries has become known as the *railway renaissance*. It has precipitated a substantial body of data, able to support research into the modalities. However, even as the railway mode enters its third century as a strong competitor, many railways still have not integrated seamlessly into global logistics and intelligent mobility; they look different from one another, and even from many other global service industries. So how does one undertake research that will lead to some understanding of the differences among them?

### **3. Railway adaptation: A research paradigm**

### **3.1 Background**

When informally comparing railways, which had not joined the renaissance, to those that had, the latter seemed to have acquired a modicum of consistent identity, or *corporate citizenship*. The latter concerns an enterprise's profitability and sustainability; balancing stakeholder expectations, including those of customers, suppliers, and communities in which it operates; maintaining sustainable partnerships with all levels of government; and accepting its role in developing countries (World Economic, n.d.). Railways attain this standing when their corporate citizenship resembles that of other global service industries,

speed trains attain average speeds in excess of 300km/h, and move 20 000 passengers per

In 1972, a landmark article (Tracks to, 1972) recognized heavy haul as a distinct market space. By then, Supporting and Coupling technologies and equipment to Association of American Railroads specifications had spread abroad to dedicated railways conveying bulkcommodities. Today, heavy haul lines can move 400 million tonnes per year in trains of 300

In 1980, the United States' Staggers Act deregulated its railways: The ensuing wave of innovation among other triggered introduction of double stack container trains (Levinson, 2006). They enhanced inherent competitiveness through increasing axle load despite conveying low-density high-value freight in containers, and leveraged it further with the

In 1989, the fall of the Berlin Wall tipped the balance of power across the world toward those advocating democratic, consensual, free-market-oriented governance (Friedman, 2006), an ongoing process that stimulated economic globalization. In the railway supply industry, the resultant increased competition and trade rationalized many nationallyfragmented system integrators into fewer strong global brands. Concurrently, accelerating agglomeration in developing economies has expanded the urban rail market. The number of

Economic globalization has of course been transforming all four abovementioned railway market spaces: As examples, the *Global Rail Freight Conference 2007* in New Delhi reflected that transformation in its title, and World Congress on Railway Research 2008 reflected it in

The foregoing four events revitalized railways in those countries that appreciated the imperative to enter as many of rail's inherently competitive market spaces as applied to them. Their accumulation across all railway countries has become known as the *railway renaissance*. It has precipitated a substantial body of data, able to support research into the modalities. However, even as the railway mode enters its third century as a strong competitor, many railways still have not integrated seamlessly into global logistics and intelligent mobility; they look different from one another, and even from many other global service industries. So how does one undertake research that will lead to some

When informally comparing railways, which had not joined the renaissance, to those that had, the latter seemed to have acquired a modicum of consistent identity, or *corporate citizenship*. The latter concerns an enterprise's profitability and sustainability; balancing stakeholder expectations, including those of customers, suppliers, and communities in which it operates; maintaining sustainable partnerships with all levels of government; and accepting its role in developing countries (World Economic, n.d.). Railways attain this standing when their corporate citizenship resembles that of other global service industries,

hour per direction.

cars or more.

Guiding and Coupling genetic technologies.

its theme *Towards a global railway.*

**3.1 Background** 

understanding of the differences among them?

**3. Railway adaptation: A research paradigm** 

cities has proliferated by some seventy in the last decade.

such as airlines and logistics service providers. Corporate citizenship therefore provided a sensible perspective on which to found the research reported here. It supports a social sciences behavioural approach, because human behaviour drives enterprises.

### **3.2 Research in a dynamic, global setting**

Railway countries have adapted themselves for competitiveness and sustainability to varying degrees in a globalized industry. Hence, in addition to rail's genetic technologies, which address their inherent competitiveness, it is necessary to control for setting variables, which influence their positioning. The research design must seamlessly compare railways in command economies with those in free economies, open access with vertical integration, heavy haul with transnational operators, and so on. It must also compare monolithic national railways, which may publish comprehensive statistics, with entities whose data are consolidated at a higher level, and with small operators whose data are confidential.

Corporate citizenship is by definition an ongoing process that requires observations over time. Behaviour implicitly includes a time scale—snapshot data cannot observe it. A behavioural approach can naturally support the foregoing requirements. One of the authors developed a methodology for longitudinal railway corporate strategy research using large samples in a doctoral dissertation (Van der Meulen, 1994), which methodology underlies the research reported here.

Fortuitously, the global population of cities and countries with railways is sufficiently small to avoid sampling, yet, using longitudinal research, at the same time sufficiently large to support multivariate statistical analysis. It has been mentioned that line haul- and urban rail are positioned differently, i.e. in respectively inherently competitive- and inherently weak market spaces. They were therefore researched separately, first line haul and thereafter urban rail. The necessary methodological distinctions start immediately below, and have been maintained throughout the rest of this chapter as appropriate.

### **3.3 The research questions**

The authors formulated their research questions within the context of an enterprise's corporate citizenship, as represented by its Contribution to Society, Core Business, Social Investment, and Engagement in Public Policy, as well as resources deployed to set about its task. In respect of the three market spaces that demarcate line-haul railways, they hypothesized the existence of some number of underlying longitudinal, or time-dependent, relations among variables associated with positioning line haul railways. The research question was therefore: *Can one identify archetypal railway corporate citizenships within the global setting*?

In respect of urban rail, the market space is somewhat different. A subsidy is generally present, so the responsible authority tends to deal directly with public policy aspects. Furthermore, multiple guided transit modes in a city are not unusual, so urban transit solutions tend to be more complex. The authors therefore hypothesized that positioning the various urban guided transit modes in particular cities reflected attributes of their ever changing economic- and social setting vis-à-vis attributes of the various transit modes. Their research question was therefore *Which country- and city green- and socio-economic attributes and relations fit guided transit solutions to particular cities?* 

www.railcorpstrat.com/Downloads/feb2008/WCR2008%20Line%20Haul%20Operational%

Whatever the detail institutional arrangements, national governments typically either own railways, or regulate to varying degrees railways that they do not own, within their jurisdictions. Exceptions do of course exist where railway operations crisscross national boundaries by agreement or directive, as in the North American Free Trade Agreement and the European Union respectively. The authors therefore elected to examine railways by

Some railway attributes are independent of track gauge, but the latter does drive inherent competitiveness. There is no evidence that railways on track gauge of less than yard/meter/3'-6'' are sustainable: The authors therefore excluded data for narrower track gauges, irrespective of the gauge mix in a country. They used the Railways/Train Operators section of Railway Directory to define the set of line haul railways. The above criteria yielded 113 countries. Some of them included suburban and regional passenger operations, which are strictly not line-haul. However, the complementary set of global railway data is the City Railways section of Railway Directory, which the authors used for urban railways: Together these two sections represent the entire global population of railways. On that scale,

Observations were predicated on the natural affinity between corporate citizenship and public domain data. Metric data was extracted from Railway Directory (2002-2007), Jane's World Railways (2005-2006, 2007-2008), or the Internet, and non-metric data was extracted by content analysis from International Railway Journal and Railway Gazette International. The detail measurement methodology has been reported by Van der Meulen & Möller (2006, 2008b). The Internet was used liberally to verify data to ensure internal consistency. The longitudinal database, containing one hundred and thirteen line-haul railways by country, populated with data for the six years 2002-2007, for each railway, gave a population (and sample) size of 113 x 6 = 678 cases, and is available at www.railcorpstrat.com/Downloads/

The authors applied multivariate statistical analysis to the database to examine simultaneously relations among multiple variables, and multiple cases. They selected Factor Analysis, to analyze relations among a large number of variables and then to explain them in terms of a smaller number of latent variables, and Cluster Analysis, to reduce a large number of cases to a smaller number of clusters. Statgraphics Centurion XV was used to analyze the data. They culled variables with low communalities that contributed noise rather than insight (i.e. those that appeared in the Operational Definitions file, but which are absent from Table 1), after which the data set arrayed thirty-seven variables and 678 cases, for a total of 25 086 observations. Statistical analysis stops at the Factor Loading Matrix in Table 1, and at the Icicle Plot available at www.railcorpstrat.com/Downloads/WCRR2008%

they were disinclined to niggle about classification of boundary cases.

20Definitions.pdf.

country.

**3.4.2 Identification and selection of cases** 

**3.4.3 Construction of a database** 

WCRR2008%20Line%20Haul%20Database.xls.

**3.4.4 Statistical analysis** 

The two different research questions reflect the essential difference between positioning line haul rail in market spaces where rail can be inherently competitive, versus positioning urban rail in a market space where it may be inherently uncompetitive. Nevertheless, the research design was set up to examine positioning, the action, and fit, the outcome, over time in both situations.

### **3.4 Line haul railways**

### **3.4.1 Variables and their definitions**

For the purpose of this chapter, line haul railways transport goods or persons over long distances or between cities. The authors measured the interaction between them and their settings by the following variables that reflected rail's corporate citizenship as well as its genetic technologies and their naturally competitive market spaces. Pending the outcome of statistical analysis, they were placed in the following groups for convenience:

Business Group represents the way in which railways deal with their task (Variables Infrastructure Operator Diversity, Train Operator Diversity, Information Technology Leverage, Total Road Network-, Motorways- and Paved Roads Percentage).

Competitiveness Group represents the way in which railways position themselves to compete in their chosen or allotted market spaces (Variables Research & Development Level, Relative Maximum Axle Load, Relative Maximum Speed, Distributed Power Presence, Heavy Haul Presence, High-speed Intercity Presence, Heavy Intermodal Presence, Motive Power Type, and Attitude to Competition).

Contribution Group describes the railways' contribution to their society (Variables Network Coverage, Transport Task—Freight- and Passenger Traffic Volume, Employment Created, and Initiative Source).

*Networkability Group* describes the extent and gauge of track, and the contiguous network beyond a country's borders (Variables *Narrow-, Standard-, and Broad Gauge; Networkability;*  and *Strategic Horizon*).

Ownership Group describes industry structure (Infrastructure-operations Separation, Infrastructure- and Rolling Stock Ownership Locus, and Infrastructure- and Rolling Stock Commitment Horizon).

Society Group describes the railway setting (Variables Country (Name), Economic Freedom, Population, Gross National Income, Physical Size, Determinism, and Climate-change Position).

Sustainability Group describes adaptation and fit (Variables Infrastructure- and Rolling Stock Investment Capacity, Stakeholder Satisfaction Level, Service Reputation, Safety Reputation, Subsidy Influence).

**Time Group** represents passage of time, a prerequisite for longitudinal research (Variable *Calendar Year*).

The operational definitions of the foregoing forty-four variables, plus their measurement scales, exceed the space available in this chapter: Full details may be found at

The two different research questions reflect the essential difference between positioning line haul rail in market spaces where rail can be inherently competitive, versus positioning urban rail in a market space where it may be inherently uncompetitive. Nevertheless, the research design was set up to examine positioning, the action, and fit, the outcome, over

For the purpose of this chapter, line haul railways transport goods or persons over long distances or between cities. The authors measured the interaction between them and their settings by the following variables that reflected rail's corporate citizenship as well as its genetic technologies and their naturally competitive market spaces. Pending the outcome of

Business Group represents the way in which railways deal with their task (Variables Infrastructure Operator Diversity, Train Operator Diversity, Information Technology

Competitiveness Group represents the way in which railways position themselves to compete in their chosen or allotted market spaces (Variables Research & Development Level, Relative Maximum Axle Load, Relative Maximum Speed, Distributed Power Presence, Heavy Haul Presence, High-speed Intercity Presence, Heavy Intermodal Presence,

Contribution Group describes the railways' contribution to their society (Variables Network Coverage, Transport Task—Freight- and Passenger Traffic Volume, Employment Created,

*Networkability Group* describes the extent and gauge of track, and the contiguous network beyond a country's borders (Variables *Narrow-, Standard-, and Broad Gauge; Networkability;* 

Ownership Group describes industry structure (Infrastructure-operations Separation, Infrastructure- and Rolling Stock Ownership Locus, and Infrastructure- and Rolling Stock

Society Group describes the railway setting (Variables Country (Name), Economic Freedom, Population, Gross National Income, Physical Size, Determinism, and Climate-change

Sustainability Group describes adaptation and fit (Variables Infrastructure- and Rolling Stock Investment Capacity, Stakeholder Satisfaction Level, Service Reputation, Safety

**Time Group** represents passage of time, a prerequisite for longitudinal research (Variable

The operational definitions of the foregoing forty-four variables, plus their measurement scales, exceed the space available in this chapter: Full details may be found at

statistical analysis, they were placed in the following groups for convenience:

Leverage, Total Road Network-, Motorways- and Paved Roads Percentage).

time in both situations.

**3.4 Line haul railways** 

and Initiative Source).

and *Strategic Horizon*).

Commitment Horizon).

Reputation, Subsidy Influence).

Position).

*Calendar Year*).

**3.4.1 Variables and their definitions** 

Motive Power Type, and Attitude to Competition).

www.railcorpstrat.com/Downloads/feb2008/WCR2008%20Line%20Haul%20Operational% 20Definitions.pdf.

### **3.4.2 Identification and selection of cases**

Whatever the detail institutional arrangements, national governments typically either own railways, or regulate to varying degrees railways that they do not own, within their jurisdictions. Exceptions do of course exist where railway operations crisscross national boundaries by agreement or directive, as in the North American Free Trade Agreement and the European Union respectively. The authors therefore elected to examine railways by country.

Some railway attributes are independent of track gauge, but the latter does drive inherent competitiveness. There is no evidence that railways on track gauge of less than yard/meter/3'-6'' are sustainable: The authors therefore excluded data for narrower track gauges, irrespective of the gauge mix in a country. They used the Railways/Train Operators section of Railway Directory to define the set of line haul railways. The above criteria yielded 113 countries. Some of them included suburban and regional passenger operations, which are strictly not line-haul. However, the complementary set of global railway data is the City Railways section of Railway Directory, which the authors used for urban railways: Together these two sections represent the entire global population of railways. On that scale, they were disinclined to niggle about classification of boundary cases.

### **3.4.3 Construction of a database**

Observations were predicated on the natural affinity between corporate citizenship and public domain data. Metric data was extracted from Railway Directory (2002-2007), Jane's World Railways (2005-2006, 2007-2008), or the Internet, and non-metric data was extracted by content analysis from International Railway Journal and Railway Gazette International. The detail measurement methodology has been reported by Van der Meulen & Möller (2006, 2008b). The Internet was used liberally to verify data to ensure internal consistency. The longitudinal database, containing one hundred and thirteen line-haul railways by country, populated with data for the six years 2002-2007, for each railway, gave a population (and sample) size of 113 x 6 = 678 cases, and is available at www.railcorpstrat.com/Downloads/ WCRR2008%20Line%20Haul%20Database.xls.

#### **3.4.4 Statistical analysis**

The authors applied multivariate statistical analysis to the database to examine simultaneously relations among multiple variables, and multiple cases. They selected Factor Analysis, to analyze relations among a large number of variables and then to explain them in terms of a smaller number of latent variables, and Cluster Analysis, to reduce a large number of cases to a smaller number of clusters. Statgraphics Centurion XV was used to analyze the data. They culled variables with low communalities that contributed noise rather than insight (i.e. those that appeared in the Operational Definitions file, but which are absent from Table 1), after which the data set arrayed thirty-seven variables and 678 cases, for a total of 25 086 observations. Statistical analysis stops at the Factor Loading Matrix in Table 1, and at the Icicle Plot available at www.railcorpstrat.com/Downloads/WCRR2008%

Variable Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 Factor 7 No factor Factor 8 Relative Maximum Speed *0.78* 0.34 -0.02 0.26 0.13 -0.01 0.02 -0.03 0.21 Gross National Income *0.76* 0.03 0.22 0.22 0.36 -0.01 0.15 -0.01 0.03 Motorways *0.76* 0.10 0.14 0.15 0.12 0.01 0.01 -0.26 0.11 Information Technology Leverage *0.70* 0.18 0.24 0.07 0.24 -0.01 0.20 0.06 0.10 High-speed Intercity Presence *0.66* 0.28 0.03 -0.02 0.08 -0.10 0.04 -0.14 0.35 Country Economic Freedom *0.64* -0.22 0.31 -0.15 0.30 -0.11 0.18 0.21 -0.12 Paved Roads *0.63* 0.13 -0.17 0.42 -0.04 -0.02 -0.01 0.14 0.01 Research and Development Level *0.56* 0.46 0.37 -0.08 0.11 -0.01 0.06 -0.08 0.32 Electric Traction *0.47* 0.42 -0.19 0.33 0.24 0.03 -0.02 0.27 -0.04 Network Coverage 0.23 *0.85* 0.27 0.03 0.20 0.02 0.02 0.08 0.11 Country Population -0.05 *0.84* 0.12 -0.31 -0.10 0.00 0.04 -0.14 0.03 Employee Count 0.31 *0.81* -0.02 0.28 -0.02 0.04 -0.02 0.18 0.08 Total Road Network 0.21 *0.80* 0.32 -0.13 0.19 0.04 0.06 0.04 0.02 Passenger Traffic Volume 0.60 *0.69* 0.00 0.05 0.16 -0.03 0.04 0.15 0.07 Country Physical Size -0.35 *0.62* 0.40 -0.32 -0.01 0.01 -0.01 0.03 0.12 Freight Traffic Volume 0.39 *0.62* 0.35 0.27 0.16 0.01 0.02 0.24 0.15 Heavy Intermodal Presence 0.03 0.09 *0.82* 0.08 -0.02 0.09 0.06 -0.09 0.08 Distributed Power Presence 0.04 0.25 *0.76* -0.01 0.00 0.04 0.05 0.04 0.16 Heavy Haul Presence 0.03 0.36 *0.73* -0.03 -0.04 0.12 0.03 0.07 0.22 Infrastructure Ownership Locus 0.04 0.05 *0.67* -0.29 0.31 -0.13 -0.03 0.01 -0.16 Relative Maximum Axle Load 0.15 0.09 *0.65* 0.47 0.13 0.01 -0.17 0.22 0.18 Infrastructure Operator Diversity 0.22 0.05 *0.62* 0.12 -0.11 0.01 0.03 -0.23 -0.13 Narrow Gauge -0.09 0.20 -0.04 *-0.84* 0.05 -0.04 0.00 -0.12 0.01 Networkability 0.29 0.04 0.00 *0.76* 0.22 0.04 0.00 -0.07 -0.03 Standard Gauge 0.33 0.30 0.24 *0.49* 0.27 0.01 -0.01 -0.47 0.08 Infrastructure-operations Separation 0.29 0.12 -0.11 0.18 *0.81* -0.05 0.07 0.04 0.18 Train Operator Diversity 0.31 0.12 -0.05 0.16 *0.80* -0.04 0.12 -0.01 0.16 Rolling Stock Ownership Locus 0.17 0.09 0.47 -0.16 *0.68* -0.16 0.12 -0.06 -0.03 Rolling Stock Commitment Horizon 0.00 0.00 0.09 0.01 -0.08 *0.90* -0.01 0.02 -0.02 Infrastructure Commitment Horizon -0.07 0.03 0.03 0.06 -0.05 *0.90* 0.01 0.06 -0.05 Calendar Year -0.03 -0.04 -0.02 -0.01 0.07 0.05 *0.81* -0.03 0.05 Climate-change Position 0.26 -0.04 -0.03 -0.20 0.17 0.03 *0.59* 0.23 -0.08 Rolling Stock Investment Capacity 0.18 0.41 0.17 0.21 -0.01 -0.04 *0.48* -0.21 0.20 Infrastructure Investment Capacity 0.15 0.41 0.14 0.12 0.05 -0.18 *0.46* -0.02 0.01 Broad Gauge -0.02 0.23 0.00 0.13 0.02 0.09 0.04 *0.88* 0.04 Attitude to Competition 0.16 0.13 0.05 0.13 0.07 -0.17 0.14 0.03 *0.72* Subsidy Influence 0.17 0.07 0.14 -0.12 0.13 0.08 -0.06 0.00 *0.67*

For the purpose of this chapter, urban guided transit offers mobility to persons within cities. The authors measured the fit between guided transit modes and their settings by the following variables that reflected their corporate citizenship. Pending the outcome of

**Business Group** represents the amount of competition or support that urban guided transit faces in performing its task (variables Bus-, Car-, and Motorcycle Populations; Fuel Price;

**City Group** describes the close urban setting (variables City Name; Surface Area; Metropolitan Population; Population Growth Rate; World Cities Score; Green Cities Score;

**Contribution Group** describes guided transit's contribution to its society (variables Inaugural Year, Number of Operators, Status of Project, Network Coverage, Rolling Stock Fleet, Passenger Journeys, Number of Routes, Number of Stations, and Employee Count). They were measured separately for each of the urban guided transit modes, namely Heavy Metro, Light Rail and Trams, Light Metro, Automated Guided Transit, Monorail, and Bus Rapid Transit.

statistical analysis, they were placed in the following groups for convenience:

Motorways, Highways; and Secondary plus Other Roads Distance).

Table 1. The line haul factor loading matrix

**3.5.2 Variables and their definitions** 

and Smart Card Application).

20Line%20Haul%20Icicle%20plot.xls . Deeper discussion on the statistical intervention is available in Van der Meulen & Möller (2008b). Latent variable- and cluster names, and the following discussion, reflect the authors' interpretation of their knowledge of the variables in the research setting.

### **3.5 Urban guided transit**

### **3.5.1 Enlarging the scope**

The authors next applied broadly the same research methodology to urban rail. Although a previous paper (Van der Meulen & Möller, 2008a) passed peer review and revealed a constructive distinction between positioning urban rail in cities in developed countries and in developing countries, they were less than satisfied with its overall predictive validity. Importantly, the research did not address and therefore could not explain the ascent of the rubber-tyred competitors Automated Guided Transit (Vuchic, 2007, p.455), Bus Rapid Transit, and Monorail, against which heavy- and light rail must compete for investment funding. The authors therefore enlarged the scope of their research in the light-axle-load, low-speed market space from urban rail to urban guided transit, by including the modes mentioned below (Van der Meulen & Möller, 2012):

**Heavy Metro** maximally exploits rail's genetic technologies in urban settings. Included are the rubber-tyred systems found on some Paris Métro lines, and similar systems elsewhere: Despite rubber-tyred Supporting and Guiding, their gleaming running rails and wheel flanges indicate that these steel components are not redundant.

**Light Rail and trams** were merged, as neither attains fully controlled right of way. By definition, at 10-11 tonnes/axle, exploitation of rail's Supporting genetic technology is weak. Likewise the built environment constrains Guiding, and typically only a small number of vehicles are coupled: Technically, their inherent competitiveness is marginal.

**Light Metro** takes Light Rail to the next level with fully segregated right-of-way. Light axle load minimizes the cost of elevated structures, while small vehicle profiles minimize the cost of underground works. Driverless operation offers consistent performance and operational flexibility free from the labour issues that disturb manned systems.

**Automated Guided Transit** e.g. VAL and similar, offers consistently higher acceleration and higher retardation than steel-on-steel, although rubber tyres constrain axle load. As for automated Light Metro, light axle load and small vehicle profile minimize the cost of civil works. Automated operation offers consistent, precise high performance.

**Monorail** excels where pre-existing built environment admits only elevated structures with small physical footprint. Transit-grade monorails have converged on rubber-tyred straddle systems. Capacity and performance is comparable to Automated Guided Transit: Once again, automated operation offers consistent, precise high performance.

**Bus Rapid Transit** reputedly rolls out faster at lower cost than comparable rail systems. Its inclusion in guided transit is justified by its narrow concrete runway to support relatively heavy 12-13 tonne axle load, plus emerging virtual guidance by lane tracking systems. Biarticulated buses even emulate rail's Coupling genetic technology.

76 Infrastructure Design, Signalling and Security in Railway

20Line%20Haul%20Icicle%20plot.xls . Deeper discussion on the statistical intervention is available in Van der Meulen & Möller (2008b). Latent variable- and cluster names, and the following discussion, reflect the authors' interpretation of their knowledge of the variables

The authors next applied broadly the same research methodology to urban rail. Although a previous paper (Van der Meulen & Möller, 2008a) passed peer review and revealed a constructive distinction between positioning urban rail in cities in developed countries and in developing countries, they were less than satisfied with its overall predictive validity. Importantly, the research did not address and therefore could not explain the ascent of the rubber-tyred competitors Automated Guided Transit (Vuchic, 2007, p.455), Bus Rapid Transit, and Monorail, against which heavy- and light rail must compete for investment funding. The authors therefore enlarged the scope of their research in the light-axle-load, low-speed market space from urban rail to urban guided transit, by including the modes

**Heavy Metro** maximally exploits rail's genetic technologies in urban settings. Included are the rubber-tyred systems found on some Paris Métro lines, and similar systems elsewhere: Despite rubber-tyred Supporting and Guiding, their gleaming running rails and wheel

**Light Rail and trams** were merged, as neither attains fully controlled right of way. By definition, at 10-11 tonnes/axle, exploitation of rail's Supporting genetic technology is weak. Likewise the built environment constrains Guiding, and typically only a small number of

**Light Metro** takes Light Rail to the next level with fully segregated right-of-way. Light axle load minimizes the cost of elevated structures, while small vehicle profiles minimize the cost of underground works. Driverless operation offers consistent performance and operational

**Automated Guided Transit** e.g. VAL and similar, offers consistently higher acceleration and higher retardation than steel-on-steel, although rubber tyres constrain axle load. As for automated Light Metro, light axle load and small vehicle profile minimize the cost of civil

**Monorail** excels where pre-existing built environment admits only elevated structures with small physical footprint. Transit-grade monorails have converged on rubber-tyred straddle systems. Capacity and performance is comparable to Automated Guided Transit: Once

**Bus Rapid Transit** reputedly rolls out faster at lower cost than comparable rail systems. Its inclusion in guided transit is justified by its narrow concrete runway to support relatively heavy 12-13 tonne axle load, plus emerging virtual guidance by lane tracking systems. Bi-

in the research setting.

**3.5 Urban guided transit 3.5.1 Enlarging the scope** 

mentioned below (Van der Meulen & Möller, 2012):

flanges indicate that these steel components are not redundant.

flexibility free from the labour issues that disturb manned systems.

works. Automated operation offers consistent, precise high performance.

again, automated operation offers consistent, precise high performance.

articulated buses even emulate rail's Coupling genetic technology.

vehicles are coupled: Technically, their inherent competitiveness is marginal.


Table 1. The line haul factor loading matrix

### **3.5.2 Variables and their definitions**

For the purpose of this chapter, urban guided transit offers mobility to persons within cities. The authors measured the fit between guided transit modes and their settings by the following variables that reflected their corporate citizenship. Pending the outcome of statistical analysis, they were placed in the following groups for convenience:

**Business Group** represents the amount of competition or support that urban guided transit faces in performing its task (variables Bus-, Car-, and Motorcycle Populations; Fuel Price; Motorways, Highways; and Secondary plus Other Roads Distance).

**City Group** describes the close urban setting (variables City Name; Surface Area; Metropolitan Population; Population Growth Rate; World Cities Score; Green Cities Score; and Smart Card Application).

**Contribution Group** describes guided transit's contribution to its society (variables Inaugural Year, Number of Operators, Status of Project, Network Coverage, Rolling Stock Fleet, Passenger Journeys, Number of Routes, Number of Stations, and Employee Count). They were measured separately for each of the urban guided transit modes, namely Heavy Metro, Light Rail and Trams, Light Metro, Automated Guided Transit, Monorail, and Bus Rapid Transit.

Where necessary, raw data for agglomerations with more than one guided transit system were adjusted to match them to the population and area that they served. Details of the

The authors constructed a new, dedicated, urban guided transit database using the variables and cases mentioned above. The Microsoft Excel file comprises two complementary data subsets, namely Countries and Cities, and is available at www.railcorpstrat.com/ Downloads/Sep2011/TRA%202012%20Database%20and%20Factor%20Loading%20Matrice s.xls. It gathered 330 cities with guided transit in sixty-eight countries, each with four years' data for the period 2009-2012, for a total of 1320 cases. The database thus contains (1320

In previous research, Van der Meulen & Möller (2008a) had used factor analysis to reduce the initial variables to a smaller set of latent variables. However, the many variables required to describe country settings in sufficient detail tended to unduly dominate some of the latent variables. Therefore, reflecting the research question, exploratory factor analysis was first undertaken separately for Country- and for City descriptive variables, using Statgraphics Centurion XV software. From the initial 36 country variables, it found seven latent variables, namely *Country Stature*, *Economic Development Level*, *Energy Demand Level* and alter ego *Alternative Energy Acceptance*, *Services Contribution to GDP*; *Trade Contribution to GDP*, and *Societal Development Level*. From the initial 60 city variables, it also found seven latent variables, namely *Heavy Metro Position*, *Automated Guided Transit Position*, *Monorail Position*, *Light Metro Position*, *Light Rail Position*, and *Green City Impediments*. The authors named the latent variables in the light of the variables that loaded onto them, within the context of the urban rail industry setting: The separate factor loading matrices are available at www.railcorpstrat.com/ Downloads/Sep2011/TRA%202012%20Database%20and%20Factor%20Loading%20Matrices. xls, while a diagram showing which variables by name loaded onto each Country- and City latent variable is available at www.railcorpstrat.com/Downloads/Sep2011/TRA%202012% 20Latent%20Variables%20Diagram.pdf. Thereafter, structural equation modeling using EQS 6.1 software found relations among these latent variables. The path diagram in Figure 2 shows the significant standardized regression coefficients as arrows pointing to the dependent latent variables. Positive correlations indicate support, negative correlations indicate opposition. Interpretation follows in §4.2.1. A detailed report on the structural equation modeling intervention is available on the authors' website at www.railcorpstrat.com/Downloads/

Exploratory factor analysis extracted seven latent variables plus one single variable, shown in boldface italics in Table 1: They represent activities by which railways position their

affected agglomerations accompany the applicable operational definitions.

**3.5.4 Construction of a database** 

**3.5.5 Statistical analysis** 

cases) x (98 variables) = 129 360 observations.

Sep2011/TRA%202012%20SEM% 20Report.pdf .

**4. Findings** 

**4.1 Line haul railways** 

**4.1.1 The factor loading matrix** 

**Country group** describes the broad national setting (variables Country Name; Agricultural Land; Agriculture, Value Added; Alternative and Nuclear Energy; CO2 Emissions; Electric Power Consumption; Energy Use; Exports of Goods and Services; Foreign Direct Investment; Forest Area; GDP; GNI per Capita; Gross Capital Formation; High-technology Exports; Imports of Goods and Services; Improved Sanitation Facilities, Urban; Improved Water Source, Urban; Industry, Value Added; Inflation, GDP Deflator; Internet Users; Life Expectancy at Birth; Merchandise Trade; Mobile Cellular Subscriptions; Out-of-pocket Health Expenditure; Population Growth; Population, Total; Public Spending on Education; Services, Value Added; and Surface Area). These variables were selected from World Bank Development Indicators: Themes identified by content analysis of Time magazine for the period July 2009 to June 2010 suggested the twenty-eight indicators actually used out of 298 available.

**Society Group** describes governance and societal attributes of the setting (variables *Economic Freedom Index* and *Income Inequality*).

**Time Group** represents passage of time, a prerequisite for longitudinal research (variable *Calendar Year*).

Operational definitions, measurement scales, and source references, either documentary or uniform resource locator, for each of the abovementioned variables, are available at www.railcorpstrat.com/Downloads/Sep2011/TRA%202012%20Operational%20Definitions. pdf.

To emphasize the difference between the line-haul rail and urban guided transit datasets, note that the latter does not include the Competitiveness-, Networkability-, and Ownership groups of the former. Urban guided transit was researched separately because it occupies a potentially low competitiveness market space; it does not naturally network with other railways and frequently cannot; and it is generally vertically integrated under a public authority, so ownership aspects recede into the background. Furthermore, urban rail responds to authority initiative rather than market initiative as more generally applies to line haul rail: Subsidies are generally present so sustainability is inherently secure. It was therefore not considered necessary to describe and measure subsidy and sustainability.

### **3.5.3 Identification and selection of cases**

The research included the entire population of cities for which sufficient data could be found to populate the database in respect of the transit modes that served them. The City Railways section of Railway Directory (2009-2011) defined a minimum set of urban railways. Cities with one or more of automated guided transit, bus rapid transit, and monorail were added from websites listed under the applicable operational definitions at www.railcorpstrat.com/Downloads/Sep2011/TRA%202012%20Operational%20Definitions. pdf.

The longitudinal research design captured the adaptation dynamics of the global urban transit industry for the three consecutive years 2009-2011. To add a fourth, projected year, 2012, greenfields- and brownfields projects were also included, their various stages of progress measured on a five-point scale (Proposed 1, Feasibility Study 2, In Design 3, Under Construction 4, and Operational 5). The latter value of course also applied to all existing systems for the years 2009-2011.

**Country group** describes the broad national setting (variables Country Name; Agricultural Land; Agriculture, Value Added; Alternative and Nuclear Energy; CO2 Emissions; Electric Power Consumption; Energy Use; Exports of Goods and Services; Foreign Direct Investment; Forest Area; GDP; GNI per Capita; Gross Capital Formation; High-technology Exports; Imports of Goods and Services; Improved Sanitation Facilities, Urban; Improved Water Source, Urban; Industry, Value Added; Inflation, GDP Deflator; Internet Users; Life Expectancy at Birth; Merchandise Trade; Mobile Cellular Subscriptions; Out-of-pocket Health Expenditure; Population Growth; Population, Total; Public Spending on Education; Services, Value Added; and Surface Area). These variables were selected from World Bank Development Indicators: Themes identified by content analysis of Time magazine for the period July 2009 to June 2010

**Society Group** describes governance and societal attributes of the setting (variables

**Time Group** represents passage of time, a prerequisite for longitudinal research (variable

Operational definitions, measurement scales, and source references, either documentary or uniform resource locator, for each of the abovementioned variables, are available at www.railcorpstrat.com/Downloads/Sep2011/TRA%202012%20Operational%20Definitions.

To emphasize the difference between the line-haul rail and urban guided transit datasets, note that the latter does not include the Competitiveness-, Networkability-, and Ownership groups of the former. Urban guided transit was researched separately because it occupies a potentially low competitiveness market space; it does not naturally network with other railways and frequently cannot; and it is generally vertically integrated under a public authority, so ownership aspects recede into the background. Furthermore, urban rail responds to authority initiative rather than market initiative as more generally applies to line haul rail: Subsidies are generally present so sustainability is inherently secure. It was therefore not considered necessary to describe and measure subsidy and sustainability.

The research included the entire population of cities for which sufficient data could be found to populate the database in respect of the transit modes that served them. The City Railways section of Railway Directory (2009-2011) defined a minimum set of urban railways. Cities with one or more of automated guided transit, bus rapid transit, and monorail were added from websites listed under the applicable operational definitions at www.railcorpstrat.com/Downloads/Sep2011/TRA%202012%20Operational%20Definitions.

The longitudinal research design captured the adaptation dynamics of the global urban transit industry for the three consecutive years 2009-2011. To add a fourth, projected year, 2012, greenfields- and brownfields projects were also included, their various stages of progress measured on a five-point scale (Proposed 1, Feasibility Study 2, In Design 3, Under Construction 4, and Operational 5). The latter value of course also applied to all existing

suggested the twenty-eight indicators actually used out of 298 available.

*Economic Freedom Index* and *Income Inequality*).

**3.5.3 Identification and selection of cases** 

systems for the years 2009-2011.

*Calendar Year*).

pdf.

pdf.

Where necessary, raw data for agglomerations with more than one guided transit system were adjusted to match them to the population and area that they served. Details of the affected agglomerations accompany the applicable operational definitions.

### **3.5.4 Construction of a database**

The authors constructed a new, dedicated, urban guided transit database using the variables and cases mentioned above. The Microsoft Excel file comprises two complementary data subsets, namely Countries and Cities, and is available at www.railcorpstrat.com/ Downloads/Sep2011/TRA%202012%20Database%20and%20Factor%20Loading%20Matrice s.xls. It gathered 330 cities with guided transit in sixty-eight countries, each with four years' data for the period 2009-2012, for a total of 1320 cases. The database thus contains (1320 cases) x (98 variables) = 129 360 observations.

### **3.5.5 Statistical analysis**

In previous research, Van der Meulen & Möller (2008a) had used factor analysis to reduce the initial variables to a smaller set of latent variables. However, the many variables required to describe country settings in sufficient detail tended to unduly dominate some of the latent variables. Therefore, reflecting the research question, exploratory factor analysis was first undertaken separately for Country- and for City descriptive variables, using Statgraphics Centurion XV software. From the initial 36 country variables, it found seven latent variables, namely *Country Stature*, *Economic Development Level*, *Energy Demand Level* and alter ego *Alternative Energy Acceptance*, *Services Contribution to GDP*; *Trade Contribution to GDP*, and *Societal Development Level*. From the initial 60 city variables, it also found seven latent variables, namely *Heavy Metro Position*, *Automated Guided Transit Position*, *Monorail Position*, *Light Metro Position*, *Light Rail Position*, and *Green City Impediments*. The authors named the latent variables in the light of the variables that loaded onto them, within the context of the urban rail industry setting: The separate factor loading matrices are available at www.railcorpstrat.com/ Downloads/Sep2011/TRA%202012%20Database%20and%20Factor%20Loading%20Matrices. xls, while a diagram showing which variables by name loaded onto each Country- and City latent variable is available at www.railcorpstrat.com/Downloads/Sep2011/TRA%202012% 20Latent%20Variables%20Diagram.pdf. Thereafter, structural equation modeling using EQS 6.1 software found relations among these latent variables. The path diagram in Figure 2 shows the significant standardized regression coefficients as arrows pointing to the dependent latent variables. Positive correlations indicate support, negative correlations indicate opposition. Interpretation follows in §4.2.1. A detailed report on the structural equation modeling intervention is available on the authors' website at www.railcorpstrat.com/Downloads/ Sep2011/TRA%202012%20SEM% 20Report.pdf .

### **4. Findings**

### **4.1 Line haul railways**

### **4.1.1 The factor loading matrix**

Exploratory factor analysis extracted seven latent variables plus one single variable, shown in boldface italics in Table 1: They represent activities by which railways position their

railways, illustrate strong performance in particular market spaces. China's Freight- and Passenger Dedicated Lines, as well as India's Freight Dedicated Corridors and its emerging interest in high speed, illustrate ability to position railways in separate market spaces where opportunities are sufficient. By contrast, Europe has the population, area, and traffic to support substantial rail freight presence, yet substantial freight volume continues to move

The variables Heavy Intermodal Presence, Distributed Power Presence, Heavy Haul Presence, Infrastructure Ownership Locus, Relative Maximum Axle Load, and Infrastructure Operator Diversity all loaded positively onto the latent variable Positioning Freight Rail. It suggested that competitive freight railways, manifested by heavy intermodal-, heavy haul-, and distributed power presence, associated with high relative maximum axle load, privately owned infrastructure, and competing infrastructure operators. Examples are preservation of competition among railways in the North American Free Trade Agreement (Canada, Mexico, and the United States), and competition among

Highly competitive and sustainable positioning of freight railways is evident in the member countries of the International Heavy Haul Association (Australia, Brazil, Canada, China, India, Russia, South Africa, Sweden-Norway, and the United States); the double stack container trains of the North American Free Trade Agreement and Australia, China, India, and Saudi Arabia; and the emerging dedicated rail freight corridors in China and India (Dedicated Freight, 2010). By contrast, the constituents of *Positioning Freight Rail* are absent in Europe: Indeed the notion of a rail freight dedicated network has already been rejected (European Freight, 2008). It is therefore unsurprising that European rail freight struggles to compete with road freight (Heydenreich & Lehrmann, 2010), and it will be interesting to observe whether the evolving rail freight network (Jackson, 2011a) will turn

Interestingly, while both freight- and passenger railways use information technology, the latent variable *Information Technology Leverage* loaded only onto *Positioning Passenger Rail*, but is absent from *Positioning Freight Rail*. This suggested that freight rail's ideal corporate citizenship is that of competent carrier, and that logistics management belongs elsewhere. It supports the assertion that few railways have had the management capability to integrate acquired logistics companies efficiently and effectively (Reinhold & Gasparic,

The variables *Narrow Gauge* (negative), *Networkability*, and *Standard Gauge* loaded onto *Exploring Horizons*. The signs indicated that Narrow Gauge opposed networkability, while Standard Gauge reinforced it. Standard gauge track allows network- and train operators to explore ever-wider horizons. This is evident in several initiatives to connect the standard gauge networks of China, Europe and the Middle East. Note from Table 1 that Broad Gauge did not load onto any latent variable: From a networkability perspective it is an independent

by road, for reasons that will become clear in the next section.

parallel iron ore railways in Australia's Pilbara and Québec's North Shore.

**4.1.4 Positioning freight rail** 

the tide.

2009).

**4.1.5 Exploring horizons** 

variable, like the real world examples.

corporate citizenship in respect of their core business. Interpretation of the latent variables follows, with a reminder that §4.1 does not address urban rail: The latter will be addressed in §4.2.

### **4.1.2 Positioning passenger rail**

The variables Relative Maximum Speed, Gross National Income, Motorways Percentage, Information Technology Leverage, High-speed Intercity Presence, Economic Freedom, Paved Roads Percentage, R&D Level, and Electric Traction, all loaded positively onto the latent variable Positioning Passenger Rail. Their effects are therefore mutually supportive. Relative Maximum Speed anchors Positioning Passenger Rail. Based on rail's Guiding genetic technology, it enabled the railway renaissance to meet passengers' high-speed expectations on dedicated high speed lines. It even created new markets, such as China's high-speed overnight electric multiple unit services, which extend their reach beyond the constraints of a working day. Such innovations facilitate rail's contribution beyond peak oil, when high fuel prices could curb air travel.

Significantly, high national income and economic freedom associate concurrently with motorways and paved roads, and with high-technology passenger railway attributes, i.e. high relative maximum speed, information technology leverage, high-speed intercity presence, electric traction, and high R&D level. Evidently road competition stimulates highspeed railways, which require high technology to remain competitive. It is therefore noteworthy that the R&D function has migrated from railway operators to industry: Emerging brand- and model competition among system integrators is comparable to that between Airbus and Boeing in the aircraft industry.

### **4.1.3 Exploiting opportunities**

The variables Network Coverage, Country Population, Employment Creation, Total Road Network, Passenger Traffic Volume, Country Physical Size, and Freight Traffic Volume all loaded positively onto the latent variable Exploiting Opportunities. It suggested competitive and cooperative symbiotic relations among a country's transport infrastructure (Network Coverage and Total Road Network), its stature (Population and Physical Size), and rail's contribution to the economy (Employment Created, Passenger Traffic Volume, and Freight Traffic Volume). It demarcated the space in which Enlightened-, Progressive-, and Assertive Railways actualize their corporate citizenship as discussed in §4.1.10.

Large countries, or smaller countries with large contiguous networks beyond their borders, are prime railway locations. Notwithstanding that, the inherently competitive applications Heavy Haul, High-speed Intercity, and Heavy Intermodal, do not load on this latent variable: *Positioning Passenger Rail*, *Exploiting Opportunities*, and *Positioning Freight Rail*, therefore present mutually exclusive corporate citizenship positioning opportunities for railways.

Real world examples reflect both actualization and absence thereof. Large developing countries with high rail traffic volumes, such as Brazil, China, India and Russia are substantially redeveloping their railways to increase their contributions to their respective national transport tasks. Europe's high-speed railways, and North America's heavy freight railways, illustrate strong performance in particular market spaces. China's Freight- and Passenger Dedicated Lines, as well as India's Freight Dedicated Corridors and its emerging interest in high speed, illustrate ability to position railways in separate market spaces where opportunities are sufficient. By contrast, Europe has the population, area, and traffic to support substantial rail freight presence, yet substantial freight volume continues to move by road, for reasons that will become clear in the next section.

### **4.1.4 Positioning freight rail**

80 Infrastructure Design, Signalling and Security in Railway

corporate citizenship in respect of their core business. Interpretation of the latent variables follows, with a reminder that §4.1 does not address urban rail: The latter will be addressed

The variables Relative Maximum Speed, Gross National Income, Motorways Percentage, Information Technology Leverage, High-speed Intercity Presence, Economic Freedom, Paved Roads Percentage, R&D Level, and Electric Traction, all loaded positively onto the latent variable Positioning Passenger Rail. Their effects are therefore mutually supportive. Relative Maximum Speed anchors Positioning Passenger Rail. Based on rail's Guiding genetic technology, it enabled the railway renaissance to meet passengers' high-speed expectations on dedicated high speed lines. It even created new markets, such as China's high-speed overnight electric multiple unit services, which extend their reach beyond the constraints of a working day. Such innovations facilitate rail's contribution beyond peak oil,

Significantly, high national income and economic freedom associate concurrently with motorways and paved roads, and with high-technology passenger railway attributes, i.e. high relative maximum speed, information technology leverage, high-speed intercity presence, electric traction, and high R&D level. Evidently road competition stimulates highspeed railways, which require high technology to remain competitive. It is therefore noteworthy that the R&D function has migrated from railway operators to industry: Emerging brand- and model competition among system integrators is comparable to that

The variables Network Coverage, Country Population, Employment Creation, Total Road Network, Passenger Traffic Volume, Country Physical Size, and Freight Traffic Volume all loaded positively onto the latent variable Exploiting Opportunities. It suggested competitive and cooperative symbiotic relations among a country's transport infrastructure (Network Coverage and Total Road Network), its stature (Population and Physical Size), and rail's contribution to the economy (Employment Created, Passenger Traffic Volume, and Freight Traffic Volume). It demarcated the space in which Enlightened-, Progressive-, and Assertive

Large countries, or smaller countries with large contiguous networks beyond their borders, are prime railway locations. Notwithstanding that, the inherently competitive applications Heavy Haul, High-speed Intercity, and Heavy Intermodal, do not load on this latent variable: *Positioning Passenger Rail*, *Exploiting Opportunities*, and *Positioning Freight Rail*, therefore present mutually exclusive corporate citizenship positioning opportunities for

Real world examples reflect both actualization and absence thereof. Large developing countries with high rail traffic volumes, such as Brazil, China, India and Russia are substantially redeveloping their railways to increase their contributions to their respective national transport tasks. Europe's high-speed railways, and North America's heavy freight

in §4.2.

**4.1.2 Positioning passenger rail** 

when high fuel prices could curb air travel.

between Airbus and Boeing in the aircraft industry.

Railways actualize their corporate citizenship as discussed in §4.1.10.

**4.1.3 Exploiting opportunities** 

railways.

The variables Heavy Intermodal Presence, Distributed Power Presence, Heavy Haul Presence, Infrastructure Ownership Locus, Relative Maximum Axle Load, and Infrastructure Operator Diversity all loaded positively onto the latent variable Positioning Freight Rail. It suggested that competitive freight railways, manifested by heavy intermodal-, heavy haul-, and distributed power presence, associated with high relative maximum axle load, privately owned infrastructure, and competing infrastructure operators. Examples are preservation of competition among railways in the North American Free Trade Agreement (Canada, Mexico, and the United States), and competition among parallel iron ore railways in Australia's Pilbara and Québec's North Shore.

Highly competitive and sustainable positioning of freight railways is evident in the member countries of the International Heavy Haul Association (Australia, Brazil, Canada, China, India, Russia, South Africa, Sweden-Norway, and the United States); the double stack container trains of the North American Free Trade Agreement and Australia, China, India, and Saudi Arabia; and the emerging dedicated rail freight corridors in China and India (Dedicated Freight, 2010). By contrast, the constituents of *Positioning Freight Rail* are absent in Europe: Indeed the notion of a rail freight dedicated network has already been rejected (European Freight, 2008). It is therefore unsurprising that European rail freight struggles to compete with road freight (Heydenreich & Lehrmann, 2010), and it will be interesting to observe whether the evolving rail freight network (Jackson, 2011a) will turn the tide.

Interestingly, while both freight- and passenger railways use information technology, the latent variable *Information Technology Leverage* loaded only onto *Positioning Passenger Rail*, but is absent from *Positioning Freight Rail*. This suggested that freight rail's ideal corporate citizenship is that of competent carrier, and that logistics management belongs elsewhere. It supports the assertion that few railways have had the management capability to integrate acquired logistics companies efficiently and effectively (Reinhold & Gasparic, 2009).

### **4.1.5 Exploring horizons**

The variables *Narrow Gauge* (negative), *Networkability*, and *Standard Gauge* loaded onto *Exploring Horizons*. The signs indicated that Narrow Gauge opposed networkability, while Standard Gauge reinforced it. Standard gauge track allows network- and train operators to explore ever-wider horizons. This is evident in several initiatives to connect the standard gauge networks of China, Europe and the Middle East. Note from Table 1 that Broad Gauge did not load onto any latent variable: From a networkability perspective it is an independent variable, like the real world examples.

*Greening the Image* reinforces *Positioning Passenger Rail* and *Positioning Freight Rail*, but the benefits of a greener but uncompetitive mode are insignificant: The real challenge is to increase rail's competitiveness and thereby shift traffic to a greener mode by ecological adaptation. Rail's green credentials are undisputed: High speed railways accept steeper gradients that minimize environmental impact; heavy axle load attracts traffic from road to rail. State-of-the-art high-speed trains, and hybrid diesel locomotives with intelligent driving aids, reduce energy consumption per passenger journey and per ton-km. However, high speed and heavy axle load are uncomfortable bedfellows: Hence, in principle and to the extent that it is viable, physically separate dedicated freight- and passenger

Passenger trains tend to be lighter and more frequent, so recovery of their regenerated braking energy poses the lesser challenge. However, *Positioning Freight Rail* promotes longer and heavier trains, so recovery of their regenerated braking energy poses the greater challenge. In particular, many heavy haul railways descend from mine to port, and several are potentially net energy generators over the empty-loaded round trip (Van der Meulen, 2010). Maximum regenerative braking should be the point of departure. However, while onboard battery storage on hybrid diesel locomotives might be worthwhile, such systems cannot deal with a net surplus. Furthermore, regenerating all instantaneously surplus energy requires locomotives to control the same load on downgrades that they haul on upgrades. While this requires symmetrical up- and downgrades, many heavy haul routes have asymmetrical grades that oblige loaded trains to dissipate potential energy through dynamic or friction braking on descending grades, which reduces sustainability. Even if gradients supported full regenerative braking, matching a three phase supply grid to single phase overhead traction supply is the next challenge. This introduces the concept of smart

grids and open systems, which one hears about, but not yet in railway traction.

The variables *Attitude to Competition* and *Subsidy Influence* both loaded positively onto the latent variable *Constraining Downside*. It suggested that encouraging competition, while applying subsidy to influence the beneficiary, could constrain downside in adverse situations. A country's railway industry is only as competitive as government will allow or encourage. Where appropriate, governments traditionally subsidized railways directly, but their role is changing. Instead of simply assuming responsibility for runaway expenses, they now tend to recognize railways as worthy corporate citizens that they influence through instruments such as investing to raise competitiveness, public-private partnerships, tax incentives, and so on. Two examples are the United States' Passenger Rail Improvement and Investment Act of 2008 and its American Recovery and Reinvestment Act of 2009, which provided seed investment for high speed rail, to be matched by state funding for operational

Whereas factor analysis finds relations among the variables in a database, the multivariate procedure cluster analysis finds relations among the cases in a database, countries in this instance. Applying cluster analysis, to the 2007 data only, reduced the 113 countries in the

infrastructure promotes greening.

**4.1.9 Constraining downside** 

support (Boardman, 2010).

**4.1.10 Cluster analysis** 

By contrast, many narrow gauge railways must forego participation in long-haul business. While they have achieved modest success in heavy haul, arguably the only viable postrenaissance narrow gauge application, heavy haul railways are usually short, and do not naturally network with one another. Queensland's are interesting—approximately parallel systems from multiple coalmines to several ports. South Africa's are on opposite sides of the continent. Brazil's Estrada de Ferro Vitória a Minas is essentially a single purpose operation. None of them establish a basis for continental scale networkability.

### **4.1.6 Pursuing competition**

The variables *Infrastructure-operations Separation*, *Train Operator Diversity*, and *Rolling Stock Ownership Locus* all loaded positively onto the latent variable *Pursuing Competition*. Vertical separation, multiple train operators, and private rolling stock ownership constitute the basis of liberal on-rail competition with open access to infrastructure, which has emerged notably in the European Union and Australia. Latent variables are mutually exclusive: *Pursuing Competition* introduces competition in the market in settings that are physically unable or politically unwilling to support competition for the market among multiple infrastructure operators as in *Positioning Freight Rail*. Whether vertical separation benefits the railway industry and its stakeholders has been debated since Sweden first implemented it in 1987: There are many arguments for and against (Jackson, 2011b). However, *Pursuing Competition* is only one of a suite of applicable corporate citizenship latent variables. It is evident that in instances where vertical separation has not worked as expected, that inherent competitiveness has also fallen short. Consider, for example, that open access has met EU expectations for passenger operators, but missed them for freight, while the freight-oriented Australian Rail Track Corporation network has met expectations: In Europe, passenger rail positioning is inherently competitive, but not so freight, while in Australia freight rail positioning is inherently competitive.

### **4.1.7 Aligning assets**

The variables *Rolling Stock Commitment Horizon* and *Infrastructure Commitment Horizon* both loaded positively onto the latent variable *Aligning Assets*. It suggested aligning infrastructure and rolling stock investment for appropriate periods, to avoid competitiveness being eroded by obsolescence. Without competition to demand ever-increasing performance, railways are not incentivized to replace existing assets with higher performing assets. If they do not routinely raise the bar of their genetic technologies by increasing axle load, speed, and/or train length, it becomes difficult to justify new- or upgraded assets. Railways then contemplate refurbishment and rehabilitation, often leading indicators of unsustainability. Sometimes they deploy new rolling stock on existing infrastructure—a palliative that may fail to realize the new trains' full performance potential. The countervailing value of private ownership emerged in *Positioning Freight Rail* and *Pursuing Competition*. Sustainable private enterprise works assets hard or works them out.

### **4.1.8 Greening the image**

The variables Calendar Year, Climate-change Position, Rolling Stock Investment Capacity, and Infrastructure Investment Capacity all loaded positively onto the latent variable Greening the Image. The anchor roles of Calendar Year and Climate-change Position suggested that actors outside rather than inside the railway industry were actually setting the pace of greening.

By contrast, many narrow gauge railways must forego participation in long-haul business. While they have achieved modest success in heavy haul, arguably the only viable postrenaissance narrow gauge application, heavy haul railways are usually short, and do not naturally network with one another. Queensland's are interesting—approximately parallel systems from multiple coalmines to several ports. South Africa's are on opposite sides of the continent. Brazil's Estrada de Ferro Vitória a Minas is essentially a single purpose operation.

The variables *Infrastructure-operations Separation*, *Train Operator Diversity*, and *Rolling Stock Ownership Locus* all loaded positively onto the latent variable *Pursuing Competition*. Vertical separation, multiple train operators, and private rolling stock ownership constitute the basis of liberal on-rail competition with open access to infrastructure, which has emerged notably in the European Union and Australia. Latent variables are mutually exclusive: *Pursuing Competition* introduces competition in the market in settings that are physically unable or politically unwilling to support competition for the market among multiple infrastructure operators as in *Positioning Freight Rail*. Whether vertical separation benefits the railway industry and its stakeholders has been debated since Sweden first implemented it in 1987: There are many arguments for and against (Jackson, 2011b). However, *Pursuing Competition* is only one of a suite of applicable corporate citizenship latent variables. It is evident that in instances where vertical separation has not worked as expected, that inherent competitiveness has also fallen short. Consider, for example, that open access has met EU expectations for passenger operators, but missed them for freight, while the freight-oriented Australian Rail Track Corporation network has met expectations: In Europe, passenger rail positioning is inherently competitive, but not so

The variables *Rolling Stock Commitment Horizon* and *Infrastructure Commitment Horizon* both loaded positively onto the latent variable *Aligning Assets*. It suggested aligning infrastructure and rolling stock investment for appropriate periods, to avoid competitiveness being eroded by obsolescence. Without competition to demand ever-increasing performance, railways are not incentivized to replace existing assets with higher performing assets. If they do not routinely raise the bar of their genetic technologies by increasing axle load, speed, and/or train length, it becomes difficult to justify new- or upgraded assets. Railways then contemplate refurbishment and rehabilitation, often leading indicators of unsustainability. Sometimes they deploy new rolling stock on existing infrastructure—a palliative that may fail to realize the new trains' full performance potential. The countervailing value of private ownership emerged in *Positioning Freight Rail* and *Pursuing* 

*Competition*. Sustainable private enterprise works assets hard or works them out.

The variables Calendar Year, Climate-change Position, Rolling Stock Investment Capacity, and Infrastructure Investment Capacity all loaded positively onto the latent variable Greening the Image. The anchor roles of Calendar Year and Climate-change Position suggested that actors outside rather than inside the railway industry were actually setting the pace of greening.

None of them establish a basis for continental scale networkability.

freight, while in Australia freight rail positioning is inherently competitive.

**4.1.6 Pursuing competition** 

**4.1.7 Aligning assets** 

**4.1.8 Greening the image** 

*Greening the Image* reinforces *Positioning Passenger Rail* and *Positioning Freight Rail*, but the benefits of a greener but uncompetitive mode are insignificant: The real challenge is to increase rail's competitiveness and thereby shift traffic to a greener mode by ecological adaptation. Rail's green credentials are undisputed: High speed railways accept steeper gradients that minimize environmental impact; heavy axle load attracts traffic from road to rail. State-of-the-art high-speed trains, and hybrid diesel locomotives with intelligent driving aids, reduce energy consumption per passenger journey and per ton-km. However, high speed and heavy axle load are uncomfortable bedfellows: Hence, in principle and to the extent that it is viable, physically separate dedicated freight- and passenger infrastructure promotes greening.

Passenger trains tend to be lighter and more frequent, so recovery of their regenerated braking energy poses the lesser challenge. However, *Positioning Freight Rail* promotes longer and heavier trains, so recovery of their regenerated braking energy poses the greater challenge. In particular, many heavy haul railways descend from mine to port, and several are potentially net energy generators over the empty-loaded round trip (Van der Meulen, 2010). Maximum regenerative braking should be the point of departure. However, while onboard battery storage on hybrid diesel locomotives might be worthwhile, such systems cannot deal with a net surplus. Furthermore, regenerating all instantaneously surplus energy requires locomotives to control the same load on downgrades that they haul on upgrades. While this requires symmetrical up- and downgrades, many heavy haul routes have asymmetrical grades that oblige loaded trains to dissipate potential energy through dynamic or friction braking on descending grades, which reduces sustainability. Even if gradients supported full regenerative braking, matching a three phase supply grid to single phase overhead traction supply is the next challenge. This introduces the concept of smart grids and open systems, which one hears about, but not yet in railway traction.

### **4.1.9 Constraining downside**

The variables *Attitude to Competition* and *Subsidy Influence* both loaded positively onto the latent variable *Constraining Downside*. It suggested that encouraging competition, while applying subsidy to influence the beneficiary, could constrain downside in adverse situations. A country's railway industry is only as competitive as government will allow or encourage. Where appropriate, governments traditionally subsidized railways directly, but their role is changing. Instead of simply assuming responsibility for runaway expenses, they now tend to recognize railways as worthy corporate citizens that they influence through instruments such as investing to raise competitiveness, public-private partnerships, tax incentives, and so on. Two examples are the United States' Passenger Rail Improvement and Investment Act of 2008 and its American Recovery and Reinvestment Act of 2009, which provided seed investment for high speed rail, to be matched by state funding for operational support (Boardman, 2010).

#### **4.1.10 Cluster analysis**

Whereas factor analysis finds relations among the variables in a database, the multivariate procedure cluster analysis finds relations among the cases in a database, countries in this instance. Applying cluster analysis, to the 2007 data only, reduced the 113 countries in the

gross national income, infrastructure investment capacity, and rolling stock investment capacity. These attributes supported competitive high-speed passenger services in developed economies, while freight technology rated low—distributed power, heavy haul, and heavy intermodal were absent. All other attributes rated moderate. However, state involvement was still present, and infrastructure operator diversity was essentially absent, hence actualization of the full spectrum of positioning latent variables was circumscribed.

The Enlightened- and Progressive clusters needed to position their rail freight for competitiveness. Setting aside Japan and South Korea, where respectively geography and present politics constrain networkability, this reduces to a European matter. The uncertain outlook of Europe's rail freight (Reinhold & Gasparic, 2009) is not unexpected. The latent variables *Positioning Passenger Rail* and *Positioning Freight Rail* indicate that positioning freight- and passenger rail are distinct corporate citizenship activities: To date, these clusters have hardly actualized *Positioning Freight Rail*. The prospect of heavy freight that will predominantly run on a dedicated Trans-European Freight Network (European Rail, 2007) is therefore encouraging. If successful, the notion of general freight transport increasingly being undertaken by relatively light containerized trains that resemble passenger trains in terms of loads exerted on the infrastructure, average speed, reliability and performance, should be expected to rearrange the latent variable *Positioning Freight Rail*, and possibly

**Assertive Railways** formed a quasi-cluster, i.e. statistically independent railways that are icicle plot neighbours but did not actually cluster. They are not insignificant railways, as the

*The United States* rated high on research and development level, relative maximum axle load and -speed; distributed power-, high-speed intercity-, and heavy intermodal presence; attitude to competition; standard gauge; infrastructure operator diversity; information technology leverage; total road network; infrastructure- and rolling stock ownership locus; network coverage; freight traffic volume; economic freedom; gross national income; physical size; infrastructure investment capacity; and subsidy influence. The US' competitive private enterprise and technology leadership have established a formidable freight railway corporate citizenship. Trucking is both a tough competitor and a symbiotic supporter, mainly in the intermodal market space. However, its comparatively high rail freight market share, one of the highest in the world, has moved shippers to seek increased competition and strengthened federal oversight (Kimes, 2011). Comparing European and US outcomes to freight and passenger separation challenges in terms of *Positioning Passenger Rail* and *Positioning Freight Rail*, note that Europe's is generally a *minus freight* outcome; the US' is generally a *minus passenger* outcome. Both actively seek to introduce the missing positioning latent variable. However, as mentioned under *Progressive Railways* above, Europe's rail freight still needs to demonstrate turnaround. Noting that the US is the only country with strong underpinning for the latent variable *Constraining Downside*, its recent modest stimulus funding (High speed, 2009) was on cue, but the quantum seemed unlikely to create dedicated passenger corridors, while admission of 145km/h intercity trains on conventional mixed-traffic routes might have diluted its potential impact. Subsequent progress has been ambivalent (Six-year high, 2011; Governor halts, 2011), with only California committing to commence construction of a 350km/h system in 2012 (California High, 2011). Evidently the

following two selected above-the-median examples illustrate.

The name speaks for itself.

other latent variables too.

population to five clusters, which the authors named Fortuitous Railways, Insecure Railways, Enlightened Railways, Progressive Railways, and the quasi-cluster Assertive Railways. The procedure maximizes within-cluster homogeneity and maximizes betweencluster heterogeneity. Mentioning cluster members by name is restricted here, because some ups and downs have occurred over time. Full details are nevertheless available in Van der Meulen & Möller (2008a), while discussion of key issues follows.

**Fortuitous Railways** clustered twenty medium-sized countries. Their *Relative Maximum Axle Load* was the only high attribute, the rest rating either moderate or low. They were standardor broad gauge state railways, redeemed by axle load that happened to be sufficiently heavy to support basic competitiveness. The authors named them *Fortuitous Railways* because they lacked attributes with which to project a distinctive corporate citizenship. Demonstrating that railway renaissance is advancing, several Middle Eastern countries, which are making substantial railway investment, have probably moved from the Fortuitous cluster to one of the Enlightened-, Progressive-, or Assertive clusters.

**Insecure Railways** clustered fifty-four medium-sized countries. It had no high attributes, had generally moderate attributes, and had low competitiveness, i.e. low maximum axle load and -speed; no distributed power-, heavy haul-, or heavy intermodal presence; predominantly narrow track gauge and low networkability. The authors named them *Insecure Railways* because they failed to exploit any of rail's strengths, and hence could be vulnerable to external threats or withdrawal of political support. Many have colonial origins, which possibly denied them wherewithal to actualize the positioning latent variables detailed in §4.1.2 to §4.1.9: In countries where line haul railways are justified at all, rebalancing of global power from developed- to developing countries could well redress this legacy, one way or another.

New Zealand, which returned full circle during the present research, characterizes the Insecure Railways cluster. Privatized in 1995, it soon fell short of expectations, running down assets along the way (New Zealand, 2008). The government repurchased the infrastructure in 2004, and the operations in 2008, thereby re-nationalizing railways. The events are unsurprising: Narrow track gauge on an island, and other handicaps, precluded it from *Positioning Passenger Rail*, *Exploiting Opportunities*, *Positioning Freight Rail*, or *Exploring Horizons*, not to mention the other positioning latent variables. Government's skepticism regarding the role of rail (KiwiRail debates, 2009) appeared justified.

**Enlightened Railways** clustered twenty small countries, mainly European Union members, -candidates, or -applicants, plus South Korea. They rated high on relative maximum axle load and -maximum speed, electric traction, networkability, information technology leverage; paved roads, economic freedom, and gross national income. All other variables were moderate, while freight technology was low—no distributed power-, heavy haul-, or heavy intermodal presence. The name reflected their enlightened approach to rail reform by encouraging competitive railway positioning per the latent variable *Pursuing Competition*.

**Progressive Railways** clustered France, Italy, Spain, Japan, Germany, and the United Kingdom. They rated high on R&D level, relative maximum speed, high-speed intercity presence, electric traction, attitude to competition, standard gauge, train operator diversity, information technology leverage, total road network, motorways, network coverage, freight traffic volume, passenger traffic volume, employee count, economic freedom, population,

population to five clusters, which the authors named Fortuitous Railways, Insecure Railways, Enlightened Railways, Progressive Railways, and the quasi-cluster Assertive Railways. The procedure maximizes within-cluster homogeneity and maximizes betweencluster heterogeneity. Mentioning cluster members by name is restricted here, because some ups and downs have occurred over time. Full details are nevertheless available in Van der

**Fortuitous Railways** clustered twenty medium-sized countries. Their *Relative Maximum Axle Load* was the only high attribute, the rest rating either moderate or low. They were standardor broad gauge state railways, redeemed by axle load that happened to be sufficiently heavy to support basic competitiveness. The authors named them *Fortuitous Railways* because they lacked attributes with which to project a distinctive corporate citizenship. Demonstrating that railway renaissance is advancing, several Middle Eastern countries, which are making substantial railway investment, have probably moved from the Fortuitous cluster to one of

**Insecure Railways** clustered fifty-four medium-sized countries. It had no high attributes, had generally moderate attributes, and had low competitiveness, i.e. low maximum axle load and -speed; no distributed power-, heavy haul-, or heavy intermodal presence; predominantly narrow track gauge and low networkability. The authors named them *Insecure Railways* because they failed to exploit any of rail's strengths, and hence could be vulnerable to external threats or withdrawal of political support. Many have colonial origins, which possibly denied them wherewithal to actualize the positioning latent variables detailed in §4.1.2 to §4.1.9: In countries where line haul railways are justified at all, rebalancing of global power from developed- to developing countries could well redress

New Zealand, which returned full circle during the present research, characterizes the Insecure Railways cluster. Privatized in 1995, it soon fell short of expectations, running down assets along the way (New Zealand, 2008). The government repurchased the infrastructure in 2004, and the operations in 2008, thereby re-nationalizing railways. The events are unsurprising: Narrow track gauge on an island, and other handicaps, precluded it from *Positioning Passenger Rail*, *Exploiting Opportunities*, *Positioning Freight Rail*, or *Exploring Horizons*, not to mention the other positioning latent variables. Government's skepticism

**Enlightened Railways** clustered twenty small countries, mainly European Union members, -candidates, or -applicants, plus South Korea. They rated high on relative maximum axle load and -maximum speed, electric traction, networkability, information technology leverage; paved roads, economic freedom, and gross national income. All other variables were moderate, while freight technology was low—no distributed power-, heavy haul-, or heavy intermodal presence. The name reflected their enlightened approach to rail reform by encouraging competitive railway positioning per the latent variable *Pursuing Competition*.

**Progressive Railways** clustered France, Italy, Spain, Japan, Germany, and the United Kingdom. They rated high on R&D level, relative maximum speed, high-speed intercity presence, electric traction, attitude to competition, standard gauge, train operator diversity, information technology leverage, total road network, motorways, network coverage, freight traffic volume, passenger traffic volume, employee count, economic freedom, population,

regarding the role of rail (KiwiRail debates, 2009) appeared justified.

Meulen & Möller (2008a), while discussion of key issues follows.

the Enlightened-, Progressive-, or Assertive clusters.

this legacy, one way or another.

gross national income, infrastructure investment capacity, and rolling stock investment capacity. These attributes supported competitive high-speed passenger services in developed economies, while freight technology rated low—distributed power, heavy haul, and heavy intermodal were absent. All other attributes rated moderate. However, state involvement was still present, and infrastructure operator diversity was essentially absent, hence actualization of the full spectrum of positioning latent variables was circumscribed. The name speaks for itself.

The Enlightened- and Progressive clusters needed to position their rail freight for competitiveness. Setting aside Japan and South Korea, where respectively geography and present politics constrain networkability, this reduces to a European matter. The uncertain outlook of Europe's rail freight (Reinhold & Gasparic, 2009) is not unexpected. The latent variables *Positioning Passenger Rail* and *Positioning Freight Rail* indicate that positioning freight- and passenger rail are distinct corporate citizenship activities: To date, these clusters have hardly actualized *Positioning Freight Rail*. The prospect of heavy freight that will predominantly run on a dedicated Trans-European Freight Network (European Rail, 2007) is therefore encouraging. If successful, the notion of general freight transport increasingly being undertaken by relatively light containerized trains that resemble passenger trains in terms of loads exerted on the infrastructure, average speed, reliability and performance, should be expected to rearrange the latent variable *Positioning Freight Rail*, and possibly other latent variables too.

**Assertive Railways** formed a quasi-cluster, i.e. statistically independent railways that are icicle plot neighbours but did not actually cluster. They are not insignificant railways, as the following two selected above-the-median examples illustrate.

*The United States* rated high on research and development level, relative maximum axle load and -speed; distributed power-, high-speed intercity-, and heavy intermodal presence; attitude to competition; standard gauge; infrastructure operator diversity; information technology leverage; total road network; infrastructure- and rolling stock ownership locus; network coverage; freight traffic volume; economic freedom; gross national income; physical size; infrastructure investment capacity; and subsidy influence. The US' competitive private enterprise and technology leadership have established a formidable freight railway corporate citizenship. Trucking is both a tough competitor and a symbiotic supporter, mainly in the intermodal market space. However, its comparatively high rail freight market share, one of the highest in the world, has moved shippers to seek increased competition and strengthened federal oversight (Kimes, 2011). Comparing European and US outcomes to freight and passenger separation challenges in terms of *Positioning Passenger Rail* and *Positioning Freight Rail*, note that Europe's is generally a *minus freight* outcome; the US' is generally a *minus passenger* outcome. Both actively seek to introduce the missing positioning latent variable. However, as mentioned under *Progressive Railways* above, Europe's rail freight still needs to demonstrate turnaround. Noting that the US is the only country with strong underpinning for the latent variable *Constraining Downside*, its recent modest stimulus funding (High speed, 2009) was on cue, but the quantum seemed unlikely to create dedicated passenger corridors, while admission of 145km/h intercity trains on conventional mixed-traffic routes might have diluted its potential impact. Subsequent progress has been ambivalent (Six-year high, 2011; Governor halts, 2011), with only California committing to commence construction of a 350km/h system in 2012 (California High, 2011). Evidently the

Fig. 2. Path Diagram showing standardized regression coefficients as arrows pointing to

*Green City Impediments* (0.545) supported the latent variable *Heavy Metro Positioning*; *Country Stature* (-0.090) opposed it. The authors interpreted these relations to mean that the variables that impede green cities, namely *Area*, *Population*, and *Population Growth*, also drive the Heavy Metro mode, rather than that Heavy Metro is not green. The road network- and vehicle population variables loaded onto *Country Stature*: Its negative sign thus suggests that countries that enjoy advanced development might ultimately come to oppose Heavy Metro. Alternatively, one could interpret the relation to mean that large cities with large populations and high population growth might find Heavy Metro out of reach, and opt for Bus Rapid Transit instead. To emphasize its pre-eminence among other urban guided transit modes, note that *Heavy Metro Position* attracted loading by the variables *World Cities Score* and *Smart Card Application*. It appears that, until the present, leading cities considered

dependent latent variables

**4.2.3 Positioning heavy metro** 

Heavy Metro to be a must have feature.

latent variables *Positioning Passenger Rail* and *Positioning Freight Rail* are so robustly rooted in rail's genetic technologies that they do not readily yield to political expediency.

*China* rated high on R&D level, relative maximum speed; distributed power-, high-speed intercity-, and heavy intermodal presence; electric traction; attitude to competition; motorways; paved roads; freight traffic volume; employee count; population; physical size; and infrastructure- and rolling stock investment capacity. Its rapid network growth and technological development, and its immense railway corporate citizenship, have drawn global admiration. Initially, it mixed high-speed passenger and freight on an upgraded, network: For a country eagerly actualizing the latent variable *Exploiting Opportunities*, that outcome aligned uneasily with the latent variables *Positioning Passenger Rail* and *Positioning Freight Rail*. However, in recent times it has vindicated the research findings by rapid expansion actualizing *Positioning Passenger Rail* through the emerging Passenger Dedicated Line (PDL) network (Li-ren & Li, 2010), and *Positioning Freight Rail* through a second heavy haul line to augment the 400 million-tonnes-per-year Daqin line (Second heavy, 2009) with an ultimate objective of a 10000km heavy haul network. Heavy axle load is absent from the variables listed above, but is set to increase to 30 tonnes on heavy haul lines (Seizing the, 2009). China's actualization of *Positioning Passenger Rail* and *Positioning Freight Rail* has positioned it as world's busiest heavy haul railway, and operates the first trains in the world timetabled to run at an average of over 300km/h (China's star, 2010).

To do justice to members of the Assertive Railways cluster requires more space than the page limit of this chapter. Because they are a quasi-cluster and not a true cluster, it is not possible to discuss them in generic terms as has been done for the Fortuitous-, Insecure-, Enlightened-, and Progressive Railways clusters. Instead each one requires discussion of its individual attributes. Further examples may be therefore be found in Van der Meulen & Möller (2008b).

### **4.2 Urban guided transit**

### **4.2.1 The path diagram**

Section 4.1 has interpreted the statistical findings of rail's three inherently competitive market spaces. Next, in urban transit language, §4.2.2 to §4.2.10 will interpret the path diagram in Fig. 2 with respect to rail's inherently weak market space. More detail is available in Van der Meulen & Möller (2012).

### **4.2.2 Green city impediments**

The latent variable *Green City Impediments* mediated between the country setting and urban rail solutions in particular cities. Noting carefully the relative directions of their signs, and that double negative is positive, the latent variables *Societal Development Level* (-0.389), *Alternative Energy Acceptance* (-0.256), *Economic Development Level* (-0.150), and *Services Contribution to GDP* (-0.149), opposed it, while *Country Stature* (0.075) supported it. From the perspective of populous, large countries that feature urban guided transit, larger is evidently not greener: Rather, positive societal development, minus alternative energy acceptance, minus economic development, and minus services contribution, associate with green cities.

latent variables *Positioning Passenger Rail* and *Positioning Freight Rail* are so robustly rooted in

*China* rated high on R&D level, relative maximum speed; distributed power-, high-speed intercity-, and heavy intermodal presence; electric traction; attitude to competition; motorways; paved roads; freight traffic volume; employee count; population; physical size; and infrastructure- and rolling stock investment capacity. Its rapid network growth and technological development, and its immense railway corporate citizenship, have drawn global admiration. Initially, it mixed high-speed passenger and freight on an upgraded, network: For a country eagerly actualizing the latent variable *Exploiting Opportunities*, that outcome aligned uneasily with the latent variables *Positioning Passenger Rail* and *Positioning Freight Rail*. However, in recent times it has vindicated the research findings by rapid expansion actualizing *Positioning Passenger Rail* through the emerging Passenger Dedicated Line (PDL) network (Li-ren & Li, 2010), and *Positioning Freight Rail* through a second heavy haul line to augment the 400 million-tonnes-per-year Daqin line (Second heavy, 2009) with an ultimate objective of a 10000km heavy haul network. Heavy axle load is absent from the variables listed above, but is set to increase to 30 tonnes on heavy haul lines (Seizing the, 2009). China's actualization of *Positioning Passenger Rail* and *Positioning Freight Rail* has positioned it as world's busiest heavy haul railway, and operates the first trains in the world

To do justice to members of the Assertive Railways cluster requires more space than the page limit of this chapter. Because they are a quasi-cluster and not a true cluster, it is not possible to discuss them in generic terms as has been done for the Fortuitous-, Insecure-, Enlightened-, and Progressive Railways clusters. Instead each one requires discussion of its individual attributes. Further examples may be therefore be found in Van der Meulen &

Section 4.1 has interpreted the statistical findings of rail's three inherently competitive market spaces. Next, in urban transit language, §4.2.2 to §4.2.10 will interpret the path diagram in Fig. 2 with respect to rail's inherently weak market space. More detail is

The latent variable *Green City Impediments* mediated between the country setting and urban rail solutions in particular cities. Noting carefully the relative directions of their signs, and that double negative is positive, the latent variables *Societal Development Level* (-0.389), *Alternative Energy Acceptance* (-0.256), *Economic Development Level* (-0.150), and *Services Contribution to GDP* (-0.149), opposed it, while *Country Stature* (0.075) supported it. From the perspective of populous, large countries that feature urban guided transit, larger is evidently not greener: Rather, positive societal development, minus alternative energy acceptance, minus economic development, and minus services contribution, associate with

rail's genetic technologies that they do not readily yield to political expediency.

timetabled to run at an average of over 300km/h (China's star, 2010).

Möller (2008b).

green cities.

**4.2 Urban guided transit 4.2.1 The path diagram** 

**4.2.2 Green city impediments** 

available in Van der Meulen & Möller (2012).

Fig. 2. Path Diagram showing standardized regression coefficients as arrows pointing to dependent latent variables

#### **4.2.3 Positioning heavy metro**

*Green City Impediments* (0.545) supported the latent variable *Heavy Metro Positioning*; *Country Stature* (-0.090) opposed it. The authors interpreted these relations to mean that the variables that impede green cities, namely *Area*, *Population*, and *Population Growth*, also drive the Heavy Metro mode, rather than that Heavy Metro is not green. The road network- and vehicle population variables loaded onto *Country Stature*: Its negative sign thus suggests that countries that enjoy advanced development might ultimately come to oppose Heavy Metro. Alternatively, one could interpret the relation to mean that large cities with large populations and high population growth might find Heavy Metro out of reach, and opt for Bus Rapid Transit instead. To emphasize its pre-eminence among other urban guided transit modes, note that *Heavy Metro Position* attracted loading by the variables *World Cities Score* and *Smart Card Application*. It appears that, until the present, leading cities considered Heavy Metro to be a must have feature.

Either *Energy Demand Level* or *Alternative Energy Acceptance* opposed each of the three rubber-tyred modes, Automated Guided Transit, Monorail, and Bus Rapid Transit. They have higher rolling resistance than steel tyred modes, and all things being equal, also higher energy consumption. Evidently, countries that already had high energy demand, and those that accepted alternative energy, were sensitive to unduly increasing their energy demand. By contrast, *Energy Demand Level* and *Alternative Energy Acceptance* both supported Light Rail: Its greenness therefore offsets its marginal inherent

The latent variable *Trade Contribution to GDP* opposed the higher technology automated modes, i.e. Automated Guided Transit, Monorail, and Light Metro; whereas it supported the lower-technology Bus Rapid Transit and Light Rail. Evidently there was an inverse relationship between technology and trade, which would manifest itself as the conservative tactic of initially deploying advanced technology close to its origin or

The latent variable *Positioning Passenger Rail* has become a prominent function of railway corporate citizenship. High speed rail has established itself as a formidable competitor against airlines in most developed countries. It is also considered to stimulate developing countries, and has become an aspirational objective in newly industrialized countries. Countries such as Brazil, India, Iran, Morocco, Russia, Thailand, and Turkey, already have, or are committed to acquiring high speed rail systems. China sees it as an environmentally responsible mode for journeys up to six hours. Dedicated passenger corridors have become the norm. China's 2010 High Speed Rail Conference sealed high speed as the way to do long-haul passenger rail for the future. *Positioning Passenger Rail* is a useful indicator of which variables should be within the high speed rail frame of

The latent variable *Positioning Freight Rail* has also become a prominent function of railway corporate citizenship. Heavy Haul is the prime solution for moving high volumes of bulk commodities, as is Heavy Intermodal for moving high volumes of containers long distances overland. Dedicated freight corridors have emerged in countries such as China and India, which have the traffic volumes to justify them. Aside from the essential technical attributes of heavy freight railways, the latent variable has highlighted the fundamental role of competition in freight transport, getting right down to private infrastructure ownership and then pitting competing railways against each other. Freight transport is generally a ruthless, low margin, and very competitive market, not well suited to a government player. It is

**4.2.9 Energy awareness** 

competitiveness.

support base.

**5. Discussion** 

reference.

**5.2 Positioning freight rail** 

**5.1 Positioning passenger rail** 

**4.2.10 Trade awareness** 

### **4.2.4 Positioning automated guided transit**

Economic Development Level (0.234) and Services Contribution to GDP (0.113) supported the latent variable Automated Guided Transit Positioning; Trade Contribution to GDP (-0.143) and Energy Demand Level (-0.141) opposed it. The authors interpreted this to mean that Automated Guided Transit fitted into developed, service economies, together with Monorail and Light Metro. See also §4.2.9 and §4.2.10 for additional interpretation.

### **4.2.5 Positioning monorail**

Green City Impediments (0.225), Economic Development Level (0.165), and Services Contribution to GDP (0.156) supported the latent variable Monorail Positioning; Trade Contribution to GDP (-0.132) and Alternative Energy Acceptance (-0.044) opposed it. As for the Heavy Metro mode, the variables that impede green cities also drive the Monorail mode. Like Automated Guided Transit and Light Metro, Monorail fitted into developed, service economies. See also §4.2.9 and §4.2.10 for additional interpretation.

### **4.2.6 Positioning bus rapid transit**

*Green City Impediments* (0.359), *Country Stature* (0.157), and *Trade Contribution to GDP* (0.079) supported the latent variable *Bus Rapid Transit Positioning*; *Energy Demand Level* (-0.120) opposed it. As for the Heavy Metro- and Monorail modes, the variables that impede green cities also drive Bus Rapid Transit. However, noting that *Country Stature* supports Bus Rapid Transit, one would naturally expect to find Bus Rapid Transit in large, rapidly growing cities, such as Jinan in China. See also §4.2.9 and §4.2.10 for additional interpretation.

### **4.2.7 Positioning light metro**

Services Contribution to GDP (0.128) and Economic Development Level (0.112) supported the latent variable Light Metro Positioning; Trade Contribution to GDP (-0.090), Country Stature (-0.088), and Societal Development Level (-0.083) opposed it. Like Automated Guided Transit and Monorail, the Light Metro mode fits into developed, service economies, although not yet assertively due to its comparatively recent emergence. Opposition by Country Stature suggested that it fits well into smallish, more intimate cities. Opposition by Societal Developmental Level appeared counter intuitive, but it might indicate that highcapacity public transport is unwanted in such cities. See also §4.2.10 for additional interpretation.

### **4.2.8 Positioning light rail**

Societal Development Level (0.138), Trade Contribution to GDP (0.137), Energy Demand Level (0.116), Country Stature (0.099), and Alternative Energy Acceptance (0.075) supported the latent variable Light Rail Positioning; Green City Impediments (-0.389) opposed it. The double negative (minus impediments) indicated that Light Rail actually supported green cities: It was the only urban guided transit mode for which all correlation coefficients that pointed to it were found to mutually reinforce its fit in a city.

### **4.2.9 Energy awareness**

88 Infrastructure Design, Signalling and Security in Railway

Economic Development Level (0.234) and Services Contribution to GDP (0.113) supported the latent variable Automated Guided Transit Positioning; Trade Contribution to GDP (-0.143) and Energy Demand Level (-0.141) opposed it. The authors interpreted this to mean that Automated Guided Transit fitted into developed, service economies, together with Monorail and Light Metro. See also §4.2.9 and §4.2.10 for additional

Green City Impediments (0.225), Economic Development Level (0.165), and Services Contribution to GDP (0.156) supported the latent variable Monorail Positioning; Trade Contribution to GDP (-0.132) and Alternative Energy Acceptance (-0.044) opposed it. As for the Heavy Metro mode, the variables that impede green cities also drive the Monorail mode. Like Automated Guided Transit and Light Metro, Monorail fitted into developed, service

*Green City Impediments* (0.359), *Country Stature* (0.157), and *Trade Contribution to GDP* (0.079) supported the latent variable *Bus Rapid Transit Positioning*; *Energy Demand Level* (-0.120) opposed it. As for the Heavy Metro- and Monorail modes, the variables that impede green cities also drive Bus Rapid Transit. However, noting that *Country Stature* supports Bus Rapid Transit, one would naturally expect to find Bus Rapid Transit in large, rapidly growing cities, such as Jinan in China. See also §4.2.9 and §4.2.10 for additional

Services Contribution to GDP (0.128) and Economic Development Level (0.112) supported the latent variable Light Metro Positioning; Trade Contribution to GDP (-0.090), Country Stature (-0.088), and Societal Development Level (-0.083) opposed it. Like Automated Guided Transit and Monorail, the Light Metro mode fits into developed, service economies, although not yet assertively due to its comparatively recent emergence. Opposition by Country Stature suggested that it fits well into smallish, more intimate cities. Opposition by Societal Developmental Level appeared counter intuitive, but it might indicate that highcapacity public transport is unwanted in such cities. See also §4.2.10 for additional

Societal Development Level (0.138), Trade Contribution to GDP (0.137), Energy Demand Level (0.116), Country Stature (0.099), and Alternative Energy Acceptance (0.075) supported the latent variable Light Rail Positioning; Green City Impediments (-0.389) opposed it. The double negative (minus impediments) indicated that Light Rail actually supported green cities: It was the only urban guided transit mode for which all correlation coefficients that

pointed to it were found to mutually reinforce its fit in a city.

economies. See also §4.2.9 and §4.2.10 for additional interpretation.

**4.2.4 Positioning automated guided transit** 

interpretation.

interpretation.

interpretation.

**4.2.8 Positioning light rail** 

**4.2.5 Positioning monorail** 

**4.2.6 Positioning bus rapid transit** 

**4.2.7 Positioning light metro** 

Either *Energy Demand Level* or *Alternative Energy Acceptance* opposed each of the three rubber-tyred modes, Automated Guided Transit, Monorail, and Bus Rapid Transit. They have higher rolling resistance than steel tyred modes, and all things being equal, also higher energy consumption. Evidently, countries that already had high energy demand, and those that accepted alternative energy, were sensitive to unduly increasing their energy demand. By contrast, *Energy Demand Level* and *Alternative Energy Acceptance* both supported Light Rail: Its greenness therefore offsets its marginal inherent competitiveness.

### **4.2.10 Trade awareness**

The latent variable *Trade Contribution to GDP* opposed the higher technology automated modes, i.e. Automated Guided Transit, Monorail, and Light Metro; whereas it supported the lower-technology Bus Rapid Transit and Light Rail. Evidently there was an inverse relationship between technology and trade, which would manifest itself as the conservative tactic of initially deploying advanced technology close to its origin or support base.

### **5. Discussion**

### **5.1 Positioning passenger rail**

The latent variable *Positioning Passenger Rail* has become a prominent function of railway corporate citizenship. High speed rail has established itself as a formidable competitor against airlines in most developed countries. It is also considered to stimulate developing countries, and has become an aspirational objective in newly industrialized countries. Countries such as Brazil, India, Iran, Morocco, Russia, Thailand, and Turkey, already have, or are committed to acquiring high speed rail systems. China sees it as an environmentally responsible mode for journeys up to six hours. Dedicated passenger corridors have become the norm. China's 2010 High Speed Rail Conference sealed high speed as the way to do long-haul passenger rail for the future. *Positioning Passenger Rail* is a useful indicator of which variables should be within the high speed rail frame of reference.

### **5.2 Positioning freight rail**

The latent variable *Positioning Freight Rail* has also become a prominent function of railway corporate citizenship. Heavy Haul is the prime solution for moving high volumes of bulk commodities, as is Heavy Intermodal for moving high volumes of containers long distances overland. Dedicated freight corridors have emerged in countries such as China and India, which have the traffic volumes to justify them. Aside from the essential technical attributes of heavy freight railways, the latent variable has highlighted the fundamental role of competition in freight transport, getting right down to private infrastructure ownership and then pitting competing railways against each other. Freight transport is generally a ruthless, low margin, and very competitive market, not well suited to a government player. It is

Note that this Section applies to line haul railways only. Urban rail is generally a local

The research journey has revealed complex relations that underlie railway positioning. As the renaissance progresses, railways migrate to clusters that exhibit more advanced corporate citizenship. However, the adaptation process has fragmented the industry into more competing entities, whose data become less accessible due to commercial sensitivities, in many instances providing no more than minimum legal requirements. The present research was fortunately conducted in a window of opportunity that has all but closed in countries whose line-haul railways have advanced the furthest. Due to the public nature of urban rail, that has not yet happened to its data. It would therefore be difficult to replicate the line haul research with current data. It might even be pointless because, having identified the Fortuitous and Insecure clusters and the determinants of their position, there is arguably no more insight to extract. It would be more productive to learn from the Enlightened, Progressive, and Assertive railways. However, that would

government responsibility, which institutional arrangements are appropriate.

reduce the population size by 65%, which would require a new research design.

The research stream described in this chapter has developed a statistical research approach to global railway positioning, both line haul- and urban, from a corporate citizenship

In supporting the hypothesized existence of some number of underlying longitudinal, or time-dependent, relations among variables associated with positioning line haul railways, the research has found the eight latent variables *Positioning Passenger Rail*, *Exploiting Opportunities*, *Positioning Freight Rail*, *Exploring Horizons*, *Pursuing Competition*, *Aligning Assets*, *Greening the Image*, and *Constraining Downside*. These latent variables represent actualization of a railway's corporate citizenship with respect to its core

In supporting the hypothesis that positioning the various urban guided transit modes in particular cities reflected attributes of their ever changing socio-economic setting vis-à-vis attributes of the various transit modes, the research found the seven country-related latent variables *Country Stature*, *Economic Development Level*, *Energy Demand Level, Services Contribution to GDP*; *Trade Contribution to GDP*, *Societal Development Level*, and *Alternative Energy Acceptance*, and the seven city-related latent variables *Heavy Metro Position*, *Automated Guided Transit Position*, *Monorail Position*, *Light Metro Position*, *Light Rail Position*, and *Green City Impediments*. The relations found between country- and city latent variables were presented in a path diagram that shows regression coefficients from the socio-economic setting to particular guided transit solutions. It represents the positioning of those solutions

The foregoing outcome has developed grounded understanding of railway positioning in all four of rail's market spaces, the three in which it is inherently competitive, namely

**6. Future research** 

**7. Conclusions** 

perspective.

business.

with respect to their country and city settings.

therefore difficult to see why some governments continue to see freight transport as a core government function (Amos, 2006). Looking ahead to §5.4, it is evident that not all rail reforms have faced this issue.

### **5.3 Positioning urban rail**

The findings on urban rail positioning have provided interesting insights into ecological adaptation in the light-axle-load low-speed market space. While Heavy Metro remains unchallenged at the highest capacity level, it appears that rubber-tyred guided transit modes have breached rail's pre-eminent status. One would therefore expect Light Rail, and by extension Light Metro, to be more vulnerable to competition from rubber-tyred systems by virtue of their low axle load. Notwithstanding that potential weakness, their good green credentials are attractive to smaller cities that value inherent environmental friendliness over the expediency of simply moving people under the weight of popular demand. Automated Guided Transit, Monorail, and Bus Rapid Transit do however seem well positioned to drive a wedge between the heavy- and light poles of urban rail. From there, one should expect them to win in medium cities such as Automated Guided Transit in Lille in France, and Bus Rapid Transit in Jinan in China.

### **5.4 The role of rail reform**

This chapter commenced with observing differences among railways. In the context of this Section, variables in the Ownership Group and the Society Group were particularly relevant. Having researched and explained the modalities of railway positioning, and finding that renaissance is an achievable aspiration, it is now apposite to return to the original differences. Why do the Fortuitous and Insecure clusters still exist? Note that countries that have advanced have in many instances liberalized their institutional arrangements, or are in process of doing so. There are of course exceptions, such as China and India, but the weight of evidence from the Fortuitous and Insecure clusters, the majority of whose members are state-owned, suggests that unless state ownership results in operational efficiency and capital investment that positions railways for competitiveness and sustainability, it is an impediment rather than a facilitator.

Vertical integration versus vertical separation and open access has been another persistent reform issue. It is helpful to benchmark positions against the United States industry model. Interoperability is near seamless, and continental-scale haul distances transcend geographically-defined railroad franchises. Extensive leasing separates rolling stock ownership from liveries and reporting marks. Symbiotic trackage rights give access to infrastructure of others. Unrestricted interchange of 32.4 tonne-per-axle vehicles give the lie to assertions that heavy haul and vertical separation cannot co-exist. All told, US railroads are effectively infrastructure managers, not unlike those in Europe, and for purpose of this argument its actual vertical integration is less than what the name suggests. Note nevertheless critical differences regarding private infrastructure ownership, and extensive though not ubiquitous competition between parallel railroads. While shippers will attest that it is not a perfect market, it does suggest that anything less free is more constraining than it need be.

Note that this Section applies to line haul railways only. Urban rail is generally a local government responsibility, which institutional arrangements are appropriate.

### **6. Future research**

90 Infrastructure Design, Signalling and Security in Railway

therefore difficult to see why some governments continue to see freight transport as a core government function (Amos, 2006). Looking ahead to §5.4, it is evident that not all rail

The findings on urban rail positioning have provided interesting insights into ecological adaptation in the light-axle-load low-speed market space. While Heavy Metro remains unchallenged at the highest capacity level, it appears that rubber-tyred guided transit modes have breached rail's pre-eminent status. One would therefore expect Light Rail, and by extension Light Metro, to be more vulnerable to competition from rubber-tyred systems by virtue of their low axle load. Notwithstanding that potential weakness, their good green credentials are attractive to smaller cities that value inherent environmental friendliness over the expediency of simply moving people under the weight of popular demand. Automated Guided Transit, Monorail, and Bus Rapid Transit do however seem well positioned to drive a wedge between the heavy- and light poles of urban rail. From there, one should expect them to win in medium cities such as Automated Guided Transit in Lille

This chapter commenced with observing differences among railways. In the context of this Section, variables in the Ownership Group and the Society Group were particularly relevant. Having researched and explained the modalities of railway positioning, and finding that renaissance is an achievable aspiration, it is now apposite to return to the original differences. Why do the Fortuitous and Insecure clusters still exist? Note that countries that have advanced have in many instances liberalized their institutional arrangements, or are in process of doing so. There are of course exceptions, such as China and India, but the weight of evidence from the Fortuitous and Insecure clusters, the majority of whose members are state-owned, suggests that unless state ownership results in operational efficiency and capital investment that positions railways for

competitiveness and sustainability, it is an impediment rather than a facilitator.

