Electronics and communications engineering Books

Book SynopsisA guide to the role of static state estimation in the mitigation of potential system failures With contributions from a noted panel of experts on the topic, Advances in Electric Power and Energy: Static State Estimation addresses the wide-range of issues concerning static state estimation as a main energy control function and major tool for evaluating prevailing operating conditions in electric power systems worldwide. This book is an essential guide for system operators who must be fully aware of potential threats to the integrity of their own and neighboring systems. The contributors provide an overview of the topic and review common threats such as cascading black-outs to model-based anomaly detection to the operation of micro-grids and much more. The book also includes a discussion of an effective mathematical programming approach to state estimation in power systems. Advances in Electric Power and Energy reviews the most recent developments inTable of ContentsAbout the Editor xi About the Contributors xiii Chapter 1 General Considerations 1 1.1 Prelude 1 1.2 Defining SSE 2 1.3 The Need for State Estimation 3 1.4 Static State Estimation in Practice 4 1.5 Applications That Use SE Solution 10 1.6 Overview of Chapters 13 Chapter 2 State Estimation In Power Systems Based On A Mathematical Programming Approach 23 2.1 Introduction 23 2.2 Formulation 24 2.3 Classical State Estimation Procedure 26 2.4 Mathematical Programming Solution 31 2.5 Alternative State Estimators 32 Part 1 System Failure Mitigation 59 Chapter 3 System Stress and Cascading Blackouts 61 3.1 Introduction 61 3.2 Cascading Blackouts and Previous Work 62 3.3 Problem Statement and Approach 66 3.4 DFAXes, Vulnerability, and Criticality Metrics 70 3.5 Validity of Metrics 78 3.6 Studies with Metrics 82 3.7 Summary 93 3.8 Application of Stress Metrics 94 3.9 Conclusions 94 Chapter 4 Model-Based Anomaly Detection For Power System State Estimation 99 4.1 Introduction 99 4.2 Cyberattacks on State Estimation 100 4.3 ATTACK-RESILIENT State Estimation 103 4.4 Model-Based Anomaly Detection 106 4.5 Conclusions 117 Chapter 5 Protection, Control, and Operation of Microgrids 123 5.1 Prelude 123 5.2 Introduction 126 5.3 State of the Art in Microgrid Protection and Control 128 5.4 Emerging Technologies 146 5.5 Test Case for DDSE 154 5.6 Test Results 159 5.7 Test Case for Adaptive Setting-Less Protection 161 5.8 Conclusions 167 Part 2 Robust State Estimation 171 Chapter 6 PSSE Redux: Convex Relaxation, Decentralized, Robust, And Dynamic Solvers 173 6.1 Introduction 173 6.2 Power Grid Modeling 174 6.3 Problem Statement 176 6.4 Distributed Solvers 186 6.5 Robust Estimators and Cyberattacks 193 6.6 Power System State Tracking 198 6.7 Discussion 202 Chapter 7 Robust Wide-Area Fault Visibility and Structural Observability In Power Systems With Synchronized Measurement Units 209 7.1 Introduction 209 7.2 Robust Fault Visibility Using Strategically Deployed Synchronized Measurements 210 7.3 Optimal PMU Deployment for System-Wide Structural Observability 221 7.4 Conclusions 229 Chapter 8 A Robust Hybrid Power System State Estimator With Unknown Measurement Noise 231 8.1 Introduction 231 8.2 Problem Statement 233 8.3 Proposed Framework for Robust Hybrid State Estimation 234 8.4 Numerical Results 245 8.5 Conclusions 249 Chapter 9 Least-Trimmed-Absolute-Value State Estimator 255 9.1 Bad Data Detection and Robust Estimators 256 9.2 Results and Discussion 266 9.3 Conclusions 287 Part 3 State Estimation For Distribution Systems 295 Chapter 10 Probabilistic State Estimation In Distribution Networks 297 10.1 Introduction 297 10.2 State Estimation in Distribution Networks 298 10.3 Improving Observability in Distribution Networks 309 10.4 Conclusion 324 Chapter 11 Advanced Distribution System State Estimation In Multi-Area Architectures 329 11.1 Issues and Challenges of Distribution System State Estimation 329 11.2 Distribution System Multi-Area State Estimation (DS-MASE) Approach 342 11.3 Application of the DS-MASE Approach 357 11.4 Validity and Applicability of DS-MASE Approach 369 Part 4 Parallel/Distributed Processing 375 Chapter 12 Hierarchical Multi-Area State Estimation 377 12.1 Introduction 377 12.2 Preliminaries 381 12.3 Modeling and Problem Formulation 385 12.4 A Brief Survey of Solution Techniques 387 12.5 Hierarchical State Estimator Via Sensitivity Function Exchanges 393 12.6 Add-On Functions in Multi-area State Estimation 399 12.7 Properties 401 12.8 Simulations 405 12.9 Conclusions 409 Chapter 13 Parallel Domain-Decomposition-Based Distributed State Estimation For Large-Scale Power Systems 413 13.1 Introduction 413 13.2 Fundamental Theory and Formulation 416 13.3 Experimental Results 436 13.4 Conclusion 449 Chapter 14 Dishonest Gauss–Newton Method-Based Power System State Estimation On A GPU 455 14.1 Introduction 455 14.2 Background 456 14.3 Performance of Dishonest Gauss–Newton Method 461 14.4 GPU Implementation 463 14.5 Simulation Results 467 14.6 Discussions on Scalability 468 14.7 Distributed Method of Parallelization 470 14.8 Conclusions 473 Index 475

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Book SynopsisA comprehensive examination of advanced battery management technologies and practices in modern electric vehicles Policies surrounding energy sustainability and environmental impact have become of increasing interest to governments, industries, and the general public worldwide. Policies embracing strategies that reduce fossil fuel dependency and greenhouse gas emissions have driven the widespread adoption of electric vehicles (EVs), including hybrid electric vehicles (HEVs), pure electric vehicles (PEVs) and plug-in electric vehicles (PHEVs). Battery management systems (BMSs) are crucial components of such vehicles, protecting a battery system from operating outside its Safe Operating Area (SOA), monitoring its working conditions, calculating and reporting its states, and charging and balancing the battery system. Advanced Battery Management Technologies for Electric Vehicles is a compilation of contemporary model-based state estimation methods and battery charging and balancing techniTable of ContentsBiographies xi Foreword by Professor Sun xiii Foreword by Professor Ouyang xv Series Preface xvii Preface xix 1 Introduction 1 1.1 Background 1 1.2 Electric Vehicle Fundamentals 2 1.3 Requirements for Battery Systems in Electric Vehicles 3 1.3.1 Range Per Charge 4 1.3.2 Acceleration Rate 10 1.3.3 Maximum Speed 11 1.4 Battery Systems 11 1.4.1 Introduction to Electrochemistry of Battery Cells 12 1.4.1.1 Ohmic Overvoltage Drop 14 1.4.1.2 Activation Overvoltage 14 1.4.1.3 Concentration Overvoltage 14 1.4.2 Lead–Acid Batteries 15 1.4.3 NiCd and NiMH Batteries 16 1.4.3.1 NiCd Batteries 16 1.4.3.2 NiMH Batteries 17 1.4.4 Lithium-Ion Batteries 18 1.4.5 Battery Performance Comparison 19 1.4.5.1 Nominal Voltage 20 1.4.5.2 Specific Energy and Energy Density 20 1.4.5.3 Capacity Efficiency and Energy Efficiency 20 1.4.5.4 Specific Power and Power Density 20 1.4.5.5 Self-discharge 21 1.4.5.6 Cycle Life 21 1.4.5.7 Temperature Operation Range 21 1.5 Key Battery Management Technologies 21 1.5.1 Battery Modeling 21 1.5.2 Battery States Estimation 23 1.5.3 Battery Charging 24 1.5.4 Battery Balancing 25 1.6 Battery Management Systems 25 1.6.1 Hardware of BMS 26 1.6.2 Software of BMS 26 1.6.3 Centralized BMS 27 1.6.4 Distributed BMS 28 1.7 Summary 28 References 28 2 BatteryModeling 31 2.1 Background 31 2.2 Electrochemical Models 31 2.3 Black Box Models 33 2.4 Equivalent Circuit Models 34 2.4.1 General n-RC Model 35 2.4.2 Models with Different Numbers of RC Networks 35 2.4.2.1 Rint Model 35 2.4.2.2 Thevenin Model 36 2.4.2.3 Dual Polarization Model 37 2.4.2.4 n-RC Model 38 2.4.3 Open Circuit Voltage 39 2.4.4 Polarization Characteristics 42 2.5 Experiments 43 2.6 Parameter Identification Methods 47 2.6.1 Offline Parameter Identification Method 47 2.6.2 Online Parameter Identification Method 50 2.7 Case Study 51 2.7.1 Testing Data 51 2.7.2 Case One – OFFPIM Application 51 2.7.3 Case Two – ONPIM Application 54 2.7.4 Discussions 56 2.8 Model Uncertainties 57 2.8.1 Battery Aging 57 2.8.2 Battery Type 59 2.8.3 Battery Temperature 61 2.9 Other Battery Models 62 2.10 Summary 64 References 64 3 Battery State of Charge and State of Energy Estimation 67 3.1 Background 67 3.2 Classification 67 3.2.1 Look-Up-Table-Based Method 67 3.2.2 Ampere-Hour Integral Method 68 3.2.3 Data-Driven Estimation Methods 69 3.2.4 Model-Based Estimation Methods 70 3.3 Model-Based SOC Estimation Method with Constant Model Parameters 71 3.3.1 Discrete-Time Realization Algorithm 71 3.3.2 Extended Kalman Filter 72 3.3.2.1 Selection of Correction Coefficients 73 3.3.2.2 SOC Estimation Based on EKF 73 3.3.3 SOC Estimation Based on HIF 75 3.3.4 Case Study 77 3.3.5 Influence of Uncertainties on SOC Estimation 78 3.3.5.1 Initial SOC Value 79 3.3.5.2 Dynamic Working Condition 80 3.3.5.3 Battery Temperature 81 3.4 Model-Based SOC Estimation Method with Identified Model Parameters in Real-Time 84 3.4.1 Real-Time Modeling Process 84 3.4.2 Case Study 86 3.5 Model-Based SOE Estimation Method with Identified Model Parameters in Real-Time 86 3.5.1 SOE Definition 87 3.5.2 State Space Modeling 87 3.5.3 Case Study 88 3.5.4 Influence of Uncertainties on SOE Estimation 89 3.5.4.1 Initial SOE Value 89 3.5.4.2 DynamicWorking Condition 90 3.5.4.3 Battery Temperature 90 3.6 Summary 92 References 92 4 Battery State of Health Estimation 95 4.1 Background 95 4.2 Experimental Methods 95 4.2.1 Direct Measurement Methods 96 4.2.1.1 Capacity or Energy Measurement 96 4.2.1.2 Internal Resistance Measurement 96 4.2.1.3 Impedance Measurement 97 4.2.1.4 Cycle Number Counting 97 4.2.1.5 Destructive Methods 98 4.2.2 Indirect Analysis Methods 98 4.2.2.1 Voltage Trajectory Method 98 4.2.2.2 ICA Method 100 4.2.2.3 DVA Method 102 4.3 Model-Based Methods 104 4.3.1 Adaptive State Estimation Methods 104 4.3.2 Data-Driven Methods 111 4.3.2.1 Empirical and Fitting Methods 112 4.3.2.2 Response Surface-Based Optimization Algorithms 112 4.3.2.3 Sample Entropy Methods 115 4.4 Joint Estimation Method 116 4.4.1 Relationship between SOC and Capacity 116 4.4.2 Case Study 117 4.5 Dual Estimation Method 118 4.5.1 Implementation with the AEKF Algorithm 118 4.5.2 SOC–SOH Estimation 122 4.5.3 Case Study 125 4.6 Summary 128 References 129 5 Battery State of Power Estimation 131 5.1 Background 131 5.2 Instantaneous SOP Estimation Methods 131 5.2.1 HPPC Method 132 5.2.2 SOC-Limited Method 133 5.2.3 Voltage-Limited Method 133 5.2.4 MCD Method 134 5.2.5 Case Study 136 5.3 Continuous SOP Estimation Method 139 5.3.1 Continuous Peak Current Estimation 139 5.3.2 Continuous SOP Estimation 140 5.3.3 Influences of Battery States and Parameters on SOP Estimation 141 5.3.3.1 Uncertainty of SOC 141 5.3.3.2 Case Study 142 5.3.3.3 Uncertainty of Model Parameters 146 5.3.3.4 Case Study 148 5.3.3.5 Uncertainty of SOH 150 5.4 Summary 154 References 154 6 Battery Charging 155 6.1 Background 155 6.2 Basic Terms for Evaluating Charging Performances 157 6.2.1 Cell and Pack 157 6.2.2 Nominal Ampere-Hour Capacity 157 6.2.3 C-rate 157 6.2.4 Cut-off Voltage for Discharge or Charge 157 6.2.5 Cut-off Current 157 6.2.6 State of Charge 158 6.2.7 State of Health 158 6.2.8 Cycle Life 158 6.2.9 Charge Acceptance 158 6.2.10 Ampere-Hour Efficiency 158 6.2.11 Ampere-Hour Charging Factor 159 6.2.12 Energy Efficiency 159 6.2.13 Watt-Hour Charging Factor 159 6.2.14 Trickle Charging 159 6.3 Charging Algorithms for Li-Ion Batteries 159 6.3.1 Constant Current and Constant Voltage Charging 160 6.3.2 Multistep Constant Current Charging 165 6.3.3 Two-Step Constant Current Constant Voltage Charging 168 6.3.4 Constant Voltage Constant Current Constant Voltage Charging 169 6.3.5 Pulse Charging 169 6.3.6 Charging Termination 172 6.3.7 Comparison of Charging Algorithms for Lithium-Ion Batteries 172 6.4 Optimal Charging Current Profiles for Lithium-Ion Batteries 173 6.4.1 Energy Loss Modeling 174 6.4.2 Minimization of Energy Loss 175 6.5 Lithium Titanate Oxide Battery with Extreme Fast Charging Capability 177 6.6 Summary 179 References 180 7 Battery Balancing 183 7.1 Background 183 7.2 Battery Sorting 184 7.2.1 Battery Sorting Based on Capacity and Internal Resistance 184 7.2.2 Battery Sorting Based on a Self-organizing Map 185 7.3 Battery Passive Balancing 189 7.3.1 Fixed Shunt Resistor 189 7.3.2 Switched Shunt Resistor 189 7.3.3 Shunt Transistor 190 7.4 Battery Active Balancing 191 7.4.1 Balancing Criterion 191 7.4.2 Balancing Control 193 7.4.3 Balancing Circuits 193 7.4.3.1 Cell to Cell 194 7.4.3.2 Cell to Pack 196 7.4.3.3 Pack to Cell 199 7.4.3.4 Cell to Energy Storage Tank to Cell 201 7.4.3.5 Cell to Pack to Cell 201 7.5 Battery Active Balancing Systems 203 7.5.1 Active Balancing System Based on the SOC as a Balancing Criterion 204 7.5.1.1 Battery Balancing Criterion 204 7.5.1.2 Battery Balancing Circuit 208 7.5.1.3 Battery Balancing Control 208 7.5.1.4 Experimental Results 208 7.5.2 Active Balancing System Based on FL Controller 212 7.5.2.1 Balancing Principle 215 7.5.2.2 Design of FL Controller 215 7.5.2.3 Adaptability of FL Controller 220 7.5.2.4 Battery Balancing Criterion 222 7.5.2.5 Experimental Results 222 7.6 Summary 227 References 227 8 Battery Management Systems in Electric Vehicles 231 8.1 Background 231 8.2 Battery Management Systems 231 8.2.1 Battery Parameter Acquisition Module 232 8.2.2 Battery System Balancing Module 233 8.2.3 Battery Information Management Module 236 8.2.4 Thermal Management Module 237 8.3 Typical Structure of BMSs 238 8.3.1 Centralized BMS 238 8.3.2 Distributed BMS 239 8.4 Representative Products 239 8.4.1 E-Power BMS 239 8.4.2 Klclear BMS 240 8.4.3 Tesla BMS 241 8.4.4 ICs for BMS Design 242 8.5 Key Points of BMSs in Future Generation 242 8.5.1 Self-Heating Management 243 8.5.2 Safety Management 244 8.5.3 Cloud Computing 244 8.6 Summary 247 References 247 Index 249

