Preface

**Chapter 9 151**

**Chapter 10 161**

**Chapter 11 179**

**Chapter 12 189**

**Chapter 13 215**

Atomistic Mathematical Theory for Metaheuristic Structures of Global

Ultrasonic Detection of Down Syndrome Using Multiscale Quantiser

Optimization Algorithms in Evolutionary Machine Learning

K-Means Efficient Energy Routing Protocol for Maximizing

Multi-Agent Implementation of Filtering Multiset Grammars

*by Bouakkaz Fatima, Ali Wided, Guemmadi Sabrina* 

Information Technology Value Engineering (ITVE)

for Power Systems *by Jonah Lissner*

Vitality of WSNs

*by Igor Sheremet*

**II**

*and Derdour Makhlouf*

*by Lukman Abdurrahman*

with Convolutional Neural Network *by Michael Dinesh Simon and A.R. Kavitha* Computational optimization is an active and important area of study, practice, and research today. It covers a wide range of applications in engineering, science, and industry. It provides solutions to a variety of real-life problems in disciplines such as health, business, government, military, politics, security, education, and many more. Various problems can be transformed into optimization problems and then can be solved simply, accurately, and efficiently. This field is a source of revolutionizing, facilitating and enhancing the exchange of knowledge among researchers involved in both the theoretical and practical aspects. It emphasizes various topics including large-scale optimization, unconstrained optimization, constrained optimization, nondifferentiable optimization, combinatorial optimization, stochastic optimization, multi-objective optimization, linear programming, quadratic programming, parametric programming, complexity theory, automatic differentiation, approximations, error analysis, sensitivity analysis, theoretical analysis, evolutionary computing, surrogate-based methods, simulated likelihood estimation, support vector machines, and others. This comprehensive reference explores the developments, methods, approaches, and surveys of computational optimization in a wide variety of fields and endeavors. It focuses on optimization techniques, algorithms, analysis, applications, fields, nature of problems, and more.

This book compiles original and innovative findings on all aspects of computational optimization. It presents various examples of optimization including cost, energy, profits, outputs, performance, and efficiency. It also discusses different types of optimization problems like nonlinearity, multimodality, discontinuity, and uncertainty. The book also addresses various real-life applications of computational optimization in the fields of science, engineering, industry, health, business, government, military, information technology, and others. The book provides researchers, practitioners, academicians, military professionals, government officials, and other industry professionals with an in-depth discussion of the latest advances in the field. It consists of thirteen chapters in different areas of interest.

Kamiński starts the book with the first chapter on "Optimization Directions for Monitoring of Ground Freezing Process for Grzegorz Shaft Sinking." It discusses the sinking of the Grzegorz mineshaft in the Silesian Coal Basin in the United States, which is the first mineshaft sunk in the 21st century using a ground freezing method. Work carried out by the Shaft Sinking Company (PBSz S.A.) is characterized by a high level of innovativeness. Geophysical measurements were conducted to optimize the ground freezing process and its monitoring. Data gathered during research was used as a starting point for optimizing particular fields during the Grzegorz shaft sinking, as well as for use in future similar ventures. Proposed solutions might bring real improvements for the safety and effectiveness of the work as well as for economic factors. Conducted tests and analysis aimed at improving the monitoring of shape, size, and quality of the frozen rock mass column in a safe and reliable manner.

Chapter 2, "A Novel PID Robotic for Speed Controller Using Optimization Based Tune Technique" by Alkhafaji et al., investigates efforts to optimize coefficient

gains, which is a significant issue for a proportional–integral–derivative (PID) controller. The authors propose massive tuning methods to resolve this problem, but there is little attention paid to optimize minimization time response significantly. The authors propose a technique to maximize optimization PID gains for the DC motor controller by combining a proper tuning method with a single-input and single-output (SISO) optimization toolbox using optimization-based tune (OBT) techniques that can be utilized for the greatest precision controller. A comparative study is carried out by applying five different tuning methods to obtain a proper tuning controller to then be combined with the SISO optimization toolbox. The utilized tuning methods include Robust Auto-Tune (RAT), Ziegler–Nichols (Z-N), Skogestad Internal Model Control (SIMC), Chien–Hrones–Reswick (CHR), and Approximate M-Constrained Integral Gain Optimization (AMIGO). The performance of all OBT tuning methods are analyzed and compared using the MATLAB/ SISO tool environment, where efficiency is assessed based on time response characteristics (Ti) in terms of dead time (td), rise time (tr), settling time (ts), peak time (tp), and peak overshoot (Pos). The simulation results of the AMIGO-based proposal show a significant reduction time response measured in microseconds (µs). The novel feature of the proposed study is that it provides superior balancing between robustness and performance.

