**A Simulation and Evaluation System Oriented to the Emergency Response Effectiveness of the Abrupt Earthquake Disaster**

Yan-Yan Huang

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Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/59422

## **1. Introduction**

The untraditional emergency disasters, like the 2008 Sichuan earthquake of China, break out with nothing indication, no time to prepare for. These emergency events always bring us the catastrophe with much casualty, homeless and immeasurable economic losses.

The emergency disasters response problem is an important thing to be researched all over the world. As we all know that we can not change the breaking out of the untraditional emergency event in present technology level, but it never means that we could do nothing, on the contrary, if we have enough response plans or preparedness, the disasters should be reduced to the minimum level. It requires us to prepare many valid emergency response plans by hands. However, how to get such valid emergency response plans?

Considering the emergency catastrophe like earthquake takes place so abruptly, it is difficult to make decisions to get the most suitable preparedness plan from many emergency response plans. In order to improve the emergency response capability for the abrupt earthquake disasters, it is necessary to build a decision-making support system to evaluate the response plans and to select a most suitable preparedness plans.

In fact, it is difficult to test and evaluate the response plans in the real conditions of a strong earthquake disaster. As far as we know, modeling and simulation methods are fit for evalu‐ ating the preparedness plans. Adopting the modeling and simulation methods, there are many advantages such as low cost, safety research, time-space easily convert, and so on.

Many emergency researches, authors in reference [1-3], show that the more preparedness for the emergency event, the less risk we suffer from the uncertainty emergency. As we all know

that, the emergency plans are oriented to the future event, we have none of the real data and sense. So the modeling and simulation methods are utilized to the decision-make support system.

More researches have discussion about the modeling and simulation method in the emergency response management [4]. At the mean time, Many researcher and experts have noticed the importance of the simulation and evaluation method in the decision-making support system [5,6]. The emergency response needs the decision making support system [7,8].

In China, there are many learners to carry out their researches on the emergency response management, Professor Wang [9] puts forth the parallel simulation method to research the emergency management. Fan Weicheng [10] points to the public incidents, provides some useful suggestion and response methods for the emergency platform system.

In this chapter, we set the research object orient to the emergency earthquake disasters. Design a decision-making support system framework for the emergency response management, and then mainly research the simulation and evaluation methods and their application in the earthquake disasters.

## **2. Systematic frameworks for simulating and evaluating the emergency preparedness for earthquake**

Judging and analyzing the advantage and disadvantages of an emergency response plan needs a good decision making support system. To build up such a decision making system, a serial of technical methods and theory models are required to support the system. In this chapter, the author sums up the research methods for the emergency response plans, and put forth a whole research route map to design and develop the system. Such a research route map is a set of systematic framework which can simulate and evaluate the response plans for the untraditional emergency disaster like earthquake, seeing the Figure 1.

In Figure 1, there are 5 main parts (subsystems) in the set of systematic framework. These subsystems are built to support the whole decision framework. They are including: (A) emergency response effectiveness concept and the evaluation indices, (B) indices weights acquisition,(C)emergency response simulation theory based on OODA-DEVS, (D) simulation system and simulation data acquirement,(E) the integrated evaluation process and decision making support system.

The next research is to describe the related subsystems in the Figure 1. The following research will take emphasis on the main techniques of the simulation and evaluation in emergency response plans.

**Figure 1.** Systematic framework to simulate and evaluate the abrupt earthquake disaster

that, the emergency plans are oriented to the future event, we have none of the real data and sense. So the modeling and simulation methods are utilized to the decision-make support

More researches have discussion about the modeling and simulation method in the emergency response management [4]. At the mean time, Many researcher and experts have noticed the importance of the simulation and evaluation method in the decision-making support system

In China, there are many learners to carry out their researches on the emergency response management, Professor Wang [9] puts forth the parallel simulation method to research the emergency management. Fan Weicheng [10] points to the public incidents, provides some

In this chapter, we set the research object orient to the emergency earthquake disasters. Design a decision-making support system framework for the emergency response management, and then mainly research the simulation and evaluation methods and their application in the

**2. Systematic frameworks for simulating and evaluating the emergency**

Judging and analyzing the advantage and disadvantages of an emergency response plan needs a good decision making support system. To build up such a decision making system, a serial of technical methods and theory models are required to support the system. In this chapter, the author sums up the research methods for the emergency response plans, and put forth a whole research route map to design and develop the system. Such a research route map is a set of systematic framework which can simulate and evaluate the response plans for the

In Figure 1, there are 5 main parts (subsystems) in the set of systematic framework. These subsystems are built to support the whole decision framework. They are including: (A) emergency response effectiveness concept and the evaluation indices, (B) indices weights acquisition,(C)emergency response simulation theory based on OODA-DEVS, (D) simulation system and simulation data acquirement,(E) the integrated evaluation process and decision

The next research is to describe the related subsystems in the Figure 1. The following research will take emphasis on the main techniques of the simulation and evaluation in emergency

[5,6]. The emergency response needs the decision making support system [7,8].

138 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

useful suggestion and response methods for the emergency platform system.

untraditional emergency disaster like earthquake, seeing the Figure 1.

system.

earthquake disasters.

making support system.

response plans.

**preparedness for earthquake**

## **3. Evaluation indices orient to the emergency response of the earthquake disaster**

In order to select a right plan from many emergency response plans, it is necessary to make a good decision to evaluate the emergency response plans. And therefore, build up a set of evaluation indices system is very important.

#### **3.1. Measurements on the effectiveness for emergency response**

To evaluate the emergency response plans, we need design a comprehensive evaluation index. Such a complex index is needed to measure what is the degree of an emergency response plan can perform.

The operational effectiveness is widely used in military evaluation. As we know that, a war is very similar to the fight for the earthquake disaster. And thus, we need to give a definition for the effectiveness. In fact, effectiveness means the degree to which objectives are achieved and the extent to which targeted problems are solved.

And therefore, the effectiveness of emergency response plan can be defined as the degree to which the emergency plans executed right by the decision makers are achieved, or the extent to which the emergency disaster risk to reduce and rapid response rescue.

By means of the definition of the emergency response effectiveness, we can put forth a comprehensive index to measure the degree of the emergency response.

Emergency response effectiveness concept includes: 1) it is a comprehensive index; 2) given a specific emergency conditions and specific mission, which degree does the emergency response plan perform in the mission.

According to the concept of the emergency response effectiveness, we can measure the emergency response plans of the earthquake disaster in some aspects including: rescue speed, capability, safety and cost. As we know that, judge whether a well earthquake emergency plan is valid need comprehensive evaluate the above factors.

#### **3.2. Evaluation indices systems for the emergency response preparedness**

As a comprehensive effectiveness index, it needs to decompose into detailed sub indices. Using the top-down analysis methodology of system engineering, we can break up the top effec‐ tiveness indices into the different sub-indices, seeing in the Figure 2.

**Figure 2.** Effectiveness indices decomposed in top-down methodology

With the top-down methodology, we can design the response effectiveness indices system for the untraditional earthquake disaster, for example, seeing Figure 3.

A Simulation and Evaluation System Oriented to the Emergency Response Effectiveness of the Abrupt Earthquake… http://dx.doi.org/10.5772/59422 141

**Figure 3.** Response effectiveness indices of earthquake disaster

the effectiveness. In fact, effectiveness means the degree to which objectives are achieved and

And therefore, the effectiveness of emergency response plan can be defined as the degree to which the emergency plans executed right by the decision makers are achieved, or the extent

By means of the definition of the emergency response effectiveness, we can put forth a

Emergency response effectiveness concept includes: 1) it is a comprehensive index; 2) given a specific emergency conditions and specific mission, which degree does the emergency

According to the concept of the emergency response effectiveness, we can measure the emergency response plans of the earthquake disaster in some aspects including: rescue speed, capability, safety and cost. As we know that, judge whether a well earthquake emergency plan

As a comprehensive effectiveness index, it needs to decompose into detailed sub indices. Using the top-down analysis methodology of system engineering, we can break up the top effec‐

A

Index A1 Aj An

Aj1 Ajm

With the top-down methodology, we can design the response effectiveness indices system for

Some kind emergency response effectiveness index

to which the emergency disaster risk to reduce and rapid response rescue.

140 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

comprehensive index to measure the degree of the emergency response.

**3.2. Evaluation indices systems for the emergency response preparedness**

tiveness indices into the different sub-indices, seeing in the Figure 2.

the extent to which targeted problems are solved.

response plan perform in the mission.

The index Aj to be decomposed

is valid need comprehensive evaluate the above factors.

**Figure 2.** Effectiveness indices decomposed in top-down methodology

the untraditional earthquake disaster, for example, seeing Figure 3.

In order to describe the indices clearly and be easy to design for programming, we adopt the XML (Extensible Markup Language) file format to describe the effectiveness indices of the earthquake disaster. The emergency response effectiveness indices system can be written in XML file format as follows:

Figure 3. Response effectiveness indices of earthquake disaster

(Extensible Markup Language) file format to describe the effectiveness indices of the earthquake

In order to describe the indices clearly and be easy to design for programming, we adopt the XML **Figure 4.** The emergency response effectiveness indices system

 </ Rescue-capability > < Action-safety >

 </ Action-safety > < Effect-and-cost >

 < Action-cost /> </ Effect-and-cost >

**EFFECTIVENESS INDICES** 

evaluation systems.

 < Beyond-the-bad-weather /> < Dependability-of-rescue plan />

< Rescue-the-victims number />

</ Evaluation-indices-system-of-emergency-response-plan >

#### disaster. The emergency response effectiveness indices system can be written in XML file format as follows: **3.3. The weights acquirement for the emergency response effectiveness indices**

<?xml version="1.0" encoding="UTF-8" ?> < Evaluation-indices-system-of-emergency-response-plan > <Timeliness > < Rescuing-speed /> < Disaster–real-time-report frequency /> </ Timeliness > For the evaluation indices system, we have to know how much the sub-indices make role in evaluating the emergency response preparedness. And therefore, it is essential to acquire and calculate the weights of the sub-indices, which support the whole response plans effectiveness. However, it is complicated to acquire the indices weights because the calculation full of experts' interaction with the evaluation systems.

< Rescue-capability > < Load-volume /> < Bring-and -fetch /> In order to calculate the indices weights smoothly and make such an weights acquirement system reusable, we design a weights evaluation system based on MVC (Model View and

Figure 4. The emergency response effectiveness indices system **3.3 THE WEIGHTS ACQUIREMENT FOR THE EMERGENCY RESPONSE** 

For the evaluation indices system, we have to know how much the sub-indices make role in evaluating the emergency response preparedness. And therefore, it is essential to acquire and calculate the weights of the sub-indices, which support the whole response plans effectiveness. However, it is complicated to acquire the indices weights because the calculation full of experts' interaction with the

In order to calculate the indices weights smoothly and make such an weights acquirement system reusable, we design a weights evaluation system based on MVC (Model View and Controller) mode. The MVC mode is a reusability mode in software engineering, seeing the Figure 5. The architecture Controller) mode. The MVC mode is a reusability mode in software engineering, seeing the Figure 5. The architecture of the weight evaluation system based on MVC is designed as the Figure 6.

**Figure 5.** The Model-View-Controller mode in software engineering

**Figure 6.** The architecture of the weight acquisition system based on MVC

In the Figure 6,the main parts are described as follows:

**Model**: it is a process algorithm of expert scoring information based on the idea of AHP (Analytic Hierarchy Process). Before the model starts, the response effectiveness indices system file (xml file) will be loaded in the weights acquisition system.

**View**: it is the graphic user interface (GUI) and it displays the visual information including the input windows of the experts, and the print of the weight values output.

**Controller**: it is the communication and control bridge between the Model and View, and it mainly includes the operations of the input, output, and calculation and saving.

As an application example, we load the xml file of the response effectiveness indices (seeing the response effectiveness indices system, Figure 3.), then the weight evaluation system with the graphic interface view is generated, (seeing the Figure 7). This system is developed in java programming language. Notice, Here the indicators are the same meaning of indices.


**Figure 7.** The weights calculation and the visual interaction system

Controller) mode. The MVC mode is a reusability mode in software engineering, seeing the Figure 5. The architecture of the weight evaluation system based on MVC is designed as the

142 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

View

Model Controller

Read the indice system file (xml file)

**Model** the 9-scale measurement , AHP, DELPHI methods)

Load the indices file and draw the GUI

**View**

display the interface of interaction buttons and output

Input the choice 9-scale values of the experts

Start AHP method

Calculation of the all the experts scores

Output the weight values file

**Model**: it is a process algorithm of expert scoring information based on the idea of AHP (Analytic Hierarchy Process). Before the model starts, the response effectiveness indices

**View**: it is the graphic user interface (GUI) and it displays the visual information including

**Figure 5.** The Model-View-Controller mode in software engineering

**Figure 6.** The architecture of the weight acquisition system based on MVC

system file (xml file) will be loaded in the weights acquisition system.

the input windows of the experts, and the print of the weight values output.

In the Figure 6,the main parts are described as follows:

**Controller**

schedule the events between the model and the view,includes the operation like input,output comunication and save

Figure 6.

By means of above system, we can get the indices weights W from index x1 to x8 : W=(0.142, 0.115, 0.091, 0.10, 0.092, 0.123, 0.159, 0.178). The weights W will be used in the integrated evaluation in later of this chapter.

#### **3.4. The acquirement of the simulation information**

The response plans of the emergency event are designed for the future emergency, so that we cannot collect the real data of emergency event, and therefore the simulation method are necessary to evaluate the future emergency plans. However, it is difficult to get the proper information from the simulation system because there is much difference between the simulation and evaluation. As we know that, the simulation system cannot get the proper information without the evaluation indices requirements. So we try to build a bridge between the two subsystems. This bridge is the so-called framework of menu of simulation data collecting, seeing the Figure 8.

**Figure 8.** The framework of the menu of the simulation data collecting

Because the simulation data is isomerous, it is difficult to save and transfer in form of the relational database format. In accordance with the format of emergency response effectiveness indices, the proper file format for the menu of the simulation data is the XML file. For the earthquake emergency response scenario, we design the menu of the simulation data to collect the simulation information as

Figure 9. The menu of the simulation data

As we know that, it is difficult to evaluate the emergency response effectiveness of the earthquake disaster in real environments. It is necessary to use simulation method to support the decision making. And therefore, a reasonable simulation method should be based on a scientific mechanism of

Figure 8. The framework of the menu of the simulation data collecting **Figure 9.** The menu of the simulation data

<?xml version="1.0" encoding="UTF-8" ?>

< Action-cost Cost-of–the-rescue-plan=""/>

< Evaluation-indices-system-of-emergency-response-plan >

< Rescuing-speed start-time=" " arrival time="" distance=" "/>

< Bring-and -fetch equipment-capability-to-carry-and-fetch="" />

 < Beyond-the-bad-weather Level-of-last-bad-weather=""/> < Dependability-of-rescue plan Dependability-probability=""/>

< Rescue-the-victims number Number-being-rescued=""/>

**4 Simulation mechanism of the emergency response process** 

</ Evaluation-indices-system-of-emergency-response-plan >

< Load-volume available-weight-to-carry -and-fetch=""/>

< Disaster–realtime-report frequency report –times-about-the-disaster=""/>

follows, seeing in Figure 9.

<Timeliness >

</ Timeliness >

< Rescue-capability >

 </ Rescue-capability > < Action-safety >

</ Action-safety > < Effect-and-cost >

</ Effect-and-cost >

emergency simulation.

Because the simulation data is isomerous, it is difficult to save and transfer in form of the relational database format. In accordance with the format of emergency response effectiveness indices, the proper file format for the menu of the simulation data is the XML file. For the earthquake emergency response scenario, we design the menu of the simulation data to collect the simulation information as follows, seeing in Figure 9.

## **4. Simulation mechanism of the emergency response process**

As we know that, it is difficult to evaluate the emergency response effectiveness of the earthquake disaster in real environments. It is necessary to use simulation method to support the decision making. And therefore, a reasonable simulation method should be based on a scientific mechanism of emergency simulation.

#### **4.1. The mechanism on the emergency response process of an earthquake disaster**

In order to deal with the emergency response to the earthquake disasters, the government especial organization such as emergency departments and their executers should keep reconnaissance on the disaster zone, and make actions according to the detail disaster condi‐ tions.

How to describe such rules of the emergency process is a big problem. Considering the OODA (Observe, Orient, Decide, Act) loop which is John. Boyd, the famous U.S. captain, first put forth. It tells us the combat rule which runs as a loop, seeing as Figure 10.

**Figure 10.** OODA loop diagram

Simulation scenario

Effectiveness indices system

Decision making support system

144 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

Memu of the simulation data

Simulation results information File

**Figure 8.** The framework of the menu of the simulation data collecting

Indices evaluation

Evaluation system

Menu of simulation data

> Simulation system

follows, seeing in Figure 9.

<Timeliness >

</ Timeliness >

< Rescue-capability >

 </ Rescue-capability > < Action-safety >

</ Action-safety > < Effect-and-cost >

</ Effect-and-cost >

emergency simulation.

<?xml version="1.0" encoding="UTF-8" ?>

**Figure 9.** The menu of the simulation data

< Action-cost Cost-of–the-rescue-plan=""/>

< Evaluation-indices-system-of-emergency-response-plan >

< Rescuing-speed start-time=" " arrival time="" distance=" "/>

< Bring-and -fetch equipment-capability-to-carry-and-fetch="" />

 < Beyond-the-bad-weather Level-of-last-bad-weather=""/> < Dependability-of-rescue plan Dependability-probability=""/>

< Rescue-the-victims number Number-being-rescued=""/>

**4 Simulation mechanism of the emergency response process** 

</ Evaluation-indices-system-of-emergency-response-plan >

< Load-volume available-weight-to-carry -and-fetch=""/>

< Disaster–realtime-report frequency report –times-about-the-disaster=""/>

simulation Simulation data Simulation model

Figure 8. The framework of the menu of the simulation data collecting

Because the simulation data is isomerous, it is difficult to save and transfer in form of the relational database format. In accordance with the format of emergency response effectiveness indices, the proper file format for the menu of the simulation data is the XML file. For the earthquake emergency response scenario, we design the menu of the simulation data to collect the simulation information as

Figure 9. The menu of the simulation data

As we know that, it is difficult to evaluate the emergency response effectiveness of the earthquake disaster in real environments. It is necessary to use simulation method to support the decision making. And therefore, a reasonable simulation method should be based on a scientific mechanism of

Requirement of

**analysis**

Requirement of evaluation

> In fact, the rapid response to the earthquake disaster is similar to a combat. And therefore, we should build the emergency response framework based on OODA loop as follows, seeing the Figure 11.