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Book SynopsisCoveringthe majortopics in lead-free soldering Lead-free Soldering Process Development and Reliabilityprovides a comprehensive discussion of all modern topics in lead-free soldering. Perfect forprocess, quality,failure analysisand reliability engineersin production industries,this reference will help practitioners address issues inresearch, development andproduction. Among other topics, the book addresses: Developments in process engineering(SMT, Wave, Rework, Paste Technology) Lowtemperature,hightemperature andhighreliabilityalloys Intermetallic compounds PCB surface finishesandlaminates Underfills, encapsulants and conformal coatings Reliability assessments In a regulatory environment that includes the adoption of mandatory lead-free requirements in a variety of countries, the book'sexplanations ofhigh-temperature, low-temperature, andhigh-reliabilitylead-free alloysin terms of process and reTable of ContentsList of Contributors xix Introduction xxi 1 Lead-Free Surface Mount Technology 1Jennifer Nguyen and Jasbir Bath 1.1 Introduction 1 1.2 Lead-Free Solder Paste Alloys 1 1.3 Solder Paste Printing 2 1.3.1 Introduction 2 1.3.2 Key Paste Printing Elements 2 1.4 Component Placement 5 1.4.1 Introduction 5 1.4.2 Key Placement Parameters 5 1.4.2.1 Nozzle 6 1.4.2.2 Vision System 6 1.4.2.3 PCB Support 6 1.4.2.4 Component Size, Packaging, and Feeder Capacity 6 1.4.2.5 Feeder Capacity 6 1.5 Reflow Process 7 1.5.1 Introduction 7 1.5.2 Key Parameters 7 1.5.2.1 Preheat 7 1.5.2.2 Soak 8 1.5.2.3 Reflow 8 1.5.2.4 Cooling 9 1.5.2.5 Reflow Atmosphere 9 1.6 Vacuum Soldering 9 1.7 Paste in Hole 10 1.8 Robotic Soldering 11 1.9 Advanced Technologies 12 1.9.1 Flip Chip 12 1.9.2 Package on Package 12 1.10 Inspection 13 1.10.1 Solder Paste Inspection (SPI) 13 1.10.2 Solder Joint Inspection 14 1.10.2.1 Automated Optical Inspection (AOI) 14 1.10.2.2 X-ray Inspection 15 1.11 Conclusions 16 References 17 2 Wave/Selective Soldering 19Gerjan Diepstraten 2.1 Introduction 19 2.2 Flux 19 2.2.1 The Function of a Flux 19 2.2.2 Flux Contents 20 2.3 Amount of Flux Application on a Board 20 2.4 Flux Handling 21 2.5 Flux Application 21 2.5.1 Methods to Apply Flux (Wave Soldering) 21 2.5.2 Methods to Apply Flux (Selective Soldering) 23 2.6 Preheat 24 2.6.1 Preheat Process-Heating Methods 24 2.6.2 Preheat Temperatures 27 2.6.3 Preheat Time 28 2.6.4 Controlling Preheat Temperatures 28 2.6.5 BoardWarpage Compensation (Selective Soldering) 29 2.7 Selective Soldering 29 2.7.1 Different Selective Soldering Point to Point Nozzles (Selective Soldering) 29 2.7.2 Solder Temperatures (Selective Soldering) 30 2.7.3 Dip/Contact Times (Selective Soldering) 31 2.7.4 Drag Conditions (Selective Soldering) 31 2.7.5 Nitrogen Environment (Selective Soldering) 31 2.7.6 Wave Height Controls (Selective Soldering) 32 2.7.7 De-Bridging Tools (Selective Soldering) 32 2.7.8 Solder Pot (Selective Soldering) 33 2.7.9 Topside Heating during Soldering (Selective Soldering) 34 2.7.10 Selective Soldering Dip Process with Nozzle Plates (Selective Soldering) 34 2.7.11 Solder Temperatures for Multi-Wave Dip Soldering (Selective Soldering) 35 2.7.12 Nitrogen Environment (Selective Soldering) 35 2.7.13 Wave Height Control (Selective Soldering) 36 2.7.14 Dip Time – Contact Time with Solder (Selective Soldering) 36 2.7.15 Solder Flow Acceleration and Deceleration (Selective Soldering) 37 2.7.16 De-Bridging Tools (Selective Soldering) 37 2.7.17 Pallets (Selective Soldering) 38 2.7.18 Conveyor (Selective Soldering) 38 2.8 Wave Soldering 39 2.8.1 Wave Formers (Wave Soldering) 39 2.8.2 Pallets (Wave Soldering) 40 2.8.3 Nitrogen Environment (Wave Soldering) 40 2.8.4 Process Control (Wave Soldering) 41 2.8.5 Conveyor (Wave Soldering) 41 2.9 Conclusions 42 References 42 3 Lead-Free Rework 43Jasbir Bath 3.1 Introduction 43 3.2 Hand Soldering Rework for SMT and PTH Components 43 3.2.1 Alloy and Flux Choices 43 3.2.1.1 Alloys 43 3.2.1.2 Flux 44 3.2.2 Soldering Iron Tip Life 44 3.2.3 Hand Soldering Temperatures and Times 47 3.3 BGA/CSP Rework 50 3.3.1 Alloy and Flux Choices 50 3.3.1.1 Alloys 50 3.3.1.2 Flux 50 3.3.2 BGA/CSP Rework Soldering Temperatures and Times 50 3.3.3 Component Temperatures in Relation to IPC/JEDEC J-STD-020 and Component/BoardWarpage Standards 52 3.3.3.1 IPC/JEDEC J-STD-020 Standard 52 3.3.3.2 ComponentWarpage Standards 52 3.3.3.3 BoardWarpage Standards 52 3.3.4 Equipment Updates for Lead-Free BGA/CSP Rework 53 3.3.5 Adjacent Component Temperatures 53 3.4 Non-standard Component Rework (Including BTC/QFN) 54 3.4.1 Alloy and Flux Choices 54 3.4.1.1 Alloys 54 3.4.1.2 Flux 54 3.4.2 Soldering Temperatures and Times 54 3.4.3 Non-standard Component Temperatures in Relation to IPC JEDEC J-STD-020 Standard and ComponentWarpage Standards 55 3.4.4 Equipment and Tooling Updates for Lead-Free Non-standard Component Rework 55 3.4.5 Adjacent Component Temperatures 56 3.4.6 Non-standard Component Rework Solder Joint Reliability 56 3.5 PTH (Pin-Through-Hole)Wave Rework 56 3.5.1 Alloy and Flux Choices 56 3.5.1.1 Alloys 56 3.5.1.2 Flux 57 3.5.2 Soldering Temperatures and Times 57 3.5.3 Component Temperatures in Relation to Industry and Board Standards During PTH Rework 67 3.5.3.1 Component Temperature Rating Standards 67 3.5.3.2 Bare Board Testing Standards and Methods for PTH Rework 67 3.5.4 Equipment Updates for PTH Component Rework 68 3.5.5 Adjacent Component Temperatures During PTH Rework 68 3.5.6 PTH Component Rework Solder Joint Reliability 68 3.5.6.1 Copper Dissolution 68 3.5.6.2 Holefill 69 3.6 Conclusions 69 References 70 4 Solder Paste and Flux Technology 73Shantanu Joshi and Peter Borgesen 4.1 Introduction 73 4.2 Solder Paste 75 4.2.1 Water-Soluble Solder Paste 75 4.2.2 No-Clean Solder Paste 76 4.3 Flux Technology 77 4.3.1 Halide-Free and Halide-Containing 77 4.4 Composition of Solder Paste 79 4.4.1 Alloy 79 4.4.2 Flux 82 4.4.3 Solder Powder Type 83 4.4.3.1 Oxide Layer 84 4.5 Characteristics of a Solder Paste 84 4.5.1 Printing 84 4.5.1.1 Printing Parameters 85 4.5.2 Reflow 86 4.5.2.1 Wetting/Spreadability of Lead-Free Solder Paste 86 4.5.2.2 Bridging 86 4.5.2.3 Micro Solder Balls 86 4.5.2.4 Voiding 86 4.5.2.5 Head-on-Pillow Component Soldering Defect 88 4.5.2.6 Non-Wet Open 90 4.5.2.7 Tombstoning 90 4.5.3 In-Circuit Test (ICT) Probe Testability 90 4.5.4 Flux Reliability Issues 91 4.6 Conclusions 92 References 92 5 Low Temperature Lead-Free Alloys and Solder Pastes 95Raiyo Aspandiar, Nilesh Badwe, and Kevin Byrd 5.1 Introduction 95 5.1.1 Definition of Low Temperature Solders 95 5.1.2 Benefits of Low Temperature Soldering 97 5.1.2.1 Reduced Manufacturing Cost 98 5.1.2.2 Power Use Savings 98 5.1.2.3 Environmental Benefits 99 5.1.2.4 Manufacturing Yield Improvements 100 5.1.3 Drawbacks 103 5.1.3.1 Brittleness 103 5.1.4 Other Low Temperature Metallurgical Systems 103 5.2 Development of Robust Bismuth-Based Low Temperature Solder Alloys 105 5.2.1 Bismuth-Tin (Bi-Sn) Phase Diagram 105 5.2.2 Mechanical Properties 107 5.2.3 Physical Properties 108 5.2.4 Alloy Development Progress 108 5.2.5 Fluxes for Low Temperature Solders 109 5.3 SMT Process Characterization of Sn-Bi Based Solder Pastes 111 5.3.1 Printability 111 5.3.2 Reflow Profiles 112 5.3.3 Rework 113 5.4 Polymeric Reinforcement of Sn-Bi Based Low Temperature Alloys 114 5.4.1 Current Polymeric Reinforcement Strategies 114 5.4.2 Joint Reinforced Pastes (JRP) 118 5.4.3 Polymeric Reinforcement Summary 128 5.5 Mixed SnAgCu-BiSn BGA Solder Joints 128 5.5.1 Formation Mechanism 128 5.5.2 Microstructural Features and Key Characteristics 133 5.5.3 Soldering Process Optimization 134 5.5.4 Possible Defects 135 5.6 Solder Joint Reliability 140 5.7 Conclusions 145 5.8 Future Development and Trends 146 References 149 6 High Temperature Lead-Free Bonding Materials – The Need, the Potential Candidates and the Challenges 155Hongwen Zhang and Ning-Cheng Lee 6.1 Introduction 155 6.2 Solder Materials 159 6.2.1 Gold-Based Solders 159 6.2.2 Bismuth-Rich Solders 160 6.2.2.1 Design of Bismuth-Rich Solders 160 6.2.2.2 Mechanical Behavior of BiAgX 163 6.2.2.3 Microstructure and Microstructural Evolution of BiAgX Joint 167 6.2.3 Tin-Antimony (Sn-Sb) High Temperature Solders 174 6.2.4 Zinc-Aluminum Solders 176 6.3 Silver (Ag)-Sintering Materials 178 6.4 Transient Liquid Phase Bonding Materials/Technique 181 6.5 Summary 182 Acknowledgment 185 References 185 7 Lead (Pb)-Free Solders for High Reliability and High-Performance Applications 191Richard J. Coyle 7.1 Evolution of Commercial Lead (Pb)-Free Solder Alloys 191 7.1.1 First Generation Commercial Pb-Free Solders 191 7.1.2 Second Generation Commercial Pb-Free Solders 192 7.1.3 Third Generation Commercial Pb-Free Solders 196 7.2 Third Generation Alloy Research and Development 196 7.2.1 Limitations of Sn-Ag-Cu Solder Alloys 196 7.2.2 Emergence of Commercial Third Generation Alloys 202 7.2.2.1 The Genesis of 3rd Generation Alloy Development 202 7.2.2.2 An Expanding Class of 3rd Generation Alloys 202 7.2.3 Metallurgical Considerations 203 7.2.3.1 Antimony (Sb) Additions to Tin (Sn) 206 7.2.3.2 Indium (In) Additions to Tin (Sn) 207 7.2.3.3 Bismuth (Bi) Additions to Tin (Sn) 209 7.3 Reliability Testing Third Generation Commercial Pb-Free Solders 210 7.3.1 Thermal Fatigue Evaluations 210 7.3.2 iNEMI/HDPUG Third Generation Alloy Pb-Free Thermal Fatigue Project 213 7.3.3 Microstructure and Reliability of Third Generation Alloys 219 7.4 Reliability Gaps and Suggestions for AdditionalWork 223 7.4.1 Root Cause of Interfacial Fractures 223 7.4.2 Effect of Component Attributes on Thermal Fatigue 224 7.4.3 Effect of Surface Finish on Thermal Fatigue 224 7.4.4 Thermomechanical Test Parameters and Test Outcomes 225 7.4.4.1 Thermal Cycling Dwell Time 225 7.4.4.2 Preconditioning (Isothermal Aging) 225 7.4.4.3 Thermal Cycling of Mixed Metallurgy BGA Assemblies 226 7.4.4.4 Thermal Shock or Aggressive Thermal Cycling 226 7.4.5 Reliability Under Mechanical Loading: Drop/Shock, and Vibration 227 7.4.6 Solder Alloy Microstructure and Reliability 230 7.4.7 Summary of Suggestions for Additional Investigation 231 7.5 Conclusions 232 Acknowledgments 234 References 234 8 Lead-Free Printed Wiring Board Surface Finishes 249Rick Nichols 8.1 Introduction: Why a Surface Finish is Needed 249 8.2 Surface Finishes in the Market 250 8.3 Application Perspective 255 8.4 A Description of Final Finishes 261 8.4.1 Hot Air Solder Leveling (HASL) 263 8.4.1.1 Process Complexity 263 8.4.1.2 Process Description 265 8.4.1.3 Issues and Remedies 267 8.4.1.4 Summary 267 8.4.2 High Temperature OSP 267 8.4.2.1 Process Complexity 267 8.4.2.2 Process Description 269 8.4.2.3 Issues and Remedies 270 8.4.2.4 Summary 270 8.4.3 Immersion Tin 271 8.4.3.1 Process Complexity 271 8.4.3.2 Process Description 273 8.4.3.3 Issues and Remedies 275 8.4.3.4 Summary 276 8.4.4 Immersion Silver 276 8.4.4.1 Process Complexity 277 8.4.4.2 Process Description 279 8.4.4.3 Issues and Remedies 280 8.4.4.4 Summary 281 8.4.5 Electroless Nickel Immersion Gold (ENIG) 281 8.4.5.1 Process Complexity 281 8.4.5.2 Process Description 283 8.4.5.3 Issues and Remedies 285 8.4.5.4 Summary 286 8.4.6 Electroless Nickel/Electroless Palladium/Immersion Gold (ENEPIG) 287 8.4.6.1 Process Complexity 287 8.4.6.2 Process Description 289 8.4.6.3 Issues and Remedies 290 8.4.6.4 Summary 291 8.4.7 Electroless Nickel Autocatalytic Gold (ENAG) 291 8.4.7.1 Process Complexity 292 8.4.7.2 Process Description 293 8.4.7.3 Issues and Remedies 295 8.4.7.4 Summary 295 8.4.8 Electroless Palladium Autocatalytic Gold (EPAG) 295 8.4.8.1 Process Complexity 295 8.4.8.2 Process Description 297 8.4.8.3 Issues and Remedies 298 8.4.8.4 Summary 299 8.4.9 Electrolytic Nickel Electrolytic Gold 299 8.4.9.1 Process Complexity 299 8.4.9.2 Process Description 301 8.4.9.3 Issues and Remedies 301 8.4.9.4 Summary 302 8.5 Conclusions 303 References 304 9 PCB Laminates (Including High Speed Requirements) 307Karl Sauter and Silvio Bertling 9.1 Introduction 307 9.2 Manufacturing Background 307 9.3 PCB Fabrication Design and Laminate Manufacturing Factors Affecting Yield and Reliability 308 9.3.1 High Frequency Loss 308 9.3.2 Mixed Dielectric 308 9.3.3 Back-Drilling 309 9.3.4 Aspect Ratio 309 9.3.5 PCB Fabrication 309 9.3.6 Press Lamination 310 9.3.7 Moisture Content 310 9.3.8 Laminate Material 311 9.4 Assembly Factors Affecting Yields and Long-Term Reliability for Laminate Materials 311 9.4.1 Reflow Temperature 311 9.4.2 Assembly Components 312 9.4.3 Thermal Stress 312 9.5 Copper Foil Trends (by Silvio Bertling) 312 9.6 High Frequency/High Speed and Other Trends Affecting Laminate Materials 316 9.6.1 High Speed Standards 316 9.6.2 Adhesion Treatment (Prior to Press Lamination) 317 9.6.3 Laminate Material Filler Content 317 9.6.4 GlassWeave Effect 317 9.6.5 Halogen-Free 318 9.7 Conclusions 318 References 319 10 Underfills and Encapsulants Used in Lead-Free Electronic Assembly 321Brian J. Toleno 10.1 Introduction 321 10.2 Rheology 322 10.2.1 Rheological Response and Behavior 323 10.2.1.1 Thixotropy 325 10.2.2 Measuring Rheology 327 10.2.2.1 Spindle Type Viscometry 327 10.2.2.2 Cone and Plate Rheometry 328 10.3 Curing of Adhesive Systems 330 10.3.1 Thermal Cure 330 10.3.2 Ultraviolet (UV) Light Curing 335 10.3.3 Moisture Cure 338 10.4 Glass Transition Temperature 339 10.5 Coefficient of Thermal Expansion (CTE) 341 10.6 Young’s Modulus (E) 343 10.7 Applications 344 10.7.1 Underfills 344 10.7.1.1 Capillary Underfill 345 10.7.1.2 Fluxing (No-Flow) Underfill 348 10.7.1.3 Removable/Reworkable Underfill 349 10.7.1.4 Staking or Corner Bond Underfill 349 10.7.2 Encapsulant Materials 350 10.7.2.1 Glob Top 351 10.7.2.2 Component Encapsulation 351 10.7.2.3 Application 353 10.7.2.4 Low-Pressure Molding 355 10.8 Conclusions 355 References 355 11 Thermal Cycling and General Reliability Considerations 359Maxim Serebreni 11.1 Introduction to Thermal Cycling of Electronics 359 11.1.1 Influence of Solder Alloy Composition and Microstructure on Thermal Cycling Reliability 362 11.2 Influence of Package Type and Thermal Cycling Profile 363 11.2.1 Influence of Board and Pad Design 366 11.3 Fatigue Life Prediction Models 371 11.3.1 Empirical Models and Acceleration Factors 371 11.3.2 Semi-empirical Models 372 11.3.3 Finite Element Analysis (FEA) Based Fatigue Life Predictions 373 11.4 Conclusions 376 References 377 12 Intermetallic Compounds 381Alyssa Yaeger, Travis Dale, Elizabeth McClamrock, Ganesh Subbarayan, and Carol Handwerker 12.1 Introduction 381 12.1.1 Solders 382 12.1.2 Interaction with Substrates 382 12.2 Setting the Stage 384 12.2.1 Mechanical and Thermomechanical Response of Solder Joints 386 12.3 Common Lead-Free Solder Alloy Systems 392 12.3.1 Solder Joints Formed Between Sn-Cu, Sn-Ag, and Sn-Ag-Cu Solder Alloys and Copper Surface Finishes 396 12.3.1.1 Sn-Cu Solder on Copper 396 12.3.1.2 Sn-Ag and Sn-Ag-Cu Solder Alloys on Copper 399 12.3.2 Solder Joints Formed Between Sn-Cu, Sn-Ag, and Sn-Ag-Cu Alloys and Nickel Surface Finishes 408 12.3.2.1 Ni-Sn 408 12.3.2.2 Sn-Ag Solder Alloys on Nickel 411 12.3.2.3 Spalling 415 12.3.2.4 Effects of Phosphorus Concentration in ENIG on Solder Joint Reliability 416 12.3.3 Au-Sn 417 12.4 High Lead – Exemption 422 12.5 Conclusions 423 References 423 13 Conformal Coatings 429Jason Keeping 13.1 Introduction 429 13.2 Environmental, Health, and Safety (EHS) Requirements 430 13.3 Overview of Types of Conformal Coatings 430 13.3.1 Types of Conformal Coatings 431 13.3.1.1 Acrylic Resins (Type AR) 432 13.3.1.2 Urethane Resins (Type UR) 433 13.3.1.3 Epoxy Resins (Type ER) 433 13.3.1.4 Silicone Resins (Type SR) 435 13.3.1.5 Para-xylylene (Type XY) 436 13.3.1.6 Synthetic Rubber (Type SC) 437 13.3.1.7 Ultra-Thin (Type UT) 438 13.4 Preparatory Steps Necessary to Ensure a Successful Coating Process 440 13.4.1 Assembly Cleaning 440 13.4.2 Assembly Masking 440 13.4.3 Priming and Other Surface Treatments 441 13.4.3.1 Measuring Surface Energy 441 13.4.3.2 Water Drop Contact Angle 447 13.4.4 Bake-Out 448 13.5 Various Methods of Applying Conformal Coating 449 13.5.1 Manual Coating 449 13.5.2 Dip 449 13.5.3 Hand Spray 450 13.5.4 Automatic Spray 451 13.5.5 Selective Coating 451 13.5.6 Vapor Deposition 451 13.6 Aspects for Cure, Inspection, and Demasking 453 13.6.1 Cure 453 13.6.1.1 Solvent Evaporation 453 13.6.1.2 Room Temperature Vulcanization (RTV) 454 13.6.1.3 Heat Cure 454 13.6.1.4 UV Cure 454 13.6.1.5 Catalyzed 454 13.6.2 UV Inspection 455 13.6.3 Demasking 455 13.7 Repair and Rework Processes 456 13.7.1 Chemical 456 13.7.2 Thermal 456 13.7.3 Mechanical 457 13.7.4 Abrasion (Micro-Abrasion) 457 13.7.5 Plasma Etch 457 13.8 Design Guidance on When and Where Conformal Coating is Required, and Which Physical Characteristics and Properties are Important to Consider 457 13.8.1 Is Conformal Coating Required? 458 13.8.1.1 Why Use It? 458 13.8.1.2 Why Not Use Conformal Coating? 459 13.8.2 Desirable Material Properties 459 13.8.3 Areas to Mask 461 13.9 Long-Term Reliability and Testing 462 13.10 Conclusions 462 13.11 Future Work 463 References 463 Index 467

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Book SynopsisGuides the reader through a risk assessment and shows them the proper tools to be used at the various steps in the process This brand new edition of one of the most authoritative books on risk assessment adds ten new chapters to its pages to keep readers up to date with the changes in the types of risk that individuals, businesses, and governments are being exposed to today. It leads readers through a risk assessment and shows them the proper tools to be used at various steps in the process. The book also provides readers with a toolbox of techniques that can be used to aid them in analyzing conceptual designs, completed designs, procedures, and operational risk. Risk Assessment: Tools, Techniques, and Their Applications, Second Editionincludes expanded case studies and real life examples; coverage on risk assessment software like SAPPHIRE and RAVEN; and end-of-chapter questions for students. Chapters progress from the concept of risk, through the simple Table of ContentsAcknowledgments vii About the Companion Website ix 1 Introduction to Risk Assessment 1 2 Risk Perception 11 3 Risks and Consequences 17 4 Ecological Risk Assessment 27 5 Task Analysis Techniques 53 6 Preliminary Hazard Analysis 61 7 Primer on Probability and Statistics 79 8 Mathematical Tools for Updating Probabilities 93 9 Developing Probabilities 115 10 Quantifying the Unquantifiable 133 11 Failure Mode and Effects Analysis 145 12 Human Reliability Analyses 159 13 Critical Incident Technique 175 14 Basic Fault Tree Analysis Technique 185 15 Critical Function Analysis 203 16 Event Tree and Decision Tree Analysis 223 17 Probabilistic Risk Assessment 251 18 Probabilistic Risk Assessment Software 261 19 Qualitative and Quantitative Research Methods Used in Risk Assessment 267 20 Risk of an Epidemic 283 21 Vulnerability Analysis Technique 293 22 Developing Risk Model for Aviation Inspection and Maintenance Tasks 317 23 Risk Assessment and Community Planning 329 24 Threat Assessment 343 25 Project Risk Management 381 26 Enterprise Risk Management Overview 409 27 Process Safety Management and Hazard and Operability Assessment 419 28 Emerging Risks 449 29 Process Plant Risk Assessment Example 461 30 Risk Assessment Framework for Detecting, Predicting, and Mitigating Aircraft Material Inspection 487 31 Traffic Risks 547 Acronyms 559 Glossary 563 Index 569

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Book SynopsisCovers all aspects of electrical systems for nuclear power plants written by an authority in the field Based on author Omar Mazzoni's notes for a graduate level course he taught in Electrical Engineering, this book discusses all aspects of electrical systems for nuclear power plants, making reference to IEEE nuclear standards and regulatory documents. It covers such important topics as the requirements for equipment qualification, acceptance testing, periodic surveillance, and operational issues. It also provides excellent guidance for students in understanding the basis of nuclear plant electrical systems, the industry standards that are applicable, and the Nuclear Regulatory Commission's rules for designing and operating nuclear plants. Electrical Systems for Nuclear Power Plants offers in-depth chapters covering: elements of a power system; special regulations and requirements; unique requirements of a Class 1E power system; nuclear plants containment electrical penetration assemTable of ContentsPreface xiii 1 Elements of a Power System 1 1.1 The Alternating Current One-Line Diagram 1 1.2 Basis for One-Line Representation 3 1.3 Main Electrical Components of Power Plants 4 1.4 Transmission Lines, Switchyards, and Substations 5 Questions and Problems 6 References 8 2 Nuclear Power Plants: General Information 9 2.1 Introduction 9 2.2 Environmental Impact 9 2.3 Nuclear Generation Fuel Cycle 10 2.4 Evolution of Nuclear Power Generation 13 2.5 Nuclear Power in the United States 13 2.6 Plans for New ReactorsWorldwide 14 2.7 Increased Capacity 14 2.8 Nuclear Plant Construction 14 2.9 Nuclear Plant Licensing 14 2.10 Current Commercial Nuclear Plants 15 2.11 Evolutionary Commercial Nuclear Plants 18 2.12 Advanced Reactors 20 2.13 Nuclear Accidents: Three Mile Island, Chernobil, and Fukushima Events 22 Questions and Problems 32 References 33 3 Special Regulations and Requirements 35 3.1 Regulations 35 3.2 IEEE Standards 39 3.3 NRC Regulatory Guides 39 Questions and Problems 42 References 43 4 Unique Requirements: Class 1E Power System 45 4.1 Class 1E Electrical Systems: General Description 45 4.2 Specific Requirements for Class 1E ac Power Systems 48 4.3 Specific Requirements for Class 1E DC Power Systems 48 4.4 Specific Requirements for Class 1E Instrumentation and Control Systems 49 4.5 Specific Requirements for Class 1E Containment Electrical Penetrations 50 4.6 Specific Requirements for Emergency On-Site ac Power Sources 50 Questions and Problems 51 References 52 5 Nuclear Plants Containment Electrical Penetration Assemblies 53 5.1 Containment Electrical Penetration Assemblies: General (Information on this chapter is based on the requirements of IEEE 317) 53 5.2 Service Classification 54 5.3 Electrical Design Requirements (extracted from IEEE 317) 56 5.4 Mechanical Design Requirements (Extracted from IEEE 317) 59 5.5 Fire Resistance Requirements (Extracted from IEEE 317) 61 5.6 Qualified Life 62 5.7 Qualification Tests 62 5.8 Design Tests (Extracted from IEEE 317) 62 5.9 Production Tests 67 5.10 Monitoring and Testability 67 Questions and Problems 67 References 68 6 On-Site Emergency Alternating Current Source 71 6.1 General Requirements of the Emergency Alternating Current Source 71 6.2 General Requirements of Diesel Generators Used as Emergency Alternating Current Source (Information in this chapter is based on the requirements of IEEE 387) 72 6.3 Specific Design Requirements for Emergency Diesel Generators 79 6.4 Factory Qualification 82 6.5 Site Acceptance Testing 87 6.6 Site Preoperational Testing 87 6.7 Site Operational Testing 87 6.8 Site Periodic Testing and Surveillance: Preventive Maintenance Program 93 Questions and Problems 96 References 97 7 On-Site Emergency Direct Current Source 101 7.1 Energy Storage Systems for Nuclear Generating Stations 101 7.2 General Requirements of Direct Current Systems 101 7.3 Design Requirements 102 7.4 Battery Loads 103 7.5 Classification of Loads in Terms of Power versus Voltage Characteristics 105 7.6 Battery Chargers 111 Questions and Problems 112 References 114 8 Protective Relaying 115 8.1 General 115 8.2 General Criteria for the Protection System 115 8.3 Specific Criteria for Protection of Alternating Current Systems 116 8.4 Degraded Voltage Protection 124 8.5 Surge Protection 128 8.6 Protection for Instrumentation and Control Power System 128 8.7 Protection Aspects for Auxiliary System Automatic Bus Transfer 129 8.8 Protection for Primary Containment Electrical Penetration Assemblies 137 8.9 Protection of Valve Actuator Motors (Direct Gear Driven) 137 8.10 Protection for DC Systems 144 8.11 Testing and Surveillance of Protective Systems 144 Questions and Problems 145 References 148 9 Interface of the Nuclear Plant with the Grid 151 9.1 Preferred Power Supply Safety Function 151 9.2 Interface between the Nuclear Plant and the Grid 155 9.3 Transmission Line and Switchyard Protective Relaying 156 9.4 Connections of the PPS to the Class 1E Systems 157 9.5 Switchyard Grounding 157 9.6 Switchyard and Transmission Line Surveillance and Testing 158 9.7 Effect of PPS Voltage Degradation on the Class 1E Bus 158 9.8 Multiunit Considerations 159 9.9 Considerations for PPS Reliability in a Deregulated Environment 159 9.10 Alternate AC Source 162 9.11 Study of Recent Events 162 Questions and Problems 163 References 165 10 Station Blackout: Issues and Regulations 167 10.1 Introduction 167 10.2 Regulations Relating to SBO Requirements 168 10.3 Specific SBO Requirements 169 10.4 Alternate Alternating Current Power Sources 170 10.5 Procedures and Training 174 10.6 QA and Specifications for Nonsafety-Related Equipment 176 10.7 Monitoring of the Grid Condition 177 Questions and Problems 177 References 178 11 Review of Electric Power Calculations 181 11.1 Introduction 181 11.2 Load and Voltage Calculations 181 11.3 Motor Starting Calculations 183 Questions and Problems 186 References 188 12 Plant Life: Equipment Aging, Life Extension, and Decommissioning 189 12.1 Nuclear Plant Licensed Life 189 12.2 Importance of Maintenance: The Maintenance Rule (Courtesy of the NRC) 189 12.3 Monitoring Issues Affecting Electrical Equipment, Transformers, Motors, Cable, Control Equipment 193 12.4 Cable-Monitoring Methods and Techniques (Courtesy of NRC) 194 12.5 Further Information on Cable Testing 201 12.6 Switchyard Maintenance Activities 202 12.7 Emergency Diesel Generators 202 12.8 Interpretation of “Standby” 202 12.9 Normally Operating SSCs of Low Safety Significance 203 12.10 Establishing SSC-Specific Performance Criteria 203 12.11 Clarification of MPFFs Related to Design Deficiencies 204 12.12 Scope of the Hazards to be Considered during Power Operations 204 12.13 Scope of Initiators to be Considered for Shutdown Conditions 204 12.14 Fire Scenario Success Path(s) 205 12.15 Establishing Action Thresholds Based on Quantitative Considerations 205 12.16 SSCs Considered under 10 CFR 50.65(a)(1) 205 12.17 Inclusion of Electrical Distribution Equipment 206 12.18 The License Renewal Rule 206 12.19 Interpretation of Aging 207 12.20 Effects of Plant Aging 207 Questions and Problems 208 References 209 13 Electrical and Control Systems Inspections 213 13.1 Purpose of Inspections 213 13.2 Objectives of Inspections 213 13.3 Areas of Review 214 13.4 Typical Approach to the Review 214 13.5 Acceptance Criteria 215 Questions and Problems 216 Reference 217 Appendix 1 Abbreviations 219 Appendix 2 Definitions 231 Index 239