solution must be found. This setting demands instantaneous operational planning and decision-making under inherent severe stress conditions. The associated responsibilities are usually divided among a number of operators and computerized decision support systems that aid these operators during the decision-making process. This chapter surveys the literature in the area of WTA systems with an

In Chapter 6, "A Review on Advanced Manufacturing Techniques and Their Applications" Patel and Kilic present a review on advanced manufacturing techniques and their applications. Advancement in manufacturing processes has drawn great interest from researchers and industry. It makes the process of manufacturing more productive and efficient. Advanced technology in manufacturing combines different manufacturing processes with similar objectives. This may include increasing material removal rate, improving surface integrity, reducing tool wear, reducing production time, and extending application areas. A combination of different processes is called a "hybrid" process. Hybrid processes open up new opportunities and applications for manufacturing various components that are not able to be produced economically by processes on their own. This chapter reviews the classification of current manufacturing processes based on the nature of the processing. It also includes reviews of existing and widely used manufacturing processes.

Chapter 7, "Stress-Strain Relationship: Postulated Concept to Understand Genetic Mechanism Associated with a Seismic Event" by Verma et.al, proposes a design methodology for monitoring earthquakes and detecting and tracking micro-seismic changes in the earthquake prediction system. The alert device includes sensors drastically different from current early warnings using the dozens of seismometers network across seismically active regions for the measurement of small acceleration signals directly. Specifically, first of all, it deals with the low-noise stage of the instruments measuring low-noise velocity signals. In this proposal, strain develops over time in the overlying stratum at a right angle to the applied shearing (max) stress. It obeys the internal friction of the stratum, available seismic energy, and laws of the stress-strain relationship. Using estimated energy (seismic), stress accumulation, the addition or subtraction in the strain rate due to stress developed, can be analyzed for a seismic event. This concept may lead to a better understanding of stress generation (build-up, transfer, and final drop). The chapter also proposes a methodology to identify the type of data to be used for spectral analysis in earthquake seismology and the type of instrument that can be used for data acquisition.

Chapter 8, "Nature Inspired Metaheuristic Approach for Best Tool Work

fies these two contradictory objectives simultaneously.

Combination for EDM Process," by Bose and Pain discusses the use of electric discharge machining (EDM) with different types of tools like copper, aluminum, and brass while machining high-carbon high- chromium (HCHCr), hot die steel (HDS), and oil-hardened nitride steel (OHNS) workpiece material. The authors determine the most efficient tool material for different workpiece materials while satisfying the contradictory objectives of high material removal rate (MRR) and low tool wear rate (TWR). The experimental data are trained and validated using an artificial neural network (ANN). Finally, the results obtained through a genetic algorithm are hybridized with a fuzzy multi-criteria decision making (MCDM) technique to obtain a single parametric combination of the process control parameters that satis-

Global optimization in the 4D nonlinear landscape generates different types of particles, waves, and extremals of power sets and singletons. In Chapter 9, "Atomistic

emphasis on modelling and solving methods.

In Chapter 3, "Highway PC Bridge Inspection by 3.95 MeV X-Ray/Neutron Source," Uesaka et al. develop portable 950 keV/3.95 MeV X-ray/neutron sources and apply them to the inspection of PC concrete thicker than 200 mm within a reasonable measuring time of seconds to minutes. T-girder-, Box- and slab- bridges are considered as part of the study. The authors suggest that it is time to begin X-ray transmission inspection for highway bridge (box) using 3.95 MeV X-ray sources in Japan. By obtaining X-ray transmission images of no-grout-filling in PC sheath and thinning of PC wires, they plan to carry out numerical structural analysis to evaluate the degradation of strength. Finally, the authors propose a technical guideline of nondestructive evaluation (NDE) of PC bridges taking into account both X-ray inspection and structural analysis. It has also been attempted to detect rainwater detection in PC sheath, and asphalt and floor slab by the 3.95 MeV neutron source. This is expected to be an early degradation inspection. Preliminary experiments are done on X-ray transmission imaging of PC wires and on-grout-filling in the same height PCs in 450–750-mm thick concretes. Moreover, the chapter also explains neutron backscattering detection of water in a PC sheath.