**Figure 11.** The response framework is based on OODA loop for the earthquake disaster

#### **4.2. Emergency response modeling theory based on OODA**

With the emergency response framework for the earthquake disaster, we need build a simulation model in scientific language. DEVS (Discrete Event System Specification) is a formalism language for modeling and analysis of discrete event systems (DESs). The emer‐ gency response system just is such a system, so that it is reasonable to using DEVS to describe the simulation process.

#### *4.2.1. The OODA loop and the DEVS theory*

The DEVS formalism was invented by Bernard P. Zeigler, who is emeritus professor at the University of Arizona. It is a modular and hierarchical formalism for modeling and analyzing general systems. There are two key models: atomic DEVS and coupled DEVS. *Atomic DEVS* captures the system behavior, while *Coupled DEVS* describes the structure of system.

The atomic DEVS is fit for describing the emergency response system behavior. Combining with the emergency response process framework based on OODA, we can build up the control structure in the DEVS factors, seeing in Figure 12.

**Figure 12.** DEVS atomic model diagram

An atomic DEVS model is defined as a 7-tuple

AtomicDEVS= <*S*, *ta*, *δ*int, *X* , *δext*, *Y* , *λ* >

Where:

**intelligence Observe**

146 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

**Emergency response process based on OODA loop**

With the emergency response framework for the earthquake disaster, we need build a simulation model in scientific language. DEVS (Discrete Event System Specification) is a formalism language for modeling and analysis of discrete event systems (DESs). The emer‐ gency response system just is such a system, so that it is reasonable to using DEVS to describe

The DEVS formalism was invented by Bernard P. Zeigler, who is emeritus professor at the University of Arizona. It is a modular and hierarchical formalism for modeling and analyzing general systems. There are two key models: atomic DEVS and coupled DEVS. *Atomic DEVS*

The atomic DEVS is fit for describing the emergency response system behavior. Combining with the emergency response process framework based on OODA, we can build up the control

> dint

*ta*

*Y*

captures the system behavior, while *Coupled DEVS* describes the structure of system.

**Information on Emergency event like Earthquake break out** 

the simulation process.

*4.2.1. The OODA loop and the DEVS theory*

structure in the DEVS factors, seeing in Figure 12.

**Figure 12.** DEVS atomic model diagram

An atomic DEVS model is defined as a 7-tuple

AtomicDEVS= <*S*, *ta*, *δ*int, *X* , *δext*, *Y* , *λ* >

*ext* d

*x <sup>S</sup>*

**Disaster zone Orient**

**Figure 11.** The response framework is based on OODA loop for the earthquake disaster

**4.2. Emergency response modeling theory based on OODA**

**Rescue Act**

**Emergency response actions and results output**

**evaluting response plans Decide**

S is the set of sequential states (or also called the set of partial states);

X is the set of input events;

Y is the set of output events;

*Q* ={(*s*, *te*)|*s* ∈*S*, 0≤*te* ≤*ta*(*s*)} is the set of total states, and *te* is the elapsed time since the last event;

*δ*int :*S* →*S* is the internal transition function which defines how a state of the system changes internally (when the elapsed time reaches the lifetime of the state);

*δext* :*Q* × *X* →*S* is the external transition function which defines how an input event changes a state of the system.

*λ* :*S* →*Y* is the output function. This function defines how a state of the system generates an output event (when the elapsed time reaches the lifetime of the state);

The output function *λ*(*s*) is decided by the state s before transition.

*ta* :*S* →*R*0,*<sup>∞</sup>* + is the time advance function which is used to determine the lifespan of a state, *R*0,*<sup>∞</sup>* + means Non negative real numbers; when no input events arrive, the state s will maintain the lifetime. When *ta*(*s*)=0, we call the state s is executing state; while *ta*(*s*)= + *∞*, the state s is called dead state, and the system always waits for the input event.

#### *4.2.2. Describe the emergency response process in OODA-DEVS*

The kernel of a simulation system is to the simulation engine. The simulation engine of the emergency response system is required to design based on the DEVS simulation theory. Considering of the emergency response process is an OODA loop, the simulation engine of the emergency response system for disaster is designed as follows, seeing the Figure 13.

In the Figure 13, it tells us the workflow of the system simulation engine. When simulation start at T0, each variable in the simulation system is initiated. Then scan the current simulation time t, and judge whether the t is more than the total simulation time T. If t>T, then the emergency simulation process is terminated, else it requires to judge the emergency events. Before dealing with the messages of the emergency system, it is needed to judge the kinds of the messages. 1) If the received message is the input event message-X-message, what's more, the simulation time t of the input event must meet the requirement of the next event time, we can define such an event as the ex-message; if the simulation time of the input event is wrong, show that the synchronization time is invalid, and the event must be cancelled and to be scanned again.

After confirm the ex-message, it is required to update the simulation time of last event tL and the time of the next event tN, and then output the simulation result information by means of the output function*λ(S)*. While the response units like rescuer teams send the simulation information to the top level simulation unit (decision making departments), the response units

**Figure 13.** OODA-DEVS simulation engine

themselves will continue to finish their missions. Such units is required to update the simula‐ tion time t again, and return to scan the simulation event time t. so far, an external input event is finished dealing with.

2) If the message received is an inner message, then we define it as an inner serial event. Other wise, confirm it as an exceptional message, and it needs to modify in the time management (a simulation service rule). For the inner serial event, the inner state transits, and update the time of the last event, and the next event time t. continue to these steps till the ex-message is coming, and transfer to the ex state loop. From above flow chart analysis, it is easy to find out, the simulation engine process just like the OODA four parts loop.

#### **4.3. Simulation system and simulation data list acquisition**

#### *4.3.1. The simulation architecture of the emergency response management*

As we all know that, the earthquake emergency response system is very complex. The simulation system includes many parts: the emergency scenario, the behaviors of response units, the interaction communications between the rescuer and the refugees. All the parts are based on the OODA loop in the response process.

Considering the emergency response plans need the many interaction operations, so that we build up a simulation system architecture based on the HLA/RTI (High Level Architecture/ Run-time Infrastructure) technology. It is suitable for the modeling developers to use HLA and RTI to describe emergency system with many uncertainty events.

The simulation architecture includes many software nodes: response plan and rescue units, the emergency information like weather and location, situation description, the environment of disaster area, emergency events generator, and rescue command system, and so on.

The simulation architecture of the emergency response for earthquake disaster is shown in Figure 14.

**Figure 14.** Simulation architecture of the emergency response

#### *4.3.2. Response units behaviors simulation scripts*

themselves will continue to finish their missions. Such units is required to update the simula‐ tion time t again, and return to scan the simulation event time t. so far, an external input event

**End of the system simulation** 

*sy* )( )( int

**Simulation start t=T0**

**Initialization of variables Ev0//emergency event parent // top class of the simulator**  *tL* **// the time of the last event** *tN* **// the time of the next event**

148 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

*A* **= <***S***,***ta***,δ***int***,***X***,δ***ext***,***Y***,λ> //unit A is a DEVS model**

**Yes**

**t<T**

**Scanning the simulation event time t**

**Receive the input event message-X-message(Time** *t***)**

**Generate an event X and inner state S**

**Yes No**

**No Yes No Yes**

> **Define the event as ex-event**

**Input event** 

*<sup>N</sup>* = *tt*

**Execute the emergency response mission, And update the next event time t**

**Send the output message y-message(***y***,***t***) to top level unit** 

 

*ttL* )( + *Xtatt tLN*

**time** 

**Ex-event advance method**

**Output function**

**Event sychnoevent has something wrong,canc el the event, go to scanning again**

**Inner-event advance**

**Inner State , continue to mantain the inner serial event**

d*ss*

**the inner event t is Smessage(Time** *t***)?**

**No**

*ttL statt* )( *LN* +

**Throw exception and modify it .**

**Observe** 

**Orient** 

**Decide**

**Act**

**method**

**Define the event as inner-event**

2) If the message received is an inner message, then we define it as an inner serial event. Other wise, confirm it as an exceptional message, and it needs to modify in the time management (a simulation service rule). For the inner serial event, the inner state transits, and update the time

is finished dealing with.

**Figure 13.** OODA-DEVS simulation engine

After we build a simulation system, we need analyze the simulation behaviors. In the simu‐ lation toolkit of STAGE (Scenario Toolkit and Generation Environment), we can create the behavior simulation scripts based on the above simulation theory and the simulation engine.

Emergency response unit is the force to execute the rescue mission like troop, emergency medical services, police, and firefighters and so on. For each of the emergency response unit, there is a script program to describe the unit behavior. The script codes are written in STAGE as follows.

### **5. Earthquake disaster scenario and emergency response simulation**

In order to analyze the emergency response plans of earthquake disasters, a typical earthquake disaster is designed as an application scenario. The next emergency response plans are evaluated based on such a scenario.

#### **5.1. Earthquake disaster scenario**

Suppose a terrible catastrophe like earthquake breaks out in some uncertainty place, seeing the Figure 15, we should carry out the emergency response plans to quickly rescue the victims. Usually the routes to the disaster zone are far away from city and the disaster conditions are very complicated and uncertainty, so that we are required a decision-making support system to get the best emergency plan from many available plans.

In this earthquake disaster scenario, the advantages and disadvantages of the emergency response plans can be shown in Table 1.

**Figure 15.** The Earthquake disaster scenario and some emergency response plans

there is a script program to describe the unit behavior. The script codes are written in STAGE

150 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

**5. Earthquake disaster scenario and emergency response simulation**

evaluated based on such a scenario.

**5.1. Earthquake disaster scenario**

to get the best emergency plan from many available plans.

In order to analyze the emergency response plans of earthquake disasters, a typical earthquake disaster is designed as an application scenario. The next emergency response plans are

Suppose a terrible catastrophe like earthquake breaks out in some uncertainty place, seeing the Figure 15, we should carry out the emergency response plans to quickly rescue the victims. Usually the routes to the disaster zone are far away from city and the disaster conditions are very complicated and uncertainty, so that we are required a decision-making support system

as follows.


**Table 1.** The advantages and disadvantages of some emergency response plans

#### **5.2. The acquisition of the simulation data**

For example, we select the emergency response plan by truck vehicle to simulate. In this plan simulation, first to arrange vehicles direction to the disaster zone, and then to design the routes with the random disasters conditions based on the discrete event simulation method (see Figure.16). During the simulation time, it is possible that the rescue trucks are hit by roll rock or mudslide from the secondary disasters, and it will spend much time to deal with the breakdown. We can simulate the trucks rescue action in different routes in the STAGE (see Figure.17).

**Figure 16.** Simulation of the breakdown of the truck plan

**Figure 17.** Simulation on the process of truck plan

Figure 16. Simulation of the breakdown of the truck plan

Through the simulation system, we can collect the needed simulation information and save it as Xml file. The simulation information file (Truck.xml) is written in the format of the menu of simulation data as follows, seeing Figure 18: Figure 17. Simulation on the process of truck plan Through the simulation system, we can collect the needed simulation information and save it as Xml file. The simulation information file (Truck.xml ) is written in the format of the menu of simulation data as follows, seeing Figure 18:

```
<?xml version="1.0" encoding="UTF-8" ?> 
< Evaluation-indices-system-of-emergency-response-plan > 
      <Timeliness > 
      < Rescuing-speed start-time=" 0" arrival time="4" distance=" 300.0"/> 
      < Disaster–realtime-report frequency report –times-about-the-disaster="15"/> 
     </ Timeliness > 
     < Rescue-capability > 
      < Load-volume available-weight-to-carry -and-fetch="12"/> 
      < Bring-and -fetch equipment-capability-to-carry-and-fetch="0.6" /> 
      </ Rescue-capability > 
      < Action-safety > 
      < Beyond-the-bad-weather Level-of-last-bad-weather="6"/> 
      < Dependability-of-rescue plan Dependability-probability="0.7"/> 
     </ Action-safety > 
     < Effect-and-cost > 
      < Rescue-the-victims number Number-being-rescued="10"/> 
     < Action-cost Cost-of–the-rescue-plan="10"/> 
     </ Effect-and-cost > 
</ Evaluation-indices-system-of-emergency-response-plan >
```
Figure 18. Simulation information in Xml file **Figure 18.** Simulation information in Xml file

or mudslide from the secondary disasters, and it will spend much time to deal with the breakdown. We can simulate the trucks rescue action in different routes in the STAGE (see

152 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

t ree

t ree mountains

t ree

t ree

t ree

End point An

t ree

t ree

t ree

t ree

t ree

**Figure 16.** Simulation of the breakdown of the truck plan

**Figure 17.** Simulation on the process of truck plan

road

Figure.17).

t ree

truck

Start point A1

> The Truck.xml file is the simulation results information about adopting the truck plan in the emergency response. The simulation and data collection of the other response plans are similar to the plan of the truck. Here it is not necessary to repeat the other emergency plans.

## **6. The integrated evaluation and decision making for the emergency plans**

As a decision-making system for the emergency response plans, it is necessary to integrate the above simulation data and the weights information of the evaluation indices system from the experts.

As for the evaluation method, because the evaluation indices are the isomer information which has different attributes. Therefore, in this paper, a good general evaluation model is adopted to build the decision-making method.

The detail evaluation method is researched as follows.

#### **6.1. Build the evaluation indices system**

The effectiveness evaluation indices system is built in Figure 19. Ai is the index i, which describes the system attributes of the alternatives. Among the indices, there are three different types of indices: one type is the effective index, which value is the more, the better; while the second type is the cost index, which value is the more, the worse; and the third type is the proper index, which characteristic is between the two indices.

**Figure 19.** The general evaluation indices system on the emergency effectiveness

#### **6.2. Effectiveness evaluation model based on TOPSIS**

TOPSIS is for short of the Technique for Order Preference by Similarity to Ideal Solution. Its main idea is to evaluate the alternatives by means of the measurement scale named Euclidean distance. It is fit for evaluating many alternatives, which have different kinds of attributes.

The evaluation method based on the TOPSIS is very suitable for evaluating the effect of the alternatives, which have many heterogeneous indices. In fact, this method is built on a decision-making matrix, which different rows in the same column index have the same attribute. This is the reason that the heterogeneous data from different plans can also be compared in this evaluation model.

First all, it is necessary to collect the related evaluation data. Combining with the evaluation indices system, get the data or attribute values from the different evaluation indices. Using such data or attributes values, we can build the evaluation matrix C, seeing the Table 2. In this table, the row denotes the alternatives, and the column name stands for the attributes values of the indices. Here the attributes data is from simulation information.


**Table 2.** Alternative-attribute information

Cij means the j-th attribute of the i-th alternative or emergency plan. Where i=1,2,…,m; j=1,2, …,n.

The evaluation method based on the TOPSIS is describes as follows.

Firstly, convert the attributes in table 2 into the decision matrix C.

types of indices: one type is the effective index, which value is the more, the better; while the second type is the cost index, which value is the more, the worse; and the third type is the

154 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

effectiveness evaluation indices

> index A3

TOPSIS is for short of the Technique for Order Preference by Similarity to Ideal Solution. Its main idea is to evaluate the alternatives by means of the measurement scale named Euclidean distance. It is fit for evaluating many alternatives, which have different kinds of attributes.

The evaluation method based on the TOPSIS is very suitable for evaluating the effect of the alternatives, which have many heterogeneous indices. In fact, this method is built on a decision-making matrix, which different rows in the same column index have the same attribute. This is the reason that the heterogeneous data from different plans can also be

First all, it is necessary to collect the related evaluation data. Combining with the evaluation indices system, get the data or attribute values from the different evaluation indices. Using such data or attributes values, we can build the evaluation matrix C, seeing the Table 2. In this table, the row denotes the alternatives, and the column name stands for the attributes values

of the indices. Here the attributes data is from simulation information.

**alternative attribute 1 attribute 2 … attribute n** alternative1 C11 C21 … C1n … … … … … alternative m Cn1 C22 … Cmn

index Ai

index Am

 means type

proper index, which characteristic is between the two indices.

index A2

**Figure 19.** The general evaluation indices system on the emergency effectiveness

**6.2. Effectiveness evaluation model based on TOPSIS**

Effective type Cost type

index A1

compared in this evaluation model.

**Table 2.** Alternative-attribute information

$$\mathbf{C} = \begin{pmatrix} c\_{11} & c\_{12} & \dots & c\_{1n} \\ c\_{21} & c\_{22} & \dots & c\_{2n} \\ \dots & \dots & \dots & \dots \\ c\_{m1} & c\_{m2} & \dots & c\_{mn} \end{pmatrix} \\ \tag{1}$$
 
$$\mathbf{r\_{ij}} = \mathbf{w}\_{j} c\_{ij} \sqrt{\sqrt{\sum\_{i=1}^{n} c\_{ij}^{2}}} \\ \tag{2}$$

For the data from the matrix C, the attributes from the same column can be compared with different rows. In order to be convenient to evaluate the different alternatives, we need to standardize the matrix C into matrix R with the unit rij in formula (1). For wj , it is the j-th weight of the indices. The matrix R becomes a normalization matrix which also adds the related weights from the evaluation indices, and R will be the foundation of the next evaluation steps.

Secondly, analyze the ideal point and negative-ideal point from the alternatives.

To get the ideal alternative and negative-ideal alternative, it depends on the type of the indices. Different type indices have different modes of process. The ideal alternative vector point is x\* in the formula (2). At the same time, the negative-ideal alternative vector point is x-in the formula (3):

$$\{ (\max\_{i} r\_{i\cdot} | j \in I), (\min\_{i} r\_{i\cdot} | \ i \in I') \mid i \in M \} = [r\_1^{\ast}, r\_2^{\ast}, \dots, r\_n^{\ast}] \tag{2}$$

$$\{ (\min\_{i} r\_{i\cdot} | i \in I), (\max\_{i} r\_{i\cdot} | i \in I') \mid i \in M \} = [r\_1^{-}, r\_2^{-}, \dots, r\_n^{-}] \tag{3}$$

In the formula (2) (3), M is the set of the alternatives, J and J' is the effective type and cost type respectively.

Thirdly, calculate Euclidean distance of each alternative to the ideal alternative or the negativeideal alternative.