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Book SynopsisSummarizes and surveys current LTE technical specifications and implementation options for engineers and newly qualified support staff Concentrating on three mobile communication technologies, GSM, 3G-WCDMA, and LTEwhile majorly focusing on Radio Access Network (RAN) technologythis book describes principles of mobile radio technologies that are used in mobile phones and service providers' infrastructure supporting their operation. It introduces some basic concepts of mobile network engineering used in design and rollout of the mobile network. It then follows up with principles, design constraints, and more advanced insights into radio interface protocol stack, operation, and dimensioning for three major mobile network technologies: Global System Mobile (GSM) and third (3G) and fourth generation (4G) mobile technologies. The concluding sections of the book are concerned with further developments toward next generation of mobile network (5G). Those include some of the maTable of ContentsForeword xvii Acknowledgements xix Abbreviations xxi 1 Introduction 1 2 Types of Mobile Network by Multiple-Access Scheme 3 3 Cellular System 5 3.1 Historical Background 5 3.2 Cellular Concept 5 3.3 Carrier-to-Interference Ratio 6 3.4 Formation of Clusters 8 3.5 Sectorization 9 3.6 Frequency Allocation 10 3.7 Trunking Effect 11 3.8 Erlang Formulas 13 3.9 Erlang B Formula 13 3.10 Worked Examples 14 3.10.1 Problem 1 14 3.10.2 Problem 2 16 3.10.3 Problem 3 16 4 Radio Propagation 19 4.1 Propagation Mechanisms 19 4.1.1 Free-Space Propagation 19 4.1.2 Propagation Models for Path Loss (Global Mean) Prediction 22 5 Mobile Radio Channel 27 5.1 Channel Characterization 28 5.1.1 Narrowband Flat Channel 31 5.1.2 Wideband Frequency Selective Channel 31 5.1.3 Doppler Shift 34 5.2 Worked Examples 36 5.2.1 Problem 1 36 5.2.2 Problem 2 36 5.3 Fading 36 5.3.1 Shadowing/Slow Fading 37 5.3.2 Fast Fading/Rayleigh Fading 40 5.4 Diversity to Mitigate Multipath Fading 42 5.4.1 Space and Polarization Diversity 42 5.5 Worked Examples 44 5.5.1 Problem 1 44 5.5.2 Problem 2 44 5.5.3 Problem 3 45 5.6 Receiver Noise Factor (Noise Figure) 45 6 Radio Network Planning 49 6.1 Generic Link Budget 49 6.1.1 Receiver Sensitivity Level 50 6.1.2 Design Level 50 6.1.2.1 Rayleigh Fading Margin 51 6.1.2.2 Lognormal Fading Margin 51 6.1.2.3 Body Loss 51 6.1.2.4 Car Penetration Loss 51 6.1.2.5 Design Level 51 6.1.2.6 Building Penetration Loss 52 6.1.2.7 Outdoor-to-Indoor Design Level 52 6.1.3 Power Link Budget 52 6.1.4 Power Balance 53 6.2 Worked Examples 56 6.2.1 Problem 1 56 6.2.2 Problem 2 57 6.2.3 Problem 3 58 7 Global System Mobile, GSM, 2G 59 7.1 General Concept for GSM System Development 59 7.2 GSM System Architecture 59 7.2.1 Location Area Identity (LAI) 62 7.2.2 The SIM Concept 63 7.2.3 User Addressing in the GSM Network 63 7.2.4 International Mobile Station Equipment Identity (IMEI) 63 7.2.5 International Mobile Subscriber Identity (IMSI) 64 7.2.6 Different Roles of MSISDN and IMSI 64 7.2.7 Mobile Station Routing Number 64 7.2.8 Calls to Mobile Terminals 65 7.2.9 Temporary Mobile Subscriber Identity (TMSI) 66 7.2.10 Security-Related Network Functions: Authentication and Encryption 66 7.2.11 Call Security 67 7.2.12 Operation and Maintenance Security 69 7.3 Radio Specifications 69 7.3.1 Spectrum Efficiency 69 7.3.2 Access Technology 71 7.3.3 MAHO and Measurements Performed by Mobile 72 7.3.4 Time Slot and Burst 73 7.3.4.1 Normal Burst 74 7.3.4.2 Frequency Correction Burst (FB) 74 7.3.4.3 Synchronization Burst 75 7.3.4.4 Access Burst 75 7.3.4.5 Dummy Burst 75 7.3.5 GSM Adaptation to a Wideband Propagation Channel 76 7.3.5.1 Training Sequence and Equalization 76 7.3.5.2 The Channel Equalization 77 7.3.5.3 Diversity Against Fast Fading 78 7.3.5.4 Frequency Hopping 79 7.4 Background for the Choice of Radio Parameters 81 7.4.1 Guard Period, Timing Advance 83 7.5 Communication Channels in GSM 84 7.5.1 Traffic Channels (TCHs) 84 7.5.2 Control Channels 85 7.5.2.1 Common Control Channels 85 7.5.2.2 Dedicated Control Channels 86 7.6 Mapping the Logical Channels onto Physical Channels 86 7.6.1 Frame Format 87 7.6.2 Transmission of User Information: Fast Associated Control Channel 88 7.6.2.1 Data Rates 88 7.6.3 Signalling Multiframe, 51-Frame Multiframe 88 7.6.4 Synchronization 89 7.6.4.1 Frequency Synchronization 90 7.6.4.2 Time Synchronization 90 7.6.5 Signalling Procedures over the Air Interface 90 7.6.5.1 Synchronization to the Base Station 90 7.6.5.2 Registering With the Base Station 91 7.6.5.3 Call Setup 91 7.7 Signalling During a Call 93 7.7.1 Measuring the Signal Levels from Adjacent Cells 93 7.7.2 Handover 94 7.7.2.1 Intra-Cell and Inter-Cell Handover 95 7.7.2.2 Intra- and Inter-BSC Handover 95 7.7.2.3 Intra- and Inter-MSC Handover 95 7.7.2.4 Intra- and Inter-PLMN Handover 95 7.7.2.5 Handover Triggering 95 7.7.3 Power Control 96 7.8 Signal Processing Chain 97 7.8.1 Speech and Channel Coding 97 7.8.2 Reordering and Interleaving of the TCH 99 7.9 Estimating Required Signalling Capacity in the Cell 100 7.9.1 SDCCH Configuration 100 7.9.2 Worked Example 101 7.9.2.1 Problem 1 101 References 102 8 EGPRS: GPRS/EDGE 103 8.1 GPRS Support Nodes 103 8.2 GPRS Interfaces 104 8.3 GPRS Procedures in Packet Call Setups 104 8.4 GPRS Mobility Management 105 8.4.1 Mobility Management States 106 8.4.1.1 IDLE State 106 8.4.1.2 READY State 106 8.4.1.3 STANDBY State 106 8.4.2 PDP Context Activation 107 8.4.3 Location Management 108 8.5 Layered Overview of the Radio Interface 108 8.5.1 SNDP 108 8.5.2 Layer Services 109 8.5.3 Radio Link Layer 110 8.5.3.1 RLC Block Structure 110 8.5.4 GPRS Logical Channels 111 8.5.5 Mapping to Physical GPRS Channels 111 8.5.6 Channel Sharing 112 8.5.6.1 Downlink Radio Channel 113 8.5.6.2 Uplink Radio Channel 113 8.5.7 TBF 113 8.5.7.1 TBF Establishment 113 8.5.7.2 DL TBF Establishment 113 8.5.8 EGPRS Channel Coding and Modulation 15 8.6 GPRS/GSM Territory in a Base-Station Transceiver 115 8.6.1 PS Capacity in the Base Station/Cell 116 8.7 Summary 118 References 119 9 Third Generation Network (3G), UMTS 121 9.1 The WCDMA Concept 123 9.1.1 Spreading (Channelization) 124 9.1.2 Scrambling 127 9.1.3 Multiservice Capacity 128 9.1.4 Power Control 129 9.1.4.1 Open-Loop Power Control 130 9.1.4.2 Outer-Loop Power Control 130 9.1.5 Handover 132 9.1.5.1 Softer Handover 132 9.1.5.2 Other Handovers 134 9.1.5.3 Compressed Mode 134 9.1.6 RAKE Reception 135 9.2 Major Parameters of 3G WCDMA Air Interface 136 9.3 Spectrum Allocation for 3G WCDMA 136 9.4 3G Services 138 9.4.1 Bearer Service and QoS 138 9.5 UMTS Reference Network Architecture and Interfaces 140 9.5.1 The NodeB (Base Station) Functions in the 3G Network 141 9.5.2 Role of the RNC in 3G Network 141 9.6 Air-Interface Architecture and Processing 142 9.6.1 Physical Layer (Layer 1) 144 9.6.2 Medium Access Control (MAC) on Layer 2 144 9.6.3 Radio Link Control (RLC) on Layer 2 145 9.6.4 RRC on Layer 3 in the Control Plane 145 9.7 Channels on the Air Interface 146 9.7.1 Logical Channels 146 9.7.2 Transport Channels 146 9.7.2.1 Dedicated Transport Channel (DCH) 147 9.7.2.2 Common Transport Channels 147 9.7.3 Physical Channels and Physical Signals 148 9.7.4 Parameters of the Transport Channel 148 9.8 Physical-Layer Procedures 150 9.8.1 Processing of Transport Blocks 151 9.8.2 Spreading and Modulation 154 9.8.3 Modulation Scheme in UTRAN FDD 155 9.8.4 Composition of the Physical Channels 157 9.8.4.1 Dedicated Physical Channel 157 9.8.4.2 Common Downlink Physical Channels 160 9.9 RRC States 162 9.9.1 Idle Mode 162 9.9.2 RRC Connected Mode 164 9.9.3 RRC Connection Procedures 165 9.9.4 RRC State Transition Cases 166 9.10 RRM Functions 167 9.10.1 Admission Control Principle 167 9.10.2 Load/Congestion Control 168 9.10.3 Code Management 168 9.10.4 Packet Scheduling 168 9.11 Initial Access to the Network 169 9.12 Summary 170 References 171 10 High-Speed Packet Data Access (HSPA) 173 10.1 HSDPA, High-Speed Downlink Packet Data Access 173 10.2 HSPA RRM Functions 175 10.2.1 Channel-Dependent Scheduling for HS-DSCH 175 10.2.2 Rate Control, Dynamic Resource Allocation, Adaptive Modulation and Coding 176 10.2.3 Hybrid-ARQ with Soft Combining, HARQ 176 10.2.4 Retransmission Mechanism in the NodeB 176 10.2.5 Impact to Protocol Architecture 177 10.2.6 HARQ Schemes 178 10.3 MAC-hs and Physical-Layer Processing 181 10.4 HSDPA Channels 182 10.4.1 High-Speed Downlink Shared Channel (HS-DSCH) 182 10.4.2 HSDPA Control Channels 183 10.4.2.1 Fractional Downlink Power Control Channel 184 10.4.3 HS-DSCH Link Adaptation 184 10.5 HSUPA (Enhanced Uplink, E-DCH) 189 10.5.1 Control Signalling 190 10.5.2 Scheduling 190 10.6 Air-Interface Dimensioning 192 10.6.1 Input Parameters and Requirements 192 10.6.2 Traffic Demand Estimation 193 10.6.2.1 PS Data Services (Release 99) 193 10.6.2.2 HSPA Data Services 193 10.6.3 Standard Traffic Model 194 10.6.4 Link Budgets 195 10.6.4.1 Uplink Load Factor 196 10.6.4.2 Downlink Load Factor 197 10.6.4.3 Link Budget for R99 Bearers 198 10.6.4.4 Link Budget for HSPA 199 10.6.4.5 Results of Link Budget: Cell Range Calculation, Balancing UL with DL 199 10.6.4.6 Link Budget for Common Pilot Channel Signal 200 10.6.4.7 Link Budget Calculation for the Shared Release 99 and HSDPA Carriers 200 10.6.5 Uplink Capacity Estimation 201 10.6.5.1 Required Bandwidth and Load for Multiple Bearers with GOS Considerations 202 10.6.5.2 Simplified Estimation of HSDPA Throughput Capacity 202 10.7 Summary 203 References 204 11 4G-Long Term Evolution (LTE) System 205 11.1 Introduction 205 11.2 Architecture of an Evolved Packet System 206 11.3 LTE Integration with Existing 2G/3G Network 207 11.3.1 EPS Reference Points and Interfaces 208 11.4 E-UTRAN Interfaces 209 11.5 User Equipment 210 11.5.1 LTE UE Category 210 11.6 QoS in LTE 211 11.7 LTE Security 212 11.8 LTE Mobility 214 11.8.1 Idle Mode Mobility 214 11.8.2 ECM-CONNECTED Mode Mobility 215 11.8.3 Mobility Anchor 216 11.8.4 Inter-eNB Handover 216 11.8.5 3GPP Inter-RAT Handover 218 11.8.6 Differences in E-UTRAN and UTRAN Mobility 218 11.9 LTE Radio Interface 219 11.10 Principle of OFDM 220 11.11 OFDM Implementation using IFFT/FFT Processing 223 11.12 Cyclic Prefix 223 11.13 Channel Estimation and Reference Symbols 225 11.14 OFDM Subcarrier Spacing 227 11.15 Output RF Spectrum Emissions 227 11.16 LTE Multiple-Access Scheme, OFDMA 228 11.17 Single-Carrier FDMA (SC-FDMA) 229 11.18 OFDMA versus SC-FDMA Operation 230 11.19 SC-FDMA Receiver 231 11.20 User Multiplexing with DFTS-OFDM 231 11.21 MIMO Techniques 232 11.21.1 Precoding 234 11.21.2 Cyclic Delay Diversity (CDD) 236 11.22 Link Adaptation and Frequency Domain Packet Scheduling 237 11.23 Radio Protocol Architecture 238 11.23.1 User Plane 239 11.23.2 Control Plane 239 11.23.3 Scheduler 240 11.23.4 Logical and Transport Channels 240 11.23.5 Physical Layer 242 11.23.6 RRC State Machine 244 11.23.7 Time-Frequency Structure of the LTE FDD Physical Layer 244 11.24 Downlink Physical Layer Processing 248 11.24.1 Multiplexing and Channel Coding for Downlink Transport Channels 248 11.24.2 CRC Computation and Attachment to the Transport Block 248 11.24.3 Code Block Segmentation and Code Block CRC Attachment 249 11.24.4 Channel Coding 249 11.24.5 Rate Matching for Turbo Coded Transport Channels 249 11.24.6 Downlink Control Information Coding 250 11.24.7 Physical Channel Processing 250 11.24.7.1 Bit-Level Scrambling 251 11.24.7.2 Data Modulation 251 11.24.7.3 Layer Mapping 252 11.24.7.4 Precoding 252 11.24.7.5 Mapping to Resource Elements 255 11.24.7.6 Downlink Reference Signals 256 11.25 Downlink Control Channels 258 11.25.1 Structure of the Synchronization Channel 258 11.25.2 Time-Domain Position of Synchronization Signals 259 11.25.3 Frequency Domain Structure of Synchronization Signals 259 11.25.3.1 PSS Structure 259 11.25.3.2 SSS Structure 260 11.25.4 PBCH 260 11.25.5 Physical Control Format Indicator Channel: PCFICH 262 11.25.6 PDCCH 263 11.25.7 PHICH, Physical Hybrid-ARQ Indicator Channel 264 11.26 Mapping the Control Channels to Downlink Transmission Resources 264 11.27 Uplink Control Signalling 264 11.27.1 Processing of the Uplink Shared Transport Channel 266 11.27.2 Channel Coding of Control Information 266 11.27.3 Multiplexing and Channel Interleaving 266 11.27.4 Processing for Physical Uplink Shared Channel 268 11.27.5 Physical Uplink Control Channel, PUCCH 269 11.27.6 Multiplexing of UEs Within a PUCCH 269 11.27.7 Physical Random Access Channel (PRACH) 270 11.28 Uplink Reference Signals 271 11.28.1 Mapping of Reference Signals to the Uplink Frame Structure 272 11.29 Physical-Layer Procedures 273 11.29.1 Cell Search 273 11.29.2 Random Access Procedure 274 11.29.3 Link Adaptation 276 11.29.4 Power Control 277 11.29.5 Paging 278 11.29.6 HARQ 278 11.30 LTE Radio Dimensioning 279 11.30.1 LTE Coverage Dimensioning: Link Budget 280 11.30.1.1 Physical-Layer Overhead Factors 281 11.30.1.2 Multi-Antenna Systems 284 11.30.1.3 Required SINR 285 11.30.1.4 Link Budget Margins 285 11.30.1.5 Interference Margin 285 11.30.1.6 Maximum Allowable Path Loss (MAPL) 287 11.30.1.7 Required SINR 288 11.30.2 Cell Range and Cell Capacity 288 11.31 Summary 289 References 290 12 LTE-A 293 12.1 Carrier Aggregation 296 12.2 Enhanced MIMO 300 12.3 Coordinated Multi-Point Operation (CoMP) 303 12.3.1 CoMP Categories 304 12.3.2 Downlink CoMP 306 12.3.3 Uplink CoMP 307 12.4 Relay Nodes 309 12.4.1 Relay Radio Access 309 12.4.2 Relay Architecture 311 12.4.3 Resource Assignment for DeNB-RN Link in a Type 1 Relay 314 12.5 Enhanced Physical Downlink Control Channel (E-PDCCH) 315 12.6 Downlink Multiuser Superposition, MUST 315 12.7 Summary of LTE-A Features 317 References 317 13 Further Development for the Fifth Generation 319 13.1 Overall Operational Requirements for a 5G Network System 320 13.2 Device Requirements 320 13.3 Capabilities of 5G 321 13.4 Spectrum Consideration 321 13.5 5G Technology Components 322 13.5.1 Technologies to Enhance the Radio Interface 322 13.5.1.1 Advanced Modulation-and-Coding Schemes 323 13.5.1.2 Non-Orthogonal Multiple Access (NOMA) 323 13.5.1.3 Active Antenna System (AAS) 326 13.5.1.4 3D Beamforming and Multiuser MIMO (MU-MIMO) 327 13.5.1.5 Massive MIMO 328 13.5.1.6 Full Duplex Mode 329 13.5.1.7 Self-Backhauling 330 13.5.2 Technologies to Enhance Network Architectures 331 13.5.2.1 Software-Defined Network 332 13.5.2.2 Cloud RAN 332 13.5.2.3 Network Slicing 332 13.5.2.4 Self-Organized Network, SON 334 13.6 5G System Architecture (Release 15) 335 13.6.1 General Concepts 335 13.6.2 Architecture Reference Model 335 13.6.3 Network Slicing Support 338 13.6.3.1 General Framework 338 13.6.3.2 Network Slice Selection Assistance Information (NSSAI) 338 13.6.3.3 Selection of a Serving AMF Supporting the Network Slices 339 13.6.3.4 UE Context Handling 340 13.7 New Radio (NR) 341 13.7.1 NG-RAN Architecture 341 13.7.2 Functional Split 342 13.7.3 Network Interfaces 343 13.7.3.1 NG Interface 343 13.7.4 Xn Interface 345 13.7.5 NG-RAN Distributed Architecture 346 13.7.5.1 F1 Interface Functions 347 13.7.5.2 F1 Protocol Structure 347 13.7.6 Radio Protocol Architecture 348 13.7.6.1 User Plane 348 13.7.7 NR Physical Channels and Modulation 350 13.7.7.1 Physical-Layer Design Requirements 350 13.7.7.2 Frame Structure and Physical Resources 352 13.7.8 Frames and Subframes 353 13.7.9 Physical Resources 354 13.7.9.1 Resource Grid 354 13.7.9.2 Resource Blocks 355 13.7.10 Carrier Aggregation 356 13.7.11 Uplink Physical Channels and Signals 356 13.7.12 Downlink Physical Channels and Signals 357 13.7.13 SS/PBCH Block 358 13.7.14 Coding and Multiplexing 359 13.7.15 NR Dual Connectivity 359 13.7.16 E-UTRA and NR Multi-RAT Dual Connectivity 360 13.7.16.1 Bearer Types for MR-DC Between LTE and NR 362 13.7.16.2 MR-DC User-Plane Connectivity 363 13.8 Summary 364 References 364 14 Annex: Base-Station Site Solutions 367 14.1 The Base-Station OBSAI Architecture 367 14.1.1 Functional Modules 367 14.1.2 Internal Interfaces 369 14.1.3 RP3 Interface 369 14.2 Common Public Radio Interface, CPRI 370 14.3 SDR and Multiradio BTS 371 14.4 Site Solution with OBSAI Type Base Stations 372 14.4.1 C-RAN Site Solutions 374 References 375 Index 377