Vertical integration versus vertical separation and open access has been another persistent reform issue. It is helpful to benchmark positions against the United States industry model. Interoperability is near seamless, and continental-scale haul distances transcend geographically-defined railroad franchises. Extensive leasing separates rolling stock ownership from liveries and reporting marks. Symbiotic trackage rights give access to infrastructure of others. Unrestricted interchange of 32.4 tonne-per-axle vehicles give the lie to assertions that heavy haul and vertical separation cannot co-exist. All told, US railroads are effectively infrastructure managers, not unlike those in Europe, and for purpose of this argument its actual vertical integration is less than what the name suggests. Note nevertheless critical differences regarding private infrastructure ownership, and extensive though not ubiquitous competition between parallel railroads. While shippers will attest that it is not a perfect market, it does suggest that anything less free is more constraining

reforms have faced this issue.

**5.3 Positioning urban rail** 

**5.4 The role of rail reform** 

than it need be.

in France, and Bus Rapid Transit in Jinan in China.

The research journey has revealed complex relations that underlie railway positioning. As the renaissance progresses, railways migrate to clusters that exhibit more advanced corporate citizenship. However, the adaptation process has fragmented the industry into more competing entities, whose data become less accessible due to commercial sensitivities, in many instances providing no more than minimum legal requirements. The present research was fortunately conducted in a window of opportunity that has all but closed in countries whose line-haul railways have advanced the furthest. Due to the public nature of urban rail, that has not yet happened to its data. It would therefore be difficult to replicate the line haul research with current data. It might even be pointless because, having identified the Fortuitous and Insecure clusters and the determinants of their position, there is arguably no more insight to extract. It would be more productive to learn from the Enlightened, Progressive, and Assertive railways. However, that would reduce the population size by 65%, which would require a new research design.

### **7. Conclusions**

The research stream described in this chapter has developed a statistical research approach to global railway positioning, both line haul- and urban, from a corporate citizenship perspective.

In supporting the hypothesized existence of some number of underlying longitudinal, or time-dependent, relations among variables associated with positioning line haul railways, the research has found the eight latent variables *Positioning Passenger Rail*, *Exploiting Opportunities*, *Positioning Freight Rail*, *Exploring Horizons*, *Pursuing Competition*, *Aligning Assets*, *Greening the Image*, and *Constraining Downside*. These latent variables represent actualization of a railway's corporate citizenship with respect to its core business.

In supporting the hypothesis that positioning the various urban guided transit modes in particular cities reflected attributes of their ever changing socio-economic setting vis-à-vis attributes of the various transit modes, the research found the seven country-related latent variables *Country Stature*, *Economic Development Level*, *Energy Demand Level, Services Contribution to GDP*; *Trade Contribution to GDP*, *Societal Development Level*, and *Alternative Energy Acceptance*, and the seven city-related latent variables *Heavy Metro Position*, *Automated Guided Transit Position*, *Monorail Position*, *Light Metro Position*, *Light Rail Position*, and *Green City Impediments*. The relations found between country- and city latent variables were presented in a path diagram that shows regression coefficients from the socio-economic setting to particular guided transit solutions. It represents the positioning of those solutions with respect to their country and city settings.

The foregoing outcome has developed grounded understanding of railway positioning in all four of rail's market spaces, the three in which it is inherently competitive, namely

Jackson, C. (2011b). Does separation really work? *Railway Gazette International*, Vol.167, No.6,

Jane's World Railways (2005-2006, 2007-2008). Englewood, Colorado, United States of

Japanese Railway Engineering (1964). *Special Issue—New Tokaido Line*, Vol.5, No.4, pp.1-

KiwiRail debates the way forward (2009). *Railway Gazette International*, Vol.165, No.11, pp39-

Levinson, M. (2006). *The box*, pp. 261-262, Princeton University, ISBN 978-0-691-12324-0,

Li-ren, D. & Li, D. (2010). Planning the world's biggest high speed network, *Railway Gazette* 

Reinhold, T. & Gasparic, C. (2009). Facing the moment of truth, *Railway Gazette International*,

Second heavy haul line gears up to handle more coal (2009). *Railway Gazette International*,

Six-year high speed plan announced (2011). *Railway Gazette International*, Vol.167, No.3,

Tracks to carry the big mineral hauls (1972). *Railway Gazette International*, Vol.128, No.2,

Van der Meulen, R.D. (1994). Some relations of corporate strategy content to organizational

Van der Meulen, R.D. (2010). Heavy haul railway electrification—experiences and prospects,

Van der Meulen, R.D. & Möller, L.C. (2006). Railway globalization: Leveraging insight from

Van der Meulen, R.D. & Möller, L.C. (2008a). Strategies for sustainable mobility: Urban

Van der Meulen, R.D. & Möller, L.C. (2008b). Ultimate interoperability: Line-haul railways

Van der Meulen, R.D. & Möller, L.C. (2012). European- and global urban guided transit: Green- and socio-economic fit, *Transport Research Arena,* Athens, Greece

environment by comparing a capital-intensive service industry across selected societies, Doctoral dissertation, University of Pretoria, *Dissertation Abstracts* 

*Proceedings of the Joint Rail Conference*, JRC2010-36151 [CD-ROM]. Urbana, Illinois, United States of America, ASME, IEEE, ASCE, TRB, AREMA, and University of

developed- into developing regions. *Proceedings of the 7th World Congress on Railway* 

railways as global corporate citizens, *Proceedings of the 8th World Congress on Railway* 

as global corporate citizens, *Proceedings of the 8th World Congress on Railway Research*,

New Zealand nationalizes (2008). *Railway Gazette International*, Vol.164, No.6, p.344 Railway Directory (2002-2007, 2009-2012). Hamburg, Germany, DVV Media Group

Seizing the opportunity (2009). *Railway Gazette International*, Vol.165, No.9, pp.31-36

Kimes, M (2011). Showdown on the railroad, *Fortune*, Vol.164, No. 5. pp.81-88

Princeton, New Jersey, United States of America

*International*, Vol.166, No.12, pp.41-46

*International*, Vol.55, No.5, p.1336-A.

*Research* [CD-ROM], Montréal, Québec, Canada

*Research*, G.2.2.2.1 [CD-ROM], Seoul, Korea

PN.1.2 [CD-ROM], Seoul, Korea

Vol.165, No.12, pp. 24-27

Vol.165, No.9, p.40

p.3

56

42

p.10

pp.49-53

Illinois.

America, IHS

Heavy Haul, High-speed Intercity, and Heavy Intermodal, as well as the market space in which it is potentially weak, namely Urban Rail. This has made it possible to understand and to predict with reasonable certainty what will be the outcome of a particular railway positioning intervention, or to analyse a situation and design appropriate remedial intervention.

Like the top-down research design, its application is primarily top down. As examples, the authors have used it as a framework for national rail development strategy, national railway economic regulation, national railway policy, rail's contribution to national transport planning, national passenger commuter rail technology, development of strategic rail plans at provincial- and regional levels, high level positioning of major rail corridors, and conceptual design of a regional rail corridor. In short, it provides high-level insight with which to assess the viability of policy options.

### **8. Acknowledgements**

The authors express their appreciation for constructive comments to peer reviewers at many conferences, colleagues in the global railway industry, and colleagues in the South African railway industry. The work reported here is much richer for it.

### **9. References**

Amos, P. (2006). *Railway reform: Vertical integration and separation*, World Bank, Accessed 2011-10-16, Available from:

www.euromedtransport.org/En/image.php?id=1129


Heavy Haul, High-speed Intercity, and Heavy Intermodal, as well as the market space in which it is potentially weak, namely Urban Rail. This has made it possible to understand and to predict with reasonable certainty what will be the outcome of a particular railway positioning intervention, or to analyse a situation and design appropriate remedial

Like the top-down research design, its application is primarily top down. As examples, the authors have used it as a framework for national rail development strategy, national railway economic regulation, national railway policy, rail's contribution to national transport planning, national passenger commuter rail technology, development of strategic rail plans at provincial- and regional levels, high level positioning of major rail corridors, and conceptual design of a regional rail corridor. In short, it provides high-level insight with

The authors express their appreciation for constructive comments to peer reviewers at many conferences, colleagues in the global railway industry, and colleagues in the South African

Amos, P. (2006). *Railway reform: Vertical integration and separation*, World Bank, Accessed

Boardman, J. (2010). Fast-tracking the future, *Railway Gazette International*, Vol.166, No.7,

California High-speed Rail Authority (2011). *Chairman issues statement*, Accessed 2011-10-16,

European Rail Research Advisory Council (2007). *Strategic Rail Research Agenda 2020*,

Friedman, T.L. (2006). *The world is flat*, Penguin, ISBN 978-0-141-03489-8, London,

Governor halts Florida high speed project (2011). *Railway Gazette International*, Vol.167, No.3,

Heydenreich, T. & Lehrmann, M. (2010). How to save wagonload freight, *Railway Gazette* 

Jackson, C. (2010). China's star blazes a high speed trail, *Railway Gazette International*,

Jackson, C. (2011a), Rail freight network starts to evolve, *Railway Gazette International*,

*dedicated lines concept final report*, Author, ISBN 978-3-00-0275700-1, Brussels,

Available from: www.cahighspeedrail.ca.gov/10102011-leg.aspx Dedicated Freight Corridor loan (2010). *Railway Gazette International*, Vol.166, No.9, p.7 European Freight and Logistics Leaders Forum (2008). *NEWOPERA The rail freight* 

intervention.

which to assess the viability of policy options.

2011-10-16, Available from:

railway industry. The work reported here is much richer for it.

*International*, Vol.166, No.9. pp.126, 128, 130

High speed scramble (2009). *Railway Gazette International*, Vol.165, No.8, p.19

www.euromedtransport.org/En/image.php?id=1129

**8. Acknowledgements** 

pp.44-47

Belgium, p.157

Vol.166, No.2, p.3

Vol.167, No.3, pp.48-52

England

p.10

Brussels, Belgium, p.13

**9. References** 


**5** 

Zhao Zhisu

*China* 

**Structural and Kinematic Analysis of** 

Maglev train is a new means of transport and an integration of the latest high-techs in the field of track-bound transportation system. Over the past half century, the research on vehicle structure has been always a very active area. The researchers realized there is great difference between the movements of the maglev train with that of the conventional rail vehicles. For designing maglev vehicle, creation of a new mechanism is necessary, and then the mechanism is converted to a specific machine to compose vehicles. In this process, machine and mechanism kinematics analysis are indispensable prerequisites. Study of kinematics analysis method and theoretical is the forefront of researching for the structure of maglev train. This chapter aims to introduce author's the latest research

EMS maglev trains have two basic structures which are represented by German Transrapid and Japanese HSST. Chinese and Korean mid-low speed maglev trains are in these two basic

The structure of EMS maglev trains has changed through a rigid aircraft - flexible coupling modularization structure process. Based on the vehicles levitation running in the air, naturally a structure type of rigid spacecraft has been designed by researchers, namely the whole vehicle in rigid structure. It takes Japanese HSST-01(Yoshio Hikasa & Yutaka Takeuchi, 1980) (Fig.1) and German Transrapid 02(J.L.He et al., 1992) (Fig. 2) as the

The vehicle shakes violently when they are experimentally running at a high speed. Both kinds of vehicles are non-manned and the researchers design a new kind of maglev vehicle structure for solving the manned riding comfort. This structure separates the car body and running gear first and a secondary suspension system is sets up with buffer spring between them. It takes Japanese HSST-02(Yoshio Hikasa & Yutaka Takeuchi, 1980) (Fig.3) as the

**2.1 Outline of structure development of ems maglev trains** 

**1. Introduction** 

outcome.

structures now.

representative.

**2. Structure of maglev trains** 

representatives of this vehicle.

**EMS Maglev Trains** 

*National University of Defense Technology* 


## **Structural and Kinematic Analysis of EMS Maglev Trains**

Zhao Zhisu *National University of Defense Technology China* 

### **1. Introduction**

94 Infrastructure Design, Signalling and Security in Railway

Vuchic, V.R. (2007). *Urban transit systems and technology*, Wiley, ISBN 978-0-471-75823-5,

World Economic Forum (n.d). *Corporate global citizenship,* Accessed 2011-10-05*,* Available

from*:* www.weforum.org/issues/corporate-global-citizenship

Hoboken, New Jersey, United States of America

Maglev train is a new means of transport and an integration of the latest high-techs in the field of track-bound transportation system. Over the past half century, the research on vehicle structure has been always a very active area. The researchers realized there is great difference between the movements of the maglev train with that of the conventional rail vehicles. For designing maglev vehicle, creation of a new mechanism is necessary, and then the mechanism is converted to a specific machine to compose vehicles. In this process, machine and mechanism kinematics analysis are indispensable prerequisites. Study of kinematics analysis method and theoretical is the forefront of researching for the structure of maglev train. This chapter aims to introduce author's the latest research outcome.

### **2. Structure of maglev trains**

EMS maglev trains have two basic structures which are represented by German Transrapid and Japanese HSST. Chinese and Korean mid-low speed maglev trains are in these two basic structures now.

### **2.1 Outline of structure development of ems maglev trains**

The structure of EMS maglev trains has changed through a rigid aircraft - flexible coupling modularization structure process. Based on the vehicles levitation running in the air, naturally a structure type of rigid spacecraft has been designed by researchers, namely the whole vehicle in rigid structure. It takes Japanese HSST-01(Yoshio Hikasa & Yutaka Takeuchi, 1980) (Fig.1) and German Transrapid 02(J.L.He et al., 1992) (Fig. 2) as the representatives of this vehicle.

The vehicle shakes violently when they are experimentally running at a high speed. Both kinds of vehicles are non-manned and the researchers design a new kind of maglev vehicle structure for solving the manned riding comfort. This structure separates the car body and running gear first and a secondary suspension system is sets up with buffer spring between them. It takes Japanese HSST-02(Yoshio Hikasa & Yutaka Takeuchi, 1980) (Fig.3) as the representative.

Structural and Kinematic Analysis of EMS Maglev Trains 97

1. Guidance magnet, 2.Overlap magnet, 3.Brake magnet, 4.Levitation magnet, 5.Car body, 6.Maglev

The structure of maglev trains has several extraordinary characteristics: 1) as light as possible; 2) enough degrees of freedom; 3) special mechanically-braking mode; 4) unique lateral load way 5) vehicles fall on rail to slide under emergency. The vehicles are composed of three parts as shown in Fig.4: car body at the top, secondary suspension at the middle and running gear at the bottom. The wheel rail vehicles have only two bogies through wheel pair contact with rail, but bogies of the maglev trains distributed along the entire length of

The two wheel pair of wheel rail vehicles is installed on a rigid frame in the same plane. The four points in the frame of maglev bogies, the detection points of gap sensors, should move independently. The bogies have two typical structures: the bogie with torsion longeron is shown as Fig.6 (Maglev Technical Committee, 2007), Fig.8 (Z.S. ZHAO & L.M. YING, 2007). Two levitation frame units 8 are connected by torsion longeron 7 to form The maglev bogies. In vertical direction, the bogies realize the independent motion of four points by reversed longeron (the bogies hereinafter referred as T-type bogies); and the bogie is assembled by

bogie, 7.Secondary suspension system, 8.Levitation frame

1. Maglev bogie, 2.Secondary Suspend system, 3.Car body.

**2.2 Characteristics of EMS maglev train structure** 

vehicles, so they are strikingly different in structure.

connection tow module 8 with anti-rolling beam 1, as shown in Fig.7.

Fig. 4. Transrapid 08

Fig. 5. HSST-100

1.Electricity box, 2.Instument panel, 3.Automate control unit, 4.Thyrist chopper, 5.Battery, 6.Gas sensor, 7.Levitation magnet, 8.Power collector, 9.Linear induction motor, 10.Hydraulic brake, 11.Saving skid, 12.Reaction plate, 13.Brakage, 14.Anchor rail, 15.Power rail

Fig. 1. HSST-01 Maglev Vehicle

Fig. 2. Transrapid-02

1. Secondary suspend, 2.Anchor rail, 3.Levitation magnet, 4.Power rail, 5.Power collector, 6.Hyraulic brake, 7.Reaction plate, 8.Linear induction motor.

Fig. 3. HSST-02

However, Vibration problem is still unresolved by use of this structure when the train are running at a high speed, because the gap size between magnetic track and suspension electromagnet is acquired by gap sensors which are generally laid for four. The four points should be controlled independently and may not in the same plane (for example, track error, vehicle passing transition curve, asynchronous dynamic adjustment of all points, etc.), but for the rigid or elastic support system in which the bogies are still rigid, the four sensors are installed in a comparatively rigid plane, so this is a conflict. After a long period of experiments and researches, a new kind of modularized vehicle structure (TEJIMA Yuichi, et al., 2004; Seki & Tomohiro, 1995; Maglev Technical Committee, 2007) (Fig.4, 5)is invented. The car body and running gear are separated and jointed by the secondary suspension system in which the four control points of bogies are decoupled, so the vibration problem of vehicles are solved perfectly.

1. Guidance magnet, 2.Overlap magnet, 3.Brake magnet, 4.Levitation magnet, 5.Car body, 6.Maglev bogie, 7.Secondary suspension system, 8.Levitation frame

Fig. 4. Transrapid 08

96 Infrastructure Design, Signalling and Security in Railway

1.Electricity box, 2.Instument panel, 3.Automate control unit, 4.Thyrist chopper, 5.Battery, 6.Gas sensor, 7.Levitation magnet, 8.Power collector, 9.Linear induction motor, 10.Hydraulic brake, 11.Saving skid,

1. Secondary suspend, 2.Anchor rail, 3.Levitation magnet, 4.Power rail, 5.Power collector,

However, Vibration problem is still unresolved by use of this structure when the train are running at a high speed, because the gap size between magnetic track and suspension electromagnet is acquired by gap sensors which are generally laid for four. The four points should be controlled independently and may not in the same plane (for example, track error, vehicle passing transition curve, asynchronous dynamic adjustment of all points, etc.), but for the rigid or elastic support system in which the bogies are still rigid, the four sensors are installed in a comparatively rigid plane, so this is a conflict. After a long period of experiments and researches, a new kind of modularized vehicle structure (TEJIMA Yuichi, et al., 2004; Seki & Tomohiro, 1995; Maglev Technical Committee, 2007) (Fig.4, 5)is invented. The car body and running gear are separated and jointed by the secondary suspension system in which the four control points of bogies are decoupled, so the vibration problem of vehicles are solved perfectly.

6.Hyraulic brake, 7.Reaction plate, 8.Linear induction motor.

12.Reaction plate, 13.Brakage, 14.Anchor rail, 15.Power rail

Fig. 1. HSST-01 Maglev Vehicle

Fig. 2. Transrapid-02

Fig. 3. HSST-02

1. Maglev bogie, 2.Secondary Suspend system, 3.Car body.

Fig. 5. HSST-100

### **2.2 Characteristics of EMS maglev train structure**

The structure of maglev trains has several extraordinary characteristics: 1) as light as possible; 2) enough degrees of freedom; 3) special mechanically-braking mode; 4) unique lateral load way 5) vehicles fall on rail to slide under emergency. The vehicles are composed of three parts as shown in Fig.4: car body at the top, secondary suspension at the middle and running gear at the bottom. The wheel rail vehicles have only two bogies through wheel pair contact with rail, but bogies of the maglev trains distributed along the entire length of vehicles, so they are strikingly different in structure.

The two wheel pair of wheel rail vehicles is installed on a rigid frame in the same plane. The four points in the frame of maglev bogies, the detection points of gap sensors, should move independently. The bogies have two typical structures: the bogie with torsion longeron is shown as Fig.6 (Maglev Technical Committee, 2007), Fig.8 (Z.S. ZHAO & L.M. YING, 2007). Two levitation frame units 8 are connected by torsion longeron 7 to form The maglev bogies. In vertical direction, the bogies realize the independent motion of four points by reversed longeron (the bogies hereinafter referred as T-type bogies); and the bogie is assembled by connection tow module 8 with anti-rolling beam 1, as shown in Fig.7.

Structural and Kinematic Analysis of EMS Maglev Trains 99

drive the air spring transverse rod 7, then the force is transmitted to thrust rod 8 whose motion drives the T-type rod to rotate, the rotation is passed to another T-type rod by linkage wire ropes, then thrust rod and transverse rod of next bogie drive its modules to

The secondary suspension system transmits three forces in different directions between car body and bogies and the transmission course is as follows: the vertical load transmits in maglev track←→ electromagnet ←→ modules ←→diaphragm air spring ←→ rolling

The transverse load transmits in car body ←→ T-type rod ←→ wire rope, transverse link ←→ lower rolling table ←→ air spring tie rod ←→ modules ←→electromagnet ←→ track. It can be seen that plenty of bogies distributed along the length of car body contribute to the relative complex joint of car body and bogies. If the tilting suspension system is adopted, the maglev bogie 4 has sixteen pendulum binding mechanisms; if the rolling table is adopted,

Although EMS maglev trains fly at a zero height, it still needs exercise along maglev guideway necessary. The position vectors can be divided along guideway (longitudinal), perpendicular guideway surface (vertical), perpendicular guideway side(lateral) three

The vertical motion is controlled by the system composed of gap sensor, levitation controller and levitation electromagnet with limitation. The transversal motion is restricted by transversal electromagnetic force and the longitudinal motion is related to the transversal motion and the constraint between all parts of vehicles. According to last paragraph, the vehicle is composed of running gear, secondary suspension system and car body and it's kinematic analysis includes the analysis on the spatial positions of all parts and the relative

deflect and so far the steering action is completed.

there are ten point of junction for the steering mechanism.

**3. Kinematic characteristics of EMS maglev trains** 

table←→ car body.

components.

positions of all parts.

Fig. 8. Bogie Decoupling by torsion beam

1. Support arm, 2.Levitation magnet, 3. Crossbeam, 4.Air spring & Pendulum arm, 5.Guidance magnet, 6.Support skid, 7.Torsional longeron, 8.Levitation frame unit, 9. Gap sensor

Fig. 6. A bogie of high-speed maglev vehicle

The bogies realize the independent motion of four points by relative torsion of two antirolling beams 1 (the bogies hereinafter referred as A-type bogies).

1. Anti-rolling beam, 2.Air spring, 3.Linear induction motor, 4.Linear rolling table, 5.Drive staff, 6.Forced steering mechanism, 7.transverse rod, 8.Module, 9.Lvitation magnet, 10.Gap sensor, 11.thrust rod, 12.Rocker.

Fig. 7. A bogie of middle-low speed maglev vehicle

Generally speaking, the running gear of maglev trains is composed of several bogies. The maglev trains and wheel rail trains also differ in the connection among bogies and between bogies and carriages. As shown in Fig.6, bogies are connected by overlap electromagnet 2 and spring hinges to form the maglev running gear (Fig.4), and joints with car body by the tilting suspension system 7. As shown in Fig.7, 9, 10, bogies are grouped in pairs by forced steering mechanisms 6 to make up the running gear, which is connected with the carriages by hinges A、C1~C4 and rolling table 4. The linear rolling table is equipped at the end of bogie modules 8 which can rotate around the shaft C in a small angle. The forced steering mechanism 6 is composed of wire ropes and T-type rod. As it turns, the modules deflect to

1. Support arm, 2.Levitation magnet, 3. Crossbeam, 4.Air spring & Pendulum arm, 5.Guidance magnet,

The bogies realize the independent motion of four points by relative torsion of two anti-

1. Anti-rolling beam, 2.Air spring, 3.Linear induction motor, 4.Linear rolling table, 5.Drive staff, 6.Forced steering mechanism, 7.transverse rod, 8.Module, 9.Lvitation magnet, 10.Gap sensor, 11.thrust

Generally speaking, the running gear of maglev trains is composed of several bogies. The maglev trains and wheel rail trains also differ in the connection among bogies and between bogies and carriages. As shown in Fig.6, bogies are connected by overlap electromagnet 2 and spring hinges to form the maglev running gear (Fig.4), and joints with car body by the tilting suspension system 7. As shown in Fig.7, 9, 10, bogies are grouped in pairs by forced steering mechanisms 6 to make up the running gear, which is connected with the carriages by hinges A、C1~C4 and rolling table 4. The linear rolling table is equipped at the end of bogie modules 8 which can rotate around the shaft C in a small angle. The forced steering mechanism 6 is composed of wire ropes and T-type rod. As it turns, the modules deflect to

6.Support skid, 7.Torsional longeron, 8.Levitation frame unit, 9. Gap sensor

rolling beams 1 (the bogies hereinafter referred as A-type bogies).

Fig. 6. A bogie of high-speed maglev vehicle

Fig. 7. A bogie of middle-low speed maglev vehicle

rod, 12.Rocker.

drive the air spring transverse rod 7, then the force is transmitted to thrust rod 8 whose motion drives the T-type rod to rotate, the rotation is passed to another T-type rod by linkage wire ropes, then thrust rod and transverse rod of next bogie drive its modules to deflect and so far the steering action is completed.

The secondary suspension system transmits three forces in different directions between car body and bogies and the transmission course is as follows: the vertical load transmits in maglev track←→ electromagnet ←→ modules ←→diaphragm air spring ←→ rolling table←→ car body.

The transverse load transmits in car body ←→ T-type rod ←→ wire rope, transverse link ←→ lower rolling table ←→ air spring tie rod ←→ modules ←→electromagnet ←→ track.

It can be seen that plenty of bogies distributed along the length of car body contribute to the relative complex joint of car body and bogies. If the tilting suspension system is adopted, the maglev bogie 4 has sixteen pendulum binding mechanisms; if the rolling table is adopted, there are ten point of junction for the steering mechanism.

### **3. Kinematic characteristics of EMS maglev trains**

Although EMS maglev trains fly at a zero height, it still needs exercise along maglev guideway necessary. The position vectors can be divided along guideway (longitudinal), perpendicular guideway surface (vertical), perpendicular guideway side(lateral) three components.

The vertical motion is controlled by the system composed of gap sensor, levitation controller and levitation electromagnet with limitation. The transversal motion is restricted by transversal electromagnetic force and the longitudinal motion is related to the transversal motion and the constraint between all parts of vehicles. According to last paragraph, the vehicle is composed of running gear, secondary suspension system and car body and it's kinematic analysis includes the analysis on the spatial positions of all parts and the relative positions of all parts.

Fig. 8. Bogie Decoupling by torsion beam

Structural and Kinematic Analysis of EMS Maglev Trains 101

Fig. 10. Connection between Secondary suspend system, car body & running gear, and two

But the problem is far from simple. For example, the relative position of car body and running gear of vehicle as shown in Fig.4 must be calculated based on the sixteen pendulum suspension mechanisms for the joint of car body and bogie. If the relative position of car body and bogie in the curve changes, the rocker deflects and the weight W of car body transmitted by the sixteen suspenders to the bogie is decomposed into two component forces Wi, Wj, so the transversal relative position of car body and bogie involves the balance of sixteen transversal forces Wi but not a simple calculation of geometric relationships.

For the vehicle as shown in Fig.5, the constraint of electromagnetic restoring force in the relative position of bogies and track is described in the preceding paragraph. It is easy to calculate the relative position of single bogie and guideway, namely the instantaneous position or locus, then the relative positions or topological relations among all components can be deduced by electromagnetic balance. However, owing to the complexity of connection relationships between several bogies and car body (Fig.10), this calculation method can not be extended to the vehicle. A typical case is when a bogie enters into the transition curve and the following bogie is still in the straight-line guideway, the front bogie rotates around the points C1, C2 and the following bogie is droved to rotate around the points C3, C4 owing to the effect of forced steering mechanism 3, so the following bogie doesn't move along a straight line. The reason lies in that there is a balance relationship of restraining force between the lateral electromagnetic restoring force and components and it should not considered simply that the bogies are pulled to the track by electromagnetic restoring forces. Therefore, different from the wheel rail vehicles, the passive guidance EMS maglev trains may not run in the track curve. The vehicle electromagnetic restoring force, constraint among all components and track geometry curve must be considered comprehensively to deduce the instantaneous position or trace of a bogie in absolute coordinate by the force balance relation and geometrical relation of vehicle in any position, then the relative positions between the rigid bodies or topological relations of all components are deduced by connection relations. However, it brings big

**4. Kinematic modeling and analysis of maglev trains (Z.S. Zhao and C. Ren,** 

The kinematic characteristics of EMS maglev trains illustrated in the preceding paragraph show that the motion of maglev trains can not be deduced simply by geometrical relations. Based on the passive EMS maglev trains, the following kinematic analysis includes

1. Railway, 2.Carbody, 3. Forced steering mechanism, 4.Module, 5.Linear bearing.

bogies is connected by forced steering mechanism

difficulties in solving this problem.

**2009)** 

1. Module, 2.anti-rolling beam, 3.pedulum rod, 4. Sphere joint.

Fig. 9. Bogie decoupling by anti-rolling beam

The maglev bogies are the basic components of running gears and their displacements are crucial for the determination of vehicle motion. Their kinematic characteristic is that A, B, C and D points(Fig.8, 9)should move independently (uncoupling). Four straight lines can be drawn by the four points. When the maglev bogies are running along curved path, the four rectilinear motion space surfaces is the Coons surface. When the maglev bogies are passing the transition curve, the four points are not in the same plane. Both A-type bogies and T-type bogies can realize this motion. T-type bogies realize the motion by torsion beams and A-type bogies by the torsion of two anti-rolling beams. However, A-type bogies and Ttype bogies have big differences in their transversal motions. The bogie as shown in Fig.6 can only make lateral movement as a whole. In addition, because its secondary suspension system is pendulous and there will produce a big transverse component of gravity force acting on the bogie by pendulum suspension system when the vehicle is passing the curve, the bogie has a bad ability to follow the guideway transversally and can not pass the curve with a small curvature radius and need an active guidance force provided by guidance electromagnet 5 as shown in Fig.6.

Two modules 8 of the bogies as shown in Fig.7 should move independently. Each module has three translational (X, Y, Z) and two rotational (Y, Z) degrees of freedom. It can pass the curves with a small curvature radius and there is hardly any limit in its lateral motion in a small range, so by adopting levitation electromagnet 9 as shown in Fig.6 it can provide a passive guidance force which is a component of levitation force and only exists when the electromagnet is deviating from the guideway and thus it is called as passive guidance force. By now it seems that the motion problem of vehicles has been solved. The track curve can determine the instantaneous position of the bogie, then the relative positions between bogies, bogie and second suspension system and car bodies by connection relationship and the absolute spatial positions of all parts, all of which only involve the deduction of geometric relationships.

The maglev bogies are the basic components of running gears and their displacements are crucial for the determination of vehicle motion. Their kinematic characteristic is that A, B, C and D points(Fig.8, 9)should move independently (uncoupling). Four straight lines can be drawn by the four points. When the maglev bogies are running along curved path, the four rectilinear motion space surfaces is the Coons surface. When the maglev bogies are passing the transition curve, the four points are not in the same plane. Both A-type bogies and T-type bogies can realize this motion. T-type bogies realize the motion by torsion beams and A-type bogies by the torsion of two anti-rolling beams. However, A-type bogies and Ttype bogies have big differences in their transversal motions. The bogie as shown in Fig.6 can only make lateral movement as a whole. In addition, because its secondary suspension system is pendulous and there will produce a big transverse component of gravity force acting on the bogie by pendulum suspension system when the vehicle is passing the curve, the bogie has a bad ability to follow the guideway transversally and can not pass the curve with a small curvature radius and need an active guidance force provided by guidance

Two modules 8 of the bogies as shown in Fig.7 should move independently. Each module has three translational (X, Y, Z) and two rotational (Y, Z) degrees of freedom. It can pass the curves with a small curvature radius and there is hardly any limit in its lateral motion in a small range, so by adopting levitation electromagnet 9 as shown in Fig.6 it can provide a passive guidance force which is a component of levitation force and only exists when the electromagnet is deviating from the guideway and thus it is called as passive guidance force. By now it seems that the motion problem of vehicles has been solved. The track curve can determine the instantaneous position of the bogie, then the relative positions between bogies, bogie and second suspension system and car bodies by connection relationship and the absolute spatial positions of all parts, all of which only involve the deduction of

1. Module, 2.anti-rolling beam, 3.pedulum rod, 4. Sphere joint.

Fig. 9. Bogie decoupling by anti-rolling beam

electromagnet 5 as shown in Fig.6.

geometric relationships.

1. Railway, 2.Carbody, 3. Forced steering mechanism, 4.Module, 5.Linear bearing.

Fig. 10. Connection between Secondary suspend system, car body & running gear, and two bogies is connected by forced steering mechanism

But the problem is far from simple. For example, the relative position of car body and running gear of vehicle as shown in Fig.4 must be calculated based on the sixteen pendulum suspension mechanisms for the joint of car body and bogie. If the relative position of car body and bogie in the curve changes, the rocker deflects and the weight W of car body transmitted by the sixteen suspenders to the bogie is decomposed into two component forces Wi, Wj, so the transversal relative position of car body and bogie involves the balance of sixteen transversal forces Wi but not a simple calculation of geometric relationships.

For the vehicle as shown in Fig.5, the constraint of electromagnetic restoring force in the relative position of bogies and track is described in the preceding paragraph. It is easy to calculate the relative position of single bogie and guideway, namely the instantaneous position or locus, then the relative positions or topological relations among all components can be deduced by electromagnetic balance. However, owing to the complexity of connection relationships between several bogies and car body (Fig.10), this calculation method can not be extended to the vehicle. A typical case is when a bogie enters into the transition curve and the following bogie is still in the straight-line guideway, the front bogie rotates around the points C1, C2 and the following bogie is droved to rotate around the points C3, C4 owing to the effect of forced steering mechanism 3, so the following bogie doesn't move along a straight line. The reason lies in that there is a balance relationship of restraining force between the lateral electromagnetic restoring force and components and it should not considered simply that the bogies are pulled to the track by electromagnetic restoring forces. Therefore, different from the wheel rail vehicles, the passive guidance EMS maglev trains may not run in the track curve. The vehicle electromagnetic restoring force, constraint among all components and track geometry curve must be considered comprehensively to deduce the instantaneous position or trace of a bogie in absolute coordinate by the force balance relation and geometrical relation of vehicle in any position, then the relative positions between the rigid bodies or topological relations of all components are deduced by connection relations. However, it brings big difficulties in solving this problem.

### **4. Kinematic modeling and analysis of maglev trains (Z.S. Zhao and C. Ren, 2009)**

The kinematic characteristics of EMS maglev trains illustrated in the preceding paragraph show that the motion of maglev trains can not be deduced simply by geometrical relations. Based on the passive EMS maglev trains, the following kinematic analysis includes

Structural and Kinematic Analysis of EMS Maglev Trains 103

accordingly based on geometrical relations. Pi is in the straight line representing bogies

respectively and should satisfy the following relations:

Fig. 12. Instantaneous Position of the maglev vehicle with four bogies

There i=1, 4,8,11. The geometrical relation between carriage and bogie is:

The intersection relation of curve and straight line is:

2 12 2 12 31 21 31 21

2 2

2 1 2 2 12 3 1 2 1 1 21

 

In the above equation, i=1, 4,8,11. The straight line representing the centre line of carriage is:

<sup>0</sup> *yy yy xy x y*

*i i i i ii i i i i i i ii i i*

4 11 4 11

4 11 4 11

*xx xx*

*y Yx Yx Yx xx x x y Yx Yx Yx xx x x*

( ) ()( ) <sup>0</sup>

( ) ( )( ) <sup>0</sup>

( )( ) <sup>0</sup> ( )( ) ( )( )

( )( ) <sup>0</sup> ( )( )

 

*ii i i ii i i ii ii ii ii ii ii*

*yy y y xx x x yy yy xx xx xx yy L*

2 2 2 3 3

4 11 4 11 ( ) ( ) 0.5 *<sup>c</sup> x x y y L* (4-2)

4 4

(4-1)

(4-3)

kinematic modelling and analysis. The vertical position of vehicle is controlled by the levitation gap between electromagnet and guideway. Because the gap is constant, the vertical position of vehicle can be determined by the track curve and the determination of lateral instantaneous position is the key of kinematic research on vehicles.

The research on instantaneous position adopts two methods based on track fitting: strict fitting track (two endpoints of the bogie on the track) (ZHAO Z.S. & YING L.M., 2000; MEI Z. & LI J., 2007; JIANG H.B., et al., 2007) and balanced lateral electromagnetic restoring force of single bogie (ZENG Y.W. & WANG S.H. 2003; ZHANG K. & LI J., 2005; ZHAO C.F & ZAI W.M., 2005). The former is obviously an unproved hypothesis and the later doesn't consider the influence of constraint among all components in the motion.

1.Anti-rolling beam, 2.Linear rolling table, 3.forced steering mechanism, 4.T type rod, 5.Wire rope, 6.Levitation magnet, 7.module.

Fig. 11. Running gear sketch of the passiveness guidance EMS maglev train

### **4.1 Kinematic modelling of EMS mid-low speed maglev trains**

To simplify the problem without loss of generality, in this article derivations is made based on the following conditions: 1) because the Z-directional motion of vehicle has a little influence on its lateral motion, its mathematical deduction is based on X-Y plane; 2) the model is established for the vehicle with four bogies; 3) the axis C1-C4 are combined into two axis P4, P11 (Fig.12); 4) the kinematic modelling is only based on the central line of track; 5) the carriages and bogies are rigid bodies with the lengths of LC、L respectively.

### **4.1.1 Kinematic modeling of maglev trains based on geometrical relations**

In the instantaneous position sketch of maglev trains as shown in Fig. 12, Pi(xi, yi)represent bogies' end point and intersection point of bogies and track curve Y(x). If Pi is definite, the instantaneous position or motion locus of vehicle and the relative positions (topological relations) among the components of vehicle and between vehicle and track may be determined. The section aims to establish the equations with the unknown quantities xi, yi

kinematic modelling and analysis. The vertical position of vehicle is controlled by the levitation gap between electromagnet and guideway. Because the gap is constant, the vertical position of vehicle can be determined by the track curve and the determination of

The research on instantaneous position adopts two methods based on track fitting: strict fitting track (two endpoints of the bogie on the track) (ZHAO Z.S. & YING L.M., 2000; MEI Z. & LI J., 2007; JIANG H.B., et al., 2007) and balanced lateral electromagnetic restoring force of single bogie (ZENG Y.W. & WANG S.H. 2003; ZHANG K. & LI J., 2005; ZHAO C.F & ZAI W.M., 2005). The former is obviously an unproved hypothesis and the later doesn't consider

1.Anti-rolling beam, 2.Linear rolling table, 3.forced steering mechanism, 4.T type rod, 5.Wire rope,

To simplify the problem without loss of generality, in this article derivations is made based on the following conditions: 1) because the Z-directional motion of vehicle has a little influence on its lateral motion, its mathematical deduction is based on X-Y plane; 2) the model is established for the vehicle with four bogies; 3) the axis C1-C4 are combined into two axis P4, P11 (Fig.12); 4) the kinematic modelling is only based on the central line of track; 5)

In the instantaneous position sketch of maglev trains as shown in Fig. 12, Pi(xi, yi)represent bogies' end point and intersection point of bogies and track curve Y(x). If Pi is definite, the instantaneous position or motion locus of vehicle and the relative positions (topological relations) among the components of vehicle and between vehicle and track may be determined. The section aims to establish the equations with the unknown quantities xi, yi

Fig. 11. Running gear sketch of the passiveness guidance EMS maglev train

the carriages and bogies are rigid bodies with the lengths of LC、L respectively.

**4.1.1 Kinematic modeling of maglev trains based on geometrical relations** 

**4.1 Kinematic modelling of EMS mid-low speed maglev trains** 

lateral instantaneous position is the key of kinematic research on vehicles.

the influence of constraint among all components in the motion.

6.Levitation magnet, 7.module.

accordingly based on geometrical relations. Pi is in the straight line representing bogies respectively and should satisfy the following relations:

Fig. 12. Instantaneous Position of the maglev vehicle with four bogies

$$\begin{cases} \frac{(y\_i - y\_{i+2})}{(x\_i - x\_{i+2})} - \frac{(y\_{i+1} - y\_{i+2})}{(x\_{i+1} - x\_{i+2})} = 0\\ \frac{(y\_{i+3} - y\_{i+1})}{(x\_{i+3} - x\_{i+1})} - \frac{(y\_{i+2} - y\_{i+1})}{(x\_{i+2} - x\_{i+1})} = 0\\ (x\_i - x\_{i+3})^2 + (y\_i - y\_{i+3})^2 = L^2 \end{cases} \tag{4-1}$$

There i=1, 4,8,11. The geometrical relation between carriage and bogie is:

$$\sqrt{\left(\mathbf{x}\_4 - \mathbf{x}\_{11}\right)^2 + \left(y\_4 - y\_{11}\right)^2} = 0.5L\_c \tag{4-2}$$

The intersection relation of curve and straight line is:

$$\begin{cases} \frac{y\_i - Y(\mathbf{x}\_{i+2})}{\mathbf{x}\_i - \mathbf{x}\_{i+2}} - \frac{Y(\mathbf{x}\_{i+1}) - Y(\mathbf{x}\_{i+2})}{\mathbf{x}\_{i+1} - \mathbf{x}\_{i+2}} = 0\\ \frac{y\_{i+3} - Y(\mathbf{x}\_{i+1})}{\mathbf{x}\_i - \mathbf{x}\_{i+1}} - \frac{Y(\mathbf{x}\_{i+2}) - Y(\mathbf{x}\_{i+1})}{\mathbf{x}\_{i+2} - \mathbf{x}\_{i+1}} = 0 \end{cases} \tag{4.-3}$$

In the above equation, i=1, 4,8,11. The straight line representing the centre line of carriage is:

$$\left(\frac{y\_4 - y\_{11}}{x\_4 - x\_{11}}\right)\mathbf{x} - y - \left(\frac{y\_4 - y\_{11}}{x\_4 - x\_{11}}\right)\mathbf{x}\_4 + y\_4 = \mathbf{0}$$

Structural and Kinematic Analysis of EMS Maglev Trains 105

In the same way, the calculation formula of the electro magnetic restoring force differential

1

(i=1,2,3,4).

sin 0

 

(4-5)

(4-6)

 

cos 0

1

tan 0

(1 ) tan <sup>0</sup>

1

2 4

<sup>1</sup> tan ( ) 0 <sup>1</sup>

(1 ) tan ( 1) ( ( )) <sup>1</sup>

<sup>4</sup> *Y x y dx* () ) 0

*kk k u K y <sup>Y</sup> <sup>x</sup> dx*

*kk k u <sup>K</sup> dx*

tan

2

*i kk u F K dx k*

4

*F F*

*F F*

1 1

1

*<sup>x</sup> s i <sup>i</sup> <sup>i</sup>*

*k*

*x ui i i*

*y ui i i*

2

*kk u <sup>K</sup> dx*

*<sup>x</sup> si i <sup>i</sup> <sup>m</sup> <sup>x</sup> <sup>i</sup> <sup>i</sup>*

*k*

2

Balance equation of moment of lateral restoring force (taking P4 as the pivoting point)

*<sup>x</sup> s i <sup>i</sup> <sup>m</sup> <sup>x</sup> <sup>i</sup> <sup>i</sup>*

*k*

1 2 4

3 1

*kk u K x <sup>x</sup>*

1 2 4

<sup>1</sup> tan ( 1) ( ) <sup>1</sup>

*kk u <sup>K</sup> x x dx*

3 1

(1 ) tan ( <sup>1</sup>

3

*k*

*k*

*<sup>x</sup> si i <sup>i</sup> <sup>i</sup>*

*<sup>x</sup> s i <sup>m</sup> <sup>x</sup>*

2 3

*<sup>x</sup> s i <sup>i</sup> <sup>m</sup> <sup>x</sup>*

*kk k u <sup>K</sup> k*

4

*<sup>x</sup> s i <sup>i</sup>*

Fig. 13. Magnet lateral reversion force of the bogie module

2 1

*i i*

*ui m <sup>x</sup>*

1

1

1. Balance equation of lateral restoring force and moment of the vehicle:

*i i i i*

4

4

1 2

*i i*

4

3

4

3

1 2

*i i*

31 32

*<sup>m</sup> <sup>x</sup> <sup>i</sup> <sup>i</sup>*

31 32

*<sup>m</sup> <sup>x</sup> <sup>i</sup> <sup>i</sup>*

unit of other bogies can be deduced:

The offset distance from the bogie endpoints to the car body obtained by the distance from

point to line: 4 11 4 4 11 4 c ( )( ) ( )( ) 0.5L *i i i y y xx x x yy* , in which i=1,7,8,1. Follow equation

(ZHAO Z.S. et al., 2000) is given by the structural symmetry and the constraint of forced steering mechanism,

$$\frac{\Delta\_1}{\Delta\_7} = \frac{\Delta\_{14}}{\Delta\_8} \tag{4-4}$$

there are twenty-two equations with twenty-eight unknown quantities Pi(xi、yi) in the above (4-1)-(4-4), it is obvious that the kinematic problem of vehicle can not be solved only by geometrical relations and other equations should be founded by the balance relations of lateral forces.

#### **4.1.2 Kinematic modeling of maglev trains based on the constraint of lateral electromagnetic restoring force and mechanism constrain**

The passive guidance EMS maglev train keeps a lateral position from electromagnetic restoring force. To seek balance of lateral force, it should be considered that the calculation of electromagnetic resilience generated by the linear bogie units fitting the curved track; the influence of constraint such as the binding force produced among the bogies owing to interconnection of the forced steering mechanisms and carriages an bogies. In this section, other equations shall be sought for by the balance of lateral forces, the calculation formula of lateral forces (Sinha P. K., 1987) is:

$$F\_u = K\_m L\_w \tan^{-1} \left(\frac{\Delta u}{\delta}\right).$$

in which 2 2 0 4 *<sup>m</sup> N I <sup>K</sup>* , *<sup>w</sup> m <sup>A</sup> <sup>L</sup> W* , Lw is length of magnetic pole,μ0, N, A, I represents

vacuum permeability and turns,effective area of magnetic pole,coil current respectively, other parameters can refer to Fig.13. Taking the first bogie for example, the electromagnetic restoring force of any infinitesimal curve unit ds in the track is:

$$dF\_{u1} = K\_m \tan^{-1} \left(\frac{\Delta \mu\_1}{\delta}\right) dL\_w$$

Δu1 represents the distance from a point q(x,y) in the curve to the line: 1 4 1 4 14 41 1 ( ) ( )() *y y x x x Yx xy xy <sup>u</sup> L* ,seeing to (Fig. 13), 1 cos( ) *w s dL ds* , cos *<sup>s</sup> ds dx* , *ks s* tan , 1 4 1 1 tan *<sup>y</sup> <sup>y</sup> <sup>k</sup> x x* , dFu1 can be written as:

$$dF\_{u1} = \frac{1 + k\_s k\_1}{\sqrt{1 + k\_1^2}} K\_m \tan^{-1} \left(\frac{\Delta u\_1}{\delta}\right) dx^1$$

1 4

The offset distance from the bogie endpoints to the car body obtained by the distance from

(ZHAO Z.S. et al., 2000) is given by the structural symmetry and the constraint of forced

1 14 7 8

there are twenty-two equations with twenty-eight unknown quantities Pi(xi、yi) in the above (4-1)-(4-4), it is obvious that the kinematic problem of vehicle can not be solved only by geometrical relations and other equations should be founded by the balance relations of

The passive guidance EMS maglev train keeps a lateral position from electromagnetic restoring force. To seek balance of lateral force, it should be considered that the calculation of electromagnetic resilience generated by the linear bogie units fitting the curved track; the influence of constraint such as the binding force produced among the bogies owing to interconnection of the forced steering mechanisms and carriages an bogies. In this section, other equations shall be sought for by the balance of lateral forces, the calculation formula of

1

1 1 <sup>1</sup>*u m* tan *<sup>w</sup> <sup>u</sup> dF K dL*

, dFu1 can be written as:

1 1 1

tan

*k k <sup>u</sup> dF <sup>K</sup> dx*

 

vacuum permeability and turns,effective area of magnetic pole,coil current respectively, other parameters can refer to Fig.13. Taking the first bogie for example, the electromagnetic

Δu1 represents the distance from a point q(x,y) in the curve to the line:

,seeing to (Fig. 13), 1 cos( ) *w s dL*

1 4

1

*k*

*x x*

*W* , Lw is length of magnetic pole,μ0, N, A, I represents

 *ds* ,

*u mw* tan *<sup>u</sup> F KL*

*m*

 , 1 4 1 1

tan *<sup>y</sup> <sup>y</sup> <sup>k</sup>*

<sup>1</sup> <sup>2</sup>

1 *<sup>s</sup> u m*

1

*<sup>A</sup> <sup>L</sup>*

restoring force of any infinitesimal curve unit ds in the track is:

1 4 1 4 14 41

( ) ( )() *y y x x x Yx xy xy <sup>u</sup> L*

, *ks s* tan

**4.1.2 Kinematic modeling of maglev trains based on the constraint of lateral** 

**electromagnetic restoring force and mechanism constrain** 

*y y xx x x yy* , in which i=1,7,8,1. Follow equation

(4-4)

c ( )( ) ( )( ) 0.5L *i i*

point to line: 4 11 4 4 11 4

*i*

lateral forces (Sinha P. K., 1987) is:

2 2 0 4 *<sup>m</sup> N I <sup>K</sup>* 

, *<sup>w</sup>*

steering mechanism,

lateral forces.

in which

1

cos *<sup>s</sup> ds dx* 

Fig. 13. Magnet lateral reversion force of the bogie module

In the same way, the calculation formula of the electro magnetic restoring force differential unit of other bogies can be deduced:

$$F\_{ui} = \int\_{x\_{i1}}^{x\_{i2}} K\_m \frac{1 + k\_s k\_i}{\sqrt{1 + k\_i^2}} \tan^{-1} \left(\frac{\Delta u\_i}{\delta}\right) d\mathbf{x} \quad (\text{ i=1,2,3,4}) \quad . $$

1. Balance equation of lateral restoring force and moment of the vehicle:

$$\begin{aligned} \sum F\_x &= \sum\_i^4 F\_{ui} \sin \alpha\_i = 0\\ \sum F\_y &= \sum\_i^4 F\_{ui} \cos \alpha\_i = 0 \end{aligned} $$

$$\begin{aligned} \sum\_i^4 \int\_{x\_{i1}}^{x\_{i2}} K\_m \frac{(1 + k\_s k\_i) k\_i}{1 + k\_i^2} \tan^{-1} \left(\frac{\Delta u\_i}{\delta}\right) d\mathbf{x} &= 0\\ \sum\_i^4 \int\_{x\_{i1}}^{x\_{i2}} K\_m \frac{1 + k\_s k\_i}{1 + k\_i^2} \tan^{-1} \left(\frac{\Delta u\_i}{\delta}\right) d\mathbf{x} &= 0 \end{aligned} \tag{4.5}$$

Balance equation of moment of lateral restoring force (taking P4 as the pivoting point)

$$\begin{aligned} &\left(\sum\_{i=1}^{4} K\_{x\_{i2}} \frac{1 + k\_s k\_i}{1 + k\_i^2} \tan^{-1} \left(\frac{\Delta u\_i}{\delta}\right) (-1)^i (\mathbf{x}\_4 - \mathbf{x}) d\mathbf{x} + \\ &\quad + \int\_{x\_{32}}^{x\_{31}} K\_m \frac{1 + k\_s k\_3}{1 + k\_3^2} \tan^{-1} \left(\frac{\Delta u\_i}{\delta}\right) (\mathbf{x} - \mathbf{x}\_4) = \mathbf{0} \\ &\quad \sum\_{i=3}^4 \int\_{x\_{i2}}^{x\_{i1}} K\_m \frac{(1 + k\_s k\_i) k\_i}{1 + k\_i^2} \tan^{-1} \left(\frac{\Delta u\_i}{\delta}\right) (-1)^i (y\_4 - Y(\mathbf{x})) d\mathbf{x} + \\ &\quad + \int\_{x\_{32}}^{x\_{31}} K\_m \frac{(1 + k\_s k\_i) k\_3}{1 + k\_3^2} \tan^{-1} \left(\frac{\Delta u\_i}{\delta}\right) (Y(\mathbf{x}) - y\_4) d\mathbf{x} = \mathbf{0} \end{aligned} \tag{4-6}$$

Structural and Kinematic Analysis of EMS Maglev Trains 107

 

1 11 1 11 1 *k x x Yx y* ( ) (( ) ) 0 (4-10)

23 2 3

Substituting x11、y11=Y(x11) in the above first equation, the following equation can be

In the above six equations in(4-5)(4-6)(4-8)(4-9)obtained by the balance between lateral electromagnetic resilience and structural constraint force, the equations (8), (9) introduce a unknown quantity η. Hereby the equation (4-10) is introduced and a reference point q11(x11、y11)to instantaneous position of vehicle is given. The equations (4-1)-(4-6) and (4-8)-(4-10) are the non-linear equation set with twenty-nine unknown quantities, namely twenty-nine unknown quantities Pi(xi、yi)and *η* can be resolved. This is the general formula for kinematic analysis on passive EMS maglev trains with four bogies which can be used to resolve the absolute position (motion trace) of any bogie and the relative position or topological relation of any component of the vehicle at any time. In the same way, kinematics equations of maglev train with other number bogies can be deduced.

( ) (( ) ) 0 ( ) (( ) ) 0

1 1

**4.1.3 General kinematic characters of passive guidance EMS maglev trains** 

Following kinematic characters of vehicles can be deduced by the above general kinematic

Character 1: kinematic the static determinacy or indeterminacy of vehicles is determined by the forced steering mechanism, namely the topological relation between a bogie and carriage (formula (4-4), (4-7)) must be given and if not, there will be multiple solutions of

Character 2: n, namely the number of intersection points of the modules (straight line) and track (convex curve), 1≤n≤2, two geometric equations will be reduced for each reduced crossing point and in the straight-line segment of track, the bogies are coincident with the

Character 3: the motion trace of vehicle is determined together by the topological relations

Character 4: The steering characteristic and yawing characteristic of vehicle with transverse interference depend on the balance relation between the lateral electromagnetic restoring

**4.2 Solution and analysis of kinematic equations of EMS mid-low speed maglev trains**  Given that N=320,Wm=28 mm,A=3360×28 mm2,L=3.4 m,Lc=14.5 m , circular curve radius R=100 m,superelevation is 60 mm,transition curve length *l0*=12 m, the easement trace curve is the clothoid generally, the curvature of easement curve <sup>0</sup> *k s Rl* and the high-order small quantities are ignored, the projection of x-y plane of

between bogie and carriage and bogie and track but not only by the track.

force and the constraint force of forced steering mechanism.

obtained:

formulas:

motion trace.

trace curve is:

track.

*k x x Yx y k x x Yx y*

*ii j i j ii j i j*

2. Balance of constraint force of forced steering mechanism

Fig. 14. Balance of two bogies linked by compelling guided mechanism

3. According to Fig.14, the balance equation of constraint force of forced steering mechanism linking the No.1,2 bogies is *f11l11=f12l12*,and the following equation can be obtained:

$$f\_{12} = f\_{11} \frac{l\_{11}}{l\_{12}} = \eta f\_{11} \tag{4-7}$$

The moment arm length from the point P4 to No.1 bogie's any point dFu1 on which electromagnetic resilience is exerted is <sup>4</sup> <sup>2</sup> 4 1 1 ( )1 cos *x x xx k* , the balance relation of No.1

bogie module's moment is <sup>12</sup> 11 1 1 11 1 1 4 0.5 cos (1 )( )tan *<sup>x</sup> m s <sup>x</sup> <sup>u</sup> <sup>f</sup> L K kk x x dx* , namely,

12 11 2 1 1 11 1 14 <sup>2</sup> (1 ) 1 ( )tan *<sup>x</sup> m s <sup>x</sup> <sup>u</sup> <sup>f</sup> K kk k x x dx L* , similarly f12 can be obtained, and substituted in(7):

$$\sum\_{i=1,2} \eta^{2-i} \int\_{x\_{i2}}^{x\_{i1}} K\_m(1+k\_s k\_i) \sqrt{1+k\_i^2} \left(x\_4 - x\right) \tan^{-1} \left(\frac{\Delta u\_i}{\delta}\right) dx = 0 \tag{4-8}$$

By the above method the constraint forces' balance equation of forced steering mechanisms connecting No.3, 4 bogies can be obtained:

$$\sum\_{i=3,4} \eta^{i-3} \int\_{x\_{i2}}^{x\_{i1}} K\_m(1+k\_s k\_i) \sqrt{1+k\_i^2} \left(x - x\_{11}\right) \tan^{-1} \left(\frac{\Delta u\_i}{\delta}\right) dx \quad \text{=} 0 \tag{4-9}$$

The upper or lower limit of integration are the coordinate x of the intersection points qi1、qi2 of two straight lines perpendicular to the endpoints Pi、Pi+3 of the No.1 bogie and the curve Y(x). Its expression is written as (corresponding to four bogies, j=1, 4, 8, and 11):

3. According to Fig.14, the balance equation of constraint force of forced steering mechanism linking the No.1,2 bogies is *f11l11=f12l12*,and the following equation can be

> 11 12 11 11 12 *<sup>l</sup> ff f <sup>l</sup>*

The moment arm length from the point P4 to No.1 bogie's any point dFu1 on which

1

*<sup>x</sup> <sup>i</sup> <sup>i</sup>*

*K kk k x x dx*

By the above method the constraint forces' balance equation of forced steering mechanisms

2 2 1

3 2 1

Y(x). Its expression is written as (corresponding to four bogies, j=1, 4, 8, and 11):

(1 ) 1 ( )tan *<sup>i</sup>*

*<sup>x</sup> <sup>i</sup> <sup>i</sup>*

*K kk k x x dx*

The upper or lower limit of integration are the coordinate x of the intersection points qi1、qi2 of two straight lines perpendicular to the endpoints Pi、Pi+3 of the No.1 bogie and the curve

11

cos

2 1 1

( )1

*x x xx k*

11 1 1 4 0.5 cos (1 )( )tan *<sup>x</sup> m s <sup>x</sup> <sup>u</sup> <sup>f</sup> L K kk x x*

, similarly f12 can be obtained, and

4

 (4-8)

11

 =0 (4-9)

(1 ) 1 ( )tan 0 *<sup>i</sup>*

4 1

*dx*

*u*

*u*

(4-7)

1 1

, the balance relation of No.1

, namely,

2. Balance of constraint force of forced steering mechanism

Fig. 14. Balance of two bogies linked by compelling guided mechanism

electromagnetic resilience is exerted is <sup>4</sup> <sup>2</sup>

bogie module's moment is <sup>12</sup>

*<sup>u</sup> <sup>f</sup> K kk k x x dx*

1 2

1 2

*i*

*m si i <sup>x</sup> <sup>i</sup>*

*m si i <sup>x</sup> <sup>i</sup>*

*i*

11 1 14 <sup>2</sup> (1 ) 1 ( )tan *<sup>x</sup>*

1,2

connecting No.3, 4 bogies can be obtained:

3,4

obtained:

12 11

substituted in(7):

*L*

*m s <sup>x</sup>*

$$\begin{aligned} k\_i(\mathbf{x}\_{i1} - \mathbf{x}\_j) + (Y(\mathbf{x}\_{i1}) - y\_j) &= \mathbf{0} \\ k\_i(\mathbf{x}\_{i2} - \mathbf{x}\_{j+3}) + (Y(\mathbf{x}\_{i2}) - y\_{j+3}) &= \mathbf{0} \end{aligned}$$

Substituting x11、y11=Y(x11) in the above first equation, the following equation can be obtained:

$$k\_1(\mathbf{x}\_{11} - \mathbf{x}\_1) + (Y(\mathbf{x}\_{11}) - y\_1) = 0 \tag{4-10}$$

In the above six equations in(4-5)(4-6)(4-8)(4-9)obtained by the balance between lateral electromagnetic resilience and structural constraint force, the equations (8), (9) introduce a unknown quantity η. Hereby the equation (4-10) is introduced and a reference point q11(x11、y11)to instantaneous position of vehicle is given. The equations (4-1)-(4-6) and (4-8)-(4-10) are the non-linear equation set with twenty-nine unknown quantities, namely twenty-nine unknown quantities Pi(xi、yi)and *η* can be resolved. This is the general formula for kinematic analysis on passive EMS maglev trains with four bogies which can be used to resolve the absolute position (motion trace) of any bogie and the relative position or topological relation of any component of the vehicle at any time. In the same way, kinematics equations of maglev train with other number bogies can be deduced.

### **4.1.3 General kinematic characters of passive guidance EMS maglev trains**

Following kinematic characters of vehicles can be deduced by the above general kinematic formulas:

Character 1: kinematic the static determinacy or indeterminacy of vehicles is determined by the forced steering mechanism, namely the topological relation between a bogie and carriage (formula (4-4), (4-7)) must be given and if not, there will be multiple solutions of motion trace.

Character 2: n, namely the number of intersection points of the modules (straight line) and track (convex curve), 1≤n≤2, two geometric equations will be reduced for each reduced crossing point and in the straight-line segment of track, the bogies are coincident with the track.

Character 3: the motion trace of vehicle is determined together by the topological relations between bogie and carriage and bogie and track but not only by the track.

Character 4: The steering characteristic and yawing characteristic of vehicle with transverse interference depend on the balance relation between the lateral electromagnetic restoring force and the constraint force of forced steering mechanism.

### **4.2 Solution and analysis of kinematic equations of EMS mid-low speed maglev trains**

Given that N=320,Wm=28 mm,A=3360×28 mm2,L=3.4 m,Lc=14.5 m , circular curve radius R=100 m,superelevation is 60 mm,transition curve length *l0*=12 m, the easement trace curve is the clothoid generally, the curvature of easement curve <sup>0</sup> *k s Rl* and the high-order small quantities are ignored, the projection of x-y plane of trace curve is:

Structural and Kinematic Analysis of EMS Maglev Trains 109

The relationships of relative positions exist among the bogies and between bogies and carriages. For the sake of intuition, the computed results of relative positions among bogies are transformed into the included angles. The figure 16 gives the fitting figure of computed results of relative positions among bogies and the Tab. 2 gives the computed results of two

> 1 2 3 4 1-2 2-3 3-4 Front⊿1 Rear⊿7 Front⊿8 Rear⊿<sup>14</sup> θ<sup>12</sup> θ<sup>23</sup> θ<sup>34</sup>

3.4, 0.0055 3.24 1.05 0.84 0.84 0.034º 0.02º 0º 6.8, 0.0437 13.78 4.52 1.02 1.02 0.424º 0.215º 0º 10.2, 0.1474 95.75 31.81 27.24 83.92 1.072º 0.556º 0.039º 13.6, 0.3494 157.8 52.54 48.05 146.03 1.771º 1.091º 0.411º

Based on the derivation and computational analysis of above kinematic kinematics mathematical formulas and test results, the following conclusions on relevant kinematic

1. The absolute position or trace of vehicle is not equal to track curve and their relation (offset Δuij) is also not constant. The change rule is: straight segment (zero) → easement

3. The bogie and carriage, bogie between any two are restricted geometrically and the bogie and track is constrained by lateral electromagnetic restoring force, so the absolute

curve segment (Monotone increasing) →bend segment (a maximum constant) 2. The kinematic static determinacy or indeterminacy of vehicles depends on the forced steering mechanism. If no forced steering mechanism, the kinematic relation of vehicles

Table 2. Angle θij between bogies & Bogie endpoint offset Δi relative to the car body

researches on passive guidance EMS maglev trains can be obtained.

position relations when q11 is valued as four typical coordinate points respectively

2. Relative positions of all components of vehicle

Fig. 16. Alteration curve of angle between No.1,2 bogies

Bogie P11(x,y)

q11(x,y)

**4.3 Conclusions** 

is indefinite.

$$\mathbf{y} = \mathbf{Y}(\mathbf{x}) = \begin{cases} 0 & \mathbf{x} \le \mathbf{0} \\\\ \frac{\mathbf{x}^3}{6l\_0 R} & 0 < \mathbf{x} < \mathbf{x}\_c \\\\ y\_c - \sqrt{R^2 - (\mathbf{x} - \mathbf{x}\_c)^2} & \mathbf{x}\_c \le \mathbf{x} \end{cases}$$

in which q0(x0,y0)、qe(xe,ye)、qc(xc,yc)represent the bonding points of the straight segment and curved segment of trace curve Q(x) and transition curve and the center

$$\text{of } \mathbf{b} \text{ bend circular curve respectively. } \mathbf{x}\_{\varepsilon} = \mathbf{x}\_{\varepsilon} - \frac{k\_{\varepsilon}R}{\sqrt{1 + k\_{\varepsilon}^2}}, \quad \mathbf{x}\_{\varepsilon} = \mathbf{y}\_{\varepsilon} + \frac{k\_{\varepsilon}R}{\sqrt{1 + k\_{\varepsilon}^2}}, \quad k\_{\varepsilon} = \mathbf{Y}'(\mathbf{x})|\_{\mathbf{x} = \mathbf{x}\_{\varepsilon} + \varepsilon} \text{ and } \mathbf{y} = \mathbf{y}\_{\varepsilon} + \frac{k\_{\varepsilon}R}{\sqrt{1 + k\_{\varepsilon}^2}}$$

qe(11.9956,0.2397),qc(11.6364,100.06). In the interval defined by track curve, a series of q11(x11, y11) are valued according to the step length of 0.1m to resolve the kinematic equations obtained in the preceding paragraph, the motion trace of vehicle and the relative positions of all vehicle components can be derived. Some primary results obtained through numerical calculation by MATHEMATICA are given below.

1. Motion trace

To express the kinematic characters, the motion trace of vehicle is shown by the offset of bogies to the track but not the coordinate figure Pi. The fig.15 gives the fitting figure of computed results and the table 1 shows the computed results when q11 is valued as four typical coordinate points.

Fig. 15. Curves of bogies endpoint offset relative to the track


Table 1. Δuij , Amount of bogie endpoint offset relative to the track

0 0

0

*x*

, <sup>2</sup> <sup>1</sup> *<sup>e</sup> c e*

*x y*

*e*

*e*

, '

( )| *<sup>e</sup> e xx k Yx* ,

*k*

*k R*

*x x*

2 2

*c ce*

( )

in which q0(x0,y0)、qe(xe,ye)、qc(xc,yc)represent the bonding points of the straight segment and curved segment of trace curve Q(x) and transition curve and the center

*<sup>e</sup> c e*

qe(11.9956,0.2397),qc(11.6364,100.06). In the interval defined by track curve, a series of q11(x11, y11) are valued according to the step length of 0.1m to resolve the kinematic equations obtained in the preceding paragraph, the motion trace of vehicle and the relative positions of all vehicle components can be derived. Some primary results obtained through

To express the kinematic characters, the motion trace of vehicle is shown by the offset of bogies to the track but not the coordinate figure Pi. The fig.15 gives the fitting figure of computed results and the table 1 shows the computed results when q11 is valued as four

> 1 2 3 4 Front⊿u11 Rear⊿u12 Front⊿u21 Rear⊿u22 Front⊿u31 Rear⊿u32 Front⊿u41 Rear⊿u42

0.0055 1.94 1.89 1.89 1.91 0 0 0 0

0.0437 3.52 3.49 3.49 3.5 0 0 0 0

0.1474 6.52 6.46 6.46 6.48 1.91 1.89 1.89 1.92

0.3494 8.05 7.94 7.94 8.01 3.52 3.51 3.51 3.53

*x x*

*e*

*k*

*k R*

*y R xx x x*

y=Y(x) =

3

*x*

0

*l R*

6

 

of bend circular curve respectively. 2 <sup>1</sup>

numerical calculation by MATHEMATICA are given below.

Fig. 15. Curves of bogies endpoint offset relative to the track

Table 1. Δuij , Amount of bogie endpoint offset relative to the track

1. Motion trace

Bogie q11(x,y)

3.4,

6.8,

10.2,

13.6,

typical coordinate points.

### 2. Relative positions of all components of vehicle

The relationships of relative positions exist among the bogies and between bogies and carriages. For the sake of intuition, the computed results of relative positions among bogies are transformed into the included angles. The figure 16 gives the fitting figure of computed results of relative positions among bogies and the Tab. 2 gives the computed results of two position relations when q11 is valued as four typical coordinate points respectively

Fig. 16. Alteration curve of angle between No.1,2 bogies


Table 2. Angle θij between bogies & Bogie endpoint offset Δi relative to the car body

### **4.3 Conclusions**

Based on the derivation and computational analysis of above kinematic kinematics mathematical formulas and test results, the following conclusions on relevant kinematic researches on passive guidance EMS maglev trains can be obtained.


Structural and Kinematic Analysis of EMS Maglev Trains 111

Obviously the distance between two module endpoints of bogie in a curve is enlarged

The distance between two endpoints of back bogie:a2=2.0205m, a1, a2 represents the distance between endpoints of front and back bogies in a curve respectively, and the change

Therefore, the change of distance between two module endpoints of front bogie is bigger and transverse thrust rod must be able to extend 13mm at most when the vehicle is in motion. To solve this problem, the transverse thrust rod may be arranged in a V type (Fig.18) and the calculation of physical dimension of the forced steering mechanisms and

As shown in Fig.17, L、t、l、d、f represent length of module and transverse thrust rod and T-type arm, the horizontal distances from rotation center of module to rotation centre of Ttype rod, the offset distance between the hinge point of transverse thrust rod and the center of air spring respectively. θ1, θ2 represent the oscillation angle of two modules respectively.

Fig. 17. Distance between two module endpoints of bogie in a curve

relatively to in straight. Its size can be examined by an instance.

The distance between two module endpoints of front bogie is:

<sup>1</sup>*a* 48.99 51.01 2 48.99 51.01 cos(0.2594) =2.03264m

their mathematical models based on kinematics principle is given below.

of distance between two module endpoints of bogie is:

Given that R=50m,h=2.02m, L=2.24m

2 2

Da1=a1-h=12.64mm Da2=a2-h=0.5mm

φ1=1.25811 φ2=1.31

position Δuij of bogies should be determined by the electromagnetic balance of vehicle and geometrical constraint relations of all its components. Δuij of different bogies is different at the same time and position.


### **5. Kinematic analysis on the secondary suspension system of maglev trains**

The composition and kinematic characteristics of secondary suspension system for the joint of car body and bogies has been illustrated in the paragraph 1, 2. The distinctive midstructure of active and passive guidance maglev trains lie in pendular suspension mechanism and forced steering mechanism respectively. In this paragraph, their kinematic characteristics analysis and the calculation method is given and other kinematic analyses can see the references (ZHAO Z.S. et al., 2000).

#### **5.1 Kinematic analysis on the forced steering mechanism of passive guidance ems maglev trains**

The functions of forced steering mechanism are to connect two bogies to form the running gear (Fig.10, 11, 14), keep a proper geometric position between the running gear and car body (Fig.10) and transmit the transversal force between the running gear and car body. When realizing these functions, the uncoupling of bogies can not be affected by the mechanism. According to Fig.14, the transverse thrust rod of the forced steering mechanism may affect the uncoupling of bogies, which can be obtained by analyzing some motions of bogie as it goes through the curve.

The relative height and distance between the ends of two bogie modules in motion may change. The transverse thrust rod are equipped at the end of bogies, so it is possible to add spherical hinges at the end of links to adapt to the change of relative height between the ends of two modules and it is hard to change the length of rigid rods. Take the vehicle with five bogies Shown as Fig.17 for example. Setting:δ1=α2-α1,δ2=φ2-φ1, h, β , L represent width of track and angle of a、R2 , length of module respectively.

$$\phi\_i = \sin^{-1}\left(\frac{L}{2R\_i}\right), \quad \alpha\_i = \mathbf{5}\phi\_i \quad .$$

outside track radius is R1 =R+h/2, inside track radius is R2 =R-h/2, distance between two module endpoints of bogie in the curve: 2 2 1 2 12 2 cos *i i a R R RR* , there i=1,2.

Fig. 17. Distance between two module endpoints of bogie in a curve

Obviously the distance between two module endpoints of bogie in a curve is enlarged relatively to in straight. Its size can be examined by an instance.

Given that R=50m,h=2.02m, L=2.24m

φ1=1.25811 φ2=1.31

110 Infrastructure Design, Signalling and Security in Railway

4. The parameter *η*=3 expressing the characteristic of relative position between bogies and

5. The change law of relative position(θij)among bogies is: straight segment (zero) → easement curve segment (Monotone increasing) →bend segment (a maximum constant). 6. The absolute position of vehicle and the relative position among all its components including the bonding points of all line segments change smoothly in the motion. 7. The results obtained by kinematics formulas are consistent with the past research

8. The article gives that the mathematical models can be used in the kinematic analysis of

**5. Kinematic analysis on the secondary suspension system of maglev trains**  The composition and kinematic characteristics of secondary suspension system for the joint of car body and bogies has been illustrated in the paragraph 1, 2. The distinctive midstructure of active and passive guidance maglev trains lie in pendular suspension mechanism and forced steering mechanism respectively. In this paragraph, their kinematic characteristics analysis and the calculation method is given and other kinematic analyses

**5.1 Kinematic analysis on the forced steering mechanism of passive guidance ems** 

The functions of forced steering mechanism are to connect two bogies to form the running gear (Fig.10, 11, 14), keep a proper geometric position between the running gear and car body (Fig.10) and transmit the transversal force between the running gear and car body. When realizing these functions, the uncoupling of bogies can not be affected by the mechanism. According to Fig.14, the transverse thrust rod of the forced steering mechanism may affect the uncoupling of bogies, which can be obtained by analyzing some motions of

The relative height and distance between the ends of two bogie modules in motion may change. The transverse thrust rod are equipped at the end of bogies, so it is possible to add spherical hinges at the end of links to adapt to the change of relative height between the ends of two modules and it is hard to change the length of rigid rods. Take the vehicle with five bogies Shown as Fig.17 for example. Setting:δ1=α2-α1,δ2=φ2-φ1, h, β , L represent

> *i L R*

outside track radius is R1 =R+h/2, inside track radius is R2 =R-h/2, distance between two

, 5 *i i* ,

1 2 12 2 cos *i i a R R RR*

, there i=1,2.

width of track and angle of a、R2 , length of module respectively.

module endpoints of bogie in the curve: 2 2

<sup>1</sup> sin 2 *<sup>i</sup>*

different at the same time and position.

vehicle by the transverse interference.

can see the references (ZHAO Z.S. et al., 2000).

bogie as it goes through the curve.

**maglev trains** 

carriages is applicable to all line segments.

results in circular curve and straight-line segment

position Δuij of bogies should be determined by the electromagnetic balance of vehicle and geometrical constraint relations of all its components. Δuij of different bogies is

The distance between two module endpoints of front bogie is:

2 2 <sup>1</sup>*a* 48.99 51.01 2 48.99 51.01 cos(0.2594) =2.03264m

The distance between two endpoints of back bogie:a2=2.0205m, a1, a2 represents the distance between endpoints of front and back bogies in a curve respectively, and the change of distance between two module endpoints of bogie is:

Da1=a1-h=12.64mm Da2=a2-h=0.5mm

Therefore, the change of distance between two module endpoints of front bogie is bigger and transverse thrust rod must be able to extend 13mm at most when the vehicle is in motion. To solve this problem, the transverse thrust rod may be arranged in a V type (Fig.18) and the calculation of physical dimension of the forced steering mechanisms and their mathematical models based on kinematics principle is given below.

As shown in Fig.17, L、t、l、d、f represent length of module and transverse thrust rod and T-type arm, the horizontal distances from rotation center of module to rotation centre of Ttype rod, the offset distance between the hinge point of transverse thrust rod and the center of air spring respectively. θ1, θ2 represent the oscillation angle of two modules respectively.

Structural and Kinematic Analysis of EMS Maglev Trains 113

2 2 2 2 4 22

1 1 1 1 ( [ ( )] ) ( ) *t h <sup>f</sup> L L dL l*

2 2 22 ( () ) *t h f Ld l* or 2 22 *t ldL h* ( )( ) *f*

There are two unknown quantities t and 1 in the above equation. One of them is set, the

Given that L=2.24m, h=2m, R=50m, f=90mm, d=1.9m and l=550mm, t≈1.39m can be obtained.

**5.2.1. Mathematical description of turing characteristic of tilting suspension system** 

Fig. 19. Force and Displacement of Tilting Suspension System & Relative Displacement

The figure 18 show the motion state of high-speed maglev train with tilting suspension system goes around the curve, in which Δij, θij represent the lateral displacement and oscillation angle of rocker respectively and w、Tij、fij represent the car body gravity, tension and lateral force of carriage acting on the rockers of tilting suspension system respectively. The train is composed of carriage, bogies, suspension system. four bogies and three overlapping modules are connected alternately to form the running gear (see the Fig. 18 left) and four set of pendular suspension systems are configured in the interval between four bogies and carriage respectively (see the Fig. 18 right). As the vehicle enters the curve, the bogies move along the track curve under the effect of active electromagnetic guiding force and produce relative displacement Δij to the carriage which is driven by the oscillation of rockers of tilting suspension system. The sixteen pendular rod of tilting suspension system will produce the lateral force acting on the carriage and bogies. Δij is determined by the balance of the forces fij acting on the carriage, the active electromagnetic guiding force can be obtained by the force fij acting on single bogie. Therefore the solution of the steering characteristic of maglev train with tilting suspension system lies in resolving the displacement of rockers and the force acting on them. From the viewpoint of design, it might as well make a hypothesis that the sixteen

Without considering of high-order small quantities, the equation (3) can be simplified as:

other can be obtained. A calculation sample is given below.

**maglev train (Zhao Z.S., 2009)** 

rockers receive the weight of carriage equally.

between Carriage and Bogie in the Curve

**5.2 Kinematic analysis on tilting suspension system of maglev train** 

2 1 1 2

*R R R R* (5-3)

Fig. 18. Kinematic sketch of forced steering mechanism

When the running gear is in motion, two transverse thrust rod and T-type rod rotate around the point P1(x1,y1), P2(x2,y2) and O1 respectively and the traces of their endpoints are three circles in the same plane with the radius of t, 1. Three circles intersect in the point P(x, y). Thereout the following equation set is given.

$$\begin{aligned} \left(\mathbf{x} - \mathbf{x}\_1\right)^2 + \left(\mathbf{y} - \mathbf{y}\_1\right)^2 &= t^2\\ \left(\mathbf{x} - \mathbf{x}\_2\right)^2 + \left(\mathbf{y} - \mathbf{y}\_2\right)^2 &= t^2\\ \left(\mathbf{x} - \mathbf{d}\right)^2 + \mathbf{y}^2 &= t^2 \end{aligned} \tag{5-1}$$

among which,

$$\begin{aligned} \alpha\_i &= L \cos 4\alpha\_i + (-1)^i f \sin 4\alpha\_i \approx L \sqrt{1 - \frac{4L^2}{R\_i^2}} \\ \alpha\_i &= (-1)^{i-1} (h - f \cos 4\alpha\_i) - L \sin 4\alpha\_i \approx (-1)^{i-1} (h - f) - \frac{2L^2}{R\_i} \end{aligned} \tag{5-2}$$

In the above equation set, i=1, 2,and by the third equation in (1), 2 2 *y l xd* ( ) is obtained.

In consideration of 1 2 *x x* , by the first and second equations in (1), <sup>2</sup> 1 2 1 1 *y L* ( ) *R R* is obtained and is substituted into second equations in(5-1):

2 22 2 2 1 1 1 *x th*[ ( )] *<sup>f</sup> L x R R* , thus the x, y is obtained and substituted respectively into third equation in (5-1):

When the running gear is in motion, two transverse thrust rod and T-type rod rotate around the point P1(x1,y1), P2(x2,y2) and O1 respectively and the traces of their endpoints are three circles in the same plane with the radius of t, 1. Three circles intersect in the

> 2 2 2 1 1

 

2 2 2 2 2 2 2 2

2 2

*i*

 

*xd y l*

<sup>4</sup> cos 4 ( 1) sin 4 1

In consideration of 1 2 *x x* , by the first and second equations in (1), <sup>2</sup>

*i*

*<sup>L</sup> xL f L <sup>R</sup>*

*i i i*

*ii i*

obtained and is substituted into second equations in(5-1):

2 22

1 1 *x th*[ ( )] *<sup>f</sup> L x*

into third equation in (5-1):

2 1

*R R*

1 1

 

*<sup>L</sup> y hf L h f <sup>R</sup>*

*i i*

<sup>2</sup> ( 1) ( cos 4 ) sin 4 ( 1) ( )

In the above equation set, i=1, 2,and by the third equation in (1), 2 2 *y l xd* ( ) is

, thus the x, y is obtained and substituted respectively

 

*x x y y t x x y y t*

Fig. 18. Kinematic sketch of forced steering mechanism

point P(x, y). Thereout the following equation set is given.

among which,

obtained.

2

(5-1)

2

 

(5-2)

1 2

1 1 *y L* ( ) *R R* is

*i*

$$\sqrt{t^2 - \left[h - f + L^2(\frac{1}{R\_2} - \frac{1}{R\_1})\right]^2} + L - d)^2 + L^4(\frac{1}{R\_1} + \frac{1}{R\_2})^2 = l^2\tag{5-3}$$

Without considering of high-order small quantities, the equation (3) can be simplified as:

$$\text{tr}\left(\sqrt{t^2 - \left(h - f\right)^2} + L - d\right)^2 = l^2 \quad \text{or} \quad t^2 = \left(l + d - L\right)^2 + \left(h - f\right)^2$$

There are two unknown quantities t and 1 in the above equation. One of them is set, the other can be obtained. A calculation sample is given below.

Given that L=2.24m, h=2m, R=50m, f=90mm, d=1.9m and l=550mm, t≈1.39m can be obtained.

#### **5.2 Kinematic analysis on tilting suspension system of maglev train**

#### **5.2.1. Mathematical description of turing characteristic of tilting suspension system maglev train (Zhao Z.S., 2009)**

The figure 18 show the motion state of high-speed maglev train with tilting suspension system goes around the curve, in which Δij, θij represent the lateral displacement and oscillation angle of rocker respectively and w、Tij、fij represent the car body gravity, tension and lateral force of carriage acting on the rockers of tilting suspension system respectively. The train is composed of carriage, bogies, suspension system. four bogies and three overlapping modules are connected alternately to form the running gear (see the Fig. 18 left) and four set of pendular suspension systems are configured in the interval between four bogies and carriage respectively (see the Fig. 18 right). As the vehicle enters the curve, the bogies move along the track curve under the effect of active electromagnetic guiding force and produce relative displacement Δij to the carriage which is driven by the oscillation of rockers of tilting suspension system. The sixteen pendular rod of tilting suspension system will produce the lateral force acting on the carriage and bogies. Δij is determined by the balance of the forces fij acting on the carriage, the active electromagnetic guiding force can be obtained by the force fij acting on single bogie. Therefore the solution of the steering characteristic of maglev train with tilting suspension system lies in resolving the displacement of rockers and the force acting on them. From the viewpoint of design, it might as well make a hypothesis that the sixteen rockers receive the weight of carriage equally.

Fig. 19. Force and Displacement of Tilting Suspension System & Relative Displacement between Carriage and Bogie in the Curve

Structural and Kinematic Analysis of EMS Maglev Trains 115

3 0.5 ( 3) ( 0.5 )

*l ml l l m*

21 21 21 21 2 22 22 2 2 2 21 21 21 21

(5 ) (2 ) ( 0.5 ) *m m m lm lm l l m* 

2 2 2 2 22 2 2 5 2 0.5 *n n nn* (5 ) (2 ) ( 0.5)

> (5 ) (2 )

 

*m*

**5.2.2 Calculation of steering characteristic parameters of maglev train with tilting** 

When the vehicle is passing the curve of 350m, R=350m;R1=351.1m;R2=348.9m.

Table 3. Displacement of suspensor rod tip & Lateral force put on car body

*m m*

*m*

Displacement of suspensor rod tip Lateral force put on car body

(KN) Transverse (m) Vertical (m) *Δ<sup>11</sup> Δ<sup>12</sup> Δ<sup>21</sup> Δ<sup>22</sup> Z*<sup>11</sup> *Z*<sup>12</sup> *Z*<sup>21</sup> *Z*<sup>22</sup> f11 f12 f21 f22

track 0.154 0.0106 0.0846 0.1085 0.056 0.0002 0.015 0.026 15.69 0.83 -7.09 -9.54 Inside track 0.156 0.0108 0.0857 0.1098 0.057 0.0002 0.0156 0.027 15.86 0.84 -7.14 -9.37

(0.5 )

The equations (5-4)(5-5)(5-9)(5-10)are the calculation formulas of steering

Structural parameters of vehicle is given, L=4.096m; l=0.24m; R=350m、400m; gauge is 2.2m; weight of carriage W=30T; w=W÷16=1.875T. Valuing the convergence accuracy as 0.005, μ can be obtained by solution of the equation (5-9) with numerical method, then the lateral force fij and lateral displacement Δij of rocker ends derived from equations (5-4) and (5-10), it is not hard to obtain the tension Tij of suspension rocket and the vertical

 

5 2 0.5

*m m*

(5-8)

(5-9)

(5-10)

From the above three equations, given that m=L2/R and substituted in (3), (4):

12 21

2

*m*

Given that Δ21=μm and substituted in the above equations:

characteristics of maglev train with tilting suspension system.

displacement of its ends. The calculation results are as follows:

among which n=l/m。

**suspension system** 

Item

Position

Outside

among which L represent the length of bogie. From the equations (5),

12 12 21 21 2 2 22 22 2 2 12 12 21 21

The lateral balance equation of carriage in the curve is:

$$\sum\_{i=1}^{4} \sum\_{j=1}^{2} \vec{f}\_{ij} = 0 \quad \text{\textquotedblleft because of the symmetry,} \quad 2 \sum\_{i=1}^{2} \sum\_{j=1}^{2} \vec{f}\_{ij} = 0 \quad \text{\textquotedblleft}$$

in the above equations, the bilateral balances are considered similarly and i、j represent the number of bogie and its ends respectively. The above equation can be written as:

$$w(\tan \theta\_{11} + \tan \theta\_{12} - \tan \theta\_{21} - \tan \theta\_{22}) = 0\tag{5-4}$$

namely:

$$\frac{\Delta\_{11}}{\sqrt{l^2 - \Delta\_{11}^2}} + \frac{\Delta\_{12}}{\sqrt{l^2 - \Delta\_{12}^2}} = \frac{\Delta\_{21}}{\sqrt{l^2 - \Delta\_{21}^2}} + \frac{\Delta\_{22}}{\sqrt{l^2 - \Delta\_{22}^2}}\tag{5-5}$$

among which *l* represent the length of rocker. The following geometrical relationships can be shown in Fig. 18:

$$
\Delta\_{11} = \Delta\_{12} + L\sin 6a$$

$$
\Delta\_{22} = \Delta\_{21} + L\sin 2a$$

Substituted into (2):

$$\frac{\Delta\_{12} + L\sin 6a}{\sqrt{l^2 - \left(\Delta\_{12} + L\sin 6a\right)^2}} + \frac{\Delta\_{12}}{\sqrt{l^2 - \Delta\_{12}^2}} = \frac{\Delta\_{21}}{\sqrt{l^2 - \Delta\_{21}^2}} + \frac{\Delta\_{21} + L\sin 2a}{\sqrt{l^2 - \left(\Delta\_{21} + L\sin 2a\right)^2}}\tag{5-6}$$

Likewise from the geometrical relationships, the following equation can be obtained:

$$
\Delta\_{12} + \Delta\_{21} = L \sin 4a \tag{5-7}
$$

From trigonometric functional relations and in considering of R>>L:

$$
\sin 2a = 2 \sin a \cos a = \frac{L}{2R} \sqrt{1 - \left(\frac{L}{2R}\right)^2} \approx \frac{L}{2R}
$$

$$
\sin 4a = 4 \sin a \cos^3 a = \frac{2L}{R} \left(1 - \left(\frac{L}{2R}\right)^2\right)^{\frac{3}{2}} \approx \frac{2L}{R}
$$

$$
\sin 6a = 2(3 \sin a - 4 \sin^3 a)(4 \cos^3 a - 3 \cos a) = \frac{L}{R} \left(3 - \left(\frac{L}{R}\right)^2\right) \left|1 - \left(\frac{L}{R}\right)^2\right| \sqrt{1 - \left(\frac{L}{2R}\right)^2} \approx \frac{3L}{R}
$$

From the above three equations, given that m=L2/R and substituted in (3), (4):

$$\begin{aligned} \frac{\Lambda\_{12} + 3m}{\sqrt{l^2 - \left(\Lambda\_{12} + 3m\right)^2}} + \frac{\Lambda\_{12}}{\sqrt{l^2 - \Lambda\_{12}^2}} &= \frac{\Lambda\_{21}}{\sqrt{l^2 - \Lambda\_{21}^2}} + \frac{\Lambda\_{21} + 0.5m}{\sqrt{l^2 - \left(\Lambda\_{21} + 0.5m\right)^2}}\\ \Lambda\_{12} + \Lambda\_{21} &= 2m \end{aligned} \tag{5-8}$$

among which L represent the length of bogie. From the equations (5),

$$\frac{5m - \Lambda\_{21}}{\sqrt{l^2 - \left(5m - \Lambda\_{21}\right)^2}} + \frac{2m - \Lambda\_{21}}{\sqrt{l^2 - \left(2m - \Lambda\_{21}\right)^2}} = \frac{\Lambda\_{21}}{\sqrt{l^2 - \Lambda\_{21}^2}} + \frac{\Lambda\_{21} + 0.5m}{\sqrt{l^2 - \left(\Lambda\_{21} + 0.5m\right)^2}}$$

Given that Δ21=μm and substituted in the above equations:

$$\frac{5-\mu}{\sqrt{n^2-\left(5-\mu\right)^2}} + \frac{2-\mu}{\sqrt{n^2-\left(2-\mu\right)^2}} = \frac{\mu}{\sqrt{n^2-\mu^2}} + \frac{\mu+0.5}{\sqrt{n^2-\left(\mu+0.5\right)^2}}\tag{5-9}$$

among which n=l/m。

114 Infrastructure Design, Signalling and Security in Railway

2 2

1 1 2 0 *ij i j*

in the above equations, the bilateral balances are considered similarly and i、j represent the

11 12 21 22 *w*(tan tan tan tan ) 0

11 12 21 22 22 22 22 22 <sup>11</sup> <sup>12</sup> <sup>21</sup> <sup>22</sup> *llll* 

among which *l* represent the length of rocker. The following geometrical relationships can

11 12 *L*sin6

22 21 *L*sin 2

2 2 2 2 2 2 2 2 12 12 21 21

sin 6 sin 2 ( sin 6 ) ( sin 2 ) *L L*

12 12 21 21

 

From trigonometric functional relations and in considering of R>>L:

 

sin 2 2sin cos 1

 

 

*lL l l lL*

Likewise from the geometrical relationships, the following equation can be obtained:

12 21 *L*sin 4

<sup>3</sup> 2 2 sin 4 4sin cos 1

3 3 <sup>3</sup> sin 6 2(3sin 4sin )(4 cos 3cos ) 3 1 1 <sup>2</sup>

2 22 *L LL R RR*

2 *LL L RRR*

2

3 2 2

number of bogie and its ends respectively. The above equation can be written as:

*f* 

,

(5-4)

(5-5)

 

(5-7)

22 2

*LL L L L R R R RR*

(5-6)

The lateral balance equation of carriage in the curve is:

,because of the symmetry,

4 2

1 1

namely:

*i j*

0 *ij*

be shown in Fig. 18:

Substituted into (2):

 

*f* 

$$\begin{aligned} \Delta\_{11} &= (5 - \mu)m\\ \Delta\_{12} &= (2 - \mu)m\\ \Delta\_{21} &= \mu m\\ \Delta\_{22} &= (0.5 + \mu)m \end{aligned} \tag{5-10}$$

The equations (5-4)(5-5)(5-9)(5-10)are the calculation formulas of steering characteristics of maglev train with tilting suspension system.

#### **5.2.2 Calculation of steering characteristic parameters of maglev train with tilting suspension system**

Structural parameters of vehicle is given, L=4.096m; l=0.24m; R=350m、400m; gauge is 2.2m; weight of carriage W=30T; w=W÷16=1.875T. Valuing the convergence accuracy as 0.005, μ can be obtained by solution of the equation (5-9) with numerical method, then the lateral force fij and lateral displacement Δij of rocker ends derived from equations (5-4) and (5-10), it is not hard to obtain the tension Tij of suspension rocket and the vertical displacement of its ends. The calculation results are as follows:

When the vehicle is passing the curve of 350m, R=350m;R1=351.1m;R2=348.9m.


Table 3. Displacement of suspensor rod tip & Lateral force put on car body

Structural and Kinematic Analysis of EMS Maglev Trains 117

beams 3, 4 move d11、d12 upward in the Z direction. Owing to the immovability of the left module 9, as the motion of the module 2, the right and left pairs of anti-rolling beams 3-5,4-6 should stagger d11、d12 in the Z direction, but the anti-rolling beams are connected by

1. R. levitation magnet, 2.R. module, 3.R. Front Anti-rolling beam, 4.R.rear Anti-rolling beam, 5.L. Front Anti-rolling beam, 6.L.Rear Anti-rolling, 7.Rear axis of rotation, 8.L. levitation magnet, 9.L. module,

For the sake of further analysis, it may emphasize the analysis on the relative motion of front two anti-rolling beams 3-5. It is obvious that the anti-rolling beam 5 can not move in the Z direction but rotate around the shaft 10. When the module 2 is moving upward, the anti-rolling beam 3 exerts a press force on the Pendular rod 1-1'. Because there are the ball hinges at the ends of the rod, the bearing anti-rolling beam 3 is instability and will deflect to drive the anti-rolling 5 to move around the shaft 10. At this moment, the anti-rolling beam 3 can move upward, namely one end of the module 2 move upward and the other anti-rolling beam moves similarly. It can be seen that the analysis on the motion of modules focuses on the calculation of kinematic parameters of connecting two module ant-rolling beams. The

For the convenience of analysis, the mechanism sketch Fig.21 of ant-rolling beam is given separately. The sketch shows the position relations of motion of all points elevated by one end of the right module. Proposed that the length of ON is L1、the length of OP is t12、the length of OP' is t11,the length of RM is H1、the length of RM' is h11, lij represents the length of four rocker respectively and the first and second subscripts represent the number

1 *ij*

*i*

*L*

*<sup>L</sup>* i=1, j=1, 2 (6-1)

*ij ij ij i t*

*ij*

*Sin*

*d*

Fig. 21. Module uncoupling movement of a type bogie mechanism

suspenders 1—2 which tend to stop this motion.

10.Front axis of rotation, 11. Pendular rod

relevant computational formulas are given below.

of modules and anti-rolling beams respectively.

From equation (5-9) it can obtain μ=1.777 and the above parameter table 3. The electromagnetic guiding forces acting on the bogie 1 and 2 are 33.22K and -33.15KN respectively, which is the reason why this kind of vehicles must adopt the active guidance structure.

### **6. Research on mechanisms and kinematics of maglev bogies**

In this paragraph, the mechanism analysis and kinematic calculation methods of maglev bogies are introduced. As described in the paragraph 1 and 2, the bogies of EMS maglev trains have two structures. T-type bogies (Fig.6, 8) are decoupled by the torsion of longerons and A-type bogies (Fig.6, 8) are decoupled by anti-rolling beams. The vertical uncoupling of both kinds of bogies is based on the principle of relative torsion of modules. Their mechanism sketches are shown respectively in Fig.19 and Fig.20.

1.Car body, 2.Secongdary system spring, 3.Rocker arm, 4.Z support for car body, 5.Linkage levitation magnet, 6.Longeron, 7.Guidance magnet, 8.Suppot arm, 9.Levitation frame unit, 10.Levitation magnet.