The Euclidean distance of the i-th alternative to the ideal vector point.

$$\mathbf{S}\_{i}^{\*} = \sqrt{\sum\_{j=1}^{n} (r\_{ij} - r\_{j}^{\*})^{2}} \quad (i \in M) \tag{4}$$

The Euclidean distance of the i-th alternative to the negative-ideal vector point.

$$\mathbf{S}\_{i}^{\cdot} = \sqrt{\sum\_{j=1}^{n} \left(r\_{ij} - \boldsymbol{r}\_{j}^{\cdot \cdot}\right)^{2}} \quad (i \in M) \tag{5}$$

Fourthly, calculate the degree of each alternative approaching the ideal alternative *Ci* in formula (6).

$$C\_i = S\_i^- / (S\_i^- + S\_i^\*) \tag{6}$$

According to the formula (6), if the degree *Ci* is larger, means that i-th alternative is better.

#### **6.3. Response effectiveness indices system and evaluation information acquisition**

In this application example, the effectiveness of several emergency response alternatives for the earthquake is evaluated based on the above evaluation model. The evaluation process is carried out as follows:

First, set up the evaluation indices system for the earthquake emergency response effective‐ ness, seeing the Figure 20.

**Figure 20.** The effectiveness evaluation indices system

Second, there are two kinds of important information to be ready: indices weights and the indices simulation data.

According to the weights acquisition system, get the weights values from x1 to x8 as follows:

#### W=0.142, 0.115, 0.091, 0.10, 0.092, 0.123, 0.159, 0.178.

The simulation values of the indices from x1 to x8 are filled in the table 3, where, x8 is the cost type index, means the less the better. The indices except x8 are the effect indices.


Notice \* : For the airplane can not carry anything back from disaster zone, here use 0.1 stands for carrying few.

**Table 3.** The indices simulation data of emergency response plan

#### **6.4. Process of the evaluation**

The Euclidean distance of the i-th alternative to the negative-ideal vector point.

156 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures


S ( )( ) *<sup>n</sup> ij j <sup>j</sup>*

**6.3. Response effectiveness indices system and evaluation information acquisition**

In this application example, the effectiveness of several emergency response alternatives for the earthquake is evaluated based on the above evaluation model. The evaluation process is

First, set up the evaluation indices system for the earthquake emergency response effective‐

Emergency Response Plan Effectiveness indices

> Beyond the bad weather (x5)

Second, there are two kinds of important information to be ready: indices weights and the

According to the weights acquisition system, get the weights values from x1 to x8 as follows:

Depend ability (x6)

Effect indices Cost

Rescue the victims number (x7)

index

Rescue Action cost (x8)

*r r iM*

Fourthly, calculate the degree of each alternative approaching the ideal alternative *Ci* in

=-Î å (5)

\* /( ) - - = + *CS S S ii i i* (6)

is larger, means that i-th alternative is better.

1

=

i

According to the formula (6), if the degree *Ci*

Load volume (x3)

Bring and fetch (x4)

formula (6).

carried out as follows:

Speed (x1)

indices simulation data.

situation report frequency (x2)

**Figure 20.** The effectiveness evaluation indices system

ness, seeing the Figure 20.

With the method, we can get the original matrix C from the information in Table 3.


Due to each of the index has different weight, it is necessary to think about the indices weights for the original matrix. In this paper, the weights values for the indices from x1 to x8 is W=0.142, 0.115, 0.091, 0.10, 0.092, 0.123, 0.159, 0.178. Using the formula (1), we can get the standard matrix P.


From the matrix P, the Ideal alternative vector point can be selected as IdealPt=(0.121, 0.078, 0.0786,0.069,0.0601, 0.072, 0.142,0.0078). Notice that X8 is the cost index, the less the better.

At the same time, the most negative alternative point can be chosen as NegativePt=(0.0015, 0.0313, 0.0010, 0.031, 0.020, 0.045,0.00071, 0.155)

By means of the formula (4), get the Euclidean distance of each alternative to the ideal alternative vector point as follows: IdealDis=(18.93,432.2, 232.1, 67.83).

Get the Euclidean distance of each alternative to the most negative alternative vector point as follows: anti-idealDis=(77.87, 502.41, 302.18, 21.53).

Combined with the idealDis and anti-dealDis, we can get the approaching degree F which stands for any alternative approaching the ideal alternative vector point, By the meantime, far way from the most negative alternative vector point, F=(0.4932 0.3946 0.6726 0.4451).

According to the approaching degree F, rank all the response plans in descending order as follows:

Plan 3-helicopter> Plan 1-truck > Plan 4-march > Plan 2-air plane. The diagram is described in Figure 21.

**Figure 21.** The effectiveness rank of the four Response plans

Based on the evaluation results, the plan 3(Helicopter rescue plan) is the first rank of all the plans, and the truck vehicle plan is the second. However, the last is the airplane response plan because it could not make its function to the maximum for example the plane can not land on the damage airport and pick up nothing back.

#### **6.5. Future work**

In this chapter, we develop a robust decision making support system, what's more, make valid application for evaluation and simulation the emergency response to the earthquake. As far as the future work concerned, there are several points to be done:

Firstly, improve the visual system of decision making system. A good visual system is welcome because we prefer the diagram to text or formulas. The future work will enforce the visual modular in the decision making system.

Secondly, improve the simulation technology for analyzing the emergency response plan, especially for the interaction simulation. There are many interactions in the simulation of the emergency response plans, and thus, it is necessary to enforce the Distributed interaction simulation technology like HLA/RTI.

Thirdly, improve the evaluation method. As we know, the evaluation method is the core of the decision-making support system. in this chapter, we adopt the experts judge method and the multi-attributes decision making method –TOPSIS. In the future work, we should adopt more evaluation methods to support the evaluation of the emergency response plans for the catastrophes.

## **7. Highlights**

By means of the formula (4), get the Euclidean distance of each alternative to the ideal

Get the Euclidean distance of each alternative to the most negative alternative vector point as

Combined with the idealDis and anti-dealDis, we can get the approaching degree F which stands for any alternative approaching the ideal alternative vector point, By the meantime, far

According to the approaching degree F, rank all the response plans in descending order as

Plan 3-helicopter> Plan 1-truck > Plan 4-march > Plan 2-air plane. The diagram is described in

1234

Based on the evaluation results, the plan 3(Helicopter rescue plan) is the first rank of all the plans, and the truck vehicle plan is the second. However, the last is the airplane response plan because it could not make its function to the maximum for example the plane can not land on

In this chapter, we develop a robust decision making support system, what's more, make valid application for evaluation and simulation the emergency response to the earthquake. As far

Firstly, improve the visual system of decision making system. A good visual system is welcome because we prefer the diagram to text or formulas. The future work will enforce the visual

Secondly, improve the simulation technology for analyzing the emergency response plan, especially for the interaction simulation. There are many interactions in the simulation of the emergency response plans, and thus, it is necessary to enforce the Distributed interaction

way from the most negative alternative vector point, F=(0.4932 0.3946 0.6726 0.4451).

alternative vector point as follows: IdealDis=(18.93,432.2, 232.1, 67.83).

158 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

follows: anti-idealDis=(77.87, 502.41, 302.18, 21.53).

0 0. 2 0. 4 0. 6 0. 8

as the future work concerned, there are several points to be done:

**Figure 21.** The effectiveness rank of the four Response plans

the damage airport and pick up nothing back.

modular in the decision making system.

simulation technology like HLA/RTI.

follows:

Figure 21.

**6.5. Future work**

In this paper, there are some highlights as follows:


## **8. Conclusions**

In this paper, put forth the concept of the emergency response effectiveness, and center on the methods of response effectiveness simulation and evaluation. A decision-making support system is built to evaluate the emergency response plans. The system is made up of several parts: indices weights acquirement subsystem, simulation mechanism of emergency response process, simulation data acquirement and the integrated evaluation method based on TOPSIS.

By means of the decision-making support system, several response plans in some earthquake disasters are evaluated for their response effectiveness. The evaluation results demonstrate that the simulation and evaluation system is available and reasonable.

## **9. Summary**

It is difficult to judge the most suitable preparedness plan from many emergency response plans. And therefore, it is necessary to build a decision-making support system to evaluate the response plans and to select the most suitable preparedness plan.

In fact, we face with the challenge to test and evaluate the response plans under the **real conditions** of a strong earthquake disaster. Modeling and simulation methods are adopted to evaluate and demonstrate the preparedness plans for their advantages such as low cost, safety research, time-space easily converting, and so on.

In this chapter, pointing to the strong earthquake disasters, a decision-making support system framework is designed to manage the emergency response plans, and this framework includes the simulation and evaluation methods. In detail, a whole research route map is designed and developed to simulate and evaluate the response plans for the untraditional emergency disaster like earthquake. As a result, a serial of technical methods and theory models are included in the systematic framework. There are 5 main parts (subsystems) in this framework. They are including: (A) emergency response effectiveness concept and the evaluation indices, (B) indices weights acquisition,(C)emergency response simulation theory based on OODA-DEVS, (D) simulation system and simulation data acquirement,(E) the integrated evaluation process and decision making support system.

In this chapter, the concept of the emergency response effectiveness is defined, and it can use as a comprehensive index to measure the degree of the emergency response plan. What's more, the evaluation indices of the emergency response plans are built up in systems engineering method.

In order to describe the evaluation indices clearly and be easy to design for programming, we adopt the XML (Extensible Markup Language) file format to describe the response effective‐ ness indices of the earthquake disaster.

To get the weights of the evaluation indices, the weights evaluation system based on MVC (Model View and Controller) mode is built.

Referring as the similar process of combat, the emergency response process framework based on OODA loop is built, and put forth a simulation model in DEVS theory. By means of the simulation model, we design the flowchart of the system simulation engines.

For many interaction operations in the emergency response simulation, we build up a simulation system architecture based on the HLA/RTI (High Level Architecture/Run-time Infrastructure) technology. It is suitable for the developers to use HLA and RTI to describe emergency response systems full of interactions and interoperability.

A typical earthquake disaster is designed as an application scenario. The following emergency response plans are evaluated based on such a scenario.

It is necessary to integrate the above simulation data and the weights information of the evaluation indices system from the experts.

As for the evaluation method, because the evaluation indices are the isomer information which has different attributes. A general evaluation model based on TOPSIS is adopted to build the decision-making method.

Taking the emergency simulation scenario of the strong earthquake disaster as example, apply with the simulation and evaluation methods in this chapter, and get the evaluation results of emergency response plans. The evaluation results show feasible. In this example, the Heli‐ copter rescue plan is evaluated as the best plan among the response plans, and the truck vehicle plan is the second. However, the last is the airplane response plan for it can not land on the damage airport and pick up nothing back.

## **Nomenclatures**

evaluate and demonstrate the preparedness plans for their advantages such as low cost, safety

160 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

In this chapter, pointing to the strong earthquake disasters, a decision-making support system framework is designed to manage the emergency response plans, and this framework includes the simulation and evaluation methods. In detail, a whole research route map is designed and developed to simulate and evaluate the response plans for the untraditional emergency disaster like earthquake. As a result, a serial of technical methods and theory models are included in the systematic framework. There are 5 main parts (subsystems) in this framework. They are including: (A) emergency response effectiveness concept and the evaluation indices, (B) indices weights acquisition,(C)emergency response simulation theory based on OODA-DEVS, (D) simulation system and simulation data acquirement,(E) the integrated evaluation

In this chapter, the concept of the emergency response effectiveness is defined, and it can use as a comprehensive index to measure the degree of the emergency response plan. What's more, the evaluation indices of the emergency response plans are built up in systems engineering

In order to describe the evaluation indices clearly and be easy to design for programming, we adopt the XML (Extensible Markup Language) file format to describe the response effective‐

To get the weights of the evaluation indices, the weights evaluation system based on MVC

Referring as the similar process of combat, the emergency response process framework based on OODA loop is built, and put forth a simulation model in DEVS theory. By means of the

For many interaction operations in the emergency response simulation, we build up a simulation system architecture based on the HLA/RTI (High Level Architecture/Run-time Infrastructure) technology. It is suitable for the developers to use HLA and RTI to describe

A typical earthquake disaster is designed as an application scenario. The following emergency

It is necessary to integrate the above simulation data and the weights information of the

As for the evaluation method, because the evaluation indices are the isomer information which has different attributes. A general evaluation model based on TOPSIS is adopted to build the

Taking the emergency simulation scenario of the strong earthquake disaster as example, apply with the simulation and evaluation methods in this chapter, and get the evaluation results of emergency response plans. The evaluation results show feasible. In this example, the Heli‐ copter rescue plan is evaluated as the best plan among the response plans, and the truck vehicle

simulation model, we design the flowchart of the system simulation engines.

emergency response systems full of interactions and interoperability.

response plans are evaluated based on such a scenario.

evaluation indices system from the experts.

decision-making method.

research, time-space easily converting, and so on.

process and decision making support system.

ness indices of the earthquake disaster.

(Model View and Controller) mode is built.

method.


## **Acknowledgements**

This work is supported by National Natural Science Foundation (NNSF) of China under Grant No. 61374186. This work also gets some support from the 28th Research Institute of China Electronic Technology Group Corporation.

## **Author details**

Yan-Yan Huang\*

Address all correspondence to: imhyy@sina.com

Automation School, Nanjing University of Science and Technology, Nanjing, Jiangsu, China

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## **Rotational Components of the Seismic Fields Caused by Local Events**

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Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/59595

## **1. Introduction**

The existence of rotation effects at the Earth surface associated with earthquakes has been observed probably at least from the times when scientific approach to the ground motions during the quake had started. They are described in several classical monographs, such as Hobbs [1] and Davison [2], in which cited examples concern, among other things, twisting of some obelisks, tombs and segments of columns. However, early publications explain such phenomena as incidental effects of interference between linear vibrations [3, 4]. For instance, Imamura [5] explained the rotation effects of some objects at the ground surface by the impact of body/surface waves: due to such impact, an object can be inclined, partly losing contact with the ground surface, and when returning to the vertical some twist occurs with respect to its former position. Hence, from the beginning, the rotational effects have been treated as derivative effects, and it was stated that although such effects are observed, they cannot be explained as effect of any rotational waves - or rotational components of seismic waves because existence of such waves or components would contradict the ideal elastic theory [6].

In the second half of last century, it was observed a spectacular development of continuum mechanics including defects, granular structure and other deviations from the ideal linear elasticity. Special interests were concentrated on the micropolar and micromorphic continua. In such elastic continua, the real rotation can be accompanied by other kind of axial motion – the twist-bend motion. On above base, it was theoretically proved that so-called the seismic rotation waves could propagate through grained rocks, initially by Teisseyre [7] who initially attributed the appearance of rotation components in seismic wave by coupling the seismic waves with the micromorphic response of the medium characterized by the an internal/ granular structure [7, 8]. From this time, this possibility was extended to rocks with micro‐

© 2015 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited.

structure or defects [9, 10] or even without any internal structure [11 -13], due to the asymmetric stresses in the medium. On this base, various types of rotational waves have been discussed theoretically [14, 15].

It should be stressed that seismologists share different opinions about the nature of rotation waves – see the preface of a monograph on rotational seismology [16]. Perhaps, as it is underlined in preface of a book [16], still the majority believes that such rotation motions are not related to inner rotations but are directly related to rotation in the displacement field which may reach much higher magnitudes in materials with an internal structure than in homoge‐ nous layers; considering damages in the high buildings, there are many examples indicating enormous increase of rotation effect caused by consecutive impacts of seismic body and surface waves.

Nevertheless, all above aspects can be treated as elements of rotational seismology. It is an emerging field for studying all aspects of rotational ground motions induced by earthquakes, explosions, an ambient vibrations. It should be noticed that nowadays there is observed rapid growth of the rotational seismology interest in many geophysical fields of knowledge [17] which includes wide seismology disciplines, seismological apparatus, seismic-origin phe‐ nomena, physical and engineering aspects of earthquakes as well as geodesy.

However practical aspect of rotational events and phenomena investigation is connected with method of their recording, and different rotational seismology branches need different devices. For example, earthquake physics need devices operating with sensitivity below 10-9 rad/s/ Hz1/2, whereas the engineering of a strong-motion seismology devices operating with a frequency range 0.05-100 Hz with sensitivity 10-6-10-1 rad/s/Hz1/2 [18]. In this subject, it should be noticed that the seismic rotation waves were for the first time effectively recorded in Poland in 1976 [19]. Even though, from this time, waves or phenomena of this type have been studied in a few centers over the world, a further experimental verification of the existing rotational phenomena needs a new approach to the construction of the measuring devices, because the conventional seismometers are inertial sensors detecting only linear velocities [20]. Thus, during measurement of the rotation present in the seismic field, with the use of a special array or set of conventional seismometers (for example based on a set of two classical mechanical seismometers [21]), data are disturbed by linear movements [22]. Therefore, an innovative device is necessary to detect the rotational seismic phenomena/events. According to our knowledge we can confirm that the technical implementation of the Saganc effect [23] is the most proper way to measure rotation directly. One can find instances of such solution: a ring laser [24] as well as a fibre optic seismometer [25-27]. It gives the opportunity to carry out the measurements without any reference system.

It should be underlined that all experimental data recorded during earthquakes shows that rotational components are small in comparison to linear motions - less than 10% [14, 19] or have half of above value and exist with some delay regarding last one [25].