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Book SynopsisThis volume describes frontiers in social-behavioral modeling for contexts as diverse as national security, health, and on-line social gaming. Recent scientific and technological advances have created exciting opportunities for such improvements. However, the book also identifies crucial scientific, ethical, and cultural challenges to be met if social-behavioral modeling is to achieve its potential. Doing so will require new methods, data sources, and technology. The volume discusses these, including those needed to achieve and maintain high standards of ethics and privacy. The result should be a new generation of modeling that willadvance science and, separately, aid decision-making on major social and security-related subjects despite the myriad uncertainties and complexities of social phenomena. Intended to be relatively comprehensivein scope, the volume balances theory-driven, data-driven, and hybrid approaches. The latter may be rapidly iterative, as when artificial-inteTable of ContentsForeword xxvii List of Contributors xxxi About the Editors xli About the Companion Website xliii Part I Introduction and Agenda 1 1 Understanding and Improving the Human Condition: A Vision of the Future for Social-Behavioral Modeling 3Jonathan Pfautz, Paul K. Davis, and Angela O’Mahony Challenges 5 About This Book 10 References 13 2 Improving Social-Behavioral Modeling 15Paul K. Davis and Angela O’Mahony Aspirations 15 Classes of Challenge 17 Inherent Challenges 17 Selected Specific Issues and the Need for Changed Practices 20 Strategy for Moving Ahead 32 Social-Behavioral Laboratories 39 Conclusions 41 Acknowledgments 42 References 42 3 Ethical and Privacy Issues in Social-Behavioral Research 49Rebecca Balebako, Angela O’Mahony, Paul K. Davis, and Osonde Osoba Improved Notice and Choice 50 Usable and Accurate Access Control 52 Anonymization 53 Avoiding Harms by Validating Algorithms and Auditing Use 55 Challenge and Redress 56 Deterrence of Abuse 57 And Finally Thinking Bigger About What Is Possible 58 References 59 Part II Foundations of Social-Behavioral Science 63 4 Building on Social Science: Theoretic Foundations for Modelers 65Benjamin Nyblade, Angela O’Mahony, and Katharine Sieck Background 65 Atomistic Theories of Individual Behavior 66 Social Theories of Individual Behavior 75 Theories of Interaction 80 From Theory to Data and Data to Models 88 Building Models Based on Social Scientific Theories 92 Acknowledgments 94 References 94 5 How Big and How Certain? A New Approach to Defining Levels of Analysis for Modeling Social Science Topics 101Matthew E. Brashears Introduction 101 Traditional Conceptions of Levels of Analysis 102 Incompleteness of Levels of Analysis 104 Constancy as the Missing Piece 107 Putting It Together 111 Implications for Modeling 113 Conclusions 116 Acknowledgments 116 References 116 6 Toward Generative Narrative Models of the Course and Resolution of Conflict 121Steven R. Corman, Scott W. Ruston, and Hanghang Tong Limitations of Current Conceptualizations of Narrative 122 A Generative Modeling Framework 125 Application to a Simple Narrative 126 Real-World Applications 130 Challenges and Future Research 133 Conclusion 135 Acknowledgment 137 Locations, Events, Actions, Participants, and Things in the Three Little Pigs 137 Edges in the Three Little Pigs Graph 139 References 142 7 A Neural Network Model of Motivated Decision-Making in Everyday Social Behavior 145Stephen J. Read and Lynn C. Miller Introduction 145 Overview 146 Theoretical Background 147 Neural Network Implementation 151 Conclusion 159 References 160 8 Dealing with Culture as Inherited Information 163Luke J. Matthews Galton’s Problem as a Core Feature of Cultural Theory 163 How to Correct for Treelike Inheritance of Traits Across Groups 167 Dealing with Non independence in Less Treelike Network Structures 173 Future Directions for Formal Modeling of Culture 178 Acknowledgments 181 References 181 9 Social Media, Global Connections, and Information Environments: Building Complex Understandings of Multi-Actor Interactions 187Gene Cowherd and Daniel Lende A New Setting of Hyperconnectivity 187 The Information Environment 188 Social Media in the Information Environment 189 Integrative Approaches to Understanding Human Behavior 190 The Ethnographic Examples 192 Conclusion 202 References 204 10 Using Neuroimaging to Predict Behavior: An Overview with a Focus on the Moderating Role of Sociocultural Context 205Steven H. Tompson, Emily B. Falk, Danielle S. Bassett, and Jean M. Vettel Introduction 205 The Brain-as-Predictor Approach 206 Predicting Individual Behaviors 208 Interpreting Associations Between Brain Activation and Behavior 210 Predicting Aggregate Out-of-Sample Group Outcomes 211 Predicting Social Interactions and Peer Influence 214 Sociocultural Context 215 Future Directions 219 Conclusion 221 References 222 11 Social Models from Non-Human Systems 231Theodore P. Pavlic Emergent Patterns in Groups of Behaviorally Flexible Individuals 232 Model Systems for Understanding Group Competition 239 Information Dynamics in Tightly Integrated Groups 246 Conclusions 254 Acknowledgments 255 References 255 12 Moving Social-Behavioral Modeling Forward: Insights from Social Scientists 263Matthew Brashears, Melvin Konner, Christian Madsbjerg, Laura McNamara, and Katharine Sieck Why Do People Do What They Do? 264 Everything Old Is New Again 264 Behavior Is Social, Not Just Complex 267 What is at Stake? 270 Sensemaking 272 Final Thoughts 275 References 276 Part III Informing Models with Theory and Data 279 13 Integrating Computational Modeling and Experiments: Toward a More Unified Theory of Social Influence 281Michael Gabbay Introduction 281 Social Influence Research 283 Opinion Network Modeling 284 Integrated Empirical and Computational Investigation of Group Polarization 286 Integrated Approach 299 Conclusion 305 Acknowledgments 307 References 308 14 Combining Data-Driven and Theory-Driven Models for Causality Analysis in Sociocultural Systems 311Amy Sliva, Scott Neal Reilly, David Blumstein, and Glenn Pierce Introduction 311 Understanding Causality 312 Ensembles of Causal Models 317 Case Studies: Integrating Data-Driven and Theory-Driven Ensembles 321 Conclusions 332 References 333 15 Theory-Interpretable, Data-Driven Agent-Based Modeling 337William Rand The Beauty and Challenge of Big Data 337 A Proposed Unifying Principle for Big Data and Social Science 340 Data-Driven Agent-Based Modeling 342 Conclusion and the Vision 353 Acknowledgments 354 References 355 16 Bringing the Real World into the Experimental Lab: Technology-Enabling Transformative Designs 359Lynn C. Miller, Liyuan Wang, David C. Jeong, and Traci K. Gillig Understanding, Predicting, and Changing Behavior 359 Social Domains of Interest 360 The SOLVE Approach 365 Experimental Designs for Real-World Simulations 368 Creating Representative Designs for Virtual Games 371 Applications in Three Domains of Interest 375 Conclusions 376 References 380 17 Online Games for Studying Human Behavior 387Kiran Lakkaraju, Laura Epifanovskaya, Mallory Stites, Josh Letchford, Jason Reinhardt, and Jon Whetzel Introduction 387 Online Games and Massively Multiplayer Online Games for Research 388 War Games and Data Gathering for Nuclear Deterrence Policy 390 MMOG Data to Test International Relations Theory 393 Analysis and Results 397 Games as Experiments: The Future of Research 403 Final Discussion 405 Acknowledgments 405 References 405 18 Using Sociocultural Data from Online Gaming and Game Communities 407Sean Guarino, Leonard Eusebi, Bethany Bracken, and Michael Jenkins Introduction 407 Characterizing Social Behavior in Gaming 409 Game-Based Data Sources 412 Case Studies of SBE Research in Game Environments 422 Conclusions and Future Recommendations 437 Acknowledgments 438 References 438 19 An Artificial Intelligence/Machine Learning Perspective on Social Simulation: New Data and New Challenges 443Osonde Osoba and Paul K. Davis Objectives and Background 443 Relevant Advances 443 Data and Theory for Behavioral Modeling and Simulation 454 Conclusion and Highlights 470 Acknowledgments 472 References 472 20 Social Media Signal Processing 477Prasanna Giridhar and Tarek Abdelzaher Social Media as a Signal Modality 477 Interdisciplinary Foundations: Sensors, Information, and Optimal Estimation 479 Event Detection and Demultiplexing on the Social Channel 481 Conclusions 492 Acknowledgment 492 References 492 21 Evaluation and Validation Approaches for Simulation of Social Behavior: Challenges and Opportunities 495Emily Saldanha, Leslie M. Blaha, Arun V. Sathanur, Nathan Hodas, Svitlana Volkova, and Mark Greaves Overview 495 Simulation Validation 498 Simulation Evaluation: Current Practices 499 Measurements, Metrics, and Their Limitations 500 Proposed Evaluation Approach 507 Conclusions 515 References 515 Part IV Innovations in Modeling 521 22 The Agent-Based Model Canvas: A Modeling Lingua Franca for Computational Social Science 523Ivan Garibay, Chathika Gunaratne, Niloofar Yousefi, and Steve Scheinert Introduction 523 The Language Gap 527 The Agent-Based Model Canvas 530 Conclusion 540 References 541 23 Representing Socio-Behavioral Understanding with Models 545Andreas Tolk and Christopher G. Glazner Introduction 545 Philosophical Foundations 546 The Way Forward 562 Acknowledgment 563 Disclaimer 563 References 564 24 Toward Self-Aware Models as Cognitive Adaptive Instruments for Social and Behavioral Modeling 569Levent Yilmaz Introduction 569 Perspective and Challenges 571 A Generic Architecture for Models as Cognitive Autonomous Agents 575 The Mediation Process 578 Coherence-Driven Cognitive Model of Mediation 581 Conclusions 584 References 585 25 Causal Modeling with Feedback Fuzzy Cognitive Maps 587Osonde Osoba and Bart Kosko Introduction 587 Overview of Fuzzy Cognitive Maps for Causal Modeling 588 Combining Causal Knowledge: Averaging Edge Matrices 592 Learning FCM Causal Edges 594 FCM Example: Public Support for Insurgency and Terrorism 597 US–China Relations: An FCM of Allison’s Thucydides Trap 603 Conclusion 611 References 612 26 Simulation Analytics for Social and Behavioral Modeling 617Samarth Swarup, Achla Marathe, Madhav V. Marathe, and Christopher L. Barrett Introduction 617 What Are Behaviors? 619 Simulation Analytics for Social and Behavioral Modeling 624 Conclusion 628 Acknowledgments 630 References 630 27 Using Agent-Based Models to Understand Health-Related Social Norms 633Gita Sukthankar and Rahmatollah Beheshti Introduction 633 Related Work 634 Lightweight Normative Architecture (LNA) 634 Cognitive Social Learners (CSL) Architecture 635 Smoking Model 639 Agent-Based Model 641 Data 645 Experiments 646 Conclusion 652 Acknowledgments 652 References 652 28 Lessons from a Project on Agent-Based Modeling 655Mirsad Hadzikadic and Joseph Whitmeyer Introduction 655 ACSES 656 Verification and Validation 661 Self-Organization and Emergence 665 Trust 668 Summary 669 References 670 29 Modeling Social and Spatial Behavior in Built Environments: Current Methods and Future Directions 673Davide Schaumann and Mubbasir Kapadia Introduction 673 Simulating Human Behavior – A Review 675 Modeling Social and Spatial Behavior with MAS 678 Discussion and Future Directions 685 Acknowledgments 687 References 687 30 Multi-Scale Resolution of Human Social Systems: A Synergistic Paradigm for Simulating Minds and Society 697Mark G. Orr Introduction 697 The Reciprocal Constraints Paradigm 699 Discussion 706 Acknowledgments 708 References 708 31 Multi-formalism Modeling of Complex Social-Behavioral Systems 711Marco Gribaudo, Mauro Iacono, and Alexander H. Levis Prologue 711 Introduction 713 On Multi-formalism 718 Issues in Multi-formalism Modeling and Use 719 Issues in Multi-formalism Modeling and Simulation 734 Conclusions 736 Epilogue 736 References 737 32 Social-Behavioral Simulation: Key Challenges 741Kathleen M. Carley Introduction 741 Key Communication Challenges 742 Key Scientific Challenges 743 Toward a New Science of Validation 748 Conclusion 749 References 750 33 Panel Discussion:Moving Social-Behavioral Modeling Forward 753Angela O’Mahony, Paul K. Davis, Scott Appling, Matthew E. Brashears, Erica Briscoe, Kathleen M. Carley, Joshua M. Epstein, Luke J. Matthews, Theodore P. Pavlic, William Rand, Scott Neal Reilly, William B. Rouse, Samarth Swarup, Andreas Tolk, Raffaele Vardavas, and Levent Yilmaz Simulation and Emergence 754 Relating Models Across Levels 765 Going Beyond Rational Actors 776 References 784 Part V Models for Decision-Makers 789 34 Human-Centered Design of Model-Based Decision Support for Policy and Investment Decisions 791William B. Rouse Introduction 791 Modeler as User 792 Modeler as Advisor 792 Modeler as Facilitator 793 Modeler as Integrator 797 Modeler as Explorer 799 Validating Models 800 Modeling Lessons Learned 801 Observations on Problem-Solving 804 Conclusions 806 References 807 35 A Complex Systems Approach for Understanding the Effect of Policy and Management Interventions on Health System Performance 809Jason Thompson, Rod McClure, and Andrea de Silva Introduction 809 Understanding Health System Performance 811 Method 813 Model Narrative 815 Policy Scenario Simulation 817 Results 817 Discussion 824 Conclusions 826 References 827 36 Modeling Information and Gray Zone Operations 833Corey Lofdahl Introduction 833 The Technological Transformation of War: Counterintuitive Consequences 835 Modeling Information Operations: Representing Complexity 838 Modeling Gray Zone Operations: Extending Analytic Capability 842 Conclusion 845 References 847 37 Homo Narratus (The Storytelling Species): The Challenge (and Importance) of Modeling Narrative in Human Understanding 849Christopher Paul The Challenge 849 What Are Narratives? 850 What Is Important About Narratives? 851 What Can Commands Try to Accomplish with Narratives in Support of Operations? 856 Moving Forward in Fighting Against, with, and Through Narrative in Support of Operations 857 Conclusion: Seek Modeling and Simulation Improvements That Will Enable Training and Experience with Narrative 861 References 862 38 Aligning Behavior with Desired Outcomes: Lessons for Government Policy from the Marketing World 865Katharine Sieck Technique 1: Identify the Human Problem 867 Technique 2: Rethinking Quantitative Data 869 Technique 3: Rethinking Qualitative Research 876 Summary 882 References 882 39 Future Social Science That Matters for Statecraft 885Kent C. Myers Perspective 885 Recent Observations 885 Interactions with the Intelligence Community 887 Phronetic Social Science 888 Cognitive Domain 891 Reflexive Processes 893 Conclusion 895 References 896 40 Lessons on Decision Aiding for Social-Behavioral Modeling 899Paul K. Davis Strategic Planning Is Not About Simply Predicting and Acting 899 Characteristics Needed for Good Decision Aiding 901 Implications for Social-Behavioral Modeling 918 Acknowledgments 921 References 923 Index 927

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Book SynopsisA practicing engineer''s inclusive review of communication systems based on shared-bus and shared-memory switch/router architectures This book delves into the inner workings of router and switch design in a comprehensive manner that is accessible to a broad audience. It begins by describing the role of switch/routers in a network, then moves on to the functional composition of a switch/router. A comparison of centralized versus distributed design of the architecture is also presented. The author discusses use of bus versus shared-memory for communication within a design, and also covers Quality of Service (QoS) mechanisms and configuration tools. Written in a simple style and language to allow readers to easily understand and appreciate the material presented, Switch/Router Architectures: Shared-Bus and Shared-Memory Based Systems discusses the design of multilayer switchesstarting with the basic concepts and on to the basic architectures. It describes thTable of ContentsAbout the Author vii Preface ix 1 Introduction to Switch/Router Architectures 1 2 Understanding Shared-Bus and Shared-Memory Switch Fabrics 17 3 Shared-Bus and Shared-Memory-Based Switch/Router Architectures 43 4 Software Requirements for Switch/Routers 61 5 Architectures with Bus-Based Switch Fabrics: Case Study-DECNIS 500/600 Multiprotocol Bridge/Router 87 6 Architectures with Bus-Based Switch Fabrics: Case Study-Fore Systems Powerhub Multilayer Switches 111 7 Architectures with Bus-Based Switch Fabrics: Case Study-Cisco Catalyst 6000 Series Switches 129 8 Architectures with Shared-Memory-Based Switch Fabrics: Case Study-Cisco Catalyst 3550 Series Switches 151 9 Architectures with Bus-Based Switch Fabrics: Case Study-Cisco Catalyst 6500 Series Switches with Supervisor Engine 32 171 10 Architectures with Shared-Memory-Based Switch Fabrics: Case Study-Cisco Catalyst 8500 CSR Series 191 11 Quality of Service Mechanisms in the Switch/Routers 213 12 Quality of Service Configuration Tools in Switch/Routers 227 13 Case Study: Quality of Service Processing in the Cisco Catalyst 6000 and 6500 Series Switches 249 Appendix A: Ethernet Appendix B: IPv4 Packet References Index

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Book SynopsisThe groundbreaking book that details the fundamentals of reliability modeling and evaluation and introduces new and future technologies Electric Power Grid Reliability Evaluation deals with the effective evaluation of the electric power grid and explores the role that this process plays in the planning and designing of the expansion of the power grid. The book is a guide to the theoretical approaches and processes that underpin the electric power grid and reviews the most current and emerging technologies designed to ensure reliability. The authorsnoted experts in the fieldalso present the algorithms that have been developed for analyzing the soundness of the power grid. A comprehensive resource, the book covers probability theory, stochastic processes, and a frequency-based approach in order to provide a theoretical foundation for reliability analysis. Throughout the book, the concepts presented are explained with illustrative examples that connect with Table of ContentsPreface xiii Acknowledgments xv Figures xvii Tables xxi Part I Concepts and Methods in System Reliability 1 1 Introduction to Reliability 3 1.1 Introduction 3 1.2 Quantitative Reliability 4 1.3 Basic Approaches for Considering Reliability in Decision-Making 6 1.4 Objective and Scope of This Book 8 1.5 Organization of This Book 9 2 Review of Probability Theory 11 2.1 Introduction 11 2.2 State Space and Event 11 2.3 Probability Measure and Related Rules 16 2.4 Random Variables 25 2.5 Jointly Distributed Random Variables 31 2.6 Expectation, Variance, Covariance and Correlation 32 2.7 Moment Generating Function 36 2.8 Functions of Random Variables 39 Exercises 51 3 Review of Stochastic Process 53 3.1 Introduction 53 3.2 Discrete-Time Markov Process 57 3.3 Continuous-Time Markov Process 72 Exercises 80 4 Frequency-Based Approach to Stochastic Process 81 4.1 Introduction 81 4.2 Concept of Transition Rate 82 4.3 Concept of Frequency 83 4.4 Concept of Frequency Balance 91 4.5 Equivalent Transition Rate 100 4.6 Coherence 102 4.7 Conditional Frequency 104 4.8 Time-Specific Frequency 109 4.9 Probability to Frequency Conversion Rules 110 Exercises 115 5 Analytical Methods in Reliability Analysis 117 5.1 Introduction 117 5.2 State Space Approach 117 5.3 Network Reduction Method 139 5.4 Conditional Probability Method 147 5.5 Cut-Set and Tie-Set Methods 152 Exercises 164 6 Monte Carlo Simulation 165 6.1 Introduction 165 6.2 Random Number Generation 166 6.3 Classification of Monte Carlo Simulation Methods 167 6.4 Estimation and Convergence in Sampling 174 6.5 Variance Reduction Techniques 178 Exercises 182 Part II Methods of Power System Reliability Modeling and Analysis 185 7 Introduction to Power System Reliability 187 7.1 Introduction 187 7.2 Scope of Power System Reliability Studies 187 7.3 Power System Reliability Indices 188 7.4 Considerations in Power System Reliability Evaluation 190 8 Generation Adequacy Evaluation Using Discrete Convolution 193 8.1 Introduction 193 8.2 Generation Model 193 8.3 Load Model 205 8.4 Generation Reserve Model 208 8.5 Determination of Reliability Indices 210 8.6 Conclusion 212 Exercises 213 9 Reliability Analysis of Multinode Power Systems 215 9.1 Introduction 215 9.2 Scope and Modeling of Multinode Systems 215 9.3 System Modeling 216 9.4 Power Flow Models and Operating Policies 222 10 Reliability Evaluation of Multi-Area Power Systems 227 10.1 Introduction 227 10.2 Overview of Methods for Multi-Area System Studies 227 10.3 The Method of State Space Decomposition 229 10.4 Conclusion 245 Exercises 245 11 Reliability Evaluation of Composite Power Systems 247 11.1 Introduction 247 11.2 Analytical Methods 247 11.3 Monte Carlo Simulation 250 11.4 Sequential Simulation 250 11.5 Nonsequential Simulation 254 11.6 Testing of States 262 11.7 Acceleration of Convergence 263 11.8 State Space Pruning: Concept and Method 263 11.9 Intelligent Search Techniques 268 11.10 Conclusion 272 12 Power System Reliability Considerations in Energy Planning 273 12.1 Introduction 273 12.2 Problem Formulation 275 12.3 Sample Average Approximation (SAA) 279 12.4 Computational Results 282 12.5 Conclusion and Discussion 288 13 Modeling of Variable Energy Resources 291 13.1 Introduction 291 13.2 Characteristics of Variable Energy Resources 292 13.3 Variable Resource Modeling Approaches 293 13.4 Integrating Renewables at the Composite System Level 301 14 Concluding Reflections 305 Bibliography 309 Index 321

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Book SynopsisOffers an integrated presentation for path planning and motion control of cooperative mobile robots using discrete-event system principles Generating feasible paths or routes between a given starting position and a goal or target positionwhile avoiding obstaclesis a common issue for all mobile robots. This book formulates the problem of path planning of cooperative mobile robots by using the paradigm of discrete-event systems. It presents everything readers need to know about discrete event system modelsmainly Finite State Automata (FSA) and Petri Nets (PN)and methods for centralized path planning and control of teams of identical mobile robots. Path Planning of Cooperative Mobile Robots Using Discrete Event Models begins with a brief definition of the Path Planning and Motion Control problems and their state of the art. It then presents different types of discrete models such as FSA and PNs. The RMTool MATLAB toolbox is described thereafter, for readers who will need it to provide Table of ContentsForeword xi Preface xv Acknowledgments xvii Acronyms xix 1 Introduction 1 1.1 Historical perspective of mobile robotics 1 1.2 Path planning. Definition and historical background 4 1.3 Motion control. Definition and historical background 9 1.4 Motivation for expressive tasks 11 1.5 Assumptions of this monograph 14 1.6 Outline of this monograph 14 2 Robot Motion Toolbox 17 2.1 Introduction 17 2.2 General description of the simulator 20 2.3 Path planning algorithms 25 2.4 Robot kinematic models 26 2.5 Motion control algorithms 29 2.5.1 Pure pursuit algorithm 29 2.5.2 PI controller 32 2.6 Illustrative examples 33 2.6.1 Examples about path planning aspects 33 2.6.2 Examples about motion control aspects 35 2.6.3 Examples about multi-robot systems and high-level tasks 37 2.7 Conclusions 40 3 Cell Decomposition Algorithms 41 3.1 Introduction 41 3.2 Cell decomposition algorithms 42 3.2.1 Hypothesis 42 3.2.2 Trapezoidal decomposition 45 3.2.3 Triangular decomposition 46 3.2.4 Polytopal decomposition 49 3.2.5 Rectangular decomposition 52 3.3 Implementation and extensions 53 3.3.1 Extensions 53 3.3.2 Implemented functions 55 3.4 Comparative analysis 58 3.4.1 Qualitative comparison 58 3.4.2 Quantitative comparison 61 3.5 Conclusions 70 4 Discrete Event System Models 71 4.1 Introduction 71 4.2 Environment abstraction 72 4.3 Transition system models 75 4.3.1 Single robot case 75 4.3.2 Multi-robot case 79 4.4 Petri net models 83 4.5 Petri nets in resource allocation systems models 90 4.6 High-level specifications 96 4.7 Linear temporal logic 100 4.8 Conclusions 106 5 Path Planning by Using Transition System Models 109 5.1 Introduction 109 5.2 Two-step planning for a single robot and reachability specification 110 5.3 Quantitative comparison of two-step approaches 115 5.4 Receding horizon approach for a single robot and reachability specification 119 5.5 Simulations and analysis 123 5.6 Path planning with an LTL 5.7 Collision avoidance using initial delay 132 5.7.1 Problem description 132 5.7.2 Solution for Problem 5.1 (decentralized) 135 5.7.3 Solution for Problem 5.2 (centralized) 137 5.8 Conclusions 139 6 Path and Task Planning Using Petri Net Models 141 6.1 Introduction 141 6.2 Boolean-based specifications for cooperative robots 144 6.2.1 Problem definition and notations 144 6.2.2 Linear restrictions for Boolean-based specifications 146 6.2.3 Solution for constraints on the final state 147 6.2.4 Solution for constraints on trajectory and final state 149 6.2.5 Discussion on the above solutions 151 6.2.6 Suboptimal solution 152 6.2.7 Simulation examples 154 6.3 LTL specifications for cooperative robots 157 6.3.1 Problem definition and solution 157 6.3.2 Simulation examples 167 6.4 A sequencing problem 170 6.4.1 Problem statement 170 6.4.2 Solution 175 6.5 Task gathering problem 180 6.5.1 Problem formulation 180 6.5.2 Solution 181 6.6 Deadlock prevention using resource allocation models 185 6.7 Conclusions 192 7 Concluding Remarks 193 Bibliography 195 Index 211