Fig. 20. Mechanism sketch of T-type bogie

The Levitation frame unit of T type bogies is distributed both front and back and may be connected with a torsional elastic longeron, and the Levitation and guidance electromagnet is installed on the bracket arms of front and back modules. It is obvious that other relative motions of the front and back Levitation frame unit of T-type bogies are limited. The two modules of A-type bogie have three translational degrees of freedom and two rotational degrees of freedom. It can be seen from the sketch that the analysis on their X, Y-directional translational degrees of freedom and Z-directional rotational degree of freedom is much simple, and X-directional rotational degree of freedom is limited by the anti-rolling beams, so in this section, the analysis and calculation focus on Z-directional translation and Ydirectional rotation of modules of A-type bogies.

Take the kinematic analysis on the right module in Fig. 19 for example. When the endpoint P of right electromagnet 1 elevates D11, the corresponding points M, M' to electromagnets in the same plane with anti-rolling beams 3, 4 elevate d11、d12, the angle between the magnet 1 and the horizontal plane is α1 and the module 2 rotates in the Y direction, namely twist relatively to the left module 9. As the motion of the module 2, the front and back anti-rolling

From equation (5-9) it can obtain μ=1.777 and the above parameter table 3. The electromagnetic guiding forces acting on the bogie 1 and 2 are 33.22K and -33.15KN respectively, which is the reason why this kind of vehicles must adopt the active guidance

In this paragraph, the mechanism analysis and kinematic calculation methods of maglev bogies are introduced. As described in the paragraph 1 and 2, the bogies of EMS maglev trains have two structures. T-type bogies (Fig.6, 8) are decoupled by the torsion of longerons and A-type bogies (Fig.6, 8) are decoupled by anti-rolling beams. The vertical uncoupling of both kinds of bogies is based on the principle of relative torsion of modules. Their

1.Car body, 2.Secongdary system spring, 3.Rocker arm, 4.Z support for car body, 5.Linkage levitation magnet, 6.Longeron, 7.Guidance magnet, 8.Suppot arm, 9.Levitation frame unit, 10.Levitation magnet.

The Levitation frame unit of T type bogies is distributed both front and back and may be connected with a torsional elastic longeron, and the Levitation and guidance electromagnet is installed on the bracket arms of front and back modules. It is obvious that other relative motions of the front and back Levitation frame unit of T-type bogies are limited. The two modules of A-type bogie have three translational degrees of freedom and two rotational degrees of freedom. It can be seen from the sketch that the analysis on their X, Y-directional translational degrees of freedom and Z-directional rotational degree of freedom is much simple, and X-directional rotational degree of freedom is limited by the anti-rolling beams, so in this section, the analysis and calculation focus on Z-directional translation and Y-

Take the kinematic analysis on the right module in Fig. 19 for example. When the endpoint P of right electromagnet 1 elevates D11, the corresponding points M, M' to electromagnets in the same plane with anti-rolling beams 3, 4 elevate d11、d12, the angle between the magnet 1 and the horizontal plane is α1 and the module 2 rotates in the Y direction, namely twist relatively to the left module 9. As the motion of the module 2, the front and back anti-rolling

**6. Research on mechanisms and kinematics of maglev bogies** 

mechanism sketches are shown respectively in Fig.19 and Fig.20.

Fig. 20. Mechanism sketch of T-type bogie

directional rotation of modules of A-type bogies.

structure.

beams 3, 4 move d11、d12 upward in the Z direction. Owing to the immovability of the left module 9, as the motion of the module 2, the right and left pairs of anti-rolling beams 3-5,4-6 should stagger d11、d12 in the Z direction, but the anti-rolling beams are connected by suspenders 1—2 which tend to stop this motion.

1. R. levitation magnet, 2.R. module, 3.R. Front Anti-rolling beam, 4.R.rear Anti-rolling beam, 5.L. Front Anti-rolling beam, 6.L.Rear Anti-rolling, 7.Rear axis of rotation, 8.L. levitation magnet, 9.L. module, 10.Front axis of rotation, 11. Pendular rod

Fig. 21. Module uncoupling movement of a type bogie mechanism

For the sake of further analysis, it may emphasize the analysis on the relative motion of front two anti-rolling beams 3-5. It is obvious that the anti-rolling beam 5 can not move in the Z direction but rotate around the shaft 10. When the module 2 is moving upward, the anti-rolling beam 3 exerts a press force on the Pendular rod 1-1'. Because there are the ball hinges at the ends of the rod, the bearing anti-rolling beam 3 is instability and will deflect to drive the anti-rolling 5 to move around the shaft 10. At this moment, the anti-rolling beam 3 can move upward, namely one end of the module 2 move upward and the other anti-rolling beam moves similarly. It can be seen that the analysis on the motion of modules focuses on the calculation of kinematic parameters of connecting two module ant-rolling beams. The relevant computational formulas are given below.

For the convenience of analysis, the mechanism sketch Fig.21 of ant-rolling beam is given separately. The sketch shows the position relations of motion of all points elevated by one end of the right module. Proposed that the length of ON is L1、the length of OP is t12、the length of OP' is t11,the length of RM is H1、the length of RM' is h11, lij represents the length of four rocker respectively and the first and second subscripts represent the number of modules and anti-rolling beams respectively.

$$\mathbf{d}\_{ij} = \frac{\mathbf{t}\_{ij}}{L\_i} \Delta\_{ij} \qquad \mathbf{i} = \mathbf{1}, \; \mathbf{j} = \mathbf{1}, \; \mathbf{2} \tag{6-1}$$

$$\mathbf{a}\_{ij} = \mathrm{Sin}^{-1} \left( \frac{\Delta\_{ij}}{L\_i} \right)$$

Structural and Kinematic Analysis of EMS Maglev Trains 119

<sup>1</sup> 2

*t ij L l Sin L t*

<sup>1</sup> <sup>2</sup>

*Sin*

*ij*

*ij*

module are similar. About these it is unnecessary to go into details.

θ11=15.1°, θ12=6.1°, β11=2.48°, β12=1.01°, Φ11=3.24°, Φ12=1.32°.

*<sup>l</sup>* width between two anti-rolling beams:

dimensions:ON=L=2700,OP'=t11=2320,

conclude that: '

11 11 11 11 *<sup>l</sup> w S*

circumstances:

be spatial.

is the diameter of suspender. If '

instance,it is given that W11=59mm.

planes separately and they are parallelogram.

1 *ij i ij*

1 *ij ij ij ij i*

*i i ij ij ij ht lL*

*HLl t*

The above equations are the computational formulas of relevant parameters to the Ydirectional rotation and Z-directional translation of the right module. When the right module is translating in the Z-direction, Δ11=Δ12 and the calculation of connecting two pairs of anti-rolling beams is identical. The calculation of X, Y-directional translation and Xdirectional rotation is comparatively simple and the analysis and calculation of the left

An example of calculation is given below. Given all relevant geometric

lij=200,OP=t12=380,RM=H1=1200,RM'=hij=26 and supposed that one end of module elevates Δ11=8mm, calculation from the above formula, S11=52, s11=11.3, S12=21.2, s12=4.6,

If the anti-rolling beams and rocker are assembled as sandwich (Fig.7), the oscillation of pendular rod may be limited, so the width between two anti-rolling beams should be enough. Take the anti-rolling beam 11 for example (Fig.20 right) and it is not difficult to

It should be pointed out that when four rockers are oscillating, connection of four endpoints of the rocker l1j、l2j can form a pair of spatial quadrangles. It has the following two

If the module translates in the Z direction, this pair of spatial quadrangles will be in two

If one end of the module elevates or rotates in the Y direction, this pair of quadrangles will

It can be seen that the motion of pendular rod is spatial and the above formulas based on simplified to the plane is approximate one in the circumstance 2. However the error is small and the results are conservative, so there is no problem to apply in the engineering design.

The research and application of maglev trains has gone for more than half century, the study of vehicle structures, focusing on the running gears and secondary suspension system, has

**7. Prospects for structure and kinematic analysis on maglev trains** 

'

11 11 11 11 11 <sup>2</sup>*<sup>l</sup> W SC l*

<sup>11</sup> *l* 75 mm, C11 =20mm,and others are same as the above

, among which C11

*i ij ij*

$$\theta\_{i\dot{j}} = \text{Cov}^{-1}\left(\mathbf{1} - \frac{d\_{i\dot{j}}}{I\_{i\dot{j}}}\right) \tag{6-2}$$

$$S\_{ij} = l\_{ij} \text{Sim}\theta\_{ij} = l\_{ij}\sqrt{1 - \text{Cov}^2 \theta\_{ij}} \tag{6-3}$$

$$\mathbf{S}\_{ij} = \frac{\hbar\_{ij}}{H\_i} \mathbf{S}\_{ij} \tag{6-4}$$

$$\phi\_{\vec{v}} = \operatorname{Sim}^{-1} \left( \frac{\mathbf{s}\_{\vec{ij}}}{I\_{\vec{ij}}} \right)$$

1 ( ) *ij*

*Sin*

*i*

*S*

*H*

*ij*

In above equation (6-3) (6-4), Sij and sij represent transverse motion of end of pendular rod 1j and 2j respectively, from the above equations:

Fig. 22. Z-directional decoupling movement of anti-rolling beam mechanism & oscillation compensation of suspender

$$S\_{ij} = I\_{ij}\sqrt{1 - \left(\mathbf{1} - \frac{t\_{ij}\Delta\_{ij}}{L\_i I\_{ij}}\right)^2} = \frac{t\_{ij}\Delta i j}{L\_i}\sqrt{\frac{2L\_i I\_{ij}}{t\_{ij}\Delta\_{ij}} - 1}$$

$$s\_{ij} = \frac{h\_{ij}t\_{ij}\Delta\_{ij}}{H\_i L\_i}\sqrt{\frac{2I\_{ij}L\_i}{t\_{ij}\Delta\_{ij}} - 1}$$

$$\theta\_{ij} = \text{Cost}^{-1}\left(\mathbf{1} - \frac{t\_{ij}}{L\_i I\_{ij}}\Delta\_{ij}\right)$$

<sup>2</sup> 1 *S l Sin l Cos ij ij ij ij ij* 

*Sin*

*Sin*

In above equation (6-3) (6-4), Sij and sij represent transverse motion of end of pendular rod 1j

Fig. 22. Z-directional decoupling movement of anti-rolling beam mechanism & oscillation

*t t ij L l S l*

*ij ij*

*ij*

*s*

2

 

1 1 1 *ij ij ij i ij*

*Ll L t*

2 1 *ij ij ij ij i*

*i i ij ij*

<sup>1</sup> 1 *ij ij ij*

*i ij t*

*L l*

*ht lL*

*HL t* 

*Cos*

*i ij i ij ij*

2

1 ( ) *ij*

*ij ij ij i h s S*

1 *ij*

*ij s*

 

*l*

*ij*

*ij*

*ij*

and 2j respectively, from the above equations:

compensation of suspender

*Cos*

<sup>1</sup> 1 *ij*

*ij d*

(6-2)

*H* (6-4)

(6-3)

*l*

*i*

*S*

*H*

 

$$\begin{aligned} \mathcal{B}\_{ij} &= \text{Sinc}^{-1} \left( \frac{t\_{ij} \Delta i j}{L\_i} \sqrt{\frac{2 L\_i l\_{ij}}{t\_{ij} \Delta\_{ij}} - 1} \right) \\\\ \phi\_{ij} &= \text{Sinc}^{-1} \left( \frac{h\_{ij} t\_{ij} \Delta\_{ij}}{H\_i L\_i l\_{ij}} \sqrt{\frac{2 I\_{ij} L\_i}{t\_{ij} \Delta\_{ij}} - 1} \right) \end{aligned}$$

The above equations are the computational formulas of relevant parameters to the Ydirectional rotation and Z-directional translation of the right module. When the right module is translating in the Z-direction, Δ11=Δ12 and the calculation of connecting two pairs of anti-rolling beams is identical. The calculation of X, Y-directional translation and Xdirectional rotation is comparatively simple and the analysis and calculation of the left module are similar. About these it is unnecessary to go into details.

An example of calculation is given below. Given all relevant geometric dimensions:ON=L=2700,OP'=t11=2320,

lij=200,OP=t12=380,RM=H1=1200,RM'=hij=26 and supposed that one end of module elevates Δ11=8mm, calculation from the above formula, S11=52, s11=11.3, S12=21.2, s12=4.6, θ11=15.1°, θ12=6.1°, β11=2.48°, β12=1.01°, Φ11=3.24°, Φ12=1.32°.

If the anti-rolling beams and rocker are assembled as sandwich (Fig.7), the oscillation of pendular rod may be limited, so the width between two anti-rolling beams should be enough. Take the anti-rolling beam 11 for example (Fig.20 right) and it is not difficult to conclude that:

$$\text{If } w\_{11} = \frac{l\_{11}}{l\_{11}} S\_{11} \text{ with between two anti-rolling beams : } \text{ } \mathcal{W}\_{11} = \frac{\mathcal{Q}\_{11}^{\prime}}{l\_{11}} S\_{11} + C\_{11} \text{ , among which } \mathcal{C}\_{11} \text{ , is the } \mathcal{C}\_{11} \text{-times} \text{ } \mathcal{C}\_{11} \text{-times} \text{ } \mathcal{C}\_{11} \text{-times} $$

is the diameter of suspender. If ' <sup>11</sup> *l* 75 mm, C11 =20mm,and others are same as the above instance,it is given that W11=59mm.

It should be pointed out that when four rockers are oscillating, connection of four endpoints of the rocker l1j、l2j can form a pair of spatial quadrangles. It has the following two circumstances:

If the module translates in the Z direction, this pair of spatial quadrangles will be in two planes separately and they are parallelogram.

If one end of the module elevates or rotates in the Y direction, this pair of quadrangles will be spatial.

It can be seen that the motion of pendular rod is spatial and the above formulas based on simplified to the plane is approximate one in the circumstance 2. However the error is small and the results are conservative, so there is no problem to apply in the engineering design.

#### **7. Prospects for structure and kinematic analysis on maglev trains**

The research and application of maglev trains has gone for more than half century, the study of vehicle structures, focusing on the running gears and secondary suspension system, has

Structural and Kinematic Analysis of EMS Maglev Trains 121

The kinematic analysis on vehicles includes kinematic analysis methods, modelling and

At present, the simulation method is widely applied and much mature. The analytic method is still developing and its main direction is to apply the mechanism kinematics theory into the kinematic analysis of maglev trains, for example, in multi-rigid-body kinematical analysis on robots, the traces and relative positions of all rigid bodies can be obtained successively by the determination of the motion trace of input end and D-H transformation, which is method of open chain analysis. However the problem is that the maglev trains have no trace of input end which is conveyed in the fourth section of this chapter, so it is Inappropriate to apply the above method into maglev trains. Another analytic method is to found an analytic equation set of the whole kinematic chain by combining geometrical analysis (traces, topological relations among rigid bodies) and equilibrium of internal with external forces, then the equation set is solved to derive traces (instantaneous positions) and topological relations of all bodies (relative positions including the relative positions with traces), which may be called as method of "closed-loop" analysis. That is to say, the traces of the whole kinematic chain and its any component are unknown and all unknown quantities are included in a non-linear equation set. This analytic method is proper to maglev trains and also universal. In this chapter, the analytical process on two kinds of EMS maglev trains

The further studies include that the dynamics vector equations of vehicles can be obtained by establishing the position vectors equations of spatial traces of all rigid bodies and derivation of the equations on time. In addition, considering the vehicle is composed of rigid-elastic bodies, its method of multi-body kinematic analysis is another important and

The analytic method is closely related to modelling, Transformation of areal model into space model becomes an important branch even though its sense may be restricted in theoretical category. If the kinematic analysis model of bogies stated in the sixth section is established based on the theory of spatial mechanism, the motion of binding mechanism of modules can be understood clearly and more accurate structural design may be guided if necessary. In addition, the model in the third section can establish the model with the width

More accurate models are also the pursuit of researchers, for example, considering the influence of change of the module Z-directional displacement caused by the adjustment of electromagnet and elastic elements which may change the kinematic models of maglev

3. The solution should not differ greatly from that of mathematic and numerical solution without much further ado. For maglev trains, their unique features are the simplification of equations, setting of boundary conditions and precision of

**7.2 Progress in kinematic analysis on vehicles** 

solutions of kinematics mathematical model, etc.

2. Establishment of kinematics mathematical model

of vehicle and track by the method of offset curve.

1. Progress in kinematic analysis methods

introduced.

difficult task.

trains.

calculation.

undergone the replacement of many generations. Great strides have also been made in the kinematic analysis which is closely related to design. However, it is to be so regretted that contents of this section is involved in the core of structure and competitiveness and this kind of references are rare, so an brief introduction is given below according to the author's work.

### **7.1 Prospects for research on vehicle structures**

The most feature parts of maglev vehicle structure are the bogies and secondary suspension system for the joint of bogies and car body on which the study touches upon the analysis methods of design and innovation of mechanisms.


undergone the replacement of many generations. Great strides have also been made in the kinematic analysis which is closely related to design. However, it is to be so regretted that contents of this section is involved in the core of structure and competitiveness and this kind of references are rare, so an brief introduction is given below according to the author's

The most feature parts of maglev vehicle structure are the bogies and secondary suspension system for the joint of bogies and car body on which the study touches upon the analysis

1. The research on the mechanism of bogies focuses on the innovation of mechanism which requires providing at most five degrees of freedom for single levitation module. Now the mechanism and its developmental direction are focusing on the spatial linkages mechanism. The number of kinematic pairs and component and joints type are two mainstream research directions, for example, at the longeron's middle of T-type bogie two hinged rods are changed into one rod and more linkage rods are set at the junction part of two modules of A-type bogies. The number of kinematic pairs and component is closely related to degrees of freedom of bogie levitation unit (reduced to connecting rods), and T-type bogies are equipped with more elastic connecting pieces to add the degrees of freedom, which will produce some additional forces and affect their structural life and motion range of component. A-type bogies with plenty of kinematic pairs and component are much complicated in structure and the operation and maintenance work are also increased. Therefore it is an important direction of research on vehicle structure how to constitute the bogie mechanisms with minimum kinematic pairs and components to realize the maximum

2. The innovation of mechanism is still the direction of research on secondary suspension system, but the mechanism of secondary suspension system is closely related to the bogies and is contrary to the bogies in the complexity. This is not hard to understand because the degrees of freedom of bogies are more and the matched secondary suspension system must satisfy its requirements but not limit its degrees of freedom. Therefore an important direction of the research on structure lies in the analysis and innovation of the whole mechanism formed by secondary suspension system and

3. As the advance in the research, the design analysis method is an important branch. It is a trend to apply the development achievements of mechanism in recent years into the structural design of maglev trains. In a nutshell, the topological structure of kinematic chain is represented by graph theory, namely the topological graph represented by points and edges is further represented by matrix. The formulation of experiences and imitation design methods may be very important to the synthesis of bogie mechanism and secondary suspension system. The optimization of mechanisms is another trend, including the objective functions such as scale of motion and degree of freedom and the parameters such as length of linkage rod and

**7.1 Prospects for research on vehicle structures** 

methods of design and innovation of mechanisms.

degrees of freedom now.

connection pair.

bogies. Of course, the difficulties are obvious.

work.

### **7.2 Progress in kinematic analysis on vehicles**

The kinematic analysis on vehicles includes kinematic analysis methods, modelling and solutions of kinematics mathematical model, etc.

1. Progress in kinematic analysis methods

At present, the simulation method is widely applied and much mature. The analytic method is still developing and its main direction is to apply the mechanism kinematics theory into the kinematic analysis of maglev trains, for example, in multi-rigid-body kinematical analysis on robots, the traces and relative positions of all rigid bodies can be obtained successively by the determination of the motion trace of input end and D-H transformation, which is method of open chain analysis. However the problem is that the maglev trains have no trace of input end which is conveyed in the fourth section of this chapter, so it is Inappropriate to apply the above method into maglev trains. Another analytic method is to found an analytic equation set of the whole kinematic chain by combining geometrical analysis (traces, topological relations among rigid bodies) and equilibrium of internal with external forces, then the equation set is solved to derive traces (instantaneous positions) and topological relations of all bodies (relative positions including the relative positions with traces), which may be called as method of "closed-loop" analysis. That is to say, the traces of the whole kinematic chain and its any component are unknown and all unknown quantities are included in a non-linear equation set. This analytic method is proper to maglev trains and also universal. In this chapter, the analytical process on two kinds of EMS maglev trains introduced.

The further studies include that the dynamics vector equations of vehicles can be obtained by establishing the position vectors equations of spatial traces of all rigid bodies and derivation of the equations on time. In addition, considering the vehicle is composed of rigid-elastic bodies, its method of multi-body kinematic analysis is another important and difficult task.

2. Establishment of kinematics mathematical model

The analytic method is closely related to modelling, Transformation of areal model into space model becomes an important branch even though its sense may be restricted in theoretical category. If the kinematic analysis model of bogies stated in the sixth section is established based on the theory of spatial mechanism, the motion of binding mechanism of modules can be understood clearly and more accurate structural design may be guided if necessary. In addition, the model in the third section can establish the model with the width of vehicle and track by the method of offset curve.

More accurate models are also the pursuit of researchers, for example, considering the influence of change of the module Z-directional displacement caused by the adjustment of electromagnet and elastic elements which may change the kinematic models of maglev trains.

3. The solution should not differ greatly from that of mathematic and numerical solution without much further ado. For maglev trains, their unique features are the simplification of equations, setting of boundary conditions and precision of calculation.

**6** 

*Iran* 

**Maglev** 

*1Iran Maglev Technology (IMT), Tehran,* 

*Payame Noor University (PNU), Tehran,* 

*2Civil Engineering Division, Department of Engineering,* 

*3Civil Engineering Division, Azad University, Ramsar,* 

Hamid Yaghoubi1,2, Nariman Barazi2 and Mohammad Reza Aoliaei3

Magnetic levitation (maglev) is a highly advanced technology. It is used in the various cases, including clean energy (small and huge wind turbines: at home, office, industry, etc.), building facilities (fan), transportation systems (magnetically levitated train, Personal Rapid Transit (PRT), etc.), weapon (gun, rocketry), nuclear engineering (the centrifuge of nuclear reactor), civil engineering (elevator), advertising (levitating everything considered inside or above various frames can be selected), toys (train, levitating spacemen over the space ship, etc.), stationery (pen) and so on. The common point in all these applications is the lack of contact and thus no wear and friction. This increases efficiency, reduce maintenance costs and increase the useful life of the system. The magnetic levitation technology can be used as a highly advanced and efficient technology in the various industrial. There are already

Among above-mentioned useful usages, the most important usage of magnetic levitation is in operation of magnetically levitated trains. Magnetically levitated trains are undoubtedly the most advanced vehicles currently available to railway industries. Maglev is the first fundamental innovation in the field of railroad technology since the invention of the railroad. Magnetically levitated train is a highly modern vehicle. Maglev vehicles use noncontact magnetic levitation, guidance and propulsion systems and have no wheels, axles and transmission. Contrary to traditional railroad vehicles, there is no direct physical contact between maglev vehicle and its guideway. These vehicles move along magnetic fields that are established between the vehicle and its guideway. Conditions of no mechanical contact and no friction provided by such technology makes it feasible to reach higher speeds of travel attributed to such trains. Manned maglev vehicles have recorded speed of travel equal to 581km/hr. The replacement of mechanical components by wear-free electronics overcomes the technical restrictions of wheel-on-rail technology. Application of magnetically levitated trains has attracted numerous transportation industries throughout the world. Magnetically levitated trains are the most recent advancement in railway engineering specifically in transportation industries. Maglev trains can be conveniently considered as a solution for transportation needs of the current time as well as future needs of the world. There is variety of designs for maglev systems and engineers keep revealing new ideas about such systems. Many systems have been proposed in different parts of the worlds, and a number of corridors have been selected and researched (Yaghoubi, 2008).

**1. Introduction** 

many countries that are attracted to maglev systems.

### **8. References**


## **Maglev**

### Hamid Yaghoubi1,2, Nariman Barazi2 and Mohammad Reza Aoliaei3

*1Iran Maglev Technology (IMT), Tehran, 2Civil Engineering Division, Department of Engineering, Payame Noor University (PNU), Tehran, 3Civil Engineering Division, Azad University, Ramsar, Iran* 

### **1. Introduction**

122 Infrastructure Design, Signalling and Security in Railway

Yoshio Hikasa, Yutaka Takeuchi.(1980). Detail and Experimental Results of Ferromagnetic

*Transactions on Vehicular Technology*, VOL. VT-29, No. 1, February, pp35-41. J.L. He, D.M. Rote, and H.T. Coffey (1992). Survey of Foreign Maglev Systems[R]. Center for

Tejima Yuichi, et al., (2004). Aichi High-speed Traffic HSST-100 Type Vehicle[J]. *Vehicle* 

Seki, Tomohiro.(1995). The Development of HSST-100L[A]. In: *Proceedings MAGLEV'95 14th* 

Maglev Technical Committee.(2007). Vehicle Part I General Requirements, In: *Rapid Maglev* 

Z.S.Zhao, L.M.Ying.(2007) One Running Gear of Maglev Vehicle: China, ZL03130750.7[p].

Zhao Zhisu, Ren Chao.(2009). Modeling of Kinematics of EMS Maglev Vehicle[J]. *Journal of* 

Zhao Zhi-Su, Et al.,(2000) Motion Analysis and Design for Yawing Mechanism of Maglev Vehicle [J].*Electric Drive for Locomotive*, (6), pp11-13,30, ISSN 1000-128x. Mei Zu, Li Jie.(2007). Dynamics Simulation for Yawing Mechanism of Maglev train Based on

Jiang Haibo et al.(2007). A Study on Forced Steering Mechanism of Low-speed Maglev

Zeng You-Wen,Wang Shao-Hua.(2003). Research on geometri- cal curve nigotiating of three-

Zhang Kun, LI Jie.(2005). CHANG Wensen. Structure de-coupling analysis of maglev train

Zhao Chun-Fa, Zai Wan-Ming.(2005). Guidance Mode and dynamic lateral characteristic of low-speed maglev vehicle[J]. *China Railway Science*, (1), pp28-32, ISSN 1001-4632. Sinha P. K.(1987). *Electromagnetic Suspension Dynamics & Control* [M]. Perter Peregrinus Ltd.,

Luo Kun, Yin Li-Ming, XIE Yun-de.(2004). Analysis on location parameters of line for mid-

Zhao Zhisu.(2009). Researches On Turing Characteristic Of Tilting Suspension High-Speed Maglev Train[J]. *Electric Drive for Locomotive*, (1), pp43-45, ISSN 1000-128x.

low speed maglev Train Calculation and analysis of gradient[J]. *Electric Drive for* 

bogie[J]. *Electric Drive for Locomotive*, (1), pp 22-39, ISSN1000-128x.

Virtual Prototype [J]. *Journal of System Simulation*, 19 (18), pp 4199-4203, ISSN 1004-

truck maglev vehicle [J]. *Journal of Southwest Jiaotong University*, 38(3), pp282-

*The China Railway Society*.,Vol.31, (4), pp32-37,ISSN 1001-8360.

9700 South Cass Avenue, Argonne, Illinois 60439, July, pp13-14

*System Design Principles* [R]. White paper, 12, pp18- 19.

Train[J]. *Diesel Locomotive*, (4), pp15-18, ISSN 1003-1839.

*Technology*, 227(3), pp86-97.

3800721554, Berlin, pp51-55.

Levitation System of Japan Air Lines HSST-01/=02 Vehicles[C]//IEEE. *IEEE* 

Transportation Research, Energy Systems Division, Argonne National Laboratory,

*International Conference on Magnetically Levitated Systems* [C]. VDE-Verlag, ISBN-10

**8. References** 

24. 10.

731x

285,ISSN 0258-2724.

ISBN 10-0863410634, London.

*Locomotive*, (4), pp17-19, ISSN 1000-128x.

Magnetic levitation (maglev) is a highly advanced technology. It is used in the various cases, including clean energy (small and huge wind turbines: at home, office, industry, etc.), building facilities (fan), transportation systems (magnetically levitated train, Personal Rapid Transit (PRT), etc.), weapon (gun, rocketry), nuclear engineering (the centrifuge of nuclear reactor), civil engineering (elevator), advertising (levitating everything considered inside or above various frames can be selected), toys (train, levitating spacemen over the space ship, etc.), stationery (pen) and so on. The common point in all these applications is the lack of contact and thus no wear and friction. This increases efficiency, reduce maintenance costs and increase the useful life of the system. The magnetic levitation technology can be used as a highly advanced and efficient technology in the various industrial. There are already many countries that are attracted to maglev systems.

Among above-mentioned useful usages, the most important usage of magnetic levitation is in operation of magnetically levitated trains. Magnetically levitated trains are undoubtedly the most advanced vehicles currently available to railway industries. Maglev is the first fundamental innovation in the field of railroad technology since the invention of the railroad. Magnetically levitated train is a highly modern vehicle. Maglev vehicles use noncontact magnetic levitation, guidance and propulsion systems and have no wheels, axles and transmission. Contrary to traditional railroad vehicles, there is no direct physical contact between maglev vehicle and its guideway. These vehicles move along magnetic fields that are established between the vehicle and its guideway. Conditions of no mechanical contact and no friction provided by such technology makes it feasible to reach higher speeds of travel attributed to such trains. Manned maglev vehicles have recorded speed of travel equal to 581km/hr. The replacement of mechanical components by wear-free electronics overcomes the technical restrictions of wheel-on-rail technology. Application of magnetically levitated trains has attracted numerous transportation industries throughout the world. Magnetically levitated trains are the most recent advancement in railway engineering specifically in transportation industries. Maglev trains can be conveniently considered as a solution for transportation needs of the current time as well as future needs of the world. There is variety of designs for maglev systems and engineers keep revealing new ideas about such systems. Many systems have been proposed in different parts of the worlds, and a number of corridors have been selected and researched (Yaghoubi, 2008).

Maglev 125

Maglev suspension systems are divided into two groups of ElectroMagnetic Suspension (EMS) and ElectroDynamic Suspension (EDS). There are varieties of vehicles that are manufactured based on these two types of systems. Vehicle path in EMS and EDS systems are called guideway and track, respectively. Basically, there are two main elements in a maglev system including its vehicle and the guideway. The three primary functions in maglev technology are levitation, propulsion, and guidance. Magnetic forces perform all of these. Magnets are used to generate such magnetic forces. For EMS systems, these magnets are located within the vehicle while for EDS systems magnets are located in the track. Performance of EMS system is based on attractive magnetic forces, while EDS system works with repulsive magnetic forces. In EDS system, the vehicle is levitated about 1 to 10 cm above the track using repulsive forces as presented in Fig. 1. In EMS system, the vehicle is levitated about 1 to 2 cm above the guideway using attractive forces as presented in Fig. 2. In EMS system, the electromagnets on the vehicle interact with and are attracted to levitation rails on the guideway. Electromagnets attached to the vehicle are directed up toward the guideway, which levitates the vehicle above the guideway and keeps the vehicle levitated. Control of allowed air gaps between the guideway and vehicle is achieved by using highly advanced control systems. Figs. 1, 2 show the components of the guideway and

track including levitation and guidance systems in aforementioned maglev systems.

Fig. 1. Schematic diagram of EDS maglev system

**2. Vehicle** 

Rapid growth of populations and the never ending demand to increase the speed of travel has always been a dilemma for city planners. The future is already here. Rapid transit and high-speed trains have always been thought of and are already in use. This is the way further into the future. Trains with magnetic levitations are part of the game. Conventional railway systems have been modified to make them travel at much higher speeds. Also, variety of technologies including magnetic levitation systems and high-speed railway (HSR) systems has been introduced. Rapid development of transportation industries worldwide, including railroads and the never ending demand to shorten travel time during trade, leisure, etc. have caused planning and implementation of high-speed railroads in many countries. Variety of such systems including maglev has been introduced to the industry. Maglev trains are a necessity for modern time transportation needs and vital for the future needs of railways, worldwide. This has resulted in the development of a variety of maglev systems that are manufactured by different countries. Maglev systems currently in use have comparable differences. The current models are also changing and improving.

Industries have to grow in order to facilitate many aspects of modern day life. This comes with a price to pay for by all members of socities. Industrial developments and widespread use of machineries have also increased risks of finanicial damages and loss of lives. Safety and needs to physically protect people against machineries may have not been a priority in the past but they are neccessities of modern times. Experts of industries have the task of solving safety and protection issues before implementing machineris. This is a step with high priority for all industrial assignments. While being fast, relaible and comfortable, maglev systems have found special places in minds of people. Running at such high speeds, maglev sytems have to be safe and need to be renown for safety. This puts much heavier loads on the shoulders of the corresponding experts and managers, compared to some other means of transportation. Safety is knowingly acting with proper functions to provide comfort and reduce dangers, as much as possdible. Risk management techniques have a vital role in organizing and implementing proper acts during incidents, accidents or mishaps in maglev systems operations. Effective management has a specific place in such processes. Obviously, such plannings put considereable finanicial load on the system. Implementation of internationally accepted standards is a fundamental step toward uplifting track safety. It will also serve to improve route quality, increase passenger loads and increase speed of travel. Maglev vehicle is one of the important transportation equipment of the urban track traffic system toward the future (Wang et al., 2007).

The overall plan for research and development and application of maglev technology should be made at the national level. This plan shall include the development plans as to research and development of key maglev technology, project implementing technology research and development of maglev project, plans of building maglev passage based on traffic demands, investment and financing system for the construction and operation of maglev system, research on implementing plans of high-density operational organization and maintenance of maglev route and so on.

It is very important to be vigilant about economical aspects of any major project during its planning and construction phases. Optimal use of local resources must be all accounted for. Technical and economical evaluation of the projects is a necessity to their success. It is necessary to have prior knowledge for investing into a project and then implementing its goals. Good planning makes it feasible to run the projects with reduced risks and increased return for the investment.

Rapid growth of populations and the never ending demand to increase the speed of travel has always been a dilemma for city planners. The future is already here. Rapid transit and high-speed trains have always been thought of and are already in use. This is the way further into the future. Trains with magnetic levitations are part of the game. Conventional railway systems have been modified to make them travel at much higher speeds. Also, variety of technologies including magnetic levitation systems and high-speed railway (HSR) systems has been introduced. Rapid development of transportation industries worldwide, including railroads and the never ending demand to shorten travel time during trade, leisure, etc. have caused planning and implementation of high-speed railroads in many countries. Variety of such systems including maglev has been introduced to the industry. Maglev trains are a necessity for modern time transportation needs and vital for the future needs of railways, worldwide. This has resulted in the development of a variety of maglev systems that are manufactured by different countries. Maglev systems currently in use have

Industries have to grow in order to facilitate many aspects of modern day life. This comes with a price to pay for by all members of socities. Industrial developments and widespread use of machineries have also increased risks of finanicial damages and loss of lives. Safety and needs to physically protect people against machineries may have not been a priority in the past but they are neccessities of modern times. Experts of industries have the task of solving safety and protection issues before implementing machineris. This is a step with high priority for all industrial assignments. While being fast, relaible and comfortable, maglev systems have found special places in minds of people. Running at such high speeds, maglev sytems have to be safe and need to be renown for safety. This puts much heavier loads on the shoulders of the corresponding experts and managers, compared to some other means of transportation. Safety is knowingly acting with proper functions to provide comfort and reduce dangers, as much as possdible. Risk management techniques have a vital role in organizing and implementing proper acts during incidents, accidents or mishaps in maglev systems operations. Effective management has a specific place in such processes. Obviously, such plannings put considereable finanicial load on the system. Implementation of internationally accepted standards is a fundamental step toward uplifting track safety. It will also serve to improve route quality, increase passenger loads and increase speed of travel. Maglev vehicle is one of the important transportation equipment of the urban track traffic system toward the

The overall plan for research and development and application of maglev technology should be made at the national level. This plan shall include the development plans as to research and development of key maglev technology, project implementing technology research and development of maglev project, plans of building maglev passage based on traffic demands, investment and financing system for the construction and operation of maglev system, research on implementing plans of high-density operational organization

It is very important to be vigilant about economical aspects of any major project during its planning and construction phases. Optimal use of local resources must be all accounted for. Technical and economical evaluation of the projects is a necessity to their success. It is necessary to have prior knowledge for investing into a project and then implementing its goals. Good planning makes it feasible to run the projects with reduced risks and increased

comparable differences. The current models are also changing and improving.

future (Wang et al., 2007).

return for the investment.

and maintenance of maglev route and so on.

### **2. Vehicle**

Maglev suspension systems are divided into two groups of ElectroMagnetic Suspension (EMS) and ElectroDynamic Suspension (EDS). There are varieties of vehicles that are manufactured based on these two types of systems. Vehicle path in EMS and EDS systems are called guideway and track, respectively. Basically, there are two main elements in a maglev system including its vehicle and the guideway. The three primary functions in maglev technology are levitation, propulsion, and guidance. Magnetic forces perform all of these. Magnets are used to generate such magnetic forces. For EMS systems, these magnets are located within the vehicle while for EDS systems magnets are located in the track. Performance of EMS system is based on attractive magnetic forces, while EDS system works with repulsive magnetic forces. In EDS system, the vehicle is levitated about 1 to 10 cm above the track using repulsive forces as presented in Fig. 1. In EMS system, the vehicle is levitated about 1 to 2 cm above the guideway using attractive forces as presented in Fig. 2. In EMS system, the electromagnets on the vehicle interact with and are attracted to levitation rails on the guideway. Electromagnets attached to the vehicle are directed up toward the guideway, which levitates the vehicle above the guideway and keeps the vehicle levitated. Control of allowed air gaps between the guideway and vehicle is achieved by using highly advanced control systems. Figs. 1, 2 show the components of the guideway and track including levitation and guidance systems in aforementioned maglev systems.

Fig. 1. Schematic diagram of EDS maglev system

Maglev 127

In 2005, China built its own maglev train. This train reached to the test speed of 150km/hr over a track length of 204m. In February 2006, Chinese government announced that they decided to extend Shanghai maglev to Hangzhou city the capital of Zhejiang province. It would create the world's first intercity maglev line. The project will be managed by a German consortium leaded by Siemens Company. This route is of 170 to 175 km in length. The Ministry of Railways chief planner said in March 2010 that China had agreed to build a maglev line between Shanghai and Hangzhou. The line will start construction this year, Xinhua news agency reported. The new link will be 199.5 kilometers, about 24 kilometers longer than that included in the 2006 plan. The top speed of the maglev will be 450 kilometers per hour. It will take about half an hour to travel from Shanghai to Hangzhou, a trip which usually takes one and an half hours on the current service. The new line will also contain a downtown section of about 34 kilometers which is expected to connect the city's

Maglev transport system features its potential development in a region with fast growing demand of intercity travel, such as the Shanghai maglev transport system (Yau, 2009). Growth of maglev technologies originated from human's pursuit of travel speed. Since the past 80 years, a number of scientists have made several researches on the feasibility of applying this transport technology. Eventually, they have realized commercial operation in Shanghai, China. Since China has a large population, the demand of applying this technology not only comes into being in the intercity longdistance transport but also in the city traffic field, which is mainly materialized in the low-speed technology and light vehicles (Siu, 2007). The Shanghai maglev line solved many important problems concerning the practical use of maglev transportation system. It has proved that the maglev technology is mature and can be put into practical application with good safety and reliability (Luguang, 2005). The construction data and operational experience of Shanghai maglev route create quite advantaged conditions for the application of maglev technology in China. It is also a blessed advantaged condition for research and development of maglev technology of China. Therefore, to share and make full use of the experiences and technical data of this operational route at national level may promote the research and development progress of maglev technology in

In field of low-speed maglev systems, the National Defense University and the South South-West Jiaotong University worked for a long time for the development of the system similar to Japanese HSST. The Beijing Enterprises Holdings Maglev Technology Development Co. together with the National Defense University built a CMS-03 test vehicle and a 204m long test line with minimum radius of 100m and maximum climbing of 4% in 2001 in Changsha. Up to now, the vehicle traveled over 7000 km with over 20,000-test run and 40,000 times start and stop operations, its safety and reliability are proved. Recently, based on the test results a new engineering prototype vehicle has been constructed. It is planned to build a 2 km test and operation line in Kunming, after all necessary testing is finished. The whole system can be accepted for real urban application

Technical specifications of high-speed and low-speed maglev trains are presented in Table 1

two international airports, Pudong and Hongqiao.

China (Baohua et al., 2008).

in 3-5 years (Luguang, 2005).

and 2, respectively (Yaghoubi & Sadat Hoseini, 2010).

Fig. 2. Schematic diagram of EMS maglev system

Germany and Japan are clearly the front runners of the maglev technology. German's Transrapid International (TRI), a joint venture by Siemens AG and ThyssenKrupp, with EMS system has presented ninth generation of its maglev vehicles namely TR01 to TR09. TRI has been investigating electromagnetic levitation since 1969 and commissioned TR02 in 1971. The eighth generation vehicle, TR08 operates on 31.5 km of the guideway at Emsland test track in northwest Germany. The contract for implementing the world's first Transrapid commercial line was signed in Shanghai in January 2001. Construction work of the Shanghai Transrapid line began in March 2001. After only 22 months of construction time, the world's first commercially operated Transrapid train made its successful maiden trip on December, 31 2002. On December, 2003, the world's first commercial Transrapid line with a five section train started scheduled operation in Shanghai. TR08 and TR09 vehcles are used for the Shanghai Maglev Train (SMT) and TR09 Munich project, respectively. TR08 consists of 2 to 10 car bodies. SMT consists of 5 car bodies and travels on a 30km double-track elevated guideway, connecting the LongYang Road station (LYR), served by Metro Line 2 situated in the Pudong trade centre in Shanghai, to the Pudong International Airport (PIA). High-speed signifies operation of at least at 250km/hr. SMT has reached to the record speed of 501km/hr, a average speed (peak operating speed) of 431km/hr and average speed of 268km/hr.

Germany and Japan are clearly the front runners of the maglev technology. German's Transrapid International (TRI), a joint venture by Siemens AG and ThyssenKrupp, with EMS system has presented ninth generation of its maglev vehicles namely TR01 to TR09. TRI has been investigating electromagnetic levitation since 1969 and commissioned TR02 in 1971. The eighth generation vehicle, TR08 operates on 31.5 km of the guideway at Emsland test track in northwest Germany. The contract for implementing the world's first Transrapid commercial line was signed in Shanghai in January 2001. Construction work of the Shanghai Transrapid line began in March 2001. After only 22 months of construction time, the world's first commercially operated Transrapid train made its successful maiden trip on December, 31 2002. On December, 2003, the world's first commercial Transrapid line with a five section train started scheduled operation in Shanghai. TR08 and TR09 vehcles are used for the Shanghai Maglev Train (SMT) and TR09 Munich project, respectively. TR08 consists of 2 to 10 car bodies. SMT consists of 5 car bodies and travels on a 30km double-track elevated guideway, connecting the LongYang Road station (LYR), served by Metro Line 2 situated in the Pudong trade centre in Shanghai, to the Pudong International Airport (PIA). High-speed signifies operation of at least at 250km/hr. SMT has reached to the record speed of 501km/hr, a

average speed (peak operating speed) of 431km/hr and average speed of 268km/hr.

Fig. 2. Schematic diagram of EMS maglev system

In 2005, China built its own maglev train. This train reached to the test speed of 150km/hr over a track length of 204m. In February 2006, Chinese government announced that they decided to extend Shanghai maglev to Hangzhou city the capital of Zhejiang province. It would create the world's first intercity maglev line. The project will be managed by a German consortium leaded by Siemens Company. This route is of 170 to 175 km in length. The Ministry of Railways chief planner said in March 2010 that China had agreed to build a maglev line between Shanghai and Hangzhou. The line will start construction this year, Xinhua news agency reported. The new link will be 199.5 kilometers, about 24 kilometers longer than that included in the 2006 plan. The top speed of the maglev will be 450 kilometers per hour. It will take about half an hour to travel from Shanghai to Hangzhou, a trip which usually takes one and an half hours on the current service. The new line will also contain a downtown section of about 34 kilometers which is expected to connect the city's two international airports, Pudong and Hongqiao.

Maglev transport system features its potential development in a region with fast growing demand of intercity travel, such as the Shanghai maglev transport system (Yau, 2009). Growth of maglev technologies originated from human's pursuit of travel speed. Since the past 80 years, a number of scientists have made several researches on the feasibility of applying this transport technology. Eventually, they have realized commercial operation in Shanghai, China. Since China has a large population, the demand of applying this technology not only comes into being in the intercity longdistance transport but also in the city traffic field, which is mainly materialized in the low-speed technology and light vehicles (Siu, 2007). The Shanghai maglev line solved many important problems concerning the practical use of maglev transportation system. It has proved that the maglev technology is mature and can be put into practical application with good safety and reliability (Luguang, 2005). The construction data and operational experience of Shanghai maglev route create quite advantaged conditions for the application of maglev technology in China. It is also a blessed advantaged condition for research and development of maglev technology of China. Therefore, to share and make full use of the experiences and technical data of this operational route at national level may promote the research and development progress of maglev technology in China (Baohua et al., 2008).

In field of low-speed maglev systems, the National Defense University and the South South-West Jiaotong University worked for a long time for the development of the system similar to Japanese HSST. The Beijing Enterprises Holdings Maglev Technology Development Co. together with the National Defense University built a CMS-03 test vehicle and a 204m long test line with minimum radius of 100m and maximum climbing of 4% in 2001 in Changsha. Up to now, the vehicle traveled over 7000 km with over 20,000-test run and 40,000 times start and stop operations, its safety and reliability are proved. Recently, based on the test results a new engineering prototype vehicle has been constructed. It is planned to build a 2 km test and operation line in Kunming, after all necessary testing is finished. The whole system can be accepted for real urban application in 3-5 years (Luguang, 2005).

Technical specifications of high-speed and low-speed maglev trains are presented in Table 1 and 2, respectively (Yaghoubi & Sadat Hoseini, 2010).

Maglev 129

Country U.S U.S U.S U.S U.S Korea Indonesia Japan

HSST-200 Colorado 200

Suspension EMS EDS EMS EMS EDS EMS EMS EMS

2 1.6 1.6 **-** 2 **-** 1 1.1

Standin: 100

Seated: 50-100 <sup>100</sup>

2.5 (seated) 1.25 - <sup>2</sup> **-** 1 1.1

**-** 3.6 3.1 **-** 4 **-** 1.25 1.1



Empty: 19.5-27 75% Loaded: 23.5- 36

28.5

Empty: 21 75% Loaded: 27.5


) <sup>12000</sup> <sup>12000</sup> <sup>6000</sup> **- - - - -** 

Speed (km/hr) <sup>160</sup> <sup>80</sup> <sup>200</sup> <sup>64</sup> **-** <sup>110</sup> <sup>110</sup> <sup>100</sup>

103

(mm) 20 25 - 10 100 - 10 -

Car-body - 1 2 1 - 2 - 2

car body (m) - 13 24.3 13.5 20- 30 13.5 13.5 15 Car width (m) - 2.6 3.2 - 3.3 28.5 28.5 - Car height (m) - 3 3.65 - 3 3.5 3.53 -

> <sup>44</sup>Empty: 11.5

CDOTa AMTb /

ODUc M2000 MOCIEd Jakarta HSSTe

**- - - -** HSST-

100L

100

Seated: 33 Standing: 67 Total:100

System/ Project

Max. Operation

Max. Initial Acceleration (m/s2)

> Capacity (pphpdf

Passenger Capacity (One Car)

Air gap

Service Brake Max. Deceleration (m/s2)

Emergency Brake Max. Deceleration (m/s2)

Number of Bogies in each Car body

Number of Magnets in each Bogie

length of each

Vehicle weight

(ton) -

(b) American Maglev Technology (c) Old Dominion University

(e) High Speed Surface Transport (f) pphpd: passengers/hr/direction

(a) Colorado Department of Transportation

(d) Ministry of Commerce, Industry and Energy

Table 2. Characteristics of low-speed maglev trains

Magne Motion

Vehicle M3 -

GA (General Atomics)

**-** 100 Seated:

Empty: 12 75% Loaded: 17.6

1.6 1.6 (standing)


Table 1. Characteristics of high-speed maglev trains

body Speed Year

TR06 2 392 1987

TR07 2 450 1993

TR08 <sup>3</sup> <sup>500</sup> <sup>1999</sup>

SMT 5 501 <sup>2003</sup>

TR09 3 350 2008

ML-500R 1 517 1979

MLU001 2 405 1980-1982

MLU001 3 352 1980-1982

MLU002 1 394 1987

MLX01 3 550 1997

MLX01 5 552 1999

MLX01 3 581 2003

(German)

(Shanghai)

Country System Suspension Performance Levitation Vehicle Car-

force

EDS Repulsive

force

At low speed and even at standstill

At speeds higher than 100km/hr

TR08

German TRI EMS Attractive

Railway Technical Research Institute (RTRI) and JR (Japan Railways) Central

Japan

Table 1. Characteristics of high-speed maglev trains


(a) Colorado Department of Transportation

(b) American Maglev Technology

(c) Old Dominion University

(d) Ministry of Commerce, Industry and Energy

(e) High Speed Surface Transport

(f) pphpd: passengers/hr/direction

Table 2. Characteristics of low-speed maglev trains

Maglev 131

span

Colorado Elevated Concrete Concrete Single-span 25 U-shaped **- -**

span

Colorado Elevated Steel Concrete Single-span 30 Truss **-** -

span

1 Elevated Concrete Concrete C 1 I Single-span 24.8 1981-83 2 Elevated Steel Concrete S 1 I Single-span 24.8 1981-83 3 Elevated Concrete Concrete C 2 I Single-span 24.8 1984-86 4 Elevated Steel Concrete S 2 I Single-span 24.8 1984-86 5 Elevated Steel Concrete S 4 I Two-span 24.8 1995 6 Elevated Concrete Concrete C 4 I Single-span 24.8 1995 7 Elevated Steel Concrete S 4 II Two-span 12.4 1997 Steel Concrete S 4 II Two-span 12.4 1997 Ground-level

Steel Concrete S 4 III Two-span 6.2 1997 Ground-level

Concrete Concrete C 4 III Two-span 6.2 1998 Ground-level

Concrete Concrete C 8 III Two-span 6.1 2006-2007 Ground-level

Hybrid Concrete H 3 II Single-span 12.4 <sup>2006</sup> Ground-level

13 Elevated Hybrid Concrete H 1 I Two-span 31 1999 14 Elevated Hybrid Concrete H 2 I Two-span 24.8 2001 15 Elevated Hybrid Concrete H 2 I Single-span 24.8 2002 Concrete Concrete C 5 II Single-span 9.3 2005 Ground-level

10 Elevated Concrete Concrete **-** I Single-span 24.8 **-**  Concrete Concrete **- -** Two-span **- -** Ground-level

Steel Concrete Single/Two

Column (elevated)/ Support (at-grade) Span (m)

Steel Concrete Single-span 25-27.5 Inverted-T **- -** 

Crosssection

20 to 30 Box 2.972

Span (m) Generation Type Span

Width of Girder (m)

36 Box 1 1.6

36 Box 1.7 1.98, 1.22

Length of

Height of Girder (m)

3.66 (at midspan) 5.49 (at the supports)

Year of Installation

System Guideway Girder Column Span Length of

at-grade Hybrid Concrete Single/Two

Table 3. Technical specifications of guideways for FTA

Table 4. Technical specifications of guideways for TRI

Motion Elevated Concrete Concrete Two-

ODU (a) Elevated Concrete**-**

Colorado Elevated Concrete**-**

GA (b) Elevated/

(a) Old Dominion University (b) General Atomics

No. Guideway Girder

(at-grade) 8

(at-grade) 9

(at-grade) 11

(at-grade) 12

(at-grade) 16

(at-grade) 17

(at-grade) 18

Magne

### **3. Guideway**

The guideway is the structure that maglev vehicles move over it and are supported and guided by it. Its main roles are: to direct the movement of the vehicle, to support the vehicle load, and to transfer the load to the ground. It is the function of the guideway structure to endure applied loads from the vehicle and transfer them to the foundations. It is the main element in maglev system and holds big share of costs for the system. It is vital for maglev trains. The cost of the guideway structure is expected to be 60-80 percent of the overall initial capital investment cost (Zicha, 1986; Uher, 1989; Cai et al., 1994; FTA, 2004; Ren et al., 2009). Maglev train levitates over single or double track guideway. Guideway can be mounted either at-grade or elevated on columns and consists of individual steel or concrete beams. Elevated guideways occupy the least amount of land on the ground. Moreover, with such systems there is guarantee of meeting no obstacle while along the route. To guarantee safety for maglev trains necessitates guarantee that there will be no intersection between guideway and other forms of traffic routes. To serve the purpose, general proposition is to have elevated guideways.

Guideway provides guidance for the movement of the vehicle, to support the vehicle load, and to transfer the load to the ground. In maglev guideways contrary to traditional railroad tracks, there is no need to ballast, sleeper, rail pad and rail fastenings to stabilize the rail gauge. A guideway consists of a beam (girder) and two levitation (guidance) rails. Guideways can be constructed at grade (ground-level) or elevated including columns with concrete, steel or hybrid beams. Maglev elevated guideways minimize land occupation and prevent collision with other forms of traffic at-grade intersections. Guideways are designed and constructed as single or double tracks. Guideways can be U-shaped, I-shaped, T-shaped, Box, Truss and etc. Majority of cross-sections of guideway girders are also U-shaped. The rail gauges (track gauges) and spans are mostly 2.8 m and 24.8 m (Type I), respectively.

During the past three decades, different guideways have been developed, constructed and tested. Technical specifications of guideways for Federal Transit Administration (FTA) in U. S. Department of Transportation and TRI in Germany are presented in Table 3 (FTA, 2004, 2005a) and Table 4 (Schwindt, 2006), respectively. The guideway for the Transrapid in the Shanghai project was realized as a double-track guideway in 2001 and 2002. This Hybrid guideway is generation H2, type I as single-span (24.8 m) and two-span (2 x 24.8 m) girders. The Shanghai guideway I-shaped hybrid girder is 24.8m long, 2.8 wide, 2.2m high with a reinforced concrete girder (Schwindt, 2006; Dai, 2005).

Guideway consists of superstructures and substructures. Fig. 3 shows components of guideway's superstructures including beam and levitation (guidance) rails in an EMS maglev system where L is span length in meters and H is girder height in meters.

Depending on height of the guideway, it is separated in:


Where h is guideway gradient height in meters.

The standard guideways are (Figs. 4, 5):


The guideway is the structure that maglev vehicles move over it and are supported and guided by it. Its main roles are: to direct the movement of the vehicle, to support the vehicle load, and to transfer the load to the ground. It is the function of the guideway structure to endure applied loads from the vehicle and transfer them to the foundations. It is the main element in maglev system and holds big share of costs for the system. It is vital for maglev trains. The cost of the guideway structure is expected to be 60-80 percent of the overall initial capital investment cost (Zicha, 1986; Uher, 1989; Cai et al., 1994; FTA, 2004; Ren et al., 2009). Maglev train levitates over single or double track guideway. Guideway can be mounted either at-grade or elevated on columns and consists of individual steel or concrete beams. Elevated guideways occupy the least amount of land on the ground. Moreover, with such systems there is guarantee of meeting no obstacle while along the route. To guarantee safety for maglev trains necessitates guarantee that there will be no intersection between guideway and other forms of traffic routes. To serve

Guideway provides guidance for the movement of the vehicle, to support the vehicle load, and to transfer the load to the ground. In maglev guideways contrary to traditional railroad tracks, there is no need to ballast, sleeper, rail pad and rail fastenings to stabilize the rail gauge. A guideway consists of a beam (girder) and two levitation (guidance) rails. Guideways can be constructed at grade (ground-level) or elevated including columns with concrete, steel or hybrid beams. Maglev elevated guideways minimize land occupation and prevent collision with other forms of traffic at-grade intersections. Guideways are designed and constructed as single or double tracks. Guideways can be U-shaped, I-shaped, T-shaped, Box, Truss and etc. Majority of cross-sections of guideway girders are also U-shaped. The rail gauges (track

During the past three decades, different guideways have been developed, constructed and tested. Technical specifications of guideways for Federal Transit Administration (FTA) in U. S. Department of Transportation and TRI in Germany are presented in Table 3 (FTA, 2004, 2005a) and Table 4 (Schwindt, 2006), respectively. The guideway for the Transrapid in the Shanghai project was realized as a double-track guideway in 2001 and 2002. This Hybrid guideway is generation H2, type I as single-span (24.8 m) and two-span (2 x 24.8 m) girders. The Shanghai guideway I-shaped hybrid girder is 24.8m long, 2.8 wide, 2.2m high with a

Guideway consists of superstructures and substructures. Fig. 3 shows components of guideway's superstructures including beam and levitation (guidance) rails in an EMS

maglev system where L is span length in meters and H is girder height in meters.


the purpose, general proposition is to have elevated guideways.

gauges) and spans are mostly 2.8 m and 24.8 m (Type I), respectively.

reinforced concrete girder (Schwindt, 2006; Dai, 2005).

Depending on height of the guideway, it is separated in:


The standard guideways are (Figs. 4, 5):


Where h is guideway gradient height in meters.

**3. Guideway** 


(a) Old Dominion University

(b) General Atomics

#### Table 3. Technical specifications of guideways for FTA


Table 4. Technical specifications of guideways for TRI

Maglev 133

The guideway height varies smoothly between 1.45 m and about 20 m. For greater guideway heights or span lengths larger than 40 m primary structures are needed in the form of conventional bridges. For substructures such as columns or foundations, reinforced concrete is proposed. The substructures for the guideway girders consist of several components. These are, depending on guideway type and gradient height, the column heads with bearing supports, the columns, tie beams and intermediate beams and the foundation slabs. They are built onto the natural soil, soil with soil improvement and/or on piles. The dimensions of the reinforced concrete substructures result from the high demands

Different types of existing maglev magnetic suspension systems and technical specifications of existing guideways are presented in Table 5. As seen in this table, the majority of the maglev suspension systems are of electromagnetic suspension type. This table shows the most commonly used guideway structures and suspension systems. As indicated in the table, majority of guideway are elevated, double-track and U-shaped. The track gauges and

> Transrapid Germany

Different Types (mostly U-shaped)

Elevated Ground-level (at grade)

> Double track

Track (rail) gauge 2.8 m 2.8 m 1.7 m 2.8 m 1-2.972 m 2.8 m

Span length (elevated) 24.8 m mostly 24.8 m 30 m - mostly 25 m 25-30 m

of tunnel in a route 0 22% 15% 87% 0 0

In recent years, different designs of guideways have been developed, constructed and tested among which U-girder guideways happens to be the most popular. In Korea, since 1980, prestressed concrete U-girder guideway for straight route applications has been proposed (Jin et al., 2007). In Germany, during 1981-1983, a U-girder guideway was built at the Transrapid Test Facility (TVE) by TRI and was used in the TR07 project (Lever, 1998). This guideway was further optimized and improved during 1984-1986 (Schwindt et al., 2007). An elevated concrete U-girder guideway was installed in TVE in 1995 (Schwindt, 2006). One of the three kinds of girders considered for Colorado Maglev Project (CMP) in the Colorado Department of Transportation (CDOT) is a concrete U-

HSST Japan

U-shaped

Elevated

Double track

JR

U-shaped Inverted Tshaped

Elevated Groundlevel (at grade)

> Double track

Japan U.S Korea

Different types (mostly EMS)

U-shaped Box Truss

> Double track

EMS

U-shaped

Double track

Elevated Elevated

on the permissible deformations of the substructures (Grossert, 2006).

China

Double track

Suspension EMS EMS EMS EDS

spans are also mostly 2.8 m and 24.8 m, respectively.

Maglev systems Shanghai

Section I-shaped

Guideway Elevated

Table 5. Guideway structures and suspension systems

Maximum number of tracks in a route (guideway structure)

Maximum percent

girder (FTA, 2004).

Fig. 5. Standard guideway types

Fig. 3. Components of guideway in an EMS maglev system

Fig. 4. Standard guideway types

Fig. 5. Standard guideway types

The guideway height varies smoothly between 1.45 m and about 20 m. For greater guideway heights or span lengths larger than 40 m primary structures are needed in the form of conventional bridges. For substructures such as columns or foundations, reinforced concrete is proposed. The substructures for the guideway girders consist of several components. These are, depending on guideway type and gradient height, the column heads with bearing supports, the columns, tie beams and intermediate beams and the foundation slabs. They are built onto the natural soil, soil with soil improvement and/or on piles. The dimensions of the reinforced concrete substructures result from the high demands on the permissible deformations of the substructures (Grossert, 2006).

Different types of existing maglev magnetic suspension systems and technical specifications of existing guideways are presented in Table 5. As seen in this table, the majority of the maglev suspension systems are of electromagnetic suspension type. This table shows the most commonly used guideway structures and suspension systems. As indicated in the table, majority of guideway are elevated, double-track and U-shaped. The track gauges and spans are also mostly 2.8 m and 24.8 m, respectively.


Table 5. Guideway structures and suspension systems

In recent years, different designs of guideways have been developed, constructed and tested among which U-girder guideways happens to be the most popular. In Korea, since 1980, prestressed concrete U-girder guideway for straight route applications has been proposed (Jin et al., 2007). In Germany, during 1981-1983, a U-girder guideway was built at the Transrapid Test Facility (TVE) by TRI and was used in the TR07 project (Lever, 1998). This guideway was further optimized and improved during 1984-1986 (Schwindt et al., 2007). An elevated concrete U-girder guideway was installed in TVE in 1995 (Schwindt, 2006). One of the three kinds of girders considered for Colorado Maglev Project (CMP) in the Colorado Department of Transportation (CDOT) is a concrete Ugirder (FTA, 2004).

Maglev 135

alignment is to stipulate the geometry of the guideway's function planes in such a way that the passenger enjoys maximum travel comfort when a vehicle travels on the guideway. Apart from acceleration, however, a consideration of changes in acceleration is also an important aspect of comfort. An exception to this is the track changing equipment, where, on the basis of the beam theory, the transition curve of the turnout position is also in the form of a clothoid in the horizontal plane. When route alignment, including determination of the spatial curve, is carried out, these or other aspects are taken into account, as well as

It is well known that torsion has particular significance on the curved bridges. A box section has a special advantage for a curved guideway because of its high torsion rigidity. A curved steel box girder guideway can provide longer curved spans with fewer supports than would be required for I girders, thereby creating greater cost savings in the substructure. For a given design speed and superelevation, the minimum radius of the circular portion of the horizontal curve may be determined based on either the passenger comfort criteria (lateral acceleration) or the vehicle stability criteria, depending on which criterion results on the

In the Colorado system, the passenger comfort criterion is based on the American Society of Civil Engineers (ASCE) People Mover standards. These standards provide a maximum recommended lateral acceleration on the passenger. The lateral acceleration is a function of the velocity and the radius of curvature. In addition to passenger comfort, the stability of the vehicle itself needs to be considered in the relationship between allowable curve radius and superelevation. Fabrication of the curved guideway sections is not widely discussed in maglev system literature. However, it is a central element of the guideway construction

When the vehicle travels on a straight piece of route, gravity is the most influential load acting on it. If the vehicle has geometrical symmetry and is loaded symmetrically, the gravity load passes through guideway axis of symmetry. When the vehicle travels on the

Ideally, if there is adjustment for superelevation on the curve, loads exerted from vehicle to the guideway are symmetric and loading pattern will not be different from that of a straight route. However, on the curves with insufficient superelevation loading pattern will be different. While the principals of calculating the guideway loading on the curves and the straight routes are basically the same the main differences arise due to insufficient superelevation on the curves. This results in different amount of loads being applied to the guideway for both cases. Eccentricity caused by such effects, makes load on internal and external levitation rails different. It is clear that as a result of eccentricity due to insufficient superelevation the portion of load transmitted from vehicle to each one of the internal and external levitation rails will not be equal. It is vital for the guideway loading calculations to

The most important part in the analysis and design of guideway is structural loading. The loading of the maglev vehicle is an important parameter in the practical application. It is related to the magnetic forces (He et al., 2009). The guideway must carry a dead load due to

technique and can become a major consideration in the guideway cost (FTA, 2004).

curves, the centrifugal force will also be added to this effect.

depict a proper pattern for its loading.

**3.1 Loading** 

the system's characteristics (Schwindt, 2006).

smallest curve radius.

Frequent studies on the technical characteristics of beams shows that the following are among the reasons for frequent use of U-shaped cross-sections in majority of projects (Yaghoubi & Ziari, 2010):


It is geometrically simpler to design railway tracks without horizontal or vertical curves and without longitudinal or lateral inclinations. Practically, this does not happen very often. When tracks have to be laid in mountain ranges, engineers have to design horizontal and vertical curves and axial and lateral slops. While passing through horizontal curves centrifugal forces are added to other forces already present. Centrifugal forces are generated due to curves and tend to push the vehicle further away from the centre of the curve. The centrifugal forces also transmit efforts to the track pillars. In fact these forces are generated in the track and the main components to resist them are the track pillars. If the track or part of it is located in a horizontal curve, the effect of centrifugal forces needs to be included for the calculation proposes. These forces act horizontally and in a direction perpendicular to the tangent to horizontal axis of the track. Normally, track superelevation is added to the guideway to compensate these centrifugal forces. Regarding the structure, presence of centrifugal forces on the horizontal curves disturbs the balance of magnetic forces acting on the guideway. Therefore, it is necessary to make allowance for such effects when analyzing and designing for guideways on the curves. An important effect of introducing centrifugal forces on the horizontal curves is the unsymmetrical distribution of vertical loads on the guideway. This causes different calculation procedures for guideways on the curves compared to the straight routes.

The maglev can easily handle tight curves and steep grades of up to 10 %, resulting in fewer tunnels and other encroachment on the terrain (Siemens AG, 2006). The main task of route

Frequent studies on the technical characteristics of beams shows that the following are among the reasons for frequent use of U-shaped cross-sections in majority of projects








It is geometrically simpler to design railway tracks without horizontal or vertical curves and without longitudinal or lateral inclinations. Practically, this does not happen very often. When tracks have to be laid in mountain ranges, engineers have to design horizontal and vertical curves and axial and lateral slops. While passing through horizontal curves centrifugal forces are added to other forces already present. Centrifugal forces are generated due to curves and tend to push the vehicle further away from the centre of the curve. The centrifugal forces also transmit efforts to the track pillars. In fact these forces are generated in the track and the main components to resist them are the track pillars. If the track or part of it is located in a horizontal curve, the effect of centrifugal forces needs to be included for the calculation proposes. These forces act horizontally and in a direction perpendicular to the tangent to horizontal axis of the track. Normally, track superelevation is added to the guideway to compensate these centrifugal forces. Regarding the structure, presence of centrifugal forces on the horizontal curves disturbs the balance of magnetic forces acting on the guideway. Therefore, it is necessary to make allowance for such effects when analyzing and designing for guideways on the curves. An important effect of introducing centrifugal forces on the horizontal curves is the unsymmetrical distribution of vertical loads on the guideway. This causes different calculation procedures for guideways on the curves

The maglev can easily handle tight curves and steep grades of up to 10 %, resulting in fewer tunnels and other encroachment on the terrain (Siemens AG, 2006). The main task of route


deflections due to vertical loads and possibly allow for higher speeds.

among cross-sections of equal sectional-area, including the I-shaped.

cross-sections including the I-shaped (as an open cross-section).

sections relative to other sections including the I-shaped.

(Yaghoubi & Ziari, 2010):

railroad bridges.

more satisfying.

compared to the straight routes.

strength) are concerned.

would cause another cost hike.

alignment is to stipulate the geometry of the guideway's function planes in such a way that the passenger enjoys maximum travel comfort when a vehicle travels on the guideway. Apart from acceleration, however, a consideration of changes in acceleration is also an important aspect of comfort. An exception to this is the track changing equipment, where, on the basis of the beam theory, the transition curve of the turnout position is also in the form of a clothoid in the horizontal plane. When route alignment, including determination of the spatial curve, is carried out, these or other aspects are taken into account, as well as the system's characteristics (Schwindt, 2006).

It is well known that torsion has particular significance on the curved bridges. A box section has a special advantage for a curved guideway because of its high torsion rigidity. A curved steel box girder guideway can provide longer curved spans with fewer supports than would be required for I girders, thereby creating greater cost savings in the substructure. For a given design speed and superelevation, the minimum radius of the circular portion of the horizontal curve may be determined based on either the passenger comfort criteria (lateral acceleration) or the vehicle stability criteria, depending on which criterion results on the smallest curve radius.

In the Colorado system, the passenger comfort criterion is based on the American Society of Civil Engineers (ASCE) People Mover standards. These standards provide a maximum recommended lateral acceleration on the passenger. The lateral acceleration is a function of the velocity and the radius of curvature. In addition to passenger comfort, the stability of the vehicle itself needs to be considered in the relationship between allowable curve radius and superelevation. Fabrication of the curved guideway sections is not widely discussed in maglev system literature. However, it is a central element of the guideway construction technique and can become a major consideration in the guideway cost (FTA, 2004).

When the vehicle travels on a straight piece of route, gravity is the most influential load acting on it. If the vehicle has geometrical symmetry and is loaded symmetrically, the gravity load passes through guideway axis of symmetry. When the vehicle travels on the curves, the centrifugal force will also be added to this effect.

Ideally, if there is adjustment for superelevation on the curve, loads exerted from vehicle to the guideway are symmetric and loading pattern will not be different from that of a straight route. However, on the curves with insufficient superelevation loading pattern will be different. While the principals of calculating the guideway loading on the curves and the straight routes are basically the same the main differences arise due to insufficient superelevation on the curves. This results in different amount of loads being applied to the guideway for both cases. Eccentricity caused by such effects, makes load on internal and external levitation rails different. It is clear that as a result of eccentricity due to insufficient superelevation the portion of load transmitted from vehicle to each one of the internal and external levitation rails will not be equal. It is vital for the guideway loading calculations to depict a proper pattern for its loading.

### **3.1 Loading**

The most important part in the analysis and design of guideway is structural loading. The loading of the maglev vehicle is an important parameter in the practical application. It is related to the magnetic forces (He et al., 2009). The guideway must carry a dead load due to

Maglev 137

wind forces, the earthquake forces, the centrifugal forces, the impact forces, etc. on the curved route. Lateral magnetic forces due to interaction of the guideway and the guidance magnets ensure the lateral stability of the vehicle. Lateral guidance is provided by the configuration of the vehicle-guideway interface and by the levitation electromagnets. The "horseshoe" configurations of the electromagnet and levitation rails provide strong lateral restoring forces when perturbed from equilibrium (FTA, 2004). Guidance magnets are located on both sides along the entire length of the vehicle to keep the vehicle laterally stable during travel on the guideway. Electronic control systems assure the preset clearance.

The mechanical load at a specific point of the structure depends on its location within the car body, but not on the overall length of the vehicles or the position of the car body within the vehicle set. The interaction forces are the magnetic forces that can be derived from magnetic suspension models. Fig. 6 schematically presents locations for interactions between the vehicle and guideway. In this figure, (a) presents location for interaction between support magnets of the vehicle and the guideway levitation rail; (b) presents location for interaction between guidance magnets of the vehicle and guideway levitation

Static (dead) load on the guideway generally consists of structural weight. It is important to remember that same type of guideway beams are selected for the straight and the curved routes. Even though, they may be selected with different types and shapes for the two types

Vertical loads imposed on maglev guideway can be categorized as dead loads due to the weight of the guideway divided by the length of the span, and live loads due to the interaction between guideway and the vehicle. Table 6 presents dead loads on guideways for some different maglev systems. Also, presented in this table, is the calculated dead loads

Fig. 6. Schematic of Interacting Maglev Vehicle and Guideway

**3.1.1 Lifting magnetic forces (vertical loads)** 

of routes (Jin et al., 2007).

on a railroad bridge.

rail.

its own weight, and live loads including the vehicle loads. To incorporate the dynamic interaction between the guideway and the vehicle, the live load is multiplied by a dynamic amplification factor. Lateral and longitudinal loads including wind and earthquake loads may also need to be considered. The guideway loadings are modeled as dynamic and uniformly distributed magnetic forces to account for the dynamic coupling between the vehicle and the guideway. As maglev vehicle speeds increase to 300-500 km/h, the dynamic interactions between vehicle and guideway become an important problem and will play a dominant role in establishing vehicle suspension requirements. Magnetic forces are generated by the maglev vehicle and cause structural loading that transmits to the guideway. This can happen whilst such a vehicle is stationary or in motion. In order to prevent contact between the vehicle and the guideway and maintain the required gap between them, the system is continuously under Operation Control System (OCS) command.

Some decisive factors for the design of maglev guideways are listed as being constructible, durable, adaptable, reliable, readily maintained, being slim in accordance with urban environment and being light to be constructed more efficiently (Jin et al., 2007; Sandberg et al., 1996a, b). In this regard, one of the main challenges to guideway designers is to produce a structure that will be easily maintainable to the narrow tolerances and precise alignment required for practical high-speed maglev operation, to achieve a structure which is economically and financially justifiable and attractive (Plotkin at al., 1996a ,b). Besides satisfying the above conditions, important parameters in the design of guideway include vertical live loads and its pursuant dynamic amplification factors (DAF), plus deflection due to this load. These parameters constantly govern the design process, and they play a major determining role in the structural optimization of the guideway girder systems.

Vehicle/guideway interaction of the maglev system is an important and complicated problem. It is influenced by the levitation system, guideway structure, vehicle mechanical structure, running speed, etc. So the investigation of it should be launched out in many aspects (Wang et al., 2007). Among the various parameters which affect on design of maglev guideway, dead and live loads, dynamic amplification factor and deflection have major importance. Assessment of deflections due to the vertical loads for guideway beam during operation of maglev vehicle is very important. It is the most influential parameter in design of guideway (Lee et al., 2009).

While there are routine processes for the calculation of the guideway dead loading, there is a need for special treatment in the calculation of its live loads. Live load intensity and its distribution patterns are highly dependent on the structural behavior. According to AREMA (American Railway Engineering and Maintenance-of-Way Association) and UIC (International Union of Railways) regulations live load models for conventional railway track are based on a combination of concentrated and distributed loads. This is compatible with the use of wheels and the behavior of locomotives in conventional trains. In the case of trains with magnetic levitation with no wheels and added complexity of lifting magnetic forces due to support magnets, the analysis is much more complicated.

The forces are of attractive magnetic forces and can be categorized as lifting magnetic forces and lateral magnetic forces. The lateral magnetic forces include the restoring magnetic forces, the impact forces, etc. on the straight route and the restoring magnetic forces, the

its own weight, and live loads including the vehicle loads. To incorporate the dynamic interaction between the guideway and the vehicle, the live load is multiplied by a dynamic amplification factor. Lateral and longitudinal loads including wind and earthquake loads may also need to be considered. The guideway loadings are modeled as dynamic and uniformly distributed magnetic forces to account for the dynamic coupling between the vehicle and the guideway. As maglev vehicle speeds increase to 300-500 km/h, the dynamic interactions between vehicle and guideway become an important problem and will play a dominant role in establishing vehicle suspension requirements. Magnetic forces are generated by the maglev vehicle and cause structural loading that transmits to the guideway. This can happen whilst such a vehicle is stationary or in motion. In order to prevent contact between the vehicle and the guideway and maintain the required gap between them, the system is continuously under Operation Control System (OCS)

Some decisive factors for the design of maglev guideways are listed as being constructible, durable, adaptable, reliable, readily maintained, being slim in accordance with urban environment and being light to be constructed more efficiently (Jin et al., 2007; Sandberg et al., 1996a, b). In this regard, one of the main challenges to guideway designers is to produce a structure that will be easily maintainable to the narrow tolerances and precise alignment required for practical high-speed maglev operation, to achieve a structure which is economically and financially justifiable and attractive (Plotkin at al., 1996a ,b). Besides satisfying the above conditions, important parameters in the design of guideway include vertical live loads and its pursuant dynamic amplification factors (DAF), plus deflection due to this load. These parameters constantly govern the design process, and they play a major

Vehicle/guideway interaction of the maglev system is an important and complicated problem. It is influenced by the levitation system, guideway structure, vehicle mechanical structure, running speed, etc. So the investigation of it should be launched out in many aspects (Wang et al., 2007). Among the various parameters which affect on design of maglev guideway, dead and live loads, dynamic amplification factor and deflection have major importance. Assessment of deflections due to the vertical loads for guideway beam during operation of maglev vehicle is very important. It is the most influential parameter in design

While there are routine processes for the calculation of the guideway dead loading, there is a need for special treatment in the calculation of its live loads. Live load intensity and its distribution patterns are highly dependent on the structural behavior. According to AREMA (American Railway Engineering and Maintenance-of-Way Association) and UIC (International Union of Railways) regulations live load models for conventional railway track are based on a combination of concentrated and distributed loads. This is compatible with the use of wheels and the behavior of locomotives in conventional trains. In the case of trains with magnetic levitation with no wheels and added complexity of lifting magnetic

The forces are of attractive magnetic forces and can be categorized as lifting magnetic forces and lateral magnetic forces. The lateral magnetic forces include the restoring magnetic forces, the impact forces, etc. on the straight route and the restoring magnetic forces, the

determining role in the structural optimization of the guideway girder systems.

forces due to support magnets, the analysis is much more complicated.

command.

of guideway (Lee et al., 2009).

wind forces, the earthquake forces, the centrifugal forces, the impact forces, etc. on the curved route. Lateral magnetic forces due to interaction of the guideway and the guidance magnets ensure the lateral stability of the vehicle. Lateral guidance is provided by the configuration of the vehicle-guideway interface and by the levitation electromagnets. The "horseshoe" configurations of the electromagnet and levitation rails provide strong lateral restoring forces when perturbed from equilibrium (FTA, 2004). Guidance magnets are located on both sides along the entire length of the vehicle to keep the vehicle laterally stable during travel on the guideway. Electronic control systems assure the preset clearance.

The mechanical load at a specific point of the structure depends on its location within the car body, but not on the overall length of the vehicles or the position of the car body within the vehicle set. The interaction forces are the magnetic forces that can be derived from magnetic suspension models. Fig. 6 schematically presents locations for interactions between the vehicle and guideway. In this figure, (a) presents location for interaction between support magnets of the vehicle and the guideway levitation rail; (b) presents location for interaction between guidance magnets of the vehicle and guideway levitation rail.

Fig. 6. Schematic of Interacting Maglev Vehicle and Guideway

Static (dead) load on the guideway generally consists of structural weight. It is important to remember that same type of guideway beams are selected for the straight and the curved routes. Even though, they may be selected with different types and shapes for the two types of routes (Jin et al., 2007).

### **3.1.1 Lifting magnetic forces (vertical loads)**

Vertical loads imposed on maglev guideway can be categorized as dead loads due to the weight of the guideway divided by the length of the span, and live loads due to the interaction between guideway and the vehicle. Table 6 presents dead loads on guideways for some different maglev systems. Also, presented in this table, is the calculated dead loads on a railroad bridge.

Maglev 139

In general, DAF is not a deterministic value and must be estimated through probabilistic methods. The amount of DAF depends on several parameters including the geometry of the

> Maximum Speed (Km/h)



Maximum DAF

Concrete girder: 1.1

Concrete girder: 1.1

guideway such as length of span, type of span (single-span or multi-span), etc.

(m)

Bechtel (Lever, 1998) 24.82 500 1.4 (a)

Germany (Lever, 1998) 24.82 500 1.56 Maglev Transit (Lever, 1998) - - 1.4 Grumman (Lever, 1998) 27 500 1.2

Grumman (Lever, 1998) 27 500 1.36(b) (Dai, 2005) 30 500 1.37

(Yeo et al., 2008; Lee et al., 2009) - 100 1+15/(40+L)

al., 2008) 25 110 Steel girder: 1.15

Linimo, Japan (Yeo et al., 2008) - 100 Steel girder: 1.15

General Atomics (FTA, 2005 a, b) 36 200 1.5 (a) The Bechtel report indicates that this is a conservative value is used to design the girder (Lever,

(b) Calculated using diagrams of static vehicular loading and dynamic vehicular passage over

Table 7. Dynamic Amplification Factor (DAF) for some typical maglev guideways

The amount of live load of some different maglev systems are presented in Table 8.

design is 0.33 (the corresponding dynamic amplification factor is 1.33) (Dai, 2005).

(c) In AASHTO LRFD Bridge Deign Specifications, the dynamic allowance (IM) for highway bridge

(d) With track maintenance to accurate standards and criteria. δ1: For Shear Force and δ2: For Bending

The interaction force (dynamic lifting magnetic force) between the i-th bogie in each car body and the guideway is transferred to two levitation rails. Due to the uniform distribution of the load on the levitation rails, the loading pattern on the guideway spans can be

Items Span Length, L

TR07, Transrapid,

New (corrected)

UTM01, Korea

AASHTO LRFD

(Dai, 2005)

1998).

Moment.

guideway (Lever, 1998).

Urban Maglev, Korea (Yeo et

Bridge Design Specifications

Conventional Railroad Bridge (d)

considered as a uniform distributed load.


(a) single-car maglev

(b) three-car maglev

(c) Consisting of four precast prestressed concrete girders of type 3 AASHTO.

Table 6. Dead loads on some typical maglev guideways

The magnetic force between the guideway and the supporting magnets causes the vehicle to levitate. The maglev guideway live loads consist of both static and dynamic loads. The static live load is the load due to the weight of the vehicle. In this case, the vehicle rests directly on the guideway. When the vehicle rises, an air gap appears between the vehicle and the guideway. The interaction force between the guideway and the i-th bogie in each car body is equal to 1/nb of the total vehicle weight, including the car body (wagon), bogies, magnets and passengers. nb is the number of bogies in each car body.

The movement of the vehicle over the guideway amplifies the static loads. Dynamic amplification factor (DAF) is a non-dimensional ratio of dynamic magnetic force to the static magnetic force. Incorporating a dynamic amplification factor, the dynamic lifting magnetic force between the guideway and the i-th bogie in each car body. DAF is the most influential parameter in design of guideway. The DAF of the guideway girder caused by the maglev vehicle is generally not severe compared with that caused by a traditional railway load, and is not significantly affected by vehicle speed. The effects of the deflection ratio and span continuity on the DAF of the guideway are negligible (Lee et al., 2009). DAF for variety of maglev systems is presented in Table 7. The DAF defined as the ratio of the maximum dynamic to the maximum static response of the guideway under the same load plus one, are used to evaluate the dynamic response of the guideway due to the moving vehicular loads.

(m)

Linimo, Japan (Jin et al., 2007) 30 2.5 7.733 AGT, Korea (Jin et al., 2007) 30 1.92 5.531

KIMM, Korea (Jin et al., 2007) 25 2.06 3.544

The magnetic force between the guideway and the supporting magnets causes the vehicle to levitate. The maglev guideway live loads consist of both static and dynamic loads. The static live load is the load due to the weight of the vehicle. In this case, the vehicle rests directly on the guideway. When the vehicle rises, an air gap appears between the vehicle and the guideway. The interaction force between the guideway and the i-th bogie in each car body is equal to 1/nb of the total vehicle weight, including the car body (wagon), bogies, magnets

The movement of the vehicle over the guideway amplifies the static loads. Dynamic amplification factor (DAF) is a non-dimensional ratio of dynamic magnetic force to the static magnetic force. Incorporating a dynamic amplification factor, the dynamic lifting magnetic force between the guideway and the i-th bogie in each car body. DAF is the most influential parameter in design of guideway. The DAF of the guideway girder caused by the maglev vehicle is generally not severe compared with that caused by a traditional railway load, and is not significantly affected by vehicle speed. The effects of the deflection ratio and span continuity on the DAF of the guideway are negligible (Lee et al., 2009). DAF for variety of maglev systems is presented in Table 7. The DAF defined as the ratio of the maximum dynamic to the maximum static response of the guideway under the same load plus one, are used to evaluate the dynamic response of the guideway due to the moving vehicular loads.

2007) 25 2.20 5.732

2007) 25 1.90 4.256 (Dai, 2005) 30 - 1.5(a), 3.5(b) (Cai, et al., 1996) - - 1.82 Railroad Bridge (c) 18 1.45 14.8

Girder Height (m)

25 1.51 2.948 25 1.99 3.460 25 1.402 2.68 30 1.625 3.10 25 1.515 2.95 30 1.837 3.28 25 1.794 3.16 30 2.183 3.63 25 1.991 3.46 30 2.320 4.05

Dead load (ton/m)

Items Span Length

(c) Consisting of four precast prestressed concrete girders of type 3 AASHTO.

Table 6. Dead loads on some typical maglev guideways

and passengers. nb is the number of bogies in each car body.

Urban Maglev Program, Korea (Jin et al., 2007)

Transrapid, Germany (Jin et al.,

Expo Park Korea, Korea (Jin et al.,

(a) single-car maglev (b) three-car maglev


In general, DAF is not a deterministic value and must be estimated through probabilistic methods. The amount of DAF depends on several parameters including the geometry of the guideway such as length of span, type of span (single-span or multi-span), etc.

(a) The Bechtel report indicates that this is a conservative value is used to design the girder (Lever, 1998).

(b) Calculated using diagrams of static vehicular loading and dynamic vehicular passage over guideway (Lever, 1998).

(c) In AASHTO LRFD Bridge Deign Specifications, the dynamic allowance (IM) for highway bridge design is 0.33 (the corresponding dynamic amplification factor is 1.33) (Dai, 2005).

(d) With track maintenance to accurate standards and criteria. δ1: For Shear Force and δ2: For Bending Moment.

Table 7. Dynamic Amplification Factor (DAF) for some typical maglev guideways

The interaction force (dynamic lifting magnetic force) between the i-th bogie in each car body and the guideway is transferred to two levitation rails. Due to the uniform distribution of the load on the levitation rails, the loading pattern on the guideway spans can be considered as a uniform distributed load.

The amount of live load of some different maglev systems are presented in Table 8.

Maglev 141

force between each bogie in each car body and each of the levitation rails is also uniformly distributed. If bogie lengths in each car body are the same, as normally is the case, then the total interaction force intensity between each car body and the guideway is equal to the interaction force intensity between the i-th bogie in each car body and the guideway over the length of bogie. Also, in such case, the total interaction force intensity between each car body and each of the levitation rails over the length of each car body is equal to the interaction force intensity between the i-th bogie in each car body and each of the levitation rails over the length of each bogie. Each maglev vehicle involves some (one to ten) car bodies with different lengths. Hence, maximum interaction force intensity between car bodies and the guideway can be considered as maglev live load. In general, maglev live loading is evenly and uniformly distributed. The amount of maglev live load is generally less than the dead load of its guideway. Also, the uniformly distributed live load of maglev

In the static case, lateral (guidance) magnetic forces do not exist. However, during vehicle movements and while it moves to the sides, interaction of guidance magnets and levitation rails brings the vehicle back to its central stable position. This causes lateral magnetic forces. These lateral forces act in lateral and normal directions to the levitation rails and transmit to the guideway. When the vehicle deviates to the right, guidance magnets on the right side of horseshoe shaped section of the vehicle and levitation rail on the right side of guideway attract each other while guidance magnets on the left side of horseshoe shaped section of the vehicle and levitation rail on the left side of guideway repulse each other. This brings the vehicle back to its stable position. At the location of interaction between guidance magnets and levitation rails, forces in the left and right zones are of the same size and act on the same

One of the main advantages of the elevated transportation systems such as maglev is the high resistance of their tracks in dealing with the earthquake forces. Earthquake forces are included in the guideway design for Shanghai in China (Dai, 2005) and in Japan. There is no report of major earthquake in central Europe. Therefore, German Transrapid TR07 has ignored such effects, all together (Lever, 1998). Earthquake lateral forces imposed on maglev

Irregular earth movements generate such forces that can be capable of damaging the man made structures. The size of such forces depends on the nature of the earthquake, the natural period for the bridge structural vibrations and the natural period for vibrations of the soil under the foundation. For the design of the exceptional bridges with very large spans or for the bridges that are near the earth's fault lines, calculations for the earthquake forces depend on some detailed studies. One may use the static analysis for the design of small to medium size bridges. Dynamic bridge analysis however, needs huge number of calculations that are economically formidable and sometimes turn to be impossible. On the other hand, the quasi static approach uses a load (or an impact) factor that converts the dynamic loads into the static loads. Therefore, such method assumes static equilibrium when determining the structural behavior. The load (or the impact factor) comes from the

applied to each levitation rail over the length of live loading.

**3.1.2 Lateral magnetic forces (lateral loads)** 

guideway are less than that of the railroad bridges.

experiences, engineering judgment and from mathematical models.

direction to the guideway.


Table 8. Live loads on some typical maglev guideways

In the static position or while maglev vehicle is resting on its guideway, the thickness of the air gap between vehicle and guideway is nil. Therefore, the total load of the vehicle weight will be transmitted to the guideway. As a result, the interaction force (total static lifting magnetic force of each car body) between each car body and the guideway is the static weight of the vehicle. Each car body is equipped with nb bogies. Thus, the total interaction force between each car body and the guideway is the summation of interaction forces (static lifting magnetic forces) between the i-th bogie in each car body and the guideway. Maglev trains achieve a weight reduction in reaching the design speed (FTA, 2004).

As presented in Fig. 3, each guideway includes one beam (girder) and two levitation rails. Therefore, the total interaction force between each car body and each of the levitation rails, is equal to one-half of the total interaction force between each car body and the guideway. In other words, the interaction force between the i-th bogie in each car body and each of the levitation rails, is equal to one-half of the interaction force between the i-th bogie in each car body and the guideway. Dynamic magnetic lifting forces are the forces generated while the vehicle moves. The interaction force (total dynamic lifting magnetic force of each car body) between each car body and the guideway, is the sum of the interaction forces (dynamic lifting magnetic forces) between the i-th bogie in each car body and the guideway. Also, considering the fact that each guideway consists of two levitation rails, the interaction force between the i-th bogie in each car body and each of the levitation rails, is equal to one-half of the interaction force between the i-th bogie in each car body and the guideway. Interaction force between each bogie in each car body and the guideway is a uniformly distributed live load. Load uniformity comes from the absence of the wheels and presence of lifting magnetic forces with uniform intensity that is generated by support magnets. Interaction

Live Load (ton/m)

25 2.3 L/2000 25 2.3 L/4000

Deflection Regulation (m)

25<L : (L/25)1/2×L/1500

(m)

(Yeo et al., 2008) 25 2.6 L/2000 Linimo, Japan (Jin et al., 2007) 30 1.78 L/1500

UTM01, Korea (Yeo et al., 2008) - 2.2 L/4000 AGT, Korea (Jin et al., 2007) 30 - L/1000

2007) 25 2.4 L/4000 KIMM, Korea (Jin et al., 2007) 25 1.86 L/4000

2007) 25 2.5 L/3000 CHSST, Japan (FTA, 2004) 30 2.3 - Colorado, U.S. (FTA, 2004) 30 2.3 -

(Schach et al., 2007) - 2.2 -

trains achieve a weight reduction in reaching the design speed (FTA, 2004).

In the static position or while maglev vehicle is resting on its guideway, the thickness of the air gap between vehicle and guideway is nil. Therefore, the total load of the vehicle weight will be transmitted to the guideway. As a result, the interaction force (total static lifting magnetic force of each car body) between each car body and the guideway is the static weight of the vehicle. Each car body is equipped with nb bogies. Thus, the total interaction force between each car body and the guideway is the summation of interaction forces (static lifting magnetic forces) between the i-th bogie in each car body and the guideway. Maglev

As presented in Fig. 3, each guideway includes one beam (girder) and two levitation rails. Therefore, the total interaction force between each car body and each of the levitation rails, is equal to one-half of the total interaction force between each car body and the guideway. In other words, the interaction force between the i-th bogie in each car body and each of the levitation rails, is equal to one-half of the interaction force between the i-th bogie in each car body and the guideway. Dynamic magnetic lifting forces are the forces generated while the vehicle moves. The interaction force (total dynamic lifting magnetic force of each car body) between each car body and the guideway, is the sum of the interaction forces (dynamic lifting magnetic forces) between the i-th bogie in each car body and the guideway. Also, considering the fact that each guideway consists of two levitation rails, the interaction force between the i-th bogie in each car body and each of the levitation rails, is equal to one-half of the interaction force between the i-th bogie in each car body and the guideway. Interaction force between each bogie in each car body and the guideway is a uniformly distributed live load. Load uniformity comes from the absence of the wheels and presence of lifting magnetic forces with uniform intensity that is generated by support magnets. Interaction

Linimo, Japan (Yeo et al., 2008) - 2.3 20<L ≤ 25m : L/1500

Items Span Length

Urban Maglev Program, Korea

Urban Maglev Program, Korea

Transrapid, Germany (Jin et al.,

Expo Park, Korea (Jin et al.,

TR08, Transrapid, Germany

Table 8. Live loads on some typical maglev guideways

(Jin et al., 2007)

force between each bogie in each car body and each of the levitation rails is also uniformly distributed. If bogie lengths in each car body are the same, as normally is the case, then the total interaction force intensity between each car body and the guideway is equal to the interaction force intensity between the i-th bogie in each car body and the guideway over the length of bogie. Also, in such case, the total interaction force intensity between each car body and each of the levitation rails over the length of each car body is equal to the interaction force intensity between the i-th bogie in each car body and each of the levitation rails over the length of each bogie. Each maglev vehicle involves some (one to ten) car bodies with different lengths. Hence, maximum interaction force intensity between car bodies and the guideway can be considered as maglev live load. In general, maglev live loading is evenly and uniformly distributed. The amount of maglev live load is generally less than the dead load of its guideway. Also, the uniformly distributed live load of maglev applied to each levitation rail over the length of live loading.

### **3.1.2 Lateral magnetic forces (lateral loads)**

In the static case, lateral (guidance) magnetic forces do not exist. However, during vehicle movements and while it moves to the sides, interaction of guidance magnets and levitation rails brings the vehicle back to its central stable position. This causes lateral magnetic forces. These lateral forces act in lateral and normal directions to the levitation rails and transmit to the guideway. When the vehicle deviates to the right, guidance magnets on the right side of horseshoe shaped section of the vehicle and levitation rail on the right side of guideway attract each other while guidance magnets on the left side of horseshoe shaped section of the vehicle and levitation rail on the left side of guideway repulse each other. This brings the vehicle back to its stable position. At the location of interaction between guidance magnets and levitation rails, forces in the left and right zones are of the same size and act on the same direction to the guideway.

One of the main advantages of the elevated transportation systems such as maglev is the high resistance of their tracks in dealing with the earthquake forces. Earthquake forces are included in the guideway design for Shanghai in China (Dai, 2005) and in Japan. There is no report of major earthquake in central Europe. Therefore, German Transrapid TR07 has ignored such effects, all together (Lever, 1998). Earthquake lateral forces imposed on maglev guideway are less than that of the railroad bridges.

Irregular earth movements generate such forces that can be capable of damaging the man made structures. The size of such forces depends on the nature of the earthquake, the natural period for the bridge structural vibrations and the natural period for vibrations of the soil under the foundation. For the design of the exceptional bridges with very large spans or for the bridges that are near the earth's fault lines, calculations for the earthquake forces depend on some detailed studies. One may use the static analysis for the design of small to medium size bridges. Dynamic bridge analysis however, needs huge number of calculations that are economically formidable and sometimes turn to be impossible. On the other hand, the quasi static approach uses a load (or an impact) factor that converts the dynamic loads into the static loads. Therefore, such method assumes static equilibrium when determining the structural behavior. The load (or the impact factor) comes from the experiences, engineering judgment and from mathematical models.