Based on above review in this chapter we present an analysis of a few examples of the rotational seismograms. Authors have concentrated on the local seismic events obtained at the Książ Observatory in Poland. These signals were obtained from two kinds of sensors described in section 2: the micro-array of TAPSs – Twin Antiparallel Pendulum Seismometers (also named rotation seismometers or double pendulum horizontal electromagnetic seismometers) and with the Sagnac interferometer of AFORS - Autonomous Fibre-Optic Rotational Seismometer, constructed at the Institute of Geophysics and the Military University of Technology, respec‐ tively. It should be also underlined that signals derived from micro-array include two components which, according to Asymmetric Continuum Theory, have character of rotational wave: rotation *ω* and shear *E* (called also pure shear) – see [14]. On the other side, the Sagnactype seismometers detect only rotation and are completely insensitive to translations [25, 28, 29] which may contaminate rotational measurements. Nevertheless, probably all the signals analyzed here suffer from some disturbances, this is referred to in the section 3.

structure or defects [9, 10] or even without any internal structure [11 -13], due to the asymmetric stresses in the medium. On this base, various types of rotational waves have been discussed

164 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

It should be stressed that seismologists share different opinions about the nature of rotation waves – see the preface of a monograph on rotational seismology [16]. Perhaps, as it is underlined in preface of a book [16], still the majority believes that such rotation motions are not related to inner rotations but are directly related to rotation in the displacement field which may reach much higher magnitudes in materials with an internal structure than in homoge‐ nous layers; considering damages in the high buildings, there are many examples indicating enormous increase of rotation effect caused by consecutive impacts of seismic body and surface

Nevertheless, all above aspects can be treated as elements of rotational seismology. It is an emerging field for studying all aspects of rotational ground motions induced by earthquakes, explosions, an ambient vibrations. It should be noticed that nowadays there is observed rapid growth of the rotational seismology interest in many geophysical fields of knowledge [17] which includes wide seismology disciplines, seismological apparatus, seismic-origin phe‐

However practical aspect of rotational events and phenomena investigation is connected with method of their recording, and different rotational seismology branches need different devices. For example, earthquake physics need devices operating with sensitivity below 10-9 rad/s/ Hz1/2, whereas the engineering of a strong-motion seismology devices operating with a frequency range 0.05-100 Hz with sensitivity 10-6-10-1 rad/s/Hz1/2 [18]. In this subject, it should be noticed that the seismic rotation waves were for the first time effectively recorded in Poland in 1976 [19]. Even though, from this time, waves or phenomena of this type have been studied in a few centers over the world, a further experimental verification of the existing rotational phenomena needs a new approach to the construction of the measuring devices, because the conventional seismometers are inertial sensors detecting only linear velocities [20]. Thus, during measurement of the rotation present in the seismic field, with the use of a special array or set of conventional seismometers (for example based on a set of two classical mechanical seismometers [21]), data are disturbed by linear movements [22]. Therefore, an innovative device is necessary to detect the rotational seismic phenomena/events. According to our knowledge we can confirm that the technical implementation of the Saganc effect [23] is the most proper way to measure rotation directly. One can find instances of such solution: a ring laser [24] as well as a fibre optic seismometer [25-27]. It gives the opportunity to carry out the

It should be underlined that all experimental data recorded during earthquakes shows that rotational components are small in comparison to linear motions - less than 10% [14, 19] or

Based on above review in this chapter we present an analysis of a few examples of the rotational seismograms. Authors have concentrated on the local seismic events obtained at the Książ Observatory in Poland. These signals were obtained from two kinds of sensors described in

have half of above value and exist with some delay regarding last one [25].

nomena, physical and engineering aspects of earthquakes as well as geodesy.

measurements without any reference system.

theoretically [14, 15].

waves.

## **2. Instrumentation for recording rotational components of the seismic events**

Figure 1 presents the general view of the measurement devices installed, at the beginning of July 2010, in the Książ Observatory, Poland (located at 50.84380333N, 16.291755 E). There are AFORS-1, the micro-array of seismometers consisting of two TAPSs (TAPS-1 and TAPS-2) oriented perpendicularly in the N-S and E-W directions, and other instruments such as accelerometers (parallel positioned with TAPSs), etc.

**Figure 1.** The general view of measurement devices installed in the Książ Observatory

The data detected by TAPSs (two channels for each of them) are stored by standard seismo‐ logical system KST while data detected by AFORS are stored both by FORS-Telemetric Server and KST. The KST system uses sampling of the signals with frequency equals 12,8 kHz. The process of data storing by KST uses frequency of 100 Hz. Figure 2 presents an example of a diagram with data collected on March 11th, 2011 at 6 h 58 min. (after the Honshu earthquake M=9.0 on March 11th, 2011 at 5 h 46 min. 23 s UT, recorded in Książ, Poland on March 11th, 2011 at 5 h 58 min. 35 s UT), used in previously presented analysis [30].

#### **2.1. Design of the Twin Antiparallel Pendulum Seismometers**

The micro-array of seismometers (system of two TAPSs perpendicularly oriented) is an experimental apparatus, devised in the Institute of Geophysics, and manufactured according to description presented below, on the base of short period SM-3 seismometers. This is one of the simplest micro-arrays for measuring the rotation and twist (shear) [14]. It was deployed at two Polish observatories, in Książ and Ojców (see [31]). The third identical set of sensors was used in Central Italy [32].

The idea of using the classical short period SM-3 seismometer as a new kind of mechanical rotational seismometer named TAPS is presented in Figure 3 [21]. It is a set of two SM-3 seismometers (named in Figure 3b as left – L and right – R) situated on a common axis and connected in parallel, but with opposite orientation. In the case of the ground motion contain‐ ing displacements *w*(*t*) and rotation *α*(*t*), the *u*(t) - electromotive force recorded by each simple seismometer contains a component of displacement (±*w*) and rotation motion (*α)* multiplied by a proper length of pendulum (*l*) [33]:

$$
\mu(t)\_{L,\ R} = \pm w(t) + l \cdot \alpha(t),\tag{1}
$$

where sign "+" and "-" are for R and L seismometer, respectively.

As one can see, in the case of identical two seismometers the rotational motions and displace‐ ment can be obtained from the sum and difference of the two recorded signals as:

$$\begin{aligned} \alpha(t) &= \left[\boldsymbol{\iota}(t)\_{\boldsymbol{R}} + \boldsymbol{\iota}(t)\_{\boldsymbol{L}}\right] / 2l, \quad \text{a} \\ \boldsymbol{w}(t) &= \left[\boldsymbol{\iota}(t)\_{\boldsymbol{R}} - \boldsymbol{\iota}(t)\_{\boldsymbol{L}}\right] / 2l. \quad \text{b} \end{aligned} \tag{2}$$

If the ground could be treated as a perfect rigid body, then the rotational motion recorded by sole one TAPS was identical to rotation. But rocks and the ground surface are not perfectly rigid; they transfer the mechanical waves due to slight, transient deformations which, seen along different axes, may different. Consequently, rotation *ω* in the plane of measurements and the given moment are calculated as a mean of rotational motions received at one and the other TAPS, while the twist *E* (pure shear) is obtained as half of their difference:

$$\begin{aligned} \alpha(t) &= [\alpha\_1(t) + \alpha\_2(t)] / 2, \quad \text{a} \\ E(t) &= [\alpha\_1(t) - \alpha\_2(t)] / 2. \quad \text{b} \end{aligned} \tag{3}$$

Relations (2a) and (2b) remain valid, however, only when both seismometers forming the system have exactly the same response characteristics. Because, as a matter of fact, the

M=9.0 on March 11th, 2011 at 5 h 46 min. 23 s UT, recorded in Książ, Poland on March 11th, 2011

166 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

The micro-array of seismometers (system of two TAPSs perpendicularly oriented) is an experimental apparatus, devised in the Institute of Geophysics, and manufactured according to description presented below, on the base of short period SM-3 seismometers. This is one of the simplest micro-arrays for measuring the rotation and twist (shear) [14]. It was deployed at two Polish observatories, in Książ and Ojców (see [31]). The third identical set of sensors was

The idea of using the classical short period SM-3 seismometer as a new kind of mechanical rotational seismometer named TAPS is presented in Figure 3 [21]. It is a set of two SM-3 seismometers (named in Figure 3b as left – L and right – R) situated on a common axis and connected in parallel, but with opposite orientation. In the case of the ground motion contain‐ ing displacements *w*(*t*) and rotation *α*(*t*), the *u*(t) - electromotive force recorded by each simple seismometer contains a component of displacement (±*w*) and rotation motion (*α)* multiplied

a

As one can see, in the case of identical two seismometers the rotational motions and displace‐

If the ground could be treated as a perfect rigid body, then the rotational motion recorded by sole one TAPS was identical to rotation. But rocks and the ground surface are not perfectly rigid; they transfer the mechanical waves due to slight, transient deformations which, seen along different axes, may different. Consequently, rotation *ω* in the plane of measurements and the given moment are calculated as a mean of rotational motions received at one and the

( ), *L R ut w t l t* (1)

*w t ut ut l* (2)

*Et t t* (3)

( ) , =± + × ( )

ment can be obtained from the sum and difference of the two recorded signals as:

( ) [ ( ) ( ) ]/2 , a [ ( ) ( ) ]/2 . b *R L R L*

*t ut ut l*

other TAPS, while the twist *E* (pure shear) is obtained as half of their difference:

 a

Relations (2a) and (2b) remain valid, however, only when both seismometers forming the system have exactly the same response characteristics. Because, as a matter of fact, the

waa

= + = - 1 2 1 2 ( ) [ ( ) ( )] / 2, a ( ) [ ( ) ( )] / 2. b

*t tt*

a

where sign "+" and "-" are for R and L seismometer, respectively.

( ) a

 = + = -

at 5 h 58 min. 35 s UT), used in previously presented analysis [30].

**2.1. Design of the Twin Antiparallel Pendulum Seismometers**

used in Central Italy [32].

by a proper length of pendulum (*l*) [33]:

**Figure 2.** Plots of the seismic events recorded in the Książ Observatory, Poland on March 11th, 2011 starting from 06:58 UT, after the Honshu M=9.0 earthquake [30]

containing displacements *w*(*t*) and rotation

multiplied by a proper length of pendulum (*l*) [33]:

where sign "+" and "-" are for R and L seismometer, respectively.

(

schematic view

connected in parallel, but with opposite orientation. In the case of the ground motion

each simple seismometer contains a component of displacement (±*w*) and rotation motion

(*t*), the *u*(t) - electromotive force recorded by

Figure 3. The TAPS – Twin Antiparallel Pendulum Seismometer: a) general view, b) **Figure 3.** The TAPS – Twin Antiparallel Pendulum Seismometer: a) general view, b) schematic view

pendulum seismometers are, inevitably, slightly different, the special TAPS channels calibra‐ tion algorithm is used. In this system, for the aim of comparing both sensors, it is possible to rotate the position of one seismometer in such a way that both the pendulum seismometers, suspended on the common axis become oriented in the same directions, one just above the other – this is the test position. The working and test position for the case of the horizontal seismometers are schematically shown in Figure 4. The records obtained in the test positions can differ mainly due to differences in their response characteristics, and to minimize these errors, the following left channel signal calibration procedure is usually applied: As one can see, in the case of identical two seismometers the rotational motions and displacement can be obtained from the sum and difference of the two recorded signals as: *t u t u t l <sup>R</sup> <sup>L</sup>* ( ) [ ( ) ( ) ]/ 2 , (2a) *wt u t u t l <sup>R</sup> <sup>L</sup>* [ ( ) ( ) ]/ 2 . (2b) If the ground could be treated as a perfect rigid body, then the rotational motion recorded

by sole one TAPS were identical to rotation. But rocks and the ground surface are not

$$
\dot{u}\_L = u\_L \sqrt{\sum u\_R \cdot u\_R / \sum u\_L \cdot u\_L} \tag{4}
$$

*t* , (3a)

where: *u*L and *uR* are electromotive forces recorded by left and right seismometers in test position. at one and the other TAPS, while the twist *E* (pure shear) is obtained as half of their difference:

> *t*

( ) [ ( ) ( )]/ 2 <sup>1</sup> <sup>2</sup>

pendulum seismometers are, inevitably, slightly different, the special TAPS channels

**Figure 4.** The TAPS: working a) and calibration b) positions of the pendulum seismometers

*t*

Nevertheless, there is some discrepancies due to the recording procedure in the case of the present of the difference of TAPS' pendulums attenuation characteristics. Figure 5 presents the simulation which indicates that there can be some errors in the data caused by the recording proceeding. The considered simulation was made for the attenuation difference equals |βL-βR| =0.05 between left and right seismometer attenuation. It is easy to see that the major error of the signal is present when the simulated rotation is characterized by smaller value of amplitude compared to the simulated translation component. However, this is the region where the seismic-origin rotation is expected. For above reason the process of TASP calibration seems to be an essential complication of the system work's correctness. Moreover, the extremely high sensitivity to the translational motions of the seismometers (preferred for the component of displacement detection) taken into account in their construction can limit the accuracy of such devices, too.

Figure 5. The simulated displacement and rotational components of the seismic event - a) and rotational signal detection by the TAPS - b) [22] From above mentioned reasons, the additional numerical procedures for improving the **Figure 5.** The simulated displacement and rotational components of the seismic event - a) and rotational signal detec‐ tion by the TAPS - b) [22]

TAPS performance may be applied, based on filtering in frequency [34] or in time [35] domains. The respective filters can then be applied to records in the normal working position to reduce the influences of non-equal operation of pendulum seismometers, presented above. However, these method use test position of the TAPS, that generally changes the condition of the TAPS operation. For this reason, another procedure of the recorded data processing, based on smoothing by the spline functions has been also proposed [36]. It should be noticed, that the main disadvantage of all listed methods is that they operate on recorded data, which can limit TAPS usefulness for some applications. In the research presented in this paper, the mentioned methods of signal correction were not used. **2.2 Design of the Autonomous Fibre-Optic Rotational Seismograph** From above mentioned reasons, the additional numerical procedures for improving the TAPS performance may be applied, based on filtering in frequency [34] or in time [35] domains. The respective filters can then be applied to records in the normal working position to reduce the influences of non-equal operation of pendulum seismometers, presented above. However, these methods use test position of the TAPS, that generally changes the condition of the TAPS operation. For this reason, another procedure of the recorded data processing, based on smoothing by the spline functions has been also proposed [36]. It should be noticed, that the main disadvantage of all listed methods is that they operate on recorded data, which can limit TAPS usefulness for some applications. In the research presented in this paper, the mentioned methods of signal correction were not used.

#### The AFORS-1, used in our research, is one of three such devices existing in Poland and manufactured on the base of fibre-optic gyroscope, all dedicated for direct measurement of **2.2. Design of the Autonomous Fibre-Optic Rotational Seismograph**

pendulum seismometers are, inevitably, slightly different, the special TAPS channels calibra‐ tion algorithm is used. In this system, for the aim of comparing both sensors, it is possible to rotate the position of one seismometer in such a way that both the pendulum seismometers, suspended on the common axis become oriented in the same directions, one just above the other – this is the test position. The working and test position for the case of the horizontal seismometers are schematically shown in Figure 4. The records obtained in the test positions can differ mainly due to differences in their response characteristics, and to minimize these

As one can see, in the case of identical two seismometers the rotational motions and displacement can be obtained from the sum and difference of the two recorded signals as:

*t u t u t l <sup>R</sup> <sup>L</sup>*

*wt u t u t l <sup>R</sup> <sup>L</sup>* [ ( ) ( ) ]/ 2 . (2b)

Figure 3. The TAPS – Twin Antiparallel Pendulum Seismometer: a) general view, b)

connected in parallel, but with opposite orientation. In the case of the ground motion

each simple seismometer contains a component of displacement (±*w*) and rotation motion

(*t*), the *u*(t) - electromotive force recorded by

, (1)

( ) ( ) , *u t w t l t <sup>L</sup> <sup>R</sup>*

168 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

containing displacements *w*(*t*) and rotation

a) b)

multiplied by a proper length of pendulum (*l*) [33]:

where sign "+" and "-" are for R and L seismometer, respectively.

(

where: *u*L and *uR* are electromotive forces recorded by left and right seismometers in test

*t*

Relations (2a) and (2b) remain valid, however, only when both seismometers forming the system have exactly the same response characteristics. Because, as a matter of fact, the pendulum seismometers are, inevitably, slightly different, the special TAPS channels

( ) [ ( ) ( )]/ 2 <sup>1</sup> <sup>2</sup>

1 2 *Et t t* ( ) [ ( ) ( )] / 2 

If the ground could be treated as a perfect rigid body, then the rotational motion recorded by sole one TAPS were identical to rotation. But rocks and the ground surface are not perfectly rigid; they transfer the mechanical waves due to slight, transient deformations which, seen along different axes, may different. Consequently, rotation *ω* in the plane of measurements and the given moment is calculated as a mean of rotational motions received at one and the other TAPS, while the twist *E* (pure shear) is obtained as half of their

Nevertheless, there is some discrepancies due to the recording procedure in the case of the present of the difference of TAPS' pendulums attenuation characteristics. Figure 5 presents the simulation which indicates that there can be some errors in the data caused by the recording proceeding. The considered simulation was made for the attenuation difference equals |βL-βR| =0.05 between left and right seismometer attenuation. It is easy to see that the major error of the signal is present when the simulated rotation is characterized by smaller value of amplitude compared to the simulated translation component. However, this is the region where the seismic-origin rotation is expected. For above reason the process of TASP calibration seems to

=×× å å ' / , *L L RR LL u u uu uu* (4)

( ) [ ( ) ( ) ]/ 2 , (2a)

*t* , (3a)

. (3b)

errors, the following left channel signal calibration procedure is usually applied:

**Figure 3.** The TAPS – Twin Antiparallel Pendulum Seismometer: a) general view, b) schematic view

**Figure 4.** The TAPS: working a) and calibration b) positions of the pendulum seismometers

*t*

position.

difference:

schematic view

rotational components existing in seismic events and having accuracy below 5·10-9 rad/s for 1 Hz detection band. The physical principle for these devices is the Sagnac effect [23] which is a result of difference between two beams propagating around closed optical path, in opposite direction. Figure 6a presents the basic principle of the Sagnac's experiment. The input light The AFORS-1, used in our research, is one of three such devices existing in Poland and manufactured on the base of fibre-optic gyroscope, all dedicated for direct measurement of rotational components existing in seismic events and having accuracy below 5‧10-9 rad/s for 1 Hz detection band.

beam is splitted by a beam splitter into a beam circulating in the loop in a clockwise - cw direction (Figure 6a - beam T) and a beam circulating in the same loop in a counterclockwise - ccw direction (Figure 6a – beam R). One can observe the interference pattern, in the output light, caused by the interference phenomenon of the two waves. In the case of the present of rotation with and angular rate represented by vector rad/s then a fringe shift ΔZ is observed in the output of the interferometer. The fringe shift is given by the formula [23]: /( ) <sup>0</sup> *Z S <sup>c</sup>* , (5) The physical principle for these devices is the Sagnac effect [23] which is a result of difference between two beams propagating around closed optical path, in opposite direction. Figure 6a presents the basic principle of the Sagnac's experiment. The input light beam is splitted by a beam splitter into a beam circulating in the loop in a clockwise - cw direction (Figure 6a - beam T) and a beam circulating in the same loop in a counterclockwise - ccw direction (Figure 6a – beam R). One can observe the interference pattern, in the output light, caused by the interfer‐ ence phenomenon of the two waves. In the case of the present of rotation with an angular rate

in which is a vector of sensor loop area, λ0 is the wavelength of the used light in vacuum, c is velocity of light in vacuum. According to the above formula a fringe shift is proportional to the cosine of angle between the axis of rotation and the normal to the sensor plane. There have been used the indigo mercury wavelength as well as the sensor area S = 866cm2 in the represented by vector *Ω* <sup>→</sup> rad/s then a fringe shift ΔZ is observed in the output of the interfer‐ ometer. The fringe shift is given by the formula [23]:

$$
\Delta Z = \vec{\Omega} \bullet \vec{S} / \langle \vec{\lambda\_0} \cdot \mathcal{c} \rangle \tag{5}
$$

in which *s* <sup>→</sup> is a vector of sensor loop area, λ<sup>0</sup> is the wavelength of the used light in vacuum, c is velocity of light in vacuum. According to the above formula a fringe shift is proportional to the cosine of angle between the axis of rotation and the normal to the sensor plane. There have been used the indigo mercury wavelength as well as the sensor area S = 866cm2 in the Sagnac's experiment [23] which gave the fringe shift equals 0.07 fringes for the rotational speed equal to 2 rps. Nevertheless other papers [37] indicate that the possible detectable fringe shift was of the order of 0.01 fringe in those time. Thus, perhaps Sagnac has been carried out the research with a maximal accuracy. Sagnac also established that the effect does not depend on the shape of surface area S or on the location of the centre of rotation, whereas future investigation shown that this effect it does not depend on the presence of a commoving refracting medium in the path of the beam [37].