Chapter 4, "Incremental Linear Switched Reluctance Actuator," by Lachheb and Amraoui describes that linear switched reluctance actuators are a focus of study for many applications because of their simple and robust electromagnetic structure. This is despite their lower thrust force density when compared with linear permanent magnet synchronous motors. This chapter deals with an incremental linear actuator, which has switched reluctance structure. It mentions different topologies of linear incremental actuators. The chapter places special focus on the switched reluctance linear actuator following the explanation of its operating principles. In addition, the authors develop an analytical model of the proposed actuator without taking account of the saturation in the magnetic circuit. Finally, the authors present control techniques that can be applied to the studied actuator.

In Chapter 5, "A Survey on Weapon Target Allocation Models and Applications," Ghanbari et al. discuss Command and Control (C2), Threat Evaluation (TE), and Weapon Target Allocation (WTA). To build an automated system in this area after modelling TE and WTA processes, the models must be solved and an optimal

solution must be found. This setting demands instantaneous operational planning and decision-making under inherent severe stress conditions. The associated responsibilities are usually divided among a number of operators and computerized decision support systems that aid these operators during the decision-making process. This chapter surveys the literature in the area of WTA systems with an emphasis on modelling and solving methods.

In Chapter 6, "A Review on Advanced Manufacturing Techniques and Their Applications" Patel and Kilic present a review on advanced manufacturing techniques and their applications. Advancement in manufacturing processes has drawn great interest from researchers and industry. It makes the process of manufacturing more productive and efficient. Advanced technology in manufacturing combines different manufacturing processes with similar objectives. This may include increasing material removal rate, improving surface integrity, reducing tool wear, reducing production time, and extending application areas. A combination of different processes is called a "hybrid" process. Hybrid processes open up new opportunities and applications for manufacturing various components that are not able to be produced economically by processes on their own. This chapter reviews the classification of current manufacturing processes based on the nature of the processing. It also includes reviews of existing and widely used manufacturing processes.

Chapter 7, "Stress-Strain Relationship: Postulated Concept to Understand Genetic Mechanism Associated with a Seismic Event" by Verma et.al, proposes a design methodology for monitoring earthquakes and detecting and tracking micro-seismic changes in the earthquake prediction system. The alert device includes sensors drastically different from current early warnings using the dozens of seismometers network across seismically active regions for the measurement of small acceleration signals directly. Specifically, first of all, it deals with the low-noise stage of the instruments measuring low-noise velocity signals. In this proposal, strain develops over time in the overlying stratum at a right angle to the applied shearing (max) stress. It obeys the internal friction of the stratum, available seismic energy, and laws of the stress-strain relationship. Using estimated energy (seismic), stress accumulation, the addition or subtraction in the strain rate due to stress developed, can be analyzed for a seismic event. This concept may lead to a better understanding of stress generation (build-up, transfer, and final drop). The chapter also proposes a methodology to identify the type of data to be used for spectral analysis in earthquake seismology and the type of instrument that can be used for data acquisition.

Chapter 8, "Nature Inspired Metaheuristic Approach for Best Tool Work Combination for EDM Process," by Bose and Pain discusses the use of electric discharge machining (EDM) with different types of tools like copper, aluminum, and brass while machining high-carbon high- chromium (HCHCr), hot die steel (HDS), and oil-hardened nitride steel (OHNS) workpiece material. The authors determine the most efficient tool material for different workpiece materials while satisfying the contradictory objectives of high material removal rate (MRR) and low tool wear rate (TWR). The experimental data are trained and validated using an artificial neural network (ANN). Finally, the results obtained through a genetic algorithm are hybridized with a fuzzy multi-criteria decision making (MCDM) technique to obtain a single parametric combination of the process control parameters that satisfies these two contradictory objectives simultaneously.

Global optimization in the 4D nonlinear landscape generates different types of particles, waves, and extremals of power sets and singletons. In Chapter 9, "Atomistic

gains, which is a significant issue for a proportional–integral–derivative (PID) controller. The authors propose massive tuning methods to resolve this problem, but there is little attention paid to optimize minimization time response significantly. The authors propose a technique to maximize optimization PID gains for the DC motor controller by combining a proper tuning method with a single-input and single-output (SISO) optimization toolbox using optimization-based tune (OBT) techniques that can be utilized for the greatest precision controller. A comparative study is carried out by applying five different tuning methods to obtain a proper tuning controller to then be combined with the SISO optimization toolbox. The utilized tuning methods include Robust Auto-Tune (RAT), Ziegler–Nichols (Z-N), Skogestad Internal Model Control (SIMC), Chien–Hrones–Reswick (CHR), and Approximate M-Constrained Integral Gain Optimization (AMIGO). The performance of all OBT tuning methods are analyzed and compared using the MATLAB/ SISO tool environment, where efficiency is assessed based on time response characteristics (Ti) in terms of dead time (td), rise time (tr), settling time (ts), peak time (tp), and peak overshoot (Pos). The simulation results of the AMIGO-based proposal show a significant reduction time response measured in microseconds (µs). The novel feature of the proposed study is that it provides superior balancing