Maglev 143

implies aerodynamic system issues, e.g. that of train induced aerodynamic loads leading to structural vibrations and a decrease of ride comfort. The pressure load caused by passing maglev vehicles has an important aerodynamic effect on the sidewall motion and therefore on the ride comfort (Tielkes, 2006). While two vehicles are passing each other at high relative speed, the quasi-static pressure distribution along each vehicle presents a dynamic load on the other vehicle. The dynamic pressure load strongly depends on the velocity of the oncoming vehicle, the geometry of the bow-part of the oncoming vehicle and the distance between the two tracks. The time behavior is given by the relative velocity between

ii. the relation between the propagation speed of the structural Eigenmode with the corresponding wavelength and the relative velocity between the two vehicles iii. the load at a specific point of the structure depends on its location within the car body, but not on the overall length of the vehicles or the position of the carriage body within

In general, the aerodynamic forces play an important role in affecting the interaction response of maglev-vehicle/guideway system due to their velocity-dependent characteristics, especially for the higher speeds over 600km/h (Yau, 2009). Further development of the ground transport calls for solution variety of problems among which aerodynamic problems are very important. The up-date state of high-speed ground transport problem shows that the use of aerodynamic effects will make it possible to

Longitudinal force can be applied to the guideway through braking and acceleration of the vehicle, vehicle weight when the guideway has a longitudinal slope, and air pressure (aerodynamics). Since maglev vehicles have no wheels, axles and transmission, they weigh less then a conventional railroad train. The lack of wheels also means that there is no friction between the vehicle and the guideway. These factors result in a reduction in energy consumption. Therefore, the vehicle requires a lesser force for braking and stopping it. For example, the attractive force due to braking in the Colorado maglev vehicle equals to 4.2-4.5 ton, which amounts to about 10% of its loaded vehicle mass of 44 ton (FTA, 2004). In conventional rail tracks, brake force is usually equal to 1/7 of the weight of the part of the

During the past four decades, many maglev models have been proposed. In 1974, Katz proposed two simplified one dimensional maglev vehicle and suspension models. A simple two degree-of-freedom (DOF) vehicle system with one car body was used in his study (Katz et al., 1974). In 1993, Cai studied a multi-car vehicle model traversing on a guideway. Concentrated loads and distributed loads were compared. The coupled effects of vehicle and guideway interactions over a wide range of vehicle speeds with various vehicle and guideway parameters were investigated. Only vertical vehicle motion is considered in their

the two vehicles. The mechanical load on the car body depends mainly on:

i. the amplitude of the pressure wave, given by

optimize the technical and economic performances of vehicles.

 the velocity of the oncoming vehicle the bow-shape of the oncoming vehicle the distance between the two tracks

the vehicle set.

train which is located on the bridge.

**3.2 Analysis** 

Guideways must endure the earthquake lateral forces in two perpendicular directions. They need to also transfer the lateral forces to the guideway foundations in both directions. These two directions normally include the guideway longitudinal axis and the direction perpendicular to it. The guideway columns must endure the earthquake forces caused by the guideway weight in addition to enduring the earthquake forces that are related to the columns weight. The later force comes from multiplying the earthquake factor by the weight of the columns. The earthquake factor is the same factor that is also used for the calculation of the earthquake force. For the calculation of the earthquake lateral force, if the size of the live load is less than half of the size of the deal load, the live load will be ignored. Otherwise, two third of the summation of the dead and live loads on the guideway needs to be accounted for. While calculating the earthquake lateral force for urban maglev guideways, at least half of the live load must be included.

Generally, the wind effect depends on the geographical position of the district, its altitude from the sea level, the local topography and to some geometrical characteristics. For the guideway static calculations, regardless from the number of the tracks the wind force affects only one maglev vehicle.

The interaction force (dynamic lateral magnetic force) between the i-th bogie in each car body and each of the levitation rails is defined by the summation of the interaction forces (dynamic lifting magnetic force) between the i-th bogie in each car body and each of the levitation rails and the wind or the earthquake lateral force, whichever that turns to be bigger. The earthquake lateral force also includes a DAF.

Lateral forces on the maglev guideway can be caused by the vehicle sliding, particularly on curves. Lateral guidance is provided by guidance magnets. The dynamic lateral magnetic force imposed on the guideway can be considered as a uniformly distributed load. Centrifugal forces, in equal speed and curve radius, are less in maglev due to lower weight of the vehicle than in rail tracks.

### **3.1.3 Longitudinal loads**

In recent years, with increasing traveling speed of the rail systems, aerodynamic load problems became very important. From the system point of view, aerodynamical topics which affect and define the interface between rolling stock, infrastructure and operation are of paramount importance and the corresponding loads increase with the vehicle speed. If maglev vehicles pass in close proximity to each other or move close to fixed objects such as barriers or buildings, the aerodynamic interactions can produce significant loads on the vehicle or the fixed object. The magnitude and duration of the load depends on the velocity and geometry of the vehicles and also on the ambient wind speed and direction. For highspeed railroads several studies have examined the loads produced by passing trains and their potential for causing an accident. The results of these studies show an important pressure load acting on the object which can have serious consequences. The experiments were carried out on conventional railroad vehicles but from the system point of view, in principle, the aerodynamics of a maglev and a high-speed railroad system do not differ. Although the safety aspect does not concern the maglev vehicle as strongly as it concerns conventional railroads, because maglev is guided by magnets on both sides and cannot derail, many aspects are similar. In both cases, the interaction of vehicles and infrastructure

Guideways must endure the earthquake lateral forces in two perpendicular directions. They need to also transfer the lateral forces to the guideway foundations in both directions. These two directions normally include the guideway longitudinal axis and the direction perpendicular to it. The guideway columns must endure the earthquake forces caused by the guideway weight in addition to enduring the earthquake forces that are related to the columns weight. The later force comes from multiplying the earthquake factor by the weight of the columns. The earthquake factor is the same factor that is also used for the calculation of the earthquake force. For the calculation of the earthquake lateral force, if the size of the live load is less than half of the size of the deal load, the live load will be ignored. Otherwise, two third of the summation of the dead and live loads on the guideway needs to be accounted for. While calculating the earthquake lateral force for urban maglev guideways,

Generally, the wind effect depends on the geographical position of the district, its altitude from the sea level, the local topography and to some geometrical characteristics. For the guideway static calculations, regardless from the number of the tracks the wind force affects

The interaction force (dynamic lateral magnetic force) between the i-th bogie in each car body and each of the levitation rails is defined by the summation of the interaction forces (dynamic lifting magnetic force) between the i-th bogie in each car body and each of the levitation rails and the wind or the earthquake lateral force, whichever that turns to be

Lateral forces on the maglev guideway can be caused by the vehicle sliding, particularly on curves. Lateral guidance is provided by guidance magnets. The dynamic lateral magnetic force imposed on the guideway can be considered as a uniformly distributed load. Centrifugal forces, in equal speed and curve radius, are less in maglev due to lower weight

In recent years, with increasing traveling speed of the rail systems, aerodynamic load problems became very important. From the system point of view, aerodynamical topics which affect and define the interface between rolling stock, infrastructure and operation are of paramount importance and the corresponding loads increase with the vehicle speed. If maglev vehicles pass in close proximity to each other or move close to fixed objects such as barriers or buildings, the aerodynamic interactions can produce significant loads on the vehicle or the fixed object. The magnitude and duration of the load depends on the velocity and geometry of the vehicles and also on the ambient wind speed and direction. For highspeed railroads several studies have examined the loads produced by passing trains and their potential for causing an accident. The results of these studies show an important pressure load acting on the object which can have serious consequences. The experiments were carried out on conventional railroad vehicles but from the system point of view, in principle, the aerodynamics of a maglev and a high-speed railroad system do not differ. Although the safety aspect does not concern the maglev vehicle as strongly as it concerns conventional railroads, because maglev is guided by magnets on both sides and cannot derail, many aspects are similar. In both cases, the interaction of vehicles and infrastructure

at least half of the live load must be included.

bigger. The earthquake lateral force also includes a DAF.

only one maglev vehicle.

of the vehicle than in rail tracks.

**3.1.3 Longitudinal loads** 

implies aerodynamic system issues, e.g. that of train induced aerodynamic loads leading to structural vibrations and a decrease of ride comfort. The pressure load caused by passing maglev vehicles has an important aerodynamic effect on the sidewall motion and therefore on the ride comfort (Tielkes, 2006). While two vehicles are passing each other at high relative speed, the quasi-static pressure distribution along each vehicle presents a dynamic load on the other vehicle. The dynamic pressure load strongly depends on the velocity of the oncoming vehicle, the geometry of the bow-part of the oncoming vehicle and the distance between the two tracks. The time behavior is given by the relative velocity between the two vehicles. The mechanical load on the car body depends mainly on:


In general, the aerodynamic forces play an important role in affecting the interaction response of maglev-vehicle/guideway system due to their velocity-dependent characteristics, especially for the higher speeds over 600km/h (Yau, 2009). Further development of the ground transport calls for solution variety of problems among which aerodynamic problems are very important. The up-date state of high-speed ground transport problem shows that the use of aerodynamic effects will make it possible to optimize the technical and economic performances of vehicles.

Longitudinal force can be applied to the guideway through braking and acceleration of the vehicle, vehicle weight when the guideway has a longitudinal slope, and air pressure (aerodynamics). Since maglev vehicles have no wheels, axles and transmission, they weigh less then a conventional railroad train. The lack of wheels also means that there is no friction between the vehicle and the guideway. These factors result in a reduction in energy consumption. Therefore, the vehicle requires a lesser force for braking and stopping it. For example, the attractive force due to braking in the Colorado maglev vehicle equals to 4.2-4.5 ton, which amounts to about 10% of its loaded vehicle mass of 44 ton (FTA, 2004). In conventional rail tracks, brake force is usually equal to 1/7 of the weight of the part of the train which is located on the bridge.

#### **3.2 Analysis**

During the past four decades, many maglev models have been proposed. In 1974, Katz proposed two simplified one dimensional maglev vehicle and suspension models. A simple two degree-of-freedom (DOF) vehicle system with one car body was used in his study (Katz et al., 1974). In 1993, Cai studied a multi-car vehicle model traversing on a guideway. Concentrated loads and distributed loads were compared. The coupled effects of vehicle and guideway interactions over a wide range of vehicle speeds with various vehicle and guideway parameters were investigated. Only vertical vehicle motion is considered in their

Maglev 145

suspension for maglev vehicle. The primary suspension consists of two to eight

Magnetic levitation is caused by magnetic forces that transmit to guideway by maglev vehicle. In fact, these forces are the consequence of interactions between vehicle and guideway caused by magnets. For EMS systems, these magnets are installed within the vehicle. The forces are of attractive magnetic forces. Lifting magnetic forces due to interaction of guideway and support magnets cause the levitation of the vehicle. Support magnets are located on both sides along the entire length of the vehicle. The attractive force produces inherently unstable vehicle support because the attractive force increases as the

The interaction forces are the magnetic forces that can be derived from magnetic suspension models. Static load on guideway generally consists of the vehcile weight. In either case, the dead load is uniformly distributed along the full length of the beam. Calculations of live load need more attention. Dynamic lifting forces are derived from static lifting forces. Therefore, accuracy of these models is vital to the accuracy of live load models. Combination of these models plus the live load models leads to the analysis and design of guideway. In static position or while maglev vehicle is resting on its guideway, thickness of the air gap between vehicle and guideway is nil. Therefore, total load of vehicle weight will be transmitted to the guideway. As a result, the interaction force (total static lifting magnetic force of each car body) between each car body and the guideway is the static weight of the vehicle. Each car body is equipped with nb bogies. Thus, the total interaction force is summation of interaction forces (static lifting magnetic forces) between the i-th bogie in each car body and the guideway. Interaction force (dynamic lifting magnetic force) between each bogie in each car body and the guideway is a uniformly distributed live load. Load uniformity comes from absence of the wheels and presence of lifting magnetic forces with uniform intensity that is generated by support magnets. Maglev live loading is evenly and uniformly distributed. Amount of maglev live load is generally less than dead load of its

These forces transfer to the guideway while the vehicle is stopped or when it moves. Each car body model can be considered as a uniform rigid mass. It is supported by two to eight springs and two to eight dashpots that form the secondary suspension for maglev vehicle. The primary suspension consists of two to eight magnetically supported bogies. The electromagnets are mounted on the rigid bogies and generate attractive magnetic forces while interacting with ferromagnetic stator packs. Connections between magnets and bogies are assumed to be rigid. Two dimensional motions of the vehicle include heave motion and rotational motion. Maglev vehicle can be single-car or multiple-car. For example, a singlecar vehicle with four bogies has 6 DOF including one translational and one rotational displacement at the center of mass of the car body, and one translational displacement for each of the four bogies. By the same token, a three-car vehicle with four bogies in each car body has 18 DOF. A dynamic simulation for maglev vehicle/guideway interaction is

A variety of these parameters are presented in Table 9 for different types of maglev

magnetically supported bogies. Maglev vehicle can be single-car or multiple-car.

vehicle/guideway gap decreases.

essential to optimize the vehicle design.

guideway.

systems.

study. A beam model with a uniform-cross-section was used. They found that a distributed load vehicle model was better than a concentrated load vehicle model which might result in vehicle accelerations in simulations. They concluded that multi-car vehicles had less car body acceleration than a single-car vehicle, because of the inter-car vertical constraints. However, a magnetic suspension model is not included in their study. The interface between the vehicle and the beam was modeled with an elastic spring and dashpot, which is not the case in a real maglev system (Cai et al., 1996). In 1995, Nagurka and Wang developed a dynamic maglev model which includes a five DOF vehicle model. The effects of the vehicle speed on the system performance were studied (Nagurka et al., 1997). In 2005, Huiguang Dai influenced by German TR08 maglev, defined a vehicle model, a magnetic suspension model and a beam roughness model. He studied dynamics of a single-car vehicle model with 4 bogies and a three-car vehicle model with 12 bogies. He used an elevated guideway with multiple concentrated moving loads. A total number of 500 simulations were performed to study the dynamic behavior of maglev vehicle and guideway beam (Dai, 2005).

Although extensive simulations and analyses have been performed, the development of design criteria for maglev guideways will require additional studies. Aerodynamic forces must be considered. Effects of horizontal curves should be considered. Maglev trains may be extended to 4 or more cars (Dai, 2005). Maglev vehicle/guideway interaction problem bothers the investigators and engineers for years. No well-accepted interpretation has been reported, yet. Vehicle/guideway interaction of the maglev system is an important and complicated problem. It is influenced by the levitation system, guideway structure, vehicle mechanical structure, running speed, etc. So the investigation of it should be launched out in many aspects (Wang et al., 2007).

During the past four decades, research and development have been performed in the areas of magnetic levitation, interaction of vehicle with guideway, and optimization of vehicle suspensions. The results of these efforts are useful in providing appropriate criteria for the design of maglev systems. The dynamic response of magnetically levitated vehicles is important because of safety, ride quality and system cost. As maglev vehicle speeds increase to 300-500km/h the dynamic interactions between vehicle and guideway become an important problem and will play a dominant role in establishing vehicle suspension requirements. Different dynamic responses of coupled vehicle/guideway systems may be observed, including periodic oscillation, random vibration, dynamic instability, chaotic motion, parametric resonance, combination resonance, and transient response. To design a proper vehicle model that provides acceptable ride quality, the dynamic interaction of vehicles and guideways must be understood. The coupled vehicle/guideway dynamics are the link between the guideway and the other maglev components. Thus, reliable analytical and simulation techniques are needed in the design of vehicle/guideway systems. Furthermore, a coupled vehicle/guideway dynamic model with multiple cars must be developed to meet system design requirements.

For a dynamic analysis of vehicle/guideway interactions, an understanding of the effects of distributed loads is essential. The maglev vehicle is the source of magnetic forces and loading starts from this vehicle. These forces transfer to the guideway while the vehicle is stopped or when it moves. Each car body model can be considered as a uniform rigid mass. It is supported by two to eight springs and two to eight dashpots that form the secondary

study. A beam model with a uniform-cross-section was used. They found that a distributed load vehicle model was better than a concentrated load vehicle model which might result in vehicle accelerations in simulations. They concluded that multi-car vehicles had less car body acceleration than a single-car vehicle, because of the inter-car vertical constraints. However, a magnetic suspension model is not included in their study. The interface between the vehicle and the beam was modeled with an elastic spring and dashpot, which is not the case in a real maglev system (Cai et al., 1996). In 1995, Nagurka and Wang developed a dynamic maglev model which includes a five DOF vehicle model. The effects of the vehicle speed on the system performance were studied (Nagurka et al., 1997). In 2005, Huiguang Dai influenced by German TR08 maglev, defined a vehicle model, a magnetic suspension model and a beam roughness model. He studied dynamics of a single-car vehicle model with 4 bogies and a three-car vehicle model with 12 bogies. He used an elevated guideway with multiple concentrated moving loads. A total number of 500 simulations were performed to study the dynamic behavior of maglev vehicle and

Although extensive simulations and analyses have been performed, the development of design criteria for maglev guideways will require additional studies. Aerodynamic forces must be considered. Effects of horizontal curves should be considered. Maglev trains may be extended to 4 or more cars (Dai, 2005). Maglev vehicle/guideway interaction problem bothers the investigators and engineers for years. No well-accepted interpretation has been reported, yet. Vehicle/guideway interaction of the maglev system is an important and complicated problem. It is influenced by the levitation system, guideway structure, vehicle mechanical structure, running speed, etc. So the investigation of it should be launched out in

During the past four decades, research and development have been performed in the areas of magnetic levitation, interaction of vehicle with guideway, and optimization of vehicle suspensions. The results of these efforts are useful in providing appropriate criteria for the design of maglev systems. The dynamic response of magnetically levitated vehicles is important because of safety, ride quality and system cost. As maglev vehicle speeds increase to 300-500km/h the dynamic interactions between vehicle and guideway become an important problem and will play a dominant role in establishing vehicle suspension requirements. Different dynamic responses of coupled vehicle/guideway systems may be observed, including periodic oscillation, random vibration, dynamic instability, chaotic motion, parametric resonance, combination resonance, and transient response. To design a proper vehicle model that provides acceptable ride quality, the dynamic interaction of vehicles and guideways must be understood. The coupled vehicle/guideway dynamics are the link between the guideway and the other maglev components. Thus, reliable analytical and simulation techniques are needed in the design of vehicle/guideway systems. Furthermore, a coupled vehicle/guideway dynamic model with multiple cars must be

For a dynamic analysis of vehicle/guideway interactions, an understanding of the effects of distributed loads is essential. The maglev vehicle is the source of magnetic forces and loading starts from this vehicle. These forces transfer to the guideway while the vehicle is stopped or when it moves. Each car body model can be considered as a uniform rigid mass. It is supported by two to eight springs and two to eight dashpots that form the secondary

guideway beam (Dai, 2005).

many aspects (Wang et al., 2007).

developed to meet system design requirements.

suspension for maglev vehicle. The primary suspension consists of two to eight magnetically supported bogies. Maglev vehicle can be single-car or multiple-car.

Magnetic levitation is caused by magnetic forces that transmit to guideway by maglev vehicle. In fact, these forces are the consequence of interactions between vehicle and guideway caused by magnets. For EMS systems, these magnets are installed within the vehicle. The forces are of attractive magnetic forces. Lifting magnetic forces due to interaction of guideway and support magnets cause the levitation of the vehicle. Support magnets are located on both sides along the entire length of the vehicle. The attractive force produces inherently unstable vehicle support because the attractive force increases as the vehicle/guideway gap decreases.

The interaction forces are the magnetic forces that can be derived from magnetic suspension models. Static load on guideway generally consists of the vehcile weight. In either case, the dead load is uniformly distributed along the full length of the beam. Calculations of live load need more attention. Dynamic lifting forces are derived from static lifting forces. Therefore, accuracy of these models is vital to the accuracy of live load models. Combination of these models plus the live load models leads to the analysis and design of guideway. In static position or while maglev vehicle is resting on its guideway, thickness of the air gap between vehicle and guideway is nil. Therefore, total load of vehicle weight will be transmitted to the guideway. As a result, the interaction force (total static lifting magnetic force of each car body) between each car body and the guideway is the static weight of the vehicle. Each car body is equipped with nb bogies. Thus, the total interaction force is summation of interaction forces (static lifting magnetic forces) between the i-th bogie in each car body and the guideway. Interaction force (dynamic lifting magnetic force) between each bogie in each car body and the guideway is a uniformly distributed live load. Load uniformity comes from absence of the wheels and presence of lifting magnetic forces with uniform intensity that is generated by support magnets. Maglev live loading is evenly and uniformly distributed. Amount of maglev live load is generally less than dead load of its guideway.

These forces transfer to the guideway while the vehicle is stopped or when it moves. Each car body model can be considered as a uniform rigid mass. It is supported by two to eight springs and two to eight dashpots that form the secondary suspension for maglev vehicle. The primary suspension consists of two to eight magnetically supported bogies. The electromagnets are mounted on the rigid bogies and generate attractive magnetic forces while interacting with ferromagnetic stator packs. Connections between magnets and bogies are assumed to be rigid. Two dimensional motions of the vehicle include heave motion and rotational motion. Maglev vehicle can be single-car or multiple-car. For example, a singlecar vehicle with four bogies has 6 DOF including one translational and one rotational displacement at the center of mass of the car body, and one translational displacement for each of the four bogies. By the same token, a three-car vehicle with four bogies in each car body has 18 DOF. A dynamic simulation for maglev vehicle/guideway interaction is essential to optimize the vehicle design.

A variety of these parameters are presented in Table 9 for different types of maglev systems.

Maglev 147

Till now, variety of design methods has already been used. The Allowable Stress Method was used for design of GA maglev system foundations in U.S (FTA, 2005b) and the Urban Maglev Program in Korea (Jin et al., 2007). The AASHTO Standard Specifications for Highway Bridges were used for design of the Colorado maglev system in U.S (FTA, 2004), the maglev system of GA in U.S (FTA, 2005b) and Transrapid TR08 maglev system in German (Dai, 2005). The AREMA Standard Specifications were used for design of the tensile stress in prestressed concrete for the maglev systems of Colorado in U.S and CHSST in Japan (FTA, 2004). The Service Load Design Method was used for preliminary design of the Colorado special guideway to obtain a reasonable proportioning of members and for

The maximum allowable total deformation of the guideway can come from the settlements caused by consolidation or creep, by dead load, by cyclic loads from the vehicles or by dynamic loads during operation. Due to the importance of the geometry deviation in the serviceability and safety of the maglev guideway, tighter control over the deflection due to live load is required. In other words, there should be very strict limit adopted for the deflection in order to provide the required serviceability and safe parathion. Main contributors to guideway beam deflection is its' live load. Deflection due to dead load of guideway beam is usually very small and time-dependant. The maglev systems of CHSST

Lower deflection in guideway brings the possibility of reaching at higher speeds of travel. Structural continuity, reduction in span length, reductions in live load and DAF, load combinations, much concrete characteristics compressive strength, use of prestressed concrete, section modulus and etc. are among effective factors in the reduction of the deflection due to the live load. In general, utilization of prestressed concrete, increase of required concrete compressive strength and modules of elasticity reduces guideway beam

Structural continuity reduces live load and dead load deflections and possibly allow for higher speeds. Deformations due to creep and joint bearing costs also reduce with the use of structural continuity. Over time, precast girders get considerable variation in cambers and early creeps, but very little time deflection after continuity and composite behavior is achieved. The design with AREMA specifications results in the relatively high live load to total load ratio combined in comparison to other load combinations (because of the high effect of this type of load). It should be noted that this loading combination in comparison to other regulations consist of the highest load factors (LF), and at the same time the current regulation scheme with the use of the allowed tensile stresses applies a more accurate

Parameter Description Unit Compressive strength at initial prestressing 0.8fck MPa Compressive strength just after prestressing 0.55fci' MPa Tensile strength just after prestressing 0.75√fci' MPa Compressive strength under design load 0.4fci' MPa Tensile strength under design load 1.50√fci' MPa

Table 10. Allowable stresses of concrete guideway girder

estimating material quantities (FTA, 2004).

and Colorado are no exceptions (FTA, 2002, 2004).

control over the deflection due to live load (FTA, 2004).

deflection.


Table 9. Parameters of some maglev vehicles

### **3.3 Design**

Guideways are designed and constructed with concrete or steel girders. Concrete guideway girders can be as reinforced or prestressed. Guideway girder is evaluated for different load cases. As example, the Shanghai guideway girder was evaluated with respect to as many as 14,000 load cases by consideration of the deflection, dynamic strength and thermal expansion. The guideway girder for Urban Maglev Program in Korea was also evaluated for five load cases that are combinations of the dead load, live load and the prestressing forces of the tendon (Jin et al., 2007).

Guideways are usually made as single-span or two-span elevated or at-grade. But for larger spans the use of continuous two span supports is recommended. This can reduce deflection and the effect of temperature variations (FTA, 2004). Guideways are modeled as a single or multi span beam with uniformly distributed dead and live loads. Analyses are aimed at obtaining maximum stresses and deflections in guideway spans. The design criteria have deflection regulation on live load and concrete strength condition on top and bottom ends of the girder. The design criteria of the maglev guideway can be summarized as the deflection regulations due to live load in the sense of serviceability and the stresses limits of the girder due to the combination of the dead load and live load. Any classical beam analysis or finite element methods can be adapted in order to obtain maximum stresses and deflections of the beams. Design methods of guideway beam should satisfy the design criteria regarding loading conditions (live load and dead load) and deflection conditions due to live load. The stresses are controlled according to regulations such as AREMA or AASHTO specifications. As example (Jin et al., 2007), the allowable stresses for prestressed concrete compressive strength fck are described in Table 10.

Colorado, U.S. (FTA, 2002, 2004)

CHSST, Japan (FTA, 2002, 2004)

HSST-100L, Japan (FTA, 2005b)

(Dai, 2005)

Shanghai, China (Guangwei et al., 2007)

146 Infrastructure Design, Signalling and Security in Railway

TR08, German (Schach et al., 2007)

1 3 1 1 5 5 2 3 2 2

13 13.7 18 25 24.8 24.8 15 24 24.38 24.38

2 2 2 8 4 4 5 4 5 5

Guideways are designed and constructed with concrete or steel girders. Concrete guideway girders can be as reinforced or prestressed. Guideway girder is evaluated for different load cases. As example, the Shanghai guideway girder was evaluated with respect to as many as 14,000 load cases by consideration of the deflection, dynamic strength and thermal expansion. The guideway girder for Urban Maglev Program in Korea was also evaluated for five load cases that are combinations of the dead load, live load and the prestressing forces

Guideways are usually made as single-span or two-span elevated or at-grade. But for larger spans the use of continuous two span supports is recommended. This can reduce deflection and the effect of temperature variations (FTA, 2004). Guideways are modeled as a single or multi span beam with uniformly distributed dead and live loads. Analyses are aimed at obtaining maximum stresses and deflections in guideway spans. The design criteria have deflection regulation on live load and concrete strength condition on top and bottom ends of the girder. The design criteria of the maglev guideway can be summarized as the deflection regulations due to live load in the sense of serviceability and the stresses limits of the girder due to the combination of the dead load and live load. Any classical beam analysis or finite element methods can be adapted in order to obtain maximum stresses and deflections of the beams. Design methods of guideway beam should satisfy the design criteria regarding loading conditions (live load and dead load) and deflection conditions due to live load. The stresses are controlled according to regulations such as AREMA or AASHTO specifications. As example (Jin et al., 2007), the allowable stresses for prestressed concrete compressive

(Cai et al., 1996)

(Wang et al., 1997)

Old Dominion Uni. (ODU), U.S. (FTA, 2005)

Table 9. Parameters of some maglev vehicles

of the tendon (Jin et al., 2007).

strength fck are described in Table 10.

General Atomics (GA), U.S. (FTA, 2005a, b)

Maglev System/ Model

Number of car body in the vehicle

Length of each car body, in meters

Number of bogies in each car body

**3.3 Design** 


Table 10. Allowable stresses of concrete guideway girder

Till now, variety of design methods has already been used. The Allowable Stress Method was used for design of GA maglev system foundations in U.S (FTA, 2005b) and the Urban Maglev Program in Korea (Jin et al., 2007). The AASHTO Standard Specifications for Highway Bridges were used for design of the Colorado maglev system in U.S (FTA, 2004), the maglev system of GA in U.S (FTA, 2005b) and Transrapid TR08 maglev system in German (Dai, 2005). The AREMA Standard Specifications were used for design of the tensile stress in prestressed concrete for the maglev systems of Colorado in U.S and CHSST in Japan (FTA, 2004). The Service Load Design Method was used for preliminary design of the Colorado special guideway to obtain a reasonable proportioning of members and for estimating material quantities (FTA, 2004).

The maximum allowable total deformation of the guideway can come from the settlements caused by consolidation or creep, by dead load, by cyclic loads from the vehicles or by dynamic loads during operation. Due to the importance of the geometry deviation in the serviceability and safety of the maglev guideway, tighter control over the deflection due to live load is required. In other words, there should be very strict limit adopted for the deflection in order to provide the required serviceability and safe parathion. Main contributors to guideway beam deflection is its' live load. Deflection due to dead load of guideway beam is usually very small and time-dependant. The maglev systems of CHSST and Colorado are no exceptions (FTA, 2002, 2004).

Lower deflection in guideway brings the possibility of reaching at higher speeds of travel. Structural continuity, reduction in span length, reductions in live load and DAF, load combinations, much concrete characteristics compressive strength, use of prestressed concrete, section modulus and etc. are among effective factors in the reduction of the deflection due to the live load. In general, utilization of prestressed concrete, increase of required concrete compressive strength and modules of elasticity reduces guideway beam deflection.

Structural continuity reduces live load and dead load deflections and possibly allow for higher speeds. Deformations due to creep and joint bearing costs also reduce with the use of structural continuity. Over time, precast girders get considerable variation in cambers and early creeps, but very little time deflection after continuity and composite behavior is achieved. The design with AREMA specifications results in the relatively high live load to total load ratio combined in comparison to other load combinations (because of the high effect of this type of load). It should be noted that this loading combination in comparison to other regulations consist of the highest load factors (LF), and at the same time the current regulation scheme with the use of the allowed tensile stresses applies a more accurate control over the deflection due to live load (FTA, 2004).

Maglev 149

Stations have emerged as a new central place in metropolitan cities and have become hub of networks due to their high accessibility by different modes of transport in high scale level. Furthermore, they produce movements which offer sufficient opportunity for the development of commercial land use. Railway stations entered a new age again in the late 20th century after the introduction of high-speed trains. Stations play a very important and influential role in the maglev transport system. The efficacy of the maglev system over the national and regional development depends on the stations. The development hub of

Transportation facilities are both collectors and distributors. The overall goal of these transit stations is to collect and distribute as many passengers as possible with a minimum amount of confusion and inconvenience. Stations should have the capacity to accommodate large concentrations of passengers at various times throughout the day. The stations activities consist of everything from passenger service to the maintenance of the building. It is important to provide the traveler with a pleasant experience and atmosphere that will hopefully lead to repeat business in the future. The station should be able to provide for all of the modern conveniences to better serve the employees as well as the weary travelers. The important idea is to be able to get the people to their next destination as quickly as possible, and if a wait happens to occur then the station should be equipped to

Maglev stations are key regional transportation facilities designed to provide access for high volumes of passengers. The Maglev stations will provide regional and local intermodal connections, as well as national and international connections to passenger facilities. The aesthetic features of the stations are intended to reflect the intrinsic values of the Maglev system: advanced technology, movement, and speed. The conceptual design calls for open-

Fundamentally, a maglev station is equivalent in planning, design, and operation to an inter-city or commuter railroad station. There is only one technical aspect of maglev that constrains station design: unlike railroad tracks, the maglev guideway cannot be crossed by passengers and vehicles at grade. As a result, maglev station designs must provide gradeseparated passenger access to the station platforms. This form of access requires "vertical circulation" (stairs, elevators, escalators) to connect the platforms with tunnels under or bridges over the tracks. Stations should provide the proper functions of typical transit stations, including platforms, Shelter, Vertical and Horizontal circulation, Amenities and Services, Climate controlled waiting room, Public restrooms, Snack service, Public telephones, Changeable message display, Safety. All the station designs are planned to be consistent with the character of the buildings in the area of operation or predicated on the community standards of the local area where each station is located. The station must support the safe movement of passengers at specified flow rates and must also support particular levels of vehicle traffic. Based on the patron markets the following elements, features, and design standards should be common to all maglev system stations, regardless of location or patronage volumes. The expression of these standards will vary and

**4. Station** 

maglev system mainly formed around stations.

accommodate the passengers' needs (Stone, 1994).

air stations with natural light and ventilation.

additional features may be added, depending on station location.

Up till now, different proposed regulations for deflection ratios due to live load such as L/500, L/1000, L/1500, L/1750, L/2000, L/2500, L/3000, and L/4000 have been proposed. In the Transrapid maglev systems generally beams are designed for the deflection ratios due to live load of L/4000 which is the optimum in design terms and in terms of economic efficiency (Jin et al., 2007; Lever, 1998; Schwindt, 2006). The allowable deflection ratios due to live load of some different maglev systems, a high-speed railway and conventional railroad bridges are presented in Table 11 where L is the span length.


(a) Structural optimization results of Korea guideway girder systems

(b) Two types of proposed U-type girder systems for Urban Maglev Program in Korea (Jin et al., 2007)

(c) A proposed U-type girder system for Urban Maglev Program in Korea (Yeo et al., 2008).

(d) The French Train a Grand Vitesse (a high-speed railway train)

Table 11. Allowable deflection due to live load for some typical maglev systems

Up till now, different proposed regulations for deflection ratios due to live load such as L/500, L/1000, L/1500, L/1750, L/2000, L/2500, L/3000, and L/4000 have been proposed. In the Transrapid maglev systems generally beams are designed for the deflection ratios due to live load of L/4000 which is the optimum in design terms and in terms of economic efficiency (Jin et al., 2007; Lever, 1998; Schwindt, 2006). The allowable deflection ratios due to live load of some different maglev systems, a high-speed railway and conventional

Items Span Length (m) Dynamic Deflection

A Proposed Girder(c) (Yeo et al., 2008) 25 L/2000 Linimo, Japan (Jin et al., 2007) 30 L/1500

AGT, Korea (Jin et al., 2007) 30 L/1000 Transrapid, Germany (Jin et al., 2007) 25 L/4000 KIMM, Korea (Jin et al., 2007) 25 L/4000 Expo Park, Korea (Jin et al., 2007) 25 L/3000 UTM01, Korea (Yeo et al., 2008) - L/4000 TGV(d) -Atlantique (Lever, 1998) - L/4000 TR07 (Lever, 1998) 25 L/4000 Bechtel (Lever, 1998) 25 L/2500 Foster-Miller (Lever, 1998) 27 L/2300 Grumman (Lever, 1998) 27 L/2500 Magneplane (Lever, 1998) 9.1 L/2000 Colorado, U.S. (FTA, 2004) 30 L/1750 CHSST, Japan (FTA, 2004) 30 L/1750 (Dai, 2005) 30 L/4000 Railroad Bridge - L/800

(a) Structural optimization results of Korea guideway girder systems

(d) The French Train a Grand Vitesse (a high-speed railway train)

Linimo, Japan (Yeo et al., 2008) - 20<L ≤ 25m : L/1500

(b) Two types of proposed U-type girder systems for Urban Maglev Program in Korea (Jin et al., 2007)

(c) A proposed U-type girder system for Urban Maglev Program in Korea (Yeo et al., 2008).

Table 11. Allowable deflection due to live load for some typical maglev systems

Regulation (m)

25<L : (L/25)1/2×L/1500

25 L/1500 30 L/1500 25 L/2000 30 L/2000 25 L/3000 30 L/3000 25 L/4000 30 L/4000

25 L/2000 25 L/4000

railroad bridges are presented in Table 11 where L is the span length.

Korea(a) (Jin et al., 2007)

Proposed Girders(b) (Jin et al., 2007)

### **4. Station**

Stations have emerged as a new central place in metropolitan cities and have become hub of networks due to their high accessibility by different modes of transport in high scale level. Furthermore, they produce movements which offer sufficient opportunity for the development of commercial land use. Railway stations entered a new age again in the late 20th century after the introduction of high-speed trains. Stations play a very important and influential role in the maglev transport system. The efficacy of the maglev system over the national and regional development depends on the stations. The development hub of maglev system mainly formed around stations.

Transportation facilities are both collectors and distributors. The overall goal of these transit stations is to collect and distribute as many passengers as possible with a minimum amount of confusion and inconvenience. Stations should have the capacity to accommodate large concentrations of passengers at various times throughout the day. The stations activities consist of everything from passenger service to the maintenance of the building. It is important to provide the traveler with a pleasant experience and atmosphere that will hopefully lead to repeat business in the future. The station should be able to provide for all of the modern conveniences to better serve the employees as well as the weary travelers. The important idea is to be able to get the people to their next destination as quickly as possible, and if a wait happens to occur then the station should be equipped to accommodate the passengers' needs (Stone, 1994).

Maglev stations are key regional transportation facilities designed to provide access for high volumes of passengers. The Maglev stations will provide regional and local intermodal connections, as well as national and international connections to passenger facilities. The aesthetic features of the stations are intended to reflect the intrinsic values of the Maglev system: advanced technology, movement, and speed. The conceptual design calls for openair stations with natural light and ventilation.

Fundamentally, a maglev station is equivalent in planning, design, and operation to an inter-city or commuter railroad station. There is only one technical aspect of maglev that constrains station design: unlike railroad tracks, the maglev guideway cannot be crossed by passengers and vehicles at grade. As a result, maglev station designs must provide gradeseparated passenger access to the station platforms. This form of access requires "vertical circulation" (stairs, elevators, escalators) to connect the platforms with tunnels under or bridges over the tracks. Stations should provide the proper functions of typical transit stations, including platforms, Shelter, Vertical and Horizontal circulation, Amenities and Services, Climate controlled waiting room, Public restrooms, Snack service, Public telephones, Changeable message display, Safety. All the station designs are planned to be consistent with the character of the buildings in the area of operation or predicated on the community standards of the local area where each station is located. The station must support the safe movement of passengers at specified flow rates and must also support particular levels of vehicle traffic. Based on the patron markets the following elements, features, and design standards should be common to all maglev system stations, regardless of location or patronage volumes. The expression of these standards will vary and additional features may be added, depending on station location.

Maglev 151

Platforms will be elevated, allowing direct access through train doors without steps or ramps. No free passenger access to the guideway will be permitted, for safety reasons. This is mandatory due to the speed and low noise profile of maglev systems. The use of docks and in-station transfer switches means that passing trains, while not necessarily in close proximity to platforms, could injure anyone who strayed into the active main guideway. For vertical circulation all maglev system stations will provide escalators and elevators as the

The station services, including public rest rooms, snack service, newsstand, staffed ticketing and information center, and public telephones should be provided. Stations should also provide facilities (shops, changing rooms, luggage storage, etc.), access to traveler services such as station cars, and advertising displays. All stations would feature public art appropriate to their locations. Public art is an excellent adjunct to station design and a popular feature. Train and station operations require the station personnel and security. Station managers and ticket agents control the station activities, providing passenger assistance and information as well as inspecting train sets when in station. Armed security personnel are provided at every station. Large stations have multiple security personnel,

The most important task or essential aim when designing the alignment is to specify the geometry of the guideway's functional planes so that the passenger traveling in the vehicle on the guideway experiences optimum comfort during the journey. The geometry defines the limit values for accelerations in the three spatial directions (X, Y, and Z direction). However, apart from the acceleration, the consideration of the change in acceleration (jerk) is also an important aspect for comfort. Therefore, various mathematical formulae were

An exception are the track switching devices which, based on beam theory, are also designed using clothoids for the horizontal transition curves in the turn-out position. The alignment is designed and the space curve established taking into consideration the aspects

primary elements and stairs as the backup.

and parking garages are policed (FTA, 2004).

discussed for the transition curves and lengths, with the result,

the vertical transition curves are designed as clothoids.

given above as well as the system characteristics, e.g.

location of the track switching devices and for the

climbing capability up to 10% and

geometry of each individual beam,

 specifying the substructures, height of the columns,

cant (superelevation) in curves up to 12%.

the horizontal transition curves are designed as sinusoidal curves and

The space curve data are used in the next design phase as the design criteria for

precise location of the functional components on the beam (Schwindt et al., 2004).

**5. Operation 5.1 Performance** 

Fig. 7. Maglev station equipment

Fig. 7. Maglev station equipment

Platforms will be elevated, allowing direct access through train doors without steps or ramps. No free passenger access to the guideway will be permitted, for safety reasons. This is mandatory due to the speed and low noise profile of maglev systems. The use of docks and in-station transfer switches means that passing trains, while not necessarily in close proximity to platforms, could injure anyone who strayed into the active main guideway. For vertical circulation all maglev system stations will provide escalators and elevators as the primary elements and stairs as the backup.

The station services, including public rest rooms, snack service, newsstand, staffed ticketing and information center, and public telephones should be provided. Stations should also provide facilities (shops, changing rooms, luggage storage, etc.), access to traveler services such as station cars, and advertising displays. All stations would feature public art appropriate to their locations. Public art is an excellent adjunct to station design and a popular feature. Train and station operations require the station personnel and security. Station managers and ticket agents control the station activities, providing passenger assistance and information as well as inspecting train sets when in station. Armed security personnel are provided at every station. Large stations have multiple security personnel, and parking garages are policed (FTA, 2004).

### **5. Operation**

### **5.1 Performance**

The most important task or essential aim when designing the alignment is to specify the geometry of the guideway's functional planes so that the passenger traveling in the vehicle on the guideway experiences optimum comfort during the journey. The geometry defines the limit values for accelerations in the three spatial directions (X, Y, and Z direction). However, apart from the acceleration, the consideration of the change in acceleration (jerk) is also an important aspect for comfort. Therefore, various mathematical formulae were discussed for the transition curves and lengths, with the result,


An exception are the track switching devices which, based on beam theory, are also designed using clothoids for the horizontal transition curves in the turn-out position. The alignment is designed and the space curve established taking into consideration the aspects given above as well as the system characteristics, e.g.


The space curve data are used in the next design phase as the design criteria for


Maglev 153

A guideway section consists of two long stators, each comprising the necessary stator sections and switching stations to cover a distance of up to 50 km, the feeder cable systems (two or three according to the selected mode of stator section switching) and the trackside switchgear. A propulsion block is made up of the converter units as well as the motor section control, diagnostics, and components of the data transfer system. In turn, one converter unit comprises a converter power section, rectifier- and output transformers, a closed-loop/open-loop

In a double-end feeding configuration, power is supplied to both ends of a guideway section from the two propulsion blocks of adjacent substations. If each substation has only one propulsion block per guideway, there must be at least one clear drive control zone between two maglev vehicles running in the same direction. However, if each substation has two propulsion blocks per guideway, the second maglev vehicle may enter a zone just cleared by the first. Data exchange between the components of a drive control zone as well as between adjacent control zones and external subsystems is made possible by a powerful data transfer

Propulsion in the maglev system is achieved by a linear synchronous motor (LSM). The linear synchronous motor comprises three-phase stator windings mounted on the underside of the guideway and producing a traveling magnetic field BS (its velocity being proportional to the frequency of the input signal) along the guideway. The second component of the LSM is the onboard excitation system. The excitation system made of the levitation electromagnets produces an excitation magnetic field BR. Propulsion is achieved when the excitation magnetic field BR synchronizes and locks to the travelling magnetic field BS. As a consequence, the speed of the vehicle is proportional to the input frequency of the three-

converter control system, a converter cooling system and converter switchgear.

Fig. 8. Structure of the propulsion system

system (Henning et al., 2004).

phase stator windings.

The reductions in speed in the track course result from slopes, where the residual acceleration abilities do not maintain a high speed. Based on faster acceleration, the operation speed of the maglev can be smaller than that of the ICE3 in order to achieve the same running time. The primary energy demand that is relevant for the comparison between different means of transport averages under the examination of the current power mix as 2.5 times the secondary needs (Witt et al., 2004).

### **5.2 Propulsion system**

Electronic control systems control the clearance (nominally 10 mm). The levitation system uses on-board batteries that are independent of the propulsion system. The vehicle is capable of hovering up to one hour without external energy. While traveling, the on-board batteries are recharged by linear generators integrated into the support magnets.

A synchronous, long stator linear motor is used in the Transrapid maglev system both for propulsion and braking. It functions like a rotating electric motor whose stator is cut open and stretched along under the guideway. Inside the motor windings, alternating current is generating a magnetic traveling field that moves the vehicle without contact. The support magnets in the vehicle function as the excitation portion (rotor). The speed can be continuously regulated by varying the frequency of the alternating current. If the direction of the traveling field is reversed, the motor becomes a generator which brakes the vehicle without any contact.

In accordance with Lenz's Law, the interaction of the levitation field with the current in the slots of the rail results in propulsion or braking force. During the motion of the magnet along the rail, the linear generator winding of the main pole is coupled with a non-constant flux, which induces a voltage and reloads the on-board batteries. The generation process begins in the range of 15 km/h and equals the losses of the magnetic suspension systems at 90 km/h. The whole energy losses of the vehicle are compensated at a velocity of 110 km/h and the batteries are reloaded. Thus the levitation magnet integrates three tasks: levitation, propulsion and transfer of energy to the vehicle (Dai, 2005).

The superhigh-speed Transrapid magnetic levitation system is powered by a synchronous, ironcored long stator linear motor which – in contrast to the classic railroad – is not installed on board the vehicle but in the guideway along the route. The special features of the long stator linear propulsion system enable its dimensions to be individually adapted to the running requirements of the route as well as to specific operating concepts.

The structure of the propulsion system developed for revenue service comprises a number of components, which are located along the guideway. These drive components are temporarily switched together to form the propulsion units necessary to permit maglev operation over the guideway. A propulsion unit remains in the switched configuration for as long as a vehicle is operating within the corresponding control range (drive control zone). It is capable of driving, accelerating and retarding one maglev train. A prolusion unit comprises the line section itself and, depending on the type of power supply selected, one or two propulsion blocks. The propulsion blocks are housed in substations, the latter being situated beside the guideway and spaced at a maximum distance of 50 kilometers. A substation for a single guideway contains one or two propulsion blocks, the necessary power supply and the decentralized operations control equipment (Fig. 8). A substation for a dual guideway simply is composed of two single-guideway substations.

The reductions in speed in the track course result from slopes, where the residual acceleration abilities do not maintain a high speed. Based on faster acceleration, the operation speed of the maglev can be smaller than that of the ICE3 in order to achieve the same running time. The primary energy demand that is relevant for the comparison between different means of transport averages under the examination of the current power

Electronic control systems control the clearance (nominally 10 mm). The levitation system uses on-board batteries that are independent of the propulsion system. The vehicle is capable of hovering up to one hour without external energy. While traveling, the on-board

A synchronous, long stator linear motor is used in the Transrapid maglev system both for propulsion and braking. It functions like a rotating electric motor whose stator is cut open and stretched along under the guideway. Inside the motor windings, alternating current is generating a magnetic traveling field that moves the vehicle without contact. The support magnets in the vehicle function as the excitation portion (rotor). The speed can be continuously regulated by varying the frequency of the alternating current. If the direction of the traveling field is reversed, the motor becomes a generator which brakes the vehicle without any contact. In accordance with Lenz's Law, the interaction of the levitation field with the current in the slots of the rail results in propulsion or braking force. During the motion of the magnet along the rail, the linear generator winding of the main pole is coupled with a non-constant flux, which induces a voltage and reloads the on-board batteries. The generation process begins in the range of 15 km/h and equals the losses of the magnetic suspension systems at 90 km/h. The whole energy losses of the vehicle are compensated at a velocity of 110 km/h and the batteries are reloaded. Thus the levitation magnet integrates three tasks: levitation,

The superhigh-speed Transrapid magnetic levitation system is powered by a synchronous, ironcored long stator linear motor which – in contrast to the classic railroad – is not installed on board the vehicle but in the guideway along the route. The special features of the long stator linear propulsion system enable its dimensions to be individually adapted to the

The structure of the propulsion system developed for revenue service comprises a number of components, which are located along the guideway. These drive components are temporarily switched together to form the propulsion units necessary to permit maglev operation over the guideway. A propulsion unit remains in the switched configuration for as long as a vehicle is operating within the corresponding control range (drive control zone). It is capable of driving, accelerating and retarding one maglev train. A prolusion unit comprises the line section itself and, depending on the type of power supply selected, one or two propulsion blocks. The propulsion blocks are housed in substations, the latter being situated beside the guideway and spaced at a maximum distance of 50 kilometers. A substation for a single guideway contains one or two propulsion blocks, the necessary power supply and the decentralized operations control equipment (Fig. 8). A substation for

batteries are recharged by linear generators integrated into the support magnets.

mix as 2.5 times the secondary needs (Witt et al., 2004).

propulsion and transfer of energy to the vehicle (Dai, 2005).

running requirements of the route as well as to specific operating concepts.

a dual guideway simply is composed of two single-guideway substations.

**5.2 Propulsion system** 

Fig. 8. Structure of the propulsion system

A guideway section consists of two long stators, each comprising the necessary stator sections and switching stations to cover a distance of up to 50 km, the feeder cable systems (two or three according to the selected mode of stator section switching) and the trackside switchgear. A propulsion block is made up of the converter units as well as the motor section control, diagnostics, and components of the data transfer system. In turn, one converter unit comprises a converter power section, rectifier- and output transformers, a closed-loop/open-loop converter control system, a converter cooling system and converter switchgear.

In a double-end feeding configuration, power is supplied to both ends of a guideway section from the two propulsion blocks of adjacent substations. If each substation has only one propulsion block per guideway, there must be at least one clear drive control zone between two maglev vehicles running in the same direction. However, if each substation has two propulsion blocks per guideway, the second maglev vehicle may enter a zone just cleared by the first. Data exchange between the components of a drive control zone as well as between adjacent control zones and external subsystems is made possible by a powerful data transfer system (Henning et al., 2004).

Propulsion in the maglev system is achieved by a linear synchronous motor (LSM). The linear synchronous motor comprises three-phase stator windings mounted on the underside of the guideway and producing a traveling magnetic field BS (its velocity being proportional to the frequency of the input signal) along the guideway. The second component of the LSM is the onboard excitation system. The excitation system made of the levitation electromagnets produces an excitation magnetic field BR. Propulsion is achieved when the excitation magnetic field BR synchronizes and locks to the travelling magnetic field BS. As a consequence, the speed of the vehicle is proportional to the input frequency of the threephase stator windings.

Maglev 155

The determination of the design speed is a strategic decision-making for a transportation model. It relates to the compatibility with social economic development. The design speed of a transportation model has remarkable influence on its construction and operation cost, the ability of its competition in transportation system, then its survivability further. The design speed of high-speed transportation system is a basic precondition for its line-planning, developing and manufacturing of vehicles and other equipments, forecast of the market demand, the assessment of economical and social benefit. It is the most important parameter

The maximum operating speed the train may be raised step by step along with the market demand and the technical development. Therefore, the optimal design speed of mobile equipment of a project should be considered according to the conditions in the near and far

The commercial service speed refers to actual operating speed of the train under synthetic consideration of the market demand and economic benefit of the project. It can be determined according to many factors such as the function of a project in the whole transportation system, the competitive ability, the operating cost, the ticket price, the paying ability and the payment wish of passenger and so on. To adapt the market demand and obtain the best economic benefit, including national economic benefit and social benefit, is the principle to determinate the commercial service speed. Along with the development of economy and society, the best commercial service speed will therefore change. Therefore, in

The optimal design speed of infrastructure will be affected by the natural conditions; The optimal commercial service speed will be affected by the social and economic environment; The optimal design speed of mobile equipments will be affected by the related industry

different period there is different optimal commercial service speed.

1. The technologically suitable speed range of high-speed maglev system;

2. The best speed to improve the speed structure of integrated transportation system;

4. The influence to the optimal design speed for a certain project situation, such as the line length or travel distance, the local economic development level and the natural

The propulsion system structure meets all the requirements for commercial operation in Shanghai, such as a modular design, high reliability, high availability as well as low maintenance expenditure. The outstanding advantage of the modular structure introduced is that individual components can be replaced in accordance with project requirements without affecting the rest of the system. For example, three different converter power sections are being used in the Shanghai project in order to adapt the converter output to the route's particular requirements regarding acceleration and speed. The double-track route is 30 km long. Consequently, at a maximum operating speed of 430 km/h, the travel time is only 7.5 minutes. Three 5-section maglev vehicles operate in round-trip mode at intervals of

The following points should be taken into account:

3. The requirement on travel speed of passenger;

conditions (Wanming et al., 2006).

**5.4 Transrapid propulsion system** 

to develop a high-speed transportation system.

future.

technical level.

The task of the power supply system is to supply all components of the Transrapid system with the demanded power. The main consumer naturally is the propulsion system; others are the power rail supply for the on-board supply of the vehicle, the auxiliary power supply for the propulsion control system as well as the operation control system, the guideway switches and the reactive power compensation.

The components of the Power supply system (PS) are installed in substations – where the main components of the propulsion system and the decentralized operation control system are installed, too – and in transformer stations, which are both located along the guideway. The distance between the substations and transformer stations mainly depends on the characteristic data of the operating program and system layout, such as speedtimediagramm, minimum interval between maglev vehicles, stations, and auxiliary stopping areas. Furthermore, the availability of the power supply system is a very important stipulation for the power supply system layout.

The propulsion system and power supply for Shanghai Maglev Transrapid Project is based on the structures described above and is designed according to the requirements of the transportation system. The main requirements for a transportation system are:


Therefore the main design parameters for a transportation system are:


In relation to these parameters and the necessary input data


### **5.3 Optimal design speed**

The optimal design speed of transportation project relates not only to the national integrated transportation system structure, but also to the energy consumption structure of national economy and the traveling quality of passengers. Starting from the analysis to technical and economical characteristics of the maglev system, this paper tries to find the optimal design speed of high-speed maglev transportation system in different aspects such as the speed structure of integrated transportation system and the project benefit. As a result, it gives reference to the planning of high-speed maglev transportation project.

The task of the power supply system is to supply all components of the Transrapid system with the demanded power. The main consumer naturally is the propulsion system; others are the power rail supply for the on-board supply of the vehicle, the auxiliary power supply for the propulsion control system as well as the operation control system, the guideway

The components of the Power supply system (PS) are installed in substations – where the main components of the propulsion system and the decentralized operation control system are installed, too – and in transformer stations, which are both located along the guideway. The distance between the substations and transformer stations mainly depends on the characteristic data of the operating program and system layout, such as speedtimediagramm, minimum interval between maglev vehicles, stations, and auxiliary stopping areas. Furthermore, the availability of the power supply system is a very important

The propulsion system and power supply for Shanghai Maglev Transrapid Project is based on the structures described above and is designed according to the requirements of the

restrictions regarding size or location of power supply or propulsion equipment the

The optimal design speed of transportation project relates not only to the national integrated transportation system structure, but also to the energy consumption structure of national economy and the traveling quality of passengers. Starting from the analysis to technical and economical characteristics of the maglev system, this paper tries to find the optimal design speed of high-speed maglev transportation system in different aspects such as the speed structure of integrated transportation system and the project benefit. As a result, it gives

propulsion system and power supply was designed (Hellinger et al., 2002).

reference to the planning of high-speed maglev transportation project.

transportation system. The main requirements for a transportation system are:

switches and the reactive power compensation.

stipulation for the power supply system layout.

maximum waiting time for passengers at the stations

In relation to these parameters and the necessary input data number of vehicles and number of sections per vehicle

operation concept including headway times

vehicle data, e.g. aerodynamic resistance

comfort criterias, e.g. max acceleration, max. jerk

Therefore the main design parameters for a transportation system are:

 track length passenger capacity travel time to destination

 alignment comfort criteria speed profiles

availability, reliability

**5.3 Optimal design speed** 

The determination of the design speed is a strategic decision-making for a transportation model. It relates to the compatibility with social economic development. The design speed of a transportation model has remarkable influence on its construction and operation cost, the ability of its competition in transportation system, then its survivability further. The design speed of high-speed transportation system is a basic precondition for its line-planning, developing and manufacturing of vehicles and other equipments, forecast of the market demand, the assessment of economical and social benefit. It is the most important parameter to develop a high-speed transportation system.

The maximum operating speed the train may be raised step by step along with the market demand and the technical development. Therefore, the optimal design speed of mobile equipment of a project should be considered according to the conditions in the near and far future.

The commercial service speed refers to actual operating speed of the train under synthetic consideration of the market demand and economic benefit of the project. It can be determined according to many factors such as the function of a project in the whole transportation system, the competitive ability, the operating cost, the ticket price, the paying ability and the payment wish of passenger and so on. To adapt the market demand and obtain the best economic benefit, including national economic benefit and social benefit, is the principle to determinate the commercial service speed. Along with the development of economy and society, the best commercial service speed will therefore change. Therefore, in different period there is different optimal commercial service speed.

The optimal design speed of infrastructure will be affected by the natural conditions; The optimal commercial service speed will be affected by the social and economic environment; The optimal design speed of mobile equipments will be affected by the related industry technical level.

The following points should be taken into account:


### **5.4 Transrapid propulsion system**

The propulsion system structure meets all the requirements for commercial operation in Shanghai, such as a modular design, high reliability, high availability as well as low maintenance expenditure. The outstanding advantage of the modular structure introduced is that individual components can be replaced in accordance with project requirements without affecting the rest of the system. For example, three different converter power sections are being used in the Shanghai project in order to adapt the converter output to the route's particular requirements regarding acceleration and speed. The double-track route is 30 km long. Consequently, at a maximum operating speed of 430 km/h, the travel time is only 7.5 minutes. Three 5-section maglev vehicles operate in round-trip mode at intervals of

Maglev 157

rescue concept influences the extent of the required properties so that the effects on the planning approval procedure are given immediately. The examples of protection against going off and rescue concept clearly show how safety concept and planning approval are connected with each other. This means that the development of a safety concept must be at the beginning of the planning process of a maglev system. However, changes of the route course may occur because of others than for safety reasons, so that corresponding

The factors affecting transportation safety and security are various, among which, the physical structure and guideway security patrols play significant roles. Elevated guideways can be operated safety and efficiently (Liu & Deng, 2003). A means will be required to transfer passengers from the emergency walkway to the ground unless rescue vehicles are used to remove passengers from the walkway. The proposed method of egress from the emergency walkway is a pair of hinged stairways located within one guideway span where the walkway beam would be discontinuous. The stairways would be hinged at the end of the walkway beam and would be attached to dampers that would control the lowering of the stair. The passengers would need to activate a manual release mechanism and then the stair would lower by gravity, slowed by the dampers. The stairways would need to be located at intervals that are a reasonable walking distance. An interval of 0.40 kilometers has been assumed for cost estimating purposes. Signs would be mounted on the emergency walkway that direct passengers to the stairways and indicate the distance from their present location. Figs. 10 to 13 and Fig. 14 show required facilities while emergency situations for Colorado maglev project in the Colorado Department of Transportation (CDOT), U.S. and MOCIE maglev project in the Ministry of Commerce, Industry & Energy of Korean

customizations of the safety concept can become necessary at a later date.

Government (MOCIE), respectively (FTA, 2004, 2005a).

Fig. 10. Double-track guideway

10 minutes. The propulsion and power supply system has been specially configured for this service frequency. Although SMT is only 30km long, the test results show it has excellent characteristics of power-energy consumption/speed and it is the best tool for long distance transportation.

### **6. Safety and risk assesment**

### **6.1 Safety concept**

Despite high speeds, passengers are safer in maglev vehicles than in other transportation systems. The electromagnetically suspended vehicle is wrapped around the guideway and therefore virtually impossible to derail. Elevated guideways ensure that no obstacles can be in the way (Dai, 2005). Maglev systems are required by law to guarantee construction and operation of a system that meets proper safety standards. The responsibility of maglev systems are schematically shown in Fig. 9.

Fig. 9. Maglev system's responsibility

The requirements resulting from safety concepts have effects on all system components and on the whole planning and approval process. Certain internal and external dangers, which affect a maglev system installation, may only be limited regarding their risk potential through constructional measures.

### **6.2 Rescue concept**

An essential component of the safety concept is the rescue concept. The maglev vehicle operator has to explain in this concept with which measures self and external rescue shall be guaranteed. Depending on conception self and/or external rescue measures require different sizes of escape routes, places for emergency stops and accessibilities. Therefore, the

10 minutes. The propulsion and power supply system has been specially configured for this service frequency. Although SMT is only 30km long, the test results show it has excellent characteristics of power-energy consumption/speed and it is the best tool for long distance

Despite high speeds, passengers are safer in maglev vehicles than in other transportation systems. The electromagnetically suspended vehicle is wrapped around the guideway and therefore virtually impossible to derail. Elevated guideways ensure that no obstacles can be in the way (Dai, 2005). Maglev systems are required by law to guarantee construction and operation of a system that meets proper safety standards. The responsibility of maglev

The requirements resulting from safety concepts have effects on all system components and on the whole planning and approval process. Certain internal and external dangers, which affect a maglev system installation, may only be limited regarding their risk potential

An essential component of the safety concept is the rescue concept. The maglev vehicle operator has to explain in this concept with which measures self and external rescue shall be guaranteed. Depending on conception self and/or external rescue measures require different sizes of escape routes, places for emergency stops and accessibilities. Therefore, the

transportation.

**6.1 Safety concept** 

**6. Safety and risk assesment** 

systems are schematically shown in Fig. 9.

Fig. 9. Maglev system's responsibility

through constructional measures.

**6.2 Rescue concept** 

rescue concept influences the extent of the required properties so that the effects on the planning approval procedure are given immediately. The examples of protection against going off and rescue concept clearly show how safety concept and planning approval are connected with each other. This means that the development of a safety concept must be at the beginning of the planning process of a maglev system. However, changes of the route course may occur because of others than for safety reasons, so that corresponding customizations of the safety concept can become necessary at a later date.

The factors affecting transportation safety and security are various, among which, the physical structure and guideway security patrols play significant roles. Elevated guideways can be operated safety and efficiently (Liu & Deng, 2003). A means will be required to transfer passengers from the emergency walkway to the ground unless rescue vehicles are used to remove passengers from the walkway. The proposed method of egress from the emergency walkway is a pair of hinged stairways located within one guideway span where the walkway beam would be discontinuous. The stairways would be hinged at the end of the walkway beam and would be attached to dampers that would control the lowering of the stair. The passengers would need to activate a manual release mechanism and then the stair would lower by gravity, slowed by the dampers. The stairways would need to be located at intervals that are a reasonable walking distance. An interval of 0.40 kilometers has been assumed for cost estimating purposes. Signs would be mounted on the emergency walkway that direct passengers to the stairways and indicate the distance from their present location. Figs. 10 to 13 and Fig. 14 show required facilities while emergency situations for Colorado maglev project in the Colorado Department of Transportation (CDOT), U.S. and MOCIE maglev project in the Ministry of Commerce, Industry & Energy of Korean Government (MOCIE), respectively (FTA, 2004, 2005a).

Fig. 10. Double-track guideway

Maglev 159

The OCS comprises all technical facilities for planning, monitoring and safeguarding of vehicle operation which means a combination of automatic vehicle operation (ATO) and automatic vehicle protection (ATP) functions like e.g. providing a safe vehicle travel path in order to avoid collisions and the monitoring of vehicle travel speed range in order to assure stopping only at predefined stopping points. The OCS consists of central, wayside and mobile components with interactions to other sub-systems respectively operational and

The system is involved in the assessment of the sub-systems Operation Control System, maglev vehicle and guideway switches are responsible for the overall system safety assessment for the safety concept, rules and regulations for operation and maintenance during commissioning and commercial operation and effectiveness of staff training. The Guideline Mü8004 (the traditional German signaling guide-lines for main lines) distinguishes safety

relevant (vital) and not safety relevant (non-vital) requirements (Sawilla & Otto, 2006).

Fig. 14. Emergency door and ladder

**6.3 Operation control system (OCS)** 

maintenance staff (Fig. 15).

Fig. 15. Structure of the OCS

Fig. 11. Separated walkway beam

Fig. 13. Stairs from emergency walkway to ground

Fig. 11. Separated walkway beam

Fig. 12. Metal grate panels

Fig. 13. Stairs from emergency walkway to ground

Fig. 14. Emergency door and ladder

### **6.3 Operation control system (OCS)**

The OCS comprises all technical facilities for planning, monitoring and safeguarding of vehicle operation which means a combination of automatic vehicle operation (ATO) and automatic vehicle protection (ATP) functions like e.g. providing a safe vehicle travel path in order to avoid collisions and the monitoring of vehicle travel speed range in order to assure stopping only at predefined stopping points. The OCS consists of central, wayside and mobile components with interactions to other sub-systems respectively operational and maintenance staff (Fig. 15).

Fig. 15. Structure of the OCS

The system is involved in the assessment of the sub-systems Operation Control System, maglev vehicle and guideway switches are responsible for the overall system safety assessment for the safety concept, rules and regulations for operation and maintenance during commissioning and commercial operation and effectiveness of staff training. The Guideline Mü8004 (the traditional German signaling guide-lines for main lines) distinguishes safety relevant (vital) and not safety relevant (non-vital) requirements (Sawilla & Otto, 2006).

Maglev 161

The operation control system (OCS) monitors and controls the various subsystems,

The risk analysis pertaining to the safety concept for maglev vehicles, which is a key document, is an important criterion in the implementation process for the entire project in accordance with the DIN EN 50 126 life-cycle model, (Fig. 17). The European railway lifecycle standard DIN EN 50126 defines a process, based on the system life-cycle including RAMS management. It is applicable to modifications of existing systems in operation prior to the creation of the standard, although it is not generally applicable to other aspects of the

An OCS may only be approved by the safety authority and accepted by the maglev transport authority if both the generic subsystem and the corresponding application data

1. Verification - to determine by analysis and test that the output of each life-cycle phase

2. Validation - to demonstrate by analysis and test that the system meets in all respects its

The need for rapid transit systems has become vital in both urban and intercity travels. There are two technologies for these systems, high-speed rail (HSR) and magnetic levitation (maglev). They are dramatically different in lots of terms. This section focuses only on the technical comparison of these technologies. For a comprehensive comparison, many

have successfully passed the safety life-cycle, including (Kron Hans, 2006b):

meets the requirements of the previous phase

**7. Technical comparison of maglev and HSR** 

integrating them to form a safe, automated overall system. (Kron Hans, 2006b).

**6.4 Safety life-cycle** 

Fig. 17. Life-cycle model

specified requirements

3. Safety assessment

existing system (Steiner & Steinert, 2006).

Operation control system (OCS) is the part of an overall maglev system that integrates all subsystems like operation control center, guideway elements, stations, maintenance areas, propulsion and power supply, and vehicles. An OCS contains all components and functions to control and monitor the safe maglev operation. OCS allows control of the vehicle movements and guideway elements both manually and automatically. On the base level, OCS provides all the safety functions generally known in railway signaling, e.g. vehicle locating, guideway switch control, route protection (interlocking), and automatic vehicle control including speed profile monitoring. There are some crucial differences between OCS and most existing railway signaling systems. All vehicle control and vehicle detection (vehicle locating) functions are purely communication-based, using a highly available radio system. Only the safe vehicle brake is used by OCS for emergency braking if the service brake is failed. Emergency systems are mechanical. They act simultaneously if there is an emergency. Each system is controlled by separate component of on-board computer. Emergency systems are independent on each bogie. Each component in the system checks the others. Each component controls at least one of the braking systems. The interior has been designed to concentrate upon the urban commuters' convenience and safety. Whole interior fittings such as panel, floor and seats are made of non-combustible material comply with international fire and safety standards, (Fig. 16) (FTA, 2005a). There are also some innovative safety functions like minimum speed profile monitoring which guarantees the availability of designated stopping points in the event of power shut-offs, transmission failures or hardware faults.

Fig. 16. Emergency landing and guidance wheel

The OCS functions comprise of:


(Kron Hans, 2006a).

Operation control system (OCS) is the part of an overall maglev system that integrates all subsystems like operation control center, guideway elements, stations, maintenance areas, propulsion and power supply, and vehicles. An OCS contains all components and functions to control and monitor the safe maglev operation. OCS allows control of the vehicle movements and guideway elements both manually and automatically. On the base level, OCS provides all the safety functions generally known in railway signaling, e.g. vehicle locating, guideway switch control, route protection (interlocking), and automatic vehicle control including speed profile monitoring. There are some crucial differences between OCS and most existing railway signaling systems. All vehicle control and vehicle detection (vehicle locating) functions are purely communication-based, using a highly available radio system. Only the safe vehicle brake is used by OCS for emergency braking if the service brake is failed. Emergency systems are mechanical. They act simultaneously if there is an emergency. Each system is controlled by separate component of on-board computer. Emergency systems are independent on each bogie. Each component in the system checks the others. Each component controls at least one of the braking systems. The interior has been designed to concentrate upon the urban commuters' convenience and safety. Whole interior fittings such as panel, floor and seats are made of non-combustible material comply with international fire and safety standards, (Fig. 16) (FTA, 2005a). There are also some innovative safety functions like minimum speed profile monitoring which guarantees the availability of designated stopping points in the event of

power shut-offs, transmission failures or hardware faults.

Fig. 16. Emergency landing and guidance wheel


The OCS functions comprise of:



(Kron Hans, 2006a).





The operation control system (OCS) monitors and controls the various subsystems, integrating them to form a safe, automated overall system. (Kron Hans, 2006b).

### **6.4 Safety life-cycle**

The risk analysis pertaining to the safety concept for maglev vehicles, which is a key document, is an important criterion in the implementation process for the entire project in accordance with the DIN EN 50 126 life-cycle model, (Fig. 17). The European railway lifecycle standard DIN EN 50126 defines a process, based on the system life-cycle including RAMS management. It is applicable to modifications of existing systems in operation prior to the creation of the standard, although it is not generally applicable to other aspects of the existing system (Steiner & Steinert, 2006).

Fig. 17. Life-cycle model

An OCS may only be approved by the safety authority and accepted by the maglev transport authority if both the generic subsystem and the corresponding application data have successfully passed the safety life-cycle, including (Kron Hans, 2006b):


### **7. Technical comparison of maglev and HSR**

The need for rapid transit systems has become vital in both urban and intercity travels. There are two technologies for these systems, high-speed rail (HSR) and magnetic levitation (maglev). They are dramatically different in lots of terms. This section focuses only on the technical comparison of these technologies. For a comprehensive comparison, many

Maglev 163

Rapid transit system is a definition that covers both HSR and maglev. It is defined as an intercity passenger transit system that is time-competitive with air and/or auto on a doorto-door basis. This is a market-based, not a speed-based, definition: it recognizes that the opportunities and requirements for high-speed transportation differ markedly among different pairs of cities (Liu & Deng, 2004). The fundamental reason for considering the implementation of rapid transit systems is higher speed, which can easily equate to shorter travel time. Therefore, there is a need to look at the technical specifications of each technology. This examines the potential improvement of each technology in terms of speed,

HSR trains represent wheel-on-rail passenger systems. These trains currently operate at maximum speeds of about 350 km/h in China, and have been tested at 574 km/h in France. Examples of HSR trains include the French Train à Grand Vitesse (TGV), the Japanese Shinkansen, the German Intercity Express (ICE), the Spanish AVE, etc. Maglev is an innovative transportation technology. It is the first fundamental innovation in the field of

HSR and maglev systems are each developed for specific purposes. Selection of the appropriate technology will depend primarily on acceptable funding levels, transportation objectives, and implementation schedule (Najafi & Nassar, 1996). Rapid transit systems must fulfill the major elements of the transport politics. The main aims consist in the increase of speed in the transportation corridors, flexibility, environmental acceptance, ride comfort, stresses (noise, pollutions, and vibrancies), etc. The two existing rapid transit systems must be evaluated and compared against the background of these requirements

HSR and maglev are guided ground transportation modes with very large capacity, and both use electric power from the utility grid for propulsion. They also exhibit some fundamental differences that distinguish them as very separable transportation modes. Maglev systems offer the unique combination of technical attributes. These include light weight vehicles, centralized and fully automated control of propulsion systems, nonreliance on adhesion for vehicle acceleration and braking forces, and the ability to operate with consists of as little as single cars. These cars carry fifty to one hundred passengers without the need for highly-skilled operators. The ability to use single or double-car allows even relatively small markets to be given high frequency, reliable service. This together with frequent, highly reliable service, are required to attract new ridership and divert passengers away from their cars. The maglev technology attracts a significantly greater ridership and

Fig. 18 shows a classification to compare the different parameters for the rapid transit systems in this research. The paper focuses only on the technical comparison of the maglev and HSR systems. For a comprehensive comparison, a lot of criterions are included. It leads to a wider consideration and the development of the technical comparison. The purpose of this research is not to recommend one technology over the other. Actually, both technologies are highly advanced and have some advantages. However, this research surveys technical advantages of the high-speed maglev systems over the HSR systems

travel time and other advantages.

railway transportation technology.

provides more benefits than HSR systems.

(Yaghoubi, 2011; Yaghoubi et al., 2011).

and the traffic demands.

criterions are included. In fact, this part surveys technical advantages of the maglev systems over the HSR systems.

Mobility and transportation infrastructure is a primary need for the population. They guarantee a high grade of freedom and quality for the citizens, for their work and leisure time. Infrastructure is an important location factor in the regional and global sense. It strongly influences the development of the society and the growth of the national economies. The mobility of individuals is impossible without an equivalent volume of traffic and transportation infrastructure. Against the background of increasing energy requirement, limited fossil resources and ever-growing CO2-loads, the road traffic may not be the adequate answer for the challenges of the future developments. It is necessary to establish integrated and sustainable traffic systems for the effectively and environmentally acceptable handling of traffic (Naumann et al., 2006). Cities' developments lead to a considerable increase of the road, a capacity overloads of road traffic network, and an increase of stresses for people and environment. The transport policy must be faced up to this challenge and take appropriate measures in time. A major vision is the development and implementation of rapid transit systems, which can relocate certain parts of road and air traffic to these systems and to enhance growth of congested urban areas and coalescence of the area (Schach & Naumann, 2007).

The congestion in transportation modes associated with increased travel has caused many problems. These problems include the public concern, among which are prolonging travel time, growing accident rates, worsening environmental pollution, and accelerating energy consumption. On the contrary, high-speed ground transportation, characterized by high speed, operating reliability, passenger ride comfort, and excellent safety record, is considered one of the most promising solutions to alleviate the congestion. There are two distinguished technologies, HSR and maglev. Both provide higher operating speed. However, they have dramatically different technical specifications. Various organizations in the world are facing difficult decisions, when choosing or settling on a specific technology, in a particular corridor. Due to the complexities of HSR and maglev technology, it is not an easy task to select the most efficient technology in any given corridor.

A new rapid transit system influences the society, the industry and the ecology in various manners. A HSR or maglev system must prove its advantages. Therefore, extensive and detailed studies must be carried out. It must be examined in an intense planning process, with feasibility studies. The criterions for the decision must be evaluated in a multi-criteria procedure. This process delivers a master plan for new construction of the transportation network. The plan for the research and development of a rapid transit technology should be made at the national level. The study focuses only on the technical comparison of these technologies. For a comprehensive comparison, a lot of criterions are included. It leads to a wider consideration and the development of the technical comparison. It comprehensively compares the characteristics of HSR and maglev in detail in different aspects. These aspects include geometrical requirements, speed, acceleration, RAMS, environmental impacts, energy consumption, noise emission, vibration level, land use, loading, etc. The obtained results clearly indicate that the maglev generally possesses better technical advantages over HSR.

criterions are included. In fact, this part surveys technical advantages of the maglev systems

Mobility and transportation infrastructure is a primary need for the population. They guarantee a high grade of freedom and quality for the citizens, for their work and leisure time. Infrastructure is an important location factor in the regional and global sense. It strongly influences the development of the society and the growth of the national economies. The mobility of individuals is impossible without an equivalent volume of traffic and transportation infrastructure. Against the background of increasing energy requirement, limited fossil resources and ever-growing CO2-loads, the road traffic may not be the adequate answer for the challenges of the future developments. It is necessary to establish integrated and sustainable traffic systems for the effectively and environmentally acceptable handling of traffic (Naumann et al., 2006). Cities' developments lead to a considerable increase of the road, a capacity overloads of road traffic network, and an increase of stresses for people and environment. The transport policy must be faced up to this challenge and take appropriate measures in time. A major vision is the development and implementation of rapid transit systems, which can relocate certain parts of road and air traffic to these systems and to enhance growth of congested urban areas and coalescence of

The congestion in transportation modes associated with increased travel has caused many problems. These problems include the public concern, among which are prolonging travel time, growing accident rates, worsening environmental pollution, and accelerating energy consumption. On the contrary, high-speed ground transportation, characterized by high speed, operating reliability, passenger ride comfort, and excellent safety record, is considered one of the most promising solutions to alleviate the congestion. There are two distinguished technologies, HSR and maglev. Both provide higher operating speed. However, they have dramatically different technical specifications. Various organizations in the world are facing difficult decisions, when choosing or settling on a specific technology, in a particular corridor. Due to the complexities of HSR and maglev technology, it is not an easy task to select the most efficient technology in any given

A new rapid transit system influences the society, the industry and the ecology in various manners. A HSR or maglev system must prove its advantages. Therefore, extensive and detailed studies must be carried out. It must be examined in an intense planning process, with feasibility studies. The criterions for the decision must be evaluated in a multi-criteria procedure. This process delivers a master plan for new construction of the transportation network. The plan for the research and development of a rapid transit technology should be made at the national level. The study focuses only on the technical comparison of these technologies. For a comprehensive comparison, a lot of criterions are included. It leads to a wider consideration and the development of the technical comparison. It comprehensively compares the characteristics of HSR and maglev in detail in different aspects. These aspects include geometrical requirements, speed, acceleration, RAMS, environmental impacts, energy consumption, noise emission, vibration level, land use, loading, etc. The obtained results clearly indicate that the maglev generally possesses better technical advantages over

over the HSR systems.

the area (Schach & Naumann, 2007).

corridor.

HSR.

Rapid transit system is a definition that covers both HSR and maglev. It is defined as an intercity passenger transit system that is time-competitive with air and/or auto on a doorto-door basis. This is a market-based, not a speed-based, definition: it recognizes that the opportunities and requirements for high-speed transportation differ markedly among different pairs of cities (Liu & Deng, 2004). The fundamental reason for considering the implementation of rapid transit systems is higher speed, which can easily equate to shorter travel time. Therefore, there is a need to look at the technical specifications of each technology. This examines the potential improvement of each technology in terms of speed, travel time and other advantages.

HSR trains represent wheel-on-rail passenger systems. These trains currently operate at maximum speeds of about 350 km/h in China, and have been tested at 574 km/h in France. Examples of HSR trains include the French Train à Grand Vitesse (TGV), the Japanese Shinkansen, the German Intercity Express (ICE), the Spanish AVE, etc. Maglev is an innovative transportation technology. It is the first fundamental innovation in the field of railway transportation technology.

HSR and maglev systems are each developed for specific purposes. Selection of the appropriate technology will depend primarily on acceptable funding levels, transportation objectives, and implementation schedule (Najafi & Nassar, 1996). Rapid transit systems must fulfill the major elements of the transport politics. The main aims consist in the increase of speed in the transportation corridors, flexibility, environmental acceptance, ride comfort, stresses (noise, pollutions, and vibrancies), etc. The two existing rapid transit systems must be evaluated and compared against the background of these requirements and the traffic demands.

HSR and maglev are guided ground transportation modes with very large capacity, and both use electric power from the utility grid for propulsion. They also exhibit some fundamental differences that distinguish them as very separable transportation modes. Maglev systems offer the unique combination of technical attributes. These include light weight vehicles, centralized and fully automated control of propulsion systems, nonreliance on adhesion for vehicle acceleration and braking forces, and the ability to operate with consists of as little as single cars. These cars carry fifty to one hundred passengers without the need for highly-skilled operators. The ability to use single or double-car allows even relatively small markets to be given high frequency, reliable service. This together with frequent, highly reliable service, are required to attract new ridership and divert passengers away from their cars. The maglev technology attracts a significantly greater ridership and provides more benefits than HSR systems.

Fig. 18 shows a classification to compare the different parameters for the rapid transit systems in this research. The paper focuses only on the technical comparison of the maglev and HSR systems. For a comprehensive comparison, a lot of criterions are included. It leads to a wider consideration and the development of the technical comparison. The purpose of this research is not to recommend one technology over the other. Actually, both technologies are highly advanced and have some advantages. However, this research surveys technical advantages of the high-speed maglev systems over the HSR systems (Yaghoubi, 2011; Yaghoubi et al., 2011).

Maglev 165

long distances and against passenger cars at distances starting of 100 kilometers. In contrast to maglev, HSR is only conditionally able to compete with passenger road and air traffic at

Although the guideway has the different procedure with the manufacturing and examination, its geometrical requirements and criteria can be compared with railway tracks. The engineering rules of guideway geometry specification define the requests at the function planes of the guideway and their permissible deviations from the nominal values. These tolerances are valid for a guideway girder, finished equipping and under load of dead weight of the girder. The geometrical examination occurs to the outfit of the girders with the functional components in the manufacturing plant. Based on the defined space curve geometry, the deviations to that can be represented graphically. A comparable criterion of the wheel-on-rail system is the internal, shortwave geometry. This is with 2 mm related to 5 m length indicated in each case for layout (y-direction) and height (z-direction). Standardized onto a consideration length of 1 meter the comparative value turns out 1.5 mm/m at the maglev and 0.4 mm/m at the wheel-on-rail-system. It results from that this tolerance request is significantly higher at the wheel-on-rail system. The tolerance requests at the geometry are approximately identical with both systems. The comparison of the geometrical requests between the maglev and wheel-on-rail shows that similar tolerance requests are made. During the change of the inclination at the wheel-on-rail, track system is

shorter distances between approx. 150 and 350 kilometers (Naumann et al., 2006).

approximately 4-times higher as the maglev guideway (Suding & Jeschull, 2006).

potential is an inherent characteristic of the maglev technology.

one quarter of the distance of HSR systems (AMG, 2002).

Based on little wear and tear, the maintenance of the maglev system is less than that of the HSR systems. Due to high operating speed and acceleration, abilities and the low maintenance expenses' maglev can reach very high operation performances (Köncke, 2002). Maglev generally has an advantage over HSR in terms of travel speed. The operating speed of maglev is about 45% higher than that of the HSR trains (Liu & Deng, 2004). The limited speed of HSR is always the main concern of railway professionals. Resistance increases as the speed increases, which limits the increase of speed of HSR. On the contrary, high-speed

If the speed of each mode plays a key role in the travel time comparison, acceleration and deceleration rate is an even more important factor in terms of safety spacing and average travel speed over certain distances. The maglev vehicle accelerates quickly to higher speeds. Acceleration and braking capabilities of the maglev system result in minimal loss of time for station stops. The vehicles reach high operating speeds in a quarter of the time and less than

A maglev vehicle with acceleration/deceleration rate of 1 m/s2 can obtain the maximum speed in much less time and space than HSR trains. For example, the distance required for the maglev vehicle to accelerate to 300 km/h from a standing start is just about 4-5 kilometers, while HSR trains require about 20-23 kilometers and over twice the time to reach the same speed. Therefore, this advantage of the maglev system results in much less loss of the time for the station stops. The German TR08 maglev vehicle takes 265 s and 19.3 km for

**7.1 Geometrical requirements** 

**7.2 Performance** 

Fig. 18. Classification to compare different parameters

In general, there are many good reasons to turn to magnetically levitated trains. By lower levels of consuming energy, pollution, less noise emission and vibration level, maglev vehicles cause fewer disturbances to the nature and have increased compatibility with environmental issues. Possibility of traveling on elevated guideways means less land occupation. In addition, maglev guideway has lower dead loading. These vehicles can travel at steeper gradients and are capable of traveling at higher speeds with increased accelerations and higher braking, more effective use of regenerative as opposed to dynamic electrical braking, and lower staff and maintenance costs. Maglev vehicles have lower static and dynamic loading, higher passenger capacity and increased passenger comfort and convenience. Such vehicles can travel along routes with lower curve radiuses. They are reliable, reasonably safe, and convenient. Other benefits of maglev systems include travel time, health, flexibility, frequency, operational and schedule reliability (weather and equipment delays), accessibility, safety and security, system availability (origin and destination). Amongst the most important aspects of using maglev vehicles is the possibility of traveling at 10% grades while for high-speed trains such as German ICE this grade angle reduces to 4%. This important aspect considerably reduces the total length of the routes for maglev vehicles. As a further bonus, the cost of constructing and establishing maglev routes at grades and hilly areas considerably reduces. Maglev is obviously the most attractive and powerful transportation system. On the other hand, it is particularly suitable for longdistance transportation of passengers. Maglev is very competitive with air transportation at

In general, there are many good reasons to turn to magnetically levitated trains. By lower levels of consuming energy, pollution, less noise emission and vibration level, maglev vehicles cause fewer disturbances to the nature and have increased compatibility with environmental issues. Possibility of traveling on elevated guideways means less land occupation. In addition, maglev guideway has lower dead loading. These vehicles can travel at steeper gradients and are capable of traveling at higher speeds with increased accelerations and higher braking, more effective use of regenerative as opposed to dynamic electrical braking, and lower staff and maintenance costs. Maglev vehicles have lower static and dynamic loading, higher passenger capacity and increased passenger comfort and convenience. Such vehicles can travel along routes with lower curve radiuses. They are reliable, reasonably safe, and convenient. Other benefits of maglev systems include travel time, health, flexibility, frequency, operational and schedule reliability (weather and equipment delays), accessibility, safety and security, system availability (origin and destination). Amongst the most important aspects of using maglev vehicles is the possibility of traveling at 10% grades while for high-speed trains such as German ICE this grade angle reduces to 4%. This important aspect considerably reduces the total length of the routes for maglev vehicles. As a further bonus, the cost of constructing and establishing maglev routes at grades and hilly areas considerably reduces. Maglev is obviously the most attractive and powerful transportation system. On the other hand, it is particularly suitable for longdistance transportation of passengers. Maglev is very competitive with air transportation at

Fig. 18. Classification to compare different parameters

long distances and against passenger cars at distances starting of 100 kilometers. In contrast to maglev, HSR is only conditionally able to compete with passenger road and air traffic at shorter distances between approx. 150 and 350 kilometers (Naumann et al., 2006).

### **7.1 Geometrical requirements**

Although the guideway has the different procedure with the manufacturing and examination, its geometrical requirements and criteria can be compared with railway tracks. The engineering rules of guideway geometry specification define the requests at the function planes of the guideway and their permissible deviations from the nominal values. These tolerances are valid for a guideway girder, finished equipping and under load of dead weight of the girder. The geometrical examination occurs to the outfit of the girders with the functional components in the manufacturing plant. Based on the defined space curve geometry, the deviations to that can be represented graphically. A comparable criterion of the wheel-on-rail system is the internal, shortwave geometry. This is with 2 mm related to 5 m length indicated in each case for layout (y-direction) and height (z-direction). Standardized onto a consideration length of 1 meter the comparative value turns out 1.5 mm/m at the maglev and 0.4 mm/m at the wheel-on-rail-system. It results from that this tolerance request is significantly higher at the wheel-on-rail system. The tolerance requests at the geometry are approximately identical with both systems. The comparison of the geometrical requests between the maglev and wheel-on-rail shows that similar tolerance requests are made. During the change of the inclination at the wheel-on-rail, track system is approximately 4-times higher as the maglev guideway (Suding & Jeschull, 2006).

### **7.2 Performance**

Based on little wear and tear, the maintenance of the maglev system is less than that of the HSR systems. Due to high operating speed and acceleration, abilities and the low maintenance expenses' maglev can reach very high operation performances (Köncke, 2002). Maglev generally has an advantage over HSR in terms of travel speed. The operating speed of maglev is about 45% higher than that of the HSR trains (Liu & Deng, 2004). The limited speed of HSR is always the main concern of railway professionals. Resistance increases as the speed increases, which limits the increase of speed of HSR. On the contrary, high-speed potential is an inherent characteristic of the maglev technology.

If the speed of each mode plays a key role in the travel time comparison, acceleration and deceleration rate is an even more important factor in terms of safety spacing and average travel speed over certain distances. The maglev vehicle accelerates quickly to higher speeds. Acceleration and braking capabilities of the maglev system result in minimal loss of time for station stops. The vehicles reach high operating speeds in a quarter of the time and less than one quarter of the distance of HSR systems (AMG, 2002).

A maglev vehicle with acceleration/deceleration rate of 1 m/s2 can obtain the maximum speed in much less time and space than HSR trains. For example, the distance required for the maglev vehicle to accelerate to 300 km/h from a standing start is just about 4-5 kilometers, while HSR trains require about 20-23 kilometers and over twice the time to reach the same speed. Therefore, this advantage of the maglev system results in much less loss of the time for the station stops. The German TR08 maglev vehicle takes 265 s and 19.3 km for

Maglev 167

Transrapid Shanghai Maglev TR-08 SMT the type series TR 08

2 6 10

2.2 5.0 7.9

Car End Section Middle Section

InterCityExpress (ICE) 3 ICE-03 the type series 403

maximum speed km/h until 300 until 450 Sections per vehicle 8 5 (from 2 to 10 possible) Seats (on average) 415 446 Length (total) 200 128.3 Capacity 8: 850 10: 1192

performance kW 8.000 approx. 25.000

200 km/h 0.9 2.2 3.6

400 km/h 4.4 10.3 16.1 500 km/h 8.2 18.7 -

Trailer

Train Size 2 6 2 0-8 Section Length m 25.68 24.78 26.99 24.77 Section Width m 2.95 2.95 3.70 3.70 Section Height m 3.84 3.84 4.16 4.16 Payload / Section ton - 10.3 13.9 Seats / Section - 62-92 84-126 Floor Space / Section m - 70 77 Weight / Seat kg Approx. 920 to 1000 500 – 700 400 – 600 Number of Sections 8 2 4 6 8 10 Seats (high density) 408 to 418 184 436 688 940 1192 Seats (low density) - 124 292 460 628 796 Passengers ton - 20.6 48.4 76.2 104 131.8

Minimum km/h 300 350 200 km/h 1400 705 250 km/h 2250 1100 300 km/h 3200 1590 350 km/h - 2160 400 km/h - 2825 450 km/h - 3580 500 km/h - 4415 Table 12. Comparison between two German trains of ICE-03 HSR and TR-08 maglev

Constant Speed of MW Train Sections


Net weight vehicle ton 409 247 Weight / Seat kg Approx. 930 Approx. 550

longitudinal gradient % 3.5 10 Acceleration m/s2 maximum 1,0 constant 1,5 Acceleration m/s2 Distance (m) Time (s) Distance (m) Time (s) 0- 100 km/h 424 31 0- 200 km/h 4400 140 1700 61 0- 300 km/h 20900 370 4200 97 0- 400 km/h 9100 148 0- 500 km/h 22700 256

> Driving Trailer/ End Car

Parameter Unit

300 km/h

Operational

Maximum engine

Power Requirement at

Maximum

Train Configuration

Curve Radii m

the acceleration to achieve the speed of 500 km/h, which are less and shorter than the corresponding values 370 s and 20.9 km for ICE03 train to achieve 300 km/h. The deceleration time and distance via maglev are both shorter so it can maintain ideal speed much longer. The eventual travel time via HSR doubles that of maglev even though the analysis only presented about 50% difference (Liu & Deng, 2004; Witt & Herzberg, 2004; Baohua et al., 2008).

The maglev vehicles can easily overcome uphill gradients and slopes with inclinations up to 10 % comparing to a maximum 3.5 % - 4 % for the HSR trains. In general, the maglev vehicle can climb grades from 2.5 to 8 times steeper than HSR trains with no loss of speed. Embankments and incisions are necessary for the compensation of the small ability of climbing and the constructive design of the guideway. This can lead to a considerable land use. The maglev vehicles can negotiate 50-percent tighter curves (horizontal and vertical) at the same speeds as HSR trains. They can travel through a curve of the same radius at much higher speeds than HSR trains. For example, the maglev vehicle can cant up to 16°. The minimum curve radius of the maglev guideway under the speed of 300 km/h is also 1590– 2360 m, which is smaller than 3350 m of HSR tracks (AMG, 2002; Liu & Deng, 2004; Dai, 2005; Jehle et al., 2006; Stephan & Fritz, 2006; Baohua et al., 2008).

Resulting from the greater propulsion performance, the maglev systems offer not only a higher travel speed but also a higher acceleration and deceleration level. The maglev accelerates very well and almost constantly with 0.9 m/s². Its maximum speed of 450 km/h is reached within 3 min. The ICE train requires nearly 5 min until it reaches its maximum speed of 300 km/h. Moreover, the maglev vehicle may run approaches to the stop stations in urban surrounding with a speed of 250 km/h due to its low noise emissions and vibrations. The pure running time difference of both systems regarding a line length of approximately 300 km from Berlin to Prague amounts of 29 minutes (50 % more) (Stephan & Fritz, 2006).

Table 12 shows the results of comparison between a maglev train and a HSR train from operational viewpoint (Schach & Naumann, 2007; Liu & Deng, 2004; Witt & Herzberg, 2004; Köncke, 2002; Baohua et al. 2008).

### **7.3 Reliability, availability, maintainability and safety**

An important issue in the proper operation of rapid transit systems is the reliability, availability, maintainability and safety (RAMS). RAMS is the item that needs to be considered in any new rapid transit system establishment. This item is the factor that affects the passenger's mode choice decisions and is important for project evaluation. Safety is amongst most important factors for ensuring operational of integrity high-speed trains. Maglev is one of the safest means of transportation in the world. The concept of maglev has essentially eliminated the safety risks associated with the operation of HSR systems. The use of a dedicated and separated guideway without intersections with other transportation modes such as roads and highways ensures no safety conflicts and allows uninterrupted maglev operations. The maglev technology has essentially eliminated the safety risks associated with the operation of rapid transit systems. Compared to the operating experiences of HSR, the maglev technology has a scarce record. On the other hand, the German Transrapid Test Track in Elmsland has been operating for more than 20 years and

the acceleration to achieve the speed of 500 km/h, which are less and shorter than the corresponding values 370 s and 20.9 km for ICE03 train to achieve 300 km/h. The deceleration time and distance via maglev are both shorter so it can maintain ideal speed much longer. The eventual travel time via HSR doubles that of maglev even though the analysis only presented about 50% difference (Liu & Deng, 2004; Witt & Herzberg, 2004;

The maglev vehicles can easily overcome uphill gradients and slopes with inclinations up to 10 % comparing to a maximum 3.5 % - 4 % for the HSR trains. In general, the maglev vehicle can climb grades from 2.5 to 8 times steeper than HSR trains with no loss of speed. Embankments and incisions are necessary for the compensation of the small ability of climbing and the constructive design of the guideway. This can lead to a considerable land use. The maglev vehicles can negotiate 50-percent tighter curves (horizontal and vertical) at the same speeds as HSR trains. They can travel through a curve of the same radius at much higher speeds than HSR trains. For example, the maglev vehicle can cant up to 16°. The minimum curve radius of the maglev guideway under the speed of 300 km/h is also 1590– 2360 m, which is smaller than 3350 m of HSR tracks (AMG, 2002; Liu & Deng, 2004; Dai,

Resulting from the greater propulsion performance, the maglev systems offer not only a higher travel speed but also a higher acceleration and deceleration level. The maglev accelerates very well and almost constantly with 0.9 m/s². Its maximum speed of 450 km/h is reached within 3 min. The ICE train requires nearly 5 min until it reaches its maximum speed of 300 km/h. Moreover, the maglev vehicle may run approaches to the stop stations in urban surrounding with a speed of 250 km/h due to its low noise emissions and vibrations. The pure running time difference of both systems regarding a line length of approximately 300 km from Berlin to Prague amounts of 29 minutes (50 % more) (Stephan &

Table 12 shows the results of comparison between a maglev train and a HSR train from operational viewpoint (Schach & Naumann, 2007; Liu & Deng, 2004; Witt & Herzberg, 2004;

An important issue in the proper operation of rapid transit systems is the reliability, availability, maintainability and safety (RAMS). RAMS is the item that needs to be considered in any new rapid transit system establishment. This item is the factor that affects the passenger's mode choice decisions and is important for project evaluation. Safety is amongst most important factors for ensuring operational of integrity high-speed trains. Maglev is one of the safest means of transportation in the world. The concept of maglev has essentially eliminated the safety risks associated with the operation of HSR systems. The use of a dedicated and separated guideway without intersections with other transportation modes such as roads and highways ensures no safety conflicts and allows uninterrupted maglev operations. The maglev technology has essentially eliminated the safety risks associated with the operation of rapid transit systems. Compared to the operating experiences of HSR, the maglev technology has a scarce record. On the other hand, the German Transrapid Test Track in Elmsland has been operating for more than 20 years and

2005; Jehle et al., 2006; Stephan & Fritz, 2006; Baohua et al., 2008).