Figure 6b presents the Sagnac interferometer in the optical fibre solution which uses optical waveguide of the long length L wound on sensor loop of the diameter D which was shown firstly in 1976 [38]. In this approach, a phase shift *∆ϕ* is produced between cw and ccw propagating light, given by:

$$
\Delta\phi = \frac{2\pi \cdot L \cdot D}{\lambda\_0 \cdot c} \Omega,\tag{6}
$$

where Ω is the rotational component perpendicular to the sensor loop. It is clearly to indicate that the sensitivity can be change by physical dimension of the sensor loop as well as by the length of the applied waveguide. It should be noticed that application of three such systems, which loops are jointly perpendicular, provides data about space vector of the rotation. One can obtain the position change in space by integrating the data in time domain. The above procedure is used in the configuration of the fibre optical gyroscope - FOG which now, nearly 40-years from 1976, is the best recognized interferometric sensor performed in the fibre-optic technology.

However, for a desired rotation rate in the range of 10-6 – 10-9 rad/s, the Sagnac effect generates a very small phase shift, so it is needful to separate and protect this effect from other distur‐ bances so that the Sagnac effect is the unique nonreciprocal effect in the device. For this reason all FOGs use, shown in Figure 7, the reciprocal configuration [39] which is also called minimum gyro-configuration [40]. This configuration guarantees an ideal equilibrium of two counterpropagating beams in the interferometer by obtaining true single mode operation at the common input-output port of the system. It is not disturbed even by non-single mode operation in the another part of the interferometer.

**Figure 6.** Schematic of the original Sagnac's experiment a) and its implementation in fibre optic technique b)

It is well known that each interferometric devices yield a cosine response. For above reason the detected signal practically do not change during the small changes of the rotation due to slow changes of the cosine function at the zero. In order to obtain higher sensitivity the operation point of the interferometer is shifted by applied additional phase shift modulation. The FOG utilizes the reciprocal phase modulator which is placed in the end of the sensor loop. It caused the modulation of the phase shift by propagation delay without any residual zero offset [41]. In this way one obtain the odd response instead of even one. An ultimate perform‐ ance is, however, obtained only if the unbiased response is perfectly even and the biasing modulation has only odd frequencies. Therefore, the applied phase modulator is also a delay line filter operating at the eigen-frequency [42] – the delay in the loop is equal to a half of modulation period which suppresses the residual even harmonic signals. Nowadays the FOG utilizes broad-band light source for eliminating the Kerr effect which produces the phase shift in the optical fiber Sagnac interferometer [43]. Such a broadband source is also needed to remove coherence related with noise and drift due to backscattering and backreflection as well as lack of rejection of the polarizer [44–46]. Finally, for achieving the high scale factor lineari‐ zation, FOG uses a digital phase step feedback [47] by the same reciprocal phase modulator as the biasing modulator and all-digital processing procedures where demodulation is carried by a digital subtracting and sampling of the modulated signal is obtained by using analoguedigital converter [48, 49].

**Figure 7.** The minimum configuration of the FOG [39]

represented by vector *Ω*

path of the beam [37].

technology.

operation in the another part of the interferometer.

propagating light, given by:

in which *s*

ometer. The fringe shift is given by the formula [23]:

D =W· ×

170 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

is velocity of light in vacuum. According to the above formula a fringe shift is proportional to the cosine of angle between the axis of rotation and the normal to the sensor plane. There have been used the indigo mercury wavelength as well as the sensor area S = 866cm2 in the Sagnac's experiment [23] which gave the fringe shift equals 0.07 fringes for the rotational speed equal to 2 rps. Nevertheless other papers [37] indicate that the possible detectable fringe shift was of the order of 0.01 fringe in those time. Thus, perhaps Sagnac has been carried out the research with a maximal accuracy. Sagnac also established that the effect does not depend on the shape of surface area S or on the location of the centre of rotation, whereas future investigation shown that this effect it does not depend on the presence of a commoving refracting medium in the

Figure 6b presents the Sagnac interferometer in the optical fibre solution which uses optical waveguide of the long length L wound on sensor loop of the diameter D which was shown firstly in 1976 [38]. In this approach, a phase shift *∆ϕ* is produced between cw and ccw

where Ω is the rotational component perpendicular to the sensor loop. It is clearly to indicate that the sensitivity can be change by physical dimension of the sensor loop as well as by the length of the applied waveguide. It should be noticed that application of three such systems, which loops are jointly perpendicular, provides data about space vector of the rotation. One can obtain the position change in space by integrating the data in time domain. The above procedure is used in the configuration of the fibre optical gyroscope - FOG which now, nearly 40-years from 1976, is the best recognized interferometric sensor performed in the fibre-optic

However, for a desired rotation rate in the range of 10-6 – 10-9 rad/s, the Sagnac effect generates a very small phase shift, so it is needful to separate and protect this effect from other distur‐ bances so that the Sagnac effect is the unique nonreciprocal effect in the device. For this reason all FOGs use, shown in Figure 7, the reciprocal configuration [39] which is also called minimum gyro-configuration [40]. This configuration guarantees an ideal equilibrium of two counterpropagating beams in the interferometer by obtaining true single mode operation at the common input-output port of the system. It is not disturbed even by non-single mode

p f

× × D= W <sup>×</sup> <sup>0</sup> <sup>2</sup> , *L D*

<sup>→</sup> is a vector of sensor loop area, λ<sup>0</sup> is the wavelength of the used light in vacuum, c

<sup>→</sup> rad/s then a fringe shift ΔZ is observed in the output of the interfer‐

<sup>0</sup> / ( ), <sup>r</sup> <sup>r</sup> *ZSc* (5)

*<sup>c</sup>* (6)

Currently, a digital processing of FOG systems is designed to record angular changes instead of rotation rates, thus, the optimization of such system to register the interesting phenomena from the rotational seismology point of view is problematic. Therefore it should be emphasized that the AFORS construction based on experiences according to the FOG development described above, but with system optimization for a direct measurement of the rotation rate only [22]. Such an approach gives a system which through a direct use of the Sagnac effect can limit drift influence on a device operation.

A detailed description of the AFORS system was published previously [29, 30, 50], hence here we summarized the above data regarding AFORS-1 construction, calibration and manage‐ ment. The second device - AFORS-2 is located in Warsaw (Poland) for initial works connected to the investigation of the irregular engineering construction torsional response and the interstory drift [51]. We anticipate that the new device, based on AFORS-1 and -2, AFORS-3 will be construed in the 2014 which gives us the opportunity to mount new innovative system instead of FORS-II assembled in seismological observatory Ojców, Poland [52].

The AFORS uses the minimum configuration of the FOG, however opposite of it, AFORS operates in open-loop architecture with digital data processing [53]. This technical solution is motivated by the fact that rotation events (Ω) are registered as sudden changes of rotational rate which amplitude is determined in a direct way from the Sagnac phase shift (Δφ) by following equation [37]:

$$
\Delta \Omega = S\_o \cdot \Delta \phi = \frac{\lambda \cdot c}{2\pi \cdot D \cdot L} \cdot \Delta \phi \tag{7}
$$

where S0 is the optical constant of interferometer which depends on the fundamental param‐ eters of fibre coil.

Upper part of Figure 8 presents the block diagram of the AFORS-1 optical part configuration. The AFORS-1 construction, designed according to the minimum-gyro configuration, contains of the: SLED diode (ΔB=31.2 nm, λ0 = 1305.7 nm, Pout= 9.43 mW; *Exalos*, Switzerland), isolator (α=0.34 dB, 39 dB isolation; *FCA*, Poland), depolarizator (DOP<5%, α=0.20 dB; *Phoenix Photonics*, UK), two mounted-in-line polarizators (ε=43 dB, α=0.45 dB each; *Phoenix Photonics*, UK), two X-couplers (α=0.20 dB; *Phoenix Photonics*, UK), sensor loop, phase modulator (*Piezomechanik GmbH*, Germany) and detector (S=0.9 A/W; *Optoway Technology Inc.*, Taiwan). The SLED diode has been chosen for two reasons. Firstly, SLED diode is the broad-band light source, which minimalizes the disadvantageous polarization as well as coherence effects [54, 55]. Additionally, this diode gives an opportunity to obtain a high optical power, which has a direct influence on the system sensitivity. In order to isolate the diode from the backscattering we applied the optical fibre isolator. To ensure truly depolarized light the depolarizer is used before the polarizers which guarantee the single mode operation in the entirely system as well as fulfil function of the filter. Two couplers ensure that both propagating waves have the same optical path. The detector's system consists of a PIN diode and a preamplifier. The sensor loop has been made by winding 15 000 m of the SMF-28e+ length on a special composite material which includes permalloy particles for shielding the system from external magnetic field. The double-quadrupole method of winding [56] was used in order to stabilize the work system during the temperature fluctuation. The technical optimization of AFORS-1 construction (optical fibre of 15 000 m with attenuation equals 0.451 dB/km in 0.63 m sensor loop) allows to obtain a theoretical sensitivity equal to 1.97‧10−9 rad/s/Hz1/2 in quantum noise limitation.

Currently, a digital processing of FOG systems is designed to record angular changes instead of rotation rates, thus, the optimization of such system to register the interesting phenomena from the rotational seismology point of view is problematic. Therefore it should be emphasized that the AFORS construction based on experiences according to the FOG development described above, but with system optimization for a direct measurement of the rotation rate only [22]. Such an approach gives a system which through a direct use of the Sagnac effect can

172 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

A detailed description of the AFORS system was published previously [29, 30, 50], hence here we summarized the above data regarding AFORS-1 construction, calibration and manage‐ ment. The second device - AFORS-2 is located in Warsaw (Poland) for initial works connected to the investigation of the irregular engineering construction torsional response and the interstory drift [51]. We anticipate that the new device, based on AFORS-1 and -2, AFORS-3 will be construed in the 2014 which gives us the opportunity to mount new innovative system

The AFORS uses the minimum configuration of the FOG, however opposite of it, AFORS operates in open-loop architecture with digital data processing [53]. This technical solution is motivated by the fact that rotation events (Ω) are registered as sudden changes of rotational rate which amplitude is determined in a direct way from the Sagnac phase shift (Δφ) by

*D L*

 f

<sup>×</sup> W= ×D = ×D × × (7)

p

where S0 is the optical constant of interferometer which depends on the fundamental param‐

Upper part of Figure 8 presents the block diagram of the AFORS-1 optical part configuration. The AFORS-1 construction, designed according to the minimum-gyro configuration, contains of the: SLED diode (ΔB=31.2 nm, λ0 = 1305.7 nm, Pout= 9.43 mW; *Exalos*, Switzerland), isolator (α=0.34 dB, 39 dB isolation; *FCA*, Poland), depolarizator (DOP<5%, α=0.20 dB; *Phoenix Photonics*, UK), two mounted-in-line polarizators (ε=43 dB, α=0.45 dB each; *Phoenix Photonics*, UK), two X-couplers (α=0.20 dB; *Phoenix Photonics*, UK), sensor loop, phase modulator (*Piezomechanik GmbH*, Germany) and detector (S=0.9 A/W; *Optoway Technology Inc.*, Taiwan). The SLED diode has been chosen for two reasons. Firstly, SLED diode is the broad-band light source, which minimalizes the disadvantageous polarization as well as coherence effects [54, 55]. Additionally, this diode gives an opportunity to obtain a high optical power, which has a direct influence on the system sensitivity. In order to isolate the diode from the backscattering we applied the optical fibre isolator. To ensure truly depolarized light the depolarizer is used before the polarizers which guarantee the single mode operation in the entirely system as well as fulfil function of the filter. Two couplers ensure that both propagating waves have the same optical path. The detector's system consists of a PIN diode and a preamplifier. The sensor loop has been made by winding 15 000 m of the SMF-28e+ length on a special composite material

instead of FORS-II assembled in seismological observatory Ojców, Poland [52].

2 *<sup>o</sup> <sup>c</sup> <sup>S</sup>*

f

limit drift influence on a device operation.

following equation [37]:

eters of fibre coil.

**Figure 8.** General schema and view of the AFORS optical head (generation of the Sagnac phase shift proportional to the measured rotation rate)

It should be emphasised that in the AFORS construction we have applied the special processing unit ASPU (Figure 9), which enables to obtain the detected rate of rotation in a direct way from the measured Sagnac phase shift (7). The ASPU detects the rotation rate (Ω) by selection and conversion of the first (A1ω) and second (A2ω) amplitude of the harmonic output signal [u(t)] using the following formula [50]:

$$\boldsymbol{\Omega} = \mathbf{S}\_o \cdot \arctan[\mathbf{S}\_e \cdot \boldsymbol{\mu}(t)] = \mathbf{S}\_o \cdot \arctan[\mathbf{S}\_e \cdot \frac{A\_{1o}}{A\_{2o}}] \,\tag{8}$$

in which *S*e is the electrical constant connected to specification of the used instrumentations and received by calibrating the sensor, while *S*<sup>o</sup> is the optical constant determined also during the calibration process which is described below. In order to eliminate a discontinuity the formula (8) uses the arc tangent which is extended to the four quarters (−π, π) after the Fourier transform. The ASPU utilizes the synchronous detection in a digital form. The 32 bit digital signal processor realizes all necessary processing processes including calculation the rate of rotation in a real time as well as data recording in the SD card. The electronic part sends also the stored data via fibre patch cord to the GSM/GPS modem which is connected FORS-Telemetric Server [30, 50]. The fundamental time constant equals 4.7104 ms and its value resulted from the used quartz oscillator. The multiplication (maximum multiplication is equal to 27 ) of the time constant allows to adjust the sampling time. This approach gives detection frequency bandpass from 0.83 Hz to 106.15 Hz. This detection band is required to detect the rotational seismic-origin events. Furthermore the electronic part is equipped with digital-toanalogue converter which enable to store the data in the analogue form by the standard recording system KST.

**Figure 9.** General schema and view of the AFORS's Autonomous Signal Processing Unit (rotation calculation and re‐ cording)

The calibration process was realized basing on the measurement of the defined slow rotation connected to the vector of Earth rotation in Warsaw, Poland (i.e. ΩE= 9.18 deg/h ≡ 4.45∙10-5rad/ s for *ϕ* = 52°20''). AFORS was mounted vertically on a special rotation table (Figure 10a) and then rotated so that the sensor loop was directed to the North, South, East and West. The detected signal was equalled to zero for East-West (sensor loop collinear with the Earth rotation axis) while the signal was maximal, equal to ± 4.45∙10-5rad/s, for North-South (the sensor loop perpendicular to the vector component of Earth rotation). During the calibration procedure in the first step were determined the position for maximal signals, North and South, then, the position of the sensor for the West and East was defined as the midpoint between those two signals because of problems with determination this position basing on searching of signals equal zero. The maximal signals were obtained with accuracy equals 0.5 deg. In order to eliminate the drift phenomenon the 10 night hours averaging signal was applied. The above procedure allows for scaling the system and determining the constant operation parameters – optical *S*o and electrical *S*e. For AFORS-1 the following values of the above constants were obtained: S0 = 0.043 s−1, Se *=* 0.0144. In order to experimental determination of the accuracy for particular device [50], which have been made according to AFORS production technology, we measured the noise level for each of them. Nevertheless the measurements were carried out at Military University of Technology, Warsaw, Poland. The place of the research could provide deviations due to urban noises. The received accuracy is equal to 5.07‧10−9 rad/s and 5.51‧10−8 rad/s, respectively, for the lower and higher working detection frequency band, as shown in Figure 10b. Additional Figure 10b shows also measured parameters for second system - AFORS-2 (theoretical sensitivity in quantum noise limitation equals 2.46‧10−9 rad/s/Hz1/2, accuracy in detection band at level of 4.81‧10−9 rad/s and 6.11‧10-8 rad/s). It should be noted that the linear dependence of AFORSs accuracy on the detection frequency band is an advantage of this system.

**Figure 10.** The calibration and investigation of AFORSs accuracies: a) general view of AFORS-1 during the calibration process with scheme showing its idea, b) the accuracy measured for the chosen detection frequency band for AFORS-1 and AFORS-2

**Figure 9.** General schema and view of the AFORS's Autonomous Signal Processing Unit (rotation calculation and re‐

174 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

The calibration process was realized basing on the measurement of the defined slow rotation connected to the vector of Earth rotation in Warsaw, Poland (i.e. ΩE= 9.18 deg/h ≡ 4.45∙10-5rad/ s for *ϕ* = 52°20''). AFORS was mounted vertically on a special rotation table (Figure 10a) and then rotated so that the sensor loop was directed to the North, South, East and West. The detected signal was equalled to zero for East-West (sensor loop collinear with the Earth rotation axis) while the signal was maximal, equal to ± 4.45∙10-5rad/s, for North-South (the sensor loop perpendicular to the vector component of Earth rotation). During the calibration procedure in the first step were determined the position for maximal signals, North and South, then, the position of the sensor for the West and East was defined as the midpoint between those two signals because of problems with determination this position basing on searching of signals equal zero. The maximal signals were obtained with accuracy equals 0.5 deg. In order to eliminate the drift phenomenon the 10 night hours averaging signal was applied. The above procedure allows for scaling the system and determining the constant operation parameters – optical *S*o and electrical *S*e. For AFORS-1 the following values of the above constants were obtained: S0 = 0.043 s−1, Se *=* 0.0144. In order to experimental determination of the accuracy for particular device [50], which have been made according to AFORS production technology, we measured the noise level for each of them. Nevertheless the measurements were carried out at Military University of Technology, Warsaw, Poland. The place of the research could provide deviations due to urban noises. The received accuracy is equal to 5.07‧10−9 rad/s and 5.51‧10−8 rad/s, respectively, for the lower and higher working detection frequency band, as shown in Figure 10b. Additional Figure 10b shows also measured parameters for second system - AFORS-2 (theoretical sensitivity in quantum noise limitation equals 2.46‧10−9 rad/s/Hz1/2, accuracy in detection band at level of 4.81‧10−9 rad/s and 6.11‧10-8 rad/s). It should be noted that the linear dependence of AFORSs accuracy on the detection frequency band is an

cording)

advantage of this system.