In Chapter 3, "Highway PC Bridge Inspection by 3.95 MeV X-Ray/Neutron Source," Uesaka et al. develop portable 950 keV/3.95 MeV X-ray/neutron sources and apply them to the inspection of PC concrete thicker than 200 mm within a reasonable measuring time of seconds to minutes. T-girder-, Box- and slab- bridges are considered as part of the study. The authors suggest that it is time to begin X-ray transmission inspection for highway bridge (box) using 3.95 MeV X-ray sources in Japan. By obtaining X-ray transmission images of no-grout-filling in PC sheath and thinning of PC wires, they plan to carry out numerical structural analysis to evaluate the degradation of strength. Finally, the authors propose a technical guideline of nondestructive evaluation (NDE) of PC bridges taking into account both X-ray inspection and structural analysis. It has also been attempted to detect rainwater detection in PC sheath, and asphalt and floor slab by the 3.95 MeV neutron source. This is expected to be an early degradation inspection. Preliminary experiments are done on X-ray transmission imaging of PC wires and on-grout-filling in the same height PCs in 450–750-mm thick concretes. Moreover, the chapter also explains

Chapter 4, "Incremental Linear Switched Reluctance Actuator," by Lachheb and Amraoui describes that linear switched reluctance actuators are a focus of study for many applications because of their simple and robust electromagnetic structure. This is despite their lower thrust force density when compared with linear permanent magnet synchronous motors. This chapter deals with an incremental linear actuator, which has switched reluctance structure. It mentions different topologies of linear incremental actuators. The chapter places special focus on the switched reluctance linear actuator following the explanation of its operating principles. In addition, the authors develop an analytical model of the proposed actuator without taking account of the saturation in the magnetic circuit. Finally, the authors present

In Chapter 5, "A Survey on Weapon Target Allocation Models and Applications," Ghanbari et al. discuss Command and Control (C2), Threat Evaluation (TE), and Weapon Target Allocation (WTA). To build an automated system in this area after modelling TE and WTA processes, the models must be solved and an optimal

between robustness and performance.

neutron backscattering detection of water in a PC sheath.

control techniques that can be applied to the studied actuator.

**IV**

Mathematical Theory for Metaheuristic Structures of Global Optimization Algorithms in Evolutionary Machine Learning for Power Systems," Lissner describes the atomistic mathematical theory for metaheuristic structures of global optimization algorithms in evolutionary machine learning for power systems. This chapter demonstrates the range of optimal problem-solving solution algorithms. Here, once, particles, or atoms of the ontological blueprint are generated inherently from the fractional optimization algorithms in metaheuristic structures of computational evolutionary development. These stigmergetics are applicable to incremental machine learning regimes for computational power generation and relay, and information management systems.

chapter offers an IT value model whose value estimation can be done quantitatively

**Muhammad Sarfraz**

Kuwait

Malaysia

College of Life Sciences, Kuwait University,

**Samsul Ariffin Abdul Karim**

Department of Information Science,

Fundamental and Applied Sciences Department,

Universiti Teknologi PETRONAS (UTP),

The book closes with Chapter 13, "Multi-Agent Implementation of Filtering Multiset Grammars" by Sheremet, who discusses the multi-agent implementation of filtering multiset grammars. This chapter is dedicated to the application of multiagent technology to generate sets of terminal multisets (TMS) defined by filtering multiset grammars (FMG). The proposed approach is based on the creation of a multi-agent system (MAS), corresponding to specific FMG in such a way that every rule of FMG is represented by an independently acting agent. Such MAS provides a high-parallel generation of TMS and may be effectively used in any proper hardware environment. The chapter ends with a discussion of the directions for further

using the Partial Adjustment Valuation (PAV) approach.

developing the proposed approach.