Baohua et al., 2008).

Fritz, 2006).

Köncke, 2002; Baohua et al. 2008).

**7.3 Reliability, availability, maintainability and safety** 


Table 12. Comparison between two German trains of ICE-03 HSR and TR-08 maglev

Maglev 169

alignment parameters allow the guideway to adapt to the landscape. Compared to roads or railway tracks, especially the elevated guideway does not affect wildlife movement. Even the ground-level guideway allows small animals to pass underneath due to the clearance planned under the guideway. Compared to all other land-bound transport systems, the maglev requires the least amount of the space and the land. The land area required for a ground-level double-track by either maglev or HSR systems is about similar so it is 14 m2/m and 12 m2/m, respectively. But for an elevated double-track guideway, approx. 2 square meter of land is needed for each meter of guideway (Schwindt, 2006). Considering the densely populated and limited land resources, an elevated structure is a preferred choice. The traffic effects on the land-use have been always considered by urban planner and transportation engineers. In the center of metropolitan areas with large economic activities, such as Mashhad, the increase of traffic volume has indirectly cost. It includes

As maglev is electrically powered, there is no direct air pollution as with airplanes and automobiles. The maglev causes lower CO2 emissions. It is also easier and more effective to control emissions at the source of electric power generation rather than at many points of consumption. Maglev is the quietest high-speed ground transportation system available today. Due to its non-contact technology, there is neither rolling nor gearing or engine noise. The frictionless operation of the maglev vehicle reduces vibration and maintenance resulting from wear. Comparing the noise levels at different speeds, the maglev vehicle is much quieter than the HSR trains. For example, The German TR07 maglev vehicle can travel about 25 percent faster than existing HSR trains before reaching the peak noise restrictions of 80 to 90 dBa. Such an advantage in speed will yield reduced the trip times along the noise-limited routes, which is most urban areas. At the speeds up to 200 km/h, the noise level compared to other noises from the surroundings can hardly be heard. At 250 km/h, the pass-by noise level is 71 dB(A), and from 250 km/h upwards, the aerodynamic noises begin to dominate the noise level. The result is that, at the speed of 300 km/h, the system is no louder than a light rail vehicle, and at 400 km/h, the noise level can be compared to a conventional train traveling at around 300 km/h. Even when at respective high speeds, data also indicates that maglev vehicle is 5 to 7 dBa quieter than the HSR train (Liu & Deng, 2004; Dai, 2005; Schwindt, 2006). The American JetTrain HSR train is almost twice as noisy as the maglev vehicle at the similar operational speeds (AMG, 2002). The results of the noise measurements of the TR08 Maglev System may be compared with similar data, documented by the Federal Railroad Administration (FRA, 1998), for other high-speed ground transportation systems (FRA, 2002a). The noise analysis associated with the Shanghai maglev train shows that the system is quieter than high-speed railway trains for comparable

A field experiment was conducted, to investigate the possible differences in perceived annoyance of noise caused by high-speed trains, both HSR and maglev. These results were evaluated for the TGV train at speeds of 140 km/h & 300 km/h and for the maglev vehicle at speeds of 200 km/h, 300 km/h and 400 km/h. The LAeq-annoyance relationships determined for the HSR and for the maglev train did not differ significantly. This study has shown that the noise annoyance caused by different types of trains at the same average

wasting time and damages such as environmental pollution.

distances from the track (Chen et al., 2007).

**7.5 Pollution** 

close to a million passengers have ridden around the 40-kilometer closed loop. The maglev vehicle wraps around the guideway beam so it is virtually impossible to derail. Redundancies achieved through the duplication of components as well as the automated radio-controlled system ensure that operational safety will not be jeopardized. The principle of synchronized propulsion on the guideway makes collisions between vehicles virtually impossible. In general, no other obstacles can be in the way. If two or more vehicles were ever placed simultaneously in the same guideway segment, they would be forced by the motor in the guideway to travel at the same speed in the same direction. The vehicles are also designed to withstand collisions with small objects on the guideway. Energizing only the section of the guideway on which the train is traveling enhances operational safety and efficiency. The maglev vehicle is absolutely weatherproof and masters wind and adverse weather easily. Regarding the aspect of fire protection the maglev vehicle meets the highest requirements of the relevant standards. No fuels or combustible materials are on board. All used materials within the vehicles are PVC-free, highly inflammable, poor conductors of heat, burn-through-proof and heat-proof. The fire proof doors can be optionally used in order to separate the vehicle sections. The system is controlled in all the directions of the movement to ensure ride comfort throughout all the phases of the operation. The seat belts are not required, and passengers are free to move about the cabin at all speeds (AMG, 2002; Köncke, 2002; Liu & Deng, 2004; Dai, 2005).

### **7.4 Energy consumption and space requirement**

With non-contact technology, there is no energy loss due to the wheel-guideway friction. The vehicle weight is lower due to the absence of wheels, axles and engine (low mass of approx. 0.5 t per seat). In terms of energy consumption, the maglev vehicles are better than HSR trains. The maglev consumes less energy per seat-mile than HSR trains due to the utilization of lightweight materials and improvement in the advanced technology. The energy consumption of the maglev system with its non-contact levitation and propulsion technology, highly efficient linear motor and low aerodynamic resistance is very economical when compared to other transportation modes. The high-speed maglev system consumes 20 to 30 percent less energy per passenger than the very modest railroad. With the same energy input, the performance of the maglev system is substantially higher than HSR systems (Liu & Deng, 2004; Köncke, 2002).

As consumers of energy, the transportation sectors are vulnerable to environmental and global warming concerns and the increasing volatile oil market. Reducing dependency on foreign oil is also an important criterion. The system of the external power supply over the contact rail causes higher investment and operational costs. The energy costs of the maglev vehicle despite higher design speed, is lower than that of ICE3 train (Witt & Herzberg, 2004). The maglev vehicles running at 400 km/h has lower environmental impact indicators, such as system energy consumption, waste gas discharges, site area and the like, then the ICE trains running at 300 km/h (Baohua et al., 2008). They also have low running resistance of approx. 0.2 kN per seat at 400 km/h (Köncke, 2002).

Maglev is one of the first transportation systems to be specially developed to protect the environment. The system can be co-located with existing transportation corridors and needs a minimum amount of land for the support of the guideway beams. Use of the elevated guideway minimizes the disturbance to the existing land, water and wildlife, while flexible

close to a million passengers have ridden around the 40-kilometer closed loop. The maglev vehicle wraps around the guideway beam so it is virtually impossible to derail. Redundancies achieved through the duplication of components as well as the automated radio-controlled system ensure that operational safety will not be jeopardized. The principle of synchronized propulsion on the guideway makes collisions between vehicles virtually impossible. In general, no other obstacles can be in the way. If two or more vehicles were ever placed simultaneously in the same guideway segment, they would be forced by the motor in the guideway to travel at the same speed in the same direction. The vehicles are also designed to withstand collisions with small objects on the guideway. Energizing only the section of the guideway on which the train is traveling enhances operational safety and efficiency. The maglev vehicle is absolutely weatherproof and masters wind and adverse weather easily. Regarding the aspect of fire protection the maglev vehicle meets the highest requirements of the relevant standards. No fuels or combustible materials are on board. All used materials within the vehicles are PVC-free, highly inflammable, poor conductors of heat, burn-through-proof and heat-proof. The fire proof doors can be optionally used in order to separate the vehicle sections. The system is controlled in all the directions of the movement to ensure ride comfort throughout all the phases of the operation. The seat belts are not required, and passengers are free to move about the cabin at all speeds (AMG, 2002;

With non-contact technology, there is no energy loss due to the wheel-guideway friction. The vehicle weight is lower due to the absence of wheels, axles and engine (low mass of approx. 0.5 t per seat). In terms of energy consumption, the maglev vehicles are better than HSR trains. The maglev consumes less energy per seat-mile than HSR trains due to the utilization of lightweight materials and improvement in the advanced technology. The energy consumption of the maglev system with its non-contact levitation and propulsion technology, highly efficient linear motor and low aerodynamic resistance is very economical when compared to other transportation modes. The high-speed maglev system consumes 20 to 30 percent less energy per passenger than the very modest railroad. With the same energy input, the performance of the maglev system is substantially higher than HSR systems (Liu

As consumers of energy, the transportation sectors are vulnerable to environmental and global warming concerns and the increasing volatile oil market. Reducing dependency on foreign oil is also an important criterion. The system of the external power supply over the contact rail causes higher investment and operational costs. The energy costs of the maglev vehicle despite higher design speed, is lower than that of ICE3 train (Witt & Herzberg, 2004). The maglev vehicles running at 400 km/h has lower environmental impact indicators, such as system energy consumption, waste gas discharges, site area and the like, then the ICE trains running at 300 km/h (Baohua et al., 2008). They also have low running resistance

Maglev is one of the first transportation systems to be specially developed to protect the environment. The system can be co-located with existing transportation corridors and needs a minimum amount of land for the support of the guideway beams. Use of the elevated guideway minimizes the disturbance to the existing land, water and wildlife, while flexible

Köncke, 2002; Liu & Deng, 2004; Dai, 2005).

& Deng, 2004; Köncke, 2002).

**7.4 Energy consumption and space requirement** 

of approx. 0.2 kN per seat at 400 km/h (Köncke, 2002).

alignment parameters allow the guideway to adapt to the landscape. Compared to roads or railway tracks, especially the elevated guideway does not affect wildlife movement. Even the ground-level guideway allows small animals to pass underneath due to the clearance planned under the guideway. Compared to all other land-bound transport systems, the maglev requires the least amount of the space and the land. The land area required for a ground-level double-track by either maglev or HSR systems is about similar so it is 14 m2/m and 12 m2/m, respectively. But for an elevated double-track guideway, approx. 2 square meter of land is needed for each meter of guideway (Schwindt, 2006). Considering the densely populated and limited land resources, an elevated structure is a preferred choice. The traffic effects on the land-use have been always considered by urban planner and transportation engineers. In the center of metropolitan areas with large economic activities, such as Mashhad, the increase of traffic volume has indirectly cost. It includes wasting time and damages such as environmental pollution.

### **7.5 Pollution**

As maglev is electrically powered, there is no direct air pollution as with airplanes and automobiles. The maglev causes lower CO2 emissions. It is also easier and more effective to control emissions at the source of electric power generation rather than at many points of consumption. Maglev is the quietest high-speed ground transportation system available today. Due to its non-contact technology, there is neither rolling nor gearing or engine noise. The frictionless operation of the maglev vehicle reduces vibration and maintenance resulting from wear. Comparing the noise levels at different speeds, the maglev vehicle is much quieter than the HSR trains. For example, The German TR07 maglev vehicle can travel about 25 percent faster than existing HSR trains before reaching the peak noise restrictions of 80 to 90 dBa. Such an advantage in speed will yield reduced the trip times along the noise-limited routes, which is most urban areas. At the speeds up to 200 km/h, the noise level compared to other noises from the surroundings can hardly be heard. At 250 km/h, the pass-by noise level is 71 dB(A), and from 250 km/h upwards, the aerodynamic noises begin to dominate the noise level. The result is that, at the speed of 300 km/h, the system is no louder than a light rail vehicle, and at 400 km/h, the noise level can be compared to a conventional train traveling at around 300 km/h. Even when at respective high speeds, data also indicates that maglev vehicle is 5 to 7 dBa quieter than the HSR train (Liu & Deng, 2004; Dai, 2005; Schwindt, 2006). The American JetTrain HSR train is almost twice as noisy as the maglev vehicle at the similar operational speeds (AMG, 2002). The results of the noise measurements of the TR08 Maglev System may be compared with similar data, documented by the Federal Railroad Administration (FRA, 1998), for other high-speed ground transportation systems (FRA, 2002a). The noise analysis associated with the Shanghai maglev train shows that the system is quieter than high-speed railway trains for comparable distances from the track (Chen et al., 2007).

A field experiment was conducted, to investigate the possible differences in perceived annoyance of noise caused by high-speed trains, both HSR and maglev. These results were evaluated for the TGV train at speeds of 140 km/h & 300 km/h and for the maglev vehicle at speeds of 200 km/h, 300 km/h and 400 km/h. The LAeq-annoyance relationships determined for the HSR and for the maglev train did not differ significantly. This study has shown that the noise annoyance caused by different types of trains at the same average

Maglev 171

The loading of the guideway is almost equal to the loading of each one of the four girders of the railroad bridge. In other words, taking into account the fact that the bridge consists of four girders, comparison of the results indicates that the load on the railroad bridge deck is four times greater than the load on the maglev guideway. This means that the guideway by itself can play the role of each one of the girders of the railroad bridge (Yaghoubi & Ziari,

Rapid increase in traffic volume in transport systems plus the need for improving passenger comfort have highlighted the subject of developing new transport systems. The recent required increases in the traffic volume in transport systems, as well as a need for the improvement of passengers' comfort, and required reductions in track life cycle costs, have caused the subject of the development of a new transportation system. One of the important systems which have attracted industries is maglev transport system. In this regard, maglev transport system turns out to be a proper choice for transportation industries around the world. Maglev systems have been recently developed in response to the need for rapid transit systems. The maglev system comes off clearly better and surpasses the HSR systems in almost most fields. These include the pollution, noise emission, vibration level, environmental issues, land occupations, loading, speed, acceleration and deceleration, braking, maintenance costs, passenger comfort, safety, travel time, etc. With the maglev guideway it is also possible to reach to the minimal radiuses for the horizontal and vertical curves. A maglev vehicle can as well travel at the steeper gradients compared with the HSR systems. This considerably reduces the total length of track for the maglev routes compared to the HSR systems. The possibility of traveling with the higher grade angles also reduces the number of tunnels that are required to travel through the mountainous areas. This can also shorten the total length for the maglev route. Therefore, construction of the maglev routes in the hilly areas, in addition to many other advantageous of these systems, can be considered as an attractive choice for the transportation industries. The lower energy consumption of the maglev vehicles in comparison with the HSR systems is also among major characteristics of the magnetically levitated trains. This can be easily associated with the absence of the wheels and the resulting situation of no physical contact between the maglev vehicle and its guideway. Therefore, the energy loss due to the unwanted friction is out of the equations. Furthermore, the vehicle weight is lower due to the absence of wheels, axles and engine. On the other hand, reduction in the travel time considerably reduces the energy consumption. The limited energy resources that are currently available to the nation have highlighted the fact that every individual has to be the energy conscious. The government had to take steps, and it started by setting the preventative rules and the tightening access to the cheap energy resources. Clearly, the widespread application of the magnetically levitated trains for the public transport, in short and long distances, can provide the nation with huge saving in the energy consumption. This is not a fact that can be easily

Effective parameters in the design of guideways including dead and live loads, dynamic amplification factor and deflection, and structural analysis and design criteria were investigated. According to AREMA regulations and UIC leaflets, live loading models for

2011; Yaghoubi & Rezvani, 2011).

ignored nor can it be bypassed.

**8. Conclusion** 

outdoor façade exposure level is not significantly different. In particular, the magnetic levitation systems are not more annoying than the HSR trains, which is in agreement with earlier research (Coensel et al., 2007).

Whatever the kind of transport system, a passing maglev vehicle always creates ground vibrations due to dynamic loading of the track. Depending on the speed, load transfer, load dispersion and the nature of the ground, these vibrations are transmitted through the ground to different degrees and may thus be felt as shocks in neighboring buildings. For especially sensitive areas, technical solutions are currently being investigated, which minimize the dynamic loads that are transferred from the vehicle to the guideway and then to the bearings in the supports and foundations (Schwindt, 2006).

TR08 vibration levels for both the concrete elevated and concrete at-grade (AG) guideways are compared with those of the TGV, the Italian Pendolino, the Swedish X2000, and the Acela at 240 km/h. The vibration levels for the TR08 traversing the at-grade guideway structures are comparable to those from HSR trains measured in Italy (Pendolino) and France (TGV), whereas the levels for the elevated structure are considerably lower for the distances measured. Vibration levels measured at 15 m for the TR08 traversing the at-grade guideway at 400 km/h are less than those previously measured at 15 m for the Acela traveling 240 km/h. These comparisons, however, are representative of data collected at various sites and are generally typical of local geological conditions. In general, groundborne vibration levels from trains on elevated structures tend to be lower than those from atgrade operations (FRA, 2002b). The curves for European HSR trains are taken from the FRA high-speed ground transportation guidance manual (FRA, 1998), and for the Acela from measurements conducted by HMMH (FRA, 2000).

### **7.6 Loading**

In this part of research, maglev guideways and road and railroad bridges are compared from loading and design aspects. The optimal design of all bridges, including road, railroads and maglev elevated guideways is really vital. Majority of the existing maglev guideways are elevated and completely built on the bridge. In fact, a maglev elevated guideway is one kind of bridges. Therefore, it can be compared with any bridge, including railroad and road.

According to the AREMA regulations and the UIC leaflets, the live loading models for the rail tracks, is a combination of the concentrated and distributed loads. However, the live loading models for the maglev trains, in the absence of wheels and pursuant to uniformity in the intensity of magnetic forces due to the magnets, are uniformly distributed on the guideways. The lateral magnetic force in maglev is less than the lateral force in the rail tracks. The low level of this force in maglev is due to the absence of the rails and wheels, lower weight of the vehicle and the presence of lateral restoring and equilibration magnetic force.

In general, vertical loadings (dead and live) in the spans of maglev guideways are much lower than those of the railroad bridges. The intensity of the uniform distributed load in live loading of the railroad bridges is almost four times that in maglev. One reason for this difference is the lower weight of the maglev vehicle due to the absence of wheels, axles and transmission parts plus the overall short length of the vehicle. The amount of the earthquake lateral force on the maglev guideway is less than one third of its value for the road bridge.

outdoor façade exposure level is not significantly different. In particular, the magnetic levitation systems are not more annoying than the HSR trains, which is in agreement with

Whatever the kind of transport system, a passing maglev vehicle always creates ground vibrations due to dynamic loading of the track. Depending on the speed, load transfer, load dispersion and the nature of the ground, these vibrations are transmitted through the ground to different degrees and may thus be felt as shocks in neighboring buildings. For especially sensitive areas, technical solutions are currently being investigated, which minimize the dynamic loads that are transferred from the vehicle to the guideway and then

TR08 vibration levels for both the concrete elevated and concrete at-grade (AG) guideways are compared with those of the TGV, the Italian Pendolino, the Swedish X2000, and the Acela at 240 km/h. The vibration levels for the TR08 traversing the at-grade guideway structures are comparable to those from HSR trains measured in Italy (Pendolino) and France (TGV), whereas the levels for the elevated structure are considerably lower for the distances measured. Vibration levels measured at 15 m for the TR08 traversing the at-grade guideway at 400 km/h are less than those previously measured at 15 m for the Acela traveling 240 km/h. These comparisons, however, are representative of data collected at various sites and are generally typical of local geological conditions. In general, groundborne vibration levels from trains on elevated structures tend to be lower than those from atgrade operations (FRA, 2002b). The curves for European HSR trains are taken from the FRA high-speed ground transportation guidance manual (FRA, 1998), and for the Acela from

In this part of research, maglev guideways and road and railroad bridges are compared from loading and design aspects. The optimal design of all bridges, including road, railroads and maglev elevated guideways is really vital. Majority of the existing maglev guideways are elevated and completely built on the bridge. In fact, a maglev elevated guideway is one kind of bridges. Therefore, it can be compared with any bridge, including railroad and road. According to the AREMA regulations and the UIC leaflets, the live loading models for the rail tracks, is a combination of the concentrated and distributed loads. However, the live loading models for the maglev trains, in the absence of wheels and pursuant to uniformity in the intensity of magnetic forces due to the magnets, are uniformly distributed on the guideways. The lateral magnetic force in maglev is less than the lateral force in the rail tracks. The low level of this force in maglev is due to the absence of the rails and wheels, lower weight of the vehicle and the presence of lateral restoring and equilibration magnetic

In general, vertical loadings (dead and live) in the spans of maglev guideways are much lower than those of the railroad bridges. The intensity of the uniform distributed load in live loading of the railroad bridges is almost four times that in maglev. One reason for this difference is the lower weight of the maglev vehicle due to the absence of wheels, axles and transmission parts plus the overall short length of the vehicle. The amount of the earthquake lateral force on the maglev guideway is less than one third of its value for the road bridge.

to the bearings in the supports and foundations (Schwindt, 2006).

measurements conducted by HMMH (FRA, 2000).

**7.6 Loading** 

force.

earlier research (Coensel et al., 2007).

The loading of the guideway is almost equal to the loading of each one of the four girders of the railroad bridge. In other words, taking into account the fact that the bridge consists of four girders, comparison of the results indicates that the load on the railroad bridge deck is four times greater than the load on the maglev guideway. This means that the guideway by itself can play the role of each one of the girders of the railroad bridge (Yaghoubi & Ziari, 2011; Yaghoubi & Rezvani, 2011).

### **8. Conclusion**

Rapid increase in traffic volume in transport systems plus the need for improving passenger comfort have highlighted the subject of developing new transport systems. The recent required increases in the traffic volume in transport systems, as well as a need for the improvement of passengers' comfort, and required reductions in track life cycle costs, have caused the subject of the development of a new transportation system. One of the important systems which have attracted industries is maglev transport system. In this regard, maglev transport system turns out to be a proper choice for transportation industries around the world. Maglev systems have been recently developed in response to the need for rapid transit systems. The maglev system comes off clearly better and surpasses the HSR systems in almost most fields. These include the pollution, noise emission, vibration level, environmental issues, land occupations, loading, speed, acceleration and deceleration, braking, maintenance costs, passenger comfort, safety, travel time, etc. With the maglev guideway it is also possible to reach to the minimal radiuses for the horizontal and vertical curves. A maglev vehicle can as well travel at the steeper gradients compared with the HSR systems. This considerably reduces the total length of track for the maglev routes compared to the HSR systems. The possibility of traveling with the higher grade angles also reduces the number of tunnels that are required to travel through the mountainous areas. This can also shorten the total length for the maglev route. Therefore, construction of the maglev routes in the hilly areas, in addition to many other advantageous of these systems, can be considered as an attractive choice for the transportation industries. The lower energy consumption of the maglev vehicles in comparison with the HSR systems is also among major characteristics of the magnetically levitated trains. This can be easily associated with the absence of the wheels and the resulting situation of no physical contact between the maglev vehicle and its guideway. Therefore, the energy loss due to the unwanted friction is out of the equations. Furthermore, the vehicle weight is lower due to the absence of wheels, axles and engine. On the other hand, reduction in the travel time considerably reduces the energy consumption. The limited energy resources that are currently available to the nation have highlighted the fact that every individual has to be the energy conscious. The government had to take steps, and it started by setting the preventative rules and the tightening access to the cheap energy resources. Clearly, the widespread application of the magnetically levitated trains for the public transport, in short and long distances, can provide the nation with huge saving in the energy consumption. This is not a fact that can be easily ignored nor can it be bypassed.

Effective parameters in the design of guideways including dead and live loads, dynamic amplification factor and deflection, and structural analysis and design criteria were investigated. According to AREMA regulations and UIC leaflets, live loading models for

Maglev 173

American Magline Group (AMG). (2002). Technology comparison: high speed ground transportation, Transrapid superspeed maglev and bombardier JetTrain. Baohua, M., Rong, H. & Shunping, J. (2008). Potential applications of maglev railway technology in China. *Journal of Transpn Sys Eng & IT*, Vol. 8, No. 1, pp. 29−39. Behbahani, H. & Yaghoubi, H. (2010). Procedures for safety and risk assessment of maglev

Cai Y., Chen, S. S., Rote, D. M., & Coffey, H. T., (1996). Vehicle/guideway dynamic

Coensel, B. D., Botteldooren, D., Berglund, B., Nilsson, M. E., Muer, T. D. & Lercher, P.

Dai, H. (2005). Dynamic behavior of maglev vehicle/guideway system with control. Ph.D.

FRA (Federal Railroad Administration). (1998). High speed ground transportation noise and

FRA. (2000). Acela trainset noise and vibration measurements on the northeast corridor.

FRA. (2002a). Noise characteristics of the Transrapid TR08 maglev system. Report No. DOT-

FRA. (2002b). Vibration characteristics of the Transrapid TR08 maglev system. Report No.

Federal Transit Administration (FTA), Office of Research, Demonstration, and Innovation,

FTA, Office of Research, Demonstration, and Innovation, (2004). Urban maglev technology

FTA, Office of Mobility Innovation, (2005a). Proceedings of the Federal Transit

FTA, Office of Research, Demonstration, and Innovation, (2005b). General Atomics low

Grossert, E. (2006). Actual development in guideway constructions at the example of the

Guangwei, S., Meisinger, R., & Gang, S. (2007). Modeling and simulation of Shanghai

(2002). Assessment of CHSST maglev for U.S. urban transpn., *U. S. Department of* 

development program Colorado maglev project, *U. S. Department of Transportation*,

Administration's urban maglev workshop, *U. S. Department of Transpn.*,

speed maglev technology development program (supplemental #3), *U.S.* 

Transrapid Munich project, *The 19th Int. Conf. on Magnetically Levitated Sys. and* 

maglev train Transrapid with random track irregularities. *Sonderdruck Schriftenreihe* 

*Acta Acustica united with Acustica*, Vol. 93, No. 4, pp. 589-601.

Report No. 295450-3, *U.S. Department of Transportation*.

VNTSC-FRA-02-13, *U.S. Department of Transportation*.

*der Georg-Simon-Ohm-Fachhochschule Nürnberg*, Nr. 39.

DOT-VNTSC-FRA-02-06, *U.S. Department of Transportation*.

Thesis, *Department of Civil Engineering, Case Western Reserve Uni*.

systems: a case-study for long-distance and high-speed maglev project in Mashhad-Tehran route. *The 1st International Conference on Railway Engineering, High-speed Railway, Heavy Haul Railway and Urban Rail Transit*, Beijing Jiaotong University, Beijing, China, China Railway Publishing House, pp. 73-83, ISBN 978-7-113-11751-

interaction in maglev systems. *ASME, Journal of Dynamic Systems, Measurement, and* 

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**10. References** 

1.

*Control*, Vol. 118, pp. 526-530.

*Transportation*.

*Transpn.*, Final Report.

Final Report.

Washington, DC.

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*Linear Drives*, Dresden, Germany.

loading of rails, is a combination of concentrated and distributed loads. However, live loading models for maglev trains, in the absence of wheels and as a result of uniformity in the intensity of lifting magnetic forces due to support magnets, are uniformly distributed on the guideways. The guideway loading is modeled as dynamic and uniformly distributed magnetic forces to account for the dynamic coupling between the vehicle and the guideway. In general, vertical loadings (dead and live) in the spans of maglev are much lower than those of the railroad bridges. The railroad bridge dead load is four times larger than the maglev guideway dead load, and the intensity of the uniformly distributed live load on the railroad bridge is almost four times that of the maglev guideway. Moreover, loading of guideway is four times that in the railroad bridge. One reason for this difference is the lower weight of the maglev vehicle due to the absence of wheels, axles and transmission parts plus the overall short length of the vehicle. The lateral force on the maglev guideway is also much lower than that on the railroad bridge. Also, it is predicted that on the straight routes as a result of negligible lateral magnetic force, there is no considerable amount of torsion created in the cross-section. Therefore, if the beam cross-section and the vertical loading are symmetrical, special design of guideway crosssections to overcome torsion, is not necessary. Moreover, there usually is no need for the design of deck-shaped cross-sections to care for tension lateral magnetic forces and for the moments due to vertical magnetic forces. Compared to the road and railway bridges, the amount of lateral earthquake force on maglev guideway is lower. Maglev guideways have high resistance against earthquake forces. Maglev vehicles are lighter compared to conventional railway vehicles. These lighter vehicles cause less centrifugal force. The absence of wheels and wheel/rail contact, lighter vehicles and presence of compensating magnetic forces opposing any lateral deviation are the main reasons behind the lower centrifugal forces. A distributed-load vehicle model is better than a concentrated-load model. Multicar vehicles have less car-body acceleration than does a single-car vehicle, because of intercar constraints. This indicates that the multicar vehicle would provide better ride comfort. Weight of required longitudinal bars of guideway is also one-fourth that in the railroad bridge. Deflections due to the vertical loads (dead and live) are also lower in guideways than in rail tracks. Torsion reduction, deflection reduction due to vertical loads, reduction in the costs of construction and operation, increase in resistance and technical justification, possibility of motion in higher speeds are among main reasons to utilize beams with a U-shaped cross-sections and structural continuity in the guideways. Therefore, as noticeable improvements and developments are made in structural optimization of these cross-sections, they could be considered as a good choice among other sections and could be used with a relatively high safety factor. Also, it is shown that the lower loads on the maglev guideway lead to lower bending moments and sheer forces in comparison with the railroad bridge. This indicates that the maglev support structure requires less mechanical strength than the railroad bridge support structure for the same loading pattern. A dynamic simulation for maglev vehicle/guideway interaction is essential to optimize the vehicle design and reduce the cost.

#### **9. Acknowledgment**

This chapter of book was performed and financially supported completely by Iran Maglev Technology (IMT).

loading of rails, is a combination of concentrated and distributed loads. However, live loading models for maglev trains, in the absence of wheels and as a result of uniformity in the intensity of lifting magnetic forces due to support magnets, are uniformly distributed on the guideways. The guideway loading is modeled as dynamic and uniformly distributed magnetic forces to account for the dynamic coupling between the vehicle and the guideway. In general, vertical loadings (dead and live) in the spans of maglev are much lower than those of the railroad bridges. The railroad bridge dead load is four times larger than the maglev guideway dead load, and the intensity of the uniformly distributed live load on the railroad bridge is almost four times that of the maglev guideway. Moreover, loading of guideway is four times that in the railroad bridge. One reason for this difference is the lower weight of the maglev vehicle due to the absence of wheels, axles and transmission parts plus the overall short length of the vehicle. The lateral force on the maglev guideway is also much lower than that on the railroad bridge. Also, it is predicted that on the straight routes as a result of negligible lateral magnetic force, there is no considerable amount of torsion created in the cross-section. Therefore, if the beam cross-section and the vertical loading are symmetrical, special design of guideway crosssections to overcome torsion, is not necessary. Moreover, there usually is no need for the design of deck-shaped cross-sections to care for tension lateral magnetic forces and for the moments due to vertical magnetic forces. Compared to the road and railway bridges, the amount of lateral earthquake force on maglev guideway is lower. Maglev guideways have high resistance against earthquake forces. Maglev vehicles are lighter compared to conventional railway vehicles. These lighter vehicles cause less centrifugal force. The absence of wheels and wheel/rail contact, lighter vehicles and presence of compensating magnetic forces opposing any lateral deviation are the main reasons behind the lower centrifugal forces. A distributed-load vehicle model is better than a concentrated-load model. Multicar vehicles have less car-body acceleration than does a single-car vehicle, because of intercar constraints. This indicates that the multicar vehicle would provide better ride comfort. Weight of required longitudinal bars of guideway is also one-fourth that in the railroad bridge. Deflections due to the vertical loads (dead and live) are also lower in guideways than in rail tracks. Torsion reduction, deflection reduction due to vertical loads, reduction in the costs of construction and operation, increase in resistance and technical justification, possibility of motion in higher speeds are among main reasons to utilize beams with a U-shaped cross-sections and structural continuity in the guideways. Therefore, as noticeable improvements and developments are made in structural optimization of these cross-sections, they could be considered as a good choice among other sections and could be used with a relatively high safety factor. Also, it is shown that the lower loads on the maglev guideway lead to lower bending moments and sheer forces in comparison with the railroad bridge. This indicates that the maglev support structure requires less mechanical strength than the railroad bridge support structure for the same loading pattern. A dynamic simulation for maglev vehicle/guideway interaction is essential to optimize the vehicle design and reduce the

This chapter of book was performed and financially supported completely by Iran Maglev

cost.

**9. Acknowledgment** 

Technology (IMT).

### **10. References**


Maglev 175

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**Part 2** 

**Modelling for Railway Infrastructure** 

**Design and Characterization** 


## **Part 2**

**Modelling for Railway Infrastructure Design and Characterization** 

176 Infrastructure Design, Signalling and Security in Railway

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guideways, *10th International Conference on Flud Control, Measurements, and* 

**7** 

*Colombia* 

**Power System Modelling for Urban Massive** 

Urban Massive Transportation Systems (UMTS), like metro, tramway, light train; requires the supply of electric power with high standards of reliability. So, an important step in the development of these transportation systems is the electric power supply system planning

Normally, the trains of a UMTS requires a DC power supply by means of rectifier AC/DC substations, know as traction substations (TS); that are connected to the electric HV/MV distribution system of a city. The DC system feeds catenaries of tramways or the third rail of metros, for example. The DC voltage is selected according to the system taking into account power demand and length of the railway's lines. Typically, a 600 Vdc – 750 Vdc is used in tramways; while 1500 Vdc is used in a metro system. Some interurban-urban

Fig. 1 presents an electric scheme of a typical traction substation (TS) with its main components: AC breakers at MV, MV/LV transformers, AC/DC rectifiers, DC breakers, traction DC breakers. As, it is shown, a redundant supply system is placed at each traction substation in order to improve reliability. In addition, some electric schemes allow the power supply of the catenaries connected to a specific traction substation (A) since the neighbour traction substation (B) by closing the traction sectioning between A and B and opening the traction DC breakers. In this way, the reliability supply is improved and allows

So, an important aspect for the planning and design of this electric power supply is a good estimation of power demand required by the traction system that will determine the required number, size and capacity of AC/DC rectifier substations. On the other hand, the design of the system requires studying impacts of the traction system on the performance of the distribution system and vice versa. Power quality disturbances are present in the

This chapter presents useful tools for modelling, analysis and system design of Electric Massive Railway Transportation Systems (EMRTS) and power supply from Distribution Companies (DisCo) or Electric Power Utilities. Firstly, a section depicting the modelling and simulation of the power demand is developed. Then, a section about the computation of

operation of these systems that could affect the performance of the traction system.

**1. Introduction** 

systems use a 3000 Vdc supply to the trains.

flexibility for maintenance of TS.

and design.

**Transportation Systems** 

Mario A. Ríos and Gustavo Ramos *Universidad de los Andes, Bogotá, D.C.,* 

## **Power System Modelling for Urban Massive Transportation Systems**

Mario A. Ríos and Gustavo Ramos *Universidad de los Andes, Bogotá, D.C., Colombia* 

### **1. Introduction**

Urban Massive Transportation Systems (UMTS), like metro, tramway, light train; requires the supply of electric power with high standards of reliability. So, an important step in the development of these transportation systems is the electric power supply system planning and design.

Normally, the trains of a UMTS requires a DC power supply by means of rectifier AC/DC substations, know as traction substations (TS); that are connected to the electric HV/MV distribution system of a city. The DC system feeds catenaries of tramways or the third rail of metros, for example. The DC voltage is selected according to the system taking into account power demand and length of the railway's lines. Typically, a 600 Vdc – 750 Vdc is used in tramways; while 1500 Vdc is used in a metro system. Some interurban-urban systems use a 3000 Vdc supply to the trains.

Fig. 1 presents an electric scheme of a typical traction substation (TS) with its main components: AC breakers at MV, MV/LV transformers, AC/DC rectifiers, DC breakers, traction DC breakers. As, it is shown, a redundant supply system is placed at each traction substation in order to improve reliability. In addition, some electric schemes allow the power supply of the catenaries connected to a specific traction substation (A) since the neighbour traction substation (B) by closing the traction sectioning between A and B and opening the traction DC breakers. In this way, the reliability supply is improved and allows flexibility for maintenance of TS.

So, an important aspect for the planning and design of this electric power supply is a good estimation of power demand required by the traction system that will determine the required number, size and capacity of AC/DC rectifier substations. On the other hand, the design of the system requires studying impacts of the traction system on the performance of the distribution system and vice versa. Power quality disturbances are present in the operation of these systems that could affect the performance of the traction system.

This chapter presents useful tools for modelling, analysis and system design of Electric Massive Railway Transportation Systems (EMRTS) and power supply from Distribution Companies (DisCo) or Electric Power Utilities. Firstly, a section depicting the modelling and simulation of the power demand is developed. Then, a section about the computation of

Power System Modelling for Urban Massive Transportation Systems 181

The power consumed by one railway vehicle depends on the velocity and acceleration that it has at each instant of time. Its computation is based on the traction effort characteristic (supplied by the manufacturer of the motors), the number of passengers and the distances between the passengers' stations (Vukan, 2007), (Chen et al., 1999), (Perrin & Vernard, 1991). The duty cycle of an urban train between two passengers' stations is composed by four operation states: acceleration, balancing speed, constant speed and deceleration. Fig. 2 shows the behavior of the speed, traction effort and power consumption of a traction vehicle

Fig. 2. Velocity, Traction Effort, and Power Consumption of an Urban Train Travel between

During the first state (I), the vehicle moves with constant positive acceleration, so the speed increases. When the vehicle reaches a determined speed lower than the constant speed, the second operation state starts. In this state, the acceleration decreases, but the speed keeps increasing. In the third state (III), the cruise speed is reached and the acceleration is zero. In the fourth state (IV), the braking operation starts with negative acceleration until the moment it decelerates with a constant rate and finally it stops at the destination station

The parametric construction of the traction and braking effort curves is based on the traction theory already implemented in locomotives and high speed rails. Three factors limit the traction effort versus velocity: the maximum traction effort *Fmax* conditioned by the number of passengers that are in the wagon, the maximum velocity of the vehicle, and the maximum power consumption. The maximum traction effort used by the acceleration, and then

*<sup>m</sup> axis wnnTMm axle* (1)

(Vukan, 2007), (Chen et al., 1999), (Perrin & Vernard, 1991), (Hsiang & Chen, 2001).

transferred to the rail, is limited by the total weight of the axles given by:

during each operation state elapsed either time or space (Hsiang & Chen, 2001).

**2.1 Power consumption model of an urban train** 

adjacent Passenger Stations (Hsiang & Chen, 2001)

**2.1.1 Net force of a traction vehicle** 

the placement and sizing of TS for urban railway systems is presented where the modelling is based on the power demand model of the previous section. After that, two sections about the power quality (PQ) impact of EMRTS on distribution systems and grounding design are presented. Both subjects make use of the load demand model presented previously.

Fig. 1. A Typical Traction Substation (TS)

### **2. Power demand computation of electric transportation systems**

This section presents a mathematical model useful to simulate urban railway systems and to compute the instantaneous power of the Electric Massive Railway Transportation Systems (EMRTS) such as a metro, light train or tramway, by means of computing models that take into account parameters such as the grid size, acceleration, velocity variation, EMRTS braking, number of wagons, number of passengers per wagon, number of rectifier substations, and passenger stations, among other factors, which permit to simulate the physical and electric characteristics of these systems in a more accurate way of a real system.

This model connects the physical and dynamic variables of the traction behaviour with electrical characteristics to determine the power consumption. The parametric construction of the traction and braking effort curves is based on the traction theory already implemented in locomotives and urban rails. Generally, there are three factors that limit the traction effort versus velocity: the maximum traction effort (*Fmax*) conditioned by the number of passengers that are in the wagons, the maximum velocity of the train (or rail), and the maximum power consumption. Based on these factors, a simulation model is formulated for computing the acceleration, speed and placement of each train in the railway line for each time step (1 second, for example). So, the power consumption or re-generation is computed also for each time step and knowing the placement of each train in the line, the power demand for each electric TS is calculated.

### **2.1 Power consumption model of an urban train**

180 Infrastructure Design, Signalling and Security in Railway

the placement and sizing of TS for urban railway systems is presented where the modelling is based on the power demand model of the previous section. After that, two sections about the power quality (PQ) impact of EMRTS on distribution systems and grounding design are

presented. Both subjects make use of the load demand model presented previously.

**2. Power demand computation of electric transportation systems** 

This section presents a mathematical model useful to simulate urban railway systems and to compute the instantaneous power of the Electric Massive Railway Transportation Systems (EMRTS) such as a metro, light train or tramway, by means of computing models that take into account parameters such as the grid size, acceleration, velocity variation, EMRTS braking, number of wagons, number of passengers per wagon, number of rectifier substations, and passenger stations, among other factors, which permit to simulate the physical and electric characteristics of these systems in a more accurate way of a real

This model connects the physical and dynamic variables of the traction behaviour with electrical characteristics to determine the power consumption. The parametric construction of the traction and braking effort curves is based on the traction theory already implemented in locomotives and urban rails. Generally, there are three factors that limit the traction effort versus velocity: the maximum traction effort (*Fmax*) conditioned by the number of passengers that are in the wagons, the maximum velocity of the train (or rail), and the maximum power consumption. Based on these factors, a simulation model is formulated for computing the acceleration, speed and placement of each train in the railway line for each time step (1 second, for example). So, the power consumption or re-generation is computed also for each time step and knowing the placement of each train in the line, the power

Fig. 1. A Typical Traction Substation (TS)

demand for each electric TS is calculated.

system.

The power consumed by one railway vehicle depends on the velocity and acceleration that it has at each instant of time. Its computation is based on the traction effort characteristic (supplied by the manufacturer of the motors), the number of passengers and the distances between the passengers' stations (Vukan, 2007), (Chen et al., 1999), (Perrin & Vernard, 1991). The duty cycle of an urban train between two passengers' stations is composed by four operation states: acceleration, balancing speed, constant speed and deceleration. Fig. 2 shows the behavior of the speed, traction effort and power consumption of a traction vehicle during each operation state elapsed either time or space (Hsiang & Chen, 2001).

Fig. 2. Velocity, Traction Effort, and Power Consumption of an Urban Train Travel between adjacent Passenger Stations (Hsiang & Chen, 2001)

During the first state (I), the vehicle moves with constant positive acceleration, so the speed increases. When the vehicle reaches a determined speed lower than the constant speed, the second operation state starts. In this state, the acceleration decreases, but the speed keeps increasing. In the third state (III), the cruise speed is reached and the acceleration is zero. In the fourth state (IV), the braking operation starts with negative acceleration until the moment it decelerates with a constant rate and finally it stops at the destination station (Vukan, 2007), (Chen et al., 1999), (Perrin & Vernard, 1991), (Hsiang & Chen, 2001).

### **2.1.1 Net force of a traction vehicle**

The parametric construction of the traction and braking effort curves is based on the traction theory already implemented in locomotives and high speed rails. Three factors limit the traction effort versus velocity: the maximum traction effort *Fmax* conditioned by the number of passengers that are in the wagon, the maximum velocity of the vehicle, and the maximum power consumption. The maximum traction effort used by the acceleration, and then transferred to the rail, is limited by the total weight of the axles given by:

$$m\_m = TM - \left(n\_{axis} - n\right) \times \omega\_{axle} \tag{1}$$

Power System Modelling for Urban Massive Transportation Systems 183

 *<sup>i</sup> F t*

The velocity is assumed an independent variable, which determines the path time of the traction vehicle, with steps fixed by velocity and acceleration (Jong & Chang, 2005b). So, the

*v v t t*

The motor torque and the velocity for an EMRTS are linear functions of the acceleration and the angular velocity. So, the instantaneous power consumption by the EMRTS, for the first three operative states (Chen et al., 1999), (Perrin & Vernard, 1991), (Hsiang & Chen, 2001), is:

*Pt B v v e B*

which describes the braking effort multiplied by the velocity in the range of 0≤*v*≤*vmax* and a multiplicative factor *ηB* which describes the efficiency of the regenerative braking which it is considered of 30% for this type of systems (Perrin & Vernard, 1991), (Jong & Chang, 2005a),

The model presented at section 2.1 allows the computation of the power consumption and travel time characteristics (*t, x*) for each train *i* in the railway line. Naturally, a railway line simulation must include a number *n* of passengers' stations and *k* trains travel in the line (go

The integration of these characteristics requires modelling the mobility of passengers associated at each train. It can be simulated in a probabilistic way, computing the number of passengers coming up and leaving the train (*i*) in each passenger's station (*j*) and the stopping time of the train in each station. This first part, stated here as Module 1, uses the following parameters: the passengers' up (*rup*) and down (*rdown*) rates, and up (*tup*) and down

The number of passengers in the first station and the number of passengers waiting in each station (*paxwait*) are modelled as random variables of uniform distribution. As, the railway line simulation includes a number *n* of passengers' stations; Module 1 computes for each

train *i* the number of passengers that the train transport between station *j* and *j+1* as:

1

*i i*

*i*

*a*

*TM t* (6)

(7)

*i i ii i* 1 1 *s s vt t* (8)

*P t TM t a t MR v v <sup>i</sup>* (9)

(10)

*a t*

1

For the last operative state where the braking acts, the consumption is given by:

*i i*

time steps and the incremental travelled distance are given by:

**2.1.3 Power consumption computation** 

(Hill, 2006).

and return).

**2.2 Simulation model** 

(*tup*) times per passenger.

where *TM* is the total vehicle mass, *n* is the number of motor drives, *naxis* the number of axles in the vehicle, and *waxle* the weight per axle (Buhrkall, 2006). The total vehicle mass is:

$$TM = w\_v + \left(n\_p \times w\_{pas}\right) \times M\_{DYN} \tag{2}$$

where *wv* corresponds to the weight per wagon without passengers, *np* the number of passengers per wagon, *wpas* the average weight per passenger, and *MDYN* the dynamic mass of the railway, which represents the stored energy in the spinning parts of the vehicle, typically of 5-10% (Buhrkall, 2006). Then, the maximum traction effort is calculated as:

$$F\_{\text{max}} = \mu \times m\_m \times \text{g} \tag{3}$$

Where *µ* corresponds to the friction coefficient between the wheels and the rail, which is about 15% for the ERMTS, and gravity *g* equals to 9.8 m/s2 (Buhrkall, 2006). The force needed to move a traction vehicle (*TM* times the acceleration (*a*)) is:

$$F = TM \times a = TM \frac{dv}{dt} = TE(v) - MR(v) - B\_e(v) \tag{4}$$

Where *TE(v)* is the traction effort in an EMRTS that provides the necessary propulsion to exceed inertia and accelerate the vehicle, *MR(v)* is the movement resistance as an opposite force to the vehicle movement, *Be(v)* is the braking effort used to decelerate the vehicle and stop it permanently (Vukan, 2007).

The traction and braking effort act directly in the vehicle wheels edges. The movement resistance is given by:

$$MR(v) = 10^{-3} \times \left(2.5 + 10^{-3} \times k(v + \Delta v)^2\right) \times TM \times \text{g} \tag{5}$$

Where *k≈0.33* for passengers' vehicles, *∆v*≈15km/h is the wind velocity variation, *TM* is the total mass of the vehicle, and g the gravity. Table 1 presents the action forces in an EMRTS that makes its path between two passengers' stations. As a result, there are four regimens of operation: stopping, acceleration, constant velocity, and deceleration. This is how the difference between the traction effort, the movement resistance, and the braking effort, which are not velocity variants, represent the net force of the vehicle (Jong & Chang, 2005b).


Table 1. Net Force and Velocity as function of the Operative Regimen (Jong & Chang, 2005b)

#### **2.1.2 Computation of dynamic variables**

The incremental acceleration (*ai*) is obtained from the net force and the total mass of the vehicle (Jong & Chang, 2005b) computed for each instant *t*, as:

$$a\_i(t) = \frac{F(t)}{TM(t)}\tag{6}$$

The velocity is assumed an independent variable, which determines the path time of the traction vehicle, with steps fixed by velocity and acceleration (Jong & Chang, 2005b). So, the time steps and the incremental travelled distance are given by:

$$t\_{i+1} = t\_i + \frac{v\_{i+1} - v\_i}{a\_i} \tag{7}$$

$$\mathbf{s}\_{i+1} = \mathbf{s}\_i + \upsilon\_i \left( t\_{i+1} - t\_i \right) \tag{8}$$

#### **2.1.3 Power consumption computation**

The motor torque and the velocity for an EMRTS are linear functions of the acceleration and the angular velocity. So, the instantaneous power consumption by the EMRTS, for the first three operative states (Chen et al., 1999), (Perrin & Vernard, 1991), (Hsiang & Chen, 2001), is:

$$P(t) = \left(TM(t) \times a\_i(t) + MR(v)\right) \times v \tag{9}$$

For the last operative state where the braking acts, the consumption is given by:

$$P(t) = B\_\varepsilon(\upsilon) \times \upsilon \times \eta\_B \tag{10}$$

which describes the braking effort multiplied by the velocity in the range of 0≤*v*≤*vmax* and a multiplicative factor *ηB* which describes the efficiency of the regenerative braking which it is considered of 30% for this type of systems (Perrin & Vernard, 1991), (Jong & Chang, 2005a), (Hill, 2006).

#### **2.2 Simulation model**

182 Infrastructure Design, Signalling and Security in Railway

where *TM* is the total vehicle mass, *n* is the number of motor drives, *naxis* the number of axles in the vehicle, and *waxle* the weight per axle (Buhrkall, 2006). The total vehicle mass is:

where *wv* corresponds to the weight per wagon without passengers, *np* the number of passengers per wagon, *wpas* the average weight per passenger, and *MDYN* the dynamic mass of the railway, which represents the stored energy in the spinning parts of the vehicle, typically of 5-10% (Buhrkall, 2006). Then, the maximum traction effort is calculated as:

> *F mg* max

Where *µ* corresponds to the friction coefficient between the wheels and the rail, which is about 15% for the ERMTS, and gravity *g* equals to 9.8 m/s2 (Buhrkall, 2006). The force

*dv F TM a TM TE v MR v B v*

Where *TE(v)* is the traction effort in an EMRTS that provides the necessary propulsion to exceed inertia and accelerate the vehicle, *MR(v)* is the movement resistance as an opposite force to the vehicle movement, *Be(v)* is the braking effort used to decelerate the vehicle and

The traction and braking effort act directly in the vehicle wheels edges. The movement

Where *k≈0.33* for passengers' vehicles, *∆v*≈15km/h is the wind velocity variation, *TM* is the total mass of the vehicle, and g the gravity. Table 1 presents the action forces in an EMRTS that makes its path between two passengers' stations. As a result, there are four regimens of operation: stopping, acceleration, constant velocity, and deceleration. This is how the difference between the traction effort, the movement resistance, and the braking effort, which are not velocity variants, represent the net force of the vehicle (Jong & Chang, 2005b).

Operative Regimen Net Force Velocity Stopping *TE(v) – MR(v) – Be(v)=0 v=0*  Acceleration *TE(v) – MR(v) – Be(v)>0 0 < v < vmax* Constant Velocity *TE(v) – MR(v) – Be(v)=0 v > 0*  Deceleration *TE(v) – MR(v) – Be(v)<0 0 < v < vmax*

Table 1. Net Force and Velocity as function of the Operative Regimen (Jong & Chang, 2005b)

The incremental acceleration (*ai*) is obtained from the net force and the total mass of the

needed to move a traction vehicle (*TM* times the acceleration (*a*)) is:

stop it permanently (Vukan, 2007).

**2.1.2 Computation of dynamic variables** 

vehicle (Jong & Chang, 2005b) computed for each instant *t*, as:

resistance is given by:

*TM w n w M <sup>v</sup> p pas DYN* (2)

() () () *<sup>e</sup>*

3 3 <sup>2</sup> *MR v*( ) 10 2.5 10 *k v v TM <sup>g</sup>* (5)

*dt* (4)

*<sup>m</sup>* (3)

The model presented at section 2.1 allows the computation of the power consumption and travel time characteristics (*t, x*) for each train *i* in the railway line. Naturally, a railway line simulation must include a number *n* of passengers' stations and *k* trains travel in the line (go and return).

The integration of these characteristics requires modelling the mobility of passengers associated at each train. It can be simulated in a probabilistic way, computing the number of passengers coming up and leaving the train (*i*) in each passenger's station (*j*) and the stopping time of the train in each station. This first part, stated here as Module 1, uses the following parameters: the passengers' up (*rup*) and down (*rdown*) rates, and up (*tup*) and down (*tup*) times per passenger.

The number of passengers in the first station and the number of passengers waiting in each station (*paxwait*) are modelled as random variables of uniform distribution. As, the railway line simulation includes a number *n* of passengers' stations; Module 1 computes for each train *i* the number of passengers that the train transport between station *j* and *j+1* as:

Power System Modelling for Urban Massive Transportation Systems 185

On the other hand, Module 2 considers the maximum velocity, the braking and traction effort curves as input variables. These curves are parameterized by means of (1), (2), and (3) and are given by manufacturers of traction equipment. Each curve is used to establish the net force at each operative regime, I to IV in Fig. 2. Fig. 4. shows an example of the simulation of placement and power consumption for a train in a metro line using a power

Finally, the simulation of Module 2 is run for the total number of *k* vehicles in the railway line, taking into account the dispatch time of each one. Then, the power consumption at each TS is computed as Fig. 5. shows. Each TS supplies the power to trains (going or returning)

Active Power (kW)

a) Graphical Interpretation of x(i,t) b) Graphical Interpretation of P(i,t)

<sup>0</sup> <sup>1000</sup> <sup>2000</sup> <sup>3000</sup> <sup>4000</sup> <sup>5000</sup> <sup>6000</sup> <sup>7000</sup> <sup>8000</sup> <sup>9000</sup> -1500

Time(s)

placed for its specific portion of the railway line (the DC section connected to the TS).

demand simulator reported at (Garcia et al., 2009).

<sup>0</sup> <sup>1000</sup> <sup>2000</sup> <sup>3000</sup> <sup>4000</sup> <sup>5000</sup> <sup>6000</sup> <sup>7000</sup> <sup>8000</sup> <sup>9000</sup> <sup>0</sup>

Time(s)

Fig. 4. Example of Simulation of Train *i* Travel – Module 2

Fig. 5. Simulation of Power Consumption of a Railway Line

Position(m)

$$\max\left(i,j\right) = \left(1 - r\_{down}\right) \times \max\left(i, j-1\right) + \max\_{unit}\left(j\right) \times r\_{up} \tag{11}$$

The number of passengers is constrained to be less or equal than the maximum capacity of passengers at the train. In addition, this module gives the stopping time for each train at each passenger's station (*tstop*(*i*,*j*)) based on passengers up and down times, as:

$$\mathbf{t}\_{stop}\left(\mathbf{i},j\right) = \mathbf{t}\_{down} \times \left(\mathbf{1} - r\_{down}\right) \times \max(\mathbf{i},j-\mathbf{1}) + \mathbf{t}\_{up} \times \max\_{uuit}(j) \times r\_{up} \tag{12}$$

The second part of the model, called Module 2, simulates the overall travel of train *i*. This means, the simulation gives the power consumption of train *i* for each instant of time *t* for a complete travel (go and return). At the same time, the placement (*x***(***t***)**) of the train is get for each *t*. If the line railway has a length *L*, then the total travel of one train is *2L*, and *x* will be between *0* and *L* in one sense and between *L* and *0* in the another sense.

So, Module 2 computes the train's time of travel between passengers' stations and the instantaneous power demand for one train based on equations (1) to (10) and the number of passengers and stopping time obtained from (11) and (12), respectively; as Fig. 3 shows. As, it is shown, the simulation considers the initial dispatch time and computes the initial value of passengers using the second term of equation (11).

Fig. 3. Simulation of Train *i* Travel – Module 2

The number of passengers is constrained to be less or equal than the maximum capacity of passengers at the train. In addition, this module gives the stopping time for each train at

The second part of the model, called Module 2, simulates the overall travel of train *i*. This means, the simulation gives the power consumption of train *i* for each instant of time *t* for a complete travel (go and return). At the same time, the placement (*x***(***t***)**) of the train is get for each *t*. If the line railway has a length *L*, then the total travel of one train is *2L*, and *x* will be

So, Module 2 computes the train's time of travel between passengers' stations and the instantaneous power demand for one train based on equations (1) to (10) and the number of passengers and stopping time obtained from (11) and (12), respectively; as Fig. 3 shows. As, it is shown, the simulation considers the initial dispatch time and computes the initial value

each passenger's station (*tstop*(*i*,*j*)) based on passengers up and down times, as:

between *0* and *L* in one sense and between *L* and *0* in the another sense.

Computation the travel of train *i* between stations *j* and *j+1* using (1) to (8)

Computation of power consumption travel of train *i* between stations *j* and *j+1* using (9) and (10) considering the Operative Regimen (Table 1)

> Update travel vectors: Placement x(i,t) Power Consumption P(i,t) Update Total travel time

Fig. 3. Simulation of Train *i* Travel – Module 2

of passengers using the second term of equation (11).

Initial data: Placement of passenger's stations *x(j)* Train characteristics (number of wagons, axles and motors; weight of wagons, axles and motors), efficiency of the regenerative braking.

, 1 ( , 1) ( ) *down wait up pax i j r pax i j pax j r* (11)

, 1 (, 1) ( ) *stop down down up wait up t i j t r pax i j t pax j r* (12)

Simulation for Train *i* Initial values: Passenger station *j*=1 Computes *pax(i,j)* Total travel time=*tdispatch*

> Last Passengers' station?

Add to Total travel time the stopping time of train *i* at station *j+1.* Computes *pax(i,j+1)*.

End

yes

j = j +1

no

On the other hand, Module 2 considers the maximum velocity, the braking and traction effort curves as input variables. These curves are parameterized by means of (1), (2), and (3) and are given by manufacturers of traction equipment. Each curve is used to establish the net force at each operative regime, I to IV in Fig. 2. Fig. 4. shows an example of the simulation of placement and power consumption for a train in a metro line using a power demand simulator reported at (Garcia et al., 2009).

Finally, the simulation of Module 2 is run for the total number of *k* vehicles in the railway line, taking into account the dispatch time of each one. Then, the power consumption at each TS is computed as Fig. 5. shows. Each TS supplies the power to trains (going or returning) placed for its specific portion of the railway line (the DC section connected to the TS).

Fig. 4. Example of Simulation of Train *i* Travel – Module 2

Fig. 5. Simulation of Power Consumption of a Railway Line

Power System Modelling for Urban Massive Transportation Systems 187

In this section, a methodology of placement and sizing of traction substations under an electric connection scheme, in which high reliable levels are guaranteed, is presented. In this scheme, each traction substation (TS) is able to support the load of each adjacent substation. That means that in the case when a fault occurs in one TS, there is a support system based on automatic switches normally opened that close and allow the two neighbour substations to supply the power to the associated load with the faulted substation (each one would feed half of the load of the faulted one). The input data to calculate the sizing of substation is obtained from the power demand computation,

On the other hand, the placement of each TS is obtained by a heuristic optimization problem. This problem minimizes the total cost of a given configuration, that is composed of investment costs (rectifiers, transformers, and protection and control cells), the cost of energy losses composed by AC losses (associated with the transformer) and DC losses (associated to rectifiers) and the failure cost, that represents the cost of the annual expected

A scheme of supply of an urban railway system must satisfy electric conditions, such as: operating limits, voltage drops through the catenaries or third rail (called here, in general, DC section), and maximum capacity of transformers. These conditions must be satisfied for supplying the power demand independently of the operating state of the system, i.e., normal state or a post-contingency state after a fault of a HV/MV substation, or TS, or one DC section. So, the TS location and configuration's selection are strongly linked problems. Fig. 8 shows three possible schemes of connection of the MV network to a set of TS. Each TS

The way of behave in a fault condition determines the following three possible

1. **One transformer-rectifier unit with possibility of power supply from the adjacent TS**. Each TS acts as a support of its adjacent TS. This implies that the substations must be able to supply at least 1.5 times the length of the normal DC section length (3L/2). 2. **Two transformer-rectifier units in each traction substation**. This configuration means the redundancy in the main equipment of the TS. In case of a fault in one transformer and/or rectifier, the parallel unit must supply the total power demand of the TS. This scheme assumes that there is not possibility of support of adjacent substations. The wide dotted line if Fig. 8 remarks the parallel unit of transformer-

3. **Two transformer-rectifier units in each TS and support of adjacent DC section**. This is the combination of configurations 1 and 2. This means that there is redundancy in each traction substation and there is also possibility of support of adjacent DC section

is designed to supply (in normal operation state) a DC sector of length L.

**3. Placement and sizing traction (rectifier) substations in urban railway** 

**systems** 

explained in the previous section.

energy not supplied (EENS).

configurations:

rectifier unit.

feeder.

**3.1 Traction substation (TS) configurations** 

### **2.3 Simulation example**

This section illustrates the application of the power consumption mathematical and simulation model in a possible metro line for the city of Bogota of 13.2 km and 13 passenger stations. Fig. 6 shows one section of the possible line 1 to be developed in Bogotá. Fig. 7. presents the results of a simulation of the Metro Line of Fig. 6 using the previous algorithms.

Fig. 6. Example Case of Power Consumption for a Metro Line

Fig. 7. Power Demand of a Traction Substation – Estimation by Simulation

The simulation establishes the trajectories of 17 trains-vehicles at the Metro Line (Fig. 7.a). The power is supplied by 3 TS. Fig. 7.b shows the power demand at the first traction substation that supplies all trains placed between position 0<x(t)<4400 m.

This section illustrates the application of the power consumption mathematical and simulation model in a possible metro line for the city of Bogota of 13.2 km and 13 passenger stations. Fig. 6 shows one section of the possible line 1 to be developed in Bogotá. Fig. 7. presents the results of a simulation of the Metro Line of Fig. 6 using the

Calle\_19

<sup>0</sup> <sup>1000</sup> <sup>2000</sup> <sup>3000</sup> <sup>4000</sup> <sup>5000</sup> <sup>6000</sup> <sup>7000</sup> <sup>8000</sup> <sup>9000</sup> -2000

(seg)

Consumo de Potencia de la Subestacion Rectificadora No: 1

NQS

Av\_Carrera\_22

Plaza\_Bolivar

Zona \_Industrial

**2.3 Simulation example** 

previous algorithms.

Portal\_Am

ericas Kennedy Tim

 iza

> A

v\_Villavicencio

Plaza\_Am

Fig. 6. Example Case of Power Consumption for a Metro Line

Av\_68

Canal\_Fucha

a) Train's Trajectories x(i,t) b) Power Demand P(i,t) substation 1

The simulation establishes the trajectories of 17 trains-vehicles at the Metro Line (Fig. 7.a). The power is supplied by 3 TS. Fig. 7.b shows the power demand at the first traction

Fig. 7. Power Demand of a Traction Substation – Estimation by Simulation

substation that supplies all trains placed between position 0<x(t)<4400 m.

(kW)

Tranv\_49A

 ericas

### **3. Placement and sizing traction (rectifier) substations in urban railway systems**

In this section, a methodology of placement and sizing of traction substations under an electric connection scheme, in which high reliable levels are guaranteed, is presented. In this scheme, each traction substation (TS) is able to support the load of each adjacent substation. That means that in the case when a fault occurs in one TS, there is a support system based on automatic switches normally opened that close and allow the two neighbour substations to supply the power to the associated load with the faulted substation (each one would feed half of the load of the faulted one). The input data to calculate the sizing of substation is obtained from the power demand computation, explained in the previous section.

On the other hand, the placement of each TS is obtained by a heuristic optimization problem. This problem minimizes the total cost of a given configuration, that is composed of investment costs (rectifiers, transformers, and protection and control cells), the cost of energy losses composed by AC losses (associated with the transformer) and DC losses (associated to rectifiers) and the failure cost, that represents the cost of the annual expected energy not supplied (EENS).

### **3.1 Traction substation (TS) configurations**

A scheme of supply of an urban railway system must satisfy electric conditions, such as: operating limits, voltage drops through the catenaries or third rail (called here, in general, DC section), and maximum capacity of transformers. These conditions must be satisfied for supplying the power demand independently of the operating state of the system, i.e., normal state or a post-contingency state after a fault of a HV/MV substation, or TS, or one DC section. So, the TS location and configuration's selection are strongly linked problems. Fig. 8 shows three possible schemes of connection of the MV network to a set of TS. Each TS is designed to supply (in normal operation state) a DC sector of length L.

The way of behave in a fault condition determines the following three possible configurations:


Power System Modelling for Urban Massive Transportation Systems 189

1 ( ) , , *m op Energy loss loss i C j Cost j AC i j DC i j* 

*loss iron loss copper loss*

On the other hand, the DC losses are power losses in the rectifiers (AC/DC converters):

*P i <sup>j</sup> <sup>t</sup> AC i j t P i UF j t P i P i*

 0

*To loss dem*

0

instantaneous demanded power (*Pdem(i,j,t)*) and the transformer rating (*Pnom*).

*cooper loss nom Cu nom Cu*

*o*

power demanded at year *j* hour *t*. It varies from 95.4% to 95.7% (Hill, 2006).

**3.3 Technical constraints** 

\* In the case of regenerative braking, 800 V is admissible. \*\* In the case of regenerative braking, 800 V is admissible. Table 2. Voltages in DC Traction Systems (White, 2009).

*o*

*To*

*To* is the operation time of the urban rail during the year. The "iron losses" in the transformer are constant (Institution of Electrical and Electronic Engineers [IEEE], 2007) and computed as it is established in (IEEE, 1992). The "copper losses" are directly proportional to the square of the utilization factor (*UF*), and the constant of proportionality is the nominal copper losses of the transformer (*Pnom\_Cu*) (IEEE, 2007). The *UF* is defined as the ratio of

<sup>1</sup> , , (, ,)

*AC i j AC i j AC i j t dt <sup>T</sup>* (16)

*DC i j eff i j t P i j t dt <sup>T</sup>* (18)

*C T PC ENS NS av fault* (19)

2 \_ \_ (, ,) (, ,) ( ( , )) *dem*

<sup>1</sup> , 1 ( , , ) ( , , ))

The *eff(i,j,t)* is the DC efficiency of the rectifier of the TS *i* and depends on the instantaneous

The third term of the objective function of the minimization problem is the cost of energy not supplied (*CENS*), computed as function of the time of no-supply in hours/year (*TNS*), the unitary cost of fault in USD\$/kWh (*Cfault*) and the average power not supplied by TS (*Pav*):

The voltage drop between a supply point and a utilization point must not be more than 15% in normal operation and as maximum 30% in special cases (Arriagada & Rudnick, 1994). These specials cases may be the outage of a substation or the last DC section in the route. Table 2 presents the voltage margins according to the different used DC system voltages.

DC system voltage (V) 600 750 1500 3000 Lowest voltage. Undefined duration (V) 400 500 1000 2000 Nominal design system voltage (V) 600 750 1500 3000 Highest voltage. Undefined duration (V) 720 900 1800 3600 Not-permanent highest voltage. Duration of 5 minutes (V) 770\* 950\*\* 1950 3900

2

(17)

*nom*

(15)

Fig. 8. Configurations of Traction Substations' Connection

#### **3.2 Optimization problem**

A minimization of the total project cost is solved for determining the quantity of traction substations, their connection configurations, and their locations. The optimization is a constrained problem that guarantees the electrical requirements, like voltage levels and high reliability requirements. The distance between TS is assumed to be equal, and each TS is located at the middle point of the DC section that it supplies, as Fig. 8 shows.

The cost function (*TC*) includes investment costs, operation costs *Cop* (associated with losses) and reliability cost or cost of energy not supplied (*CENS*). So, the total cost for each configuration is given by:

$$TC = C\_{inv} + \sum\_{j=1}^{T} \left( \frac{C\_{op}(j)}{(1+r)^j} + \frac{C\_{ENS}(j)}{(1+r)^j} \right) \tag{13}$$

Where *T* is the number of years of the project, and *r* is the discount rate of the project. The investment cost depends on the length of the DC network, and is given by:

$$\mathbf{C}\_{inv} = \left(\mathbf{L}\_{cat} \times \mathbf{C}\_{cat}\right) + \sum\_{i=1}^{m} \left(\mathbf{N}\_{Mod}(i) \times \mathbf{C}\_{Mod}(i) + \mathbf{C}\_{Place}(i)\right) \tag{14}$$

Where, *Lcat* and *Ccat* are the total length and the unitary cost of the catenaries or rail (DC section, in general). *NMod* is the number of modules in one traction substation (1 or 2). *CMod* is the cost associated to one module; *Cplace* is the cost of the terrain where the substation is built; *m* is the number of substations.

The annual operation cost (*Cop(j)*) is computed as the sum of annual AC and DC losses in the year *j* multiplied by the energy cost. Transformer losses are defined as the sum of the instantaneous iron losses (*ACiron-loss*) and copper losses (*ACcopper-loss*) during the year. Then, the total losses cost for *m* substations is:

A minimization of the total project cost is solved for determining the quantity of traction substations, their connection configurations, and their locations. The optimization is a constrained problem that guarantees the electrical requirements, like voltage levels and high reliability requirements. The distance between TS is assumed to be equal, and each TS is

The cost function (*TC*) includes investment costs, operation costs *Cop* (associated with losses) and reliability cost or cost of energy not supplied (*CENS*). So, the total cost for each

> ( ) ( ) (1 ) (1 )

(14)

(13)

*op ENS*

*inv j j <sup>j</sup> C j C j TC C*

( ) () () ()

Where *T* is the number of years of the project, and *r* is the discount rate of the project. The

*C L C N iC iC i* 

Where, *Lcat* and *Ccat* are the total length and the unitary cost of the catenaries or rail (DC section, in general). *NMod* is the number of modules in one traction substation (1 or 2). *CMod* is the cost associated to one module; *Cplace* is the cost of the terrain where the substation is built;

The annual operation cost (*Cop(j)*) is computed as the sum of annual AC and DC losses in the year *j* multiplied by the energy cost. Transformer losses are defined as the sum of the instantaneous iron losses (*ACiron-loss*) and copper losses (*ACcopper-loss*) during the year. Then, the

*r r*

1

1

*i*

*m inv cat cat Mod Mod Place*

*T*

located at the middle point of the DC section that it supplies, as Fig. 8 shows.

investment cost depends on the length of the DC network, and is given by:

Fig. 8. Configurations of Traction Substations' Connection

**3.2 Optimization problem** 

configuration is given by:

*m* is the number of substations.

total losses cost for *m* substations is:

$$\text{CC}\_{op}(j) = \text{Cost}\_{Energy}(j) \times \sum\_{i=1}^{m} \left( A \text{C}\_{loss} \left( i, j \right) + D \text{C}\_{loss} \left( i, j \right) \right) \tag{15}$$

$$AC\_{loss}\left(\mathbf{i}\_{\prime},\mathbf{j}\right) = \frac{1}{T\_o} \times \int\_0^{To} \left(AC\_{iron-loss}\left(\mathbf{i}\_{\prime},\mathbf{j}\right) + AC\_{copper-loss}\left(\mathbf{i}\_{\prime},\mathbf{j},\mathbf{t}\right)\right) d\mathbf{t} \tag{16}$$

*To* is the operation time of the urban rail during the year. The "iron losses" in the transformer are constant (Institution of Electrical and Electronic Engineers [IEEE], 2007) and computed as it is established in (IEEE, 1992). The "copper losses" are directly proportional to the square of the utilization factor (*UF*), and the constant of proportionality is the nominal copper losses of the transformer (*Pnom\_Cu*) (IEEE, 2007). The *UF* is defined as the ratio of instantaneous demanded power (*Pdem(i,j,t)*) and the transformer rating (*Pnom*).

On the other hand, the DC losses are power losses in the rectifiers (AC/DC converters):

$$AC\_{\text{copper}-loss}(i, j, t) = P\_{\text{nom\\_Cu}}(i) \times \left( \text{LIF}(j, t) \right)^2 = P\_{\text{nom\\_Cu}}(i) \times \left( \frac{P\_{\text{dem}}(i, j, t)}{P\_{\text{nom}}(i)} \right)^2 \tag{17}$$

$$DC\_{loss}\left(i,j\right) = \frac{1}{T\_o} \times \int\_0^{T\_o} \left(1 - \epsilon \mathcal{G}\left(i,j,t\right)\right) \times P\_{dem}\left(i,j,t\right) \right) dt\tag{18}$$

The *eff(i,j,t)* is the DC efficiency of the rectifier of the TS *i* and depends on the instantaneous power demanded at year *j* hour *t*. It varies from 95.4% to 95.7% (Hill, 2006).

The third term of the objective function of the minimization problem is the cost of energy not supplied (*CENS*), computed as function of the time of no-supply in hours/year (*TNS*), the unitary cost of fault in USD\$/kWh (*Cfault*) and the average power not supplied by TS (*Pav*):

$$\mathbf{C}\_{\rm ENS} = T\_{\rm NS} \times P\_{\rm av} \times \mathbf{C}\_{\rm fault} \tag{19}$$

#### **3.3 Technical constraints**

The voltage drop between a supply point and a utilization point must not be more than 15% in normal operation and as maximum 30% in special cases (Arriagada & Rudnick, 1994). These specials cases may be the outage of a substation or the last DC section in the route. Table 2 presents the voltage margins according to the different used DC system voltages.


\* In the case of regenerative braking, 800 V is admissible.

\*\* In the case of regenerative braking, 800 V is admissible.

Table 2. Voltages in DC Traction Systems (White, 2009).

Power System Modelling for Urban Massive Transportation Systems 191

*P P t It Lt It Lt* 

*Ij* is the current in each DC section that is defined as the catenaries/rail between two vehicles or between a vehicle and the TS (in the case of the nearest vehicle to the feeding point of the TS). The total losses at the DC section takes into account all vehicles placed at left and right of the TS. is the resistivity of the DC section [Ω/km or Ω/mi]; *To* is the total annual operation time.

The analysis was developed for the metro line showed in Fig. 6 corresponding to the study case of section 2.3. The study was developed as function of the number of substations and

The unitary cost of fault was assumed 1074 US\$/kWh, from reliability analysis. Simulations were done for three levels of load: high (the maximum number of vehicles in service), medium (half of the total vehicles in service), and low (with no vehicles in service). The simulator allows the calculation of power losses in N-0 state, and the demand of each

Simple contingencies (N-1) at the maximum load were made in order to sizing the TS when configurations 1 and 3 are used, to give support of adjacent TS. While, normal state

Table 3 presents the total cost computed as function of the number of TS and configuration of connection. Additionally, the investment cost (C\_inv) and the net present value of the

The investment cost (without the cost of catenaries/rail that is common for all alternatives), noted C\_inv, includes the switchgear in SF6, rectifiers, transformers, having into account the number of each equipment depending on the configuration (see Fig. 8). The NPV\_Oper

In the second column, in brackets, the rating commercial capacity of each substation is shown, based on the results of simulations and the algorithm for finding catenaries/rail losses. The capacities of each substation for configurations 1 and 3 are the same, due to the

> 1 (5MW) 8.8 6.11 0.81 7.95 2 (4 MW) 4.4 9.75 1.63 12.4 3 (5MW) 8.8 11.9 1.62 14.5

1 (5 MW) 6.6 6.73 0.90 8.65 2 (3.75MW) 3.3 12.3 1.79 15.1 3 (5 MW) 6.6 13.0 1.79 15.8

1 (3.75MW) 5.28 7.97 0.98 9.97 2 (3.75MW) 2.64 14.3 1.97 17.3 3 (3.75MW) 5.28 15.4 1.96 18.3

operation cost (NPV\_Oper) is shown. The fault cost was of 155.000 USD\$/year.

Maximum length of catenary/rail (km)

Table 3. Cost Comparison of Several Configuration of TS's Connections – Study Case

includes the operation cost for a useful life of the project of 20 years.

2 2

(26)

 

Millions of dollars C\_inv NPV\_Oper Total Cost

() () () () ()

'

**3.4 Application to the study case** 

the three possible configurations explained in section 3.1.

substation for N-0 and N-1 contingencies state.

operation was used for sizing TS in configuration 2.

high electrical similitude between both schemes.

#TS's Configuration

3

4

5

(rating/TS)

*To To n n LOSS loss j j j j t tj j*

0 01 1

A voltage drop of 30% between the TS and the last vehicle can be tolerated in a suburban system, where the vehicles are constantly accelerating, but a voltage drop over the principal line of a *metro* during any time interval might exceed all the established limits. Therefore, the maximum voltage drop allowed is limited to 15% on nominal voltages under normal conditions. A voltage drop in the farthest point of a section supplied by TS is defined as:

$$V\_T = V\_S - L\_2 Z n I - Z\_x (n + n') I - \frac{1}{4} (Z n \times I \times L \text{Cat}(i) - Z \times L\_2) \tag{20}$$

$$Z\_x = (R\_u + R\_T)\cos\phi + (X\_u + X\_T)\sin\phi \quad \text{and} \quad Z = R\cos\phi + X\sin\phi \tag{21}$$

Where *Vs* is the DC voltage at the TS (p.u), *VT* is the minimum DC voltage in the DC section for correct vehicle operation (p.u.); *I* is the current demanded by a vehicle (p.u.); *Ru* and *Xu* are the equivalent resistance and reactance, respectively (p.u.); *RT* and *XT* are the transformer resistance and reactance, respectively (p.u.); is the angle of power factor (zero for DC systems); *R* and *X* are the DC section resistance and reactance, including the return way, in p.u./mi; *L2* is the distance between the TS and the nearest vehicle at the right; *n* and *n'* are the number of vehicles at the right and the left, respectively, of the TS.

Voltage drop in the farthest point is determined by the maximum length of the sector supplied. In normal conditions, this value is the length *L* (see Fig. 8). However, when a contingency occurs, the sector length must be modified to almost twice the original length. Then, for normal conditions, the voltage must satisfy:

$$V\_T \le V\_S(i) - Z(i, L \mid \mathcal{D}) \times I\_{TS}(i) \tag{22}$$

Where *ITS* is the current delivered by the TS depending on the number of vehicles in sector *i* supplied in a determined time by the substation. Under a contingency of the TS, the voltage must satisfy the constraint for the sector *i-1* and sector *i+1* (adjacent sectors):

$$V\_T(i \pm 1) \le V\_S(i \pm 1) - Z(i \pm 1, \Im L \ne 2) \times I\_{TS}(i \pm 1) \tag{23}$$

The minimum capacity of transformers and rectifiers is calculated from the maximum demanded current in each TS. The transformers and rectifiers size must be chosen as the nearest superior value to the demanded power, depending on the commercial capacities. As previously, normal conditions and post-contingency operation must be considered. In normal operation with 2 transformers, the power capacity of transformers must satisfy:

$$\Pr\left(\text{MVV}\left(\text{i}\right)\right) \ge I\_{\text{TS}}\left(\text{i}, L\right) \times V\_{\text{DC}} + P\_{\text{Loss}}\left(\text{L}\right) \tag{24}$$

Meanwhile, when the traction substation *i* is unavailable, the capacity of active power of the 2 transformers in the *i-1* and *i+1* sector must satisfy:

$$\Pr\left(\text{MWV}\right)\left(\mathbf{i}\pm\mathbf{1}\right) \ge I\_{\text{TS}}\left(\mathbf{i}\pm\mathbf{1}, \Im\left.\mathbf{L}\right/\mathbf{2}\right) \times V\_{\text{DC}} + P\_{\text{Loss}}\left(\Im\mathbf{L}/\mathbf{2}\right) \tag{25}$$

The capacity in MVA of the transformer is computed dividing the capacity in MW by the power factor (p.f.). As shown in (24) and (25), the power loss (*Ploss*) in the DC section feeder for the maximum demand must be determined for each section. The total power loss in DC section associated to the TS for a round trip is:

$$P\_{LOSS} = \sum\_{t=0}^{To} P\_{loss}(t) = \sum\_{t=0}^{To} \left[ \sum\_{j=1}^{n^\star} I\_j(t)^2 \times \rho \times L\_j(t) + \sum\_{j=1}^n I\_j(t)^2 \times \rho \times L\_j(t) \right] \tag{26}$$

*Ij* is the current in each DC section that is defined as the catenaries/rail between two vehicles or between a vehicle and the TS (in the case of the nearest vehicle to the feeding point of the TS). The total losses at the DC section takes into account all vehicles placed at left and right of the TS. is the resistivity of the DC section [Ω/km or Ω/mi]; *To* is the total annual operation time.

### **3.4 Application to the study case**

190 Infrastructure Design, Signalling and Security in Railway

A voltage drop of 30% between the TS and the last vehicle can be tolerated in a suburban system, where the vehicles are constantly accelerating, but a voltage drop over the principal line of a *metro* during any time interval might exceed all the established limits. Therefore, the maximum voltage drop allowed is limited to 15% on nominal voltages under normal conditions. A voltage drop in the farthest point of a section supplied by TS is defined as:

*Z R R X X and Z R X x uT uT* ( )cos ( )sin

Where *Vs* is the DC voltage at the TS (p.u), *VT* is the minimum DC voltage in the DC section for correct vehicle operation (p.u.); *I* is the current demanded by a vehicle (p.u.); *Ru* and *Xu* are the equivalent resistance and reactance, respectively (p.u.); *RT* and *XT* are the transformer

systems); *R* and *X* are the DC section resistance and reactance, including the return way, in p.u./mi; *L2* is the distance between the TS and the nearest vehicle at the right; *n* and *n'* are

Voltage drop in the farthest point is determined by the maximum length of the sector supplied. In normal conditions, this value is the length *L* (see Fig. 8). However, when a contingency occurs, the sector length must be modified to almost twice the original length.

Where *ITS* is the current delivered by the TS depending on the number of vehicles in sector *i* supplied in a determined time by the substation. Under a contingency of the TS, the voltage

The minimum capacity of transformers and rectifiers is calculated from the maximum demanded current in each TS. The transformers and rectifiers size must be chosen as the nearest superior value to the demanded power, depending on the commercial capacities. As previously, normal conditions and post-contingency operation must be considered. In normal operation with 2 transformers, the power capacity of transformers must satisfy:

Meanwhile, when the traction substation *i* is unavailable, the capacity of active power of the

The capacity in MVA of the transformer is computed dividing the capacity in MW by the power factor (p.f.). As shown in (24) and (25), the power loss (*Ploss*) in the DC section feeder for the maximum demand must be determined for each section. The total power loss in DC

the number of vehicles at the right and the left, respectively, of the TS.

must satisfy the constraint for the sector *i-1* and sector *i+1* (adjacent sectors):

resistance and reactance, respectively (p.u.);

Then, for normal conditions, the voltage must satisfy:

2 transformers in the *i-1* and *i+1* sector must satisfy:

section associated to the TS for a round trip is:

2 2

<sup>1</sup> ( ') ( () ) <sup>4</sup> *V V L Zn I Z n n I Zn I LCat i Z L T S <sup>x</sup>* (20)

( ) ( , /2) ( ) *V V i ZiL I i T S TS* (22)

( 1) ( 1) ( 1,3 / 2) ( 1) *V i V i Zi L I i <sup>T</sup> <sup>S</sup> TS* (23)

( )( ) ( , ) ( ) *CapT MW i I i L V P L TS DC Loss* (24)

( )( 1) ( 1,3 / 2) (3 /2) *CapT MW i I i L V P L TS DC Loss* (25)

cos sin (21)

is the angle of power factor (zero for DC

The analysis was developed for the metro line showed in Fig. 6 corresponding to the study case of section 2.3. The study was developed as function of the number of substations and the three possible configurations explained in section 3.1.

The unitary cost of fault was assumed 1074 US\$/kWh, from reliability analysis. Simulations were done for three levels of load: high (the maximum number of vehicles in service), medium (half of the total vehicles in service), and low (with no vehicles in service). The simulator allows the calculation of power losses in N-0 state, and the demand of each substation for N-0 and N-1 contingencies state.

Simple contingencies (N-1) at the maximum load were made in order to sizing the TS when configurations 1 and 3 are used, to give support of adjacent TS. While, normal state operation was used for sizing TS in configuration 2.

Table 3 presents the total cost computed as function of the number of TS and configuration of connection. Additionally, the investment cost (C\_inv) and the net present value of the operation cost (NPV\_Oper) is shown. The fault cost was of 155.000 USD\$/year.

The investment cost (without the cost of catenaries/rail that is common for all alternatives), noted C\_inv, includes the switchgear in SF6, rectifiers, transformers, having into account the number of each equipment depending on the configuration (see Fig. 8). The NPV\_Oper includes the operation cost for a useful life of the project of 20 years.

In the second column, in brackets, the rating commercial capacity of each substation is shown, based on the results of simulations and the algorithm for finding catenaries/rail losses. The capacities of each substation for configurations 1 and 3 are the same, due to the high electrical similitude between both schemes.


Table 3. Cost Comparison of Several Configuration of TS's Connections – Study Case

Power System Modelling for Urban Massive Transportation Systems 193

Fig. 9. PQ Phenomena and Railways' Electrical System Components Relationships

The identification of PQ problems in power systems represents an important issue to the distribution utilities. The harmonic distortion is one of the main PQ phenomena in the electrical system feeding an EMRTS because the injection of harmonics by its nonlinear loads flows through the network and affects other consumers connected to the distribution system. According to the conceptual diagram of Fig. 9, the production of harmonics in the EMRTS is a PQ phenomenon at steady state caused by the rectifier substations, normally, a

In addition, the computation of the total harmonic distortion (THD) in the AC side of the rectifier substation at the railway system must take into account the time load variability at each TS. So, the instantaneous power load must be computed as function of time and distance as it was explained at section 2. Once the current consumption in each TS is

Generally, deterministic models have been adopted for network harmonic analysis; however, these models can fail for modelling the load variation in systems such as the railways' electrical system (Chang et al., 2009). So, a probabilistic analysis to characterize the harmonic current loads properly must be used in order to obtain an accurate model.

An EMRTS is characterized by fluctuating loads due to the different operation states of the trains in the traction system (See Fig. 7 b). Thus, the harmonics injection from the rectifier substations to the MV network causes that the current harmonic spectrum at the distribution system's connection point (PCC) varies over time. So, each traction substation can be represented as a harmonic current source that provides a probabilistic spectral content at the

obtained, it is possible to identify the variation of the THD during the time.

**4.2 Harmonic distortion analysis** 

controlled rectifier of 6 or 12 pluses.

**4.2.1 Probabilistic model** 

PCC (Rios et al., 2009).

The third column shows the maximum length of the DC section that each TS can supply. TS in configurations 1 and 3 must have a capacity to supply even twice the total length of the line divided by the number of considered substations. Instead, TS in configuration 2 supply the maximum length of catenaries/rail, just the normal operation length because this configuration is not able of supporting of adjacent substation in case of fault.

The lowest total cost at Table 3 is presented in the case of three 5 MW TS because, in the study case of section 2.3, the investment cost weights more in the final cost than the operation cost. That is, looking just the configuration 1, it is evident that even though the operation costs do not grow up linearly as more TS are considered, the difference between investment costs is higher than operation costs, so the optimal solution is the location of 3 TS of 5 MW, under the configuration 1.

### **4. Power quality impact of urban railway systems on distribution systems**

Power quality phenomena originated in power distribution systems impacts on the electrical power supply system of UMTS and, at the same time, power electronics used in the traction system impacts on the power quality (PQ) service of the distribution system.

In addition, the power demand of UMTS presents high and fast variations as consequence of the operation cycles of each train-vehicle and the non-coincidence of operational cycles among several vehicles. So, PQ phenomena are time variable (Singh et al., 2006).

### **4.1 PQ Phenomena and railways' electrical system components**

Fig. 9 shows the existing relationships between the different PQ phenomena and the railways' electrical system components. As it is shown, the main electrical components in the railway system are: the train-vehicle as an electric load that involves a great use of power electronics, rectifier substations, the electric HV/MV substation, and the distribution network system (White, 2008).

On the other hand, the main PQ phenomena involved in the interaction between the railways' electrical systems and the power distribution system are: electromagnetic interference (EMI/RFI) at high frequency (HF); harmonics, flicker, and voltage regulation at low frequency (LF) (Sutherland et al., 2006). Also, PQ phenomena include sags at instantaneous regime, unbalance of the three-phase power system, and transients' phenomena (Lamedica et al., 2004).

Fig. 9 (Garcia & Rios, 2010) presents also where the cause of the phenomena is, what are the affected or perturbed systems, and where a solution of the problem can be implemented. For example, the electromagnetic transients occur in microseconds and they are caused by capacitor switching or lightning. Hence, they can be generated in the distribution network, MV side of the rectifier substation or in the train (represented by X in Fig. 9). The main problems are related to the rectifier substation or the train (represented by circle in Fig. 10) where the electronic sensitive equipment are susceptible to misuse or damage due to the transient overvoltage. An effective overvoltage transient protection could be located at the rectifier substation and, finally, at the train (represented by triangle Fig. 9).

Fig. 9. PQ Phenomena and Railways' Electrical System Components Relationships

### **4.2 Harmonic distortion analysis**

192 Infrastructure Design, Signalling and Security in Railway

The third column shows the maximum length of the DC section that each TS can supply. TS in configurations 1 and 3 must have a capacity to supply even twice the total length of the line divided by the number of considered substations. Instead, TS in configuration 2 supply the maximum length of catenaries/rail, just the normal operation length because this

The lowest total cost at Table 3 is presented in the case of three 5 MW TS because, in the study case of section 2.3, the investment cost weights more in the final cost than the operation cost. That is, looking just the configuration 1, it is evident that even though the operation costs do not grow up linearly as more TS are considered, the difference between investment costs is higher than operation costs, so the optimal solution is the location of 3 TS

**4. Power quality impact of urban railway systems on distribution systems** 

Power quality phenomena originated in power distribution systems impacts on the electrical power supply system of UMTS and, at the same time, power electronics used in the traction system impacts on the power quality (PQ) service of the distribution

In addition, the power demand of UMTS presents high and fast variations as consequence of the operation cycles of each train-vehicle and the non-coincidence of operational cycles

Fig. 9 shows the existing relationships between the different PQ phenomena and the railways' electrical system components. As it is shown, the main electrical components in the railway system are: the train-vehicle as an electric load that involves a great use of power electronics, rectifier substations, the electric HV/MV substation, and the distribution

On the other hand, the main PQ phenomena involved in the interaction between the railways' electrical systems and the power distribution system are: electromagnetic interference (EMI/RFI) at high frequency (HF); harmonics, flicker, and voltage regulation at low frequency (LF) (Sutherland et al., 2006). Also, PQ phenomena include sags at instantaneous regime, unbalance of the three-phase power system, and transients'

Fig. 9 (Garcia & Rios, 2010) presents also where the cause of the phenomena is, what are the affected or perturbed systems, and where a solution of the problem can be implemented. For example, the electromagnetic transients occur in microseconds and they are caused by capacitor switching or lightning. Hence, they can be generated in the distribution network, MV side of the rectifier substation or in the train (represented by X in Fig. 9). The main problems are related to the rectifier substation or the train (represented by circle in Fig. 10) where the electronic sensitive equipment are susceptible to misuse or damage due to the transient overvoltage. An effective overvoltage transient protection could be located at the rectifier substation and, finally, at the train (represented

among several vehicles. So, PQ phenomena are time variable (Singh et al., 2006).

**4.1 PQ Phenomena and railways' electrical system components** 

configuration is not able of supporting of adjacent substation in case of fault.

of 5 MW, under the configuration 1.

network system (White, 2008).

phenomena (Lamedica et al., 2004).

by triangle Fig. 9).

system.

The identification of PQ problems in power systems represents an important issue to the distribution utilities. The harmonic distortion is one of the main PQ phenomena in the electrical system feeding an EMRTS because the injection of harmonics by its nonlinear loads flows through the network and affects other consumers connected to the distribution system. According to the conceptual diagram of Fig. 9, the production of harmonics in the EMRTS is a PQ phenomenon at steady state caused by the rectifier substations, normally, a controlled rectifier of 6 or 12 pluses.

In addition, the computation of the total harmonic distortion (THD) in the AC side of the rectifier substation at the railway system must take into account the time load variability at each TS. So, the instantaneous power load must be computed as function of time and distance as it was explained at section 2. Once the current consumption in each TS is obtained, it is possible to identify the variation of the THD during the time.

### **4.2.1 Probabilistic model**

Generally, deterministic models have been adopted for network harmonic analysis; however, these models can fail for modelling the load variation in systems such as the railways' electrical system (Chang et al., 2009). So, a probabilistic analysis to characterize the harmonic current loads properly must be used in order to obtain an accurate model.

An EMRTS is characterized by fluctuating loads due to the different operation states of the trains in the traction system (See Fig. 7 b). Thus, the harmonics injection from the rectifier substations to the MV network causes that the current harmonic spectrum at the distribution system's connection point (PCC) varies over time. So, each traction substation can be represented as a harmonic current source that provides a probabilistic spectral content at the PCC (Rios et al., 2009).

Power System Modelling for Urban Massive Transportation Systems 195

Then, a process called "Vector Sum - Phasor" is run through Monte Carlo simulations. Finally, the probabilistic characterization is obtained; where the probability distribution function of current THD, the probability distribution function of rms current and the

Table 10.3 of Std. IEEE - 519 (IEEE, 1993) contains the current distortion limits in the voltage range of 120 V to 69 kV, which applies for typical railways' electrical systems connected to distribution systems at MV. So, based on this standard, a comparison between the current distortion levels at 95% and 50% of probability and the given limits must be realized to assess if the current distortion must be reduced or not. If a current THD distortion must be reduced, it could be used several filters methods. The next section presents the application

The harmonic distortion produced by railways' systems at the distribution system's connection point can be reduced using passive or active power filters (APF). However, due to the random and time variability of the harmonic distortion in traction systems, it is required an active power compensation with the ability of adaptation to different load conditions. Passive filters are designed with fixed parameters and for specific harmonics, so this type of filter does not have the required ability. By contrast, APFs based on the p-q theory became an effective solution in traction systems; normally, they are used for dynamic harmonic suppression (Xu & Chen, 2009). This type of compensation presents the advantage

On the other hand, the traction system has several rectifier substations and from the economic point of view it is difficult to install an APF in each TS due to its high cost. Then, it is necessary to allocate APFs in the most sensitive positions in the own power system of the EMRTS using the least number of filters and minimizing their size. An important factor to be considered in the decision of harmonic compensation in traction system is the sudden fluctuation of traction load because this dynamic behavior is also observed in the harmonic

The allocation methodology of APFs in distribution systems supplying a traction load is based on probabilistic data of harmonic distortion presented in all traction substations. According to the Std. IEEE - 519 (IEEE, 1993), using a 15 minutes time interval it is enough to understand the dynamic behavior of the traction load because in this interval there are 900 different data of the load behaviour in each TS. Fig. 11 shows the proposed

As, it was shown in section 3.4, for the study case of this Chapter, the metro line can be supplied by three TS at MV. The total harmonic distortion in the distribution system is analyzed with and without active compensation. The APF is allocated in the low voltage side of the transformer in the TS. As, the railway line has three TS, there are seven possible

Table 4 shows the THD distortion at levels of 50% and 95% of probability when the system is without active power compensation and when APFs compensation is used according to the seven different configurations. This table shows the effectiveness of the APFs to reduce

probability distribution of each harmonic component are obtained.

of active power filtering to reduce THD distortion.

**4.2.2 Active power filter allocation methodology** 

of eliminating a wide range of harmonics simultaneously.

distortion, as it has been explained in the previous section.

methodology of allocation of APF in urban railways systems.

allocations of APF, as Table 4 shows at the first column.