## **3. Analysis of rotational components of the seismic fields caused by local events**

In this section we present analysis of data obtained at Książ Observatory, reveal the rotational components presence in entire seismograms (from P-wave arrival onwards), for the cases of local seismic events, of the mining (Lubin on January 20th, 2011, two events starting at 04 h 59 min. 1 s UT - shown below as Figure 11) and tectonic (Jarocin on January 6th, 2012, the event starting at 15 h 38 min. 10 s UT - shown below as Figure 12) provenience.

The results were obtained directly from KST recording system and they include five plots: channels 1 and 2 for TAPS-1; channel 3 for AFORS-1; channels 4 and 5 for TAPS-2. The TAPSs' records show linear motions that appeared during the earthquakes, and rotational components are calculated as described in the section 2.1. The channel 3 for AFORS-1 shows rotational oscillations measured in a direct way.

As one can see, the both kinds of devices (AFORS-1 as well as set of micro-array of TAPSs) recorded the events in the same time, which can confirm some correlation between devices. However the following investigation needs an additional data proceedings. To limit noise influence on recorded signals the average procedure in the beginning has been applied. From above mentioned reason the recorded seismic events have been averaged in moving windows of 100 samples (which is equal to period of 1 second).

The results of above operation are presented in Figures 13a-13c respectively for above three events. Consistently, we present five plots for all of them. The first plot, named TAPS-1 channel 2, presents the velocity of linear ground motion in m/s registered by second seismometer in this device. Second diagram shows channel 1 of TAPS-2. It should be noticed that second channel for any TAPS, after change of sign, has very similar plot to the first channel, so they

**Figure 11.** Plots of two seismic events with source in Lubin area: TAPS – ground motion velocity, AFORS – ground motion rotation rate

**Figure 12.** Plots of the seismic event with source in Jarocin area: TAPS – ground motion velocity, AFORS – ground motion rotation rate

are not presented both in our Figures. Third plot, named AFORS, presents the rotation velocity in rad/s, registered directly by AFORS-1. The result of measurement of the same component, but using the four simultaneous signals from micro-array of TAPSs (the procedure is described in section 2.1), is presented as plot four named Rotation from TAPS. Finally, last plot named Twist from TAPS, presents twist component obtained from the same micro-array in accord with, mentioned in the introduction, the Asymmetric Continuum Theory [14] – also in rad/s.

**Figure 13.** (a). Results for the first event in the Lubin area registered on January 20th, 2011; (b). Results for the second event in the Lubin area registered on January 20th, 2011; (c). Results for the Jarocin area earthquake registered on Janu‐ ary 6th, 2012

are not presented both in our Figures. Third plot, named AFORS, presents the rotation velocity in rad/s, registered directly by AFORS-1. The result of measurement of the same component, but using the four simultaneous signals from micro-array of TAPSs (the procedure is described in section 2.1), is presented as plot four named Rotation from TAPS. Finally, last plot named Twist from TAPS, presents twist component obtained from the same micro-array in accord with, mentioned in the introduction, the Asymmetric Continuum Theory [14] – also in rad/s.

**Figure 12.** Plots of the seismic event with source in Jarocin area: TAPS – ground motion velocity, AFORS – ground

**Figure 11.** Plots of two seismic events with source in Lubin area: TAPS – ground motion velocity, AFORS – ground

176 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

motion rotation rate

motion rotation rate

Even though the results presented in Figures 13a-13c show similar time of occurrence of the rotational components recorded by the AFORS-1 and calculated from TAPSs, their shape differs, and inevitably the correlation coefficients between them are low (though greater than zero). These coefficients are presented in Table 1, for both events recorded on January 20th, 2011, and for their selected parts. This selection consists of: time-period when P waves arrive – 2 seconds in each case; time period of firsts S waves arrivals – again 2 seconds, and a timeperiod when great S-type oscillations dominate; here we choose twenty seconds in each case (such unusually high amplitudes of low frequency oscillations, dominating in the late stage of the tremor, characterize the seismic field generated by mining seismic events in the Lubin area and received at Książ observatory).


**Table 1.** The correlation coefficients

Additionally, correlation between both rotational components calculated from TAPSs record‐ ings, that is – rotation and twist – was checked too, for the same chosen time-periods. This appeared generally high (especially in the second event), which confirms previous observa‐ tions by KP. Teisseyre that in the recordings of seismic events made with a set of TAPSs, there usually occurs conformance between rotation and twist, either direct or reverse.

Dissimilarity between simultaneous rotation recordings obtained from AFORS and the microarray of TAPSs may be explained by different characteristics of the used instruments or by certain errors or/and noise present in one or the other side of compared results, or in both. Here, there is dramatic difference in spectra (Figure 14), that of AFORS is always much longer. For the analyzed case of mining events, the spectrum of AFORS signal bears high amplitudes in the range of 2 – 8 Hz. Spectra of all the signals and rotational components obtained from TAPSs are short – they practically decrease to zero level at about 20 Hz – and bear sharp maximum at about 0.5 Hz, while the linear signals have also wide area of relatively high amplitudes in the range of 1 – 8 Hz. Moreover, the signals from AFORS bear high percentage of noise, probably of electronic provenience.

Even though the results presented in Figures 13a-13c show similar time of occurrence of the rotational components recorded by the AFORS-1 and calculated from TAPSs, their shape differs, and inevitably the correlation coefficients between them are low (though greater than zero). These coefficients are presented in Table 1, for both events recorded on January 20th, 2011, and for their selected parts. This selection consists of: time-period when P waves arrive – 2 seconds in each case; time period of firsts S waves arrivals – again 2 seconds, and a timeperiod when great S-type oscillations dominate; here we choose twenty seconds in each case (such unusually high amplitudes of low frequency oscillations, dominating in the late stage of the tremor, characterize the seismic field generated by mining seismic events in the Lubin area

178 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

0.092 0.063

0.600 0.894

0.200 0.354 0.073 0.187 0.050 0.140

0.166 0.483 0.641 0.534 0.724 0.958

P 128.40 – 130.40 s

great S 30.00 – 50.00 s

Additionally, correlation between both rotational components calculated from TAPSs record‐ ings, that is – rotation and twist – was checked too, for the same chosen time-periods. This appeared generally high (especially in the second event), which confirms previous observa‐ tions by KP. Teisseyre that in the recordings of seismic events made with a set of TAPSs, there

Dissimilarity between simultaneous rotation recordings obtained from AFORS and the microarray of TAPSs may be explained by different characteristics of the used instruments or by certain errors or/and noise present in one or the other side of compared results, or in both. Here, there is dramatic difference in spectra (Figure 14), that of AFORS is always much longer. For the analyzed case of mining events, the spectrum of AFORS signal bears high amplitudes in the range of 2 – 8 Hz. Spectra of all the signals and rotational components obtained from TAPSs are short – they practically decrease to zero level at about 20 Hz – and bear sharp maximum at about 0.5 Hz, while the linear signals have also wide area of relatively high amplitudes in the range of 1 – 8 Hz. Moreover, the signals from AFORS bear high percentage

usually occurs conformance between rotation and twist, either direct or reverse.

**Second event 05 h 01 min., M=3.3 128.40 – 234.45 s**

> S 137.50 – 139.50 s

great S 146.00 – 166.00 s

**First event 04 h 59 min., M=3.1 17 – 107.75 s**

> S 26.00 – 28.00 s

and received at Książ observatory).

P 17.00 – 19.00 s

of noise, probably of electronic provenience.

**20.01.2011. Lubin**

AFORS – Rot TAPS

Twist TAPS – ROT TAPS

Wave type time-period

AFORS – Rot TAPS

Twist TAPS – Rot TAPS

**Table 1.** The correlation coefficients

**Figure 14.** Spectra of linear and rotational signals, from ones of analysed seismic mining events, recorded on January 20th, 2011 at Książ observatory. The second one has the similar spectra

To find similarities in the obtained results in other way than just by sight, the following analysis has been applied. First – any of compared data chains was transformed into chain of absolute values (moduli). Then, the chains of moving averages of these moduli are created, with the window length of 100 samples, which is equivalent to 1 s. Here, absolute values of rotation (velocities) were compared – these from AFORS with those calculated from set of TAPSs. Further, analogical moving averages were investigated, but calculated from moduli of all four signals recorded by the TAPSs. If the rotation obtained from AFORS is symbolized with ω<sup>o</sup> , rotation obtained from the TAPSs with *ω*, mean signal modulus from micro-array at the given sample with *ū*, and length of window used in moving average calculation with *w,* then formulae for described moving averages are as follows:

$$\begin{aligned} \frac{\mathbf{u}\_0^0}{\mathbf{u}\_0^0} &= \frac{\sum\_{i=1}^{i=w} |\alpha\_i^0|}{w}, & \mathbf{a} \\ \frac{\mathbf{u}\_0^i}{\mathbf{u}\_0^0} &= \frac{\sum\_{i=1}^{i=w} |\alpha\_i|}{w}, & \mathbf{b} \\ \frac{\mathbf{u}\_i^{i=w}}{\mathbf{u}\_i} &= \frac{\left(\frac{|\ln\_1| + |\ln\_2| + |\ln\_3| + |\ln\_4|}{4}\right)\_i}{w}, & \mathbf{c} \end{aligned} \tag{9}$$

Results of this analysis are shown in Figures 15-17, which all have the same scheme. Diagrams a) show the plot of moving average of absolute values of the rotation rate obtained from AFORS; diagrams c) – analogical averages of rotation rate calculated from TAPSs' data; diagrams e) – analogical averages of the mean signals moduli from TAPSs – as in formula (9c). The blue plots presented in diagrams b) represent the moving correlation coefficient between moving averages of absolute rotation from AFORS and its analogue from TAPSs (compare the plots in diagrams a) and c) described mathematically by equations (9a) and (9b)). This coefficient is calculated for a window of 100 samples (1s). Additionally, in the same diagram we present reference thick lines – orange or mauve, and turquoise – which should facilitate the comparison of correlation coefficient with compared chains. The procedure for obtaining the upper reference line is following: create normalized chain (9b) to (9a) by comparing both maximum values, as (9b'). Next, make new chain as sum of (9a) with (9b'), and normalize it to 1. Thus we have obtained a doubly–normalized mean chain which joins shapes of the original two chains. The turquoise reference line is analogical to orange one, but multiplied by -1. Purpose of this line presence is to facilitate comparison of stages of high negative correla‐ tions between compared chains, again with the described doubly–normalized averages. Analogically, curves presented in diagrams d) and f) are the plots of the correlation coefficient in a moving window of 100 samples; in d) – between averages plotted in diagrams c) and e), and in f) – between averages plotted in e) and a). Reference lines are produced in analogical way as for diagrams b); the upper one is mauve in diagrams f). Figure 15 shows results of such analysis applied to recordings of first event from Lubin area; Figures 16 and 17 are made for second event from Lubin area and for Jarocin earthquake, in the same methodology.

Comparison of the moving correlation coefficients with the moving averages allows to find certain rule. In time-periods when main seismic phase arrive – as P and S (for local distances, it might be jointly for example Pg and Pb phases and analogically Sg and Sb in the S-type phases family), all investigated correlations between moving averages of the absolute signals are generally high. These are some of the time-periods in which blue line in the diagrams b), d) and f) is near 1, and the upper reference line rises. More interestingly, these time-periods starts slightly before any noticeable rise in initial moving averages, despite facts that all the moving windows had the same length. This phenomenon may have two causes: certain common order in concerned signals starts just before noticeable arrival of seismic waves, or/and this is a mere effect of filtration (which used in every contemporary seismic recording system).

The chosen time-periods of high correlations and rise of the moving averages are as follows.

For the first seismic event from Lubin - two time periods: from 16.2 to 18.5 s, this include arrival of P waves, and from 25.8 to 27 s, which include S waves arrival (see Table 1). For the second seismic event from Lubin – only one time period, from 127.9 to 129.5 s, which include arrival of P waves. For the Jarocin earthquake – one non-continuous time period, for diagrams b) and f): 21.7 – 24.1 s and for diagram d) : 20.9 – 24.1 s. This time-period, in all three diagrams, starts before arrival of P waves and comprises arrival of this seismic phase.

Results of this analysis are shown in Figures 15-17, which all have the same scheme. Diagrams a) show the plot of moving average of absolute values of the rotation rate obtained from AFORS; diagrams c) – analogical averages of rotation rate calculated from TAPSs' data; diagrams e) – analogical averages of the mean signals moduli from TAPSs – as in formula (9c). The blue plots presented in diagrams b) represent the moving correlation coefficient between moving averages of absolute rotation from AFORS and its analogue from TAPSs (compare the plots in diagrams a) and c) described mathematically by equations (9a) and (9b)). This coefficient is calculated for a window of 100 samples (1s). Additionally, in the same diagram we present reference thick lines – orange or mauve, and turquoise – which should facilitate the comparison of correlation coefficient with compared chains. The procedure for obtaining the upper reference line is following: create normalized chain (9b) to (9a) by comparing both maximum values, as (9b'). Next, make new chain as sum of (9a) with (9b'), and normalize it to 1. Thus we have obtained a doubly–normalized mean chain which joins shapes of the original two chains. The turquoise reference line is analogical to orange one, but multiplied by -1. Purpose of this line presence is to facilitate comparison of stages of high negative correla‐ tions between compared chains, again with the described doubly–normalized averages. Analogically, curves presented in diagrams d) and f) are the plots of the correlation coefficient in a moving window of 100 samples; in d) – between averages plotted in diagrams c) and e), and in f) – between averages plotted in e) and a). Reference lines are produced in analogical way as for diagrams b); the upper one is mauve in diagrams f). Figure 15 shows results of such analysis applied to recordings of first event from Lubin area; Figures 16 and 17 are made for

180 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

second event from Lubin area and for Jarocin earthquake, in the same methodology.

system).

Comparison of the moving correlation coefficients with the moving averages allows to find certain rule. In time-periods when main seismic phase arrive – as P and S (for local distances, it might be jointly for example Pg and Pb phases and analogically Sg and Sb in the S-type phases family), all investigated correlations between moving averages of the absolute signals are generally high. These are some of the time-periods in which blue line in the diagrams b), d) and f) is near 1, and the upper reference line rises. More interestingly, these time-periods starts slightly before any noticeable rise in initial moving averages, despite facts that all the moving windows had the same length. This phenomenon may have two causes: certain common order in concerned signals starts just before noticeable arrival of seismic waves, or/and this is a mere effect of filtration (which used in every contemporary seismic recording

The chosen time-periods of high correlations and rise of the moving averages are as follows.

For the first seismic event from Lubin - two time periods: from 16.2 to 18.5 s, this include arrival of P waves, and from 25.8 to 27 s, which include S waves arrival (see Table 1). For the second seismic event from Lubin – only one time period, from 127.9 to 129.5 s, which include arrival of P waves. For the Jarocin earthquake – one non-continuous time period, for diagrams b) and f): 21.7 – 24.1 s and for diagram d) : 20.9 – 24.1 s. This time-period, in all three diagrams, starts

before arrival of P waves and comprises arrival of this seismic phase.

**Figure 15.** Relations of rotations and linear signals at the first event in Lubin area registered on January 20th, 2011. Dia‐ grams: a) moving average of absolute values of AFORS – signal; b) correlation coefficient between (a) and (c) in mov‐ ing window – blue line, orange reference line – doubly normalized means of (a) and (c), turquoise – the same as orange but with reversed sign; c) moving average of absolute values of rotations obtained from TAPSs; d) correlation coeffi‐ cient between (c) and (e) in moving window, orange reference line – doubly normalized means of (c) and (e), turquoise – the same as orange but with reversed sign; e) moving average of absolute values of four channels of TAPSs; f) corre‐ lation coefficient between (e) and (a) in moving window, mauve reference line – doubly normalized means of (e) and (a), turquoise – the same as mauve but with reversed sign

**Figure 16.** Relations of rotations and linear signals at the second event in Lubin area registered on January 20th, 2011. Diagrams descriptions as in Fig. 15

**Figure 17.** Relations of rotations and linear signals at the event in Jarocin area registered on January 6th, 2012. Diagrams descriptions as in Fig. 15

We did not find yet any other rules, especially – we did not find any relation between episodes of negative correlations (near -1) and the initial moving averages. We suppose that such comparison method may be useful in analysis of various chains, and especially their moving

**Figure 16.** Relations of rotations and linear signals at the second event in Lubin area registered on January 20th, 2011.

182 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

Diagrams descriptions as in Fig. 15

averages, as in this work. Crucial point is that not the original signals, but chains of their absolute values are compared.

## **4. Conclusions**

Simultaneous measurements of the rotations in seismic field with the use of completely different instruments – here AFORS-1 which is the Sagnac interferometer and the micro-array of TAPSs allow for comparison of the used equipment. In this work, such comparison revealed that signals differ significantly, to the degree which complicates analysis. From both kind of instruments, rotations are obtained in the same time-periods, but their plots differ. These differences are attributed partly to difference in instruments spectra and partly to disturbances in the signals, of technical provenience. Nevertheless, an analysis using the moving averages of absolute signals values, and consequently also coefficients of correlation between these averages confirmed common roots of these recorded signals, despite all their imperfections.

Research on seismic rotational effects, especially in buildings and other large constructions is widely recognized as very important and therefore these studies flourish. On the other hand, rotational components in the seismic field are also studied in various ways, but even existence of these components still evoke controversy. Presence of these components in seismograms, especially in their initial part which, according to classical theory of elasticity, contain only compressional waves, is explained in various ways. Authors believe that no one contemporary explanation is complete and proven, but this not preclude usefulness of further studies.