Chapter 10, "Ultrasonic Detection of Down Syndrome Using Multiscale Quantizer with Convolutional Neural Network" by Simon and Kavitha discusses echogenic intracardiac focus (EIF), which is one of the possible symptoms of Down syndrome (DS). In comparison to other symptoms like nasal bone hypoplasia and increased thickness in the nuchal fold, EIF is rare in DS. Hence, recommending pregnant women with EIF to undergo diagnostic processes like amniocentesis, chorionic villus sampling (CVS), and percutaneous umbilical cord blood sampling (PUBS) is not always the right choice, as these processes may result in serious adverse effects like miscarriage and uterine infections. This chapter presents a new ultrasonic method to detect EIF. It entails two stages: the training phase and the testing phase. The training phase aims at learning the features of EIF that can cause DS, whereas the testing phase classifies EIF into DS positive or DS negative based on the knowledge cluster formed during the training phase. A new algorithm, a multiscale quantizer with a convolutional neural network, is used in the training phase. An enhanced learning vector classifier is used in the testing phase to differentiate normal EIF from EIF causing DS. The performance of the proposed system is analyzed in terms of sensitivity, accuracy, and specificity.

Wireless sensor networks (WSNs) are used in diverse applications in the fields of military, agriculture, health care, medical monitoring, and more. The main issue of WSNs is energy consumption. Clustering with k-means is a successful technique for achieving a prolonged network lifetime using less energy. Chapter 11, "K-Means Efficient Energy Routing Protocol for Maximizing Vitality of WSNs" by Fatima et al. discusses the low-energy adaptive clustering hierarchy (LEACH) protocol, which is integrated with clustering where the choice of a number of clusters and their hierarchy uses the k-means method and the distance between nodes and residual energy. Clustering k-means gives the best partition with cluster separation. This chapter discusses related work using k-means to improve the vitality of WSNs. In addition, the chapter proposes an adaptation protocol. The simulation results using MATLAB show that the proposed protocol outperforms the LEACH protocol and optimizes the nodes' energy and the network's lifetime.

Today, Information Technology (IT) assists in providing main infrastructures for conducting business. Initially, IT emerged to automate business operations. As such, IT has been able to make business operations more effective due to its nature as a business enabler. Consequently, resource-based business efficiency is also the cornerstone of utilizing IT. Recently, IT has become over-the-top (OTT), where IT is the basic layer for conducting online business. In the current literature, the business operations rely on qualitative estimates and are not based on quantitative estimates. In Chapter 12, "Information Technology Value Engineering (ITVE)," Abdurrahman discusses Information Technology Value Engineering (ITVE). This

chapter offers an IT value model whose value estimation can be done quantitatively using the Partial Adjustment Valuation (PAV) approach.

The book closes with Chapter 13, "Multi-Agent Implementation of Filtering Multiset Grammars" by Sheremet, who discusses the multi-agent implementation of filtering multiset grammars. This chapter is dedicated to the application of multiagent technology to generate sets of terminal multisets (TMS) defined by filtering multiset grammars (FMG). The proposed approach is based on the creation of a multi-agent system (MAS), corresponding to specific FMG in such a way that every rule of FMG is represented by an independently acting agent. Such MAS provides a high-parallel generation of TMS and may be effectively used in any proper hardware environment. The chapter ends with a discussion of the directions for further developing the proposed approach.

> **Muhammad Sarfraz** Department of Information Science, College of Life Sciences, Kuwait University, Kuwait

## **Samsul Ariffin Abdul Karim**

Fundamental and Applied Sciences Department, Universiti Teknologi PETRONAS (UTP), Malaysia

Mathematical Theory for Metaheuristic Structures of Global Optimization Algorithms in Evolutionary Machine Learning for Power Systems," Lissner

information management systems.

of sensitivity, accuracy, and specificity.

**VI**

optimizes the nodes' energy and the network's lifetime.

describes the atomistic mathematical theory for metaheuristic structures of global optimization algorithms in evolutionary machine learning for power systems. This chapter demonstrates the range of optimal problem-solving solution algorithms. Here, once, particles, or atoms of the ontological blueprint are generated inherently from the fractional optimization algorithms in metaheuristic structures of computational evolutionary development. These stigmergetics are applicable to incremental machine learning regimes for computational power generation and relay, and