Then, it is necessary to perform the vector sum of several harmonic sources (i.e. traction substations) at the distribution system's connection point to determine the total harmonic distortion. There are two methods to evaluate the effect of different non-linear loads: the analytical method and Monte Carlo simulation method. The complex implementation of analytical methods for large power systems studies involves little practical application in real systems. By contrast, Monte Carlo simulation has proved to be a practical technique (Casteren & Groeman, 2009) based on the low correlation between different harmonic loads (independence of the sources). Fig. 10 presents the methodology useful for probabilistic harmonic distortion analysis of railways' electrical systems with different harmonic sources.

The methodology for probabilistic analysis of harmonic starts from values obtained from deterministic simulations. Once the different conditions of loads are defined in the behaviour of the traction system, it is possible to use probability distribution plots to evaluate the harmonic level in the system during the travel time. So, the next step is to determine the probability density function to fit the harmonic components of each harmonic source and its phase angle.

Fig. 10. Methodology for Harmonic Distortion Probabilistic Analysis of EMRTS

Many studies agree that the normal function is suitable as probability density function to use in the case of a random behaviour (Wang et al., 1994). In addition, according to the Std. IEEE - 519 (IEEE, 1993) the recommended window time to evaluate the harmonic distortion is 15 or 30 minutes. Therefore, it is recommended the selection of random time intervals of 15 minutes to make a probabilistic characterization of the THD distortion.

Then, it is necessary to perform the vector sum of several harmonic sources (i.e. traction substations) at the distribution system's connection point to determine the total harmonic distortion. There are two methods to evaluate the effect of different non-linear loads: the analytical method and Monte Carlo simulation method. The complex implementation of analytical methods for large power systems studies involves little practical application in real systems. By contrast, Monte Carlo simulation has proved to be a practical technique (Casteren & Groeman, 2009) based on the low correlation between different harmonic loads (independence of the sources). Fig. 10 presents the methodology useful for probabilistic harmonic distortion analysis of railways' electrical systems with different harmonic sources. The methodology for probabilistic analysis of harmonic starts from values obtained from deterministic simulations. Once the different conditions of loads are defined in the behaviour of the traction system, it is possible to use probability distribution plots to evaluate the harmonic level in the system during the travel time. So, the next step is to determine the probability density function to fit the harmonic components of each harmonic

Fig. 10. Methodology for Harmonic Distortion Probabilistic Analysis of EMRTS

15 minutes to make a probabilistic characterization of the THD distortion.

Many studies agree that the normal function is suitable as probability density function to use in the case of a random behaviour (Wang et al., 1994). In addition, according to the Std. IEEE - 519 (IEEE, 1993) the recommended window time to evaluate the harmonic distortion is 15 or 30 minutes. Therefore, it is recommended the selection of random time intervals of

source and its phase angle.

Then, a process called "Vector Sum - Phasor" is run through Monte Carlo simulations. Finally, the probabilistic characterization is obtained; where the probability distribution function of current THD, the probability distribution function of rms current and the probability distribution of each harmonic component are obtained.

Table 10.3 of Std. IEEE - 519 (IEEE, 1993) contains the current distortion limits in the voltage range of 120 V to 69 kV, which applies for typical railways' electrical systems connected to distribution systems at MV. So, based on this standard, a comparison between the current distortion levels at 95% and 50% of probability and the given limits must be realized to assess if the current distortion must be reduced or not. If a current THD distortion must be reduced, it could be used several filters methods. The next section presents the application of active power filtering to reduce THD distortion.

### **4.2.2 Active power filter allocation methodology**

The harmonic distortion produced by railways' systems at the distribution system's connection point can be reduced using passive or active power filters (APF). However, due to the random and time variability of the harmonic distortion in traction systems, it is required an active power compensation with the ability of adaptation to different load conditions. Passive filters are designed with fixed parameters and for specific harmonics, so this type of filter does not have the required ability. By contrast, APFs based on the p-q theory became an effective solution in traction systems; normally, they are used for dynamic harmonic suppression (Xu & Chen, 2009). This type of compensation presents the advantage of eliminating a wide range of harmonics simultaneously.

On the other hand, the traction system has several rectifier substations and from the economic point of view it is difficult to install an APF in each TS due to its high cost. Then, it is necessary to allocate APFs in the most sensitive positions in the own power system of the EMRTS using the least number of filters and minimizing their size. An important factor to be considered in the decision of harmonic compensation in traction system is the sudden fluctuation of traction load because this dynamic behavior is also observed in the harmonic distortion, as it has been explained in the previous section.

The allocation methodology of APFs in distribution systems supplying a traction load is based on probabilistic data of harmonic distortion presented in all traction substations. According to the Std. IEEE - 519 (IEEE, 1993), using a 15 minutes time interval it is enough to understand the dynamic behavior of the traction load because in this interval there are 900 different data of the load behaviour in each TS. Fig. 11 shows the proposed methodology of allocation of APF in urban railways systems.

As, it was shown in section 3.4, for the study case of this Chapter, the metro line can be supplied by three TS at MV. The total harmonic distortion in the distribution system is analyzed with and without active compensation. The APF is allocated in the low voltage side of the transformer in the TS. As, the railway line has three TS, there are seven possible allocations of APF, as Table 4 shows at the first column.

Table 4 shows the THD distortion at levels of 50% and 95% of probability when the system is without active power compensation and when APFs compensation is used according to the seven different configurations. This table shows the effectiveness of the APFs to reduce

Power System Modelling for Urban Massive Transportation Systems 197

A primary requirement to ensure the appropriate operation of any electrical system is to guarantee personnel and system safety, either under normal and fault conditions. So,

Grounding in electric traction systems requires a different treatment than in typical AC electrical systems, because of the existence of traction substations AC/DC of high capacity, the high variable load characteristic in time and distance, the direct contact of the rails with the earth, the current flow through the ground during normal operating conditions that can cause corrosion of underground metallic elements, the appearance of step and touch voltage

The grounding system is composed by two subsystems. The first one (subsystem 1) assures the personnel safety and the protective device operation; while, the second one (subsystem 2) is used to ground the negative pole in the DC side of the railway's traction substation.

The grounding subsystem 1 is used to ground all metallic structures: boxes, protective panels, pipeline, bridges, passenger platforms, etc. There are two ways to connect this



Technical Features Description HRGM LRGM Monitor constant voltage 25 Vdc 1 Vdc Relay circuit resistance High (200-700 ) Low (< 1 ) Current fault-ground structure Low (1-2 A) High (70-1500 A)

The second subsystem is used to ground the negative conductor of the TS (Paul, 2002) (Lee & Wang, 2001) which corresponds physically to running rails. In DC traction systems, the rails are used as return conductor current, which could cause corrosion problems in



underground metallic structures. There are three options to connect this subsystem:

module. This path is supplied with a resistance of 500 Ω.

Table 5. Comparison of HRMG and LRMG performance.

the corrosion of the elements grounded to the earth.

permits high touch and step voltages.

So, Table 5 presents a comparison of the performance of these two methods.

grounding is the most important component to control electrical system failures.

**5. Grounding in DC urban railway systems** 

that can jeopardize the integrity of persons.

subsystem:

protection system.

the current THD distortion. Although the reduction is achieved with one filter, the amount of reduction is low because the two rectifier substations without active power filter present high variability and distortion. It is also observed that when an additional filter is used the amount of reduction in the THD is higher. Obviously, if three APF are used (one at each TS), the higher THD reduction is obtained.

Fig. 11. Methodology for Allocation of Active Power Filters in Urban Railway Systems

The final decision about what configuration selects depends on the short circuit level of the system; for example, if the short circuit level is lower than 50 MVA a placement of one APF at each TS is required to satisfy Std. IEEE-519. By contrast, if the short circuit level is between 50 and 100 MVA, the best option is to place APF at TS1 and TS2.


Table 4. Total Current Harmonic Distortion – Active Power Filter Allocation

### **5. Grounding in DC urban railway systems**

196 Infrastructure Design, Signalling and Security in Railway

the current THD distortion. Although the reduction is achieved with one filter, the amount of reduction is low because the two rectifier substations without active power filter present high variability and distortion. It is also observed that when an additional filter is used the amount of reduction in the THD is higher. Obviously, if three APF are used (one at each

Fig. 11. Methodology for Allocation of Active Power Filters in Urban Railway Systems

Without filter 22.96 22.98 23.66 23.66 APF in TS1 14.59 14.84 19.31 19.25 APF in TS2 13.81 13.82 18.94 18.94 APF in TS3 13.75 13.50 17.80 17.77 APF in TS1 and TS2 3.64 3.69 5.44 5.56 APF in TS1 and TS3 3.81 3.82 5.21 5.17 APF in TS2 and TS3 3.68 3.64 5.18 5.06 APF in all TS 3.01 3.00 3.60 3.59

between 50 and 100 MVA, the best option is to place APF at TS1 and TS2.

Table 4. Total Current Harmonic Distortion – Active Power Filter Allocation

Case

The final decision about what configuration selects depends on the short circuit level of the system; for example, if the short circuit level is lower than 50 MVA a placement of one APF at each TS is required to satisfy Std. IEEE-519. By contrast, if the short circuit level is

> MEAN THD (%) THD of 95% of time (%) SUPPLY 1 SUPPLY 2 SUPPLY 1 SUPPLY 2

TS), the higher THD reduction is obtained.

A primary requirement to ensure the appropriate operation of any electrical system is to guarantee personnel and system safety, either under normal and fault conditions. So, grounding is the most important component to control electrical system failures.

Grounding in electric traction systems requires a different treatment than in typical AC electrical systems, because of the existence of traction substations AC/DC of high capacity, the high variable load characteristic in time and distance, the direct contact of the rails with the earth, the current flow through the ground during normal operating conditions that can cause corrosion of underground metallic elements, the appearance of step and touch voltage that can jeopardize the integrity of persons.

The grounding system is composed by two subsystems. The first one (subsystem 1) assures the personnel safety and the protective device operation; while, the second one (subsystem 2) is used to ground the negative pole in the DC side of the railway's traction substation.

The grounding subsystem 1 is used to ground all metallic structures: boxes, protective panels, pipeline, bridges, passenger platforms, etc. There are two ways to connect this subsystem:



So, Table 5 presents a comparison of the performance of these two methods.

Table 5. Comparison of HRMG and LRMG performance.

The second subsystem is used to ground the negative conductor of the TS (Paul, 2002) (Lee & Wang, 2001) which corresponds physically to running rails. In DC traction systems, the rails are used as return conductor current, which could cause corrosion problems in underground metallic structures. There are three options to connect this subsystem:


Power System Modelling for Urban Massive Transportation Systems 199

delivered or absorbed by the trains and the substations are known as well as the location of each of the trains at the moment that these currents are delivered. Different scenarios can arise during the operation, which can be described as: railway starting point (P1); railway ending point (Pn); point where a train is passing (P2, P3, P4, … , Pn-1); and point where a

The model uses information on the train location and current consumption or delivered by the traction substations, for all time t. The power demand simulator (section 2) gives the power consumed and delivered by each train and TS, as well as the location of each train




along the rail for each time instant. Fig. 13 shows the flowchart of the algorithm.

traction substation is located, for example (Pi).

**5.2 DC grounding algorithm model in time** 

Fig. 13. DC Grounding Algorithm Model in Time

This algorithm has the following characteristics:

to determine the track to be evaluated.

for each constant c(2xi-1) and c(2xi) respectively.

presented in section 2.


Table 6 compares the main characteristics of the three options of railway's grounding system.


Table 6. Comparison of the Railway's Grounding Systems

### **5.1 Generalized grounding model in DC to EMRTS**

Fig. 12 illustrates a grounded scheme for a railway line, in which for general purposes there are k trains, m substations and a total rail length *l*.

Fig. 12. Grounded System – General Scheme

The behavior of the current and voltage on the rail for each section between points Pi and Pi+1 for i = 1, 2, 3…, n, is modeled by:

$$I\_{Ri,i+1}(\mathbf{x}) = c\_{\{2xi-1\}} e^{\gamma \mathbf{x}} + c\_{\{2xi\}} e^{-\gamma \mathbf{x}} \tag{27}$$

$$dL\_i(\mathbf{x}) = -R\_0(c\_{\{2\le i-1\}}e^{\mathcal{I}^\mathbf{x}} - c\_{\{2\le i\}}e^{-\mathcal{I}^\mathbf{x}}) \tag{28}$$

For 0 ≤ x ≤ *l*, where *n* is equal to the number of trains running (*k*) plus the number of TS that are in operation (m), n = k + m. *Ui(x)* is the rail to ground potential [V], and *IRi,i+1(x)* is the stray current in the rail conductor [A].

The constant values c(2xi-1) and c(2xi) can be determined from the solution of a linear system of 2x(n-1) equations with 2x(n-1) unknowns obtained from the boundary conditions of each point Pi applying Kirchhoff's laws and assuming that the magnitudes of the currents delivered or absorbed by the trains and the substations are known as well as the location of each of the trains at the moment that these currents are delivered. Different scenarios can arise during the operation, which can be described as: railway starting point (P1); railway ending point (Pn); point where a train is passing (P2, P3, P4, … , Pn-1); and point where a traction substation is located, for example (Pi).

### **5.2 DC grounding algorithm model in time**

198 Infrastructure Design, Signalling and Security in Railway


Table 6 compares the main characteristics of the three options of railway's grounding

Fig. 12 illustrates a grounded scheme for a railway line, in which for general purposes there

The behavior of the current and voltage on the rail for each section between points Pi and

, 1 (2 1) (2 ) ( ) *x x Ri i xi xi I xc e c e* 

0 (2 1) (2 ) () ( ) *x x Ux Rc e c e <sup>i</sup> xi xi* 

For 0 ≤ x ≤ *l*, where *n* is equal to the number of trains running (*k*) plus the number of TS that are in operation (m), n = k + m. *Ui(x)* is the rail to ground potential [V], and *IRi,i+1(x)* is the

The constant values c(2xi-1) and c(2xi) can be determined from the solution of a linear system of 2x(n-1) equations with 2x(n-1) unknowns obtained from the boundary conditions of each point Pi applying Kirchhoff's laws and assuming that the magnitudes of the currents

(28)

(27)

(Vehicle touch voltage)

Stray current level

mode which increases stray currents and their associated effects.

Grounding method Riel to ground voltage

Table 6. Comparison of the Railway's Grounding Systems

**5.1 Generalized grounding model in DC to EMRTS** 

are k trains, m substations and a total rail length *l*.

Fig. 12. Grounded System – General Scheme

Pi+1 for i = 1, 2, 3…, n, is modeled by:

stray current in the rail conductor [A].

Solid-grounded system Low High Ungrounded system (Floating) High Low Diode-grounded system Middle-Low Middle-High

system.

The model uses information on the train location and current consumption or delivered by the traction substations, for all time t. The power demand simulator (section 2) gives the power consumed and delivered by each train and TS, as well as the location of each train along the rail for each time instant. Fig. 13 shows the flowchart of the algorithm.

Fig. 13. DC Grounding Algorithm Model in Time

This algorithm has the following characteristics:


Power System Modelling for Urban Massive Transportation Systems 201

This chapter has presented useful tools for power systems modelling, analysis and system design of Electric Massive Railway Transportation Systems (EMRTS) and power supply from Distribution Companies (DisCo) or Electric Power Utilities. Firstly, a section depicted to present the modelling and simulation of the power demand was developed. Then, a section about the computation of the placement and sizing of traction substations for urban railway systems was presented where the modelling is based on the power demand model

After that, two sections about the power quality impact of EMRTS on distribution systems and grounding design are presented. Both subjects make use of the load demand model

These tools allow the optimization of the design scheme of railway electrification for UMTS, taking into account an adequate sizing and number of traction substations, and the number

The authors want to thanks to Ana María Ospina, Camilo Andrés Ordoñez, and Elkín

Arriagada, A.; & Rudnick, H. (1994). *Reliability Evaluation in Electric Distribution Systems* (in spanish). Escuela de Ingeniería, Pontificia Universidad Católica de Chile. Buhrkall, L. (2006). Traction System Case Study, In: *Electric Traction Systems*, IET (Ed.), pp.

Casteren, J.V.; Groeman, F. (2006). Harmonic analysis of rail transportation systems with

Chen, C.S.; Chuang, H.J.; & Chen, J.L. (1999). Analysis of dynamic load behavior for

Garcia, J.G.; Ríos, M.A.; Ramos, G. (2009). A power demand simulator of electric transportation

Garcia, J.G.; Rios, M.A. (2010). PQ analysis in tramway systems, *2010 IEEE ANDESCON*,

Hill, R.J. (2006). DC and AC Traction Motors, In: *Electric Traction Systems*, IET (Ed.), 33-52,

Hsiang, P.; & Chen, S. (2001). Electric Load Estimation Techniques for High-Speed Railway

ISBN 978-1-4244-6740-2, Bogotá, Colombia, 15-17 Sept., 2010.

No. 5, (September 2001), pp. 1260-1266, ISSN 0018-9545.

probabilistic techniques, *9th International Conference on Probabilistic Methods Applied to Power Systems,* ISBN 978-91-7178-585-5, Stockholm, Sweden, June 11-15, 2006. Chang, G.W.; Hung-Lu, W.; Gen-Sheng, C.; Shou-Yung, C. (2009). Passive harmonic filter

planning in a power system with considering probabilistic constraints, *IEEE Transactions on Power Delivery,* Vol. 24, No.1, (Jan. 2009), pp. 208-218, ISSN 0885-

electrified mass rapid transit systems, *34th IEEE Industry Applications Conference*, Vol. 2, pp. 992-998, ISBN: 0-7803-5589-X, Phoenix, Arizona, USA, October 3-7, 1999.

systems for distribution utilities, *44th International Universities Power Engineering Conference UPEC 2009*, ISBN 978-1-4244-6823-2, Glasgow, Scotland, September 1-4, 2009.

(HSR) Traction Power Systems, *IEEE Transactions on Vehicular Technology*, Vol. 50,

and location of harmonic filters to improve the power quality of the system.

Cantor for the support given in the preparation of the material for this Chapter.

53-71, ISBN 978-0-86341-9485, London, UK.

ISBN 978-0-86341-9485, London, UK.

**6. Conclusion** 

of the previously mentioned.

presented at section 2.

**7. Acknowledgment** 

8977.

**8. References** 


### **5.3 Example**

Let us consider a simplified study case similar to the system of section 2.3 (Fig. 6) with three TS located at 0, 2000 and 4000 meters and four trains moving along the 4 kilometers of rail. Constant system parameters are: R=0.04Ω/km, G=0.1S/km, Rg=0.01Ω/km and R01=R8∞=R0.

Fig. 14. Example of Simulation of Grounding

Fig. 14a shows the current magnitude of each train and its location on the rail for each moment. Likewise, Fig. 14b shows the current magnitude in each traction substations for each time instant.

Fig. 15 shows the voltage profile along of the rail length at different points in time obtained from the simulation for the case of diode-grounded system. With this system, it is possible to reduce the voltage difference presented in the ungrounded system as the solid-grounded system behaviour. The simulations results show that the diode-grounded system guarantees greater security because it control the step and touch voltage and reduces the stray currents that cause the deterioration of the physical installation.

Fig. 15. Rail to Ground Time Voltage Profile

### **6. Conclusion**

200 Infrastructure Design, Signalling and Security in Railway


Let us consider a simplified study case similar to the system of section 2.3 (Fig. 6) with three TS located at 0, 2000 and 4000 meters and four trains moving along the 4 kilometers of rail. Constant system parameters are: R=0.04Ω/km, G=0.1S/km, Rg=0.01Ω/km and R01=R8∞=R0.

a) Currents at Trains b) Currents at Traction Substation

Fig. 14a shows the current magnitude of each train and its location on the rail for each moment. Likewise, Fig. 14b shows the current magnitude in each traction substations for

Fig. 15 shows the voltage profile along of the rail length at different points in time obtained from the simulation for the case of diode-grounded system. With this system, it is possible to reduce the voltage difference presented in the ungrounded system as the solid-grounded system behaviour. The simulations results show that the diode-grounded system guarantees greater security because it control the step and touch voltage and reduces the stray currents

is saved. This process is repeated from the second step until all points in time.

**5.3 Example** 

each time instant.

Fig. 14. Example of Simulation of Grounding

that cause the deterioration of the physical installation.

Fig. 15. Rail to Ground Time Voltage Profile

This chapter has presented useful tools for power systems modelling, analysis and system design of Electric Massive Railway Transportation Systems (EMRTS) and power supply from Distribution Companies (DisCo) or Electric Power Utilities. Firstly, a section depicted to present the modelling and simulation of the power demand was developed. Then, a section about the computation of the placement and sizing of traction substations for urban railway systems was presented where the modelling is based on the power demand model of the previously mentioned.

After that, two sections about the power quality impact of EMRTS on distribution systems and grounding design are presented. Both subjects make use of the load demand model presented at section 2.

These tools allow the optimization of the design scheme of railway electrification for UMTS, taking into account an adequate sizing and number of traction substations, and the number and location of harmonic filters to improve the power quality of the system.

### **7. Acknowledgment**

The authors want to thanks to Ana María Ospina, Camilo Andrés Ordoñez, and Elkín Cantor for the support given in the preparation of the material for this Chapter.

### **8. References**


**0**

**8**

*Sweden*

**Optimized Model Updating of a Railway Bridge for**

The moving load problem has been studied intensively since the first research by Willis in 1849 (Willis, 1850). Today's railway bridges are analyzed in more detail for moving loads due to increased speeds, axle loads and more slender bridge designs. Such analyzes are very time consuming as it involves many simulations using different train configurations passing at different speeds. Thus, simplified bridge and train models are chosen for time efficient simulations. However, these FE models are often called into question when they are in conflict with in-situ bridge measurements. Model updating has therefore been a rapidly developing technology and has gained a lot of interest in recent years. It is the popular name for using measured structural data to correct the errors in FE models. Clearly, the approach of numerical predictions to the behavior of a physical system is limited by the assumptions used in the development of the mathematical model (Friswell & Mottershead, 1995). Model updating, at

its most ambitious, is about correcting invalid assumptions by processing test results.

Mottershead & Friswell (1993) provided a state of the art and addressed the problem of updating a numerical model by using data acquired from a physical vibration test (Friswell & Mottershead, 1995). Optimization has been used by many others since then, improving FE model predictions based on real measurements. This chapter highlights the importance and the potential of such optimization procedures for increased accuracy in moving load simulations. A large-scale simplified railway bridge FE model is used and the updating process is based on previously identified updating parameters in Wiberg et al. (2009). Natural frequency, static strain, static deflection and acceleration residuals are used, separately and combined, to optimize the values of modulus of elasticity, mass density and modal damping ratio. The updated FE model is finally used to identify and analyze the most critical moving load configuration in CEN (2002) concerning bending moment, vertical bridge deck deflection

The optimization algorithm was easily implemented for FE model updating and was shown to operate efficiently in a benchmark test and for the specific bridge. The optimization algorithm converges against reasonable values of the updating parameters. A previously questioned high-valued equivalent modulus of elasticity, found for a manually tuned FE model in Wiberg (2009), was proven to be reliable. Further, the difference in load effect between an initial manually tuned FE model and the optimized FE model is found most significant for vertical deflection. However, more measured dynamic characteristics (natural frequencies, mode

**1. Introduction**

and acceleration.

**Increased Accuracy in Moving Load Simulations**

Johan Wiberg, Raid Karoumi and Costin Pacoste

*KTH Royal Institute of Technology*


## **Optimized Model Updating of a Railway Bridge for Increased Accuracy in Moving Load Simulations**

Johan Wiberg, Raid Karoumi and Costin Pacoste *KTH Royal Institute of Technology Sweden*

### **1. Introduction**

202 Infrastructure Design, Signalling and Security in Railway

IEEE (1992). IEEE Loss Evaluation Guide for Power Transformers and Reactors, IEEE (ed.),

IEEE (1993). IEEE recommended practices and requirements for harmonic control in electrical power systems Standard 519 – 1992, IEEE (ed.), ISBN 1-55937-239-7, New York, USA. IEEE (2007). IEEE standard general requirements for liquid-immersed distribution, power,

Jong, JC..; & Chang, S. (2005a). Models for Estimating Energy Consumption of Electric

Jong, J.C.; & Chang, S. (2005b). Algorithms for Generating Train Speed Profiles, *Journal of the* 

Lamedica, R.; Maranzano, G.; Marzinotto, M.; & Prudenzi, A. (2004). Power quality

Lee, C.H.; Wang, H.M. (2001). Effects of Grounding Schemes on Rail Potential and Stray

Rios, M.A.; Ramos, G.; Moreno, R. (2009). Evaluación de Calidad de la Potencia en la

*CLAGTEE*, ISBN 978-85-61065-01-0, Ubatuba, Brazil, October 18-22, 2009. Singh, B.; Bhuvaneswari, G.; & Garg, V. (2006). Improved power quality AC-DC converter

Sutherland, P.; Waclawiak, M.; & McGranaghan, M. (2006). Harmonic Impacts Evaluation

Vukan, R. (2007). *Urban Transit Systems and Technology*, John Wiley & Sons, Inc., ISBN 978-

Xu, X.; Chen, B. (2009). Research on Power Quality Control for Railway Traction Power

Wang, Y.J.; Pierrat, L.; Wang, L. (1994), Summation of harmonic currents produced by

White, R.D. (2008). AC/DC railway electrification and protection, In: *2008 IET professional* 

White, R.D. (2009). DC electrification supply system design, In: *4th IET professional* 

*Applications*, Vol. 148, No. 2, (Mar. 2001), pp. 148–154, ISSN 1350-2352. Paul, D. (2002). DC traction power system grounding, *IEEE Transactions on Industry Applications,* Vol. 38, No.3, (May/Jun 2002), pp. 818 - 824, ISSN 0093-9994. Perrin, J.P.; & Vernard, C. (1991). *Urban Electric Transportations* (in French), D5-554

and regulating transformers C57.12.00-2006, IEEE(ed.), ISBN 0-7381-5251-X, New

Trains, *Journal of the Eastern Asia Society for Transportation Studies*, Vol. 6, (2005), pp.

*Eastern Asia Society for Transportation Studies*, Vol. 6, (2005), pp. 356 - 371, ISSN 1881-

disturbance in power supply system of the subway of Rome, *IEEE Power Engineering Society General Meeting*, pp. 924 – 929, ISBN 0-7803-8465-2, Denver,

Currents in Taipei Rail Transit Systems, *IEE Proceedings on Electric Power* 

Interacción del Sistema de Distribución y los Sistemas Eléctricos Ferroviarios Urbanos, *8th Latin-American Congress on Electricity Generation and Transmission* 

for electric multiple units in electric traction, *2006 IEEE Power India Conference*, ISBN

for Single-Phase Traction Load, *International Journal on Energy Technology and Policy*,

Supply System, *Pacific-Asia Conference on Circuits, Communications and Systems,*

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*development course on Electric Traction Systems*, IET (ed.), pp. 258 – 305, ISBN 978-0-

*development course on Railway Electrification Infrastructure and Systems*, IET (ed.), 44–

ISBN 1-55937-245-1, New York, USA.

York, USA.

1124.

278 - 291, ISSN 1881-1124.

USA, 6-10 June, 2004.

0471758235, NJ, USA.

0885-8977.

86341-948-5, UK.

69, ISBN 978-1-84919-133-3, UK.

Techniques de l'Ingénieur, France.

0-7803-9525-5, New Delhi, India, 2006.

Vol. 4, No. 1, (2006), pp. 37-59, ISSN 1472-8923.

ISBN 978-0-7695-3614-9, Chengdu, China, May 16-17, 2009.

The moving load problem has been studied intensively since the first research by Willis in 1849 (Willis, 1850). Today's railway bridges are analyzed in more detail for moving loads due to increased speeds, axle loads and more slender bridge designs. Such analyzes are very time consuming as it involves many simulations using different train configurations passing at different speeds. Thus, simplified bridge and train models are chosen for time efficient simulations. However, these FE models are often called into question when they are in conflict with in-situ bridge measurements. Model updating has therefore been a rapidly developing technology and has gained a lot of interest in recent years. It is the popular name for using measured structural data to correct the errors in FE models. Clearly, the approach of numerical predictions to the behavior of a physical system is limited by the assumptions used in the development of the mathematical model (Friswell & Mottershead, 1995). Model updating, at its most ambitious, is about correcting invalid assumptions by processing test results.

Mottershead & Friswell (1993) provided a state of the art and addressed the problem of updating a numerical model by using data acquired from a physical vibration test (Friswell & Mottershead, 1995). Optimization has been used by many others since then, improving FE model predictions based on real measurements. This chapter highlights the importance and the potential of such optimization procedures for increased accuracy in moving load simulations. A large-scale simplified railway bridge FE model is used and the updating process is based on previously identified updating parameters in Wiberg et al. (2009). Natural frequency, static strain, static deflection and acceleration residuals are used, separately and combined, to optimize the values of modulus of elasticity, mass density and modal damping ratio. The updated FE model is finally used to identify and analyze the most critical moving load configuration in CEN (2002) concerning bending moment, vertical bridge deck deflection and acceleration.

The optimization algorithm was easily implemented for FE model updating and was shown to operate efficiently in a benchmark test and for the specific bridge. The optimization algorithm converges against reasonable values of the updating parameters. A previously questioned high-valued equivalent modulus of elasticity, found for a manually tuned FE model in Wiberg (2009), was proven to be reliable. Further, the difference in load effect between an initial manually tuned FE model and the optimized FE model is found most significant for vertical deflection. However, more measured dynamic characteristics (natural frequencies, mode

Hessian matrices, the Nelder-Mead simplex algorithm is less prone to numerical difficulties at iteration steps. Also for noisy measurements the Nelder-Mead simplex algorithm has been proven effective, see e.g. the updating results of a simple beam in Jonsson & Johnson (2007) or the more extensive study of Schlune et al. (2009) to improve the FE model of the new Svinesund Bridge between Sweden and Norway. Further, the optimization algorithm is general, problem independent and can be implemented easily for FE model updating.

<sup>205</sup> Optimized Model Updating of a Railway Bridge

The objective function is the crucial heart of FE model updating. It represents the magnitude of the error of the response vector, **z**, defined as the difference between the observed responses

Typically, the response residual vector is weighted to reflect the confidence in different

*T* **Wz z***<sup>m</sup>* − **z***<sup>j</sup>* 

where **z***<sup>m</sup>* is the measured response vector, **z***<sup>j</sup>* is the FE response vector at iteration *j* and the response weighting matrix, **Wz**, is a diagonal matrix with corresponding reciprocals as diagonal elements depending on the type of objective function. Notations are also to be found

The selection of the objective function has a profound impact on the problem (Jaishi & Ren, 2005). A classical least squares approach fails to acknowledge that the observations are not recorded with equal confidence (Friswell & Mottershead, 1995). In reality, different error sources will also reduce the ability of the FE model to reproduce the experimental measurements. This can be systematic errors, experimental noise and modeling limitations. In a weighted least squares approach each squared measurement residual is therefore multiplied by a weight, *wi*, and the sum of weighted squares of the residuals is calculated. When the

*<sup>T</sup>* (**z** − *E* {**z**})

(2)

(3)

(4)

(5)

(6)

(**z** − *E* {**z**})

and the expected responses *E* {**z**} (Friswell & Mottershead, 1995):

Π = *E* 

> **<sup>z</sup>**Π = **z***<sup>m</sup>* − **z***<sup>j</sup>*

weights are given by the inverse observation variances,

**z** *<sup>σ</sup>*Π =

*Nz* ∑ *i*=1

objective function reformulated as:

**z** *<sup>σ</sup>*Π = **<sup>W</sup>** <sup>=</sup> diag

the minimization problem, min**<sup>p</sup>** *<sup>σ</sup>*Π, has the objective function:

(*zmi* − *zi*)<sup>2</sup> *σ* <sup>2</sup> *zi*

*Nz* ∑ *i*=1 = **z***m* − **z p***j <sup>T</sup>* **Wz z***m* − **z p***j*

, 1 *σ* <sup>2</sup> 2

(*zmi* − *zi*)<sup>2</sup> *σ* <sup>2</sup> *zi*

This is the objective function used by Jonsson & Johnson (2007) and Schlune et al. (2009). To keep the least squares form of the objective function, the square root is omitted and the

,..., <sup>1</sup> *σ* 2 *i*

> = *Nz* ∑ *i*=1

,..., <sup>1</sup> *σ* <sup>2</sup> *Nz*

> |*zmi* − *zi*| *σzi*

**2.2 The objective function**

for Increased Accuracy in Moving Load Simulations

measurements:

in Appendix 5.1.

shapes and modal damping ratios), together with complementing updating parameters and a more detailed FE model are considered necessary for dynamic load effect predictions with highest accuracy.

Finally, it should be given attention that the adopted methodology can not only be used for model updating based on measurements, but also introduced in the early design phase. The reasonable range of a typical modeling factor or parameter is then based on the drilled engineer's qualified guess and the risk of for example a resonance problem can be investigated by, e.g. letting the maximum allowed code limit for vertical bridge deck acceleration be "measured" response. Performing the optimization will then result in a model configuration, needed to fulfill the requirements in the code.

### **2. FE model optimization**

### **2.1 General**

The objective of FE model updating is to improve an FE model in order to reproduce the measured response of a structure. Model updating brings together the skills of the numerical analyst and the load test engineer, and requires the application of modern estimation techniques to produce the desired improvement (Friswell & Mottershead, 1995). Basically, an understanding of the updated model is necessary. The updated model may only reproduce physical test data but could lack physical meaning. It is therefore required to accurately know the application area of the updated model. Typically, the physical meaning of the model must be improved if the updated model is to assess the effect of changes in construction.

Optimization techniques are used to find a set of design parameters, **p** = {*p*1, *p*2,..., *pn*}, that can somehow be defined as optimal. FE modeling procedures involve an optimization with respect to an objective function, i.e. finding an optimal model that behaves similarly to the real structure and represents the physical characteristics of it (Zárate & Caicedo, 2008). Thus, residuals of the response, as a nonlinear function of the input parameters, are established and accounted for in the objective function. Different types of objective functions are found in the literature and by their minimization an FE model may be optimally updated.

The optimization process is rather straightforward. More complex is the choice of updating parameters, i.e. those exerting an influence on the bridge model in question. It is reasonable to believe that an accurate representation of a structure depends on the type of FE model used to represent the structural members and the properties assigned to these elements. Therefore, relatively large differences can exist between the behavior of a FE model before updating and the real structure.

Considering the minimization problem as unconstrained nonlinear, i.e. finding a vector **p** that is local minimum to a scalar function Π(**p**):

$$\min\_{\mathbf{p}} \Pi(\mathbf{p}) \tag{1}$$

with no restriction placed on the range of **p**, the Nelder-Mead simplex algorithm as described in Lagarias et al. (1998) can be used for optimization. The algorithm is capable of escaping local minima in some cases and can even handle discontinuities (Coleman & Zhang, 2009). Unlike gradient based optimization routines, facing ill-conditioning for the Jacobian and Hessian matrices, the Nelder-Mead simplex algorithm is less prone to numerical difficulties at iteration steps. Also for noisy measurements the Nelder-Mead simplex algorithm has been proven effective, see e.g. the updating results of a simple beam in Jonsson & Johnson (2007) or the more extensive study of Schlune et al. (2009) to improve the FE model of the new Svinesund Bridge between Sweden and Norway. Further, the optimization algorithm is general, problem independent and can be implemented easily for FE model updating.

#### **2.2 The objective function**

2 Will-be-set-by-IN-TECH

shapes and modal damping ratios), together with complementing updating parameters and a more detailed FE model are considered necessary for dynamic load effect predictions with

Finally, it should be given attention that the adopted methodology can not only be used for model updating based on measurements, but also introduced in the early design phase. The reasonable range of a typical modeling factor or parameter is then based on the drilled engineer's qualified guess and the risk of for example a resonance problem can be investigated by, e.g. letting the maximum allowed code limit for vertical bridge deck acceleration be "measured" response. Performing the optimization will then result in a model configuration,

The objective of FE model updating is to improve an FE model in order to reproduce the measured response of a structure. Model updating brings together the skills of the numerical analyst and the load test engineer, and requires the application of modern estimation techniques to produce the desired improvement (Friswell & Mottershead, 1995). Basically, an understanding of the updated model is necessary. The updated model may only reproduce physical test data but could lack physical meaning. It is therefore required to accurately know the application area of the updated model. Typically, the physical meaning of the model must

Optimization techniques are used to find a set of design parameters, **p** = {*p*1, *p*2,..., *pn*}, that can somehow be defined as optimal. FE modeling procedures involve an optimization with respect to an objective function, i.e. finding an optimal model that behaves similarly to the real structure and represents the physical characteristics of it (Zárate & Caicedo, 2008). Thus, residuals of the response, as a nonlinear function of the input parameters, are established and accounted for in the objective function. Different types of objective functions are found in the

The optimization process is rather straightforward. More complex is the choice of updating parameters, i.e. those exerting an influence on the bridge model in question. It is reasonable to believe that an accurate representation of a structure depends on the type of FE model used to represent the structural members and the properties assigned to these elements. Therefore, relatively large differences can exist between the behavior of a FE model before updating and

Considering the minimization problem as unconstrained nonlinear, i.e. finding a vector **p** that

with no restriction placed on the range of **p**, the Nelder-Mead simplex algorithm as described in Lagarias et al. (1998) can be used for optimization. The algorithm is capable of escaping local minima in some cases and can even handle discontinuities (Coleman & Zhang, 2009). Unlike gradient based optimization routines, facing ill-conditioning for the Jacobian and

Π(**p**) (1)

min **p**

be improved if the updated model is to assess the effect of changes in construction.

literature and by their minimization an FE model may be optimally updated.

highest accuracy.

needed to fulfill the requirements in the code.

**2. FE model optimization**

**2.1 General**

the real structure.

is local minimum to a scalar function Π(**p**):

The objective function is the crucial heart of FE model updating. It represents the magnitude of the error of the response vector, **z**, defined as the difference between the observed responses and the expected responses *E* {**z**} (Friswell & Mottershead, 1995):

$$\Pi = E\left\{ \left( \mathbf{z} - E\left\{ \mathbf{z} \right\} \right)^{T} \left( \mathbf{z} - E\left\{ \mathbf{z} \right\} \right) \right\} \tag{2}$$

Typically, the response residual vector is weighted to reflect the confidence in different measurements:

$$\mathbf{^Z II} = \left(\mathbf{z\_m} - \mathbf{z\_j}\right)^T \mathbf{W\_z} \left(\mathbf{z\_m} - \mathbf{z\_j}\right) \tag{3}$$

where **z***<sup>m</sup>* is the measured response vector, **z***<sup>j</sup>* is the FE response vector at iteration *j* and the response weighting matrix, **Wz**, is a diagonal matrix with corresponding reciprocals as diagonal elements depending on the type of objective function. Notations are also to be found in Appendix 5.1.

The selection of the objective function has a profound impact on the problem (Jaishi & Ren, 2005). A classical least squares approach fails to acknowledge that the observations are not recorded with equal confidence (Friswell & Mottershead, 1995). In reality, different error sources will also reduce the ability of the FE model to reproduce the experimental measurements. This can be systematic errors, experimental noise and modeling limitations. In a weighted least squares approach each squared measurement residual is therefore multiplied by a weight, *wi*, and the sum of weighted squares of the residuals is calculated. When the weights are given by the inverse observation variances,

$$\mathbf{W} = \text{diag}\left(\frac{1}{\sigma\_1^{-2}}, \frac{1}{\sigma\_2^{-2}}, \dots, \frac{1}{\sigma\_i^{-2}}, \dots, \frac{1}{\sigma\_{N\_\varepsilon}^{-2}}\right) \tag{4}$$

the minimization problem, min**<sup>p</sup>** *<sup>σ</sup>*Π, has the objective function:

$$\sigma\_{\sigma}^{\mathbf{z}} \Pi = \sum\_{i=1}^{N\_{\mathbf{z}}} \sqrt{\frac{(z\_{mi} - z\_i)^2}{\sigma\_{z\_i}^2}} = \sum\_{i=1}^{N\_{\mathbf{z}}} \frac{|z\_{mi} - z\_i|}{\sigma\_{z\_i}} \tag{5}$$

This is the objective function used by Jonsson & Johnson (2007) and Schlune et al. (2009). To keep the least squares form of the objective function, the square root is omitted and the objective function reformulated as:

$$\mathbf{r}\_{\sigma}^{\mathbf{z}}\Pi = \sum\_{i=1}^{N\_{\mathbf{z}}} \frac{(z\_{mi} - z\_i)^2}{\sigma\_{z\_i}^2} = \left(\mathbf{z}\_{\mathfrak{M}} - \mathbf{z}\left(\mathbf{p}\_j\right)\right)^T \mathbf{W}\_{\mathbf{z}}\left(\mathbf{z}\_{\mathfrak{M}} - \mathbf{z}\left(\mathbf{p}\_j\right)\right) \tag{6}$$

*<sup>v</sup> <sup>δ</sup>*

for Increased Accuracy in Moving Load Simulations

*m*<sup>2</sup>

*k c*

Fig. 1. The physical benchmark problem.

<sup>20000</sup> ) and ending at ( <sup>210</sup>

Appendix 7.

function:

( <sup>175</sup> <sup>175</sup> , <sup>20000</sup>

**4. Case study**

*m*<sup>1</sup>

**<sup>z</sup>**Π = *Nz* ∑ *i*=1

<sup>175</sup> , <sup>16000</sup>

local minimum but proceeded to the global minimum.

Span 1 Span 2

of the beam was increased to include the mass of the ballast. Direct time integration with the Hilber method was adopted. All necessary input data to the Solvia FE system is given in

<sup>207</sup> Optimized Model Updating of a Railway Bridge

To symbolize "measured" result, material properties of 210 GPa and 16000 kg/m<sup>3</sup> for modulus of elasticity and mass density, respectively, were used and the corresponding "measured" maximum deflection in each span was calculated to 2.152 mm and 2.165 mm. In addition to these "measured" responses, the predicted finite element analysis responses, as a function of the iteratively updated material properties, constituted the objective function expression. For simplicity, the Euclidean norm of the normalized response residual was chosen as objective

> (*zmi* − *zi*)<sup>2</sup> *z* <sup>2</sup> *mi*

Using the modulus of elasticity and mass density as updating parameters, with initial values of 175 GPa and 20000 kg/m3, i.e. corresponding to initial deflections of 2.658 mm and 2.607 mm, the fminsearch solver in Matlab® converged towards 210 GPa and 16000 kg/m<sup>3</sup> at the deflections 2.152 mm and 2.165 mm in 30 iterations and 62 objective function counts. Fig. 2 illustrates the iteration sequence, starting at the normalized input parameter coordinates

The New Årsta Bridge in Stockholm, Sweden, was adopted for FE model updating (see Fig. 3). Previous research pointed out some of the difficulties in studying bridge dynamics resulting from moving traffic (Wiberg et al., 2009). Not only does the dynamic amplification depends on the considered load effect, but different modeling parameters, individually or jointly, influence the dynamic load effect or dynamic property in question. The use of statistically identified updating parameters as a step in more effective model optimization is highlighted in previous study by the author and typical results from a statistical parameter study on this specific bridge are exemplified in Fig. 4 and found in Wiberg et al. (2009) where the factorial experimentation technique was used. The type of information encountered in Fig. 4 is considered extremely important and valuable. Thus, the statistical method of factorial experimentation, in contrast to ordinary parameter sensitivity analyzes where parameters are varied one at a time, captures the synergy effects. Consequently, a modeling parameter can be significant even though it individually is found insignificant and an optimal amount of updating parameters to include in the optimization can therefore be identified. This leads to shorter solution times as the optimization algorithm itself is iterative and becomes

= 

**z***<sup>m</sup>* − **z**(**p***j*) **z***m*

<sup>20000</sup> ). Interestingly, the algorithm first seemed to localize a

 

(8)

which corresponds to Eq. 3 with possibility to take the significance of different measurements into account and with dimensionless terms as a result. The normalized updating parameter vector is defined as

$$\mathbf{p}\_{j} = \left(\frac{p\_{1,j}}{p\_{1,0}}, \frac{p\_{2,j}}{p\_{2,0}}, \dots, \frac{p\_{n,j}}{p\_{n,0}}\right) \tag{7}$$

#### **2.3 Optimization procedure**

FE model updating becomes very efficient, neat and easy to implement by coupling the FE analysis software in question to a mathematical analysis software such as the Matlab® package. This also most conveniently facilitate the use of the Matlab® incorporated optimization toolbox and the updating process is therefore fully controlled from within Matlab®. In order to use a typical optimization solver, a function handle of the objective function together with an initial normalized updating parameter vector are sent to the optimization subroutine. The updated FE model code is then automatically generated by the optimization algorithm as it iterates. The Matlab® syntax for a general and problem independent optimization procedure is then:

```
% Response function as function handle @:
z=@(p)FEA(p);
% Objective function as function handle @:
obj=@(p)obj_func(zm,z,sigma);
% Initial normalized updating parameter vector:
p0=[1 1];
% Nelder-Mead simplex optimization based on functions Z and OBJ:
[p,objval,exitflag,output]=fminsearch(obj,p0,options);
```
In this case FEA(p) includes the appropriate code for initiation of the finite element analysis and calculation of the response vector as a function of the updating parameter vector p from the optimization solver fminsearch in the optimization toolbox of Matlab®. In this case the Solvia FE system software was adopted.

The optimization algorithm starts at the point p0 and attempts to find a local minimum p of the function described in obj, with measured response zm, standard deviations in responses sigma and optimization options specified in options. The algorithm returns in objval the value of the objective function obj at the solution p, in exitflag the exit condition of fminsearch and in output the user specified information about the optimization are found.

#### **3. Benchmark test**

A benchmark test was performed to verify the updating procedure implemented in Matlab®. The physical problem consisted of a 2D dynamic analysis of a moving vehicle across a ballasted railway bridge with vehicle-bridge interaction due to contact definitions, see Fig. 1. The I-beam steel bridge had two spans, assumed to be linearly elastic, and the vehicle speed was 30 m/s. The bridge surface and the neighboring rigid surface portions are assumed to initially form a horizontal straight line. Each span was modeled to consist of 20 beam elements and a mass-spring-damper system was used to model the vehicle. The mass density 4 Will-be-set-by-IN-TECH

which corresponds to Eq. 3 with possibility to take the significance of different measurements into account and with dimensionless terms as a result. The normalized updating parameter

FE model updating becomes very efficient, neat and easy to implement by coupling the FE analysis software in question to a mathematical analysis software such as the Matlab® package. This also most conveniently facilitate the use of the Matlab® incorporated optimization toolbox and the updating process is therefore fully controlled from within Matlab®. In order to use a typical optimization solver, a function handle of the objective function together with an initial normalized updating parameter vector are sent to the optimization subroutine. The updated FE model code is then automatically generated by the optimization algorithm as it iterates. The Matlab® syntax for a general and problem independent optimization procedure is then:

,..., *pn*,*<sup>j</sup> pn*,0 

(7)

**p***<sup>j</sup>* =

 *p*1,*<sup>j</sup> p*1,0 , *p*2,*<sup>j</sup> p*2,0

vector is defined as

z=@(p)FEA(p);

p0=[1 1];

**3. Benchmark test**

**2.3 Optimization procedure**

% Response function as function handle @:

% Objective function as function handle @:

% Initial normalized updating parameter vector:

[p,objval,exitflag,output]=fminsearch(obj,p0,options);

% Nelder-Mead simplex optimization based on functions Z and OBJ:

In this case FEA(p) includes the appropriate code for initiation of the finite element analysis and calculation of the response vector as a function of the updating parameter vector p from the optimization solver fminsearch in the optimization toolbox of Matlab®. In this case the

The optimization algorithm starts at the point p0 and attempts to find a local minimum p of the function described in obj, with measured response zm, standard deviations in responses sigma and optimization options specified in options. The algorithm returns in objval the value of the objective function obj at the solution p, in exitflag the exit condition of fminsearch and in output the user specified information about the optimization are found.

A benchmark test was performed to verify the updating procedure implemented in Matlab®. The physical problem consisted of a 2D dynamic analysis of a moving vehicle across a ballasted railway bridge with vehicle-bridge interaction due to contact definitions, see Fig. 1. The I-beam steel bridge had two spans, assumed to be linearly elastic, and the vehicle speed was 30 m/s. The bridge surface and the neighboring rigid surface portions are assumed to initially form a horizontal straight line. Each span was modeled to consist of 20 beam elements and a mass-spring-damper system was used to model the vehicle. The mass density

obj=@(p)obj\_func(zm,z,sigma);

Solvia FE system software was adopted.

Fig. 1. The physical benchmark problem.

of the beam was increased to include the mass of the ballast. Direct time integration with the Hilber method was adopted. All necessary input data to the Solvia FE system is given in Appendix 7.

To symbolize "measured" result, material properties of 210 GPa and 16000 kg/m<sup>3</sup> for modulus of elasticity and mass density, respectively, were used and the corresponding "measured" maximum deflection in each span was calculated to 2.152 mm and 2.165 mm. In addition to these "measured" responses, the predicted finite element analysis responses, as a function of the iteratively updated material properties, constituted the objective function expression. For simplicity, the Euclidean norm of the normalized response residual was chosen as objective function:

$$\mathbf{^Z II} = \sqrt{\sum\_{i=1}^{N\_{\mathbf{\bar{z}}}} \frac{(z\_{\mathfrak{mi}} - z\_i)^2}{z\_{\mathfrak{mi}}^2}} = \left\| \frac{\mathbf{z}\_m - \mathbf{z}(\mathbf{p}\_j)}{\mathbf{z}\_m} \right\|\tag{8}$$

Using the modulus of elasticity and mass density as updating parameters, with initial values of 175 GPa and 20000 kg/m3, i.e. corresponding to initial deflections of 2.658 mm and 2.607 mm, the fminsearch solver in Matlab® converged towards 210 GPa and 16000 kg/m<sup>3</sup> at the deflections 2.152 mm and 2.165 mm in 30 iterations and 62 objective function counts. Fig. 2 illustrates the iteration sequence, starting at the normalized input parameter coordinates ( <sup>175</sup> <sup>175</sup> , <sup>20000</sup> <sup>20000</sup> ) and ending at ( <sup>210</sup> <sup>175</sup> , <sup>16000</sup> <sup>20000</sup> ). Interestingly, the algorithm first seemed to localize a local minimum but proceeded to the global minimum.

### **4. Case study**

The New Årsta Bridge in Stockholm, Sweden, was adopted for FE model updating (see Fig. 3). Previous research pointed out some of the difficulties in studying bridge dynamics resulting from moving traffic (Wiberg et al., 2009). Not only does the dynamic amplification depends on the considered load effect, but different modeling parameters, individually or jointly, influence the dynamic load effect or dynamic property in question. The use of statistically identified updating parameters as a step in more effective model optimization is highlighted in previous study by the author and typical results from a statistical parameter study on this specific bridge are exemplified in Fig. 4 and found in Wiberg et al. (2009) where the factorial experimentation technique was used. The type of information encountered in Fig. 4 is considered extremely important and valuable. Thus, the statistical method of factorial experimentation, in contrast to ordinary parameter sensitivity analyzes where parameters are varied one at a time, captures the synergy effects. Consequently, a modeling parameter can be significant even though it individually is found insignificant and an optimal amount of updating parameters to include in the optimization can therefore be identified. This leads to shorter solution times as the optimization algorithm itself is iterative and becomes

Fig. 3. The spectacular New Årsta Bridge in Stockholm.

for Increased Accuracy in Moving Load Simulations

locations is found in Wiberg (2006).

**4.2 The loadings**

specified in design codes.

**4.2.2 The Rc6 locomotive**

**4.2.1 General**

was released for longitudinal movements at other supports. The totally 24 Swiss mageba pot bearings had the function of hinges for free rotation about the transverse bridge deck axis. Torsional rotation of the bridge over piers was constrained to follow the bending of the oval piers in their stiff direction. Bridge deck rotation about the vertical axis over each pier was prevented due to the support consisting of two bearings in the transverse direction. The lower basis of all piers were assumed to be clamped but in reality the foundation blocks of P8 and P9 rested on concrete filled steel piles. A thorough description of the bridge with all sensor

<sup>209</sup> Optimized Model Updating of a Railway Bridge

In this study the FE model was updated using tests with Swedish Rc6 locomotives. The updated model was then used to study the effect of passing high speed trains (HSLM) as

The updating process considered a field test with two Swedish Rc6 locomotives positioned at different locations in a static load test according to Wiberg (2009) and, in a dynamic load test, one locomotive crossing the bridge at different speeds. The locomotive is visualized in Fig. 7(a). Each of the four axles was represented as a point load of 19.5 tons and a

Normalized modulus of elasticity (*p*1,*j*/*p*1,0) Fig. 2. Sequence of updating parameter points in the normalized updating parameter space. The contours represent the magnitude of the response objective function.

very time-consuming for large dynamic simulations with inappropriately many updating parameters causing unnecessarily many iterations.

A large-scale simplified bridge FE model in the Solvia FE system was verified as reliable for global analysis and manually tuned concerning an equivalent modulus of elasticity and mass density by using operational modal analysis and static load tests (Wiberg, 2006; 2007; 2009; Wiberg & Karoumi, 2009). This 3D modified Bernoulli-Euler beam model was therefore used as a basis for the present study.

### **4.1 The bridge**

The eleven span New Årsta Bridge of approximately 815 m has main spans of 78 m. Elevation and plan view with the monitoring sections is presented in Fig. 5. The cross section of the bridge is complex with a parabolic height variation. To make the slender design possible, the sections were extensively reinforced and prestressed. To use a simplified inclusion of tendons in the model, they were concentrated to the center of gravity along the bridge and not distributed within the cross section. Further, the UIC 60 rails of the double track bridge were modeled with rectangular beam elements, giving cross sectional properties corresponding to the actual rail cross section. The element length was at most 0.5 m (both for bridge and rail elements) and each rail node was connected to the corresponding bridge node with a rigid link. The FE model of the bridge consisted of linear, elastic and isotropic materials. Support conditions were assumed according to bridge design documents, but also verified as reliable in previous work (Wiberg, 2009). Fig. 6 represents the boundary conditions, where the legend *F* indicates that the bridge deck and pier are fixed in translation movement. The main girder 6 Will-be-set-by-IN-TECH

Normalized modulus of elasticity (*p*1,*j*/*p*1,0)

Fig. 2. Sequence of updating parameter points in the normalized updating parameter space.

very time-consuming for large dynamic simulations with inappropriately many updating

A large-scale simplified bridge FE model in the Solvia FE system was verified as reliable for global analysis and manually tuned concerning an equivalent modulus of elasticity and mass density by using operational modal analysis and static load tests (Wiberg, 2006; 2007; 2009; Wiberg & Karoumi, 2009). This 3D modified Bernoulli-Euler beam model was therefore used

The eleven span New Årsta Bridge of approximately 815 m has main spans of 78 m. Elevation and plan view with the monitoring sections is presented in Fig. 5. The cross section of the bridge is complex with a parabolic height variation. To make the slender design possible, the sections were extensively reinforced and prestressed. To use a simplified inclusion of tendons in the model, they were concentrated to the center of gravity along the bridge and not distributed within the cross section. Further, the UIC 60 rails of the double track bridge were modeled with rectangular beam elements, giving cross sectional properties corresponding to the actual rail cross section. The element length was at most 0.5 m (both for bridge and rail elements) and each rail node was connected to the corresponding bridge node with a rigid link. The FE model of the bridge consisted of linear, elastic and isotropic materials. Support conditions were assumed according to bridge design documents, but also verified as reliable in previous work (Wiberg, 2009). Fig. 6 represents the boundary conditions, where the legend *F* indicates that the bridge deck and pier are fixed in translation movement. The main girder

The contours represent the magnitude of the response objective function.

parameters causing unnecessarily many iterations.

1 1.05 1.1 1.15 1.2 1.25

Normalized

0.75

as a basis for the present study.

**4.1 The bridge**

0.8

0.85

0.9

0.95

1

 mass density

 (

*p*2,

/*j*

*p*2,0)

Fig. 3. The spectacular New Årsta Bridge in Stockholm.

was released for longitudinal movements at other supports. The totally 24 Swiss mageba pot bearings had the function of hinges for free rotation about the transverse bridge deck axis. Torsional rotation of the bridge over piers was constrained to follow the bending of the oval piers in their stiff direction. Bridge deck rotation about the vertical axis over each pier was prevented due to the support consisting of two bearings in the transverse direction. The lower basis of all piers were assumed to be clamped but in reality the foundation blocks of P8 and P9 rested on concrete filled steel piles. A thorough description of the bridge with all sensor locations is found in Wiberg (2006).

### **4.2 The loadings**

### **4.2.1 General**

In this study the FE model was updated using tests with Swedish Rc6 locomotives. The updated model was then used to study the effect of passing high speed trains (HSLM) as specified in design codes.

### **4.2.2 The Rc6 locomotive**

The updating process considered a field test with two Swedish Rc6 locomotives positioned at different locations in a static load test according to Wiberg (2009) and, in a dynamic load test, one locomotive crossing the bridge at different speeds. The locomotive is visualized in Fig. 7(a). Each of the four axles was represented as a point load of 19.5 tons and a

( )

F FFF F FF

NL P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 SL 1 2 3 4 5 6 7 8 9 10 11 48.15 9 x 78 65

<sup>211</sup> Optimized Model Updating of a Railway Bridge

(a) Rc6 locomotive.

(b) HSLM-A configurations.

representative distribution in the moving load case using amplitude functions. The internal distance between the axles in a bogie was 2.7 m and the bogie center to center distance was

The high speed load models, intended for railway bridge simulations above 200 km/h, were adopted here to subject the optimized FE model for more extreme dynamics than the current maximum speed limit of 140 km/h across the bridge. Fig. 7(b) is used in Eurocode to represent the HSLM-A configurations (CEN, 2002). Appendix 5.1 specifies the varying number of intermediate coaches, coach lengths, bogie axle spacings and point forces between the 10

In dynamic modeling, the dynamic characteristics of the bridge are of main concern, i.e. natural frequencies, mode shapes and damping ratios, why those should be focused on in detail. For that purpose, the objective function of Zárate & Caicedo (2008) would be optimal:

*fmi* − *fi*

� **p***j* � � � � � � � ⎤

<sup>⎦</sup> (9)

*fmi*

*φmi*, *φ<sup>i</sup>* � **p***j* ��� + � � � � � �

Fig. 6. Boundary conditions assigned to the bridge model.

for Increased Accuracy in Moving Load Simulations

Fig. 7. Representation of vehicle loads.

**4.2.3 The HSLM-A con¿gurations**

different HSLM-A configurations.

Π =

*n* ∑ *i*=1 ⎡ ⎣ �

1 − MAC �

**4.3 Model optimization**

Pier Span

7.7 m.

Positive normal scores

Fig. 4. Half normal plot with absolute values of estimated FE modeling parameter effect on vertical bridge deck acceleration. Factor definition: (*A*) damping ratio, (*B*) tendons and (*C*) vehicle speed.

Fig. 5. Elevation and plan view of the New Årsta Bridge. Between the northern and southern abutment, NL and SL, respectively, the 10 piers are designated P1 to P10. Strain and acceleration sensor sections are marked A, B and C. Section 1, 2, 3 and 4 were used for vertical deflection measurements.

8 Will-be-set-by-IN-TECH

*C*

*BC*

*B*

*A*

( ) ( ) ( ) ( ) ( )

( )

( )


vehicle speed.

0

( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )

P2

P3

( )

P1

vertical deflection measurements.

NL

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

 effect|

Positive normal scores

( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )

P4 P5 P6 P7 P8 P9 P10 SL

78 m C A B

4 3 2 1

Fig. 4. Half normal plot with absolute values of estimated FE modeling parameter effect on vertical bridge deck acceleration. Factor definition: (*A*) damping ratio, (*B*) tendons and (*C*)

NL P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 SL

Fig. 5. Elevation and plan view of the New Årsta Bridge. Between the northern and southern

abutment, NL and SL, respectively, the 10 piers are designated P1 to P10. Strain and acceleration sensor sections are marked A, B and C. Section 1, 2, 3 and 4 were used for

0 0.5 1 1.5 2 2.5

Fig. 6. Boundary conditions assigned to the bridge model.

(b) HSLM-A configurations.

Fig. 7. Representation of vehicle loads.

representative distribution in the moving load case using amplitude functions. The internal distance between the axles in a bogie was 2.7 m and the bogie center to center distance was 7.7 m.

### **4.2.3 The HSLM-A con¿gurations**

The high speed load models, intended for railway bridge simulations above 200 km/h, were adopted here to subject the optimized FE model for more extreme dynamics than the current maximum speed limit of 140 km/h across the bridge. Fig. 7(b) is used in Eurocode to represent the HSLM-A configurations (CEN, 2002). Appendix 5.1 specifies the varying number of intermediate coaches, coach lengths, bogie axle spacings and point forces between the 10 different HSLM-A configurations.

#### **4.3 Model optimization**

In dynamic modeling, the dynamic characteristics of the bridge are of main concern, i.e. natural frequencies, mode shapes and damping ratios, why those should be focused on in detail. For that purpose, the objective function of Zárate & Caicedo (2008) would be optimal:

$$\Pi = \sum\_{i=1}^{n} \left[ \left[ 1 - \text{MAC} \left( \phi\_{mi}, \phi\_{i} \left( \mathbf{p}\_{j} \right) \right) \right] + \left| \frac{f\_{mi} - f\_{i} \left( \mathbf{p}\_{j} \right)}{f\_{mi}} \right| \right] \tag{9}$$

No. Type

for Increased Accuracy in Moving Load Simulations

<sup>a</sup> Wiberg (2006)

<sup>c</sup> Wiberg (2007)

⎧ ⎪⎨

⎪⎩

manually tuned FE model.

small in this case, see Wiberg (2009).

bridges in design codes (see CEN (2002)).

<sup>b</sup> Wiberg & Karoumi (2009)

Predicted Measured

tuned1 FFT<sup>a</sup> EFDD<sup>b</sup> SSI-PC<sup>c</sup>

⎫ ⎪⎬

⎪⎭

(10)

(11)

FEinitial FE<sup>a</sup>

1 bending 1.03 1.30 1.30 1.29 (-) 2 coupled 1.13 1.44 1.45 1.45 (-) 3 coupled 1.91 2.45 2.43 2.43 2.43 4 coupled 2.53 3.26 3.26 - 3.24 5 coupled 2.78 3.55 3.55 3.50 3.55

<sup>213</sup> Optimized Model Updating of a Railway Bridge

Table 1. Natural frequencies (Hz) from measured acceleration signals and for an initial and

the optimizing algorithm unstable. However, the effect of unconstrained warping is relatively

Frequency residuals only, strain residuals only, deflection residuals only, acceleration residuals

� *Ej E*0 , *ρj ρ*0 �

**z**<sup>1</sup> = (*f*1, *f*5,*ε*1,...,*ε*51, *v*1,..., *v*20)

**z**<sup>2</sup> = (*a*1,..., *a*3)

with the indexes 1 and 2 on **p** and **z** corresponding to the two different optimization steps. Thus, Eq. 10 was used with 2 frequencies, 51 strains and 20 deflections all together included, but also for frequencies, strains and deflections separately. Unfortunately, none of the installed axial strain transducers was active during the dynamic load testing. Therefore, according to Eq. 11, modal damping was tuned against acceleration residuals only, based on the three monitoring sections of Fig. 5. The location of all sensors within the monitoring sections were considered redundant information here but is to be found in for example Wiberg (2006).

An educated guess of the initial vector of updating parameters was necessary. Based on the results of Wiberg (2006) and Wiberg (2009), manually tuned start values of *E*<sup>0</sup> = 55 GPa and *ρ*<sup>0</sup> = 2500 kg/m<sup>3</sup> were used for modulus of elasticity and mass density, respectively, and a constant damping ratio of *ζ*<sup>0</sup> = 0.01 was assigned to all modes and used in the mode superposition procedure. This corresponds to the modal damping ratio found for prestressed

All load testing used Rc6 locomotives and is described in detail in Wiberg (2009). Mode superposition was used to calculate the responses of the simulated Rc6 locomotive crossings with a time step of Δ*t* = 5 ms. The initial implicit time integration in the geometrically

� *ζj ζ*0 � ⎫ ⎪⎬

⎪⎭

only and their combinations were studied independently according to the principle:

**p**<sup>1</sup> =

**p**<sup>2</sup> =

⎧ ⎪⎨

⎪⎩

However, as the modal assurance criterion (MAC) values were unavailable the objective function in Eq. 6 was considered instead. No focuses was placed in evaluating different objective functions and the influence of variations in standard deviations (weight).

All 6 modeling parameters in Wiberg et al. (2009), i.e. damping ratios, modulus of elasticity, rails, tendons, vehicle speed and mass density, were significantly influencing typical dynamic load effects and the dynamic properties of the bridge. Therefore, they were all included in the optimization process. Damping and vehicle speed were obviously only considered in the dynamic analyzes. The importance of rails and tendons was analyzed based on their inclusion or exclusion in the FE model. The material properties of the rails and tendons were assumed as known. The prestress effect was included in a geometrically nonlinear large displacement analysis preceding each linear FE model restart execution for static and dynamic load effects. Modal damping was used in mode superposition of the moving load simulations. Thus, in the calculation of the mode shapes and frequencies, the effects of the axial compressive load on the modes and frequencies are included since the numerical calculation is based on the configuration at the start of the restart analysis. The linear mode superposition analysis that followed were then based on these mode shapes and frequencies, resulting in a dynamic response relative the prestressed bridge configuration.

In Table 1 the frequency columns from left to right are results from: an initial and manually tuned FE model in Wiberg (2006) but without rails and tendons, fast Fourier transforms of acceleration signals in Wiberg (2006), enhanced frequency domain decompositions from operational modal analysis in Wiberg & Karoumi (2009) and stochastic subspace identifications from operational modal analysis in Wiberg (2007). A dash only (see EFDD in Table 1) means undetected, while the dashes with parentheses (see SSI-PC in Table 1) stands for detected but unstable in the stabilization diagram as a result of operational modal analysis in Wiberg (2007). As can be seen from Table 1, already a simple manual updating resulted in a correct estimation of natural frequencies. However, the obtained high equivalent modulus of elasticity was questioned and therefore object of optimized updating. In addition, the initial manually tuned FE model used boundary conditions proven to be somewhat inaccurate according to Wiberg (2009). Henceforth, the notations differ between initial, FEinitial, initial manually tuned, FEtuned1 , final manually tuned, FEtuned2 , and optimized FE model, FEoptimized.

The optimization process was performed in the following two steps, based on the final manually tuned FE model:


The frequency residuals were based on FE solutions using the subspace iteration method carried out for the structure linearized at the start of the restart analysis after prestress. The frequencies *f*<sup>1</sup> and *f*<sup>5</sup> at 1.3 Hz and 3.55 Hz were used, see Table 1. Strain residuals were based on axial beam stresses. The FE code can be modified to include the constrained warping effect on stresses. This was not considered here as it is based on torsional curvatures, manually given from separate analyzes. To include them as updating parameters was tested but made 10 Will-be-set-by-IN-TECH

However, as the modal assurance criterion (MAC) values were unavailable the objective function in Eq. 6 was considered instead. No focuses was placed in evaluating different

All 6 modeling parameters in Wiberg et al. (2009), i.e. damping ratios, modulus of elasticity, rails, tendons, vehicle speed and mass density, were significantly influencing typical dynamic load effects and the dynamic properties of the bridge. Therefore, they were all included in the optimization process. Damping and vehicle speed were obviously only considered in the dynamic analyzes. The importance of rails and tendons was analyzed based on their inclusion or exclusion in the FE model. The material properties of the rails and tendons were assumed as known. The prestress effect was included in a geometrically nonlinear large displacement analysis preceding each linear FE model restart execution for static and dynamic load effects. Modal damping was used in mode superposition of the moving load simulations. Thus, in the calculation of the mode shapes and frequencies, the effects of the axial compressive load on the modes and frequencies are included since the numerical calculation is based on the configuration at the start of the restart analysis. The linear mode superposition analysis that followed were then based on these mode shapes and frequencies, resulting in a dynamic

In Table 1 the frequency columns from left to right are results from: an initial and manually tuned FE model in Wiberg (2006) but without rails and tendons, fast Fourier transforms of acceleration signals in Wiberg (2006), enhanced frequency domain decompositions from operational modal analysis in Wiberg & Karoumi (2009) and stochastic subspace identifications from operational modal analysis in Wiberg (2007). A dash only (see EFDD in Table 1) means undetected, while the dashes with parentheses (see SSI-PC in Table 1) stands for detected but unstable in the stabilization diagram as a result of operational modal analysis in Wiberg (2007). As can be seen from Table 1, already a simple manual updating resulted in a correct estimation of natural frequencies. However, the obtained high equivalent modulus of elasticity was questioned and therefore object of optimized updating. In addition, the initial manually tuned FE model used boundary conditions proven to be somewhat inaccurate according to Wiberg (2009). Henceforth, the notations differ between initial, FEinitial, initial manually tuned, FEtuned1 , final manually tuned, FEtuned2 , and optimized FE

The optimization process was performed in the following two steps, based on the final

1. Identification of updated material parameters (modulus of elasticity and mass density) from static load tests for strain and deflection residuals, together with frequency residuals. 2. Identification of modal damping ratio from dynamic load tests with maximum and root

The frequency residuals were based on FE solutions using the subspace iteration method carried out for the structure linearized at the start of the restart analysis after prestress. The frequencies *f*<sup>1</sup> and *f*<sup>5</sup> at 1.3 Hz and 3.55 Hz were used, see Table 1. Strain residuals were based on axial beam stresses. The FE code can be modified to include the constrained warping effect on stresses. This was not considered here as it is based on torsional curvatures, manually given from separate analyzes. To include them as updating parameters was tested but made

objective functions and the influence of variations in standard deviations (weight).

response relative the prestressed bridge configuration.

model, FEoptimized.

manually tuned FE model:

mean square (rms) acceleration residuals.


<sup>a</sup> Wiberg (2006)

<sup>b</sup> Wiberg & Karoumi (2009)

$$^c\text{ Wiberg (2007)}$$

Table 1. Natural frequencies (Hz) from measured acceleration signals and for an initial and manually tuned FE model.

the optimizing algorithm unstable. However, the effect of unconstrained warping is relatively small in this case, see Wiberg (2009).

Frequency residuals only, strain residuals only, deflection residuals only, acceleration residuals only and their combinations were studied independently according to the principle:

$$\begin{cases} \mathbf{p}\_1 = \left( \frac{E\_j}{E\_0}, \frac{\rho\_j}{\rho\_0} \right) \\ \mathbf{z}\_1 = (f\_{1\prime} f\_{5\prime} \varepsilon\_{1\prime}, \dots, \varepsilon\_{51\prime} v\_{1\prime}, \dots, v\_{20}) \end{cases} \tag{10}$$

$$\left\{ \begin{array}{c} \mathbf{p}\_{2} = \left( \frac{\mathcal{J}\_{j}}{\mathcal{J}\_{0}} \right) \\\\ \mathbf{z}\_{2} = (a\_{1}, \ldots, a\_{3}) \end{array} \right\} \tag{11}$$

with the indexes 1 and 2 on **p** and **z** corresponding to the two different optimization steps. Thus, Eq. 10 was used with 2 frequencies, 51 strains and 20 deflections all together included, but also for frequencies, strains and deflections separately. Unfortunately, none of the installed axial strain transducers was active during the dynamic load testing. Therefore, according to Eq. 11, modal damping was tuned against acceleration residuals only, based on the three monitoring sections of Fig. 5. The location of all sensors within the monitoring sections were considered redundant information here but is to be found in for example Wiberg (2006).

An educated guess of the initial vector of updating parameters was necessary. Based on the results of Wiberg (2006) and Wiberg (2009), manually tuned start values of *E*<sup>0</sup> = 55 GPa and *ρ*<sup>0</sup> = 2500 kg/m<sup>3</sup> were used for modulus of elasticity and mass density, respectively, and a constant damping ratio of *ζ*<sup>0</sup> = 0.01 was assigned to all modes and used in the mode superposition procedure. This corresponds to the modal damping ratio found for prestressed bridges in design codes (see CEN (2002)).

All load testing used Rc6 locomotives and is described in detail in Wiberg (2009). Mode superposition was used to calculate the responses of the simulated Rc6 locomotive crossings with a time step of Δ*t* = 5 ms. The initial implicit time integration in the geometrically

Parameter FEinit FEtuned1 FEtuned2 FEoptimized Modulus of elasticity (GPa) 36 55 55 60 Mass density (kg/m3) 2500 2400 2500 2700 Modal damping ratio (%) - - 1.0 0.92;2.10 Rail excluded excluded included included Tendons excluded excluded included included Boundary condition state 1 state 1 state 2 state 2

<sup>215</sup> Optimized Model Updating of a Railway Bridge

Table 2. Differences between updating parameters of initial, manually tuned and optimized FE model. Modal damping ratios for the optimized FE model corresponds to rms and

with its restrictions as a beam model and the relatively few number of updating parameters chosen for the FE model. In addition, some sensors and deflection measurements resulted in result distortion, probably due to a difference in assumed sensor position or other sources of errors. Frequencies and load effects are also non stationary due to time dependent effects, not considered in the FE model and therefore influencing the optimization accuracy since the

The mean result of adding the updating parameter vector from the frequency optimization procedure separately, the deflection optimization procedure separately and the strain optimization procedure separately, constituted the updating parameter values of modulus of elasticity and mass density in the optimized FE model. Consequently, these three different objective function contributors, separately gave different optimized updating parameter values of modulus of elasticity and mass density. Notice therefore, if the intention for example is superior dynamic characteristics, it would have been better to concentrate on the frequency residuals solely, complemented with mode shape information. However, the intention here was again to implement the algorithm and investigate the possibilities with a simplified FE

The results of the optimized updating parameters are summarized in Table 2 as parameter value or structural condition before and after optimization. Obviously, the optimized values of modulus of elasticity and mass density had a negligible influence concerning the frequencies. This was reasonable as Table 1 already indicated good agreement in frequencies between measurements and manually tuned FE model. Therefore, the bending stiffness to mass ratio for the final manually tuned FE model at iteration start (55/2500) was similar to the ratio of the converged optimized FE model at (60/2700) in the typical iteration sequence of Fig. 8. Still, frequencies were included in the objective function to account for the change in

The increased values in modulus of elasticity and mass density were believed to have a larger effect in the optimization based on static strains and deflections. Table 3 summarizes results for static strains and deflections as initially predicted, predicted with the optimized FE model and measured. Observe that strain results are exemplified with the values of one single strain transducer and its position in that monitoring section (A, B or C) according to Fig. 5 for one of the six different static load test configurations in Wiberg (2009). Deflections were presented

structural system concerning the inclusion of rails and tendons.

maximum acceleration, respectively.

for Increased Accuracy in Moving Load Simulations

model.

measurements took place at different occasions.

nonlinear axial load case operated on the basic equation of motion using the BFGS matrix update method algorithm (SOLVIA® Finite Element System, 2007).

Due to the restrictions of the beam FE model, i.e. using a beam element node to compare accelerations at the locations of accelerometers in the cross section, these signals were not comparable in the first place. Measured and modeled acceleration signals from the crossing Rc6 locomotive were therefore first low-pass filtered with a Butterworth filter at 5 Hz and then smoothed, using Savitzky-Golay filtering. Generally, a FE model is not optimal in reproducing high frequency content, especially not in representing a complex structure with a simple beam as is the case here. The low-pass filter at 5 Hz for reasonable acceleration comparison was therefore motivated. A Savitzky-Golay smoothing filter was chosen as they typically are used for a noisy signal whose frequency span (without noise) is large and they are considered optimal in the sense that they minimize the least-squares error in fitting a polynomial to frames of noisy data (The MathWorks, Inc., 2009).

To remove the rotational accelerations due to torsion, the measured signals from two accelerometers, 1 and 2, at the same distance from the center of gravity but on opposite sides were combined to compute the vertical translation acceleration only according to:

$$a\_{\mathbf{b}} = \frac{a\_1 + a\_2}{2} \tag{12}$$

In this way, assuming an infinitely stiff cross section, predicted vertical node accelerations were directly comparable with the measured bending acceleration *a*<sup>b</sup> in monitoring section *C*, see Fig. 5. However, with only one accelerometer in monitoring section *B*, the predicted total vertical acceleration *a*tot for comparison with measurements was calculated from beam node accelerations as:

$$a\_{\rm tot} = a\_{\rm b} + L \cdot a\_{\rm r} \tag{13}$$

with *a*<sup>b</sup> the bending acceleration at center of gravity, *a*<sup>r</sup> the rotational acceleration around the axial beam axis through center of gravity and *L* the distance perpendicular to the vertical axis, from center of gravity to the measuring position.

#### **4.4 Relevant moving load simulations**

After optimization, resulting in updated modulus of elasticity, mass density and modal damping ration, the FE model was finally subjected to all ten HSLM-A configurations for more reliable moving load simulations. These load configurations crossed the bridge as point loads with corresponding amplitude functions on the outermost track solely, moving from NL to SL, at speeds between 100 and 250 km/h. Typical results of interest were bridge deck deflection, acceleration and bending moment. These were all estimated and evaluated in more detail for the most critical HSLM configurations.

#### **5. Results and discussion**

#### **5.1 Model optimization**

The optimization algorithm operated efficiently but it was found unattainable to include all measurements in the response vector simultaneously. This was basically since the large-scale simplified model is incapable of predicting results based on all monitoring sections in Fig. 5 12 Will-be-set-by-IN-TECH

nonlinear axial load case operated on the basic equation of motion using the BFGS matrix

Due to the restrictions of the beam FE model, i.e. using a beam element node to compare accelerations at the locations of accelerometers in the cross section, these signals were not comparable in the first place. Measured and modeled acceleration signals from the crossing Rc6 locomotive were therefore first low-pass filtered with a Butterworth filter at 5 Hz and then smoothed, using Savitzky-Golay filtering. Generally, a FE model is not optimal in reproducing high frequency content, especially not in representing a complex structure with a simple beam as is the case here. The low-pass filter at 5 Hz for reasonable acceleration comparison was therefore motivated. A Savitzky-Golay smoothing filter was chosen as they typically are used for a noisy signal whose frequency span (without noise) is large and they are considered optimal in the sense that they minimize the least-squares error in fitting a polynomial to

To remove the rotational accelerations due to torsion, the measured signals from two accelerometers, 1 and 2, at the same distance from the center of gravity but on opposite sides

*<sup>a</sup>*<sup>b</sup> <sup>=</sup> *<sup>a</sup>*<sup>1</sup> <sup>+</sup> *<sup>a</sup>*<sup>2</sup>

In this way, assuming an infinitely stiff cross section, predicted vertical node accelerations were directly comparable with the measured bending acceleration *a*<sup>b</sup> in monitoring section *C*, see Fig. 5. However, with only one accelerometer in monitoring section *B*, the predicted total vertical acceleration *a*tot for comparison with measurements was calculated from beam node

with *a*<sup>b</sup> the bending acceleration at center of gravity, *a*<sup>r</sup> the rotational acceleration around the axial beam axis through center of gravity and *L* the distance perpendicular to the vertical axis,

After optimization, resulting in updated modulus of elasticity, mass density and modal damping ration, the FE model was finally subjected to all ten HSLM-A configurations for more reliable moving load simulations. These load configurations crossed the bridge as point loads with corresponding amplitude functions on the outermost track solely, moving from NL to SL, at speeds between 100 and 250 km/h. Typical results of interest were bridge deck deflection, acceleration and bending moment. These were all estimated and evaluated in more

The optimization algorithm operated efficiently but it was found unattainable to include all measurements in the response vector simultaneously. This was basically since the large-scale simplified model is incapable of predicting results based on all monitoring sections in Fig. 5

<sup>2</sup> (12)

*a*tot = *a*<sup>b</sup> + *L* · *a*<sup>r</sup> (13)

were combined to compute the vertical translation acceleration only according to:

update method algorithm (SOLVIA® Finite Element System, 2007).

frames of noisy data (The MathWorks, Inc., 2009).

from center of gravity to the measuring position.

detail for the most critical HSLM configurations.

**4.4 Relevant moving load simulations**

**5. Results and discussion**

**5.1 Model optimization**

accelerations as:


Table 2. Differences between updating parameters of initial, manually tuned and optimized FE model. Modal damping ratios for the optimized FE model corresponds to rms and maximum acceleration, respectively.

with its restrictions as a beam model and the relatively few number of updating parameters chosen for the FE model. In addition, some sensors and deflection measurements resulted in result distortion, probably due to a difference in assumed sensor position or other sources of errors. Frequencies and load effects are also non stationary due to time dependent effects, not considered in the FE model and therefore influencing the optimization accuracy since the measurements took place at different occasions.

The mean result of adding the updating parameter vector from the frequency optimization procedure separately, the deflection optimization procedure separately and the strain optimization procedure separately, constituted the updating parameter values of modulus of elasticity and mass density in the optimized FE model. Consequently, these three different objective function contributors, separately gave different optimized updating parameter values of modulus of elasticity and mass density. Notice therefore, if the intention for example is superior dynamic characteristics, it would have been better to concentrate on the frequency residuals solely, complemented with mode shape information. However, the intention here was again to implement the algorithm and investigate the possibilities with a simplified FE model.

The results of the optimized updating parameters are summarized in Table 2 as parameter value or structural condition before and after optimization. Obviously, the optimized values of modulus of elasticity and mass density had a negligible influence concerning the frequencies. This was reasonable as Table 1 already indicated good agreement in frequencies between measurements and manually tuned FE model. Therefore, the bending stiffness to mass ratio for the final manually tuned FE model at iteration start (55/2500) was similar to the ratio of the converged optimized FE model at (60/2700) in the typical iteration sequence of Fig. 8. Still, frequencies were included in the objective function to account for the change in structural system concerning the inclusion of rails and tendons.

The increased values in modulus of elasticity and mass density were believed to have a larger effect in the optimization based on static strains and deflections. Table 3 summarizes results for static strains and deflections as initially predicted, predicted with the optimized FE model and measured. Observe that strain results are exemplified with the values of one single strain transducer and its position in that monitoring section (A, B or C) according to Fig. 5 for one of the six different static load test configurations in Wiberg (2009). Deflections were presented

Static load effect FEAinitial FEAoptimized Measured Strain A (10<sup>−</sup>6) 37.9 22.7 23.2 Strain B (10<sup>−</sup>6) 2.8 1.7 1.8 Strain C (10<sup>−</sup>6) 16.9 10.2 11.1 Deflection 1 (mm) 4.3 2.6 3.0 Deflection 2 (mm) 5.8 3.5 4.0 Deflection 3 (mm) 9.5 5.7 6.5 Deflection 4 (mm) 5.8 3.5 3.5

<sup>217</sup> Optimized Model Updating of a Railway Bridge

FEAinitial FEAinitial FEAoptimized FEAoptimized Measured Measured max rms max rms max rms 0.01630 0.00387 0.01195 0.00303 0.01195 0.00303

Time/s

Fig. 9. Measured acceleration signal together with maximum and rms acceleration of the

optimized FE model. All signals are filtered with a low pass filter at 5 Hz.

0 5 10 15 20 25

0 5 10 15 20 25

0 5 10 15 20 25

**measured**

**max**

**rms**

Table 4. Modeled and measured vertical accelerations (m/s**2**) in the center of gravity of

Table 3. Modeled and measured static strains and deflections.

for Increased Accuracy in Moving Load Simulations

monitoring section C, filtered with a low pass filter at 5 Hz.

Acceleration/ms




−2

Fig. 8. Typical iteration sequence for optimization according to frequency residuals separately.

for the largest residual between initial FE model prediction and measured mean deflection in the point of interest (1, 2, 3 or 4) in Fig. 5. Notice that the initial FE model gave results on the safe side in all cases, while the updated FE model tended to be too optimistic, i.e. gave smaller load effect values than the measured ones.

Results for accelerations, based on the optimized values of modal damping ratios in Table 2, are presented in Table 4 for both measured, maximum and rms predicted acceleration. The corresponding acceleration signals are shown in Fig. 9. These signals represent a complete Rc6 locomotive crossing from SL to NL, traveling in outer curve at a speed of 120 km/h. Observe that the measured acceleration in the top of Fig. 9 is based on the signal manipulation according to Eq. 12. However, the way the measured signal looks may indicate that it still has some torsional acceleration included, i.e. that the beam element assumption of a rigid cross section with negligible in-plane stresses may not be completely satisfactory for the studied section. To be correct, a volume or shell element model of part of the bridge is necessary to include typical local flange modes, probably influencing the edge beam but are completely missed with the stiff cross section of the beam element. Consequently, it seems reasonable to base an optimized damping ratio on maximum acceleration for comparison with design codes, as those specify requirements on the maximum acceleration. However, in this case the predicted maximum acceleration may be too low due to the discretization and solution errors.

Even if the optimized model did not reproduce measured responses with highest accuracy in all cases it was considered reliable for the type of dynamic analysis assigned in design codes. At the same time, this is likely to be as far as one can get with a simplified FE model. It was not the intention with the simplified model in the first place to most accurately

14 Will-be-set-by-IN-TECH

*E ρ* Π

Iteration

for the largest residual between initial FE model prediction and measured mean deflection in the point of interest (1, 2, 3 or 4) in Fig. 5. Notice that the initial FE model gave results on the safe side in all cases, while the updated FE model tended to be too optimistic, i.e. gave smaller

Results for accelerations, based on the optimized values of modal damping ratios in Table 2, are presented in Table 4 for both measured, maximum and rms predicted acceleration. The corresponding acceleration signals are shown in Fig. 9. These signals represent a complete Rc6 locomotive crossing from SL to NL, traveling in outer curve at a speed of 120 km/h. Observe that the measured acceleration in the top of Fig. 9 is based on the signal manipulation according to Eq. 12. However, the way the measured signal looks may indicate that it still has some torsional acceleration included, i.e. that the beam element assumption of a rigid cross section with negligible in-plane stresses may not be completely satisfactory for the studied section. To be correct, a volume or shell element model of part of the bridge is necessary to include typical local flange modes, probably influencing the edge beam but are completely missed with the stiff cross section of the beam element. Consequently, it seems reasonable to base an optimized damping ratio on maximum acceleration for comparison with design codes, as those specify requirements on the maximum acceleration. However, in this case the predicted maximum acceleration may be too low due to the discretization and solution errors. Even if the optimized model did not reproduce measured responses with highest accuracy in all cases it was considered reliable for the type of dynamic analysis assigned in design codes. At the same time, this is likely to be as far as one can get with a simplified FE model. It was not the intention with the simplified model in the first place to most accurately

Fig. 8. Typical iteration sequence for optimization according to frequency residuals

0 5 10 15 20 25 30 35 40 15 20 25 30 35 40

Objective


0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

 value

function

Normalized

separately.

0.95

1

load effect values than the measured ones.

1.05

1.1

1.15

1.2

1.25

1.3

1.35

updating

parameters


Table 3. Modeled and measured static strains and deflections.


Table 4. Modeled and measured vertical accelerations (m/s**2**) in the center of gravity of monitoring section C, filtered with a low pass filter at 5 Hz.

Fig. 9. Measured acceleration signal together with maximum and rms acceleration of the optimized FE model. All signals are filtered with a low pass filter at 5 Hz.

Speed/kmh−<sup>1</sup>

Deflection/mm

Acceleration/ms

3.9

4

4.1

4.2

4.3

4.4

4.5

4.6

4.7

0.1

0.2

0.3

0.4

−2

Fig. 11. Identification of the HSLM-A configurations corresponding to the envelope results. Bending moment is symbolized with (◦), vertical acceleration with () and vertical deflection

<sup>219</sup> Optimized Model Updating of a Railway Bridge

Speed/kmh−<sup>1</sup>

acceleration and deflection. A speed increment of 5 km/h was used.

Fig. 12. The three most critical HSLM-A configurations, corresponding to HSLM-A2, HSLM-A7 and HSLM-A10, respectively, for bridge deck bending moment, vertical

100 100150 200 250

100 150 200 250

HSLM-A

with (�).

Moment/MNm

17.5

18

18.5

19

1

moment acceleration deflection

2

3

4

5

6

7

8

9

10

for Increased Accuracy in Moving Load Simulations

configuration

Fig. 10. Envelopes for bridge deck bending moment, vertical acceleration and deflection among all ten HSLM-A configurations with a speed increment of 10 km/h.

predict measurements. The main objective was to implement the optimization methodology and procedure in combination with statistical techniques to identify individually and jointly influencing FE modeling parameters to perform time efficient and relevant moving load simulations. In addition, the number and choice of updating parameters and the content of the objective function influence the possibilities of the adopted model.

Based on the optimized FE model, moving load simulations were performed with the ten HSLM-A train loads for increased accuracy in dynamic load effect predictions. Fig. 10 illustrates the envelope results for bridge deck bending moment, vertical acceleration and vertical deflection with a speed increment of 10 km/h between 100 km/h and 250 km/h. The most critical configurations were identified in Fig. 11 and found to be HSLM-A2, HSLM-A7 and HSLM-A10, respectively. For those three train loads, new results were presented in Fig. 12 for a speed increment of 5 km/h. Finally, the identified critical speeds in Fig. 12 were used to predict the load effects, at the critical location found in Fig. 13, from complete train crossings in time domain. The critical speeds corresponded to 165 km/h, 240 km/h and 180 km/h for HSLM-A2, HSLM-A7 and HSLM-A10, respectievely.

Moments and accelerations showed relatively small differences compared to results using the initial FE model. However, deflections were considerably smaller compared to the results of the initial FE model according to Fig. 14. The optimized FE model corresponded to a dynamic amplification factor of 1.15 in deflection, compared to 1.09 for the initial FE model. Observe that these results are given for the node with maximum vertical acceleration. Obviously, the dynamic amplification can be larger elsewhere.

16 Will-be-set-by-IN-TECH

moment

acceleration deflection

Speed/kmh−<sup>1</sup>

among all ten HSLM-A configurations with a speed increment of 10 km/h.

of the objective function influence the possibilities of the adopted model.

HSLM-A2, HSLM-A7 and HSLM-A10, respectievely.

dynamic amplification can be larger elsewhere.

Fig. 10. Envelopes for bridge deck bending moment, vertical acceleration and deflection

predict measurements. The main objective was to implement the optimization methodology and procedure in combination with statistical techniques to identify individually and jointly influencing FE modeling parameters to perform time efficient and relevant moving load simulations. In addition, the number and choice of updating parameters and the content

Based on the optimized FE model, moving load simulations were performed with the ten HSLM-A train loads for increased accuracy in dynamic load effect predictions. Fig. 10 illustrates the envelope results for bridge deck bending moment, vertical acceleration and vertical deflection with a speed increment of 10 km/h between 100 km/h and 250 km/h. The most critical configurations were identified in Fig. 11 and found to be HSLM-A2, HSLM-A7 and HSLM-A10, respectively. For those three train loads, new results were presented in Fig. 12 for a speed increment of 5 km/h. Finally, the identified critical speeds in Fig. 12 were used to predict the load effects, at the critical location found in Fig. 13, from complete train crossings in time domain. The critical speeds corresponded to 165 km/h, 240 km/h and 180 km/h for

Moments and accelerations showed relatively small differences compared to results using the initial FE model. However, deflections were considerably smaller compared to the results of the initial FE model according to Fig. 14. The optimized FE model corresponded to a dynamic amplification factor of 1.15 in deflection, compared to 1.09 for the initial FE model. Observe that these results are given for the node with maximum vertical acceleration. Obviously, the

100 100150 200 250

Deflection/mm

Acceleration/ms

4.1

4.2

4.3

4.4

4.5

4.6

4.7

4.8

0.1

0.2

0.3

0.4

−2

Moment/MNm

17.5

18

18.5

19

Fig. 11. Identification of the HSLM-A configurations corresponding to the envelope results. Bending moment is symbolized with (◦), vertical acceleration with () and vertical deflection with (�).

Fig. 12. The three most critical HSLM-A configurations, corresponding to HSLM-A2, HSLM-A7 and HSLM-A10, respectively, for bridge deck bending moment, vertical acceleration and deflection. A speed increment of 5 km/h was used.

**6. Conclusions**

reasonable.

chosen for time efficient simulations.

for Increased Accuracy in Moving Load Simulations

static and dynamic load effects more accurately.

comparison with the initial model.

acceleration, respectively, were predicted.

stands for better predictions when optimization is used.

design code requirements) and more cost-effective designs.

necessary for dynamic load effect predictions with highest accuracy.

of interest and therefore based on a suitable objective function with that intention.

Railway bridge design codes require detailed analyzes of passing trains at high speeds. Such analyzes are very time consuming as it involves many simulations using different train configurations passing at different speeds. Thus, simplified bridge and train models are

<sup>221</sup> Optimized Model Updating of a Railway Bridge

In this chapter a large-scale simplified railway bridge FE model for time efficient moving load simulations was optimized. The optimization uses natural frequencies from operational modal analysis and load effects from load testing, based on previously identified updating parameters. The optimization algorithm was easily implemented for FE model updating and was shown to operate efficiently in a benchmark test and for the specific bridge. The importance and the potential of optimization procedures in FE modeling for increased accuracy in moving load simulations is highlighted. Further, it was generally concluded that: • Based on individually and jointly influencing factors, the optimized FE model predicted

• Even though the updated FE model predicted too optimistic load effects, i.e. not being on the safe side, the updated model resulted in larger dynamic amplification factor in

• The optimized FE model predicted static load effects most accurately. The natural frequencies were already accurately calculated for the manually tuned FE model.

• The previously questioned high-valued equivalent modulus of elasticity was proven to be

• Reliable modal damping ratios of 0.92% and 2.10%, for rms and maximum bridge deck

• Even if the simplified FE model in some sense is insufficient in load effect predictions, it

• More measured dynamic characteristics (natural frequencies, mode shapes and modal damping ratios), complementing updating parameters and a more detailed FE model are

To conclude, the author strongly recommend the working procedure of (1) manual FE model tuning, (2) updating parameter identification, and (3) final optimization focused on the result

Finally, this chapter highlights the potential of the adopted optimization procedure. This methodology can not only be used for model updating based on measurements, but also be introduced and customized to work already in the bridge design phase for better (based on

Fig. 13. Identification of bridge deck location of maximum bending moment, vertical acceleration and deflection of HSLM-A2, HSLM-A7 and HSLM-A10. Bending moment is symbolized with (◦), vertical acceleration with () and vertical deflection with (�).

Fig. 14. Vertical deflection at the most critical node, i.e. midspan P4-P5 , for HSLM-A10 at 180 km/h.

### **6. Conclusions**

18 Will-be-set-by-IN-TECH

Location

Deflection/mm

180 km/h.




0

1

2

3

SL P10 P9 P8 P7 P6 P5 P4 P3 P2 P1 NL

Speed/kmh−<sup>1</sup>

FEAoptimized FEAinitial

Time/s

Fig. 14. Vertical deflection at the most critical node, i.e. midspan P4-P5 , for HSLM-A10 at

0 5 10 15 20 25

Fig. 13. Identification of bridge deck location of maximum bending moment, vertical acceleration and deflection of HSLM-A2, HSLM-A7 and HSLM-A10. Bending moment is symbolized with (◦), vertical acceleration with () and vertical deflection with (�).

100 150 200 250

Railway bridge design codes require detailed analyzes of passing trains at high speeds. Such analyzes are very time consuming as it involves many simulations using different train configurations passing at different speeds. Thus, simplified bridge and train models are chosen for time efficient simulations.

In this chapter a large-scale simplified railway bridge FE model for time efficient moving load simulations was optimized. The optimization uses natural frequencies from operational modal analysis and load effects from load testing, based on previously identified updating parameters. The optimization algorithm was easily implemented for FE model updating and was shown to operate efficiently in a benchmark test and for the specific bridge. The importance and the potential of optimization procedures in FE modeling for increased accuracy in moving load simulations is highlighted. Further, it was generally concluded that:


To conclude, the author strongly recommend the working procedure of (1) manual FE model tuning, (2) updating parameter identification, and (3) final optimization focused on the result of interest and therefore based on a suitable objective function with that intention.