## **Acknowledgements**

This work was done in 2013-2014 under the financial support of the Polish Ministry of Science and Higher Education under Key Project POIG.01.03.01-14-016/08 "New photonic materials and their advanced application", the MUT statutory activity PBS-850 and partially the the Polish National Centre for Research and Development under contract No PBS1/B3/7/2012.

## **Author details**

Anna Kurzych1 , Krzysztof P. Teisseyre2 , Zbigniew Krajewski1 and Leszek R. Jaroszewicz1\*

\*Address all correspondence to: jarosz@wat.edu.pl

1 Institute of Applied Physics, Military University of Technology, Warsaw, Poland

2 Institute of Geophysics, Polish Academy of Sciences, Warsaw, Poland

## **References**

averages, as in this work. Crucial point is that not the original signals, but chains of their

184 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

Simultaneous measurements of the rotations in seismic field with the use of completely different instruments – here AFORS-1 which is the Sagnac interferometer and the micro-array of TAPSs allow for comparison of the used equipment. In this work, such comparison revealed that signals differ significantly, to the degree which complicates analysis. From both kind of instruments, rotations are obtained in the same time-periods, but their plots differ. These differences are attributed partly to difference in instruments spectra and partly to disturbances in the signals, of technical provenience. Nevertheless, an analysis using the moving averages of absolute signals values, and consequently also coefficients of correlation between these averages confirmed common roots of these recorded signals, despite all their imperfections.

Research on seismic rotational effects, especially in buildings and other large constructions is widely recognized as very important and therefore these studies flourish. On the other hand, rotational components in the seismic field are also studied in various ways, but even existence of these components still evoke controversy. Presence of these components in seismograms, especially in their initial part which, according to classical theory of elasticity, contain only compressional waves, is explained in various ways. Authors believe that no one contemporary explanation is complete and proven, but this not preclude usefulness of further studies.

This work was done in 2013-2014 under the financial support of the Polish Ministry of Science and Higher Education under Key Project POIG.01.03.01-14-016/08 "New photonic materials and their advanced application", the MUT statutory activity PBS-850 and partially the the Polish National Centre for Research and Development under contract No PBS1/B3/7/2012.

, Zbigniew Krajewski1

1 Institute of Applied Physics, Military University of Technology, Warsaw, Poland

2 Institute of Geophysics, Polish Academy of Sciences, Warsaw, Poland

and Leszek R. Jaroszewicz1\*

absolute values are compared.

**4. Conclusions**

**Acknowledgements**

**Author details**

Anna Kurzych1

, Krzysztof P. Teisseyre2

\*Address all correspondence to: jarosz@wat.edu.pl


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## **Earthquakes and Dams**

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[45] Lefèvre HC, Bettini JP, Vatoux S, Papuchon M. Progress in Optical Fiber Gyroscopes Using Integrated Optics. Proceedings of AGARD-NATO 1985; CPP-383 9A1-9A13.

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[47] Lefèvre HC, Graindorge Ph, Arditty HJ, Vatoux S, Papuchon M. Double Closed-Loop Hybrid Fiber Gyroscope Using Digital Phase Ramp. Proceeding of OFS-3 1985, San

[48] Auch W. The Fiber-Optic Gyro – a Device for Laboratory Use Only?, SPIE Proceed‐

[49] Arditty HJ, Graindorge Ph, Lefèvre HC, Martin Ph, Morisse J, Simonpiétri P. Fiber-Optic Gyroscope with All-Digital Processing. Proceedings of OFS- 6, Paris, Springer-

[50] Jaroszewicz LR, Krajewski Z, Kowalski H, Mazur G, Zinówko P, Kowalski JK. AFORS Autonomous Fibre-Optic Rotational Seismograph: Design and Application.

[51] Jaroszewicz L.R., Krajewski Z., Teisseyre, K. P. The Possibility of a Continuous Moni‐ toring of the Horizontal Buildings' Rotation by the Autonomous Fibre-Optic Rota‐ tional Seismograph AFORS Type. In: Lavan O., De Stefano M. (eds) Seismic Behaviour and Design of Irregular and Complex Civil Structures. Berlin-Heidelberg:

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http://dx.doi.org/10.5772/59372

## **1. Introduction**

Earthquake is defined as a sudden and rapid shaking of the earth caused by the breaking and shifting of rock beneath the Earth's surface and it creates seismic waves, which can result in damages and failures on man-made structures constructed on the crust of earth [18]. Dams and large reservoirs constructed on the area with high seismicity, pose a high-risk potential for downstream life and property. It is clear that active faults, which are located close to dam sites, can induce to damaging deformation of the embankment as based on instability of the dam and strength loss of foundation materials. Scientists have realized so many researches for explaining the behavior of earth structures under seismic forces.

Earthquake effects on dams mainly depend on dam types. [28] stated that safety concerns for embankment dams subjected to earthquakes involve either the loss of stability due to a loss of strength of the embankment and foundation materials or excessive deformations such as slumping, settlement, cracking and planer or rotational slope failures. According to [9], safety requirements for concrete dams subjected to dynamic loadings should involve evaluation of the overall stability of the structure, such as verifying its ability to resist induced lateral forces and moments and preventing excessive cracking of the concrete.

Earthquakes can result in damages or failures for dam structures, while dams with large reservoirs can induce to earthquakes. Case studies about the seismic performance of dams under large earthquakes are available in the literature. [31] state that earthquake safety of dams is an important phenomenon in dam engineering and requires more comprehensive seismic studies for understanding the seismic behavior of dams subjected to severe earthquakes. It is a well-known phenomenon that earthquakes can result damages and failures for dams and their appurtenant structures. There is another fact that dams with large reservoirs also trigger earthquake.

© 2015 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Ground shaking from earthquakes can collapse dams. There are some important cases, which subjected to damages and failures after earthquake. Lower San Fernando Dam in USA is first example failed as a result of liquefaction phenomenon under the earthquake loading condi‐ tions. In case of the May 12, 2008 Wenchuan earthquake in China many dams and reservoirs had been subjected to strong ground shaking. So many dams and hydropower plants were damaged. During the 2001 Bhuj earthquake in Gujarat, India, 245 dams had been affected and rehabilitated or strengthened after the earthquake. Also, in the case of the March 11, 2011 Tohoku earthquake in Japan, damages were observed about 400 dams and the 18 m high embankment dam failed and 8 people lost their live.

Large reservoirs can trigger earthquake. According to recent surveys, Reservoir Triggering Seismicity (RTS) has been observed at over 100 locations worldwide [4, 19, 20]. The largest and most damaging earthquake triggered by a man-made reservoir may be the 7.9-magnitude Sichuan earthquake in May 12, 2008. One of the most serious cases was in 1967 in Koyna, India. The magnitude of this earthquake was 6.3. Also significant effects have been observed Hsingfengkiang dam in China, Kariba dam in Zimbabwe and Kremasta dam in Greece. The effect of reservoir loading on the existing stress field has been investigated by several studies [1, 5, 13, 14, 15, 19, 20, 21, 22, 23]. The field studies indicates that the main factors acting reservoir seismicity are in-situ stress conditions, availability of fractures and faults, geology of the regional area, dimensions of the reservoir and the nature of reservoir level fluctuations.

The paper gives an overview on the dams, which are under the effects of strong ground motions. It investigates the effects of earthquake on dams, also effects of dam on earthquake occurrence. Some cases are given to explain both phenomena and clarify the total risk of large dam structures when considered earthquake effects. The subjects presented in the paper were addressed by the international committees and recent surveys. It mentions main requirements for large dams on view of earthquake engineering to find rational design solutions. The purpose of this paper is to sketch the state of the art in dam engineering, as based on lessons learnt from seismic events.

## **2. Effects of earthquake on dams**

[8] states that damages to dams and their appurtenant facilities may result from (1) direct fault movement across the dam foundation or (2) from ground motion induced at the dam site by an earthquake located at some distance from the dam. The second one is commonly seen, however first one results to more serious problems for dams and their appurtenant structures. A good example to damages resulted by ground shaking vibrations in dams is Sefid buttress dam, which was damaged near crest due to ground shaking the 1990 Manjil earthquake with a magnitude of 7.5 in Iran. In this dam, damages have been observed near crest due to ground vibration. For fault movements in dam site, the Shih-Kang weir can be considered as good case study. In this dam, two openings were failed due to large movements of Chelungpu fault during the magnitude of 7.3 in Chi-Chi earthquake of September 1999 in Tawian. After severe damages observed on this dam, dam engineers more seriously considered active or seismo‐ genic faults on dam sites. Because dams located on active faults pose significant risk for total stability of project and public safety.

Ground shaking from earthquakes can collapse dams. There are some important cases, which subjected to damages and failures after earthquake. Lower San Fernando Dam in USA is first example failed as a result of liquefaction phenomenon under the earthquake loading condi‐ tions. In case of the May 12, 2008 Wenchuan earthquake in China many dams and reservoirs had been subjected to strong ground shaking. So many dams and hydropower plants were damaged. During the 2001 Bhuj earthquake in Gujarat, India, 245 dams had been affected and rehabilitated or strengthened after the earthquake. Also, in the case of the March 11, 2011 Tohoku earthquake in Japan, damages were observed about 400 dams and the 18 m high

190 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

Large reservoirs can trigger earthquake. According to recent surveys, Reservoir Triggering Seismicity (RTS) has been observed at over 100 locations worldwide [4, 19, 20]. The largest and most damaging earthquake triggered by a man-made reservoir may be the 7.9-magnitude Sichuan earthquake in May 12, 2008. One of the most serious cases was in 1967 in Koyna, India. The magnitude of this earthquake was 6.3. Also significant effects have been observed Hsingfengkiang dam in China, Kariba dam in Zimbabwe and Kremasta dam in Greece. The effect of reservoir loading on the existing stress field has been investigated by several studies [1, 5, 13, 14, 15, 19, 20, 21, 22, 23]. The field studies indicates that the main factors acting reservoir seismicity are in-situ stress conditions, availability of fractures and faults, geology of the regional area, dimensions of the reservoir and the nature of reservoir level fluctuations.

The paper gives an overview on the dams, which are under the effects of strong ground motions. It investigates the effects of earthquake on dams, also effects of dam on earthquake occurrence. Some cases are given to explain both phenomena and clarify the total risk of large dam structures when considered earthquake effects. The subjects presented in the paper were addressed by the international committees and recent surveys. It mentions main requirements for large dams on view of earthquake engineering to find rational design solutions. The purpose of this paper is to sketch the state of the art in dam engineering, as based on lessons

[8] states that damages to dams and their appurtenant facilities may result from (1) direct fault movement across the dam foundation or (2) from ground motion induced at the dam site by an earthquake located at some distance from the dam. The second one is commonly seen, however first one results to more serious problems for dams and their appurtenant structures. A good example to damages resulted by ground shaking vibrations in dams is Sefid buttress dam, which was damaged near crest due to ground shaking the 1990 Manjil earthquake with a magnitude of 7.5 in Iran. In this dam, damages have been observed near crest due to ground vibration. For fault movements in dam site, the Shih-Kang weir can be considered as good case study. In this dam, two openings were failed due to large movements of Chelungpu fault during the magnitude of 7.3 in Chi-Chi earthquake of September 1999 in Tawian. After severe damages observed on this dam, dam engineers more seriously considered active or seismo‐

embankment dam failed and 8 people lost their live.

learnt from seismic events.

**2. Effects of earthquake on dams**

Liquefaction is defined as a phenomena in which the strength and stiffness of a saturated soil is reduced earthquake shaking. It generally means the state change from solid to liquid. Lower San Fernando Dam in USA is first known dam failed as a result of liquefaction phenomenon under the earthquake loading conditions. During the 1972 San Fernando Earthquake, Lower San Fernando Dam failed a result of liquefaction phenomena [12, 17, 24]. Its embankment with the structures on crest slid into the reservoir. In other words, approximately 3.0 million cubic meter of dam embankment was displaced into the reservoir. The 1994 Northridge earthquake, some ground movement with minor cracking seems to have occurred at the sites of Los Angeles Dam, which was constructed to replace the San Fernando Reservoir. There was significant differential settlement of the ground of about 5 cm in the northern section, and 20 cm in the southwestern section of the site [24].

During the 2001 Bhuj earthquake in Gujarat, India, 245 dams had been affected and rehabili‐ tated or strengthened after the earthquake [34]. Due to Mid Niigata Prefecture Earthquake in 2004, Japan, several embankment dams and some off-stream impounding facilities for power generation and irrigation system suffered damages such as cracks on dam bodies [10].

In case of the May 12, 2008 Wenchuan earthquake in China many structures about 1803 dams and 403 hydropower plants having a total installed capacity of 3.3 GW were damaged due to strong ground shaking. Most of dams were small earth dams with exception of four large dams having a height greater than 100 m. According to Chinese officials the earthquake occurred along the Longmenshan fault, which is a thrust structure along the border of the Indo-Australian Plate and Eurasian Plate, the rupture lasted 120 sec, the rupture propagated at an average speed of 3.1 km/s toward northeast. The rupture length and focus depth is about 300 km and 10 km, respectively. The maximum displacement was recorded as 9.0 m [6]. As a result of this earthquakes so many elements of dam such as dam body, spillways, powerhouses, penstocks, switchyards, hydro-mechanical and electro-mechanical equipments, temporary structures were damaged, other disasters such as rockfalls, landslides and landslide dams were observed. No dams were failed during this earthquake, although there were so many damaged dams. [8] states that dams must be designed to withstand strong earthquakes, which can seriously result multiple hazards.

In the case of the March 11, 2011 Tohoku earthquake in Japan, damages were observed about 400 dams and the 18 m high embankment dam failed and 8 people lost their live [34].

The dams, which are located on shear zones, have high risk potential when they are subjected to strong ground motion. There are some examples in India for structures located at the northern India. One of the Namada Valley dam, which is built at the triple junction of the fault zones, tectonically and geologically a disturbed area. Terhi dam in India has also similar position under dynamic loading conditions. Researchers states that Terhi dam might release energy along the fault segment between Nepal and Tibet and also trigger an earthquake which has a magnitude close to or greater than 8.0.

In Turkey, there is a sheared zone which is close the triple junction of the famous strike slip faults in east of Turkey. [28] stated that Surgu dam, which damaged on the Dogansehir earthquake with Ms of 5.8 in 1986, Polat dam and Cat dam have the PGA values of 0.256g, 0.170g and 0.211g, respectively. The geology of dam sites are very complicated and frequently jointed, fractured and faulted. The author points out the fact that these dams are under the influence of local near-source zone and have high-risk potential for earthquake conditions. The author's thought was absolutely confirmed by damage on the Dogansehir earthquake with Ms of 5.8 on Surgu dam.

In general, strong ground shaking can result in the instability of the embankment and loss of strength at the foundations [2, 9, 16, 17]. Most of dam engineers have thought that embankment dams are suitable types when well compacted according to the specification, However, it is not an acceptable thought that embankment dams can be induced to damages and failures even if well compacted, while they are under near source effect.

There is no one major problem in seismic safety of embankment dams. Whereas near source effect seems the most serious problem for embankment dams. [28] reveals the fact that active faults, which are very close to the foundation of dams, have the potential to cause damaging displacement of the structure. Especially Concrete Faced Rockfill Dams (CFRD's) have high risk potential when considered near source effect (earthquake epicenter to dam axis is less than 10 km). This phenomenon is dealed with the fact that the transferred energy by rockfill is not absorbed by concrete face during earthquake. Wieland (2010) state that until the Wenchuan earthquake of 12 May 2008 no large concrete face rockfill dam (CFRD) was subjected to strong ground shaking. He questioned that faced concrete of CFRD's can have a behavior as the river embankment which was subjected the 21 September 1999 Chi-Chi earthquake in Taiwan [32 and 33]. Figure 1 shows buckling of river embankment lining after the earthquake.

### **3. Effects of dams on seismicity of the region**

Large reservoirs can trigger earthquake. This phenomenon is defined as Reservoir-induced Seismicity that is mainly depended to excessive water pressure created in the micro-cracks and fissures in the foundation units under and near the reservoir. Water within the rock masses under huge hydrostatic pressure acts to lubricate faults, which are already under tectonic strain, however are prevented from slipping by friction of rock planes. It is clearly known that it mainly depends on nature of structural geology and lithology of surrounding rocks. However, it is very difficult to accurately predict when and where reservoir induced earth‐ quake will occur. ICOLD recommends that Reservoir Triggered Seismicity (RTS) should be considered for reservoirs having a depth more than 100 m. USCOLD has reported that Reservoir Induced Seismicity (RIS) should be taken into account for reservoirs deeper than 80-100m.

It is clear that number of seismic events increases near reservoir areas of large dams after impounding sequence. The earthquake seismicity was firstly observed in 1929 for Marathon

**Figure 1.** Buckling of river embankment lining after the 1999 Chi-Chi earthquake [32]

In Turkey, there is a sheared zone which is close the triple junction of the famous strike slip faults in east of Turkey. [28] stated that Surgu dam, which damaged on the Dogansehir earthquake with Ms of 5.8 in 1986, Polat dam and Cat dam have the PGA values of 0.256g, 0.170g and 0.211g, respectively. The geology of dam sites are very complicated and frequently jointed, fractured and faulted. The author points out the fact that these dams are under the influence of local near-source zone and have high-risk potential for earthquake conditions. The author's thought was absolutely confirmed by damage on the Dogansehir earthquake with

192 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

In general, strong ground shaking can result in the instability of the embankment and loss of strength at the foundations [2, 9, 16, 17]. Most of dam engineers have thought that embankment dams are suitable types when well compacted according to the specification, However, it is not an acceptable thought that embankment dams can be induced to damages and failures

There is no one major problem in seismic safety of embankment dams. Whereas near source effect seems the most serious problem for embankment dams. [28] reveals the fact that active faults, which are very close to the foundation of dams, have the potential to cause damaging displacement of the structure. Especially Concrete Faced Rockfill Dams (CFRD's) have high risk potential when considered near source effect (earthquake epicenter to dam axis is less than 10 km). This phenomenon is dealed with the fact that the transferred energy by rockfill is not absorbed by concrete face during earthquake. Wieland (2010) state that until the Wenchuan earthquake of 12 May 2008 no large concrete face rockfill dam (CFRD) was subjected to strong ground shaking. He questioned that faced concrete of CFRD's can have a behavior as the river embankment which was subjected the 21 September 1999 Chi-Chi earthquake in Taiwan [32

and 33]. Figure 1 shows buckling of river embankment lining after the earthquake.