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Book SynopsisA guide to the physics of Dynamic Temperature Sensing (DTS) measurements including practical information about procedures and applications Distributed Fiber Sensing and Dynamic Ratings of Power Cable offers a comprehensive review of the physics of dynamic temperature sensing measurements (DTS), examines its functioning, and explores possible applications. The expert authors describe the available fiber optic cables, their construction, and methods of installation. The book also includes a discussion on the variety of testing methods with information on the advantages and disadvantages of each. The book reviews the application of the DTS systems in a utility environment, and highlights the possible placement of the fiber optic cable. The authors offer a detailed explanation of the cable ampacity (current rating) calculations and examines how the measured fiber temperature is used to obtain the dynamic cable rating information in real time. In addition, the book details the leading RTTable of ContentsPreface xiii Acknowledgments xvi 1 Application of Fiber Optic Sensing 1 1.1 Types of Available FO Sensors 2 1.2 Fiber Optic Applications for Monitoring of Concrete Structures 4 1.3 Application of FO Sensing Systems in Mines 7 1.4 Composite Aircraft Wing Monitoring 8 1.5 Application in the Field of Medicine 9 1.6 Application in the Power Industry 9 1.6.1 Brief Literature Review 10 1.6.2 Monitoring of Strain in the Overhead Conductor of Transmission Lines 15 1.6.3 Temperature Monitoring of Transformers 16 1.6.4 Optical Current Measurements 17 1.7 Application for Oil, Gas, and Transportation Sectors 17 2 Distributed Fiber Optic Sensing 20 2.1 Introduction 20 2.2 Advantages of the Fiber Optic Technology 20 2.3 Disadvantages of the Distributed Sensing Technology 22 2.4 Power Cable Applications 23 3 Distributed Fiber Optic Temperature Sensing 26 3.1 Fundamental Physics of DTS Measurements 26 3.1.1 Rayleigh Scattering 26 3.1.2 Raman Spectroscopy 27 3.1.3 Brillouin Scattering 27 3.1.4 Time and Frequency Domain Reflectometry 30 4 Optical Fibers, Connectors, and Cables 32 4.1 Optical Fibers 32 4.1.1 Construction of the Fiber Optic Cable and Light Propagation Principles 33 4.1.2 Protection and Placement of Optical Fibers in Power Cable Installations 38 4.1.3 Comparison of Multiple and Single‐Mode Fibers 44 4.2 Optical Splicing 45 4.3 Fiber Characterization 47 4.4 Standards for Fiber Testing 55 4.4.1 Fiber Optic Testing 56 4.4.2 Fiber Optic Systems and Subsystems 56 4.5 Optical Connectors 68 4.6 Utility Practice for Testing of Optical Fibers 74 4.7 Aging and Maintenance 75 5 Types of Power Cables and Cable with Integrated Fibers 77 5.1 Methods of Incorporating DTS Sensing Optical Fibers (Cables) into Power Transmission Cable Corridors 77 5.1.1 Integration of Optical Cable into Land Power Cables 77 5.1.2 Integration of Optical Cable into Submarine Power Cables 78 5.1.3 Other Types of Constructions 78 5.1.4 Example of Construction of the Stainless Steel Sheathed Fiber Optic Cable 81 5.1.5 Example of a Retrofit Placement of an Optical Cable into 525 kV Submarine SCFF Power Cable Conductor 82 5.1.5.1 Objectives of the Project 82 5.1.5.2 Installation 84 5.2 Advantages and Disadvantages of Different Placement of Optical Fibers in the Cable 87 5.2.1 An Example with Placement of FO Sensors at Different Locations Within the Cable Installation 89 5.3 What are Some of the Manufacturing Challenges? 92 6 DTS Systems 94 6.1 What Constitutes a DTS System? 94 6.2 Interpretation and Application of the Results Displayed by a DTS System 95 6.2.1 General 95 6.2.2 Comparison of Measured and Calculated Temperatures 97 6.3 DTS System Calibrators 100 6.4 Computers 100 6.5 DTS System General Requirements 101 6.5.1 General Requirements 101 6.5.2 Summary of Performance and Operating Requirements 102 6.5.3 Electromagnetic Compatibility Performance Requirements for the Control PC and the DTS Unit 103 6.5.4 Software Requirements for the DTS Control 104 6.5.5 DTS System Documentation 105 7 DTS System Calibrators 106 7.1 Why is Calibration Needed? 106 7.2 How Should One Undertake the Calibration? 107 7.3 Accuracy and Annual Maintenance and Its Impact on the Measurement Accuracy 109 8 DTS System Factory and Site Acceptance Tests 112 8.1 Factory Acceptance Tests 113 8.1.1 Factory QA Tests on the Fiber Optic Cable 113 8.1.2 FIMT Cable Tests 114 8.1.3 Temperature Accuracy Test 115 8.1.4 Temperature Resolution Test 116 8.1.5 Temperature Reading Stability Test 116 8.1.6 Long‐Term Temperature Stability Test 116 8.1.7 Transient Response Test 117 8.1.8 Initial Functional Test and Final Inspection 117 8.2 DTS Site Acceptance Tests (SAT) 119 8.2.1 Final Visual Inspection and Verification of Software Functionality 120 8.2.2 Functionality Test on the DTS Unit 120 8.2.3 Verification of the Optical Switch 120 8.2.4 System Control Tests 120 8.2.5 System Integration Test with Control Center (if Applicable) 121 8.3 Typical Example of DTS Site Acceptance Tests 121 8.4 Site QA Tests on the Optical Cable System 125 8.5 Site Acceptance Testing of Brillouin‐Based DTS Systems 126 8.6 Testing Standards That Pertain to FO Cables 127 9 How Can Temperature Data Be Used to Forecast Circuit Ratings? 129 9.1 Introduction 129 9.2 Ampacity Limits 129 9.2.1 Steady‐State Summer and Winter Ratings 130 9.2.2 Overload Ratings 130 9.2.3 Dynamic Ratings 130 9.3 Calculation of Cable Ratings – A Review 131 9.3.1 Steady‐State Conditions 132 9.3.2 Transient Conditions 133 9.3.2.1 Response to a Step Function 134 9.4 Application of a DTS for Rating Calculations 138 9.4.1 Introduction 138 9.4.2 A Review of the Existing Approaches 139 9.4.3 Updating the Unknown Parameters 144 9.5 Prediction of Cable Ratings 146 9.5.1 Load Forecasting Methodology 146 9.6 Software Applications and Tools 148 9.6.1 CYME Real‐Time Thermal Rating System 150 9.6.1.1 Verification of the Model 151 9.6.2 EPRI Dynamic Thermal Circuit Rating 154 9.6.3 DRS Software by JPS (Sumitomo Corp) in Japan 156 9.6.4 RTTR Software by LIOS 158 9.7 Implementing an RTTR System 161 9.7.1 Communications with EMS 162 9.7.2 Communications with the Grid Operator 163 9.7.3 IT‐Security, Data Flow, Authentication, and Vulnerability Management 163 9.7.4 Remote Access to the RTTR Equipment 164 9.8 Conclusions 164 10 Examples of Application of a DTS System in a Utility Environment 166 10.1 Sensing Cable Placement in Cable Corridors 166 10.2 Installation of the Fiber Optic Cable 167 10.3 Retrofits and a 230 kV SCFF Transmission Application 172 10.3.1 Early 230 kV Cable Temperature Profiling Results 172 10.3.2 Location, Mitigation, and Continued Monitoring of the 230 kV Hot Spots 175 10.4 Example of a DTS Application on 69 kV Cable System 177 10.5 Verification Steps 178 10.5.1 Analytical Methods 179 10.5.2 Dynamic Thermal Circuit Ratings 180 10.6 Challenges and Experience with Installing Optical Fibers on Existing and New Transmission Cables in a Utility Environment 181 11 Use of Distributed Sensing for Strain Measurement and Acousitc Monitoring in Power Cables 185 11.1 Introduction 185 11.2 Strain Measurement 185 11.3 Example of Strain Measurement of a Submarine Power Cable 186 11.3.1 Introduction 186 11.3.2 The Importance of Tight Buffer Cable 187 11.3.3 Description of the Brillouin Optical Time Domain Reflectometer (BOTDR) System for Strain Measurement 188 11.3.4 Experimental Setup 188 11.3.5 Measurement Results 191 11.3.6 Discussion 195 11.4 Calculation of the Cable Stress from the Strain Values 197 11.5 Conclusions from the DSM Tests 198 11.6 Distributed Acoustic Sensing 199 11.7 Potential DAS Applications in the Power Cable Industry 202 11.8 An Example of a DAS Application in the USA 203 11.9 An Example of a DAS Application in Scotland 207 11.10 Conclusions 208 Bibliography 210 Index 216

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Book SynopsisThe purpose of this book is first to study cloud computing concepts, security concern in clouds and data centers, live migration and its importance for cloud computing, the role of firewalls in domains with particular focus on virtual machine (VM) migration and its security concerns. The book then tackles design, implementation of the frameworks and prepares test-beds for testing and evaluating VM migration procedures as well as firewall rule migration. The book demonstrates how cloud computing can produce an effective way of network management, especially from a security perspective.Table of ContentsList of Figures xii List of Tables xv Preface xvii Acknowledgments xxiii Acronyms xxv Introduction xxvii 1 Live Virtual Concept in Cloud Environment 1 1.1 Live Migration 2 1.1.1 Definition of Live Migration 2 1.1.2 Techniques for Live Migration 2 1.2 Issues with Migration 4 1.2.1 Application Performance Degradation 4 1.2.2 Network Congestion 4 1.2.3 Migration Time 5 1.3 Research on Live Migration 5 1.3.1 Sequencer (CQNCR) 5 1.3.2 The COMMA System 5 1.3.3 Clique Migration 6 1.3.4 Time-Bound Migration 6 1.3.5 Measuring Migration Impact 7 1.4 Total Migration Time 7 1.4.1 VM Traffic Impact 7 1.4.2 Bin Packing 8 1.5 Graph Partitioning 8 1.5.1 Learning Automata Partitioning 9 1.5.2 Advantages of Live Migration over WAN 11 1.6 Conclusion 12 References 12 2 Live Virtual Machine Migration in Cloud 15 2.1 Introduction 16 2.1.1 Virtualization 16 2.1.2 Types of Virtual Machines 18 2.1.3 Virtual Machine Applications 18 2.2 Business Challenge 19 2.2.1 Dynamic Load Balancing 19 2.2.2 No VM Downtime During Maintenance 20 2.3 Virtual Machine Migration 20 2.3.1 Advantages of Virtualization 22 2.3.2 Components of Virtualization 22 2.3.3 Types of Virtualization 23 2.4 Virtualization System 26 2.4.1 Xen Hypervisor 26 2.4.2 KVM Hypervisor 27 2.4.3 OpenStack 30 2.4.4 Storage 31 2.4.5 Server Virtualization 33 2.5 Live Virtual Machine Migration 33 2.5.1 QEMU and KVM 34 2.5.2 Libvirt 35 2.6 Conclusion 36 References 37 3 Attacks and Policies in Cloud Computing and Live Migration 39 3.1 Introduction to Cloud Computing 40 3.2 Common Types of Attacks and Policies 42 3.2.1 Buffer Overflows 42 3.2.2 Heap Overflows 42 3.2.3 Web-Based Attacks 43 3.2.4 DNS Attacks 47 3.2.5 Layer 3 Routing Attacks 48 3.2.6 ManintheMiddle Attack (MITM) 3.3 Conclusion 50 References 50 49 4 Live Migration Security in Cloud 53 4.1 Cloud Security and Security Appliances 54 4.2 VMM in Clouds and Security Concerns 54 4.3 Software-Defined Networking 56 4.3.1 Firewall in Cloud and SDN 57 4.3.2 SDN and Floodlight Controllers 61 4.4 Distributed Messaging System 62 4.4.1 Approach 63 4.4.2 MigApp Design 63 4.5 Customized Testbed for Testing Migration Security in Cloud 63 4.5.1 Preliminaries 65 4.5.2 Testbed Description 66 4.6 A Case Study and Other Use Cases 67 4.6.1 Case Study: Firewall Rule Migration and Verification 68 4.6.2 Existing Security Issues in Cloud Scenarios 68 4.6.3 Authentication in Cloud 69 4.6.4 Hybrid Approaches for Security in Cloud Computing 71 4.6.5 Data Transfer Architecture in Cloud Computing 71 4.7 Conclusion 72 References 72 5 Solution for Secure Live Migration 75 5.1 Detecting and Preventing Data Migrations to the Cloud 76 5.1.1 Internal Data Migrations 76 5.1.2 Movement to the Cloud 76 5.2 Protecting Data Moving to the Cloud 76 5.3 Application Security 77 5.4 Virtualization 78 5.5 Virtual Machine Guest Hardening 79 5.6 Security as a Service 82 5.6.1 Ubiquity of Security as a Service 83 5.6.2 Advantages of Implementing Security as a Service 85 5.6.3 Identity, Entitlement, and Access Management Services 87 5.7 Conclusion 93 References 94 6 Dynamic Load Balancing Based on Live Migration 95 6.1 Introduction 96 6.2 Classification of Load Balancing Techniques 96 6.2.1 Static and Dynamic Scheduling 97 6.2.2 Load Rebalancing 97 6.3 Policy Engine 98 6.4 Load Balancing Algorithm 100 6.5 Resource Load Balancing 101 6.5.1 Server Load Metric 102 6.5.2 System Imbalance Metric 102 6.5.3 Other Key Parameters 102 6.6 Load Balancers in Virtual Infrastructure Management Software 103 6.7 VMware Distributed Resource Scheduler 103 6.7.1 OpenNebula 104 6.7.2 Scheduling Policies 105 6.8 Conclusion 105 References 105 7 Live Migration in Cloud Data Center 107 7.1 Definition of Data Center 108 7.2 Data Center Traffic Characteristics 110 7.3 Traffic Engineering for Data Centers 111 7.4 Energy Efficiency in Cloud Data Centers 113 7.5 Major Cause of Energy Waste 113 7.5.1 Lack of a Standardized Metric of Server Energy Efficiency 7.5.2 Energy Efficient Solutions Are Still Not 113 Widely Adopted 114 7.6 Power Measurement and Modeling in Cloud 114 7.7 Power Measurement Techniques 114 7.7.1 Power Measurement for Servers 114 7.7.2 Power Measurement for VMS 115 7.7.3 Power and Energy Estimation Models 115 7.7.4 Power and Energy Modeling for Servers 115 7.7.5 Power Modeling for VMs 116 7.7.6 Power Modeling for VM Migration 116 7.7.7 Energy Efficiency Metrics 117 7.8 Power Saving Policies in Cloud 117 7.8.1 Dynamic Frequency and Voltage Scaling 118 7.8.2 Powering Down 118 7.8.3 EnergyAware Consolidation 118 7.9 Conclusion 118 References 119 8 Trusted VM-vTPM Live Migration Protocol in Clouds 121 8.1 Trusted Computing 122 8.2 TPM Operations 122 8.3 TPM Applications and Extensions 123 8.4 TPM Use Cases 124 8.5 State of the Art in Public Cloud Computing Security 125 8.5.1 Cloud Management Interface 125 8.5.2 Challenges in Securing the Virtualized Environment 126 8.5.3 The Trust in TPM 127 8.5.4 Challenges 129 8.6 Launch and Migration of Virtual Machines 130 8.6.1 Trusted Virtual Machines and Virtual Machine Managers 130 8.6.2 Seeding Clouds with Trust Anchors 131 8.6.3 Securely Launching Virtual Machines on Trustworthy Platforms in a Public Cloud 131 8.7 Trusted VM Launch and Migration Protocol 132 8.8 Conclusion 134 References 134 9 Lightweight Live Migration 137 9.1 Introduction 138 9.2 VM Checkpointing 138 9.2.1 Checkpointing Virtual Cluster 139 9.2.2 VM Resumption 140 9.2.3 Migration without Hypervisor 140 9.2.4 Adaptive Live Migration to Improve Load Balancing 141 9.2.5 VM Disk Migrations 142 9.3 Enhanced VM Live Migration 143 9.4 VM Checkpointing Mechanisms 144 9.5 Lightweight Live Migration for Solo VM 145 9.5.1 Block Sharing and Hybrid Compression Support 145 9.5.2 Architecture 146 9.5.3 FGBI Execution Flow 147 9.6 Lightweight Checkpointing 148 9.6.1 High-Frequency Checkpointing Mechanism 150 9.6.2 Distributed Checkpoint Algorithm in VPC 150 9.7 StorageAdaptive Live Migration 152 9.8 Conclusion 154 References 154 10 Virtual Machine Mobility with SelfMigration 157 10.1 Checkpoints and Mobility 158 10.2 Manual and Seamless Mobility 158 10.3 Fine-and Coarse-Grained Mobility Models 159 10.3.1 Data and Object Mobility 159 10.3.2 Process Migration 160 10.4 Migration Freeze Time 160 10.5 Device Drivers 161 10.5.1 Design Space 162 10.5.2 In-Kernel Device Drivers 162 10.5.3 Use of VMs for Driver Isolation 164 10.5.4 Context Switching Overhead 164 10.5.5 Restarting Device Drivers 165 10.5.6 External Device State 165 10.5.7 Type Safe Languages 166 10.5.8 Software Fault Isolation 166 10.6 Self-Migration 167 10.6.1 Hosted Migration 167 10.6.2 Self-Migration Prerequisites 169 10.7 Conclusion 170 References 170 11 Different Approaches for Live Migration 173 11.1 Virtualization 174 11.1.1 Hardware-Assisted Virtualization 174 11.1.2 Horizontal Scaling 175 11.1.3 Vertical Scaling 175 11.2 Types of Live Migration 176 11.2.1 Cold Migration 176 11.2.2 Suspend/Resume Migration 176 11.2.3 Live VM Migration 176 11.3 Live VM Migration Types 177 11.3.1 Pre-Copy Live Migration 177 11.3.2 Post-copy Live Migration 178 11.3.3 Hybrid Live Migration 178 11.4 Hybrid Live Migration 179 11.4.1 Hybrid Approach for Live Migration 179 11.4.2 Basic Hybrid Migration Algorithm 180 11.5 Reliable Hybrid Live Migration 180 11.5.1 Push Phase 181 11.5.2 Stop-and-Copy Phase 181 11.5.3 Pull Phase 181 11.5.4 Network Buffering 181 11.6 Conclusion 181 References 182 12 Migrating Security Policies in Cloud 183 12.1 Cloud Computing 184 12.2 Firewalls in Cloud and SDN 187 12.3 Distributed Messaging System 191 12.4 Migration Security in Cloud 192 12.5 Conclusion 194 References 194 13 Case Study 195 13.1 Kernel-Based Virtual Machine 196 13.2 Xen 196 13.3 Secure Data Analysis in GIS 196 13.3.1 Database 197 13.3.2 Data Mining and Techniques 197 13.3.3 Distributed Database 197 13.3.4 Spatial Data Mining 198 13.3.5 Secure Multi-Party Computation 198 13.3.6 Association Rule Mining Problem 198 13.3.7 Distributed Association Ruling 199 13.3.8 Data Analysis in GIS System 13.4 Emergence of Green Computing in Modern Computing Environment 200 13.5 Green Computing 203 13.6 Conclusion 204 References 205