Finally, this chapter highlights the potential of the adopted optimization procedure. This methodology can not only be used for model updating based on measurements, but also be introduced and customized to work already in the bridge design phase for better (based on design code requirements) and more cost-effective designs.

**C. Notation**

*The following symbols are used in this chapter*

for Increased Accuracy in Moving Load Simulations

*a* = acceleration (m/s2); *A* = cross section area (m2); *E* = modulus of elasticity (Pa); *f* = natural frequency (Hz);

*n* = mode number;

*p* = elements of **p**;

*w* = elements of **W**; **W** = weighting matrix; **z** = response vector; *ε* = axial strain;

*N* = response vector length;

**p** = updating parameter vector; *v* = vertical deflection (m);

*ζ* = equivalent modal critical damping ratio;

CEN (2002). *Eurocode 1: Actions on structures – Part 2: Traffic loads on bridges (prEN 1991-2)*. Coleman, T. F. & Zhang, Y. (2009). *Optimization Toolbox*TM *4 User's Guide*, The MathWorks, Inc. Friswell, M. I. & Mottershead, J. E. (1995). *Finite Element Model Updating in Structural Dynamics*,

<sup>223</sup> Optimized Model Updating of a Railway Bridge

Jaishi, B. & Ren, W. X. (2005). Structural finite element model updating using ambient

Jonsson, F. & Johnson, D. (2007). *Finite Element Model Updating of the New Svinesund*

Lagarias, J. C., Reeds, J. A., Wright, M. H. & Wright, P. E. (1998). Convergence properties of

Mottershead, J. E. & Friswell, M. I. (1993). Model updating in structural dynamics: A survey,

*Bridge. Manual Model Refinement with Non-Linear Optimization*, Msc thesis, Chalmers

the nelder-mead simplex method in low dimensions, *SIAM Journal of Optimization*

vibration test results, *J. Struct. Engrg.* 131(4): 617–628.

University of Technology, Sweden.

*Journal of Sound and Vibration* 167(2): 347–375.

Π = scalar objective function value;

*ρ* = mass density (kg/m3); *σ* = standard deviation; *φ* = natural vibration mode; *ω* = circular frequency (rad/s);

**8. References**

Springer.

9(1): 112–147.

### **7. Appendix**

### **A. Benchmark input**

*The following input are used in the Benchmark test:*


#### **B. HSLM-A**


### **C. Notation**

20 Will-be-set-by-IN-TECH

*m*<sup>2</sup> = 20000 kg

*I* = 0.01573 m<sup>4</sup>

*ρ* = 16000 kg/m<sup>3</sup>

Coach length *D* (m)

*<sup>P</sup>* (kN) intermediate coaches spacing *N d* (m)

A1 18 18 2.0 170 A2 17 19 3.5 200 A3 16 20 2.0 180 A4 15 21 3.0 190 A5 14 22 2.0 170 A6 13 23 2.0 180 A7 13 24 2.0 190 A8 12 25 2.5 190 A9 11 26 2.0 210 A10 11 27 2.0 210

Bogie axle Point force

*ν* = 0.3

Number of

**7. Appendix**

**B. HSLM-A**

**A. Benchmark input**

*The following input are used in the Benchmark test:*

Masses: *m*<sup>1</sup> = 1000 kg

Initial velocity: *v* = 30 m/s Initial displacement of *m*2: *δ* = 0.05 m Stiffness: *k* = 4 · 106 N/m Damping: *c* = 1 · 105 Ns/m

Time step: Δ*t* = 0.5 ms Beam section properties: *A* = 0.06128 m<sup>2</sup>

Material properties: *E* = 210 GPa

Universal Train

*The following symbols are used in this chapter*


### **8. References**

CEN (2002). *Eurocode 1: Actions on structures – Part 2: Traffic loads on bridges (prEN 1991-2)*.


**9** 

*Iran* 

**Collection Mats** 

**Controlling and Simulation of Stray Currents in** 

**DC Railway by Considering the Effects of** 

*School of Railway Engineering, Iran University of Science and Technology, Tehran,* 

Urban rail transit systems are mostly electrically DC type. Usually in these systems for reducing the costs, running rails are used as the return current paths. Because of the electrical resistance of rails against the flow of traction currents and also rail to ground conductivity (despite rail-to-ground insulations), parts of the return current that flow from trains to traction substations leak to the ground. These leaking currents are called stray currents (as shown in Fig. 1). Stray currents can enter their neighboring metallic infrastructures and, as a result of

The amount of electrochemical mass reduction as a result of anodic interaction due to flow

2

*t*

()()

1

in which *C* is the electrochemical coefficient and is based on the type of the metal, electrolyte, and chemical calculations. For example, *C* is 9.11 KgA-1Year-1 for iron. It means that a current of 1 ampere can oxidize 9.11 kilograms of iron per year. This can reduce the safety and the life time of structures and infrastructures in tunnels. The corrosions caused by stray currents yield a total loss of \$500 million each year to the American railway system [1]. When a train is running, especially during its accelerating time, the traction supply current can sometimes reach 6000 amperes. Since the resistance of rails is between 15 to 20 mΩKm-1, the return current can face a voltage drop of up to 120 VKm-1. This voltage, due to inadequate insulations of rails and their underlying structures, allows the current to leak to the ground. Stray current control is usually done via improvements performed to transportation systems or the neighboring ground structures. Increasing the resistance between rail and ground is a very effective method in reducing stray currents. The increase in resistance reduces the tendency of return current to flow in any path other than the rails. Other methods for avoiding corrosions include cathodic protection, rail insulation, traction voltage increase, employment of proper rails that have very low electrical resistance and

*t*

anodic interactions, cause electrochemical corrosions in their leakage path.

usage of proper grounding systems in traction substations.

of current *i(t)* from a metal to an electrolytic environment can be gained as below

**1. Introduction** 

Mohammad Ali Sandidzadeh and Amin Shafipour

*<sup>M</sup> C itdt* (1)


## **Controlling and Simulation of Stray Currents in DC Railway by Considering the Effects of Collection Mats**

Mohammad Ali Sandidzadeh and Amin Shafipour *School of Railway Engineering, Iran University of Science and Technology, Tehran, Iran* 

### **1. Introduction**

22 Will-be-set-by-IN-TECH

224 Infrastructure Design, Signalling and Security in Railway

Schlune, H., Plos, M. & Gylltoft, K. (2009). Improved bridge evaluation through finite element

Wiberg, J. (2006). *Bridge Monitoring to Allow for Reliable Dynamic FE Modelling. A Case Study of the New Årsta Railway Bridge*, Lic thesis, Royal Institute of Technology, Sweden. Wiberg, J. (2007). Railway bridge dynamic characteristics from output only signal analysis,

Wiberg, J. (2009). An equivalent modulus of elasticity approach for simplified modelling and

Wiberg, J. & Karoumi, R. (2009). Monitoring dynamic behaviour of a long-span railway bridge,

Wiberg, J., Karoumi, R. & Pacoste, C. (2009). Statistical screening of individual and joint effect

Willis (1850). Deflexion of railway bridges under the passage of heavy bodies, *Journal of the*

Zárate, B. A. & Caicedo, J. M. (2008). Finite element model updating: Multiple alternatives,

SOLVIA® Finite Element System (2007). Users Manual Version 03. The MathWorks, Inc. (2009). *Signal Processing Toolbox*TM *6 User's Guide*.

*Structure and Infrastructure Engineering* 5(5): 419–433.

*Control and Health Monitoring* . Submitted.

*Engineering Structures* 30(12): 3724–3730.

31(7): 1477–1485.

Submitted.

*(EVACES'07)*, Porto, Portugal.

*Franklin Institute* 49(1): 7–8.

model updating using static and dynamic measurements, *Engineering Structures*

*Proc., Int. Conf. on Experimental Vibration Analysis for Civil Engineering Structures*

analysis of a complex prestressed railway bridge, *Advances in Structural Engineering* .

of several modeling factors on the dynamic fe response of a railway bridge, *Structural*

Urban rail transit systems are mostly electrically DC type. Usually in these systems for reducing the costs, running rails are used as the return current paths. Because of the electrical resistance of rails against the flow of traction currents and also rail to ground conductivity (despite rail-to-ground insulations), parts of the return current that flow from trains to traction substations leak to the ground. These leaking currents are called stray currents (as shown in Fig. 1). Stray currents can enter their neighboring metallic infrastructures and, as a result of anodic interactions, cause electrochemical corrosions in their leakage path.

The amount of electrochemical mass reduction as a result of anodic interaction due to flow of current *i(t)* from a metal to an electrolytic environment can be gained as below

$$M = \mathbb{C} \bigcap\_{t1}^{t2} i(t)d(t) \tag{l}$$

in which *C* is the electrochemical coefficient and is based on the type of the metal, electrolyte, and chemical calculations. For example, *C* is 9.11 KgA-1Year-1 for iron. It means that a current of 1 ampere can oxidize 9.11 kilograms of iron per year. This can reduce the safety and the life time of structures and infrastructures in tunnels. The corrosions caused by stray currents yield a total loss of \$500 million each year to the American railway system [1]. When a train is running, especially during its accelerating time, the traction supply current can sometimes reach 6000 amperes. Since the resistance of rails is between 15 to 20 mΩKm-1, the return current can face a voltage drop of up to 120 VKm-1. This voltage, due to inadequate insulations of rails and their underlying structures, allows the current to leak to the ground. Stray current control is usually done via improvements performed to transportation systems or the neighboring ground structures. Increasing the resistance between rail and ground is a very effective method in reducing stray currents. The increase in resistance reduces the tendency of return current to flow in any path other than the rails. Other methods for avoiding corrosions include cathodic protection, rail insulation, traction voltage increase, employment of proper rails that have very low electrical resistance and usage of proper grounding systems in traction substations.

Controlling and Simulation of Stray Currents in

investigated.

Fig. 2. Tehran Metro line 4 plan

**2. An introduvtion of Tehran metro line 4** 

Fig. 3. General diagram of Tehran Metro Line 4 power system.

DC Railway by Considering the Effects of Collection Mats 227

4. The simulations are performed for various grounding scenarios of traction substations and the influence of stray current collection mats, under various scenarios, and effective parameters on performance improvement of the collection system, in the simulated line, are discussed. In the end the stray current and touch potential of rails under presence and absence of the stray current collection mats, in the worst scenarios, and movement of four trains from three stations, with the middle station not having a traction substation, are

Tehran metro line 4 is the forth subway line in Tehran with a length of 25 Km and comprises 22 stations. It is stretched from the west to the east part of the city and is equipped with 18 traction substations. The details of the substations are shown in tables 1 and 2. The total trip time in line 4 is 42 minutes, which includes 25 seconds of dwell time in each station. At the most crowded hours, the train headways reach 2 minute cycles. Fig. 2 shows the line 4 plan. Each traction substation is supplied with two rectifier transformers that have nominal powers of 2.5 or 3.3 MW. The required power is supplied directly by 63 KV power grid of Tehran Regional Electric Co. in B4, H4 and R4 substations, and is then stepped down to 20 kV via 3×2 (63 to 20kV) transformers (Fig. 3). After that, it is distributed in LPSs (Lighting and Power Substations) and RSs (Rectifier Substations) by means of separate 20 kV rings.

For a 750V power supply, under full load and setting of 6%, the substation output voltage has a voltage drop of 45V. Since the train requires high power amounts during its acceleration, the RS should be able to supply the extra required load. Based on class VI in

Fig. 1. Exposure of Stray Current in DC Railway Systems.

Despite application of the mentioned methods for controlling stray currents, some portion of the traction current would still flow through the ground instead of the rails to reach the negative terminal of the substation. In this paper, by discussing the ways for using stray current collection mat and grounding system via simulations, the effects of collector cables and stray current collection mats below the rails are described.

Many papers, published between 1995 and 2005, discussed and examined various grounding systems in railway transportation. In addition, general techniques for reducing voltage and stray current levels were discussed in these papers. "Paul" specifically examined grounding in power grid systems of subways [2]. "Goodman", for the first time, calculated the rail voltage and stray current profiles. His calculations were not computer aided and instead based on simple hypothesis [3]. Later, "Case" used Π model to investigate a diode grounding system and compared it with EN50122-2 standard [4]. "Lee" used the floating models instead of "Case"'s proposed Π model [5, 6]. Although Lee's model benefited from high accuracy, it showed no significant different results. In the mentioned papers, the effects of grounding systems on voltage and stray current profiles were investigated. Despite mentioning corrosion in the previous papers, it was "Cotton" who, for the first time, discussed the influence of soil structures and stray current collection mats on corrosion performance of metallic infrastructures. The outcome of his survey was software that analyzed and studied influences of soil and current collection mats on corrosion of metallic infrastructures [7].

"Cotton" discussed the importance of stray current reduction in DC rail transit systems and proposed usage of stray current collection mats. Also, he talked about the influences of his proposed system's performance and resistivity of soil on stray currents and the resulting corrosions [8].

"Lee" used the floating model to simulate and investigate stray currents and their effects on underground structures. He used a coefficient of 0.1V voltage increase of these structures as a high stray current leakage in these systems. In the end, he proposed some methods for reducing stray currents by improving railway systems and the neighboring structures [9].

In this research, after a brief introduction of Tehran Metro line 4, the present methods used for simulation and analysis of stray currents are investigated and later stray current and touch potentials are studied by simulating the current path between two substations of line

Despite application of the mentioned methods for controlling stray currents, some portion of the traction current would still flow through the ground instead of the rails to reach the negative terminal of the substation. In this paper, by discussing the ways for using stray current collection mat and grounding system via simulations, the effects of collector cables

Many papers, published between 1995 and 2005, discussed and examined various grounding systems in railway transportation. In addition, general techniques for reducing voltage and stray current levels were discussed in these papers. "Paul" specifically examined grounding in power grid systems of subways [2]. "Goodman", for the first time, calculated the rail voltage and stray current profiles. His calculations were not computer aided and instead based on simple hypothesis [3]. Later, "Case" used Π model to investigate a diode grounding system and compared it with EN50122-2 standard [4]. "Lee" used the floating models instead of "Case"'s proposed Π model [5, 6]. Although Lee's model benefited from high accuracy, it showed no significant different results. In the mentioned papers, the effects of grounding systems on voltage and stray current profiles were investigated. Despite mentioning corrosion in the previous papers, it was "Cotton" who, for the first time, discussed the influence of soil structures and stray current collection mats on corrosion performance of metallic infrastructures. The outcome of his survey was software that analyzed and studied influences of soil and current collection mats on corrosion of metallic

"Cotton" discussed the importance of stray current reduction in DC rail transit systems and proposed usage of stray current collection mats. Also, he talked about the influences of his proposed system's performance and resistivity of soil on stray currents and the resulting

"Lee" used the floating model to simulate and investigate stray currents and their effects on underground structures. He used a coefficient of 0.1V voltage increase of these structures as a high stray current leakage in these systems. In the end, he proposed some methods for reducing stray currents by improving railway systems and the neighboring structures [9]. In this research, after a brief introduction of Tehran Metro line 4, the present methods used for simulation and analysis of stray currents are investigated and later stray current and touch potentials are studied by simulating the current path between two substations of line

Fig. 1. Exposure of Stray Current in DC Railway Systems.

and stray current collection mats below the rails are described.

infrastructures [7].

corrosions [8].

4. The simulations are performed for various grounding scenarios of traction substations and the influence of stray current collection mats, under various scenarios, and effective parameters on performance improvement of the collection system, in the simulated line, are discussed. In the end the stray current and touch potential of rails under presence and absence of the stray current collection mats, in the worst scenarios, and movement of four trains from three stations, with the middle station not having a traction substation, are investigated.

Fig. 2. Tehran Metro line 4 plan

### **2. An introduvtion of Tehran metro line 4**

Tehran metro line 4 is the forth subway line in Tehran with a length of 25 Km and comprises 22 stations. It is stretched from the west to the east part of the city and is equipped with 18 traction substations. The details of the substations are shown in tables 1 and 2. The total trip time in line 4 is 42 minutes, which includes 25 seconds of dwell time in each station. At the most crowded hours, the train headways reach 2 minute cycles. Fig. 2 shows the line 4 plan.

Each traction substation is supplied with two rectifier transformers that have nominal powers of 2.5 or 3.3 MW. The required power is supplied directly by 63 KV power grid of Tehran Regional Electric Co. in B4, H4 and R4 substations, and is then stepped down to 20 kV via 3×2 (63 to 20kV) transformers (Fig. 3). After that, it is distributed in LPSs (Lighting and Power Substations) and RSs (Rectifier Substations) by means of separate 20 kV rings.

Fig. 3. General diagram of Tehran Metro Line 4 power system.

For a 750V power supply, under full load and setting of 6%, the substation output voltage has a voltage drop of 45V. Since the train requires high power amounts during its acceleration, the RS should be able to supply the extra required load. Based on class VI in

Controlling and Simulation of Stray Currents in

1 A4-6 RS

Table 2. Characteristics of line 4 substations and their capacities

in which *i(x)* is the rail current, *v(x)* is the rail voltage,

**3. Stray current modeling** 

should be altered.

**Name Item** 

DC Railway by Considering the Effects of Collection Mats 229

2 A4-5 RS 2×3300 3 A4-4 RS 2×2500 4 A4-3 RS 2×3300 5 A4-2 RS 2×2500 6 A4 RS 2×2500 7 B4 RS 2×2500 8 C4 RIC - 9 D4-H2 RS 2×2500 10 E4 RS 2×2500 11 F4 RS 2×2500 12 I3G'4 RS 2×2500 13 I4 RS 2×3300 14 K1J4 RIC - 15 P2K4 RS 2×3300 16 M4 RS 2×3300 17 N4 RIC - 18 O4 RS 2×3300 19 P4 RIC - 20 Q4 RS 2×3300 21 R4 RS 2×2500 22 S4 RS 2×3300

For simulation of a DC traction network and analysis of stray currents, two different methods can be used. The first method is based on the floating model and distributed elements [5, 6]. In this method, distributed elements like rail conductance and resistance per unit length are used for the calculations, and by utilizing the floating equations, the equations for stray current and touch voltages of rails are determined. Equations (2) and (3)

> 1 2 *ix c x c x* ( ) exp( ) exp( )

0 1 <sup>2</sup> *vx R c x c x* ( ) ( exp( ) exp( )) 

(= *RG* ), *R*0 is the characteristic resistance of the rail (= *R G*/ ), *c1* and *c2* are the equitation constants and determined based on the boundary values, *R* is the resistance per unit length of the rail and *G* is the leakage conductance between the rail and the ground. Although this method has the ability of determining quantities in each part with high accuracy, it has a low flexibility and therefore for various structures, many of its equations

(2)

(3)

is the propagation constant

show the current and voltage in various parts of the rail, respectively as below: [6]

**Type of Substation Capacity Station** 

compliance with IEC146 standard, the RS should be capable of a constant load supply of 100%, a nominal load supply of 150% for a period of 2 hours and a nominal load supply of 300% for a period of 1 minute. Based on its internal resistance, at 300% overload times, the voltage drop in the RS would be around 135V.

Fig. 4. The order of rolling stock cars

The trains comprise 8 cars and weigh around 274 tons without passengers and 379 tons in normal transit conditions (Fig. 4). The traction power is supplied from 750V voltage source and from the third rail. Each train includes 16×200kW traction motors. The maximum train speed and acceleration is 80 kmh-1 and 0.2 ms-2, respectively. The rolling resistance equation (i.e., the Davis formula) is 1.57+0.00106V2 for the traction mode and 1.97+0.0025V + 0.00106V2 for the breaking mode. Also, the internal auxiliary power consumption of each train is 125 kW.


Table 1. Characteristics of line 4 stations

compliance with IEC146 standard, the RS should be capable of a constant load supply of 100%, a nominal load supply of 150% for a period of 2 hours and a nominal load supply of 300% for a period of 1 minute. Based on its internal resistance, at 300% overload times, the

The trains comprise 8 cars and weigh around 274 tons without passengers and 379 tons in normal transit conditions (Fig. 4). The traction power is supplied from 750V voltage source and from the third rail. Each train includes 16×200kW traction motors. The maximum train speed and acceleration is 80 kmh-1 and 0.2 ms-2, respectively. The rolling resistance equation (i.e., the Davis formula) is 1.57+0.00106V2 for the traction mode and 1.97+0.0025V + 0.00106V2 for the breaking mode. Also, the internal auxiliary power consumption of each

2 A4-5 -3+645 -3+566 -3+487 3 A4-4 -1+611 -1+532 -1+453 4 A4-3 -0+15 0+063 0+142 5 A4-2 1+661 1+740 1+819 6 A4 2+811 2+890 2+969 7 B4 3+971 4+050 4+129 8 C4 4+926 5+005 5+084 9 D4-H2 5+645 5+724 5+803 10 E4 7+064 7+143 7+222 11 F4 8+153 8+232 8+311 12 I3G'4 9+427 9+506 9+585 13 I4 10+716 10+795 10+874 14 K1J4 11+310 11+389 11+468 15 P2K4 12+461 12+540 12+619 16 M4 13+773 13+852 13+931 17 N4 14+537 14+616 14+695 18 O4 15+593 15+671 15+750 19 P4 16+489 16+568 16+647 20 Q4 17+443 17+522 17+601 21 R4 18+793 18+872 18+951 22 S4 20+661 20+740 20+819

**Begin Center End** 

**Item Station Name Station Characteristics** 

voltage drop in the RS would be around 135V.

Fig. 4. The order of rolling stock cars

1 A4-6

Table 1. Characteristics of line 4 stations

train is 125 kW.


Table 2. Characteristics of line 4 substations and their capacities

### **3. Stray current modeling**

For simulation of a DC traction network and analysis of stray currents, two different methods can be used. The first method is based on the floating model and distributed elements [5, 6]. In this method, distributed elements like rail conductance and resistance per unit length are used for the calculations, and by utilizing the floating equations, the equations for stray current and touch voltages of rails are determined. Equations (2) and (3) show the current and voltage in various parts of the rail, respectively as below: [6]

$$i(\mathbf{x}) = c\_1 \exp(\gamma \mathbf{x}) + c\_2 \exp(-\gamma \mathbf{x}) \tag{2}$$

$$w(\mathbf{x}) = -R\_0(c\_1 \exp(\gamma \mathbf{x}) + c\_2 \exp(-\gamma \mathbf{x})) \tag{3}$$

in which *i(x)* is the rail current, *v(x)* is the rail voltage, is the propagation constant (= *RG* ), *R*0 is the characteristic resistance of the rail (= *R G*/ ), *c1* and *c2* are the equitation constants and determined based on the boundary values, *R* is the resistance per unit length of the rail and *G* is the leakage conductance between the rail and the ground. Although this method has the ability of determining quantities in each part with high accuracy, it has a low flexibility and therefore for various structures, many of its equations should be altered.

Controlling and Simulation of Stray Currents in

performance.

DC Railway by Considering the Effects of Collection Mats 231

Although this method is not as accurate as the first one, selection of 100-meter sections creates the acceptable preciseness required for analysis of stray currents. Besides, this method allows simulating and modeling different structures with minimal changes in them. Since all the equations in this method are linear, the simulations have an acceptable

Fig. 6. Flowchart for determining the touch potential and stray current in the discrete model

The second method is based on using concentrated elements or Π line model in the DC mode. In this method, the line is divided into sections with equal lengths and each section is modeled with a rail to ground resistance and conductance (Fig. 5). In most applications, selecting the length of each section as 100 meter creates a good accuracy for stray current determination. Each substation is modeled via its Thevenin equivalent (i.e., a voltage source and an equivalent resistance) or Norton equivalent circuit. The train is also modeled via a time-varying current source. Finally, based on proposed model and node analysis rules, rail surface potential and the current amount profiles are resolved. The linear equation for node analysis is as below: [4]

$$
\overline{Y}\_n \cdot \overline{e} = \overline{i}\_s \tag{4}
$$

in which *Yn* is the node admittance matrix, *e* is the node voltage matrix and *<sup>s</sup> i* is the node current sources matrix. In the node admittance matrix, *ii y* entry is the sum of all conductances tied to the *i*th node and *ij y* is the negative of the sum of all conductances between the *i*th and the *j*th nodes. Also, *si i* is the sum of all currents entering the *i*th node. The currents entering the positive and exiting the negative nodes are also considered here. The node voltage matrix is the unknown matrix that is determined by solving the above equation. This matrix actually represents the amount of rail surface voltage.

Fig. 5. Simplest form of discrete Norton line model for two stations and rail

Because of the existence of resistance network, the admittance matrix is symmetrical and has a positive determinant. The voltage of the station rectifier can be determined from the DC load distribution of the traction network. The current amount in the *IT* current model, which is the train model, can be determined from the train's current – velocity equations.

Fig. 6 shows the calculation steps based on this model in a DC railway network. According to the presented flowchart, at first, based on the train time schedule, the locations of various trains are determined and then each substation voltage is gained by distributing the load through the system. Also, the traction current of each train is determined according to the velocity of that specific train. Finally, by solving the node equations, the touch voltage and stray current for each node are calculated. [10]

The second method is based on using concentrated elements or Π line model in the DC mode. In this method, the line is divided into sections with equal lengths and each section is modeled with a rail to ground resistance and conductance (Fig. 5). In most applications, selecting the length of each section as 100 meter creates a good accuracy for stray current determination. Each substation is modeled via its Thevenin equivalent (i.e., a voltage source and an equivalent resistance) or Norton equivalent circuit. The train is also modeled via a time-varying current source. Finally, based on proposed model and node analysis rules, rail surface potential and the current amount profiles are resolved. The linear equation for node

in which *Yn* is the node admittance matrix, *e* is the node voltage matrix and *<sup>s</sup>*

equation. This matrix actually represents the amount of rail surface voltage.

Fig. 5. Simplest form of discrete Norton line model for two stations and rail

stray current for each node are calculated. [10]

is the train model, can be determined from the train's current – velocity equations.

Because of the existence of resistance network, the admittance matrix is symmetrical and has a positive determinant. The voltage of the station rectifier can be determined from the DC load distribution of the traction network. The current amount in the *IT* current model, which

Fig. 6 shows the calculation steps based on this model in a DC railway network. According to the presented flowchart, at first, based on the train time schedule, the locations of various trains are determined and then each substation voltage is gained by distributing the load through the system. Also, the traction current of each train is determined according to the velocity of that specific train. Finally, by solving the node equations, the touch voltage and

current sources matrix. In the node admittance matrix, *ii y* entry is the sum of all conductances tied to the *i*th node and *ij y* is the negative of the sum of all conductances between the *i*th and the *j*th nodes. Also, *si i* is the sum of all currents entering the *i*th node. The currents entering the positive and exiting the negative nodes are also considered here. The node voltage matrix is the unknown matrix that is determined by solving the above

*Ye i n s* (4)

*i* is the node

analysis is as below: [4]

Although this method is not as accurate as the first one, selection of 100-meter sections creates the acceptable preciseness required for analysis of stray currents. Besides, this method allows simulating and modeling different structures with minimal changes in them. Since all the equations in this method are linear, the simulations have an acceptable performance.

Fig. 6. Flowchart for determining the touch potential and stray current in the discrete model

Controlling and Simulation of Stray Currents in

Fig. 9. The train speed-location curve

Train Current (A)

Fig. 10. Current – location curve of traction motor

Speed (m/s)

return modes

DC Railway by Considering the Effects of Collection Mats 233

Fig. 8. The current-speed relation of train traction motors in the power consumption and

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> <sup>1400</sup> <sup>0</sup>

Location (m)

0 200 400 600 800 1000 1200

Fig. 10 shows the current-speed curve in the line. It shows the total train consumed current for all the 16 traction motors. Since stray current effect on metallic structure in long term, in this analysis transition currents and the current related to train auxiliary power have been ignored. Also, the train regenerative current is lossed on the resistors located on the train.

Location (m)

### **4. Modeling the line and determining the parameters**

For line modeling, Fig. 7 schematic is used, in which *Vdc* is voltage of the DC busbar, *It* is the train model, *Rrr* is the resistance per unit length of the rail, *Rrm* is the rail to mat resistance, *Rmm* is the resistance per unit length of the mat and *Rmg* is the mat to ground resistance. Also, *Rg* is the resistance of the substation ground. The type of grounding can be defined based on the way the negative substation busbar is connected to the ground; if, as shown in Fig. 7, *S1* key is closed, the system is grounded and if this key is open, the system is floating. If a diode is used instead of *S1* key, then the system is diode grounded.

The amount of *It* current varies based on the train velocity and is calculated from the power consumption of traction motors and the Davis formula. Fig. 8 shows the relation between the current and speed of the traction motors.

The parameters used in the simulation are determined from the available line 4 characteristic data, the available standards, references [8], [11] and division of the line into equal 100 meter cells. According to the manufacturers' data, *Rrr* is 1650 µΩ (i.e., with 5% corrosion, the resistance per unit length of the rail is 16.5 µΩm-1.) The rail to soil conductivity, based on the type of foundation, is 10 Ωkm-1 and therefore *Rrm* is assumed to be 100Ω. Assuming the special resistance of steel as 15.9 µΩcm-1, a corrosion coefficient of 5% and a cross sectional area of 1800mm2 for the underground stray current collection mat, the amount of *Rmm* is calculated as 12mΩ. The stray current collector cable with a cross sectional area of 185mm2 is assumed to have a resistance per unit length of 180 µΩm-1. The *Rmg* is assumed to be 1Ω.

Fig. 7. The schematic used for line modeling

Since the grounds in I3G4 and F4 stations have the lowest resistance values, the line between the two stations, which is 1274 meters long, is selected for the simulation. Fig. 9 shows the time-speed relation for this line.

As shown here, the train starts its movement with acceleration of 0.75 ms-2 and after 330 meters reaches a speed of 80kmh-1. Then the supply from the power source is cut and the train runs the rest of the line as the result of its inertia, and its speed starts to decrease. After 1150 meters the dynamic brakes are engaged and the train begins to stop.

For line modeling, Fig. 7 schematic is used, in which *Vdc* is voltage of the DC busbar, *It* is the train model, *Rrr* is the resistance per unit length of the rail, *Rrm* is the rail to mat resistance, *Rmm* is the resistance per unit length of the mat and *Rmg* is the mat to ground resistance. Also, *Rg* is the resistance of the substation ground. The type of grounding can be defined based on the way the negative substation busbar is connected to the ground; if, as shown in Fig. 7, *S1* key is closed, the system is grounded and if this key is open, the system is floating. If a

The amount of *It* current varies based on the train velocity and is calculated from the power consumption of traction motors and the Davis formula. Fig. 8 shows the relation between

The parameters used in the simulation are determined from the available line 4 characteristic data, the available standards, references [8], [11] and division of the line into equal 100 meter cells. According to the manufacturers' data, *Rrr* is 1650 µΩ (i.e., with 5% corrosion, the resistance per unit length of the rail is 16.5 µΩm-1.) The rail to soil conductivity, based on the type of foundation, is 10 Ωkm-1 and therefore *Rrm* is assumed to be 100Ω. Assuming the special resistance of steel as 15.9 µΩcm-1, a corrosion coefficient of 5% and a cross sectional area of 1800mm2 for the underground stray current collection mat, the amount of *Rmm* is calculated as 12mΩ. The stray current collector cable with a cross sectional area of 185mm2 is assumed to have a resistance per unit length of 180 µΩm-1. The

Since the grounds in I3G4 and F4 stations have the lowest resistance values, the line between the two stations, which is 1274 meters long, is selected for the simulation. Fig. 9 shows the

As shown here, the train starts its movement with acceleration of 0.75 ms-2 and after 330 meters reaches a speed of 80kmh-1. Then the supply from the power source is cut and the train runs the rest of the line as the result of its inertia, and its speed starts to decrease. After

1150 meters the dynamic brakes are engaged and the train begins to stop.

**4. Modeling the line and determining the parameters** 

diode is used instead of *S1* key, then the system is diode grounded.

the current and speed of the traction motors.

Fig. 7. The schematic used for line modeling

time-speed relation for this line.

*Rmg* is assumed to be 1Ω.

Fig. 9. The train speed-location curve

Fig. 10. Current – location curve of traction motor

Fig. 10 shows the current-speed curve in the line. It shows the total train consumed current for all the 16 traction motors. Since stray current effect on metallic structure in long term, in this analysis transition currents and the current related to train auxiliary power have been ignored. Also, the train regenerative current is lossed on the resistors located on the train.

Controlling and Simulation of Stray Currents in

meters away from the initial substation


meters away from the initial substation

0

5

Rail Potential (V)

10

15

20

grounded and 0.42 amperes in direct grounded systems.

DC Railway by Considering the Effects of Collection Mats 235

Fig. 12. The rail touch potential for three different grounding systems when the train is 100

It can be concluded from the presented graphs that in all three grounding system, the current is leaking from the rail to the ground in locations where rail to ground voltage is positive, and the amount of current flow depends on the rail voltage with respect to ground. In solidly grounded systems, due to the zero voltage at the substation and the positive rail to ground voltage, stray current leakage is observed in all locations of the line. In diode grounded system less stray current leakage is observed, since the rail voltage is negative at the substation. The reason for this is that diodes turn on only when the voltage of their cathode is -0.8v less than their anode voltage. In ungrounded system, the stray currents case is much improved. In the first half of the line, from the train to the substation, stray currents leak and flow from the rail to the ground (since the rail to ground voltage is positive,) and in the second half of the line, the leaked stray current flow back to the rail. The cumulative stray current in the floating system is 0.136 amperes, while it is 0.33 amperes in the diode

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> -10

Fig. 13. The rail touch potential in three different grounding systems when the train is 300

Location (m)

Float Diod Grounded Grounded

### **5. Simulation results and analysis**

For analyzing level of the stray current for Tehran Metro line 4, the simulations are performed under various scenarios. In the first scenario, while no collection system is utilized, effect of grounding systems on current leakage from rail is studied; then in the second scenario while the reinforcement grid exit in the second stage of concrete under rail, effect of electrical continuity of this grid on controlling and collecting stray current is investigated. In the next scenario, stray current collector cable is added to collection mat and in the last part, previous scenarios are considered on the passenger stations (without traction substations).

### **5.1. Effect of grounding systems**

This part is when no stray current collection system is utilized and train is assumed to be running and 2 below cases are studied:

At first, while the train is in a specific location, the stray current and rail potential is observed along the whole line (case I) later, the stray current is studied for a specific location, while the train moves along the whole line (case 2) finally, the effects of the collection mats and then the collector cable, in addition to the mats, are investigated.

### **5.1.1 Case Ι**

The first mode is when the train is at a location 100m from the start substation and is accelerating, while a current of 4400 amperes is fed to the train via the third rail. Such that, a current of 4060 amperes is fed to the train from the nearest substation. Fig. 11 shows the leakage current from rail and fig.12 shows potential of running rail along the way for three different grounding systems.

Fig. 11. Leakage current from rail for three different grounding system when the train is 100 meters away from the initial substation

For analyzing level of the stray current for Tehran Metro line 4, the simulations are performed under various scenarios. In the first scenario, while no collection system is utilized, effect of grounding systems on current leakage from rail is studied; then in the second scenario while the reinforcement grid exit in the second stage of concrete under rail, effect of electrical continuity of this grid on controlling and collecting stray current is investigated. In the next scenario, stray current collector cable is added to collection mat and in the last part, previous scenarios are considered on the passenger stations (without

This part is when no stray current collection system is utilized and train is assumed to be

At first, while the train is in a specific location, the stray current and rail potential is observed along the whole line (case I) later, the stray current is studied for a specific location, while the train moves along the whole line (case 2) finally, the effects of the

The first mode is when the train is at a location 100m from the start substation and is accelerating, while a current of 4400 amperes is fed to the train via the third rail. Such that, a current of 4060 amperes is fed to the train from the nearest substation. Fig. 11 shows the leakage current from rail and fig.12 shows potential of running rail along the way for three

> Float Diode Grounded Grounded

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> -0.04

Fig. 11. Leakage current from rail for three different grounding system when the train is 100

Location (m)

collection mats and then the collector cable, in addition to the mats, are investigated.

**5. Simulation results and analysis** 

traction substations).

**5.1.1 Case Ι**

**5.1. Effect of grounding systems** 

different grounding systems.


meters away from the initial substation

0

0.02

Local Stray Current (A)

0.04

0.06

0.08

running and 2 below cases are studied:

Fig. 12. The rail touch potential for three different grounding systems when the train is 100 meters away from the initial substation

It can be concluded from the presented graphs that in all three grounding system, the current is leaking from the rail to the ground in locations where rail to ground voltage is positive, and the amount of current flow depends on the rail voltage with respect to ground. In solidly grounded systems, due to the zero voltage at the substation and the positive rail to ground voltage, stray current leakage is observed in all locations of the line. In diode grounded system less stray current leakage is observed, since the rail voltage is negative at the substation. The reason for this is that diodes turn on only when the voltage of their cathode is -0.8v less than their anode voltage. In ungrounded system, the stray currents case is much improved. In the first half of the line, from the train to the substation, stray currents leak and flow from the rail to the ground (since the rail to ground voltage is positive,) and in the second half of the line, the leaked stray current flow back to the rail. The cumulative stray current in the floating system is 0.136 amperes, while it is 0.33 amperes in the diode grounded and 0.42 amperes in direct grounded systems.

Fig. 13. The rail touch potential in three different grounding systems when the train is 300 meters away from the initial substation

Controlling and Simulation of Stray Currents in


> 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07

0 0.01 0.02 0.03 0.04 0.05 0.06

Solidly grounded system c) Diode grounded system

current exists.

Local Stray Current (A)

Local Stray Current (A)

Local Stray Current (A)

DC Railway by Considering the Effects of Collection Mats 237

0 200 400 600 800 1000 1200

(a)

0 200 400 600 800 1000 1200

(b)

0 200 400 600 800 1000 1200

(c)

Fig. 16 shows the stray current at location 300 m in the line. Like the previous instances, the stray current is at its peak when the train is also at this location. At location 300m, due to sufficient distance from the substation, unlike location 100 m, always in all grounding system, when there is current flow, the touch potential is positive and stray

Fig. 15. Stray current at location 100 m on the rail in case ΙΙ for a) The floating system b)

Location (m)

Location (m)

Location (m)

When the train is 300 meters away from the initial substation, its current amount reaches a maximum of 4960 amperes. From this current, 3814 amperes are supplied by the first and 1146 amperes are supplied by the second substation. Because of the increase in traction current in this case, the stray current and touch potential are also amplified for the three grounding systems (Fig. 13 -14). As it is shown, touch potential in grounded system in nearly zero in substations and it's positive in other locations. Also it's approximately twice that of the floating system in train location. In this case, the amount of rails stray current increases to 1.1 amperes in the grounded system, 1.0 amperes in the diode grounded system and 0.3 amperes in the floating system.

Fig. 14. Leakage current from rail for the three different grounding systems when the train is 300 meters away from the initial station

#### **5.1.2 Case ΙΙ**

At first the investigation is done for a location that is 100m away from the initial first substation. Fig. 15 presents the resulting stray current for the grounding systems. As shown, the floating system has the lowest amount of stray current among all the existing grounding systems, and when the train is more than 200 meters away from the initial substation, current return from the ground to the rail is also observed. In the grounded system of Fig. 15, at all points of the rail, current leakage, which is more than the other systems, is observed. The highest amount of stray current is observed when the train is near the 100 meter point.

In solidly and diode grounded systems, in which the rail voltage about the substation is zero, even after the train has passed location 100m, the rail voltage near the substation remains positive and the current leakage continues, although at lower magnitudes. The traction current, however, increases up to location 330 m. In the floating system when the train passed location 200m, the rail voltage at location 100m point become zero and the flow of stray current stops. However, further train running makes the voltage of this location negative and therefore the stray current flows back to the rail.

When the train is 300 meters away from the initial substation, its current amount reaches a maximum of 4960 amperes. From this current, 3814 amperes are supplied by the first and 1146 amperes are supplied by the second substation. Because of the increase in traction current in this case, the stray current and touch potential are also amplified for the three grounding systems (Fig. 13 -14). As it is shown, touch potential in grounded system in nearly zero in substations and it's positive in other locations. Also it's approximately twice that of the floating system in train location. In this case, the amount of rails stray current increases to 1.1 amperes in the grounded system, 1.0 amperes in the diode grounded system

> Float Diod Grounded Grounded

0 200 400 600 800 1000 1200

Fig. 14. Leakage current from rail for the three different grounding systems when the train is

At first the investigation is done for a location that is 100m away from the initial first substation. Fig. 15 presents the resulting stray current for the grounding systems. As shown, the floating system has the lowest amount of stray current among all the existing grounding systems, and when the train is more than 200 meters away from the initial substation, current return from the ground to the rail is also observed. In the grounded system of Fig. 15, at all points of the rail, current leakage, which is more than the other systems, is observed. The highest amount of stray current is observed when the train is near the 100

In solidly and diode grounded systems, in which the rail voltage about the substation is zero, even after the train has passed location 100m, the rail voltage near the substation remains positive and the current leakage continues, although at lower magnitudes. The traction current, however, increases up to location 330 m. In the floating system when the train passed location 200m, the rail voltage at location 100m point become zero and the flow of stray current stops. However, further train running makes the voltage of this location

negative and therefore the stray current flows back to the rail.

Location (m)

and 0.3 amperes in the floating system.


300 meters away from the initial station

**5.1.2 Case ΙΙ**

meter point.


0

0.05

Local Stray Current (A)

0.1

0.15

0.2

Fig. 15. Stray current at location 100 m on the rail in case ΙΙ for a) The floating system b) Solidly grounded system c) Diode grounded system

Fig. 16 shows the stray current at location 300 m in the line. Like the previous instances, the stray current is at its peak when the train is also at this location. At location 300m, due to sufficient distance from the substation, unlike location 100 m, always in all grounding system, when there is current flow, the touch potential is positive and stray current exists.

Controlling and Simulation of Stray Currents in


0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07

Solidly grounded c) Diode grounded system

**5.2 Using stray current collection mat** 

Local Stray Current (A)

Local Stray Current (A)

Local Stray Current (A)

DC Railway by Considering the Effects of Collection Mats 239

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> -0.035

(a)

0 200 400 600 800 1000 1200

(b)

0 200 400 600 800 1000 1200

(c) Fig. 17. Stray current at location 1000 m when the train is running for a) Floating system b)

The simulations in this section are performed assuming the presence of a reinforcement bars. If the metal bars in the concrete under the rail intersect with each other, they collect main portions of stray currents due to creating a low resistance path for conducting these currents from rail to traction substation. So this collection mat result increasing leakage current from rail because of making return path to traction substation. Some portions of

Location (m)

Location (m)

Location (m)

Fig. 16. The stray current at position 300 m, on the rail in case ΙΙ for A) Floating system b) solidly grounded system c) Diode grounded system

Fig.17 shows the stray current at location 1000 m from the initial substation. The voltage at this location is just similar to the voltage at location 100 m, however the stray current is lower and the current amount that returns from the rail to this point is higher. In the floating system, since this location is closer to the first substation, its voltage remains negative and the current keeps flowing back to the rail.

0 200 400 600 800 1000 1200

(a)

0 200 400 600 800 1000 1200

(b)

0 200 400 600 800 1000 1200

(c ) Fig. 16. The stray current at position 300 m, on the rail in case ΙΙ for A) Floating system b)

Fig.17 shows the stray current at location 1000 m from the initial substation. The voltage at this location is just similar to the voltage at location 100 m, however the stray current is lower and the current amount that returns from the rail to this point is higher. In the floating system, since this location is closer to the first substation, its voltage remains negative and

Location (m)

Location (m)

Location (m)

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18

> 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18

solidly grounded system c) Diode grounded system

the current keeps flowing back to the rail.

Local Stray Current (A)

Local Stray Current (A)

Local Stray Current (A)

Fig. 17. Stray current at location 1000 m when the train is running for a) Floating system b) Solidly grounded c) Diode grounded system

### **5.2 Using stray current collection mat**

The simulations in this section are performed assuming the presence of a reinforcement bars. If the metal bars in the concrete under the rail intersect with each other, they collect main portions of stray currents due to creating a low resistance path for conducting these currents from rail to traction substation. So this collection mat result increasing leakage current from rail because of making return path to traction substation. Some portions of

Controlling and Simulation of Stray Currents in

and making the current flow one directional (Fig. 19).

DC Railway by Considering the Effects of Collection Mats 241

In the first part, this metallic structure is consumed disconnected and there is no direct

In this case, in the floating system, stray current leak from the rail when the train is at location 100m from the first substation is 1.37 amperes, of which 0.06 amperes flows through the concrete's metallic structure and causes severe damages to this structure. When the train is at location 300m, the stray current becomes 0.3 amperes, of which 0.145 amperes flows through the collection mat. Also about 50% of stray current from rail doesn't enter to this mat. To overcome this flaw, in addition to interconnecting all parts of the mat to each other, a path for connecting the collection mat to the negative busbar of the substation should be provided. This connection is done by means of a diode that helps having cathodic protection

return path to substation for current that enters which results are shown is fig. 18.

Fig. 19. Using the concrete metallic structure as the stray current collection mat

Fig. 20 shows the stray current from rail when the train is at locations 100m and 300m from the first substation and the stray current collection mat is used. Because of the mat to ground resistance and connection of the mat to the negative busbar by the diode, the situation here is like that of the diode grounded system. In this case, although the substation ground is considered floating, the substation voltage remains around zero (which is the diode on voltage) and the rail touch potential at the train's location becomes more than the floating system's voltage and, as a result, the stray current increases. Fig.21 shows the current which captured by the collection mat and as shown this amount has increased compared to previous part. However, as shown in Fig. 22, a large portion of the stray current is collected by the collection mat and only a small portion of it leaks to the ground. In this case, the total rail output current at locations 100m and 300m are 0.33 and 1.01 amperes, respectively, of which 0.065 and 0.099 amperes leak to the ground, respectively, and the rest is collected by the mats. Using equation (5) for evaluating the efficiency of the stray current collection system, the system performance becomes 81% at position 100m and 90% at position 300m.

stray currents leak from the rail to metal bars of the reinforced concrete and continue to flow through the underlying concrete structure. If this current is not returned to the substation through a specific current path, the current leak from the concrete structure to the ground would create corrosions in the metal bars of the concrete. In fact for executing reasons, the mats are installed in sections with length of 100 m such that there is a gap of nearly 100 mm between sections. If there is no electrical connections (by wire or cable) between separate sections of mat, entering current to this structure cause severe damages to them.

Fig. 18. Stray current when the train is at locations 100 m and 300 m from the initial station and the metallic concrete structure is unprotected a) Stray current leak from the rail b) Stray current leak to the ground c) Current entering the concrete collection mat

stray currents leak from the rail to metal bars of the reinforced concrete and continue to flow through the underlying concrete structure. If this current is not returned to the substation through a specific current path, the current leak from the concrete structure to the ground would create corrosions in the metal bars of the concrete. In fact for executing reasons, the mats are installed in sections with length of 100 m such that there is a gap of nearly 100 mm between sections. If there is no electrical connections (by wire or cable) between separate

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> -0.1

(a)

0 200 400 600 800 1000 1200

(b)

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> -0.08

(c) Fig. 18. Stray current when the train is at locations 100 m and 300 m from the initial station and the metallic concrete structure is unprotected a) Stray current leak from the rail b) Stray

current leak to the ground c) Current entering the concrete collection mat

Location (m)

Location (m)

Location (m)

100 m 300 m

100 m 300 m

100 m 300 m

sections of mat, entering current to this structure cause severe damages to them.




Mesh Current (A)

0

Secondary Stray Current (A)

0.05

Primary Stray Current (A)

In the first part, this metallic structure is consumed disconnected and there is no direct return path to substation for current that enters which results are shown is fig. 18.

In this case, in the floating system, stray current leak from the rail when the train is at location 100m from the first substation is 1.37 amperes, of which 0.06 amperes flows through the concrete's metallic structure and causes severe damages to this structure. When the train is at location 300m, the stray current becomes 0.3 amperes, of which 0.145 amperes flows through the collection mat. Also about 50% of stray current from rail doesn't enter to this mat. To overcome this flaw, in addition to interconnecting all parts of the mat to each other, a path for connecting the collection mat to the negative busbar of the substation should be provided. This connection is done by means of a diode that helps having cathodic protection and making the current flow one directional (Fig. 19).

Fig. 19. Using the concrete metallic structure as the stray current collection mat

Fig. 20 shows the stray current from rail when the train is at locations 100m and 300m from the first substation and the stray current collection mat is used. Because of the mat to ground resistance and connection of the mat to the negative busbar by the diode, the situation here is like that of the diode grounded system. In this case, although the substation ground is considered floating, the substation voltage remains around zero (which is the diode on voltage) and the rail touch potential at the train's location becomes more than the floating system's voltage and, as a result, the stray current increases. Fig.21 shows the current which captured by the collection mat and as shown this amount has increased compared to previous part. However, as shown in Fig. 22, a large portion of the stray current is collected by the collection mat and only a small portion of it leaks to the ground. In this case, the total rail output current at locations 100m and 300m are 0.33 and 1.01 amperes, respectively, of which 0.065 and 0.099 amperes leak to the ground, respectively, and the rest is collected by the mats. Using equation (5) for evaluating the efficiency of the stray current collection system, the system performance becomes 81% at position 100m and 90% at position 300m.

Controlling and Simulation of Stray Currents in



85

area of the mat at location 300 m (the worst scenario)

90

Efficiency of the Collection system (%)

95

the first substation and collection mat is used



Local Stray Current (A)

0

0.02

0.04

Mesh Current (A)

DC Railway by Considering the Effects of Collection Mats 243

100 m 300 m

> 100 m 300 m

0 200 400 600 800 1000 1200

Fig. 21. The current collected by the mat when the train is at locations 100 m and 300 m from

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> -0.08

Fig. 22. Stray current leakage to ground when the train is at locations 100 m and 300 m from

<sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> <sup>1400</sup> <sup>1600</sup> <sup>1800</sup> <sup>2000</sup> <sup>2200</sup> <sup>2400</sup> <sup>80</sup>

Fig. 23. Efficiency of Stray current collection system based on changes of the cross sectional

Cross-Sectional area of the mesh (mm2

)

Location (m)

the initial substation and stray current collection mat is also used

Location (m)

The equation is

$$
\eta = (I\_{\text{Coefficient}} \; / \; I\_{st}) \times 100 \tag{5}
$$

in which *Collected I* is the amount of stray current collected by the mats and *st I* is the total stray current that has leaked from the rail. As shown in Fig. 22, the highest amount of stray current leakage occurs in the middle point of the line. The reason for this is the long distance of this position from the substations. Although the highest stray current is observed at location 300m, the stray current at location 600m is also high and is 70% of the stray current amount at location 300m. Besides, since location 600m has the highest distance from the line terminating substations, the resistance remains high at this location for stray currents that enter the mats, and this makes this middle position to have the highest rate of stray current leakage to ground in the entire line.

Fig. 20. Rail stray current when the train is at locations 100 m and 300 m and collection mats are used

In Fig. 23, the efficiency of the collection system, based on changes of the cross sectional area of the mat is presented. As mentioned before, the mats used in Tehran Metro line 4 have cross sectional areas of 1800 mm2. The higher the cross sectional area of the mat, the lower its resistance per unit length and the higher its stray current collection amount would be. *Rmm* is 27.4 mΩ for a cross sectional area of 700 mm2 and 8 mΩ for a cross sectional area of 2400mm2. Fig. 23 shows the graph for the time the highest traction current supply, when the train is at position 300 m.

( / ) 100 *Collected st*

in which *Collected I* is the amount of stray current collected by the mats and *st I* is the total stray current that has leaked from the rail. As shown in Fig. 22, the highest amount of stray current leakage occurs in the middle point of the line. The reason for this is the long distance of this position from the substations. Although the highest stray current is observed at location 300m, the stray current at location 600m is also high and is 70% of the stray current amount at location 300m. Besides, since location 600m has the highest distance from the line terminating substations, the resistance remains high at this location for stray currents that enter the mats, and this makes this middle position to have the highest rate of stray current

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> -0.02

Fig. 20. Rail stray current when the train is at locations 100 m and 300 m and collection mats

In Fig. 23, the efficiency of the collection system, based on changes of the cross sectional area of the mat is presented. As mentioned before, the mats used in Tehran Metro line 4 have cross sectional areas of 1800 mm2. The higher the cross sectional area of the mat, the lower its resistance per unit length and the higher its stray current collection amount would be. *Rmm* is 27.4 mΩ for a cross sectional area of 700 mm2 and 8 mΩ for a cross sectional area of 2400mm2. Fig. 23 shows the graph for the time the highest traction current supply, when the

Location (m)

*I I* (5)

100 m 300 m

The equation is

leakage to ground in the entire line.

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18

train is at position 300 m.

Primary Stray Current (A)

are used

Fig. 21. The current collected by the mat when the train is at locations 100 m and 300 m from the initial substation and stray current collection mat is also used

Fig. 22. Stray current leakage to ground when the train is at locations 100 m and 300 m from the first substation and collection mat is used

Fig. 23. Efficiency of Stray current collection system based on changes of the cross sectional area of the mat at location 300 m (the worst scenario)

Controlling and Simulation of Stray Currents in

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2

substation and collector cable is used


> -0.02 -0.015 -0.01 -0.005 0 0.005 0.01 0.015

initial substation and collector cable is used

Secondry Stray Current (A)

away from the initial substation and collector cable is used

Mesh Current (A)

Primary Stray Current (A)

DC Railway by Considering the Effects of Collection Mats 245

100 m 300 m

> 100 m 300 m

100 m 300 m

0 200 400 600 800 1000 1200

0 200 400 600 800 1000 1200

Fig. 26. The current collected by the collection system when the train is 100 m and 300 m

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> -0.025

Fig. 27. Stray current leakage to ground when the train is 100 m and 300 m away from the

Location (m)

Location (m)

Fig. 25. The rail stray current when the train is 100 m and 300 m away from the initial

Location (m)

### **5.3 Using stray current collector cable**

Due to the problems in building a continuous collection mat system, existence of current in the mat system increases the chance for stray current leakage from the mat system itself (especially at connection points). For protecting and retaining high efficiency of the mat system, stray current collector cables are used. Stray current collector cables are installed alongside the rail and they are, at specific locations (e.g., connection points,) connected to the underlying stray current collection mat. In this way these cables provide a low resistance and insulated parallel current path that canalizes and directs the main part of the mat currents to the negative busbar of the substation (Fig. 24).

Fig. 24. Using stray current collection mat and cable

The collector cable not only creates a suitable path for the currents collected by the collection mat, but also avoids current leakage to ground due to its insulation. It directs all the collected currents to the negative substation busbar.

Fig. 25 shows the rail stray current for a line with a collector cable and when the train is at locations 100m and 300m from the initial substation. Since stray current collection mat resistance changes in comparison to resistance between rail and mat are so small, the leakage current from rail is not that much different from the previous scenario (fig.20) in floating system. But in comparison, the current captured by collection mat has increased (fig.26) and the current leakage to the ground has significantly decreased (Fig. 27). When the train is at location 300m, the total rail output current is 1.01 amperes, of which 0.049 amperes leak to the ground. In this case the efficiency of the collector system is 95%. When the train is at location 100m from the initial substation, the total rail current output is 0.33 amperes, of which 0.043 amperes enter the ground. The collector system's efficiency is 87% in this case.

Due to the problems in building a continuous collection mat system, existence of current in the mat system increases the chance for stray current leakage from the mat system itself (especially at connection points). For protecting and retaining high efficiency of the mat system, stray current collector cables are used. Stray current collector cables are installed alongside the rail and they are, at specific locations (e.g., connection points,) connected to the underlying stray current collection mat. In this way these cables provide a low resistance and insulated parallel current path that canalizes and directs the main part of the mat

The collector cable not only creates a suitable path for the currents collected by the collection mat, but also avoids current leakage to ground due to its insulation. It directs all the

Fig. 25 shows the rail stray current for a line with a collector cable and when the train is at locations 100m and 300m from the initial substation. Since stray current collection mat resistance changes in comparison to resistance between rail and mat are so small, the leakage current from rail is not that much different from the previous scenario (fig.20) in floating system. But in comparison, the current captured by collection mat has increased (fig.26) and the current leakage to the ground has significantly decreased (Fig. 27). When the train is at location 300m, the total rail output current is 1.01 amperes, of which 0.049 amperes leak to the ground. In this case the efficiency of the collector system is 95%. When the train is at location 100m from the initial substation, the total rail current output is 0.33 amperes, of which 0.043 amperes enter the ground. The collector system's efficiency is 87%

**5.3 Using stray current collector cable** 

currents to the negative busbar of the substation (Fig. 24).

Fig. 24. Using stray current collection mat and cable

collected currents to the negative substation busbar.

in this case.

Fig. 25. The rail stray current when the train is 100 m and 300 m away from the initial substation and collector cable is used

Fig. 26. The current collected by the collection system when the train is 100 m and 300 m away from the initial substation and collector cable is used

Fig. 27. Stray current leakage to ground when the train is 100 m and 300 m away from the initial substation and collector cable is used

Controlling and Simulation of Stray Currents in

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18

mat and cable are connected at two points.


> -0.02 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18

Mesh Current (A)

Secondary Stray Current (A)

Primary Stray Current (A)

DC Railway by Considering the Effects of Collection Mats 247

The type of collector cable connections to the mats can be also changed. The above simulations were for scenarios where the mats were connected to the cables only at one point (Fig. 24). In Fig. 29, the mats are connected to the collector cables at two points. Figs 30-32 show stray current leakage from the rail, current leakage to the ground and the stray current collected by the collector system. In this case, the rail stray current becomes 1.01 amperes and the total stray

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> -0.02

Fig. 30. The rail stray current when the train is 300 m away from the initial substation and

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> -0.025

Fig. 31. Current leak to the ground when the train is at location 300 m from the first

substation and the cable and mat are connected at two points.

initial substation and the cable and mat are connected at two points.

Location (m)

0 200 400 600 800 1000 1200

Fig. 32. The stray current collected by the mats when the train is at location 300 m from the

Location (m)

Location (m)

current becomes 0.04, which creates an increase in system efficiency to 96.1%.

The reason for the small effect of the collector cable on system efficiency at location 100m is the closeness of this location to the initial substation. At this short distance of the train from the substation where the rails have high current output amounts, the substation voltage cannot decrease enough so as to turn the current collector diode on. As a result, the current leakage to the ground remains high and the collector cable shows no significant effect on system efficiency. Fig. 28 shows the collector system efficiency based on the cross sectional area of the utilized cable, when the cross sectional area of mat is constant. Creation of a low resistance current path and insulation from the ground (via the collector cable) significantly decreases the stray current leakage to the ground. Changes in the cross sectional areas of the cable have effects around 1~2 % on the efficiency of the collector system. Resistances of cables with cross-sectional areas of 90 mm2 and 270 mm2 are 36 mΩ and 12 mΩ, respectively.

Fig. 28. Efficiency of the collector system based on the cross sectional area of the cable

Fig. 29. Using the stray current collection mat and cable with two connection points between the mat and the cable.

The reason for the small effect of the collector cable on system efficiency at location 100m is the closeness of this location to the initial substation. At this short distance of the train from the substation where the rails have high current output amounts, the substation voltage cannot decrease enough so as to turn the current collector diode on. As a result, the current leakage to the ground remains high and the collector cable shows no significant effect on system efficiency. Fig. 28 shows the collector system efficiency based on the cross sectional area of the utilized cable, when the cross sectional area of mat is constant. Creation of a low resistance current path and insulation from the ground (via the collector cable) significantly decreases the stray current leakage to the ground. Changes in the cross sectional areas of the cable have effects around 1~2 % on the efficiency of the collector system. Resistances of cables with cross-sectional areas of 90 mm2 and 270 mm2 are 36 mΩ and 12 mΩ, respectively.

<sup>80</sup> <sup>100</sup> <sup>120</sup> <sup>140</sup> <sup>160</sup> <sup>180</sup> <sup>200</sup> <sup>220</sup> <sup>240</sup> <sup>260</sup> <sup>280</sup> <sup>94</sup>

Cross-Sectional area of the Cable (mm2

Fig. 29. Using the stray current collection mat and cable with two connection points between

Fig. 28. Efficiency of the collector system based on the cross sectional area of the cable

)

94.2 94.4 94.6 94.8 95 95.2 95.4 95.6 95.8 96

the mat and the cable.

Efficiency of the Collection system (%)

The type of collector cable connections to the mats can be also changed. The above simulations were for scenarios where the mats were connected to the cables only at one point (Fig. 24). In Fig. 29, the mats are connected to the collector cables at two points. Figs 30-32 show stray current leakage from the rail, current leakage to the ground and the stray current collected by the collector system. In this case, the rail stray current becomes 1.01 amperes and the total stray current becomes 0.04, which creates an increase in system efficiency to 96.1%.

Fig. 30. The rail stray current when the train is 300 m away from the initial substation and mat and cable are connected at two points.

Fig. 31. Current leak to the ground when the train is at location 300 m from the first substation and the cable and mat are connected at two points.

Fig. 32. The stray current collected by the mats when the train is at location 300 m from the initial substation and the cable and mat are connected at two points.

Controlling and Simulation of Stray Currents in


0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45

Floating system b) Diode grounded system c) Solidly grounded system.

Rail Stray Current (A)

Rail Stray Current (A)

Rail Stray Current (A)

these stations.

DC Railway by Considering the Effects of Collection Mats 249

Fig. 35 shows the rail stray current for the southern and northern lines when no collection mats is used. It is obvious that current leakage in P4 station is more than any other location in the line. These numbers also indicate that the rail potential is high in the neighborhood of

> South Line North Line

South Line North Line

South Line North Line

0 200 400 600 800 1000 1200 1400 1600 1800

(a)

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> <sup>1400</sup> <sup>1600</sup> <sup>1800</sup> -0.05

(b)

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> <sup>1400</sup> <sup>1600</sup> <sup>1800</sup> -0.05

Location (m)

(c) Fig. 35. The rail stray current in the four-train system in the southern and northern lines a)

Location (m)

Location (m)

### **5.4 Simulation results in the case of usage passenger stations without traction substation**

Some stations in line 4 of Tehran Metro are equipped with electrical substations. The traction power in these stations is supplied form substations of the neighboring stations. The train traction current should return to these substations via the running rails. Since the current path, compared to the previous cases, is increased, different stray current amounts and rail potentials are observed in these stations. The shorter headways between trains can result in presence of multiple trains in neighboring stations. The minimum headway in line 4 is planned to be two minutes. In this part of the research, in order to study one of the worst scenarios, the effect of presence of four trains at the following section is investigated. For this purpose, P4 station (which has no substation) and its neighboring O4 and Q4 stations (which have substation) are discussed.

In order to analyze the stray current and rail potential, four trains are assumed to be in the following locations:

Train A, in the southern line of O4 station (travel direction towards P4 station)

Train B, in the southern line of P4 station (travel direction towards Q4 station)

Train C, in the northern line of P4 station (travel direction towards O4 station)

Train D, in the northern line of O4 station (travel direction towards P4 station)

Fig. 33. Trains in the 4 train system between Q4 and O4 stations.

The order of the trains is shown in Fig. 33. It is assumed that all of the trains here start their trips simultaneously and follow the same trip profile. The mentioned parameters are investigated when the trains have traveled 300 m from their initial stations and require the highest amount of traction current. The order of trains, in this case, is shown in Fig. 34.

Fig. 34. Location of trains when they are 300m away from their initial stations.

Some stations in line 4 of Tehran Metro are equipped with electrical substations. The traction power in these stations is supplied form substations of the neighboring stations. The train traction current should return to these substations via the running rails. Since the current path, compared to the previous cases, is increased, different stray current amounts and rail potentials are observed in these stations. The shorter headways between trains can result in presence of multiple trains in neighboring stations. The minimum headway in line 4 is planned to be two minutes. In this part of the research, in order to study one of the worst scenarios, the effect of presence of four trains at the following section is investigated. For this purpose, P4 station (which has no substation) and its neighboring O4 and Q4

In order to analyze the stray current and rail potential, four trains are assumed to be in the

The order of the trains is shown in Fig. 33. It is assumed that all of the trains here start their trips simultaneously and follow the same trip profile. The mentioned parameters are investigated when the trains have traveled 300 m from their initial stations and require the highest amount of traction current. The order of trains, in this case, is shown in Fig. 34.

Fig. 34. Location of trains when they are 300m away from their initial stations.

Train A, in the southern line of O4 station (travel direction towards P4 station) Train B, in the southern line of P4 station (travel direction towards Q4 station) Train C, in the northern line of P4 station (travel direction towards O4 station) Train D, in the northern line of O4 station (travel direction towards P4 station)

Fig. 33. Trains in the 4 train system between Q4 and O4 stations.

**5.4 Simulation results in the case of usage passenger stations without traction** 

**substation** 

following locations:

stations (which have substation) are discussed.

Fig. 35 shows the rail stray current for the southern and northern lines when no collection mats is used. It is obvious that current leakage in P4 station is more than any other location in the line. These numbers also indicate that the rail potential is high in the neighborhood of these stations.

Fig. 35. The rail stray current in the four-train system in the southern and northern lines a) Floating system b) Diode grounded system c) Solidly grounded system.

Controlling and Simulation of Stray Currents in


0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65

metallic structure of the concrete.

lower stray current leakage to the ground.

amperes, which results in system efficiency of 94%.

Mesh Current (A)

Secondary Stray Current (A)

DC Railway by Considering the Effects of Collection Mats 251

0 200 400 600 800 1000 1200 1400 1600 1800

(c)

0 200 400 600 800 1000 1200 1400 1600 1800

(d) Fig. 36. The rail potential and stray current of the two lines when collection mats are used a) Rail potential b) Rail stray current c) Current leakage to the ground d) Current entering the

In this case, the stray current leakage from the southern and northern lines is 5.95 and 5.51 amperes, respectively; however, only a current of 1.14 amperes leaks to the ground. In fact, the efficiency of the collector system is 90%. The system efficiency can be further improved by using a collector cable alongside the underlying collection mat, which results in even

Fig. 37 shows the rail potential and currents in a system that has both the collection mat and the collector cable. In this system, stray current leakage from the southern and northern line is 5.96 and 5.52 amperes, respectively. Also, the current leakage to the ground is 0.71

Location (m)

Location (m)

The total rail stray current in the southern and northern line is 1.6 and 1.26 amperes for the floating system, 5.87 and 5.55 amperes for the diode grounded system, and 6.17 and 5.84 amperes for the solidly grounded system, respectively. These numbers are for the times when all 4 trains are consuming their maximum traction supply current from the network.

Utilizing stray current collection mats under the rails, with the previously mentioned characteristics, would highly minimize the amount of stray current leakage to the ground. Fig. 36 presents the rail voltage, rail stray current, stray current leakage to the ground and the stray current collected by the mats in the current scenario.

The total rail stray current in the southern and northern line is 1.6 and 1.26 amperes for the floating system, 5.87 and 5.55 amperes for the diode grounded system, and 6.17 and 5.84 amperes for the solidly grounded system, respectively. These numbers are for the times when all 4 trains are consuming their maximum traction supply current from the

Utilizing stray current collection mats under the rails, with the previously mentioned characteristics, would highly minimize the amount of stray current leakage to the ground. Fig. 36 presents the rail voltage, rail stray current, stray current leakage to the ground and

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> <sup>1400</sup> <sup>1600</sup> <sup>1800</sup> -5

Location (m)

(a)

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> <sup>1400</sup> <sup>1600</sup> <sup>1800</sup> -0.05

(b)

Location (m)

South Line North Line

South Line North Line

the stray current collected by the mats in the current scenario.

> 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45

Primary Stray Current (A)

Rail Potential (V)

network.

Fig. 36. The rail potential and stray current of the two lines when collection mats are used a) Rail potential b) Rail stray current c) Current leakage to the ground d) Current entering the metallic structure of the concrete.

In this case, the stray current leakage from the southern and northern lines is 5.95 and 5.51 amperes, respectively; however, only a current of 1.14 amperes leaks to the ground. In fact, the efficiency of the collector system is 90%. The system efficiency can be further improved by using a collector cable alongside the underlying collection mat, which results in even lower stray current leakage to the ground.

Fig. 37 shows the rail potential and currents in a system that has both the collection mat and the collector cable. In this system, stray current leakage from the southern and northern line is 5.96 and 5.52 amperes, respectively. Also, the current leakage to the ground is 0.71 amperes, which results in system efficiency of 94%.

Controlling and Simulation of Stray Currents in

**6. Conclusions** 

corrosions would be.

at a specific location.

collection up to 0.94.

EN50122-2 standard [12].

**7. Acknowledgements** 

818–824.

**8. References** 

necessary in stations without traction substations.

DC Railway by Considering the Effects of Collection Mats 253

Based on the performed simulations, it can be concluded that among the existing grounding schemes, the solidly grounded system creates the highest amounts of stray current. Using floating ground systems reduces the stray currents leakage. The systems that create direct rail to ground connections increase the corrosion rates significantly. The higher the connection current and the longer the time, the higher the magnitude of the resulting

The metallic mats of track-beds and foundations increase the stray current leakage to the ground. The stray current travels through the mat and creates metallic corrosion in system terminations. If the mats are used as low resistance paths for absorbing stray currents and directing them to the substations, not only the corrosions of the mats, but also damages to the neighboring structures are avoided. For this purpose, the detached structures are bonded to each other and finally connected to the negative busbar of the substation. Employing stray current collection mats greatly reduces current leakages to ground. Increased cross sectional areas (of cables) and unified connectivity would further improve system efficiency and protection of the mats against corrosions. Stray current collector cables are also used for increasing system efficiency and protecting against corrosions. These cables are insulated from the ground and by collecting the stray currents from the mats, greatly diminish current leakages to soil. The cables can be connected to the collection mats at specific locations. The number of connections depends on the magnitude of stray current

Using collection systems as mats can help collect more than 0.85 of rails stray currents. Also addition of cables to these systems further boosts the system lifetime and stray current

However, usage of stray current collection system causes floating system acts like diode grounded system, but as shown in the last scenario, use of voltage control device is

At locations where there is negative current leakage to the ground, the health of the existing metallic structures is threatened. Therefore it is recommended to use stray current and metallic structures voltage changes monitoring systems, at these locations, that conform to

The authors would like to thank Tehran Urban and Suburban Railway Company for assistance to perform the testing, study and evaluation. They express their appreciations to

[1] Y. C. Liu and J. F. Chen, Control scheme for reducing rail potential and stray current in MRT systems, IEE Proc. Electr. Power Appl.,2005, vol. 152issue 3, pp 612-618. [2] D. Paul, DC traction power system grounding, IEEE Trans. Ind. Appl., 2002, vol. 38, pp

Mr. Hamed Zafari for his effort to revise this paper in English language.

Fig. 37. Rail potential and stray currents of the two lines when collection mats and collector cable are used a) Rail potential b) Rail stray current c) Current leakage to the ground d) Current entering the current collector mat.

### **6. Conclusions**

252 Infrastructure Design, Signalling and Security in Railway

South Line North Line

> South Line North Line

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> <sup>1400</sup> <sup>1600</sup> <sup>1800</sup> -5

Location (m)

a)

<sup>0</sup> <sup>200</sup> <sup>400</sup> <sup>600</sup> <sup>800</sup> <sup>1000</sup> <sup>1200</sup> <sup>1400</sup> <sup>1600</sup> <sup>1800</sup> -0.05

b)

0 200 400 600 800 1000 1200 1400 1600 1800

c)

0 200 400 600 800 1000 1200 1400 1600 1800

d) Fig. 37. Rail potential and stray currents of the two lines when collection mats and collector cable are used a) Rail potential b) Rail stray current c) Current leakage to the ground d)

Location (m)

Location (m)

Location (m)

> 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45


0.1 0.2 0.3 0.4 0.5 0.6 0.7

Current entering the current collector mat.

Mesh Current (A)


Secondary Stray Current (A)

0

0.05

0.1

Primary Stray Current (A)

Rail Potential (V)

Based on the performed simulations, it can be concluded that among the existing grounding schemes, the solidly grounded system creates the highest amounts of stray current. Using floating ground systems reduces the stray currents leakage. The systems that create direct rail to ground connections increase the corrosion rates significantly. The higher the connection current and the longer the time, the higher the magnitude of the resulting corrosions would be.

The metallic mats of track-beds and foundations increase the stray current leakage to the ground. The stray current travels through the mat and creates metallic corrosion in system terminations. If the mats are used as low resistance paths for absorbing stray currents and directing them to the substations, not only the corrosions of the mats, but also damages to the neighboring structures are avoided. For this purpose, the detached structures are bonded to each other and finally connected to the negative busbar of the substation. Employing stray current collection mats greatly reduces current leakages to ground. Increased cross sectional areas (of cables) and unified connectivity would further improve system efficiency and protection of the mats against corrosions. Stray current collector cables are also used for increasing system efficiency and protecting against corrosions. These cables are insulated from the ground and by collecting the stray currents from the mats, greatly diminish current leakages to soil. The cables can be connected to the collection mats at specific locations. The number of connections depends on the magnitude of stray current at a specific location.

Using collection systems as mats can help collect more than 0.85 of rails stray currents. Also addition of cables to these systems further boosts the system lifetime and stray current collection up to 0.94.

However, usage of stray current collection system causes floating system acts like diode grounded system, but as shown in the last scenario, use of voltage control device is necessary in stations without traction substations.

At locations where there is negative current leakage to the ground, the health of the existing metallic structures is threatened. Therefore it is recommended to use stray current and metallic structures voltage changes monitoring systems, at these locations, that conform to EN50122-2 standard [12].

### **7. Acknowledgements**

The authors would like to thank Tehran Urban and Suburban Railway Company for assistance to perform the testing, study and evaluation. They express their appreciations to Mr. Hamed Zafari for his effort to revise this paper in English language.

### **8. References**


**1. Introduction**

recently termed as "Jamology" [4, 5] .

study jamming phenomena as a mathematical science.

Jamming phenomena are observed everywhere in our daily live. These stagnations in flow occur not only on highways, but also in stadiums, in public transportation like buses and trains, in the world of the Internet, and even in our bodies. Almost everyone will have a negative image of a "jam", which means the clogging of the flow of traffic, however we do have positive reactions to some kinds of jams. For instance, it is gratifying to interrupt the

**Modeling of Passenger Transport Systems** 

*Meiji Institute for Advanced Study of Mathematical Sciences, JST CREST,* 

*1-1-1 Higashi Mita, Tama-ku, Kawasaki, Kanagawa,* 

**Cellular Automaton** 

Akiyasu Tomoeda

*Meiji University,* 

*Japan* 

**10**

The important point is that all these kinds of phenomena have the commonality of being a congestion in a transporting process which comes about through a universal jamming formation process. Especially from the point of statistical physics, these jamming phenomena are also interesting as a system of interacting particles, such as vehicles, pedestrians, ants, Internet packets, and so on, driven far from equilibrium. By considering all the above particles in various transporting processes as "Self-Driven Particles" (SDPs), we are allowed to treat various transportation phenomena universally under the physics of complex systems [1–3] . This interdisciplinary research on jamming phenomena of SDPs in various fields has been

Now, let us consider the state of "Jam", i.e., what is a "Jamming flow"? It is difficult for anyone to answer this question exactly. Japanese expressway companies incorporate specific threshold velocities to define the jamming flow. That is, if the average traffic velocity becomes less than the defined threshold velocity, the state of traffic is considered to have transitioned to a jamming flow. Whereas, if the average traffic velocity is above the threshold, the state of traffic flow corresponds to "Free flow". For example, one company defines the threshold velocity to be 40km per hour. In this case, if the average traffic velocity becomes less than 40km per hour, the state of traffic flow is called jamming flow. Whereas, another company identifies jamming flow by defining the threshold as 30km per hour. There is a lack of uniformity, since the definition of jamming flow depends on the company. Moreover, when it comes to considering the jamming phenomena in the dynamics of non-vehicles, such as pedestrians and ants, it becomes difficult to properly translate these definitions based on threshold velocity to another definition of the jamming state in the dynamics of non-vehicles. Thus, we should begin to provide a clear definition of jamming flow in the next section to

transmission of infectious disease or prevent the spreading of fire.


## **Cellular Automaton Modeling of Passenger Transport Systems**

Akiyasu Tomoeda

*Meiji Institute for Advanced Study of Mathematical Sciences, JST CREST, Meiji University, 1-1-1 Higashi Mita, Tama-ku, Kawasaki, Kanagawa, Japan* 

### **1. Introduction**

254 Infrastructure Design, Signalling and Security in Railway

[3] G. Yu and C. J. Goodman, Modeling of rail potential rise and leakage current in DC rail

[4] S. Case, DC Traction Stray Current Control. So What is the Problem?, Inst. Elect. Eng.

[5] C. H. Lee, and Wang, H.M., Effects of earthing schemes on rail potential and stray

[6] C. H. Lee and C. J. Lu, Assessment of Grounding Schemes on Rail Potential and Stray

[7] C. Charalambous and I. Cotton, Influence of soil structures on corrosion performance of floating-DC transit systems, IET Electr. Power Appl., 2007, vol. 1, pp .9-16 [8] I. Cotton, P. Aylott and P. Ernst, Stray Current Control in DC Mass Transit Systems, IEEE Transaction on vehicular technology,2005, vol. 54, no.2. pp 722-730 [9] C. Lee, Evaluation of the Maximum Potential Rise in Taipei Rail Transit Systems, IEEE

[10] C. H. Lee and Y. S. Tzeng, Assessment of grounding, bonding, and insulation on rail

[11] W. M. Sim, C. F. Chan, Stray current monitoring and control on Singapore MRT system, IEEE international Conf. on power system tech., Powercon (2004), pp 1898-1903. [12] European Standard EN 50122 -2, Railway applications - Protection again leaked

potential and stray currents in a direct current transit system, JRRT206, 2009, vol.

Transactions on Power Delivery, 2005, vol. 20, no. 2, pp. 1379-1384.

railways and tramways, 1990, pp 221-226.

Seminar (1999).

148–154.

pp.1941-1947

223, pp. 229-240

currents, CENELEC, Bruxelles(1999).

transit systems, Presented at IEE colloquium on Stray current effects of DC

current in Taipei rail transit systems, IEE Proc. Electr. Power Appl., vol. 148(2001),

Currents in a DC Transit System, IEEE Trans. on Power Delivery,2006, vol. 21,

Jamming phenomena are observed everywhere in our daily live. These stagnations in flow occur not only on highways, but also in stadiums, in public transportation like buses and trains, in the world of the Internet, and even in our bodies. Almost everyone will have a negative image of a "jam", which means the clogging of the flow of traffic, however we do have positive reactions to some kinds of jams. For instance, it is gratifying to interrupt the transmission of infectious disease or prevent the spreading of fire.

The important point is that all these kinds of phenomena have the commonality of being a congestion in a transporting process which comes about through a universal jamming formation process. Especially from the point of statistical physics, these jamming phenomena are also interesting as a system of interacting particles, such as vehicles, pedestrians, ants, Internet packets, and so on, driven far from equilibrium. By considering all the above particles in various transporting processes as "Self-Driven Particles" (SDPs), we are allowed to treat various transportation phenomena universally under the physics of complex systems [1–3] . This interdisciplinary research on jamming phenomena of SDPs in various fields has been recently termed as "Jamology" [4, 5] .

Now, let us consider the state of "Jam", i.e., what is a "Jamming flow"? It is difficult for anyone to answer this question exactly. Japanese expressway companies incorporate specific threshold velocities to define the jamming flow. That is, if the average traffic velocity becomes less than the defined threshold velocity, the state of traffic is considered to have transitioned to a jamming flow. Whereas, if the average traffic velocity is above the threshold, the state of traffic flow corresponds to "Free flow". For example, one company defines the threshold velocity to be 40km per hour. In this case, if the average traffic velocity becomes less than 40km per hour, the state of traffic flow is called jamming flow. Whereas, another company identifies jamming flow by defining the threshold as 30km per hour. There is a lack of uniformity, since the definition of jamming flow depends on the company. Moreover, when it comes to considering the jamming phenomena in the dynamics of non-vehicles, such as pedestrians and ants, it becomes difficult to properly translate these definitions based on threshold velocity to another definition of the jamming state in the dynamics of non-vehicles. Thus, we should begin to provide a clear definition of jamming flow in the next section to study jamming phenomena as a mathematical science.

of vehicles on the road. So long as the density is sufficiently small, the average velocity is practically independent of the density as the vehicles are too far apart to interact. Therefore, at sufficiently low density of vehicles, the system effectively acts in a state of "free flow". However, in practice, vehicles have to move more slowly with increasing density. This reality

Cellular Automaton Modeling of Passenger Transport Systems 257

As mentioned before, each expressway company in Japan defines the jamming state by a threshold velocity. Hence, there is no universal definition of the jamming state that can be treated in a mathematical sense. In order to provide a clear definition of "free flow" and "jamming flow", one transforms the vertically plotted value from velocity to flow, i.e., from Fig. 1 (a) to Fig. 1 (b). Surprisingly, this type of fundamental diagram (Fig. 1 (b)) shows the universal features not only in the dynamics of traffic vehicles but also for other general SDPs

**(a)** At low density, there is almost a linear relation between the flow and the density, which intersects at zero. The slope at low density corresponds to the average velocity without

**(b)** If the density exceeds some critical value, the so-called *critical density ρc*, the flow decreases monotonically and it vanishes together with the velocity at some maximum

The critical density indicates the changing point of the flow state from free flow to jamming flow. Therefore, free flow and jamming flow can be defined as the lower density region and higher density region which are separated by the critical density as shown in Fig. 2. Once free flow and jamming flow are defined in terms of the fundamental diagram, one can determine whether the flow is really in a state of "Jam" or not in a rigorous, mathematical sense, even in the dynamics of various other kinds of SDPs, where the jamming state has been considered undefinable or unclear. Thus, the fundamental diagrams are essential to treat the jamming

Now let us introduce two simple stochastic cellular automaton models, i.e., ASEP and ZRP, which are the simple models for non-equilibrium systems of interacting self-driven particles. In these cellular automaton models, the path (a road or rail) is partitioned into *L* identical cells such that each cell can accommodate at most one particle at a time, enforcing the so-called *exclusion principle*, that is, the excluded-volume effect is not supposed to be ignored unlike in the flow of water. <sup>3</sup> Generally, the dynamics of these models are described by a rule 4. The rule for dynamics of particles in case of ASEP is very simple, i.e., "*If the front cell is empty, a particle can move forward with hopping probability p.*" as shown in Fig. 3. Note that, in general,

<sup>2</sup> In several situations involving vehicle dynamics, it has been observed that flow does not depend uniquely on density in an intermediate regime of density. This indicates the existence of a *hysteresis*

<sup>4</sup> Some of them can be described in the form of equations, such as a "master equation" or "max-plus

*effect* and *metastable states*. The critical density in vehicle dynamics is about 25 (vehicles/km). <sup>3</sup> In traditional queuing theory, this excluded-volume effect and spatial structure have never been introduced into the queuing model. An extension of the *M*/*M*/1 queuing process with a spatial structure and excluded-volume effect is introduced in [15, 16] , as the TASEP on a semi-infinite chain

is correctly described in the fundamental diagrams.

**(c)** The flow has one maximum value at medium density.

phenomena as a mathematical science.

with open boundary.

equation / tropical-polynomial".

as follows (also see Fig. 2):

congestion.

density. <sup>2</sup>

Fig. 1. Fundamental diagrams plotted by real data from a Japanese expressway (one-lane data). The horizontal axis indicates the density of vehicles (vehicles/km) and the vertical axis indicates (a) the velocity (km/hour) and (b) flow (vehicles/hour), respectively.

First, in Sec. 2 of this chapter, we introduce the *fundamental diagram* to provide a clear definition of jamming flow and explain two rule-based models for describing the dynamics of SDPs, the so-called *Asymmetric Simple Exclusion Process* (ASEP) and *Zero Range Process* (ZRP), which can capture fundamental features of jamming phenomena in various collective dynamical systems. These models have the important property of being exactly solvable, that is, their steady states are given by a form [6–11] . Therefore, we treat the behavior of particles in complex systems by not only numerical simulations but also analytical calculations in the steady state. In Sec. 3, as an extension of the above stochastic cellular automata, we explain in detail the *Public Conveyance Model* (PCM) [12] , which is a fundamental mathematical model for the passenger transport system by introducing a second field (passengers field) which tracks the number of waiting passengers. In addition, by introducing the route choice model of passengers explicitly into PCM, we have built a real-time railway network simulation tool "KUTTY", which has been applied to the *Tokyo Metro Railway Network* [13, 14] , as described in Sec. 4. Finally, Sec. 5 is devoted to concluding discussions.

The aim of this chapter is to understand the mathematical model for the passenger transport system built on analytical rule-based models and to introduce the real-time railway network simulation tool "KUTTY" as an application of our proposed model.

### **2. Fundamental diagrams and stochastic cellular automata**

Now we introduce the *fundamental diagram* to provide a clear definition of jamming flow. The fundamental diagram is a basic tool in understanding the behavior of the flow in transportation systems: it relates the flow *Q*(*x*, *t*) in the system and the density of vehicles *ρ*(*x*, *t*) <sup>1</sup> . The fundamental is sometimes drawn to indicate the relation between velocity *v*(*x*, *t*) and density *ρ*(*x*, *t*), however, we can easily translate velocity into flow by the relation *Q* = *ρv* .

Fig. 1 is an example of the fundamental diagrams of a Japanese expressway. From these diagrams, it is obvious that the state of traffic flow and velocity strongly depend on the density

<sup>1</sup> In the following, we use *"particle"* in mathematical models to represent a vehicle, a bus, or a train, to keep this discussion as general as possible.

2 Will-be-set-by-IN-TECH

(a) density vs. velocity (b) density vs. flow

First, in Sec. 2 of this chapter, we introduce the *fundamental diagram* to provide a clear definition of jamming flow and explain two rule-based models for describing the dynamics of SDPs, the so-called *Asymmetric Simple Exclusion Process* (ASEP) and *Zero Range Process* (ZRP), which can capture fundamental features of jamming phenomena in various collective dynamical systems. These models have the important property of being exactly solvable, that is, their steady states are given by a form [6–11] . Therefore, we treat the behavior of particles in complex systems by not only numerical simulations but also analytical calculations in the steady state. In Sec. 3, as an extension of the above stochastic cellular automata, we explain in detail the *Public Conveyance Model* (PCM) [12] , which is a fundamental mathematical model for the passenger transport system by introducing a second field (passengers field) which tracks the number of waiting passengers. In addition, by introducing the route choice model of passengers explicitly into PCM, we have built a real-time railway network simulation tool "KUTTY", which has been applied to the *Tokyo Metro Railway Network* [13, 14] , as described

The aim of this chapter is to understand the mathematical model for the passenger transport system built on analytical rule-based models and to introduce the real-time railway network

Now we introduce the *fundamental diagram* to provide a clear definition of jamming flow. The fundamental diagram is a basic tool in understanding the behavior of the flow in transportation systems: it relates the flow *Q*(*x*, *t*) in the system and the density of vehicles *ρ*(*x*, *t*) <sup>1</sup> . The fundamental is sometimes drawn to indicate the relation between velocity *v*(*x*, *t*) and density *ρ*(*x*, *t*), however, we can easily translate velocity into flow by the relation

Fig. 1 is an example of the fundamental diagrams of a Japanese expressway. From these diagrams, it is obvious that the state of traffic flow and velocity strongly depend on the density

<sup>1</sup> In the following, we use *"particle"* in mathematical models to represent a vehicle, a bus, or a train, to

Fig. 1. Fundamental diagrams plotted by real data from a Japanese expressway (one-lane data). The horizontal axis indicates the density of vehicles (vehicles/km) and the vertical axis

indicates (a) the velocity (km/hour) and (b) flow (vehicles/hour), respectively.

in Sec. 4. Finally, Sec. 5 is devoted to concluding discussions.

simulation tool "KUTTY" as an application of our proposed model.

**2. Fundamental diagrams and stochastic cellular automata**

keep this discussion as general as possible.

*Q* = *ρv* .

of vehicles on the road. So long as the density is sufficiently small, the average velocity is practically independent of the density as the vehicles are too far apart to interact. Therefore, at sufficiently low density of vehicles, the system effectively acts in a state of "free flow". However, in practice, vehicles have to move more slowly with increasing density. This reality is correctly described in the fundamental diagrams.

As mentioned before, each expressway company in Japan defines the jamming state by a threshold velocity. Hence, there is no universal definition of the jamming state that can be treated in a mathematical sense. In order to provide a clear definition of "free flow" and "jamming flow", one transforms the vertically plotted value from velocity to flow, i.e., from Fig. 1 (a) to Fig. 1 (b). Surprisingly, this type of fundamental diagram (Fig. 1 (b)) shows the universal features not only in the dynamics of traffic vehicles but also for other general SDPs as follows (also see Fig. 2):


The critical density indicates the changing point of the flow state from free flow to jamming flow. Therefore, free flow and jamming flow can be defined as the lower density region and higher density region which are separated by the critical density as shown in Fig. 2. Once free flow and jamming flow are defined in terms of the fundamental diagram, one can determine whether the flow is really in a state of "Jam" or not in a rigorous, mathematical sense, even in the dynamics of various other kinds of SDPs, where the jamming state has been considered undefinable or unclear. Thus, the fundamental diagrams are essential to treat the jamming phenomena as a mathematical science.

Now let us introduce two simple stochastic cellular automaton models, i.e., ASEP and ZRP, which are the simple models for non-equilibrium systems of interacting self-driven particles. In these cellular automaton models, the path (a road or rail) is partitioned into *L* identical cells such that each cell can accommodate at most one particle at a time, enforcing the so-called *exclusion principle*, that is, the excluded-volume effect is not supposed to be ignored unlike in the flow of water. <sup>3</sup> Generally, the dynamics of these models are described by a rule 4. The rule for dynamics of particles in case of ASEP is very simple, i.e., "*If the front cell is empty, a particle can move forward with hopping probability p.*" as shown in Fig. 3. Note that, in general,

<sup>2</sup> In several situations involving vehicle dynamics, it has been observed that flow does not depend uniquely on density in an intermediate regime of density. This indicates the existence of a *hysteresis effect* and *metastable states*. The critical density in vehicle dynamics is about 25 (vehicles/km).

<sup>3</sup> In traditional queuing theory, this excluded-volume effect and spatial structure have never been introduced into the queuing model. An extension of the *M*/*M*/1 queuing process with a spatial structure and excluded-volume effect is introduced in [15, 16] , as the TASEP on a semi-infinite chain with open boundary.

<sup>4</sup> Some of them can be described in the form of equations, such as a "master equation" or "max-plus equation / tropical-polynomial".

*the next particle in front.*", as illustrated in Fig. 4. Indeed, ASEP is considered as a special case

Cellular Automaton Modeling of Passenger Transport Systems 259

Here, we impose periodic boundary conditions <sup>5</sup> , that is, we consider that the particles to move on a circuit so that the transport system is operated as a loop. This means that the number of particles *N* on the circuit is conserved at each discrete time step. Moreover, we distinguish three basic types of dynamics: the dynamical variables may be updated one after the other in a certain order (*sequential update*), one after another in random order (*random-sequential update*), or in parallel for all sites (*parallel update*). <sup>6</sup> Now let us employ the

As mentioned before, ASEP and ZRP have the important property of being exactly solvable, that is, their steady states are given by a form [6–11] . In the case of ASEP with periodic boundary condition and in parallel dynamics, one obtains the form (see [7] for details)

where *Q*(*ρ*) is flow of particles, *p* is the hopping probability and *ρ* = *N*/*L* is the density of

On the other hand, in the case of ZRP, as a simple example, we now assume that the hopping

If *q* = *p*, this model is reduced to the ASEP with hopping probability *p*, as denoted above. Moreover, if *p* = *q* = 1 in ZRP or *p* = 1 in ASEP, this model is reduced to the deterministic version of ASEP, which is called the rule-184 cellular automaton. This rule-184 CA model is one of the elementary cellular automata, which are defined by S. Wolfram (1959 ∼) [17, 18] . Various extensions of this rule-184 CA are also proposed as a powerful model for realistically

The fundamental diagram of ZRP defined by (4) with periodic boundary conditions and parallel update in a parametric representation, where the density *ρ*(*w*) = 1/(1 + *h*) and the flow *Q*(*ρ*) = *wρ*(*w*) are calculated for the parameter 0 ≤ *w* ≤ 1, is given by the following

Fig. 5 shows the numerical simulation results (dots) and analytical calculated results (line) for ASEP and ZRP, respectively. In both cases, the analytical results show good agreements with the numerical results. Moreover, both figures captures the universal features (*a*) − (*c*) of general SDPs in transport systems, which were introduced earlier in this section. Therefore,

<sup>6</sup> Sometimes, updating the dynamics in parallel for all sites of a given sub-lattice (*sub-lattice update*) is

∞ ∑ *n*=0 *<sup>w</sup><sup>n</sup> <sup>n</sup>* ∏ *j*=1

1 − 4*pρ*(1 − *ρ*)

*p*(1) = *p*, *p*(*h* ≥ 2) = *q*. (4)

1 − *p*(*j*) *p*(*j*)

. (6)

, (5)

, (3)

parallel update for all sites in the system as the updating procedures.

*<sup>Q</sup>*(*ρ*) = <sup>1</sup>

2 1 − 

of ZRP.

particles.

probability is

describing one-dimensional traffic flow.

distinguished from this parallel update.

*F*(*w*) =

*h*(*w*) = *w*

1 − *p*(1)

*∂ ∂w* 

<sup>5</sup> ASEP and ZRP with open boundary conditions are also well investigated.

 (1 + *w*)

log *F*(*w*)

equations (see [11] for details)

Fig. 3. Dynamics of the Asymmetric Simple Exclusion Process: if the next cell is empty, a particle can move forward with hopping probability *p*.

Fig. 4. Dynamics of the Zero Range Process after the mapping to the asymmetric exclusion process: if the next cell is empty, a particle can move forward with hopping probability *p*(*h*), which depends on the distance to the next particle in front.

ASEP is characterized by the hopping rate

$$P\_{\{10\} \to \{01\}} = p\_\prime \tag{1}$$

$$P\_{\{01\} \to \{10\}} = q\_\prime \tag{2}$$

which is considered as a model of interacting random walks.

The most important special case, theoretically as well as in the application to transport systems, is known by the full name of *Totally Asymmetric Simple Exclusion Process* (TASEP), which has *q* = 0 so that its motion is allowed only in one direction. Here, we use the general name ASEP to mean TASEP for simplicity' sake. Moreover, the hopping probability *p* is usually called the hopping rate in ASEP, since time is continuous in ASEP. However, we call the rate *p* the hopping probability *p*, since we treat only the discrete time case in this chapter.

In the case of ZRP, after a suitably precise mapping, the rule is considered as "*If the front cell is empty, a particle can move forward with hopping probability p*(*h*)*, which depends on the distance to* 4 Will-be-set-by-IN-TECH

Fig. 2. Features and definition of the jamming state in the simplified fundamental diagram

Fig. 3. Dynamics of the Asymmetric Simple Exclusion Process: if the next cell is empty, a

Fig. 4. Dynamics of the Zero Range Process after the mapping to the asymmetric exclusion process: if the next cell is empty, a particle can move forward with hopping probability *p*(*h*),

The most important special case, theoretically as well as in the application to transport systems, is known by the full name of *Totally Asymmetric Simple Exclusion Process* (TASEP), which has *q* = 0 so that its motion is allowed only in one direction. Here, we use the general name ASEP to mean TASEP for simplicity' sake. Moreover, the hopping probability *p* is usually called the hopping rate in ASEP, since time is continuous in ASEP. However, we call the rate *p* the hopping probability *p*, since we treat only the discrete time case in this chapter. In the case of ZRP, after a suitably precise mapping, the rule is considered as "*If the front cell is empty, a particle can move forward with hopping probability p*(*h*)*, which depends on the distance to*

*<sup>P</sup>*{10}→{01} <sup>=</sup> *<sup>p</sup>*, (1) *<sup>P</sup>*{01}→{10} <sup>=</sup> *<sup>q</sup>*, (2)

particle can move forward with hopping probability *p*.

which depends on the distance to the next particle in front.

which is considered as a model of interacting random walks.