Chapter 10, "Ultrasonic Detection of Down Syndrome Using Multiscale Quantizer with Convolutional Neural Network" by Simon and Kavitha discusses echogenic intracardiac focus (EIF), which is one of the possible symptoms of Down syndrome (DS). In comparison to other symptoms like nasal bone hypoplasia and increased thickness in the nuchal fold, EIF is rare in DS. Hence, recommending pregnant women with EIF to undergo diagnostic processes like amniocentesis, chorionic villus sampling (CVS), and percutaneous umbilical cord blood sampling (PUBS) is not always the right choice, as these processes may result in serious adverse effects like miscarriage and uterine infections. This chapter presents a new ultrasonic method to detect EIF. It entails two stages: the training phase and the testing phase. The training phase aims at learning the features of EIF that can cause DS, whereas the testing phase classifies EIF into DS positive or DS negative based on the knowledge cluster formed during the training phase. A new algorithm, a multiscale quantizer with a convolutional neural network, is used in the training phase. An enhanced learning vector classifier is used in the testing phase to differentiate normal EIF from EIF causing DS. The performance of the proposed system is analyzed in terms

Wireless sensor networks (WSNs) are used in diverse applications in the fields of military, agriculture, health care, medical monitoring, and more. The main issue of WSNs is energy consumption. Clustering with k-means is a successful technique for achieving a prolonged network lifetime using less energy. Chapter 11, "K-Means Efficient Energy Routing Protocol for Maximizing Vitality of WSNs" by Fatima et al. discusses the low-energy adaptive clustering hierarchy (LEACH) protocol, which is integrated with clustering where the choice of a number of clusters and their hierarchy uses the k-means method and the distance between nodes and residual energy. Clustering k-means gives the best partition with cluster separation. This chapter discusses related work using k-means to improve the vitality of WSNs. In addition, the chapter proposes an adaptation protocol. The simulation results using MATLAB show that the proposed protocol outperforms the LEACH protocol and

Today, Information Technology (IT) assists in providing main infrastructures for conducting business. Initially, IT emerged to automate business operations. As such, IT has been able to make business operations more effective due to its nature as a business enabler. Consequently, resource-based business efficiency is also the cornerstone of utilizing IT. Recently, IT has become over-the-top (OTT), where IT is the basic layer for conducting online business. In the current literature, the business operations rely on qualitative estimates and are not based on quantitative estimates. In Chapter 12, "Information Technology Value Engineering (ITVE)," Abdurrahman discusses Information Technology Value Engineering (ITVE). This

**1**

freezing method [1].

**Chapter 1**

*Paweł Kamiński*

**Abstract**

Optimization Directions for

quality of frozen rock mass column in a safe and reliable manner.

**sunk using ground freezing method in 21st century**

monitoring methods in mining and civil engineering

**Keywords:** mine shaft, ground freezing, mine safety, geophysics measurements,

**1. Introduction. Grzegorz shaft: The first shaft in Silesian Coal Basin** 

Grzegorz shaft is one of the biggest today's projects in Polish mining industry. Difficult conditions in its geological cross-section forced application of special shaft sinking method, which is ground freezing. This method was in common use in Silesian Coal Basin back in the days, but nowadays it is rarely used, mostly because of a small number of new shafts sunk. This venture was entrusted to Shaft Sinking Company (PBSz S.A.), part of the JSW Group and a leader of highly specialized mining services market in Poland. Company has got 75 years of experience in shaft sinking, including projects in extremely hard conditions, as well as in use of ground

Application of typical shaft sinking method in case of Grzegorz shaft is impossible because of high rock mass' water accumulation and rock's low soaking resilience. Utilization of different methods, such as rock mass drainage and grouting, were analyzed, but expected low effectiveness effected in their abandonment. As the most effective, safe and reliable, ground freezing method was chosen for purpose of Grzegorz shaft sinking. Its essence is creating a column of frozen ground and it is realized by pumping freezing medium to boreholes. Mine shaft is sunk in such prepared rock mass using traditional methods, such as drill sand blasts. Column of frozen soils and rocks prevents shaft heading from flooding. It can also play a role

Monitoring of Ground Freezing

Process for Grzegorz Shaft Sinking

Grzegorz shaft is the first mine shaft sunk in 21st century in Silesian Coal Basin in USA of ground freezing method. Work carried out by Shaft Sinking Company (PBSz S.A.) is characterized by high level of innovativeness. Geophysical measurements were conducted to find directions of optimization of ground freezing process and its monitoring. Data gathered during research is a starting point for finding directions of optimization of particular fields during Grzegorz shaft sinking, as well as to be used in future similar ventures. Proposed solutions might have bring real improvements for safety and effectiveness of work and also for economic factors. Conducted tests and analysis aim at improvement of monitoring of shape, size and