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Book SynopsisDiscusses the fundamental principles of the design and development of microwave satellite switches utilized in military, commercial, space, and terrestrial communication This book deals with important RF/microwave components such as switches and phase shifters, which are relevant to many RF/microwave applications. It provides the reader with fundamental principles of the operation of some basic ferrite control devices and explains their system uses. This in-depth exploration begins by reviewing traditional nonreciprocal components, such as circulators, and then proceeds to discuss the most recent advances. This sequential approach connects theoretical and scientific characteristics of the devices listed in the title with practical understanding and implementation in the real world. Microwave Polarizers, Power Dividers, Phase Shifters, Circulators and Switches covers the full scope of the subject matter and serves as both an educational text and resTable of ContentsPreface xiii Acknowledgments xv List of Contributors xvii 1 Microwave Switching Using Junction Circulators 1 Joseph Helszajn 1.1 Microwave Switching Using Circulators 1 1.2 The Operation of the Switched Junction Circulator 1 1.3 The Turnstile Circulator 4 1.4 Externally and Internally Latched Junction Circulators 7 1.5 Standing Wave Solution of Resonators with Threefold Symmetry 7 1.6 Magnetic Circuit Using Major Hysteresis Loop 8 1.7 Display of Hysteresis Loop 9 1.8 Switching Coefficient of Magnetization 11 1.9 Magnetostatic Problem 13 1.10 Multiwire Magnetostatic Problem 14 1.11 Shape Factor of Cylindrical Resonator 15 Bibliography 16 2 The Operation of Nonreciprocal Microwave Faraday Rotation Devices and Circulators 19 Joseph Helszajn 2.1 Introduction 19 2.2 Faraday Rotation 20 2.3 Magnetic Variables of Faraday Rotation Devices 25 2.4 The Gyrator Network 27 2.5 Faraday Rotation Isolator 29 2.6 Four-port Faraday Rotation Circulator 30 2.7 Nonreciprocal Faraday Rotation-type Phase Shifter 31 2.8 Coupled Wave Theory of Faraday Rotation Section 32 2.9 The Partially Ferrite-filled Circular Waveguide 33 Bibliography 34 3 Circular Polarization in Parallel Plate Waveguides 37 Joseph Helszajn 3.1 Circular Polarization in Rectangular Waveguide 37 3.2 Circular Polarization in Dielectric Loaded Parallel Plate Waveguide with Open Sidewalls 40 Bibliography 47 4 Reciprocal Quarter-wave Plates in Circular Waveguides 49 Joseph Helszajn 4.1 Quarter-wave Plate 50 4.2 Coupled Mode Theory of Quarter-wave Plate 53 4.3 Effective Waveguide Model of Quarter-wave Plate 58 4.4 Phase Constants of Quarter-wave Plate Using the Cavity Method 59 4.5 Variable Rotor Power Divider 62 Bibliography 63 5 Nonreciprocal Ferrite Quarter-wave Plates 65 Joseph Helszajn 5.1 Introduction 65 5.2 Birefringence 65 5.3 Nonreciprocal Quarter-wave Plate Using the Birefringence Effect 67 5.4 Circulator Representation of Nonreciprocal Quarter-wave Plates 71 5.5 Coupled and Normal Modes in Magnetized Ferrite Medium 72 5.6 Variable Phase-shifters Employing Birefringent, Faraday Rotation, and Dielectric Half-wave Plates 73 5.7 Circulators and Switches Using Nonreciprocal Quarter-wave Plates 76 5.8 Nonreciprocal Circular Polarizer Using Elliptical Gyromagnetic Waveguide 77 Bibliography 79 6 Ridge, Coaxial, and Stripline Phase-shifters 81 Joseph Helszajn 6.1 Differential Phase-shift, Phase Deviation, and Figure of Merit of Ferrite Phase-shifter 82 6.2 Coaxial Differential Phase-shifter 82 6.3 Ridge Waveguide Differential Phase-shifter 88 6.4 The Stripline Edge Mode Phase-shifter 90 6.5 Latched Quasi-TEM Phase-shifters 91 Bibliography 92 7 Finite Element Adjustment of the Rectangular Waveguide-latched Differential Phase-shifter 95 Joseph Helszajn and Mark McKay 7.1 Introduction 95 7.2 FE Discretization of Rectangular Waveguide Phase-shifters 97 7.3 LS Modes Limit Waveguide Bandwidths 98 7.4 Cutoff Numbers and Split Phase Constants of a Twin Slab Ferrite Phase-shifter 99 7.5 The Waveguide Toroidal Phase-shifter 102 7.6 Industrial Practice 103 7.7 Magnetic Circuits Using Major and Minor Hysteresis Loops 103 7.8 Construction of Latching Circuits 106 7.9 Temperature Compensation Using Composite Circuits 107 Bibliography 109 8 Edge Mode Phase-shifter 111 Joseph Helszajn and Henry Downs 8.1 Edge Mode Effect 112 8.2 Edge Mode Characteristic Equation 115 8.3 Fields and Power in Edge Mode Devices 115 8.4 Circular Polarization and the Edge Mode Effect 118 8.5 Edge Mode Phase-shifter 120 8.6 Edge Mode Isolators, Phase-shifters, and Circulators 123 Bibliography 124 9 The Two-port On/Off H-plane Waveguide Turnstile Gyromagnetic Switch 127 Joseph Helszajn, Mark McKay, Alicia Casanueva, and Angel Mediavilla Sánchez 9.1 Introduction 127 9.2 Two-port H-plane Turnstile On/Off Switch 127 9.3 Even and Odd Eigenvectors of E-plane Waveguide Tee Junction 129 9.4 Eigenvalue Adjustment of Turnstile Plane Switch 130 9.5 Eigen-networks 132 9.6 Numerical Adjustments of Passbands 133 9.7 An Off/On H-plane Switch 134 Bibliography 136 10 Off/On and On/Off Two-port E-plane Waveguide Switches Using Turnstile Resonators 137 Joseph Helszajn, Mark McKay, and John Sharp 10.1 Introduction 137 10.2 The Shunt E-plane Tee Junction 138 10.3 Operation of Off/On and On/Off E-plane Switches 140 10.4 Even and Odd Eigenvector of H-plane Waveguide Tee Junction 141 10.5 Phenomenological Description of Two-port Off/On and On/Off Switches 142 10.6 Eigenvalue Diagrams of Small- and Large-gap E-plane Waveguide Tee Junction 144 10.7 Eigenvalue Diagrams of E-plane Waveguide Tee Junction 145 10.8 Eigen-networks of E-plane Tee Junction 146 10.9 Eigenvalue Algorithm 147 10.10 Pass and Stop Bands in Demagnetized E-plane Waveguide Tee Junction 148 Bibliography 150 11 Operation of Two-port On/Off and Off/On Planar Switches Using the Mutual Energy–Finite Element Method 153 Joseph Helszajn and David J. Lynch 11.1 Introduction 153 11.2 Impedance and Admittance Matrices from Mutual Energy Consideration 154 11.3 Impedance and Admittance Matrices for Reciprocal Planar Circuits 157 11.4 Immittance Matrices of n-Port Planar Circuits Using Finite Elements 160 11.5 Frequency Response of Two-port Planar Circuits Using the Mutual Energy–Finite Element Method 161 11.6 Stripline Switch Using Puck/Plug Half-spaces 166 Bibliography 169 12 Standing Wave Solutions and Cutoff Numbers of Planar WYE and Equilateral Triangle Resonators 171 Joseph Helszajn 12.1 Introduction 171 12.2 Cutoff Space of WYE Resonator 172 12.3 Standing Wave Circulation Solution of WYE Resonator 174 12.4 Resonant Frequencies of Quasi-wye Magnetized Resonators 175 12.5 The Gyromagnetic Cutoff Space 179 12.6 TM Field Patterns of Triangular Planar Resonator 180 12.7 TM1,0,−1 Field Components of Triangular Planar Resonator 182 12.8 Circulation Solutions 182 Bibliography 184 13 The Turnstile Junction Circulator: First Circulation Condition 185 Joseph Helszajn 13.1 Introduction 185 13.2 The Four-port Turnstile Junction Circulator 186 13.3 The Turnstile Junction Circulator 188 13.4 Scattering Matrix 190 13.5 Frequencies of Cavity Resonators 193 13.6 Effective Dielectric Constant of Open Dielectric Waveguide 193 13.7 The Open Dielectric Cavity Resonator 196 13.8 The In-phase Mode 198 13.9 First Circulation Condition 200 Bibliography 200 14 The Turnstile Junction Circulator: Second Circulation Condition 203 Joseph Helszajn and Mark McKay 14.1 Introduction 203 14.2 Complex Gyrator of Turnstile Circulator 204 14.3 Susceptance Slope Parameter, Gyrator Conductance, and Quality Factor 207 14.4 Propagation in Gyromagnetic Waveguides 208 14.5 Eigen-network of Turnstile Circulator 209 14.6 The Quality Factor of the Turnstile Circulator 211 14.7 Susceptance Slope Parameter of Turnstile Junction 213 Bibliography 213 15 A Finite-Element Algorithm for the Adjustment of the First Circulation Condition of the H-plane Turnstile Waveguide Circulator 217 Joseph Helszajn 15.1 Introduction 217 15.2 Bandpass Frequency of a Turnstile Junction 219 15.3 In-phase and Counterrotating Modes of Turnstile Junction 221 15.4 Reference Plane 222 15.5 FE Algorithm 222 15.6 FE Adjustment 224 15.7 The Reentrant Turnstile Junction in Standard WR75 Waveguide 230 15.8 Susceptance Slope Parameter of Degree-1 Junction 230 15.9 Split Frequencies of Gyromagnetic Resonators 233 References 236 16 The E-plane Waveguide Wye Junction: First Circulation Conditions 239 Joseph Helszajn and Marco Caplin 16.1 Introduction 239 16.2 Scattering Matrix of Reciprocal E-plane Three-port Y-junction 240 16.3 Reflection Eigenvalue Diagrams of Three-port Junction Circulator 242 16.4 Eigen-networks 244 16.5 Pass Band and Stop Band Characteristic Planes 246 16.6 The Dicke Eigenvalue Solution 247 16.7 Stop Band Characteristic Plane 248 16.8 The E-plane Geometry 249 16.9 First Circulation Condition 251 16.10 Calculations of Eigenvalues 253 Bibliography 254 17 Adjustment of Prism Turnstile Resonators Latched by Wire Loops 257 Joseph Helszajn and William D’Orazio 17.1 Introduction 257 17.2 The Prism Resonator 258 17.3 Split Frequency of Cavity Resonator with Up or Down Magnetization 260 17.4 Quality Factor of Gyromagnetic Resonator with Up and Down Magnetization 261 17.5 Shape Factor of Tri-toroidal Resonator 262 17.6 Squareness Ratio 264 17.7 The Complex Gyrator Circuit of the Three-port Junction Circulator 265 17.8 The Alternate Line Transformer 266 17.9 Effective Complex Gyrator Circuit 267 Bibliography 267 18 Numerical Adjustment of Waveguide Ferrite Switches Using Tri-toroidal Resonators 269 Joseph Helszajn and Mark McKay 18.1 Introduction 269 18.2 The Tri-toroidal Resonator 270 18.3 The Wire Carrying Slot Geometry 272 18.4 The Magnetostatic Problem 273 18.5 Quality Factor of Junction Circulators with Up and Down Magnetization 274 18.6 Split Frequencies of Planar and Cavity Gyromagnetic Resonators 275 18.7 The Split Frequencies of Prism Resonator with Up and Down Magnetization 276 18.8 Exact Calculation of Split Frequencies in Tri-toroidal Cavity 277 18.9 Calculation and Experiment 278 18.10 Tri-toroidal Composite Prism Resonator 279 18.11 Tri-toroidal Wye Resonator with Up and Down Magnetization 280 Bibliography 282 19 The Waveguide H-plane Tee Junction Circulator Using a Composite Gyromagnetic Resonator 285 Joseph Helszajn 19.1 Introduction 285 19.2 Eigenvalue Problem of the H-plane Reciprocal Tee Junction 286 19.3 Electrically Symmetric H-plane Junction at the Altman Planes 289 19.4 Characteristic Planes 290 19.5 The Septum-loaded H-plane Waveguide 292 19.6 The Waveguide Tee Junction Using a Dielectric Post Resonator: First Circulation Condition 294 19.7 The Waveguide Tee Junction Circulator Using a Gyromagnetic Post Resonator: Second Circulation Condition 296 19.8 Composite Dielectric Resonator 297 Bibliography 299 20 0 , 90 , and 180 Passive Power Dividers 301 Joseph Helszajn and Mark McKay 20.1 Introduction 301 20.2 Wilkinson Power Divider 302 20.3 Even and Odd Mode Adjustment of the Wilkinson Power Divider 302 20.4 Scattering Matrix of 90 Directional Coupler 305 20.5 Even and Odd Mode Theory of Directional Couplers 309 20.6 Power Divider Using 90 Hybrids 311 20.7 Variable Power Dividers 313 20.8 180 Waveguide Hybrid Network 314 Bibliography 318 Index 321

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Book SynopsisThe mobile market has experienced unprecedented growth over the last few decades. Consumer trends have shifted towards mobile internet services supported by 3G and 4G networks worldwide. Inherent to existing networks are problems such as lack of spectrum, high energy consumption, and inter-cell interference. These limitations have led to the emergence of 5G technology. It is clear that any 5G system will integrate optical communications, which is already a mainstay of wide area networks. Using an optical core to route 5G data raises significant questions of how wireless and optical can coexist in synergy to provide smooth, end-to-end communication pathways. Optical and Wireless Convergence for 5G Networks explores new emerging technologies, concepts, and approaches for seamlessly integrating optical-wireless for 5G and beyond. Considering both fronthaul and backhaul perspectives, this timely book provides insights on managing an ecosystem of mixed and multiple access network communiTable of ContentsAbout the Editors xiii List of Contributors xvii Preface xxxi Acknowledgments xxxiii Introduction xxxv 1 Towards a Converged Optical-Wireless Fronthaul/Backhaul Solution for 5G Networks and Beyond 1Isiaka Ajewale Alimi, Nelson Jesus Muga, Abdelgader M. Abdalla, Cátia Pinho, Jonathan Rodriguez, Paulo Pereira Monteiro, and Antonio Luís Teixeira 1.1 Introduction 1 1.2 Cellular Network Interface and Solution 2 1.2.1 MBH/MFH Architecture 2 1.2.1.1 Mobile Backhaul (MBH) 2 1.2.1.2 Mobile Fronthaul (MFH) 3 1.2.2 Integrated MBH/MFH Transport Network 3 1.3 5G Enabling Technologies 4 1.3.1 Ultra-Densification 4 1.3.2 C-RAN and RAN Virtualization 4 1.3.3 Advanced Radio Coordination 6 1.3.4 Millimeter-Wave Small Cells 7 1.3.5 Massive MIMO 8 1.3.6 New Multicarrier Modulations for 5G 8 1.4 Fiber-Wireless Network Convergence 9 1.5 Radio-Over-Fiber Transmission Scheme 10 1.5.1 Digital Radio-Over-Fiber (D-RoF) Transmission 10 1.5.2 Analog Radio-Over-Fiber (A-RoF) Transmission 10 1.6 Optical MBH/MFH Transport Network Multiplexing Schemes 11 1.6.1 Wavelength-Division Multiplexing (WDM) Based Schemes 11 1.6.2 Spatial-Division Multiplexing (SDM) Based Schemes 12 1.6.2.1 State-of-the-Art of SDM in 5G Infrastructure 12 1.6.2.2 Spatial Division Multiplexing Enabling Tools 13 1.7 Wireless based MFH/MBH 16 1.7.1 FSO Communication Systems 17 1.7.1.1 Log-Normal Distribution (LN) 17 1.7.1.2 Gamma-Gamma (ΓΓ) Distribution 19 1.7.2 Hybrid RF/FSO Technology 20 1.7.3 Relay-Assisted FSO Transmission 20 1.8 Experimental Channel Measurement and Characterization 21 1.9 Results and Discussions 23 1.10 Conclusion 24 Acknowledgments 24 Bibliography 25 2 Hybrid Fiber Wireless (HFW) Extension for GPON Toward 5G 31Rattana Chuenchom, Andreas Steffan, Robert G. Walker, Stephen J. Clements, Yigal Leiba, Andrzej Banach, Mateusz Lech, and Andreas Stöhr 2.1 Introduction 31 2.2 Passive Optical Network 32 2.2.1 GPON and EPON Standards 32 2.3 Transparent Wireless Extension of Optical Links 33 2.3.1 Transparent Wireless Extension of Optical Links Using Coherent RoF (CRoF) 33 2.4 Key Enabling Photonic and Electronic Technologies 36 2.4.1 Coherent Photonic Mixer 36 2.4.2 Single Side Band Mach–Zehnder Modulator 39 2.4.3 High Power Amplifier in the E-band for GPON Extension 42 2.4.4 Integrated Radio Access Units 44 2.5 Field Trial for a 2.5 Gbit s−1 GPON over Wireless 46 2.5.1 RX Throughput and Packet Loss 50 2.5.2 Latency 52 2.5.3 Jitter 53 2.6 Conclusions 53 Bibliography 54 3 Software Defined Networking and Network Function Virtualization for Converged Access-Metro Networks 57Marco Ruffini and Frank Slyne 3.1 Introduction 57 3.2 The 5G Requirements Driving Network Convergence and Virtualization 58 3.3 Access and Metro Convergence 61 3.3.1 Long-Reach Passive Optical Network 62 3.3.2 New Architectures in Support of 5G Networks, Network Virtualization and Mobile Functional Split 63 3.4 Functional Convergence and Virtualization of the COs 66 3.4.1 Infrastructure 67 3.4.1.1 Disaggregated Hardware 67 3.4.1.2 I/O Abstraction and Data Path 68 3.4.1.3 Data Centre Switching Fabric 70 3.4.1.4 Optimized Infrastructure Projects 70 3.4.2 Management and Control 70 3.4.2.1 Network Control 70 3.4.2.2 Cloud and Virtual Management 71 3.4.2.3 Orchestration, Management and Policy 72 3.4.3 Cross-Layer Components 73 3.5 Conclusions 73 Bibliography 74 4 Multicore Fibres for 5G Fronthaul Evolution 79Ivana Gasulla and José Capmany 4.1 Why 5G Communications Demand Optical Space-Division Multiplexing 79 4.2 Multicore Fibre Transmission Review 81 4.2.1 Homogeneous MCFs 82 4.2.2 Heterogeneous MCFs 83 4.3 Radio Access Networks Using Multicore Fibre Links 84 4.3.1 Basic MCF Link Between the Central Office and Base Station 86 4.3.2 MCF Based RoF C-RAN 87 4.3.3 MCF Based DRoF C-RAN 89 4.4 Microwave Signal Processing Enabled by Multicore Fibers 90 4.4.1 Signal Processing Over a Heterogeneous MCF Link 93 4.4.2 RF Signal Processing Over a Homogeneous MCF Multi-Cavity Device 94 4.5 Final Remarks 97 Bibliography 97 5 Enabling VLC and WiFi Network Technologies and Architectures Toward 5G 101Isiaka Ajewale Alimi, Abdelgader M. Abdalla, Jonathan Rodriguez, Paulo Pereira Monteiro, Antonio Luís Teixeira, Stanislav Zvánovec, and Zabih Ghassemlooy 5.1 Introduction 101 5.2 Optical Wireless Systems 103 5.3 Visible Light Communication (VLC) System Fundamentals 105 5.4 VLC Current and Anticipated Future Applications 107 5.4.1 Underwater Wireless Communications 109 5.4.2 Airline and Aviation 112 5.4.3 Hospitals 112 5.4.4 Vehicular Communication Systems 113 5.4.5 Sensitive Areas 114 5.4.6 Manufacturing and Industrial Applications 114 5.4.7 Retail Stores 114 5.4.8 Consumer Electronics 114 5.4.9 Internet of Things 115 5.4.10 Other Application Areas 115 5.5 Hybrid VLC and RF Networks 116 5.6 Challenges and Open-Ended Issues 117 5.6.1 Flicker and Dimming 117 5.6.2 Data Rate Improvement 117 5.7 Conclusions 118 Acknowledgments 118 Bibliography 118 6 5G RAN: Key Radio Technologies and Hardware Implementation Challenges 123Hassan Hamdoun, Mohamed Hamid, Shoaib Amin, and Hind Dafallah 6.1 Introduction 123 6.2 5G NR Enabled Use Cases 124 6.2.1 eMBB and uRLLC 124 6.2.1.1 mMTC 125 6.2.2 Migration to 5G 125 6.3 5G RAN Radio Enabling Technologies 126 6.3.1 Massive MIMO (M-MIMO) 126 6.3.1.1 M-MIMO in mmWave 128 6.3.1.2 M-MIMO in sub 6 GHz 128 6.3.1.3 Distributed MIMO (D-MIMO) 128 6.3.2 Carrier Aggregation and Licensed Assisted Access to an Unlicensed Spectrum 129 6.3.3 Dual Connectivity 130 6.3.4 Device-to-Device (D2D) Communication 130 6.4 Hardware Impairments 131 6.4.1 Hardware Impairments – Transmitters 132 6.4.2 Hardware Impairments – Receivers 133 6.4.3 Hardware Impairments – Transceivers 133 6.5 Technology and Fabrication Challenges 135 6.6 Conclusion 135 Bibliography 136 7 Millimeter Wave Antenna Design for 5G Applications 139Issa Elfergani, Abubakar Sadiq Hussaini, Abdelgader M. Abdalla, Jonathan Rodriguez, and Raed Abd-Alhameed 7.1 Introduction 139 7.2 Antenna Design and Procedure 142 7.3 Antenna Optimization and Analysis 143 7.3.1 The Influence of Ground Plane Length (G L) 143 7.3.2 The Effect of Feeding Strip Position (F P) 144 7.3.3 The Influences of the Substrate Type 145 7.4 Millimeter Wave Antenna Design with Notched Frequency Band 146 7.5 Millimeter Wave Antenna Design with Loaded Capacitor 148 7.6 Conclusion 152 Acknowledgments 153 Bibliography 153 8 Wireless Signal Encapsulation in a Seamless Fiber–Millimeter Wave System 157 Pham Tien Dat, Atsushi Kanno, Naokatsu Yamamoto, and Testuya Kawanishi 8.1 Introduction 157 8.2 Principle of Signal Encapsulation 158 8.2.1 Downlink System 158 8.2.2 Uplink System 161 8.3 Examples of Signal Encapsulation 162 8.3.1 Downlink Transmission 162 8.3.2 Uplink Transmission 166 8.3.3 MmWave Link Distance 170 8.4 Conclusion 174 Bibliography 175 9 5G Optical Sensing Technologies 179Seedahmed S. Mahmoud, Bernhard Koziol, and Jusak Jusak 9.1 Introduction 179 9.2 Optical Fibre Communication Network: Intrusion Methods 182 9.3 Physical Protection of Optical Fiber Communication Cables 183 9.3.1 Location-Based Optical Fibre Sensors 185 9.3.1.1 OTDR Based Sensor 185 9.3.1.2 Mach–Zehnder Interferometry 186 9.3.2 Point-Based OFSs 187 9.3.2.1 FBGs 187 9.3.3 Zone-Based OFSs 188 9.3.3.1 Michelson Interferometer 188 9.4 Design Considerations and Performance Characteristics 189 9.4.1 Performance Parameters 189 9.4.2 The Need for Robust Signal Processing Methods 190 9.4.3 System Installation and Technology Suitability 191 9.5 Conclusions 192 Bibliography 192 10 The Tactile Internet over 5G FiWi Architectures 197Amin Ebrahimzadeh, Mahfuzulhoq Chowdhury, and Martin Maier 10.1 Introduction 197 10.2 The TI: State of the Art and Open Challenges 203 10.3 Related Work 206 10.4 HITL Centric Teleoperation over AI Enhanced FiWi Networks 207 10.5 HART Centric Task Allocation over Multi-Robot FiWi Based TI Infrastructures 213 10.6 Conclusions 219 Bibliography 220 11 Energy Efficiency in the Cloud Radio Access Network (C-RAN) for 5G Mobile Networks: Opportunities and Challenges 225Isiaka Ajewale Alimi, Abdelgader M. Abdalla, Akeem Olapade Mufutau, Fernando Pereira Guiomar, Ifiok Otung, Jonathan Rodriguez, Paulo Pereira Monteiro, and Antonio Luís Teixeira 11.1 Introduction 225 11.1.1 Environmental Effects 226 11.1.2 Economic Benefits 227 11.2 Standardized Energy Efficiency Metric (Green Metric) 229 11.2.1 Power Per Subscriber, Traffic and Distance/Area 230 11.2.2 Energy Consumption Rating (ECR) Measured in W Gbps−1 231 11.2.3 Telecommunications Energy Efficiency Ratio (TEER) 231 11.2.4 Telecommunication Equipment Energy Efficiency Rating (TEEER) 231 11.3 Green Design for Energy Crunch Prevention in 5G Networks 232 11.3.1 Hardware Solutions 233 11.3.2 Network Planning and Deployment 234 11.3.2.1 Dense Networks 234 11.3.2.2 Offloading Techniques 234 11.3.3 Resource Allocation 235 11.3.4 Energy Harvesting (EH) and Transfer 235 11.3.4.1 Dedicated EH 235 11.3.4.2 Ambient EH 235 11.4 Fiber Based Energy Efficient Network 237 11.4.1 Zero Power RAU PoF Network 238 11.4.2 Battery Powered RRH PoF Network 238 11.5 System and Power Consumption Model 238 11.5.1 Remote Unit Power Consumption 240 11.5.2 Centralized Unit Power Consumption 241 11.5.3 Fronthaul Power Consumption 241 11.5.4 Massive MIMO Energy Efficiency 242 11.6 Simulation Results and Discussions 243 11.7 Conclusion 245 Acknowledgments 245 Bibliography 245 12 Fog Computing Enhanced Fiber-Wireless Access Networks in the 5G Era 249Bhaskar Prasad Rimal and Martin Maier 12.1 Background and Motivation 249 12.1.1 Next-Generation PON and Beyond 249 12.1.2 FiWi Broadband Access Networks 251 12.1.3 Role of Fog Computing 253 12.1.4 Computation Offloading 253 12.1.5 Key Issues and Contributions 255 12.2 Fog Computing Enhanced FiWi Networks 257 12.2.1 Network Architecture 257 12.2.2 Protocol Description 259 12.3 Analysis 259 12.3.1 Survivability Analysis 259 12.3.2 End-to-End Delay Analysis 262 12.4 Implementation and Validation 263 12.4.1 Experimental Testbed 264 12.4.2 Results 264 12.5 Conclusions and Outlook 267 12.5.1 Conclusions 267 12.5.2 Outlook 267 Bibliography 268 13 Techno-economic and Business Feasibility Analysis of 5G Transport Networks 273Forough Yaghoubi, Mozhgan Mahloo, Lena Wosinska, Paolo Monti, Fabricio S. Farias, Joao C. W. A. Costa, and Jiajia Chen 13.1 Introduction 273 13.2 Mobile Backhaul Technologies 275 13.3 Techno-economic Framework 278 13.3.1 Architecture Module 279 13.3.2 Topology Module 279 13.3.3 Market Module 280 13.3.4 Network Dimensioning Tool 280 13.3.5 Cost Module 280 13.3.6 Total Cost of Ownership (TCO) Module 280 13.3.6.1 Capital Expenditure (CAPEX) 281 13.3.6.2 Operational Expenditure (OPEX) 281 13.3.7 Business Models and Scenarios 283 13.3.8 Techno-economic Module 283 13.4 Case Study 284 13.4.1 Application of Methodology/Scenarios 284 13.4.2 Techno-economic Evaluation Results 286 13.4.3 Sensitivity Analysis 289 13.5 Conclusion 292 Bibliography 293 Index 297