ASEP is characterized by the hopping rate

(density vs. flow).

*the next particle in front.*", as illustrated in Fig. 4. Indeed, ASEP is considered as a special case of ZRP.

Here, we impose periodic boundary conditions <sup>5</sup> , that is, we consider that the particles to move on a circuit so that the transport system is operated as a loop. This means that the number of particles *N* on the circuit is conserved at each discrete time step. Moreover, we distinguish three basic types of dynamics: the dynamical variables may be updated one after the other in a certain order (*sequential update*), one after another in random order (*random-sequential update*), or in parallel for all sites (*parallel update*). <sup>6</sup> Now let us employ the parallel update for all sites in the system as the updating procedures.

As mentioned before, ASEP and ZRP have the important property of being exactly solvable, that is, their steady states are given by a form [6–11] . In the case of ASEP with periodic boundary condition and in parallel dynamics, one obtains the form (see [7] for details)

$$Q(\rho) = \frac{1}{2} \left[ 1 - \sqrt{1 - 4p\rho(1 - \rho)} \right],\tag{3}$$

where *Q*(*ρ*) is flow of particles, *p* is the hopping probability and *ρ* = *N*/*L* is the density of particles.

On the other hand, in the case of ZRP, as a simple example, we now assume that the hopping probability is

$$p(1) = p, \quad p(h \ge 2) = q. \tag{4}$$

If *q* = *p*, this model is reduced to the ASEP with hopping probability *p*, as denoted above. Moreover, if *p* = *q* = 1 in ZRP or *p* = 1 in ASEP, this model is reduced to the deterministic version of ASEP, which is called the rule-184 cellular automaton. This rule-184 CA model is one of the elementary cellular automata, which are defined by S. Wolfram (1959 ∼) [17, 18] . Various extensions of this rule-184 CA are also proposed as a powerful model for realistically describing one-dimensional traffic flow.

The fundamental diagram of ZRP defined by (4) with periodic boundary conditions and parallel update in a parametric representation, where the density *ρ*(*w*) = 1/(1 + *h*) and the flow *Q*(*ρ*) = *wρ*(*w*) are calculated for the parameter 0 ≤ *w* ≤ 1, is given by the following equations (see [11] for details)

$$F(w) = \left(1 - p(1)\right) (1 + w) \sum\_{n=0}^{\infty} \left(w^n \prod\_{j=1}^{n} \frac{1 - p(j)}{p(j)}\right),\tag{5}$$

$$h(w) = w \frac{\partial}{\partial w} \Big(\log F(w)\Big). \tag{6}$$

Fig. 5 shows the numerical simulation results (dots) and analytical calculated results (line) for ASEP and ZRP, respectively. In both cases, the analytical results show good agreements with the numerical results. Moreover, both figures captures the universal features (*a*) − (*c*) of general SDPs in transport systems, which were introduced earlier in this section. Therefore,

<sup>5</sup> ASEP and ZRP with open boundary conditions are also well investigated.

<sup>6</sup> Sometimes, updating the dynamics in parallel for all sites of a given sub-lattice (*sub-lattice update*) is distinguished from this parallel update.

Fig. 6. Schematic illustration of the PCM. The hopping probability to the bus stop depends on the number of waiting passengers. Accordingly, if the waiting passengers increase, the hopping probability to the bus stop decreases. Although case (a) and (b) is the same hopping probability, the situation is different: (a) next cell is without bus stop, (b) next cell is with bus stop but without passengers. Case (d) has smaller probability than the case (c), since the hopping probability depend on the number of waiting passengers. Of course, case (c) is

Cellular Automaton Modeling of Passenger Transport Systems 261

The symbol *H* is used to denote the hopping probability of a bus entering into a cell that has

where min(*Ni*, *N*max) is the number of passengers who can get into a bus which arrives at the bus stop *i* at the instant of time when the number of passengers waiting at the bus stop *i* (*i* = 1, ··· , *S*) is *Ni*. The form (7) is motivated by the common expectation that the time needed for the passengers to board a bus is proportional to their number. Fig. 6 depicts the hopping probabilities schematically. The hopping probability of a bus to the cells that are not designated as bus stops is *Q*; this is already captured by the expression (7) since no passenger

If the form *H* does not depend on the number of waiting passengers but depends on the

*Q* no waiting passengers,

where both *Q* and *q* (*Q > q*) are constants independent of the number of waiting passengers, this model corresponds to the *Ant-Trail-Model*, which also shows quite similar clustering phenomena to those of vehicles in the collective movement of ants and obtains the results through approximate analysis [22, 23] . Moreover, if the form *H* is always constant, this model

In principle, the hopping probability *H* for a real bus would depend also on the number of passengers who get off at the bus stop; in the extreme situations where no passenger is waiting at a bus stop, the hopping probability *H* would be solely decided by the disembarking passengers. However, in order to keep the model theoretically simple and tractable, we ignore the latter situation and assume that passengers get off only at those stops where waiting passengers get into the bus and that the time taken by the waiting passengers to get into

the bus is always adequate for the disembarking passengers to get off the bus.

min(*Ni*, *<sup>N</sup>*max) + <sup>1</sup> (7)

*<sup>q</sup>* waiting passengers exist, (8)

*<sup>H</sup>* <sup>=</sup> *<sup>Q</sup>*

smaller than the case (b) (also case (a))).

ever waits at those locations.

is reduced to the ASEP.

presence of passengers in the case *S* = *L*, i.e.,

*H* =

been designated as a bus stop. We assume *H* has the form

Fig. 5. Fundamental diagram of (a) Asymmetric Simple Exclusion Process and (b) Zero Range Process with the parallel update. The dots and the line correspond to the simulation data and analytical results, respectively. The numerical simulations are done with *L* = 100 sites. In the case of ASEP, the hopping probability *p* is 0.5. In the case of ZRP, the hopping probability *p*(*h*) is *p*(0) = 0, *p*(1) = 0.1, *p*(2 ≥ *h*) = 0.5.

various extensions of these models have been reported in the last few years for capturing the essential features of the collective spatio-temporal organizations in wide varieties of systems, including those in vehicular traffic [1, 2, 19] .

Until now, public conveyance traffic systems such as buses, bicycles and trains have also been modeled by an extension of ASEP using similar approaches [12–14, 20, 21]. A simple bus route model [21] exhibits clustering of the buses along the route. The quantitative features of the coarsening of the clusters have strong similarities with coarsening phenomena in many other physical systems. Under normal circumstances, such clustering of buses is undesirable in any real bus route as the efficiency of the transportation system is adversely affected by clustering.

In the next section, a new public conveyance model (PCM) will be explained which is applicable to buses and trains in a transport system by introducing realistic effects encountered in the field (the number of stops (stations) and the behavior of passengers getting on a vehicle at stops) into the stochastic cellular automaton models.

#### **3. Public conveyance model for a bus-route system**

Now we will explain the PCM in detail. Although we refer to each of the public vehicles as a "bus", which is a one-dimensional example of a transport system, the model is equally applicable to train traffic on a given route. We impose periodic boundary conditions as well as the stochastic cellular automata described in the previous section and partition the road into *L* identical cells. Moreover, a total of *S* (0 ≤ *S* ≤ *L*) *equispaced* cells are identified in the beginning as bus stops. Note that, the special case *S* = *L* corresponds to the *hail-and-ride* system, in which the passengers could board the bus whenever and wherever they stopped a bus by raising their hand. In contrast to most of the earlier bus route models built on the stochastic cellular automaton, we assume that the maximum number of passengers that can get into one bus at a bus stop is *N*max, which indicates the *maximum boarding capacity* at each bus stop rather than the *maximum carrying capacity* of each bus.

6 Will-be-set-by-IN-TECH

**flux**

Fig. 5. Fundamental diagram of (a) Asymmetric Simple Exclusion Process and (b) Zero Range Process with the parallel update. The dots and the line correspond to the simulation data and analytical results, respectively. The numerical simulations are done with *L* = 100 sites. In the case of ASEP, the hopping probability *p* is 0.5. In the case of ZRP, the hopping

various extensions of these models have been reported in the last few years for capturing the essential features of the collective spatio-temporal organizations in wide varieties of systems,

Until now, public conveyance traffic systems such as buses, bicycles and trains have also been modeled by an extension of ASEP using similar approaches [12–14, 20, 21]. A simple bus route model [21] exhibits clustering of the buses along the route. The quantitative features of the coarsening of the clusters have strong similarities with coarsening phenomena in many other physical systems. Under normal circumstances, such clustering of buses is undesirable in any real bus route as the efficiency of the transportation system is adversely affected by

In the next section, a new public conveyance model (PCM) will be explained which is applicable to buses and trains in a transport system by introducing realistic effects encountered in the field (the number of stops (stations) and the behavior of passengers getting

Now we will explain the PCM in detail. Although we refer to each of the public vehicles as a "bus", which is a one-dimensional example of a transport system, the model is equally applicable to train traffic on a given route. We impose periodic boundary conditions as well as the stochastic cellular automata described in the previous section and partition the road into *L* identical cells. Moreover, a total of *S* (0 ≤ *S* ≤ *L*) *equispaced* cells are identified in the beginning as bus stops. Note that, the special case *S* = *L* corresponds to the *hail-and-ride* system, in which the passengers could board the bus whenever and wherever they stopped a bus by raising their hand. In contrast to most of the earlier bus route models built on the stochastic cellular automaton, we assume that the maximum number of passengers that can get into one bus at a bus stop is *N*max, which indicates the *maximum boarding capacity* at each

on a vehicle at stops) into the stochastic cellular automaton models.

**3. Public conveyance model for a bus-route system**

bus stop rather than the *maximum carrying capacity* of each bus.

**0.00 0.02 0.04 0.06 0.08 0.10**

**0.0 0.2 0.4 0.6 0.8 1.0**

**density**

(b) ZRP

**0.0 0.2 0.4 0.6 0.8 1.0**

**density**

(a) ASEP

probability *p*(*h*) is *p*(0) = 0, *p*(1) = 0.1, *p*(2 ≥ *h*) = 0.5.

including those in vehicular traffic [1, 2, 19] .

**0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14**

**flux**

clustering.

Fig. 6. Schematic illustration of the PCM. The hopping probability to the bus stop depends on the number of waiting passengers. Accordingly, if the waiting passengers increase, the hopping probability to the bus stop decreases. Although case (a) and (b) is the same hopping probability, the situation is different: (a) next cell is without bus stop, (b) next cell is with bus stop but without passengers. Case (d) has smaller probability than the case (c), since the hopping probability depend on the number of waiting passengers. Of course, case (c) is smaller than the case (b) (also case (a))).

The symbol *H* is used to denote the hopping probability of a bus entering into a cell that has been designated as a bus stop. We assume *H* has the form

$$H = \frac{Q}{\min(N\_{\dot{\nu}}, N\_{\max}) + 1} \tag{7}$$

where min(*Ni*, *N*max) is the number of passengers who can get into a bus which arrives at the bus stop *i* at the instant of time when the number of passengers waiting at the bus stop *i* (*i* = 1, ··· , *S*) is *Ni*. The form (7) is motivated by the common expectation that the time needed for the passengers to board a bus is proportional to their number. Fig. 6 depicts the hopping probabilities schematically. The hopping probability of a bus to the cells that are not designated as bus stops is *Q*; this is already captured by the expression (7) since no passenger ever waits at those locations.

If the form *H* does not depend on the number of waiting passengers but depends on the presence of passengers in the case *S* = *L*, i.e.,

$$H = \begin{cases} Q & \text{no waiting passengers,} \\ q & \text{wating passengers exist,} \end{cases} \tag{8}$$

where both *Q* and *q* (*Q > q*) are constants independent of the number of waiting passengers, this model corresponds to the *Ant-Trail-Model*, which also shows quite similar clustering phenomena to those of vehicles in the collective movement of ants and obtains the results through approximate analysis [22, 23] . Moreover, if the form *H* is always constant, this model is reduced to the ASEP.

In principle, the hopping probability *H* for a real bus would depend also on the number of passengers who get off at the bus stop; in the extreme situations where no passenger is waiting at a bus stop, the hopping probability *H* would be solely decided by the disembarking passengers. However, in order to keep the model theoretically simple and tractable, we ignore the latter situation and assume that passengers get off only at those stops where waiting passengers get into the bus and that the time taken by the waiting passengers to get into the bus is always adequate for the disembarking passengers to get off the bus.

The PCM model reported here can be easily extended to incorporate an additional dynamical variable associated with each bus to account for the instantaneous number of passengers in it. But, for the sake of simplicity, such an extension of PCM is not reported here <sup>7</sup> . Instead, we focus on the simple version of PCM. As shown in Fig. 7, the model is updated according to the following rules:

1. *Arrival of a passenger*

A bus stop *i* (*i* = 1, ··· , *S*) is picked up randomly, with probability 1/*S*, and then the corresponding number of waiting passengers is increased by unity, i.e., *Ni* → *Ni* + 1, with probability *f* to account for the arrival of a passenger at the selected bus stop. Thus, the average number of passengers that arrive at each bus stop per unit time is given by *f* /*S*.

2. *Bus motion*

If the cell in front of a bus is not occupied by another bus, each bus hops to the next cell with probability *H*. Specifically, if passengers do not exist in the next cell the hopping probability equals *Q* because *Ni* is equal to 0. Otherwise, if passengers exist in the next cell, the hopping probability is *Q*/(min(*Ni*, *N*max) + 1). Note that, when a bus is loaded with passengers to its maximum boarding capacity *N*max, the hopping probability is *Q*/(*N*max + 1), the smallest allowed hopping probability.

3. *Boarding a bus*

When a bus arrives at the *i*-th (*i* = 1, ··· , *S*) bus stop cell, the corresponding number *Ni* of waiting passengers is updated to max(*Ni* − *N*max, 0) to account for the passengers boarding the bus. Once the door is closed, no more waiting passengers can get into the bus at the same bus stop although the bus may remain stranded at the same stop for a longer period of time either because of the unavailability of the next bus stop or because of the traffic control rule explained next.

We introduce a traffic control system that exploits the information on the number of buses in each *segment* between successive bus stops, as well as a block section of the railway system. Every bus stop has information *Ii* (*i* = 1, ··· , *S*) which is the number of buses in the *i*-th segment of the route between the *i*-th and next (*i* + 1)-th bus stops at that instant of time. If *Ii* is larger than the average value *I*<sup>0</sup> = *m*/*S*, where *m* indicates the total number of buses, a bus remains stranded at a stop *i* as long as *Ii* exceeds *I*0. In steps 2, 3, and the information-based control system (step 4), these rules are applied in parallel to all buses and passengers, respectively.

We use the average speed �*V*� of the buses, the number of waiting passengers �*N*� at a bus stop and the transportation volume *R*, which is defined by the product of velocity of the *i*-th bus *Vi* ∈ {0, 1} and the number of on-board passengers *Mi* (0 ≤ *Mi* ≤ *N*max), i.e.,

$$R = \sum\_{i=1}^{m} M\_i V\_{i\nu} \tag{9}$$

Fig. 7. Time development of public conveyance model. The upper path of cells indicates the state of particles and the lower one indicates the state of passengers. The number in each cell represents the number of waiting passengers. The cells with diagonal lines indicate cells

Cellular Automaton Modeling of Passenger Transport Systems 263

Waiting passengers

Fig. 8. The plot of *V* and *N* without information for *S* = 5 and *f* = 0.3, 0.6 and 0.9.

In the simulations presented here, we set *L* = 500, *S* = 5, *Q* = 0.9, *q* = 0.5 and *N*max = 60. The main parameters of this model, which we varied, are the number of buses *m* and the probability *f* of the arrival of passengers. The density of buses is defined by *ρ* = *m*/*L* in the same way. We study not only the efficiency of the system but also the effects of our control system by comparing the characteristics of two traffic systems one of which includes

0 0.2 0.4 0.6 0.8 1 Density

(b) Waiting passengers *N*

f 0.3 f 0.6 f 0.9

without bus stops.

0.2

0.4

Average velocity

0.6

0.8

0 0.2 0.4 0.6 0.8 1 Density

the information-based control system while the other does not.

(a) Average velocity *V*

f 0.3 f 0.6 f 0.9

as three quantitative measures of the efficiency of the public conveyance system under consideration; a higher �*V*� , a higher *R* and smaller �*N*� correspond to a more efficient transportation system.

<sup>7</sup> We have reported the extended PCM by incorporating the disembarking passengers explicitly for the case of the elevator system in [24] .

8 Will-be-set-by-IN-TECH

The PCM model reported here can be easily extended to incorporate an additional dynamical variable associated with each bus to account for the instantaneous number of passengers in it. But, for the sake of simplicity, such an extension of PCM is not reported here <sup>7</sup> . Instead, we focus on the simple version of PCM. As shown in Fig. 7, the model is updated according to

A bus stop *i* (*i* = 1, ··· , *S*) is picked up randomly, with probability 1/*S*, and then the corresponding number of waiting passengers is increased by unity, i.e., *Ni* → *Ni* + 1, with probability *f* to account for the arrival of a passenger at the selected bus stop. Thus, the average number of passengers that arrive at each bus stop per unit time is given by *f* /*S*.

If the cell in front of a bus is not occupied by another bus, each bus hops to the next cell with probability *H*. Specifically, if passengers do not exist in the next cell the hopping probability equals *Q* because *Ni* is equal to 0. Otherwise, if passengers exist in the next cell, the hopping probability is *Q*/(min(*Ni*, *N*max) + 1). Note that, when a bus is loaded with passengers to its maximum boarding capacity *N*max, the hopping probability is *Q*/(*N*max +

When a bus arrives at the *i*-th (*i* = 1, ··· , *S*) bus stop cell, the corresponding number *Ni* of waiting passengers is updated to max(*Ni* − *N*max, 0) to account for the passengers boarding the bus. Once the door is closed, no more waiting passengers can get into the bus at the same bus stop although the bus may remain stranded at the same stop for a longer period of time either because of the unavailability of the next bus stop or because of the

We introduce a traffic control system that exploits the information on the number of buses in each *segment* between successive bus stops, as well as a block section of the railway system. Every bus stop has information *Ii* (*i* = 1, ··· , *S*) which is the number of buses in the *i*-th segment of the route between the *i*-th and next (*i* + 1)-th bus stops at that instant of time. If *Ii* is larger than the average value *I*<sup>0</sup> = *m*/*S*, where *m* indicates the total number of buses, a bus remains stranded at a stop *i* as long as *Ii* exceeds *I*0. In steps 2, 3, and the information-based control system (step 4), these rules are applied in parallel to all buses and

We use the average speed �*V*� of the buses, the number of waiting passengers �*N*� at a bus stop and the transportation volume *R*, which is defined by the product of velocity of the *i*-th

as three quantitative measures of the efficiency of the public conveyance system under consideration; a higher �*V*� , a higher *R* and smaller �*N*� correspond to a more efficient

<sup>7</sup> We have reported the extended PCM by incorporating the disembarking passengers explicitly for the

*MiVi*, (9)

bus *Vi* ∈ {0, 1} and the number of on-board passengers *Mi* (0 ≤ *Mi* ≤ *N*max), i.e.,

*R* = *m* ∑ *i*=1

the following rules:

2. *Bus motion*

3. *Boarding a bus*

passengers, respectively.

transportation system.

case of the elevator system in [24] .

1. *Arrival of a passenger*

1), the smallest allowed hopping probability.

traffic control rule explained next.

Fig. 7. Time development of public conveyance model. The upper path of cells indicates the state of particles and the lower one indicates the state of passengers. The number in each cell represents the number of waiting passengers. The cells with diagonal lines indicate cells without bus stops.

Fig. 8. The plot of *V* and *N* without information for *S* = 5 and *f* = 0.3, 0.6 and 0.9.

In the simulations presented here, we set *L* = 500, *S* = 5, *Q* = 0.9, *q* = 0.5 and *N*max = 60. The main parameters of this model, which we varied, are the number of buses *m* and the probability *f* of the arrival of passengers. The density of buses is defined by *ρ* = *m*/*L* in the same way. We study not only the efficiency of the system but also the effects of our control system by comparing the characteristics of two traffic systems one of which includes the information-based control system while the other does not.

f � 0.3 f � 0.6 f � 0.9 f � 0.3 f � 0.6 f � 0.9

Density <sup>Ρ</sup>

0.0 0.2 0.4 0.6 0.8

(b) with information

0.00 0.05 0.10 0.15 0.20 0.25 0.30

Flux

Fig. 12. Fundamental diagrams for the flow of vehicles. (a) The case without the

information-based control system, (b) The case with the information-based control system.

passengers *N*, whose inverse is another measure of the efficiency of the bus traffic system, is vanishingly small in the region 0.3 *< ρ <* 0.7; *N* increases with decreasing (increasing) *ρ* in the regime *ρ <* 0.3 (*ρ >* 0.7). The results for the PCM with information-based traffic control system are shown in Fig. 9. The density corresponding to the peak of the average velocity shifts to lower values when the information-based traffic control system is switched on. The average number of waiting passengers *N* decreases between Fig. 8 (b) and Fig. 9 (b) in the

The other measurement of the efficiency, the transportation volume *R*, is shown in Fig. 10. The optimal density which shows higher *V* and lower *N* does not always correspond to the most efficient operation for the transportation volume, since that is maintained substantially constant except at low density, even though the density of vehicles increases. This is because the number of buses with small transportation volume increases even though the average velocity decreases. Thus, we have found that the excess buses result in unneeded buses which

The data shown in Fig. 11 establishes that implementation of the information-based traffic control system does not necessarily always improve the efficiency of the public conveyance system. In fact, in the region 0.3 *< ρ <* 0.7, the average velocity of the buses is higher if the information-based control system is switched off. Comparing *V* and *N* in Fig. 11, we find that the information-based traffic control system can improves the efficiency by reducing the crowd of waiting passengers. However, in the absence of waiting passengers, introduction of the information-based control system adversely affects the efficiency of the public conveyance system by holding up the buses at bus stops when the number of buses in the next segment of the route exceeds *I*0. Therefore, we have found the information-based traffic control system can improve the efficiency in a certain density region, but not in all possible situations.

The typical fundamental diagrams for the flow of vehicles in the PCM are given in Fig. 12. The flow of vehicles without the information-based control system gradually decreases as the arrival rate of passengers increases. In contrast, the flow with the information-based control system drastically decreases for intermediate densities, where there are no waiting passengers in Fig. 9, showing a trapezoidal shape. This trapezoidal shape is similar to the fundamental diagram in [25] and [26] , where a blockage effect is artificially introduced into the rule-184 cellular automaton to take a flow bottleneck into account. Thus, in the absence of waiting

Vehicles

Cellular Automaton Modeling of Passenger Transport Systems 265

Density <sup>Ρ</sup>

has no passengers since the transportation volume is the same.

0.0 0.2 0.4 0.6 0.8

(a) without information

regions 0.1 *< ρ <* 0.3 and 0.7 *< ρ <* 0.9.

0.00 0.05 0.10 0.15 0.20 0.25 0.30

Flux

Vehicles

Fig. 9. The plot of �*V*� and �*N*� with information for *S* = 5 and *f* = 0.3, 0.6 and 0.9

Fig. 10. Fundamental diagrams for the transportation volume. (a) The case without the information-based control system, (b) The case with the information-based control system.

Fig. 11. Two efficiency plots �*V*� and �*N*� for the parameters *S* = 5, *Q* = 0.9, *q* = 0.5, and *f* = 0.9.

Some of the significant results of the numerical simulations of the PCM are as follows. In Fig. 8 and Fig. 9, we plot �*V*� and �*N*� against the density of buses for several different values of *f* . Fig. 8 (a) demonstrates that the average speed �*V*�, which is a measure of the efficiency of the bus traffic system, exhibits a *maximum* at around *ρ* = 0.2 ∼ 0.3, which reflects the bus bunching especially at large *f* . As shown in Fig. 8 (b), The average number of waiting

10 Will-be-set-by-IN-TECH

Waiting passengers

Flux

Fig. 10. Fundamental diagrams for the transportation volume. (a) The case without the information-based control system, (b) The case with the information-based control system.

Fig. 11. Two efficiency plots �*V*� and �*N*� for the parameters *S* = 5, *Q* = 0.9, *q* = 0.5, and

Some of the significant results of the numerical simulations of the PCM are as follows. In Fig. 8 and Fig. 9, we plot �*V*� and �*N*� against the density of buses for several different values of *f* . Fig. 8 (a) demonstrates that the average speed �*V*�, which is a measure of the efficiency of the bus traffic system, exhibits a *maximum* at around *ρ* = 0.2 ∼ 0.3, which reflects the bus bunching especially at large *f* . As shown in Fig. 8 (b), The average number of waiting

without info with info

Passengers

Waiting

Fig. 9. The plot of �*V*� and �*N*� with information for *S* = 5 and *f* = 0.3, 0.6 and 0.9

passengers

0 0.2 0.4 0.6 0.8 1 Density

(b) Waiting passengers �*N*�

f � 0.3 f � 0.6 f � 0.9 0.0 0.2 0.4 0.6 0.8 1.0

Density <sup>Ρ</sup>

without info with info

0 0.2 0.4 0.6 0.8 1 Density

(b) Waiting passengers �*N*�

(b) with information

f � 0.3 f � 0.6 f � 0.9

0 0.2 0.4 0.6 0.8 1 Density

(a) Average velocity �*V*�

f � 0.3 f � 0.6 f � 0.9 0.0 0.2 0.4 0.6 0.8 1.0

Density <sup>Ρ</sup>

0 0.2 0.4 0.6 0.8 1 Density

(a) Average velocity �*V*�

(a) without information

f � 0.3 f � 0.6 f � 0.9

0.2

0

0.2 0.4 0.6 0.8

Average velocity

*f* = 0.9.

Flux

Passengers

0.4

Average velocity

0.6

0.8

Fig. 12. Fundamental diagrams for the flow of vehicles. (a) The case without the information-based control system, (b) The case with the information-based control system.

passengers *N*, whose inverse is another measure of the efficiency of the bus traffic system, is vanishingly small in the region 0.3 *< ρ <* 0.7; *N* increases with decreasing (increasing) *ρ* in the regime *ρ <* 0.3 (*ρ >* 0.7). The results for the PCM with information-based traffic control system are shown in Fig. 9. The density corresponding to the peak of the average velocity shifts to lower values when the information-based traffic control system is switched on. The average number of waiting passengers *N* decreases between Fig. 8 (b) and Fig. 9 (b) in the regions 0.1 *< ρ <* 0.3 and 0.7 *< ρ <* 0.9.

The other measurement of the efficiency, the transportation volume *R*, is shown in Fig. 10. The optimal density which shows higher *V* and lower *N* does not always correspond to the most efficient operation for the transportation volume, since that is maintained substantially constant except at low density, even though the density of vehicles increases. This is because the number of buses with small transportation volume increases even though the average velocity decreases. Thus, we have found that the excess buses result in unneeded buses which has no passengers since the transportation volume is the same.

The data shown in Fig. 11 establishes that implementation of the information-based traffic control system does not necessarily always improve the efficiency of the public conveyance system. In fact, in the region 0.3 *< ρ <* 0.7, the average velocity of the buses is higher if the information-based control system is switched off. Comparing *V* and *N* in Fig. 11, we find that the information-based traffic control system can improves the efficiency by reducing the crowd of waiting passengers. However, in the absence of waiting passengers, introduction of the information-based control system adversely affects the efficiency of the public conveyance system by holding up the buses at bus stops when the number of buses in the next segment of the route exceeds *I*0. Therefore, we have found the information-based traffic control system can improve the efficiency in a certain density region, but not in all possible situations.

The typical fundamental diagrams for the flow of vehicles in the PCM are given in Fig. 12. The flow of vehicles without the information-based control system gradually decreases as the arrival rate of passengers increases. In contrast, the flow with the information-based control system drastically decreases for intermediate densities, where there are no waiting passengers in Fig. 9, showing a trapezoidal shape. This trapezoidal shape is similar to the fundamental diagram in [25] and [26] , where a blockage effect is artificially introduced into the rule-184 cellular automaton to take a flow bottleneck into account. Thus, in the absence of waiting

the database and explain its components: *OD (origin-destination) traffic demand* and *network*

Cellular Automaton Modeling of Passenger Transport Systems 267

In order to apply our PCM to the railway transportation system in a realistic way, real data of the OD traffic demand of passengers is indispensable on the network. In general, it is very difficult to obtain this sort of data. Fortunately, the Tokyo Metro Company posts one-day rider-ship of all stations on its web-site. Moreover, at the mutual entry stations 8, the rider-ship also includes the influx and outflux of passengers. Nevertheless, the data only record the sum of passengers getting through the station gate and do not distinguish whether the passengers enter or leave the station. Therefore, we assume that half of the passengers enter the station and the other half leave the station. This is reasonable because most people go to work or school in the morning and go back home in the evening. Thus they return to the station where

Under these reasonable assumptions, we can estimate the OD demand from one-day rider-ship data of all stations and have verified that the estimated number of passengers is

When a passenger enters a station *i*, the probability that the passenger's destination is *j* is

*Pi*→*<sup>j</sup>* <sup>=</sup> *Nj*

In 2007, the Tokyo Metro Railway Network consisted of 8 lines and 138 stations <sup>9</sup> . Some of these stations are transfer stations, in which several lines intersect. In our model, the stations are mapped to nodes. Under our scheme, each node corresponds one-to-one to the ID number of each station on each line. That is, a transfer station is mapped to more than one nodes, depending on how many lines intersect (e.g., "Otemachi" of the Tozai Line (T09) and "Otemachi" of the Marunouchi Line (M18) are mapped to different nodes). The connection between neighboring stations is referred to as a "segment" and the connection inside a transfer station is referred to as a "link". Using this system, the Tokyo Metro Railway Network has 169 nodes, 170 segments and 50 links. Passengers can travel from any station to any other station in this network with at most two transfers. Therefore, the calculation time in searching for a possible route notably is decreased by restricting transfers to more than two. We have made

In this section, we first present the route choice model of the passengers. Then, the train movement model, which is built on PCM, is introduced. After that, we propose a

<sup>8</sup> The trains still move on from these stations, beyond which the transportation system is operated by other companies, such as Japan Railway. The mutual entry stations are shared by several companies.

<sup>9</sup> Since 2008, a new line has opened to traffic, but we have not included the new line here.

where *Nj* indicates the number of passengers who leave from station *j*.

the database of all paths by using *Dijkstra's Algorithm* [31].

homogenization re-scheduling method to alleviate congestion.

**4.2 Models and homogenization method**

∑*<sup>j</sup> Nj*

, (10)

*structure*.

they originally entered .

suitable for the data.

**4.1.2 Network structure**

**4.1.1 Origin-destination traffic demand estimation**

Fig. 13. The design flow diagram of our simulator "KUTTY".

passengers, implementation of the information-based control system corresponds to creating a bottleneck effect and decreases the flow of vehicles.

As a theoretical approach, mean-field analysis is also applied to the model to estimate the efficiency. The details of mean-field analysis can be found in [12–14] .

Next, let us explain an expanded PCM for the railway transportation system in the Tokyo metropolitan area by introducing the route choice model of passengers.

#### **4. Public conveyance model for Tokyo metro subway network**

Disturbances of well scheduled trains occur everyday. The disturbances may be caused by, for example, a slight delay of trains, traffic accidents, or other factors. Under such circumstances, how does the train company adjust and operate the train schedule? The conventional method of rescheduling the timetable is that the scheduling specialists adjust the timetable by their own empirical rules. This conventional method usually only considers the performance of a single (metro) line and does not take into account the performance of the whole network. Furthermore, this method tries to adjust the trains so that they are equally-spaced in time without considering the flow of passengers. Recently, various kinds of models of the train network, which treat the network as a complex system, have been proposed and studied [27– 30]. However, the behaviors of passengers have not been considered in these models either.

A public conveyance model (PCM) which could reproduce the bus clustering phenomenon and estimate the efficiency of the bus system on a one-dimensional route was proposed in the previous section, where passengers arrive at a stop randomly and their destinations have not been considered explicitly. Furthermore, since buses run on a single route, passengers do not need to choose the route. In this section, we have extended the PCM by introducing realistic passengers' behaviors explicitly and proposed a real-time railway network simulation tool "KUTTY", which has been applied to the *Tokyo Metro Railway Network*. It is shown that the passenger flow pattern is well simulated. Moreover, we have presented a homogenization re-scheduling method to alleviate congestion of crowded trains, and it is found that our method is more efficient than the conventional one.

#### **4.1 Database**

Our real-time simulator "KUTTY" is operated not only based on the input data but also by extracting data from a database (see Fig. 13). In this section, we present the assembly of the database and explain its components: *OD (origin-destination) traffic demand* and *network structure*.

#### **4.1.1 Origin-destination traffic demand estimation**

In order to apply our PCM to the railway transportation system in a realistic way, real data of the OD traffic demand of passengers is indispensable on the network. In general, it is very difficult to obtain this sort of data. Fortunately, the Tokyo Metro Company posts one-day rider-ship of all stations on its web-site. Moreover, at the mutual entry stations 8, the rider-ship also includes the influx and outflux of passengers. Nevertheless, the data only record the sum of passengers getting through the station gate and do not distinguish whether the passengers enter or leave the station. Therefore, we assume that half of the passengers enter the station and the other half leave the station. This is reasonable because most people go to work or school in the morning and go back home in the evening. Thus they return to the station where they originally entered .

Under these reasonable assumptions, we can estimate the OD demand from one-day rider-ship data of all stations and have verified that the estimated number of passengers is suitable for the data.

When a passenger enters a station *i*, the probability that the passenger's destination is *j* is

$$P\_{\bar{i}\to\bar{j}} = \frac{N\_{\bar{j}}}{\sum\_{\bar{j}} N\_{\bar{j}}} \,\tag{10}$$

where *Nj* indicates the number of passengers who leave from station *j*.

#### **4.1.2 Network structure**

12 Will-be-set-by-IN-TECH

passengers, implementation of the information-based control system corresponds to creating

As a theoretical approach, mean-field analysis is also applied to the model to estimate the

Next, let us explain an expanded PCM for the railway transportation system in the Tokyo

Disturbances of well scheduled trains occur everyday. The disturbances may be caused by, for example, a slight delay of trains, traffic accidents, or other factors. Under such circumstances, how does the train company adjust and operate the train schedule? The conventional method of rescheduling the timetable is that the scheduling specialists adjust the timetable by their own empirical rules. This conventional method usually only considers the performance of a single (metro) line and does not take into account the performance of the whole network. Furthermore, this method tries to adjust the trains so that they are equally-spaced in time without considering the flow of passengers. Recently, various kinds of models of the train network, which treat the network as a complex system, have been proposed and studied [27– 30]. However, the behaviors of passengers have not been considered in these models either. A public conveyance model (PCM) which could reproduce the bus clustering phenomenon and estimate the efficiency of the bus system on a one-dimensional route was proposed in the previous section, where passengers arrive at a stop randomly and their destinations have not been considered explicitly. Furthermore, since buses run on a single route, passengers do not need to choose the route. In this section, we have extended the PCM by introducing realistic passengers' behaviors explicitly and proposed a real-time railway network simulation tool "KUTTY", which has been applied to the *Tokyo Metro Railway Network*. It is shown that the passenger flow pattern is well simulated. Moreover, we have presented a homogenization re-scheduling method to alleviate congestion of crowded trains, and it is found that our

Our real-time simulator "KUTTY" is operated not only based on the input data but also by extracting data from a database (see Fig. 13). In this section, we present the assembly of

Fig. 13. The design flow diagram of our simulator "KUTTY".

efficiency. The details of mean-field analysis can be found in [12–14] .

metropolitan area by introducing the route choice model of passengers.

**4. Public conveyance model for Tokyo metro subway network**

a bottleneck effect and decreases the flow of vehicles.

method is more efficient than the conventional one.

**4.1 Database**

In 2007, the Tokyo Metro Railway Network consisted of 8 lines and 138 stations <sup>9</sup> . Some of these stations are transfer stations, in which several lines intersect. In our model, the stations are mapped to nodes. Under our scheme, each node corresponds one-to-one to the ID number of each station on each line. That is, a transfer station is mapped to more than one nodes, depending on how many lines intersect (e.g., "Otemachi" of the Tozai Line (T09) and "Otemachi" of the Marunouchi Line (M18) are mapped to different nodes). The connection between neighboring stations is referred to as a "segment" and the connection inside a transfer station is referred to as a "link". Using this system, the Tokyo Metro Railway Network has 169 nodes, 170 segments and 50 links. Passengers can travel from any station to any other station in this network with at most two transfers. Therefore, the calculation time in searching for a possible route notably is decreased by restricting transfers to more than two. We have made the database of all paths by using *Dijkstra's Algorithm* [31].

#### **4.2 Models and homogenization method**

In this section, we first present the route choice model of the passengers. Then, the train movement model, which is built on PCM, is introduced. After that, we propose a homogenization re-scheduling method to alleviate congestion.

<sup>8</sup> The trains still move on from these stations, beyond which the transportation system is operated by other companies, such as Japan Railway. The mutual entry stations are shared by several companies.

<sup>9</sup> Since 2008, a new line has opened to traffic, but we have not included the new line here.

(a) One of the traditional methods

Cellular Automaton Modeling of Passenger Transport Systems 269

(b) Our homogenization method

Fig. 15. Two types of the re-scheduling methods. The traditional rescheduling method (a) is to adjust the time gap to *Tsch*. However, our homogenization method (b) is to adjust the time

at the instant of time when a train arrives at the upstream neighboring cell as *W* and the

where *a* is a parameter. However, if the train fails to hop into the platform cell once, then it will hop with probability *Q* in the next time step. This is because trains are controlled in units of very small segment by the railway signaling system, and it is not realistic that trains stop stochastically again and again. In this section, the parameters are set to *a* = 0.2, *Q* = 1.

Now let us propose a homogenization re-scheduling method. Suppose there is a sudden increase in passengers at a station. Since there are a lot of passengers waiting on the platform, the nearest upstream train from the station will become congested and thus delayed. If there is no re-scheduling, this train will become more and more delayed at the next stations.

In order to solve this problem, some re-scheduling method could be adopted by delaying the preceding trains of the delayed train, so that the congestion could be shared by preceding

*a* min(*W*,*W*max) + 1

, *Q* 

, (13)

gap to a value which depends on the distribution of the number of passengers.

*<sup>H</sup>* <sup>=</sup> min <sup>1</sup>

maximum carrying capacity of trains as *W*max, we assume that

**4.2.3 Homogenization re-scheduling**

Fig. 14. Illustration of all cases of the hopping probability from a train: (a) Hopping into a non-platform cell. (b) Hopping into a platform cell (first time). (c) Hopping into a platform cell after one stop in the case of (b).

#### **4.2.1 Route choice model**

When a passenger *p* arrives at a station, his/her destination is determined by (10). Suppose *S*(*p*) is the set of all routes from the origin to the destination. The cost *E* of each route *s* ∈ *S*(*p*) at time *t* is calculated by

$$E\left(T(p,s),\mathbb{C}(p,s),D(p,s,t)\right) = aT(p,s)^a + b\mathbb{C}(p,s)^\beta - c\mathbb{D}(p,s,t)^{-\gamma},\tag{11}$$

where *a*, *b*, *c*, *α*, *β*, *γ* are parameters with positive value. In this formula, *T*(*p*,*s*) is the expected travel time on route *s*, 0 ≤ *C*(*p*,*s*) ≤ 2 is the transfer number on route *s*. *T*(*p*,*s*) is calculated by *T*(*p*,*s*) = *nTt* + *C*(*p*,*s*)*Tc*. Here *n* is the number of stations on the route (excluding the origin) and *Tt* is set to 2 minutes, which denotes the average travel time between two neighboring stations. *Tc* is the average transfer time, which is set to 1 minute. The term *bC*(*p*,*s*)*<sup>β</sup>* is adopted to reflect how passengers are reluctant to transfer. Sometimes, passengers would rather choose a route with smaller *C*(*p*,*s*), despite the fact that the travel time on this route is longer. *<sup>D</sup>*(*p*,*s*, *<sup>t</sup>*) is defined as *<sup>D</sup>*(*p*,*s*, *<sup>t</sup>*) = max(*Dtr*, *Dpl*), where *Dtr* = max*i*∈*I*(*Dtr*,*i*) and *Dpl* = max*j*∈*J*(*Dpl*,*j*). Here *Dtr*,*<sup>i</sup>* is passenger density on train *<sup>i</sup>* at time *<sup>t</sup>*, and *Dpl*,*<sup>j</sup>* is passenger density on platform *j* at time *t*; *I* denotes the set of all trains that move on route *s* at time *t*; *J* denotes the set of all platforms on route *s*.

The normalized probability *P*(*p*,*s*, *t*), for the passenger *p* to select route *s*, is described as follows,

$$P(p,s,t) = \frac{\exp\left[-E(p,s,t)\right]}{\sum\_{\mathbf{s}\_i \in S(p)} \exp\left[-E(p,s\_i,t)\right]}.\tag{12}$$

This means that the smaller the cost *E*(*p*,*s*, *t*) is, the larger is the probability that the route will be selected.

#### **4.2.2 Train movement model**

For simplicity, we assume that each *segment* of all lines is partitioned into four identical cells and each *platform* is designated as one cell such that each cell can also accommodate at most one train at a time. Fig. 14 depicts the hopping probabilities in the train model schematically. Let us denote the probability that trains hop into a non-platform cell as *Q*, the hopping probability of a train to a platform cell as *H*, the number of passengers waiting at the platform 14 Will-be-set-by-IN-TECH

Fig. 14. Illustration of all cases of the hopping probability from a train: (a) Hopping into a non-platform cell. (b) Hopping into a platform cell (first time). (c) Hopping into a platform

When a passenger *p* arrives at a station, his/her destination is determined by (10). Suppose *S*(*p*) is the set of all routes from the origin to the destination. The cost *E* of each route *s* ∈ *S*(*p*)

where *a*, *b*, *c*, *α*, *β*, *γ* are parameters with positive value. In this formula, *T*(*p*,*s*) is the expected travel time on route *s*, 0 ≤ *C*(*p*,*s*) ≤ 2 is the transfer number on route *s*. *T*(*p*,*s*) is calculated by *T*(*p*,*s*) = *nTt* + *C*(*p*,*s*)*Tc*. Here *n* is the number of stations on the route (excluding the origin) and *Tt* is set to 2 minutes, which denotes the average travel time between two neighboring stations. *Tc* is the average transfer time, which is set to 1 minute. The term *bC*(*p*,*s*)*<sup>β</sup>* is adopted to reflect how passengers are reluctant to transfer. Sometimes, passengers would rather choose a route with smaller *C*(*p*,*s*), despite the fact that the travel time on this route is longer. *<sup>D</sup>*(*p*,*s*, *<sup>t</sup>*) is defined as *<sup>D</sup>*(*p*,*s*, *<sup>t</sup>*) = max(*Dtr*, *Dpl*), where *Dtr* = max*i*∈*I*(*Dtr*,*i*) and *Dpl* = max*j*∈*J*(*Dpl*,*j*). Here *Dtr*,*<sup>i</sup>* is passenger density on train *<sup>i</sup>* at time *<sup>t</sup>*, and *Dpl*,*<sup>j</sup>* is passenger density on platform *j* at time *t*; *I* denotes the set of all trains that move on route *s* at time *t*; *J*

The normalized probability *P*(*p*,*s*, *t*), for the passenger *p* to select route *s*, is described as

exp 

<sup>∑</sup>*si*∈*S*(*p*) exp

This means that the smaller the cost *E*(*p*,*s*, *t*) is, the larger is the probability that the route will

For simplicity, we assume that each *segment* of all lines is partitioned into four identical cells and each *platform* is designated as one cell such that each cell can also accommodate at most one train at a time. Fig. 14 depicts the hopping probabilities in the train model schematically. Let us denote the probability that trains hop into a non-platform cell as *Q*, the hopping probability of a train to a platform cell as *H*, the number of passengers waiting at the platform

−*E*(*p*,*s*, *t*)

. (12)

−*E*(*p*,*si*, *t*)

<sup>=</sup> *aT*(*p*,*s*)*<sup>α</sup>* <sup>+</sup> *bC*(*p*,*s*)*<sup>β</sup>* <sup>−</sup> *cD*(*p*,*s*, *<sup>t</sup>*)−*γ*, (11)

cell after one stop in the case of (b).

*T*(*p*,*s*), *C*(*p*,*s*), *D*(*p*,*s*, *t*)

denotes the set of all platforms on route *s*.

*P*(*p*,*s*, *t*) =

**4.2.1 Route choice model**

at time *t* is calculated by

follows,

be selected.

**4.2.2 Train movement model**

*E* 

(a) One of the traditional methods

(b) Our homogenization method

Fig. 15. Two types of the re-scheduling methods. The traditional rescheduling method (a) is to adjust the time gap to *Tsch*. However, our homogenization method (b) is to adjust the time gap to a value which depends on the distribution of the number of passengers.

at the instant of time when a train arrives at the upstream neighboring cell as *W* and the maximum carrying capacity of trains as *W*max, we assume that

$$H = \min\left(\frac{1}{a' \min(W, W\_{\max}) + 1}, \mathbb{Q}\right),\tag{13}$$

where *a* is a parameter. However, if the train fails to hop into the platform cell once, then it will hop with probability *Q* in the next time step. This is because trains are controlled in units of very small segment by the railway signaling system, and it is not realistic that trains stop stochastically again and again. In this section, the parameters are set to *a* = 0.2, *Q* = 1.

#### **4.2.3 Homogenization re-scheduling**

Now let us propose a homogenization re-scheduling method. Suppose there is a sudden increase in passengers at a station. Since there are a lot of passengers waiting on the platform, the nearest upstream train from the station will become congested and thus delayed. If there is no re-scheduling, this train will become more and more delayed at the next stations.

In order to solve this problem, some re-scheduling method could be adopted by delaying the preceding trains of the delayed train, so that the congestion could be shared by preceding

(a) Dynamical animation window (b) Visualization window

Cellular Automaton Modeling of Passenger Transport Systems 271

Fig. 16. Snapshots of our simulator "KUTTY". (a) The dynamical animation window of our model. (b) The entire map view, used to visualize the changing-flow in the route map. In KUTTY, the high flow regions (low-flow regions) are colored red (blue). This flow

(a) per train in each line (b) per segment of the Ginza Line

Fig. 17. Comparison plot of the number of passengers between normal operation and operation with an accident at T09. (a)The number of passengers in each line comparing ordinary operation and congested conditions. (b)The number of passengers in each segment

because the Ginza Line intersects with the Tozai Line at T10, and the Hibiya Line intersects with the Tozai Line at T11, both of which are important transfer stations. In contrast, the Hanzomon Line intersects with the Tozai Line at T07, which is not such an important transfer station as T10 and T11. As a result, the passenger flow of the Hanzomon Line is essentially unaffected. Moreover, this result also implies that Otemachi Station is not the destination of most passengers on the Tozai Line, because otherwise the flow rate of the Hanzomon Line would increase (from T10 to Z09 to Z08, and from T07 to Z07 to Z08). Fig. 17 (b) shows the number of passengers on all segments of the Ginza Line. It can be seen that in the area from G05 to G11, the number of passengers increases remarkably. By transferring at these stations, passengers could change to the Marunouchi Line at G09, the Chiyoda Line at G06, and the Namboku Line at G05 and G06. Note that under normal operation, passengers change to the

of the Ginza Line comparing ordinary operation and congested conditions.

dynamically changes with time.

trains. In the conventional re-scheduling method, this is fulfilled by equalizing the time gaps between neighboring trains. For instance (see Fig. 15), suppose that train *B* is expected to arrive at the next station at time *t* = *TB* and train *A* is expected to arrive at the station at time *t* = *TA*. If *TA* − *TB > Tsch*, then the delay time of train *B* is determined by *T*� *<sup>D</sup>* = *TA* − *TB* − *Tsch* (see Fig. 15 (a)). Here *Tsch* is the scheduled time gap.

The delay times of trains located further downstream can be calculated similarly.

In our homogenization re-scheduling method, the number of passengers in each train is homogeneously-distributed by adjusting the distribution of trains as shown in Fig. 15 (b). Here *PB* and *PA* correspond to the number of boarding passengers on trains *B* and *A* respectively. *Ps* denotes the number of passengers waiting at the platform. *EB* and *EA* denote the number of passengers that will get off at the station *i*. Let symbol *I* be the number of passengers who arrive at the station per unit time. The expected arrival times of *B* and *A* at the station *i* are still denoted as *TB* and *TA*. Our objective is not equalizing the time gap but homogenizing the number of passengers, that is, the number of passengers on *B* and *A* is homogenized by extending *TB* to *X*. We calculate *X* from the equation <sup>10</sup>

$$P\_B + (P\_s + IX) - E\_B = P\_A + I(T\_A - X) - E\_A. \tag{14}$$

The left-hand side (right-hand side) of (14) is the number of passengers on *B* (*A*) after departing from the station. The delay time *TD* of *B* is thus decided by

$$T\_D = X - T\_B.\tag{15}$$

Having obtained the delay time of train *B*, the delay times of trains located further downstream can be calculated similarly.

#### **4.3 Simulations and results**

Fig. 16 shows two snapshots of our simulator "KUTTY" which display the direct simulation model and the flow pattern of the passengers of each segment as a visualization on the route map.

By simulating the flow of passengers quantitatively in all segments all over the network, we have found that the most congested area in the Tokyo Metro Railway Network is Otemachi Station on the Tozai Line (T09). Based on this result, we have simulated the case where a virtual accident occurs at Otemachi Station on the Tozai Line so that the trains of Tozai Line could only be operated on two sides of the station. Under this circumstance, the flow pattern of passengers will be changed significantly. This simulation, therefore, provides a very important clue for train scheduling with respect to the potential needs of users for alternative routes in case of accidents.

Fig. 17 shows the quantitative results of several simulations. Fig. 17 (a) shows that the number of passengers who take the Tozai Line decreasing by about 25 percent from normal operation due to the accident at T09. In contrast, the number of passengers who take the Ginza Line and the Hibiya Line increases by about 15 percent and 10 percent respectively. We believe this is

<sup>10</sup> Here we would like to mention that Eq.(5) is not always valid. For example, when *PB* <sup>+</sup> *Ps* <sup>−</sup> *EB <sup>&</sup>gt; <sup>W</sup>*max, Eq.(5) will be invalid. In order for Eq.(5) to be valid, the conditions *TB < X < TA* and 0 *< PB* + (*Ps* + *IX*) − *EB < W*max should be met. Fortunately, in our simulations, this is always the case.

16 Will-be-set-by-IN-TECH

trains. In the conventional re-scheduling method, this is fulfilled by equalizing the time gaps between neighboring trains. For instance (see Fig. 15), suppose that train *B* is expected to arrive at the next station at time *t* = *TB* and train *A* is expected to arrive at the station at time

In our homogenization re-scheduling method, the number of passengers in each train is homogeneously-distributed by adjusting the distribution of trains as shown in Fig. 15 (b). Here *PB* and *PA* correspond to the number of boarding passengers on trains *B* and *A* respectively. *Ps* denotes the number of passengers waiting at the platform. *EB* and *EA* denote the number of passengers that will get off at the station *i*. Let symbol *I* be the number of passengers who arrive at the station per unit time. The expected arrival times of *B* and *A* at the station *i* are still denoted as *TB* and *TA*. Our objective is not equalizing the time gap but homogenizing the number of passengers, that is, the number of passengers on *B* and *A* is

The left-hand side (right-hand side) of (14) is the number of passengers on *B* (*A*) after

Having obtained the delay time of train *B*, the delay times of trains located further

Fig. 16 shows two snapshots of our simulator "KUTTY" which display the direct simulation model and the flow pattern of the passengers of each segment as a visualization on the route

By simulating the flow of passengers quantitatively in all segments all over the network, we have found that the most congested area in the Tokyo Metro Railway Network is Otemachi Station on the Tozai Line (T09). Based on this result, we have simulated the case where a virtual accident occurs at Otemachi Station on the Tozai Line so that the trains of Tozai Line could only be operated on two sides of the station. Under this circumstance, the flow pattern of passengers will be changed significantly. This simulation, therefore, provides a very important clue for train scheduling with respect to the potential needs of users for alternative

Fig. 17 shows the quantitative results of several simulations. Fig. 17 (a) shows that the number of passengers who take the Tozai Line decreasing by about 25 percent from normal operation due to the accident at T09. In contrast, the number of passengers who take the Ginza Line and the Hibiya Line increases by about 15 percent and 10 percent respectively. We believe this is

<sup>10</sup> Here we would like to mention that Eq.(5) is not always valid. For example, when *PB* <sup>+</sup> *Ps* <sup>−</sup> *EB <sup>&</sup>gt; <sup>W</sup>*max, Eq.(5) will be invalid. In order for Eq.(5) to be valid, the conditions *TB < X < TA* and 0 *< PB* + (*Ps* +

*IX*) − *EB < W*max should be met. Fortunately, in our simulations, this is always the case.

*PB* + (*Ps* + *IX*) − *EB* = *PA* + *I*(*TA* − *X*) − *EA*. (14)

*TD* = *X* − *TB*. (15)

*<sup>D</sup>* = *TA* − *TB* − *Tsch*

*t* = *TA*. If *TA* − *TB > Tsch*, then the delay time of train *B* is determined by *T*�

homogenized by extending *TB* to *X*. We calculate *X* from the equation <sup>10</sup>

departing from the station. The delay time *TD* of *B* is thus decided by

downstream can be calculated similarly.

**4.3 Simulations and results**

routes in case of accidents.

map.

The delay times of trains located further downstream can be calculated similarly.

(see Fig. 15 (a)). Here *Tsch* is the scheduled time gap.

(a) Dynamical animation window (b) Visualization window

Fig. 16. Snapshots of our simulator "KUTTY". (a) The dynamical animation window of our model. (b) The entire map view, used to visualize the changing-flow in the route map. In KUTTY, the high flow regions (low-flow regions) are colored red (blue). This flow dynamically changes with time.

Fig. 17. Comparison plot of the number of passengers between normal operation and operation with an accident at T09. (a)The number of passengers in each line comparing ordinary operation and congested conditions. (b)The number of passengers in each segment of the Ginza Line comparing ordinary operation and congested conditions.

because the Ginza Line intersects with the Tozai Line at T10, and the Hibiya Line intersects with the Tozai Line at T11, both of which are important transfer stations. In contrast, the Hanzomon Line intersects with the Tozai Line at T07, which is not such an important transfer station as T10 and T11. As a result, the passenger flow of the Hanzomon Line is essentially unaffected. Moreover, this result also implies that Otemachi Station is not the destination of most passengers on the Tozai Line, because otherwise the flow rate of the Hanzomon Line would increase (from T10 to Z09 to Z08, and from T07 to Z07 to Z08). Fig. 17 (b) shows the number of passengers on all segments of the Ginza Line. It can be seen that in the area from G05 to G11, the number of passengers increases remarkably. By transferring at these stations, passengers could change to the Marunouchi Line at G09, the Chiyoda Line at G06, and the Namboku Line at G05 and G06. Note that under normal operation, passengers change to the

immediately provide an estimation of the passenger flow pattern required when an accident occurs in the Tokyo Metro Railway Network. Furthermore, we have also presented a homogenization re-scheduling method to alleviate congestion of a crowded train. It is based on the idea that the number of passengers in each train should be homogeneously-distributed.

Cellular Automaton Modeling of Passenger Transport Systems 273

Finally, we hope that this mathematical model and this simulator as an application of the mathematical model can be applied to other transportation systems and help in demonstrating the dynamical patterns and estimating the efficiency, traffic volume, and the

This chapter is owed to colaborated works with my colleagues. I would like to give a huge thanks to Debashish Chowdhury, Andreas Schadschneider, Katsuhiro Nishinari, Rui Jiang, Daichi Yanagisawa, Ryosuke Nishi, Mitsuhito Komatsu, Il Yun Yoo, Makoto Uchida, and Ryo

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We found that our method is more efficient than the conventional approach.

other measurements to optimize their operation.

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Takayama for enjoyable collaborations.

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600-612 (2007).

Scientific).

1404 (1998).

**6. Acknowledgements**

**7. References**

Fig. 18. Comparison plot of the passenger density of train A among the three systems. The congestion rate among the uncontrolled system, ordinary controlled system, and our homogenization system.

Marunouchi Line and to the Chiyoda Line at Station T09 and to the Namboku Line at Station T06.

Next we investigate the effect of our homogenization re-scheduling method. We suppose that the number of passengers waiting at G03 on the Ginza Line increases suddenly at *t* = *t*0, so that the passenger density of the nearest upstream train *A* becomes 1 when it arrives at G03 at *t* = *t*1. We have compared the evolution of the passenger density on train *A* in three systems: the system without re-scheduling, the system with conventional re-scheduling, and the system with homogenization re-scheduling. In Fig. 18, it can be seen that systems with re-scheduling decrease the passenger density of the train when the train is between G13 and G18. Moreover, we have found that our homogenization method is better than the conventional re-scheduling method.

### **5. Concluding discussions**

In this chapter, we have proposed a new mathematical model for passenger transport systems, the so-called *public conveyance model*, built on the stochastic cellular automaton, which is exactly solved in the steady state. First, we defined the jamming state as a mathematical science and introduce the fundamental diagram to discuss the flow of particles. As two examples of analytical rule-based models, ASEP and ZRP, the fundamental diagrams obtained from numerical simulations and analytical calculations have been demonstrated.

As a one-dimensional case of public conveyance model, we investigated the bus route system and its efficiency by introducing three measurements: average velocity, the number of waiting passengers and transportation volume. Moreover, the effectiveness of an information-based control system, in which the number of particles between successive stops is adjusted, was discussed by comparing the case without control and with control in terms of these three measurements. As we found that implementation of the information-based traffic control system does not necessarily always improve the efficiency of the public conveyance system.

As an application of the public conveyance model, we have proposed a network simulator "KUTTY", which is based on the route choice behaviors of passengers. "KUTTY" takes into account the complex topology of the Tokyo Metro Railway Network and the OD demand estimated from the rider-ship data provided by the Tokyo Metro company. "KUTTY" can immediately provide an estimation of the passenger flow pattern required when an accident occurs in the Tokyo Metro Railway Network. Furthermore, we have also presented a homogenization re-scheduling method to alleviate congestion of a crowded train. It is based on the idea that the number of passengers in each train should be homogeneously-distributed. We found that our method is more efficient than the conventional approach.

Finally, we hope that this mathematical model and this simulator as an application of the mathematical model can be applied to other transportation systems and help in demonstrating the dynamical patterns and estimating the efficiency, traffic volume, and the other measurements to optimize their operation.

### **6. Acknowledgements**

This chapter is owed to colaborated works with my colleagues. I would like to give a huge thanks to Debashish Chowdhury, Andreas Schadschneider, Katsuhiro Nishinari, Rui Jiang, Daichi Yanagisawa, Ryosuke Nishi, Mitsuhito Komatsu, Il Yun Yoo, Makoto Uchida, and Ryo Takayama for enjoyable collaborations.

### **7. References**

18 Will-be-set-by-IN-TECH

Fig. 18. Comparison plot of the passenger density of train A among the three systems. The congestion rate among the uncontrolled system, ordinary controlled system, and our

Marunouchi Line and to the Chiyoda Line at Station T09 and to the Namboku Line at Station

Next we investigate the effect of our homogenization re-scheduling method. We suppose that the number of passengers waiting at G03 on the Ginza Line increases suddenly at *t* = *t*0, so that the passenger density of the nearest upstream train *A* becomes 1 when it arrives at G03 at *t* = *t*1. We have compared the evolution of the passenger density on train *A* in three systems: the system without re-scheduling, the system with conventional re-scheduling, and the system with homogenization re-scheduling. In Fig. 18, it can be seen that systems with re-scheduling decrease the passenger density of the train when the train is between G13 and G18. Moreover, we have found that our homogenization method is better than the

In this chapter, we have proposed a new mathematical model for passenger transport systems, the so-called *public conveyance model*, built on the stochastic cellular automaton, which is exactly solved in the steady state. First, we defined the jamming state as a mathematical science and introduce the fundamental diagram to discuss the flow of particles. As two examples of analytical rule-based models, ASEP and ZRP, the fundamental diagrams obtained

As a one-dimensional case of public conveyance model, we investigated the bus route system and its efficiency by introducing three measurements: average velocity, the number of waiting passengers and transportation volume. Moreover, the effectiveness of an information-based control system, in which the number of particles between successive stops is adjusted, was discussed by comparing the case without control and with control in terms of these three measurements. As we found that implementation of the information-based traffic control system does not necessarily always improve the efficiency of the public conveyance system. As an application of the public conveyance model, we have proposed a network simulator "KUTTY", which is based on the route choice behaviors of passengers. "KUTTY" takes into account the complex topology of the Tokyo Metro Railway Network and the OD demand estimated from the rider-ship data provided by the Tokyo Metro company. "KUTTY" can

from numerical simulations and analytical calculations have been demonstrated.

homogenization system.

conventional re-scheduling method.

**5. Concluding discussions**

T06.


**11** 

Sebastiaan Meijer

*1The Netherlands* 

*2Sweden* 

*1Delft University of Technology* 

*2Royal Institute of Technology, Stockholm* 

**Gaming Simulations for Railways:** 

**Lessons Learned from Modeling Six Games** 

The Dutch railway system is a highly complex and heavily utilized network (Goverde, 2005; CBS, 2009). Worldwide it is one of the most densely driven networks, yet its capacity has to increase further. Improvements in the domain of capacity management and traffic control are increasingly difficult to implement because of the large interconnectedness of all processes. The de-bundling of rail infra management (ProRail) and train services (predominantly NS, and some smaller regional lines by Syntus, Veolia, Arriva a.o. plus freight train operators) has created an operational process in which multiple offices and

ProRail, the Dutch railway infrastructure manager, has stated a goal to increase the capacity by 50% as a challenge till the year 2020. This cannot be done the 'old way' through increased amounts of physical infrastructure, as both money and geographical space are insufficient. Furthermore, the complexity and interconnectedness of the network is yet at such a level that more of this will lead to less resilience and becoming (even more) prone to disturbances. Because of the 50% growth challenge till the year 2020, new and smarter ways of managing capacity and traffic are key for the success of the Dutch rail infrastructure for society. The ProRail organization has taken up gaming simulation as a key method to

Unique for gaming simulation is the highly detailed simulation of both technical and process variables of rail infrastructures and the decision and communication function of real people in their real roles. The method does not assume models of decision-making but draws upon the real-world knowledge of professionals in the operation. Over the course of the projects that ran in 2009, 2010 and 2011, the specific setting of the ProRail organization proved to be both a complex and fruitful environment for gaming simulation. The complexity was found in the large number of stakeholders both in and outside the organization and in the interconnectedness of every aspect of train traffic control on the

platform/line operations need to synchronize to control the daily train flow.

improve the innovation process (Meijer, forthcoming).

performance of passenger and freight train service providers.

**1. Introduction** 

**for the Dutch Infrastructure Management** 


## **Gaming Simulations for Railways: Lessons Learned from Modeling Six Games for the Dutch Infrastructure Management**

Sebastiaan Meijer

*1Delft University of Technology 2Royal Institute of Technology, Stockholm 1The Netherlands 2Sweden* 

### **1. Introduction**

20 Will-be-set-by-IN-TECH

274 Infrastructure Design, Signalling and Security in Railway

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(2008) 549.

(2007) 659.

The Dutch railway system is a highly complex and heavily utilized network (Goverde, 2005; CBS, 2009). Worldwide it is one of the most densely driven networks, yet its capacity has to increase further. Improvements in the domain of capacity management and traffic control are increasingly difficult to implement because of the large interconnectedness of all processes. The de-bundling of rail infra management (ProRail) and train services (predominantly NS, and some smaller regional lines by Syntus, Veolia, Arriva a.o. plus freight train operators) has created an operational process in which multiple offices and platform/line operations need to synchronize to control the daily train flow.

ProRail, the Dutch railway infrastructure manager, has stated a goal to increase the capacity by 50% as a challenge till the year 2020. This cannot be done the 'old way' through increased amounts of physical infrastructure, as both money and geographical space are insufficient. Furthermore, the complexity and interconnectedness of the network is yet at such a level that more of this will lead to less resilience and becoming (even more) prone to disturbances. Because of the 50% growth challenge till the year 2020, new and smarter ways of managing capacity and traffic are key for the success of the Dutch rail infrastructure for society. The ProRail organization has taken up gaming simulation as a key method to improve the innovation process (Meijer, forthcoming).

Unique for gaming simulation is the highly detailed simulation of both technical and process variables of rail infrastructures and the decision and communication function of real people in their real roles. The method does not assume models of decision-making but draws upon the real-world knowledge of professionals in the operation. Over the course of the projects that ran in 2009, 2010 and 2011, the specific setting of the ProRail organization proved to be both a complex and fruitful environment for gaming simulation. The complexity was found in the large number of stakeholders both in and outside the organization and in the interconnectedness of every aspect of train traffic control on the performance of passenger and freight train service providers.

Gaming Simulations for Railways:

**2.2 Capacity increases** 

simultaneously and flexibly and is not resilient.

schedule is High Frequency Train Transport.

**3. Gaming simulation for process innovations** 

general the terms depend on the intended use of the method.

future games that incorporate automated agents.

Lessons Learned from Modeling Six Games for the Dutch Infrastructure Management 277

(2006), railways, from their assessment of safety operations at the Dutch Railways, would seem to be examples of poor, or at best mixed, resilience, which can, however, still achieve high levels of safety, at least in certain areas of their operations. Hence safety is achieved by sacrificing goals, traffic volume and punctuality. The system does not achieve all its goals

The Dutch railway sector will face a massive growth of transport demand in the forthcoming decade. This growth is both expected in passenger and in freight transport. Currently, the Dutch railway network is one of the most densely used networks in the world, approaching its maximum capacity given the current infrastructure and control mechanisms. The projected increase in demand requires a step-change in both the physical and control aspects of the railways. ProRail formulated an ambitious program, called 'Room on the Railways" (Ruimte op de Rails, in Dutch) to increase the number of trains on the network by 50% before the year 2020. One of the major components of this program is the plan for high-frequency passenger trains on the major corridors. Currently there are (on average) 4 intercity, 2 to 4 local and 1 or 2 freight trains per hour on the major corridors. This should increase to 6 intercity, 6 local and 2 freight trains before 2013. This new frequency of trains is often called 'untimetabled travelling" as the passenger can just go to a station without checking departure times: the next train will be there soon. The official title of the

The projected increase of capacity cannot be achieved by building new infrastructure alone: the costs for the complete program would be around 9 billion euro, and the time for procedures and construction would frustrate the transport demand for years. ProRail has taken up the challenge to achieve the goals with only half of this budget by combining

Gaming simulation, here defined as 'simulating a system through gaming methods' is one of the terms in a loosely demarcated field of interactive participatory activities, aiming to involve participants, who may be the real stakeholders, in an activity. Other terms used are simulation game, policy exercise and serious gaming. The word gaming will be used here as the short term for gaming simulation. Different authors have different preferences, but in in

Game theory and gaming simulation are often intertwined. Game theory is the mathematical approach of analyzing calculated circumstances where a person's success is based upon the choices of others. In games, these situations often occur, and therefore is game theory a popular method of modeling artificial intelligence in games. This chapter does not use game theory per se, however a more prominent and explicit use is foreseen in

Given the number of gaming titles and scientific publications, the use of gaming methods for learning is the most popular by far, typically occupying 'serious gaming' and 'simulation game' for usually computer-supported games that place the player in a simulated world

strategic choices for new infrastructure with new control and management solutions.

In the year 2009, the gaming group of Delft University of Technology was asked to facilitate three projects using gaming simulation methodology. These projects ran so successful that the organization asked the Delft researchers to identify where in the organization large-scale implementation of gaming simulation methodology would be most promising. Based upon a series of interviews through the organization, ProRail and TU Delft jointly formulated a four-year research and implementation proposal that is now in operation. The first gaming sessions in this new collaboration have been held and results have led to methodological lessons-learned on how to model. This chapter reports on three modeling issues crucial to gaming simulation for railway and similar systems. How to abstract from the nitty-gritty details while keeping the simulation real and valid enough for real-world operators to participate and do their job is the focus of this chapter.

### **2. Problem description**

Innovation in the Dutch railways is on one hand much needed, while on the other hand very complex to achieve. The 1995 politically instigated de-bundling of rail infra management (ProRail) and train services (predominantly NS, and some smaller regional lines by Syntens, Veolia, a.o.) has created an operational process in which multiple offices and platform/line operations need to synchronize to control the daily train flow. The increasing importance of rail services for individual provinces in the Netherlands has led to multi-party tendering (Van de Velde et al, 2008). In this complex multi-actor and multi-level environment the strategic safeguarding of public values in managing operations proofs often impossible (Steenhuisen et al, 2009). The combination of these events and trends leads to a challenge to innovate on two aspects, being quality in operations and ways to increase the capacity.

### **2.1 Quality in operations – Robustness and resilience**

Over the past decade, the railways in The Netherlands have received major criticism for the quality of its operations. From a policy perspective this has led to performance contracts for both the main train service operator (NS) and the publicly owned infrastructure manager ProRail (Van de Velde et al, 2009). Over the past decade the performance has seen improvements on the critical performance indicators, but still it is not regarded to be a high quality service due to many small delays, overly crowded trains and non- or mal-informed passengers. The rail system often suffers from small defects, leading to bigger delays when the problems spread like an oil spill over the regions and lines. If we define robustness as the degree to which a system is capable to withstand problems within the limits of the designed system, then the robustness of the railways is questionable.

A lower score on robustness would not have been so detrimental is the railways were more resilient. Hollnagel et al (2006) define resilience as the ability of a system or an organization to react to and recover from disturbances at an early stage, with minimal effect on the dynamic stability. The challenges to system safety come from instability, and resilience engineering is an expression of the methods and principles that prevent this from taking place. Furthermore the recent years have shown that snow, storms, national festivities and other outliers in the situation for which the system is not specifically designed cause total or at best partial collapse of the national system, as soon as small problems start to occur. This has led to Parliamentary Investigation (Rekenkamer, 2011). According to Hale and Heijer (2006), railways, from their assessment of safety operations at the Dutch Railways, would seem to be examples of poor, or at best mixed, resilience, which can, however, still achieve high levels of safety, at least in certain areas of their operations. Hence safety is achieved by sacrificing goals, traffic volume and punctuality. The system does not achieve all its goals simultaneously and flexibly and is not resilient.

### **2.2 Capacity increases**

276 Infrastructure Design, Signalling and Security in Railway

In the year 2009, the gaming group of Delft University of Technology was asked to facilitate three projects using gaming simulation methodology. These projects ran so successful that the organization asked the Delft researchers to identify where in the organization large-scale implementation of gaming simulation methodology would be most promising. Based upon a series of interviews through the organization, ProRail and TU Delft jointly formulated a four-year research and implementation proposal that is now in operation. The first gaming sessions in this new collaboration have been held and results have led to methodological lessons-learned on how to model. This chapter reports on three modeling issues crucial to gaming simulation for railway and similar systems. How to abstract from the nitty-gritty details while keeping the simulation real and valid enough for real-world operators to

Innovation in the Dutch railways is on one hand much needed, while on the other hand very complex to achieve. The 1995 politically instigated de-bundling of rail infra management (ProRail) and train services (predominantly NS, and some smaller regional lines by Syntens, Veolia, a.o.) has created an operational process in which multiple offices and platform/line operations need to synchronize to control the daily train flow. The increasing importance of rail services for individual provinces in the Netherlands has led to multi-party tendering (Van de Velde et al, 2008). In this complex multi-actor and multi-level environment the strategic safeguarding of public values in managing operations proofs often impossible (Steenhuisen et al, 2009). The combination of these events and trends leads to a challenge to innovate on two

Over the past decade, the railways in The Netherlands have received major criticism for the quality of its operations. From a policy perspective this has led to performance contracts for both the main train service operator (NS) and the publicly owned infrastructure manager ProRail (Van de Velde et al, 2009). Over the past decade the performance has seen improvements on the critical performance indicators, but still it is not regarded to be a high quality service due to many small delays, overly crowded trains and non- or mal-informed passengers. The rail system often suffers from small defects, leading to bigger delays when the problems spread like an oil spill over the regions and lines. If we define robustness as the degree to which a system is capable to withstand problems within the limits of the

A lower score on robustness would not have been so detrimental is the railways were more resilient. Hollnagel et al (2006) define resilience as the ability of a system or an organization to react to and recover from disturbances at an early stage, with minimal effect on the dynamic stability. The challenges to system safety come from instability, and resilience engineering is an expression of the methods and principles that prevent this from taking place. Furthermore the recent years have shown that snow, storms, national festivities and other outliers in the situation for which the system is not specifically designed cause total or at best partial collapse of the national system, as soon as small problems start to occur. This has led to Parliamentary Investigation (Rekenkamer, 2011). According to Hale and Heijer

participate and do their job is the focus of this chapter.

aspects, being quality in operations and ways to increase the capacity.

designed system, then the robustness of the railways is questionable.

**2.1 Quality in operations – Robustness and resilience** 

**2. Problem description** 

The Dutch railway sector will face a massive growth of transport demand in the forthcoming decade. This growth is both expected in passenger and in freight transport. Currently, the Dutch railway network is one of the most densely used networks in the world, approaching its maximum capacity given the current infrastructure and control mechanisms. The projected increase in demand requires a step-change in both the physical and control aspects of the railways. ProRail formulated an ambitious program, called 'Room on the Railways" (Ruimte op de Rails, in Dutch) to increase the number of trains on the network by 50% before the year 2020. One of the major components of this program is the plan for high-frequency passenger trains on the major corridors. Currently there are (on average) 4 intercity, 2 to 4 local and 1 or 2 freight trains per hour on the major corridors. This should increase to 6 intercity, 6 local and 2 freight trains before 2013. This new frequency of trains is often called 'untimetabled travelling" as the passenger can just go to a station without checking departure times: the next train will be there soon. The official title of the schedule is High Frequency Train Transport.

The projected increase of capacity cannot be achieved by building new infrastructure alone: the costs for the complete program would be around 9 billion euro, and the time for procedures and construction would frustrate the transport demand for years. ProRail has taken up the challenge to achieve the goals with only half of this budget by combining strategic choices for new infrastructure with new control and management solutions.

### **3. Gaming simulation for process innovations**

Gaming simulation, here defined as 'simulating a system through gaming methods' is one of the terms in a loosely demarcated field of interactive participatory activities, aiming to involve participants, who may be the real stakeholders, in an activity. Other terms used are simulation game, policy exercise and serious gaming. The word gaming will be used here as the short term for gaming simulation. Different authors have different preferences, but in in general the terms depend on the intended use of the method.

Game theory and gaming simulation are often intertwined. Game theory is the mathematical approach of analyzing calculated circumstances where a person's success is based upon the choices of others. In games, these situations often occur, and therefore is game theory a popular method of modeling artificial intelligence in games. This chapter does not use game theory per se, however a more prominent and explicit use is foreseen in future games that incorporate automated agents.

Given the number of gaming titles and scientific publications, the use of gaming methods for learning is the most popular by far, typically occupying 'serious gaming' and 'simulation game' for usually computer-supported games that place the player in a simulated world

Gaming Simulations for Railways:

Lessons Learned from Modeling Six Games for the Dutch Infrastructure Management 279

second issue, especially with the more policy-oriented approaches and the popularity for learning in higher education is the focus on participants with a relatively large capability in thinking abstract, as policy makers and students tend to have more of this skill than the average operator. Peters et al (1998) describe the process from real world to simulated game world as a process of abstraction and reduction. The big question is how far can you abstract

The operational skill training is recently getting more and more addressed in the gaming literature. Druckman (1994) proved already the need for more 'fidelity' (that could be translated as 'detailed realism') when training less abstract skills. Applications for operational skill training is getting common in the domains of image-based medical procedures (like laparoscopy, gastrointestinal flexible endoscopy, image-guided neurosurgery, and endovascular surgery) (Gaba, 2001; Botden et al, 2008; Hamdorf and Hall, 2000), aviation (Proctor et al, 2007), and safety training for dike inspection (Harteveld, 2011) and the oil and gas industry (Meijer and Poelman, 2011). Each of these domains finds a solution in 3D-based computer games that model an environment, either geographical or the organs in a body, through which the player has to navigate and perform a coherent set of actions. There is an

Involving operators in games for policymaking or for testing hypotheses is almost undocumented, with some notable exceptions like the work at CIRAD and Cemagref (Barreteau, 2003). Traditionally the questions in policymaking and the hypotheses tested are at a higher level of abstraction. In Meijer (2009), the author argued that involving the real operators in a gaming simulation has the benefit of avoiding models and assumptions about their behavior, and thus can increase the validity of the behavior of the entire socio-technical system simulated. This has been proven in the domain of supply chain management

In our work we focus on the behavior of the people in the daily operations in railway systems, with a focal point at the train traffic controllers. Within the scope of the infrastructure management ProRail, their behavior has the most direct influence on the robustness and resilience of the network. To base decisions upon their behavior in gaming

The most common critique for behavior observed in a session is "it is only a game.....". In the literal meaning the statement is true. A gaming simulation is a model of reality, and the roles, rules, objectives and constraints are necessarily different from the real world. The insinuation of the statement is, however, that behavior observed in a session is unlike behavior in the real world and is no valid representation of real-world behavior. Peters et al (1998) discuss the validity of games (gaming simulation) based upon the work of Raser (1969) who defined validity of models in the following way: "A model can be said to be valid to the extent that investigation of that model provides the same outcomes as would investigation in the reference system." Raser (1969) suggests four aspects of validity that

Psychological reality: To what degree does the gaming simulation provide an

 Structural validity: To what degree is the structure of the gaming simulation (the theory and assumptions on which it is built) isomorphic to that of the reference system?

and reduce from reality before operators loose their grip on the simulated reality?

overlap between the fields of virtual reality, simulation and gaming here.

research, studying the organization of transactions.

apply to gaming simulation:

simulations it is essential to consider the validity of this behavior.

environment that seems realistic to the participants?

(Bekebrede and Mayer, 2005; De Freitas and Martin, 2006; Kriz and Hense, 2003). Learning about innovation in games is a popular topic for MBA-style versions, typically related to markets and supply chains (Meijer et al, 2006; Meijer, 2009). Learning and communicating complex issues are in this stream highly related. An important aspect for ProRail is the opportunity to communicate ideas. While a slideshow can communicate a message, a gaming simulation enables you to experience it for yourself (Bekebrede, 2010). The aspects about which it is sometimes difficult to communicate at present include: the impact of new timetables (on all categories of employees), the need for precision in carrying out tasks (employees), the influence of disruptions on the network as a whole (general public) and to experience the key aspects of traffic control / capacity management (general public). At present, visualizations of train flow models such as FRISO and SIMONE (Middelkoop and Loeve, 2006) are available, but it is not possible to experience these aspects by sitting at the controls. The opportunity for communication gives employees the chance to play a role that they do not have in reality. This can help clarify different points of view.

In the world of policymaking, there is half a century of history in using gaming as an intervention to bring together policy makers and other stakeholders in participatory events. Games provide a way to collectively decide firstly on the system boundaries and secondly on the dynamics of the system that will be played. Then, policies can be formulated in this simulated environment (Duke, 1974; Duke and Geurts, 2004; Mayer, 2010). This approach relies on Duke and Geurts' (2004) 5-C's of gaming simulation for improving policy making, namely by understanding the Complexity, enhancing Creativity, enabling Communication, reaching Consensus and Commitment to action. Within ProRail this role of gaming simulation is particularly relevant for management questions.

Increasingly popular is the possibility to try out the effect of policies on a simulated system, and see whether innovation in roles, rules, objectives and constraints can be made. This approach, although very relevant for policy-making, is actually a third use of gaming, for testing hypotheses (Peters et al, 1998). This application is less common and puts great emphasis on the verification and validation of the gaming simulation (Klabbers, 2003, 2006; Noy et al, 2006; Meijer, 2009). For innovation at ProRail, this use is at the core of the reasoning behind choosing gaming simulation as a new method in reducing uncertainty in more complex, system level changes.

A fourth use that is emerging is linked to the gamification of society (Hiltbrand and Burke, 2011). Innovation can take place through game play if the incentives are such that the crowd can generate and implement their ideas in a system. Few scientific literature on this exists as of yet, but examples are UK innovation in pensions (Gartner, 2011), crowd sourcing of ideas in an insurance company (Bekebrede and Meijer, Forthcoming)

### **4. Modeling challenges in gaming simulation for railways**

In the world of gaming simulation several design guides and principles exist on how to capture real world problems in a gaming simulation. In the field of policy making the most important method is the one that Duke and Geurts (2004) describe, where for learning, sensemaking and related issues the more recent work of Harteveld (2011) is gaining footage among some others. However, the problem is that these methods are so generic that the specific issues for technical domains like the railways have to be addressed specifically for that domain. A

(Bekebrede and Mayer, 2005; De Freitas and Martin, 2006; Kriz and Hense, 2003). Learning about innovation in games is a popular topic for MBA-style versions, typically related to markets and supply chains (Meijer et al, 2006; Meijer, 2009). Learning and communicating complex issues are in this stream highly related. An important aspect for ProRail is the opportunity to communicate ideas. While a slideshow can communicate a message, a gaming simulation enables you to experience it for yourself (Bekebrede, 2010). The aspects about which it is sometimes difficult to communicate at present include: the impact of new timetables (on all categories of employees), the need for precision in carrying out tasks (employees), the influence of disruptions on the network as a whole (general public) and to experience the key aspects of traffic control / capacity management (general public). At present, visualizations of train flow models such as FRISO and SIMONE (Middelkoop and Loeve, 2006) are available, but it is not possible to experience these aspects by sitting at the controls. The opportunity for communication gives employees the chance to play a role that

In the world of policymaking, there is half a century of history in using gaming as an intervention to bring together policy makers and other stakeholders in participatory events. Games provide a way to collectively decide firstly on the system boundaries and secondly on the dynamics of the system that will be played. Then, policies can be formulated in this simulated environment (Duke, 1974; Duke and Geurts, 2004; Mayer, 2010). This approach relies on Duke and Geurts' (2004) 5-C's of gaming simulation for improving policy making, namely by understanding the Complexity, enhancing Creativity, enabling Communication, reaching Consensus and Commitment to action. Within ProRail this role of gaming

Increasingly popular is the possibility to try out the effect of policies on a simulated system, and see whether innovation in roles, rules, objectives and constraints can be made. This approach, although very relevant for policy-making, is actually a third use of gaming, for testing hypotheses (Peters et al, 1998). This application is less common and puts great emphasis on the verification and validation of the gaming simulation (Klabbers, 2003, 2006; Noy et al, 2006; Meijer, 2009). For innovation at ProRail, this use is at the core of the reasoning behind choosing gaming simulation as a new method in reducing uncertainty in

A fourth use that is emerging is linked to the gamification of society (Hiltbrand and Burke, 2011). Innovation can take place through game play if the incentives are such that the crowd can generate and implement their ideas in a system. Few scientific literature on this exists as of yet, but examples are UK innovation in pensions (Gartner, 2011), crowd sourcing of ideas

In the world of gaming simulation several design guides and principles exist on how to capture real world problems in a gaming simulation. In the field of policy making the most important method is the one that Duke and Geurts (2004) describe, where for learning, sensemaking and related issues the more recent work of Harteveld (2011) is gaining footage among some others. However, the problem is that these methods are so generic that the specific issues for technical domains like the railways have to be addressed specifically for that domain. A

they do not have in reality. This can help clarify different points of view.

simulation is particularly relevant for management questions.

in an insurance company (Bekebrede and Meijer, Forthcoming)

**4. Modeling challenges in gaming simulation for railways** 

more complex, system level changes.

second issue, especially with the more policy-oriented approaches and the popularity for learning in higher education is the focus on participants with a relatively large capability in thinking abstract, as policy makers and students tend to have more of this skill than the average operator. Peters et al (1998) describe the process from real world to simulated game world as a process of abstraction and reduction. The big question is how far can you abstract and reduce from reality before operators loose their grip on the simulated reality?

The operational skill training is recently getting more and more addressed in the gaming literature. Druckman (1994) proved already the need for more 'fidelity' (that could be translated as 'detailed realism') when training less abstract skills. Applications for operational skill training is getting common in the domains of image-based medical procedures (like laparoscopy, gastrointestinal flexible endoscopy, image-guided neurosurgery, and endovascular surgery) (Gaba, 2001; Botden et al, 2008; Hamdorf and Hall, 2000), aviation (Proctor et al, 2007), and safety training for dike inspection (Harteveld, 2011) and the oil and gas industry (Meijer and Poelman, 2011). Each of these domains finds a solution in 3D-based computer games that model an environment, either geographical or the organs in a body, through which the player has to navigate and perform a coherent set of actions. There is an overlap between the fields of virtual reality, simulation and gaming here.

Involving operators in games for policymaking or for testing hypotheses is almost undocumented, with some notable exceptions like the work at CIRAD and Cemagref (Barreteau, 2003). Traditionally the questions in policymaking and the hypotheses tested are at a higher level of abstraction. In Meijer (2009), the author argued that involving the real operators in a gaming simulation has the benefit of avoiding models and assumptions about their behavior, and thus can increase the validity of the behavior of the entire socio-technical system simulated. This has been proven in the domain of supply chain management research, studying the organization of transactions.

In our work we focus on the behavior of the people in the daily operations in railway systems, with a focal point at the train traffic controllers. Within the scope of the infrastructure management ProRail, their behavior has the most direct influence on the robustness and resilience of the network. To base decisions upon their behavior in gaming simulations it is essential to consider the validity of this behavior.

The most common critique for behavior observed in a session is "it is only a game.....". In the literal meaning the statement is true. A gaming simulation is a model of reality, and the roles, rules, objectives and constraints are necessarily different from the real world. The insinuation of the statement is, however, that behavior observed in a session is unlike behavior in the real world and is no valid representation of real-world behavior. Peters et al (1998) discuss the validity of games (gaming simulation) based upon the work of Raser (1969) who defined validity of models in the following way: "A model can be said to be valid to the extent that investigation of that model provides the same outcomes as would investigation in the reference system." Raser (1969) suggests four aspects of validity that apply to gaming simulation:


Gaming Simulations for Railways:

dispatching at the operational level.

**5.1 Rail cargo market game (RCM)** 

(2009).

cases and the intermezzo phase are described.

session including a small number of network controllers.

Lessons Learned from Modeling Six Games for the Dutch Infrastructure Management 281

As of 2011, the gaming collaboration resulted in six different gaming simulations, specifically built for innovation projects within ProRail. Each of these projects used gaming simulation to investigate various solution strategies with the aim of increasing capacity utilization, resilience and robustness on the rail network. The initial pilot project covered

From the launch of the initial project, ProRail formulated three preliminary cases to study using gaming simulation. TU Delft was to developed unique approaches for each of these cases, after which the initial success of gaming simulation for the Dutch Railways would be re-evaluated. The cases differed in nature. The first was about the potential value of market mechanisms for management of demand of cargo capacity. This game could be seen as a management game on the tactical level. The second case was about studying a control concept for high-frequency train transport at the Bijlmer junction. This game was at the operational level of train dispatching and network control. The third case was about the opening regimes of the bridge over the river Vecht. This game was purely about train

During the course of these three cases, the success became very apparent to the senior management involved at ProRail. This led to an Intermezzo phase after the third game to reflect upon the results so far and to identify the value from interviews with ProRail internal stakeholder held by Delft researchers. The launch of a large four-year project was marked by a kick-off case that convinced the last skeptics. In the following sub-sections each of the

The first and kick-off subproject called Goederenmarktplaats (Freight Market) introduced ProRail to a paper-based and partly computer-supported game with a high degree of abstraction. This game type was referred to as a management game, due to the focus on more abstract policy-related aspects. Most of the participants were managers, with one

Table 1 lists the core description of this game, more information can be found in Meijer et al

The game sessions delivered results timely, and in a positive and active manner. This game is still referred to two years later in the organization. Important to note for the introduction of gaming is that this project happened to have many people on board in senior staff functions from two different divisions (Traffic Control and Capacity Management) who appeared to be key people in later problems that called for gaming simulation methodology.

The research team then conducted interviews within ProRail to evaluate the pilot project and identify the opportunities it presented. In these interviews, the management game was repeatedly described positively. However, this generated few new ideas as regards applicability. Many of the issues encountered within the ProRail organization are

The foundation in terms of exposure to key personnel therefore couldn't be better.

operational and thus call for less abstract forms of gaming simulation.

**5. Modeling gaming simulations for rail innovation projects** 

three projects while the long-term collaboration yielded three so far.


The psychological reality demands that sessions are conducted in such a way that participants are emotionally involved and really play their role. The situation of the session in the life of the participants, the consequences of participation or non-participation and the location and atmosphere of a session and its moderation are important factors. This requires craftsmanship of the game leader that is hard to operationalize in a scientific context. Various authors have made attempts at determining the quality of conducting sessions. Kriz and Hense (2006) offer an elaborate and theory-based evaluation methodology, that according to Klabbers (2008) does a good job in (temporarily) bridging the gap between analytical and design sciences. Kriz and Hense's approach is an adapted version of the theory-based evaluation method by Reynolds (1998). They distinguish between concept, design and application that can be evaluated.

The psychological reality and process and structural validity of Raser (1969) come together in the concept of situation awareness (Endsley, 2004) for operators. Operators should get involved psychologically when they can recognize sufficient components of the processes and structures they are used to in their real work. In the medical world this has led to consensus guidelines for validation of virtual reality surgical simulators (Carter et al, 2005), but in railways this work is only done for train drivers (Hamilton and Clarke, 2005)

When we take the concept of situation awareness as the central concept for considering the validity of railway operator behavior in gaming simulations, the list of items in the situation awareness still becomes vast. The modeling issue could include nearly any technical aspect of the railways, interface and representation items as well as the cognitive state of operators during their normal workdays. This chapter focuses on three important issues, posed as how-to questions:

1. How to immerse train traffic controllers in a gaming simulation?

Immersion is one of the important indicators of presence and therefore psychological reality in simulated environments (Witmer and Singer, 1998). Therefore an indication of how to model a game so that railway operators get immersed in a first important step towards validity.


These questions will be answered in the remainder of this chapter. The next section discusses six projects from which the experiences are gained, then Section 6 translates this into lessons learned.

### **5. Modeling gaming simulations for rail innovation projects**

As of 2011, the gaming collaboration resulted in six different gaming simulations, specifically built for innovation projects within ProRail. Each of these projects used gaming simulation to investigate various solution strategies with the aim of increasing capacity utilization, resilience and robustness on the rail network. The initial pilot project covered three projects while the long-term collaboration yielded three so far.

From the launch of the initial project, ProRail formulated three preliminary cases to study using gaming simulation. TU Delft was to developed unique approaches for each of these cases, after which the initial success of gaming simulation for the Dutch Railways would be re-evaluated. The cases differed in nature. The first was about the potential value of market mechanisms for management of demand of cargo capacity. This game could be seen as a management game on the tactical level. The second case was about studying a control concept for high-frequency train transport at the Bijlmer junction. This game was at the operational level of train dispatching and network control. The third case was about the opening regimes of the bridge over the river Vecht. This game was purely about train dispatching at the operational level.

During the course of these three cases, the success became very apparent to the senior management involved at ProRail. This led to an Intermezzo phase after the third game to reflect upon the results so far and to identify the value from interviews with ProRail internal stakeholder held by Delft researchers. The launch of a large four-year project was marked by a kick-off case that convinced the last skeptics. In the following sub-sections each of the cases and the intermezzo phase are described.

### **5.1 Rail cargo market game (RCM)**

280 Infrastructure Design, Signalling and Security in Railway

Process validity: To what degree are the processes observed in the gaming simulation

Predictive validity: To what degree can the gaming simulation produce outcomes of the

The psychological reality demands that sessions are conducted in such a way that participants are emotionally involved and really play their role. The situation of the session in the life of the participants, the consequences of participation or non-participation and the location and atmosphere of a session and its moderation are important factors. This requires craftsmanship of the game leader that is hard to operationalize in a scientific context. Various authors have made attempts at determining the quality of conducting sessions. Kriz and Hense (2006) offer an elaborate and theory-based evaluation methodology, that according to Klabbers (2008) does a good job in (temporarily) bridging the gap between analytical and design sciences. Kriz and Hense's approach is an adapted version of the theory-based evaluation method by Reynolds (1998). They distinguish between concept, design and application that can be evaluated.

The psychological reality and process and structural validity of Raser (1969) come together in the concept of situation awareness (Endsley, 2004) for operators. Operators should get involved psychologically when they can recognize sufficient components of the processes and structures they are used to in their real work. In the medical world this has led to consensus guidelines for validation of virtual reality surgical simulators (Carter et al, 2005),

When we take the concept of situation awareness as the central concept for considering the validity of railway operator behavior in gaming simulations, the list of items in the situation awareness still becomes vast. The modeling issue could include nearly any technical aspect of the railways, interface and representation items as well as the cognitive state of operators during their normal workdays. This chapter focuses on three important issues, posed as

Immersion is one of the important indicators of presence and therefore psychological reality in simulated environments (Witmer and Singer, 1998). Therefore an indication of how to model a game so that railway operators get immersed in a first important step

Where real-world train flow is a continuous time process, this does not necessarily translate one-to-one to a gaming simulation, as the research question may ask for another solution than continuous, like step-wise, round-based, or asynchronous time.

In the real operations the data flow to operators is bundled in machine interfaces or is fairly constant as time tables typically change only once a year, and infrastructure doesn't change fast either. In a game the standard tools may not be available and timetables and infrastructure may be new to the participants. How to present the

These questions will be answered in the remainder of this chapter. The next section discusses six projects from which the experiences are gained, then Section 6 translates this

but in railways this work is only done for train drivers (Hamilton and Clarke, 2005)

1. How to immerse train traffic controllers in a gaming simulation?

isomorphic to those observed in the reference system?

historical or future reference system?

how-to questions:

towards validity. 2. How to model time?

into lessons learned.

3. How to present operational data?

information so that operators can still use it?

The first and kick-off subproject called Goederenmarktplaats (Freight Market) introduced ProRail to a paper-based and partly computer-supported game with a high degree of abstraction. This game type was referred to as a management game, due to the focus on more abstract policy-related aspects. Most of the participants were managers, with one session including a small number of network controllers.

Table 1 lists the core description of this game, more information can be found in Meijer et al (2009).

The game sessions delivered results timely, and in a positive and active manner. This game is still referred to two years later in the organization. Important to note for the introduction of gaming is that this project happened to have many people on board in senior staff functions from two different divisions (Traffic Control and Capacity Management) who appeared to be key people in later problems that called for gaming simulation methodology. The foundation in terms of exposure to key personnel therefore couldn't be better.

The research team then conducted interviews within ProRail to evaluate the pilot project and identify the opportunities it presented. In these interviews, the management game was repeatedly described positively. However, this generated few new ideas as regards applicability. Many of the issues encountered within the ProRail organization are operational and thus call for less abstract forms of gaming simulation.

Gaming Simulations for Railways:

Core aspect Description

Time model Continuous