Large reservoirs can trigger earthquake. This phenomenon is defined as Reservoir-induced Seismicity that is mainly depended to excessive water pressure created in the micro-cracks and fissures in the foundation units under and near the reservoir. Water within the rock masses under huge hydrostatic pressure acts to lubricate faults, which are already under tectonic strain, however are prevented from slipping by friction of rock planes. It is clearly known that it mainly depends on nature of structural geology and lithology of surrounding rocks. However, it is very difficult to accurately predict when and where reservoir induced earth‐ quake will occur. ICOLD recommends that Reservoir Triggered Seismicity (RTS) should be considered for reservoirs having a depth more than 100 m. USCOLD has reported that Reservoir Induced Seismicity (RIS) should be taken into account for reservoirs deeper than

It is clear that number of seismic events increases near reservoir areas of large dams after impounding sequence. The earthquake seismicity was firstly observed in 1929 for Marathon

even if well compacted, while they are under near source effect.

**3. Effects of dams on seismicity of the region**

Ms of 5.8 on Surgu dam.

80-100m.

dam having 60 m height, Greece. Increase in seismicity was also seen in 1935 after the im‐ pounding of Hoover dam, which is a concrete arch dam with a height of 220 m. Up to now, RTS has been observed on over 100 dams in the world. The earthquake intensity has increased after impounding of Keban Dam, which is the second largest dam of Turkey with a storage capacity of 31000 hm3 .and 207 m height from foundation [30]. Recently scientists believe the fact that the over one percent of reservoirs resulted to earthquake which can damage or fail the main structure. It is not a negligible value that this mechanism should be considered by engineers in design stage.

Damages due to RTS have been in two dams: (1) Koyna dam, which is gravity dam having 103 m height in India. It was subjected to an earthquake with magnitude of 6.3 in 1967. (2) Hsinfengkiang dam, which a buttress dam having a height of 105 m in China. It was subjected to earthquake with magnitude of 6.1 in 1962. Researchers state that earthquakes were caused in their reservoirs by RTS. The substantial longitudial cracks were developed near crest for both dams. Both dams are still in operation after strengthened.

The reservoir capacity is an important factor in triggering earthquakes as well as reservoir depth. Phenomenon about Reservoir Induced Seismicity (RIS) mainly conforms for the reservoir filling periods. It can also be seen for a reservoir after a certain time lag [5].

There are some important cases that strong earthquakes may affect a large area. Recent surveys indicate that there are at least 100 cases of earthquakes, which were triggered by reservoirs. The most serious case may be the 7.9-magnitude Sichuan earthquake in May 12, 2008, which killed an estimated 90,000 people. This earthquake has been related to the construction of the Zipingpu Dam, which is a 156 m high concrete faced rockfill dam with a reservoir of 1 120 hm3 . [7] classified two types of earthquakes associated with reservoirs while explaining the complicated mechanisms of RTS after the 12 May 2008 Wenchuan earthquake in China: (1) The small magnitude earthquakes, which occur immediately after reservoir impounding or following sudden reservoir water level fluctuations are mainly related to stress adjustments in the foundation rock, collapse of karst caves and mining pits and mass movements, (2) Earthquakes, which are caused by seismicgenic faults passing through or adjacent to the reservoir area, are referred to as RTS. [7] states that the initial stress state must already be close to failure so that a minor change in strength properties in a fault plane caused by water in the reservoir could trigger seismic events and the magnitude of RTS events may gradually increase until the main shock occurs. Authors have explained the mechanism of Wenchuan earthquake by the earthquake of tectonic nature.

### **4. A case study on the reservoir triggered seismicity for an existing dam**

Turkey is one of the most seismically active regions in the world. There are so many dams, which are under the effect of near-source zones in Turkey. There are some examples of embankment dam in Turkey, which were damaged during the earthquakes occurred in past. There is no any concrete dam, which was damaged as a result of earthquake in Turkey [25, 26].

Ataturk dam, which is a 169 m height zoned rockfill dam on the Euphrates River in Turkey with an 84 000 hm3 of water reservoir, poses high risk about triggering phenomena by reservoir. It has the largest reservoir of Turkey with 48 700 hm3 (Figure 2). Its crest length is 1 670 m and base width is approximately 900 m. It is located 35 km north of the Birecik dam reservoir and 120 km south of Karakaya dam body.

Its main embankment construction was started in 1985 and completed in 1990. The reservoir level has maximally reached to 537 m up to now. Its level fluctuates from 526 to 535 m as based on climate change and energy demand. It was designed a multi-purpose structure for irrigating lands, producing electricity and providing flood control. It generates electricity of 8100 GWh per year with an installed capacity of 2400 MW.

It is a rockfill dam with central core. There is a transition section of sand, gravel and small sized crushed rock between the core and rockfill materials. It has also a coarse grained soil zone obtained from river deposits and a random zone, which is composed of laminated limestone. The upstream and downstream shells are composed of large-sized crushed rocks. The alluvium on river bed, which is composed of sand, gravel, clay and silt mixtures, was removed before beginning the construction of the main embankment. The basement of Ataturk dam is formed by karstic limestone, regarded as problematic rock for dam foundation. An intensive grouting program was applied to prevent water leakage from the reservoir [28].

Author has completed a study from seismic hazard analysis to 2-D finite element analysis to assess its static and dynamic stability for Ataturk dam [31]. For the seismic hazard analyses of

**Figure 2.** A general view from Ataturk dam

killed an estimated 90,000 people. This earthquake has been related to the construction of the Zipingpu Dam, which is a 156 m high concrete faced rockfill dam with a reservoir of 1 120

194 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

**4. A case study on the reservoir triggered seismicity for an existing dam**

Turkey is one of the most seismically active regions in the world. There are so many dams, which are under the effect of near-source zones in Turkey. There are some examples of embankment dam in Turkey, which were damaged during the earthquakes occurred in past. There is no any concrete dam, which was damaged as a result of earthquake in Turkey [25, 26].

Ataturk dam, which is a 169 m height zoned rockfill dam on the Euphrates River in Turkey

base width is approximately 900 m. It is located 35 km north of the Birecik dam reservoir and

Its main embankment construction was started in 1985 and completed in 1990. The reservoir level has maximally reached to 537 m up to now. Its level fluctuates from 526 to 535 m as based on climate change and energy demand. It was designed a multi-purpose structure for irrigating lands, producing electricity and providing flood control. It generates electricity of 8100 GWh

It is a rockfill dam with central core. There is a transition section of sand, gravel and small sized crushed rock between the core and rockfill materials. It has also a coarse grained soil zone obtained from river deposits and a random zone, which is composed of laminated limestone. The upstream and downstream shells are composed of large-sized crushed rocks. The alluvium on river bed, which is composed of sand, gravel, clay and silt mixtures, was removed before beginning the construction of the main embankment. The basement of Ataturk dam is formed by karstic limestone, regarded as problematic rock for dam foundation. An intensive

Author has completed a study from seismic hazard analysis to 2-D finite element analysis to assess its static and dynamic stability for Ataturk dam [31]. For the seismic hazard analyses of

grouting program was applied to prevent water leakage from the reservoir [28].

of water reservoir, poses high risk about triggering phenomena by reservoir.

(Figure 2). Its crest length is 1 670 m and

. [7] classified two types of earthquakes associated with reservoirs while explaining the complicated mechanisms of RTS after the 12 May 2008 Wenchuan earthquake in China: (1) The small magnitude earthquakes, which occur immediately after reservoir impounding or following sudden reservoir water level fluctuations are mainly related to stress adjustments in the foundation rock, collapse of karst caves and mining pits and mass movements, (2) Earthquakes, which are caused by seismicgenic faults passing through or adjacent to the reservoir area, are referred to as RTS. [7] states that the initial stress state must already be close to failure so that a minor change in strength properties in a fault plane caused by water in the reservoir could trigger seismic events and the magnitude of RTS events may gradually increase until the main shock occurs. Authors have explained the mechanism of Wenchuan earthquake

hm3

by the earthquake of tectonic nature.

It has the largest reservoir of Turkey with 48 700 hm3

per year with an installed capacity of 2400 MW.

120 km south of Karakaya dam body.

with an 84 000 hm3

the dam site, first all possible seismic sources were identified as based on the new seismic zonation map of Turkey by means of a software, which was developed at the Earthquake Research Center in Eskisehir Osmangazi University [29]. As a result of detailed evaluation, the dam site and vicinity were separated into four seismic zones. Figure 3 shows these zones including faults and earthquakes occurred in the basin along last 100 years.

At the first design stage, it was considered only Eastern Anatolian Fault System (DAF) for seismic hazard analysis. As a result of this study, the value of Peak Ground Acceleration (PGA) was low for MDE. Recent study conducted by author indicates that the PGA value is consid‐ erable level and Bozova fault has a significant potential for reservoir triggering seismicity for Ataturk dam. It was located 3.0 m far away from the dam body and has a parallel position to the dam crest. This fault can produce an earthquake with a magnitude of 6.5 to 7.0. The seismic hazard analysis was performed for the dam by means of two separate methods. The deter‐ ministic seismic hazard analysis shows that the PGA value ranges from 0.284 to 0.536. These PGA values are high. Because the fault is very close to the dam site. The results of probabilistic seismic hazard analysis indicate that peak ground acceleration (PGA) changes within a wide range (0.057g and 0.203g) for OBE. For MDE and SEE, the PGA value averages to 0.197g and 0.408, respectively [31].

The seismic hazard analyses performed throughout this study indicates that Ataturk dam is one of the most critical dams within the basin. As based on the author's recent studies, Total Risk Factor (TRF) value is 146.5 and it is identified as risk class of III. It means that it has high risk potential for downstream life and structures. [31] states that the 25-years old rockfill dam also has some problems in static condition and it cannot meet current seismic design standards. The earthquake intensity in dam site and reservoir area has been increased after reservoir impounding or following sudden reservoir water level fluctuations. The Bozova fault, which is very close to dam body, can be a source of earthquake triggered by the reservoir of Ataturk dam. Also, Terbela dam with a reservoir of 13 690 hm3 in Pakistan can be classified as high risk dam when considered this phenomena.

**Figure 3. Location of dam site on seismo-tectonic map and earthquakes Figure 3.** Location of dam site on seismo-tectonic map and earthquakes

complete picture of the seismic hazard (Kramer, 1996).

#### The seismic activity of dam sites is generally analyzed by two methods: (1) The deterministic **5. Main design principles for dams located on active seismic area**

**5. Main Design Principles for Dams Located on Active Seismic Area** 

seismic hazard analysis and (2) The probabilistic seismic hazard analysis. The deterministic seismic hazard analysis is a very simple procedure and gives rational solutions for large dams. Due to the unavailability of strong motion records, various attenuation relationships were adopted to calculate the peak ground acceleration (PGA) acting on dam sites. The probabilistic seismic hazard analysis considers uncertainties in size, location and recurrence The seismic activity of dam sites is generally analyzed by two methods: (1) The deterministic seismic hazard analysis and (2) The probabilistic seismic hazard analysis. The deterministic seismic hazard analysis is a very simple procedure and gives rational solutions for large dams. Due to the unavailability of strong motion records, various attenuation relationships were adopted to calculate the peak ground acceleration (PGA) acting on dam sites. The probabilistic seismic hazard analysis considers uncertainties in size, location and recurrence rate of

rate of earthquakes. The probabilistic seismic hazard analysis provides a framework in which uncertainties can be identified and combined in a rational manner to provide a more

The computer program used for seismic analysis should be available for the probabilistic and deterministic assessment of seismic hazard. The seismic sources should be identified and the recurrence interval of earthquakes should be estimated. As a result of an extensive survey and a search of available literature (Tosun et al, 2007a; Tosun et al 2007b; Tosun and Seyrek, 2012). Several sources have been identified to help analyzing the seismic hazard of dams in Turkey and surrounding countries. The earthquakes that occurred within the last 100 years should be used for estimating seismic parameters. Seismic zones and earthquakes. The probabilistic seismic hazard analysis provides a framework in which uncertainties can be identified and combined in a rational manner to provide a more complete picture of the seismic hazard [11].

The computer program used for seismic analysis should be available for the probabilistic and deterministic assessment of seismic hazard. The seismic sources should be identified and the recurrence interval of earthquakes should be estimated. As a result of an extensive survey and a search of available literature [28, 29, 31]. Several sources have been identified to help analyzing the seismic hazard of dams in Turkey and surrounding countries. The earthquakes that occurred within the last 100 years should be used for estimating seismic parameters. Seismic zones and earthquakes within the area having a radius of 100 km around the dam site should be considered.

For beginning to a seismic hazard analysis, primary factors such as regional geological setting, seismic history and local geological setting should be studied, and then earthquake definitions should be executed. Figure 4 summarizes the methods of analysis for a dam site and dam body. After selection of earthquakes, static, pseudo-static and dynamic analyses should be per‐ formed and liquefaction phenomenon and near source effect should be evaluated. In Turkey, a design engineer should conform to diagram given in Figure 4.

Earthquake definitions are given below:

risk potential for downstream life and structures. [31] states that the 25-years old rockfill dam also has some problems in static condition and it cannot meet current seismic design standards. The earthquake intensity in dam site and reservoir area has been increased after reservoir impounding or following sudden reservoir water level fluctuations. The Bozova fault, which is very close to dam body, can be a source of earthquake triggered by the reservoir of Ataturk

196 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

Eastern Anatolian Fault System (DAF)

**Figure 3. Location of dam site on seismo-tectonic map and earthquakes** 

The seismic activity of dam sites is generally analyzed by two methods: (1) The deterministic seismic hazard analysis and (2) The probabilistic seismic hazard analysis. The deterministic seismic hazard analysis is a very simple procedure and gives rational solutions for large dams. Due to the unavailability of strong motion records, various attenuation relationships were adopted to calculate the peak ground acceleration (PGA) acting on dam sites. The probabilistic seismic hazard analysis considers uncertainties in size, location and recurrence rate of earthquakes. The probabilistic seismic hazard analysis provides a framework in which uncertainties can be identified and combined in a rational manner to provide a more

The seismic activity of dam sites is generally analyzed by two methods: (1) The deterministic seismic hazard analysis and (2) The probabilistic seismic hazard analysis. The deterministic seismic hazard analysis is a very simple procedure and gives rational solutions for large dams. Due to the unavailability of strong motion records, various attenuation relationships were adopted to calculate the peak ground acceleration (PGA) acting on dam sites. The probabilistic seismic hazard analysis considers uncertainties in size, location and recurrence rate of

The computer program used for seismic analysis should be available for the probabilistic and deterministic assessment of seismic hazard. The seismic sources should be identified and the recurrence interval of earthquakes should be estimated. As a result of an extensive survey and a search of available literature (Tosun et al, 2007a; Tosun et al 2007b; Tosun and Seyrek, 2012). Several sources have been identified to help analyzing the seismic hazard of dams in Turkey and surrounding countries. The earthquakes that occurred within the last 100 years should be used for estimating seismic parameters. Seismic zones and

**5. Main Design Principles for Dams Located on Active Seismic Area** 

**5. Main design principles for dams located on active seismic area**

Bozova fault

complete picture of the seismic hazard (Kramer, 1996).

**Figure 3.** Location of dam site on seismo-tectonic map and earthquakes

in Pakistan can be classified as high risk

Reservoir of Ataturk dam

dam. Also, Terbela dam with a reservoir of 13 690 hm3

dam when considered this phenomena.

The Operating Basis Earthquake (OBE) was defined by means of the probabilistic methods. It is known as the earthquake that produces the ground motions at the site that can reasonably be expected to occur within the service life of the project [3]. It will be appropriate to choose a minimum return period of 145 years. It means a 50 percent probability of not being exceeded in 100 years.

Maximum Credible Earthquake (MCE), which is the largest earthquake magnitude that could occur along a recognized fault or within a particular seismo-tectonic province, was obtained for each zone and the most critical framework for the dam site was selected as Controlling Maximum Credible Earthquake (CMCE). The Maximum Design Earthquake (MDE) was then defined. It generally represents the ground motion with 475 years of return period [28]. It means a 10 percent probability of not being exceeded in 50 years.

According to [3], MDE is normally characterized by a level of motion equal to that expected at the dam site from the occurrence of deterministically evaluated MCE and Safety Evaluation Earthquake (SEE) should be used for critical structures located in very active seismic area. Most of large dams in Turkey were analyzed by using these definitions [28].

Terminology used for seismic analysis of dams varies between countries. In the last publication of [8], new earthquake definitions have been made. In this bulletin the Safety Evaluation Earthquake (SEE) is newly defined as the level of shaking for which damage can be accepted but for which there should be no uncontrolled release of water from the reservoir. In Turkey, it is defined as a level of ground motion having 2 percent probability of not being exceeded in 50 years. [8] states that SEE may be chosen to have a lower return period depending on the consequences of dam failure.

**Figure 4.** Methods of analysis for a dam located on active seismic area in Turkey

#### **6. Conclusions**

The total risk for dam structures mainly depends on the seismic hazard rating of dam site and the risk rating of the completed structure. This paper gives an overview on the effects of earthquake on dams and effects of dam on earthquake occurrence, and points out the necessity of special design and construction measures for the dams, which are under the effects of strong ground motions. It is clear that the main requirement in earthquake-resistant design for dams is to protect public safety, downstream life and property. Therefore, some important factors listed below should be taken into account in design stage:


## **Acknowledgements**

The author expresses his gratitude to the authorities of State Hydraulics Works for providing some technical data during completion of this study.

## **Author details**

Hasan Tosun\*

**Figure 4.** Methods of analysis for a dam located on active seismic area in Turkey

198 Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

listed below should be taken into account in design stage:

The total risk for dam structures mainly depends on the seismic hazard rating of dam site and the risk rating of the completed structure. This paper gives an overview on the effects of earthquake on dams and effects of dam on earthquake occurrence, and points out the necessity of special design and construction measures for the dams, which are under the effects of strong ground motions. It is clear that the main requirement in earthquake-resistant design for dams is to protect public safety, downstream life and property. Therefore, some important factors

**i.** Large dams must be designed with a capability of resisting severe earthquake motion

**ii.** For large dams located on non active seismic area, Reservoir Triggering Seismicity

or fault movement at the dam site without uncontrolled release of water stored in

(RTS) can be more critical. Therefore, RTS should be defined sensitively as based on local geologic units and tectonic structures by means a detail seismic hazard analysis.

**6. Conclusions**

reservoir.

Address all correspondence to: htosun@ogu.edu.tr

Civil Engineering Department, Uşak University, Uşak, Turkey

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