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Book SynopsisComputer Processing of Remotely-Sensed Images A thorough introduction to computer processing of remotely-sensed images, processing methods, and applications Remote sensing is a crucial form of measurement that allows for the gauging of an object or space without direct physical contact, allowing for the assessment and recording of a target under conditions which would normally render access difficult or impossible. This is done through the analysis and interpretation of electromagnetic radiation (EMR) that is reflected or emitted by an object, surveyed and recorded by an observer or instrument that is not in contact with the target. This methodology is particularly of importance in Earth observation by remote sensing, wherein airborne or satellite-borne instruments of EMR provide data on the planet's land, seas, ice, and atmosphere. This permits scientists to establish relationships between the measurements and the nature and distribution of phenomena on the Earth'Table of ContentsPreface to the First Edition Preface to the Second Edition Preface to the Third Edition Preface to the Fourth Edition Preface to the Fifth Edition List of Examples Chapter 1: Remote Sensing: Basic Principles 1.1 Introduction 1.2 Electromagnetic radiation and its properties 1.2.1 Terminology 1.2.2 Nature of electromagnetic radiation 1.2.3 The electromagnetic spectrum 1.2.4 Sources of electromagnetic radiation 1.2.5 Interactions with the Earth's atmosphere 1.3 Interaction with Earth surface materials 1.3.1 Introduction 1.3.2 Spectral reflectance of Earth surface materials 1.3.2.1 Vegetation 1.3.2.2 Geology 1.3.2.3 Water bodies 1.3.2.4 Soils 1.4 Summary References Chapter 2: Remote Sensing Platforms and Sensors 2.1 Introduction 2.2 Characteristics of imaging remote sensing instruments 2.2.1 Spatial resolution 2.2.2 Spectral resolution 2.2.3 Radiometric resolution 2.3 Optical, near-infrared and thermal imaging sensors 2.3.1 Along-Track Scanning Radiometer (ATSR) 2.3.2 Advanced Very High Resolution Radiometer (AVHRR) and Visible Infrared Imager Radiometer Suite (VIIRS) 2.3.3 MODIS (MODerate Resolution Imaging Spectrometer) 2.3.4 Ocean observing instruments 2.3.5 IRS LISS 2.3.6 Landsat instruments 2.3.6.1 Landsat Multi-Spectral Scanner (MSS) 2.3.6.2 Landsat Thematic Mapper (TM) 2.3.6.3 Enhanced Thematic Mapper Plus (ETM+) 2.3.6.4 Landsat 8 2.3.6.5 Landsat 9 2.3.6.6 Landsat Next 2.3.7 SPOT sensors 2.3.7.1 SPOT High Resolution Visible (HRV) 2.3.7.2 Vegetation (VGT) 2.3.7.3 SPOT Follow-on Programme 2.3.8 Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 2.3.9ESA Sentinel Programme 2.3.9.1 Sentinel-2 Multi-Spectral Imager (MSI) 2.3.9.2 Sentinel-3 OLCI and SLSTR 2.3.10 High-resolution commercial and small satellite systems 2.4 Microwave imaging sensors 2.4.1. European Space Agency Synthetic Aperture Spaceborne Radars 2.4.2 Radarsat 2.4.3 TerraSAR-X and COSMO-SkyMed 2.4.3 ALOS PALSAR 2.4.4 Sentinel-1 SAR 2.5 Summary References Chapter 3: Pre-Processing of Remotely Sensed Data 3.1 Introduction 3.2 Cosmetic operations 3.2.1 Missing scan lines 3.2.2 De-striping methods 3.2.2.1 Linear method 3.2.2.2 Histogram matching 3.2.2.3 Other de-striping methods 3.3 Geometric correction and registration 3.3.1 Orbital geometry model 3.3.2 Transformation based on ground control points 3.3.3 Resampling procedures 3.3.4 Image registration 3.3.5 Other geometric correction methods 3.4 Atmospheric correction 3.4.1 Background 3.4.2 Image-based methods 3.4.3 Radiative transfer models 3.4.4 Empirical line method 3.5 Illumination and view angle effects 3.6 Sensor calibration 3.7 Terrain effects 3.8 Summary References Chapter 4: Image Enhancement Techniques 4.1 Introduction 4.2 Human visual system 4.3 Contrast enhancement 4.3.1 Linear contrast stretch 4.3.2 Histogram equalisation 4.3.3 Gaussian stretch 4.4 Pseudocolour enhancement 4.4.1 Density slicing 4.4.2 Pseudocolour transform 4.5 Summary References Chapter 5: Image Transforms 5.1 Introduction 5.2 Arithmetic operations 5.2.1 Image addition 5.2.2 Image subtraction 5.2.3 Image multiplication 5.2.4 Image division and vegetation indices 5.3 Empirically based image transforms 5.3.1 Perpendicular Vegetation Index 5.3.2 Tasselled Cap (Kauth-Thomas) transformation 5.4 Principal Components Analysis 5.4.1 Standard Principal Components Analysis 5.4.2 Noise-adjusted Principal Components Analysis 5.4.3 Decorrelation stretch 5.5 Hue, Saturation and Intensity (HSI) transform 5.6 The Discrete Fourier Transform 5.6.1 Introduction 5.6.2 Two-dimensional Fourier transform 5.6.3 Applications of the Fourier transform 5.7 The Discrete Wavelet Transform 5.7.1 Introduction 5.7.2 The one-dimensional Discrete Wavelet Transform 5.7.3 The two-dimensional Discrete Wavelet Transform 5.8 Change Detection 5.8.1 Introduction 5.8.2 NDVI Difference Image 5.8.3 Principal Components Analysis 5.8.4 Canonical Correlation Change Analysis 5.8.5 Time Series Analysis 5.8.6 Summary 5.9 Image fusion 5.9.1 Introduction 5.9.2 Hue, Saturation and Intensity (HSI) algorithm. 5.9.3 Principal Components Analysis 5.9.4 Gram-Schmidt orthogonalisation 5.9.5 Wavelet based methods 5.9.6 Evaluation – Subjective methods 5.9.7 Evaluation – Objective methods 5.10 Summary References Chapter 6: Filtering Techniques 6.1 Introduction 6.2 Spatial domain low-pass (smoothing) filters 6.2.1 Moving average filter 6.2.2 Median filter 6.2.3 Adaptive filters 6.3 Spatial domain high-pass (sharpening) filters 6.3.1 Image subtraction method 6.3.2 Derivative-based methods 6.4 Spatial domain edge detectors 6.5 Frequency domain filters 6.6 Summary References Chapter 7: Classification 7.1 Introduction 7.2 Geometrical basis of classification 7.3 Unsupervised classification 7.3.1 The k-means algorithm 7.3.2 ISODATA 7.3.3 A modified k-means algorithm 7.4 Supervised classification 7.4.1 Training samples 7.4.2 Statistical classifiers 7.4.2.1 Parallelepiped classifier 7.4.2.2 Centroid (k-means) classifier 7.4.2.3 Maximum likelihood method 7.4.3 Neural classifiers 7.5 Sub-pixel classification techniques 7.5.1 The linear mixture model 7.5.2 Spectral Angle Mapping 7.5.3 Independent Components Analysis 7.5.4 Fuzzy classifiers 7.6 More advanced approaches to image classification 7.6.1 Support Vector Machines 7.6.2 Decision tree classifiers 7.6.3 Other approaches to classification 7.6.3.1Rule based methods and the Genetic Algorithm 7.6.3.2Object-oriented methods 7.6.3.3Other methods 7.6.3.3.1Evidential Reasoning 7.6.3.3.2Bagging, boosting and ensembles of classifiers 7.7 Incorporation of non-spectral features 7.7.1 Texture 7.7.2 Use of external data 7.8 Contextual information 7.9 Feature selection 7.10 Classification accuracy 7.11 Summary References Chapter 8 Advanced Topics 8.1 Introduction 8.2 SAR interferometry 8.2.1 Basic principles 8.2.2 Interferometric processing 8.2.3 Problems in SAR interferometry 8.2.4 Applications of SAR interferometry 8.3 Imaging spectroscopy 8.3.1 Introduction 8.3.2 Processing imaging spectrometer data 8.3.2.1 Derivative analysis 8.3.2.2 Smoothing and denoising the reflectance spectrum 8.3.2.2.1 Savitzky-Golay polynomial smoothing 8.3.2.2.2 Denoising using the Discrete Wavelet Transform 8.3.2.3 Determination of ‘red edge’ characteristics of vegetation 8.3.2.4 Continuum removal 8.4 Lidar 8.4.1 Introduction 8.4.2 Lidar details 8.4.3 Lidar applications 8.5 Summary References Appendix A Index

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Book SynopsisThe new edition of the leading single-volume resource on designing, operating, and managing mission critical infrastructure Maintaining Mission Critical Systems in a 24/7 Environment provides in-depth coverage of operating, managing, and maintaining power quality and emergency power systems in mission critical facilities. This extensively revised third edition provides invaluable insight into the mission critical environment, helping professionals and students alike understand how to sustain continuous functionality, minimize the occurrence of costly unexpected downtime, and guard against power disturbances that can damage any organization''s daily operations. Bridging engineering, operations, technology, and training, this comprehensive volume covers each component of specialized systems used in mission critical infrastructures worldwide. Throughout the text, readers are provided the up-to-date information necessary to design and analyze mission criticaTable of ContentsForeword xvii Preface xxi Acknowledgments xxiii 1 An Overview of Reliability and Resiliency in Today’s Mission Critical Environment 1 1.1 Introduction 1 1.2 Risk Assessment 5 1.2.1 Levels of Risk 6 1.3 Capital Costs versus Operation Costs 7 1.4 Critical Environment Workflow and Change Management 9 1.4.1 Change Management 10 1.5 Testing and Commissioning 11 1.6 Documentation and Human Factor 16 1.7 Education and Training 20 1.8 Corporate Knowledge Transfer – the Means to Securing Tomorrow’s Critical Infrastructure 21 1.9 Operation and Maintenance 24 1.10 Employee Certification 25 1.11 Standards and Benchmarking 25 1.12 What is a Mission Critical Engineer 26 1.13 Conclusion 28 1.14 An Overview of Reliability and Resiliency in Today’s Mission Critical Environment - Questions to Consider 28 2 Energy and Cyber Security and its Effect on Business Resiliency 31 2.1 Introduction 31 2.2 Risks Related to Information Security 36 2.3 Electro Magnetic Pulse and Solar Flares 42 2.4 How Risks Are Addressed 47 2.5 Use of Distributed Energy Resources and Generation 52 2.6 Documentation and Its Relation to Information Security 55 2.7 Smart Grid 57 2.8 Conclusion 60 2.9 Energy Security and Its Effect on Business Resiliency – Questions to Consider 60 3 Mission Critical Engineering with an Overview of Green Technologies 63 3.1 Introduction 63 3.2 Companies’ Expectations: Risk Tolerance and Reliability 65 3.3 Identifying the Appropriate Redundancy in a Mission Critical Facility 67 3.4 Improving Reliability, Maintainability, and Proactive Preventative Maintenance 69 3.5 The Mission Critical Facilities Manager and the Importance of the Boardroom 71 3.6 Quantifying Reliability and Availability 71 3.6.1 Review of Reliability Terminology 72 3.7 Design Considerations for the Mission Critical Data Center 73 3.7.1 Data Center Certification 74 3.8 The Evolution of Mission Critical Facility Design 76 3.9 Human Factors and the Commissioning Process 77 3.10 Short Circuit & Coordination Studies 79 3.11 Introduction to Direct Current in the Data Center 84 3.11.1 Advantages of DC Distribution 85 3.11.2 Lighting Updates 87 3.11.3 DC Storage Options 87 3.11.4 Renewable Energy Integration 88 3.11.5 DC and Combined Cooling, Heat & Power 89 3.11.6 Safety Issues 91 3.11.7 Maintenance 91 3.11.8 Education & Training 92 3.11.9 Future Vision 93 3.12 Containerized Systems Overview 93 3.13 Mission Critical Engineering with an Overview of Green Technologies - Questions to Consider 95 4 Mission Critical Electrical System Maintenance & Safety 103 4.1 Introduction 103 4.2 The History of the Maintenance Supervisor and the Evolution of the Mission Critical Facilities Engineer 105 4.3 Internal Building Deficiencies and Analysis 107 4.4 Evaluating Your System 108 4.5 Choosing a Maintenance Approach 110 4.5.1 Annual Preventive Maintenance 111 4.6 Safe Electrical Maintenance 112 4.6.1 Standards and Regulations 112 4.6.2 Electrical Safety: NFPA 70E Arc Flash Mitigation 114 4.6.3 Personal Protective Equipment (PPE) 117 4.6.4 Lockout/Tagout 126 4.7 Maintenance of Typical Electrical Distribution Equipment 127 4.7.1 Thermal Scanning and Thermal Monitoring 127 4.7.2 15 KV Class Equipment 129 4.7.3 480 Volt Switchgear 130 4.7.4 Motor Control Centers and Panel Boards 131 4.7.5 Automatic Transfer Switches 131 4.7.6 Automatic Static Transfer Switches (ASTS) 132 4.7.7 Power Distribution Units 132 4.7.8 277/480 Volt Transformers 133 4.7.9 Uninterruptible Power Systems 133 4.8 Being Proactive in Evaluating the Test Reports 134 4.9 Designing for Safety and Reliability 135 4.10 Conclusion 136 5 Standby Generators 137 5.1 Introduction 137 5.2 The Necessity for Standby Power 138 5.3 Emergency, Legally Required, and Optional Systems 140 5.4 Standby Systems That Are Legally Required 141 5.5 Optional Standby Systems 142 5.6 Understanding Your Power Requirements 142 5.7 Management Commitment and Training 142 5.7.1 Lockout/ Tagout (LOTO) 143 5.7.2 Training 144 5.8 Standby Generator Systems Maintenance Procedures 144 5.8.1 Maintenance Record Keeping and Data Trending 145 5.8.2 Engine 145 5.8.3 Coolant System 145 5.8.4 Electrical / Control System 146 5.8.5 Generator 146 5.8.6 Automatic and Manual Switchgear 147 5.8.7 Load Bank Testing 147 5.9 Documentation Plan 148 5.9.1 Proper Documentation and Forms 148 5.9.2 Record keeping 148 5.10 Emergency Procedures 149 5.11 Cold Start 150 5.12 Non-Linear Load Concerns 151 5.12.1 Line Notches and Harmonic Current 151 5.12.2 Voltage / Frequency Drop 152 5.12.3 Voltage / Frequency Rise 152 5.12.4 Frequency Fluctuation 153 5.12.5 Synchronizing to Parallel 154 5.12.6 Automatic Transfer Switch 154 5.13 Conclusion 155 6 Fuel Systems Design and Maintenance 157 6.1 Introduction 157 6.2 Brief Discussion on Diesel Engines 158 6.3 Bulk Storage Tank Selection 159 6.3.1 Aboveground Tanks 159 6.3.2 Modern Underground Tanks and Piping Systems 160 6.3.3 Fuel Receiving Tanks 161 6.3.4 Generator Sub-Base Tanks 161 6.4 Codes and Standards 162 6.5 Recommended Practices for all Tanks 163 6.6 Fuel Distribution System Configuration 168 6.7 Day Tank Control System 170 6.8 Diesel Fuel and a Fuel Quality Assurance Program 174 6.9 Conclusion 186 7 Power Transfer Switch Technology, Applications, and Maintenance 187 7.1 Introduction 187 7.2 Transfer Switch Technology and Applications 189 7.3 Types of Power Transfer Switches 191 7.3.1 Manual Transfer Switches 191 7.3.2 Automatic Transfer Switches 191 7.4 Control Devices 204 7.4.1 Time Delays 204 7.4.2 In-Phase Monitor 205 7.4.3 Test Switches 206 7.4.4 Exercise Clock 207 7.4.5 Current, Voltage and Frequency Sensing 207 7.5 Design Features 207 7.5.1 Close Against High In-Rush Currents 208 7.5.2 Withstand and Closing Rating (WCR) 208 7.5.3 Carry Full Rated Current Continuously 208 7.5.4 Interrupt Current 209 7.6 Additional Characteristics and Ratings of ATS 209 7.6.1 NEMA Classification 209 7.6.2 System Voltage Ratings 209 7.6.3 ATS Sizing 209 7.6.4 Seismic Requirement 210 7.7 Installation & Commissioning, Maintenance, and Safety 210 7.7.1 Installation & Commissioning 210 7.7.2 Maintenance & Safety 212 7.7.3 Maintenance Tasks 214 7.7.4 Drawings and Manuals 215 7.7.5 Testing & Training 215 7.8 General Recommendations 218 7.9 Conclusion 219 8 The Static Transfer Switch 221 8.1 Introduction 221 8.2 Overview 222 8.2.1 Major Components 222 8.3 Typical Static Switch One Line 223 8.3.1 Normal Operation 223 8.3.2 Bypass Operation 224 8.3.3 STS and STS/transformer Configurations 225 8.4 STS Technology and Application 225 8.4.1 General Parameters 225 8.4.2 STS Location and Type 226 8.4.3 Advantages and Disadvantages of the Primary and Secondary STS/Transformer Systems 226 8.4.4 Monitoring, Data Logging, and Data Management 227 8.4.5 Downstream Device Monitoring 227 8.4.6 STS Remote Communication 228 8.4.7 Security 228 8.4.8 Human Engineering and Eliminating Human Errors 229 8.4.9 Reliability and Availability 230 8.4.10 Repairability and Maintainability 231 8.4.11 Fault Tolerance and Abnormal Operation 232 8.5 Testing 232 8.6 Conclusion 233 9 The Fundamentals of Power Quality 235 9.1 Introduction 235 9.2 Electricity Basics 237 9.2.1 Basic Circuit 238 9.2.2 Power Factor 238 9.3 Transmission of Power 241 9.3.1 Life Cycle of Electricity 241 9.3.2 Single-Phase and Three-Phase Power Basics 243 9.3.3 Unreliable Power versus Reliable Power 245 9.4 Understanding Power Problems 245 9.4.1 Power Quality Standards 246 9.4.2 Power Quality Transients 249 9.4.3 RMS Variations 250 9.4.4 Causes of Power Line Disturbances 255 9.4.5 Power Line Disturbance Levels 261 9.5 Tolerances of Critical Loads 261 9.5.1 CBEMA Curve 263 9.5.2 ITIC Curve 263 9.5.3 Purpose of Curves 265 9.6 Power Monitoring 265 9.7 The Impact of Alternative Energy Generation 268 9.8 Conclusion 269 10 UPS Systems: Applications and Maintenance with an Overview of Green Technologies 273 10.1 Introduction 273 10.1.1 Green and Reliability Overview 273 10.2 Purpose of UPS Systems 275 10.3 General Description of UPS Systems 279 10.3.1 What is a UPS system? 279 10.3.2 How does a UPS system work? 279 10.3.3 Static UPS Systems 280 10.3.4 Online 281 10.3.5 Double Conversion 282 10.3.6 Double Conversion UPS Power Path 282 10.4 Components of a Static UPS System 284 10.4.1 Power Control Devices 284 10.5 Online - Line Interactive UPS Systems 291 10.6 Offline (Standby) 292 10.7 The Evolution of Static UPS Technology 293 10.7.1 Emergence of the IGBT 293 10.7.2 Two and Three-Level Rectifier/Inverter Topology 294 10.7.3 Silicon Carbide Replaces Silicon as UPS Semiconductor of Electricity 295 10.8 Rotary UPS Systems 299 10.8.1 UPSs Using Diesel 300 10.8.2 Hybrid UPS Systems 301 10.9 Redundancy, Configurations, and Topology 301 10.9.1 N 302 10.9.2 N+1 302 10.9.3 Isolated Redundant 303 10.9.4 N+2 303 10.9.5 2N 304 10.9.6 2(N+1) 305 10.9.7 Distributed Redundant / Catcher UPS 305 10.9.8 “Eco-Mode” for Static UPS 306 10.9.9 Availability Calculations 307 10.10 Energy Storage Devices 308 10.10.1 Battery 308 10.10.2 Flywheel Energy 314 10.11 UPS Maintenance & Testing 316 10.11.1 Physical Preventive Maintenance (PM) 318 10.11.2 Protection Settings, Calibration, and Guidelines 318 10.11.3 Functional Load Testing 319 10.11.4 Steady State Load Test 319 10.11.5 Steady State Load Test at 0%, 50% and 100% load: 320 10.11.6 Harmonic Analysis and Testing 320 10.11.7 Filter Integrity and Testing 321 10.11.8 Transient Response Load Test 322 10.11.9 Module Fault Test 322 10.11.10 Battery Run Down Test 322 10.12 Static UPS and Maintenance 323 10.12.1 Examples of Semi-Annual Checks and Services for UPS Systems 324 10.13 UPS Management 324 10.14 Conclusion 325 11 Data Center Cooling Systems 327 11.1 Introduction 327 11.2 Background Information 330 11.3 Cooling within Datacom Rooms 331 11.4 Cooling Process 332 11.4.1 Cooling Process in Datacom Space 332 11.4.2 Direct Expansion (DX) Systems 333 11.4.3 Chilled Water Systems 334 11.5 Cooling Final Dissipation 334 11.5.1 Air Cooled System 335 11.5.2 Water Side 335 11.6 The Refrigeration Process 337 11.6.1 Refrigeration Equipment – Compressors 337 11.6.2 Refrigeration Equipment – Chillers 338 11.6.3 Heat Rejection Equipment 342 11.6.4 Energy Recovery Equipment 353 11.6.5 Heat Exchangers 360 11.7 Components Inside Datacom Room 363 11.7.1 Computer Room Cooling Units 363 11.8 Conclusion 373 12 Data Center Cooling Efficiency, Concepts, & Technologies 375 12.1 Introduction 375 12.2 Heat Transfer Inside Data Centers 379 12.2.1 Heat Generation 379 12.2.2 Heat Return 380 12.2.3 Cooling Air 380 12.3 Cooling and Other Airflow Topics 381 12.3.1 Leakage 381 12.3.2 Mixing and its Relationship to Efficiency 382 12.3.3 Re-circulation 382 12.3.4 Venturi Effect 382 12.3.5 Vortex Effect 383 12.3.6 CRAC/CRAH Types 383 12.3.7 Potential CRAC Operation Issues 383 12.3.8 Sensible vs. Latent Cooling 384 12.3.9 Humidity Control 386 12.3.10 CRAC Fighting / Too Many CRACs 387 12.4 Design Approaches for Data Center Cooling 388 12.4.1 Hot Aisle/Cold Aisle 388 12.4.2 Cold Aisle Containment 388 12.4.3 In-Row Cooling with Hot Aisle Containment 388 12.4.4 Overhead Supplemental Cooling 389 12.4.5 Chimney or Ducted Returns 389 12.4.6 Advanced Active Airflow Management for Server Cabinets 390 12.5 Additional Considerations 390 12.5.1 Active Air Movement 390 12.5.2 Adaptive Capacity 390 12.5.3 Liquid Cooling 391 12.5.4 Cold Storage 392 12.6 Hardware & Associated Efficiencies 392 12.6.1 Server Efficiency 392 12.6.2 Server Virtualization 392 12.6.3 Multi-Core Processors 393 12.6.4 Blade Servers 393 12.6.5 Energy Efficient Servers 393 12.6.6 Power Managed Servers 393 12.6.7 Effect of Dynamic Server Loads on Cooling 393 12.7 Best Practices 394 12.8 Efficiency Problem Solving 394 12.9 Conclusion 396 12.10 Conversions, Formulas, Guidelines 396 13 Raised Access Floors 397 13.1 Introduction 397 13.1.1 What is an Access Floor? 397 13.1.2 What are the Typical Applications for Access Floors? 399 13.1.3 Why use an Access Floor? 399 13.2 Design Considerations 400 13.2.1 Determine the Structural Performance Required 400 13.2.2 Determine the Required Finished Floor Height 403 13.2.3 Determine the Understructure Support Design Type Required 404 13.2.4 Determine the Appropriate Floor Finish 405 13.2.5 Air Flow Requirements 406 13.3 Safety Concerns 409 13.3.1 Removal & Reinstallation of Panels 409 13.3.2 Removing Panels 409 13.3.3 Stringer Systems 411 13.3.4 Protection of the Floor from Heavy Loads 412 13.3.5 Grounding the Access Floor 417 13.3.6 Fire Protection 418 13.3.7 Zinc Whiskers 419 13.4 Panel Cutting (For all Steel Panels or Cement Filled Panels that do not Contain an Aggregate) 419 13.4.1 Safety Requirements for Cutting Panels 419 13.4.2 Guidelines for Cutting Panels 420 13.4.3 Cutout Locations in Panels; Supplemental Support for Cut Panels 420 13.4.4 Saws and Blades for Panel Cutting 420 13.4.5 Interior Cutout Procedure: 421 13.4.6 Round Cutout Procedure 421 13.4.7 Installing Protective Trim Around Cut Edges 421 13.4.8 Cutting and Installing the Trim 422 13.5 Access Floor Maintenance 423 13.5.1 Best Practices for Standard High Pressure Laminate Floor Tile (HPL) and for Vinyl Conductive & Static Dissipative Tile 423 13.5.2 Damp Mopping Procedure for HPL and Conductive & Static Dissipative Vinyl Tile 423 13.5.3 Cleaning the Floor Cavity 424 13.6 Troubleshooting 424 13.6.1 Making Pedestal Height Adjustments 425 13.6.2 Rocking Panel Condition 425 13.6.3 Panel Lipping Condition (Panel Sitting High) 425 13.6.4 Out-of-Square Stringer Grid (Twisted Grid) 426 13.6.5 Tipping at Perimeter Panels 427 13.6.6 Tight Floor or Loose Floor: Floor Systems Laminated with HPL Tile 427 13.7 Additional Design Considerations 428 13.7.1 LEED Certification 428 13.7.2 Energy Efficiency - Hot and Cold Air Containment 428 13.7.3 Airflow Distribution and CFD Analysis 429 13.8 Conclusion 437 14 Fire Protection in Mission Critical Infrastructures 439 14.1 Introduction 439 14.2 Hazard Analysis 441 14.3 Alarm and Notification 441 14.4 Early Warning Detection 444 14.4.1 Wireless Detection 445 14.5 Fire Suppression 445 14.5.1 Hybrid Fire Suppression Systems 448 14.5.2 Protecting Lithium Ion Batteries 449 14.6 Systems Design 450 14.6.1 Stages of a Fire 450 14.6.2 Fire and Building Codes 451 14.7 Fire Detection 452 14.8 Fire Suppression Systems 461 14.8.1 Water Mist Systems 467 14.8.2 Carbon Dioxide Systems 470 14.8.3 Clean Agent Systems 472 14.8.4 Inert Gas Agents 472 14.8.5 IG-541 473 14.8.6 IG-55 474 14.8.7 Chemical Clean Agents 474 14.8.8 Portable Fire Extinguishers 479 14.8.9 Clean Agents and the Environment 479 14.9 Conclusion 480 15 Managing Through Pandemics 481 15.1 Executive Summary: COVID-19’s Impact on Critical Infrastructure Globally 481 15.2 Architectural Solutions and Air Purification Systems 482 15.2.1 HVAC Systems 482 15.2.2 UV Technology 482 15.2.3 Bipolar Ionization 485 15.2.4 Copper Doorknobs 485 15.2.5 Architectural Improvements to be Considered 486 15.3 Building Equipment Solutions and Technology 487 15.3.1 Cleaning vs. Disinfecting vs. Sanitizing 487 15.3.2 Intensify Cleaning Frequency and Measures 487 15.3.3 IR Scans 488 15.3.4 Rethinking the flush, the sink, and the hand dryer 488 15.3.5 Technology 489 15.4 Operations, Maintenance and Training 491 15.4.1 Personal Protection 491 15.4.2 Change in Operation 491 15.4.3 Data Center Betterment Opportunities 492 15.5 Site Protection: Safeguarding the Staff and Visitors 493 15.6 The Workforce of Tomorrow 494 15.7 Assessment Tasks - HVAC and Air Handling Units Filter Upgrades 495 15.8 Managing Through Pandemics -Questions to Consider 496 15.9 Conclusion 497 Appendix A Policies and Regulations 499 A.1 Introduction 499 A.2 Industry Policies & Regulations 501 A.2.1 USA PATRIOT Act 503 A.2.2 Sarbanes-Oxley Act (SOX) 505 A.2.3 Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (also known as the Superfund Act) 506 A.2.4 Executive Order 13423: Strengthening Federal Environmental, Energy and Transportation Management 507 A.2.5 ISO27000 Information Security Management System (ISMS) 508 A.2.6 The National Strategy for the Physical Protection of Critical Infrastructures and Key Assets 513 A.2.7 2009 National Infrastructure Protection Plan 514 A.2.8 North American Electric Reliability Corporation (NERC) Critical Infrastructure Protection Program 514 A.2.9 U.S. Security & Exchange Commission (SEC) 516 A.2.10 Sound Practices to Strengthen the Resilience of the U.S. Financial System 516 A.2.11 C4I Command, Control, Communications, Computers, and Intelligence 517 A.2.12 Basel II Accord 519 A.2.13 National Institute of Standards and Technology (NIST) 519 A.2.14 Business Continuity Management Agencies and Regulating Organizations 521 A.2.15 FFIEC - Federal Financial Institutions Examination Council 523 A.2.16 National Fire Prevention Association 1600 – Standards on Disaster/Emergency Management and Business Continuity Programs 524 A.2.17 Private Sector Preparedness Act 525 A.3 Data Protection 526 A.4 Encryption 528 A.4.1 Protecting Critical Data through Security and Vaulting 529 A.5 Business Continuity Plan (BCP) 529 A.6 Conclusion 531 Appendix B Consolidated List of Key Questions 535 Appendix C Airflow Management (A System Approach) 553 C.1 Introduction 553 C.2 Control is the Key 555 C.3 Obtaining Control 558 C.4 Air Management Technologies 565 C.5 Conclusion 570 Glossary 573 References 595 Index 609

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Book SynopsisProvides a semi-quantitative approach to recent developments in the study of optical properties of condensed matter systems Featuring contributions by noted experts in the field of electronic and optoelectronic materials and photonics, this book looks at the optical properties of materials as well as their physical processes and various classes. Taking a semi-quantitative approach to the subject, it presents a summary of the basic concepts, reviews recent developments in the study of optical properties of materials and offers many examples and applications. Optical Properties of Materials and Their Applications, 2nd Edition starts by identifying the processes that should be described in detail and follows with the relevant classes of materials. In addition to featuring four new chapters on optoelectronic properties of organic semiconductors, recent advances in electroluminescence, perovskites, and ellipsometry, the book covers: optical properties of disorTable of ContentsList of Contributors xv Series Preface xvii Preface xix 1 Fundamental Optical Properties of Materials I 1S.O. Kasap, W.C. Tan, Jai Singh, and Asim K. Ray 1.1 Introduction 1 1.2 Optical Constants n and K 2 1.2.1 Refractive Index and Extinction Coefficient 2 1.2.2 n and K, and Kramers–Kronig Relations 5 1.3 Refractive Index and Dispersion 7 1.3.1 Cauchy Dispersion Relation 7 1.3.2 Sellmeier Equation 8 1.3.3 Refractive Index of Semiconductors 10 1.3.3.1 Refractive Index of Crystalline Semiconductors 10 1.3.3.2 Bandgap and Temperature Dependence 11 1.3.4 Refractive Index of Glasses 11 1.3.5 Wemple–DiDomenico Dispersion Relation 14 1.3.6 Group Index 15 1.4 The Swanepoel Technique: Measurement of n and 𝛼 for Thin Films on Substrates 16 1.4.1 Uniform Thickness Films 16 1.4.2 Thin Films with Non-uniform Thickness 22 1.5 Transmittance and Reflectance of a Partially Transparent Plate 25 1.6 Optical Properties and Diffuse Reflection: Schuster–Kubelka–Munk Theory 27 1.7 Conclusions 31 Acknowledgments 31 References 32 2 Fundamental Optical Properties of Materials II 37S.O. Kasap, K. Koughia, Jai Singh, Harry E. Ruda, and Asim K. Ray 2.1 Introduction 37 2.2 Lattice or Reststrahlen Absorption and Infrared Reflection 40 2.3 Free Carrier Absorption (FCA) 42 2.4 Band-to-Band or Fundamental Absorption (Crystalline Solids) 45 2.5 Impurity Absorption and Rare-Earth Ions 48 2.6 Effect of External Fields 54 2.6.1 Electro-Optic Effects 54 2.6.2 Electro-Absorption and Franz–Keldysh Effect 55 2.6.3 Faraday Effect 56 2.7 Effective Medium Approximations 58 2.8 Conclusions 61 Acknowledgments 61 References 62 3 Optical Properties of Disordered Condensed Matter 67Koichi Shimakawa, Jai Singh, and S.K. O’Leary 3.1 Introduction 67 3.2 Fundamental Optical Absorption (Experimental) 69 3.2.1 Amorphous Chalcogenides 69 3.2.2 Hydrogenated Nano-Crystalline Silicon (nc-Si:H) 72 3.3 Absorption Coefficient (Theory) 74 3.4 Compositional Variation of the Optical Bandgap 79 3.4.1 In Amorphous Chalcogenides 79 3.5 Conclusions 80 References 80 4 Optical Properties of Glasses 83Andrew Edgar 4.1 Introduction 83 4.2 The Refractive Index 84 4.3 Glass Interfaces 86 4.4 Dispersion 88 4.5 Sensitivity of the Refractive Index 90 4.5.1 Temperature Dependence 90 4.5.2 Stress Dependence 91 4.5.3 Magnetic Field Dependence—The Faraday Effect 92 4.5.4 Chemical Perturbations—Molar Refractivity 94 4.6 Glass Color 95 4.6.1 Coloration by Colloidal Metals and Semiconductors 95 4.6.2 Optical Absorption in Rare-Earth-Doped Glass 96 4.6.3 Absorption by 3d Metal Ions 99 4.7 Fluorescence in Rare-Earth-Doped Glass 102 4.8 Glasses for Fiber Optics 104 4.9 Refractive Index Engineering 106 4.10 Glass and Glass–Fiber Lasers and Amplifiers 109 4.11 Valence Change Glasses 111 4.12 Transparent Glass Ceramics 114 4.12.1 Introduction 114 4.12.2 Theoretical Basis for Transparency 116 4.12.3 Rare-Earth-Doped Transparent Glass Ceramics for Active Photonics 120 4.12.4 Ferroelectric Transparent Glass Ceramics 121 4.12.5 Transparent Glass Ceramics for X-ray Storage Phosphors 121 4.13 Conclusions 124 References 124 5 Concept of Excitons 129Jai Singh, Harry E. Ruda, M.R. Narayan, and D. Ompong 5.1 Introduction 129 5.2 Excitons in Crystalline Solids 130 5.2.1 Excitonic Absorption in Crystalline Solids 133 5.3 Excitons in Amorphous Semiconductors 135 5.3.1 Excitonic Absorption in Amorphous Solids 137 5.4 Excitons in Organic Semiconductors 139 5.4.1 Photoexcitation and Formation of Excitons 140 5.4.1.1 Photoexcitation of Singlet Excitons Due to Exciton–Photon Interaction 141 5.4.1.2 Excitation of Triplet Excitons 142 5.4.2 Exciton Up-Conversion 147 5.4.3 Exciton Dissociation 148 5.4.3.1 Conversion from Frenkel to CT Excitons 151 5.4.3.2 Dissociation of CT Excitons 152 5.5 Conclusions 153 References 154 6 Photoluminescence 157Takeshi Aoki 6.1 Introduction 157 6.2 Fundamental Aspects of Photoluminescence (PL) in Materials 158 6.2.1 Intrinsic Photoluminescence 159 6.2.2 Extrinsic Photoluminescence 160 6.2.3 Up-Conversion Photoluminescence (UCPL) 162 6.2.4 Other Related Optical Transitions 163 6.3 Experimental Aspects 164 6.3.1 Static PL Spectroscopy 164 6.3.2 Photoluminescence Excitation Spectroscopy (PLE) and Photoluminescence Absorption Spectroscopy (PLAS) 167 6.3.3 Time Resolved Spectroscopy (TRS) 168 6.3.4 Time-Correlated Single Photon Counting (TCSPC) 171 6.3.5 Frequency-Resolved Spectroscopy (FRS) 172 6.3.6 Quadrature Frequency Resolved Spectroscopy (QFRS) 173 6.4 Photoluminescence Lifetime Spectroscopy of Amorphous Semiconductors by QFRS Technique 175 6.4.1 Overview 175 6.4.2 Dual-Phase Double Lock-in (DPDL) QFRS Technique 176 6.4.3 Exploring Broad PL Lifetime Distribution in a-Si:H by Wideband QFRS 178 6.4.3.1 Effects of Excitation Intensity, Excitation, and Emission Energies 179 6.4.3.2 Temperature Dependence 184 6.4.3.3 Effect of Electric and Magnetic Fields 185 6.4.4 Residual PL Decay of a-Si:H 189 6.5 QFRS on Up-Conversion Photoluminescence (UCPL) of RE-Doped Materials 192 6.6 Conclusions 197 Acknowledgments 198 References 198 7 Photoluminescence, Photoinduced Changes, and Electroluminescence in Noncrystalline Semiconductors 203Jai Singh 7.1 Introduction 203 7.2 Photoluminescence 205 7.2.1 Radiative Recombination Operator and Transition Matrix Element 206 7.2.2 Rates of Spontaneous Emission 211 7.2.2.1 At Nonthermal Equilibrium 212 7.2.2.2 At Thermal Equilibrium 214 7.2.2.3 Determining E0 215 7.2.3 Results of Spontaneous Emission and Radiative Lifetime 216 7.2.4 Temperature Dependence of PL 222 7.2.5 Excitonic Concept 223 7.3 Photoinduced Changes in Amorphous Chalcogenides 225 7.3.1 Effect of Photo-Excitation and Phonon Interaction 226 7.3.2 Excitation of a Single Electron–Hole Pair 228 7.3.3 Pairing of Like Excited Charge Carriers 229 7.4 Radiative Recombination of Excitons in Organic Semiconductors 232 7.4.1 Rate of Fluorescence 233 7.4.2 Rate of Phosphorescence 233 7.4.3 Organic Light Emitting Diodes (OLEDs) 234 7.4.3.1 Second- and Third-Generation OLEDs: TADF 235 7.5 Conclusions 236 Acknowledgments 236 References 237 8 Photoinduced Bond Breaking and Volume Change in Chalcogenide Glasses 241Sandor Kugler, Rozália Lukács, and Koichi Shimakawa 8.1 Introduction 241 8.2 Atomic-Scale Computer Simulations of Photoinduced Volume Changes 243 8.3 Effect of Illumination 244 8.4 Kinetics of Volume Change 245 8.4.1 a-Se 245 8.4.2 a-As2Se3 246 8.5 Additional Remarks 248 8.6 Conclusions 249 References 249 9 Properties and Applications of Photonic Crystals 251Harry E. Ruda and Naomi Matsuura 9.1 Introduction 251 9.2 PC Overview 252 9.2.1 Introduction to PCs 252 9.2.2 Nanoengineering of PC Architectures 253 9.2.3 Materials Selection for PCs 255 9.3 Tunable PCs 255 9.3.1 Tuning PC Response by Changing the Refractive Index of Constituent Materials 256 9.3.1.1 PC Refractive Index Tuning Using Light 256 9.3.1.2 PC Refractive Index Tuning Using an Applied Electric Field 256 9.3.1.3 Refractive Index Tuning of Infiltrated PCs 257 9.3.1.4 PC Refractive Index Tuning by Altering the Concentration of Free Carriers (Using Electric Field or Temperature) in Semiconductor-Based PCs 257 9.3.2 Tuning PC Response by Altering the Physical Structure of the PC 258 9.3.2.1 Tuning PC Response Using Temperature 258 9.3.2.2 Tuning PC Response Using Magnetism 258 9.3.2.3 Tuning PC Response Using Strain 258 9.3.2.4 Tuning PC Response Using Piezoelectric Effects 259 9.3.2.5 Tuning PC Response Using MEMS Actuation 260 9.4 Selected Applications of PC 260 9.4.1 Waveguide Devices 261 9.4.2 Dispersive Devices 262 9.4.3 Add/Drop Multiplexing Devices 262 9.4.4 Applications of PCs for Light-Emitting Diodes (LEDs) and Lasers 263 9.5 Conclusions 265 Acknowledgments 265 References 265 10 Nonlinear Optical Properties of Photonic Glasses 269Keiji Tanaka 10.1 Introduction 269 10.2 Photonic Glass 271 10.3 Nonlinear Absorption and Refractivity 272 10.3.1 Fundamentals 272 10.3.2 Two-Photon Absorption 275 10.3.3 Nonlinear Refractivity 278 10.4 Nonlinear Excitation-Induced Structural Changes 280 10.4.1 Fundamentals 280 10.4.2 Oxides 281 10.4.3 Chalcogenides 283 10.5 Conclusions 285 10.A Addendum: Perspectives on Optical Devices 286 References 288 11 Optical Properties of Organic Semiconductors 295Takashi Kobayashi and Hiroyoshi Naito 11.1 Introduction 295 11.2 Molecular Structure of π-Conjugated Polymers 296 11.3 Theoretical Models 298 11.4 Absorption Spectrum 300 11.5 Photoluminescence 304 11.6 Non-Emissive Excited States 306 11.7 Electron–Electron Interaction 309 11.8 Interchain Interaction 314 11.9 Conclusions 320 References 321 12 Organic Semiconductors and Applications 323Furong Zhu 12.1 Introduction 323 12.1.1 Device Architecture and Operation Principle 324 12.1.2 Technical Challenges and Process Integration 325 12.2 Anode Modification for Enhanced OLED Performance 327 12.2.1 Low-Temperature High-Performance ITO 327 12.2.1.1 Experimental Methods 328 12.2.1.2 Morphological Properties 329 12.2.1.3 Electrical Properties 331 12.2.1.4 Optical Properties 333 12.2.1.5 Compositional Analysis 336 12.2.2 Anode Modification 339 12.2.3 Electroluminescence Performance of OLEDs 340 12.3 Flexible OLEDs 345 12.3.1 Flexible OLEDs on Ultrathin Glass Substrate 346 12.3.2 Flexible Top-Emitting OLEDs on Plastic Foils 347 12.3.2.1 Top-Emitting OLEDs 348 12.3.2.2 Flexible TOLEDs on Plastic Foils 350 12.4 Solution-Processable High-Performing OLEDs 353 12.4.1 Performance of OLEDs with a Hybrid MoO3-PEDOT:PSS Hole Injection Layer (HIL) 353 12.4.2 Morphological Properties of the MoO3-PEDOT:PSS HIL 361 12.4.3 Surface Electronic Properties of MoO3-PEDOT:PSS HIL 363 12.5 Conclusions 368 References 369 13 Transparent White OLEDs 373Choi Wing Hong and Furong Zhu 13.1 Introduction—Progress in Transparent WOLEDs 373 13.2 Performance of WOLEDs 374 13.2.1 Optimization of Dichromatic WOLEDs 374 13.2.2 J-L-V Characteristics of WOLEDs 377 13.2.3 Electron-Hole Current Balance in Transparent WOLEDs 384 13.3 Emission Behavior of Transparent WOLEDs 386 13.3.1 Visible-Light Transparency of WOLEDs 386 13.3.2 L-J Characteristics of Transparent WOLEDs 390 13.3.3 Angular-Dependent Color Stability of Transparent WOLEDs 395 13.4 Conclusions 400 References 400 14 Optical Properties of Thin Films 403V.-V. Truong, S. Tanemura, A. Haché, and L. Miao 14.1 Introduction 403 14.2 Optics of Thin Films 404 14.2.1 An Isotropic Film on a Substrate 404 14.2.2 Matrix Methods for Multi-Layered Structures 406 14.2.3 Anisotropic Films 407 14.3 Reflection-Transmission Photoellipsometry for Determination of Optical Constants 408 14.3.1 Photoellipsometry of a Thick or a Thin Film 408 14.3.2 Photoellipsometry for a Stack of Thick and Thin Films 410 14.3.3 Remarks on the Reflection-Transmission Photoellipsometry Method 412 14.4 Application of Thin Films to Energy Management and Renewable-Energy Technologies 412 14.4.1 Electrochromic Thin Films 413 14.4.2 Pure and Metal-Doped VO2 Thermochromic Thin Films 414 14.4.3 Temperature-Stabilized V1-xWxO2 Sky Radiator Films 417 14.4.4 Optical Functional TiO2 Thin Film for Environmentally Friendly Technologies 420 14.5 Application of Tunable Thin Films to Phase and Polarization Modulation 424 14.6 Conclusions 430 References 430 15 Optical Characterization of Materials by Spectroscopic Ellipsometry 435J. Mistrík 15.1 Introduction 435 15.2 Notions of Light Polarization 436 15.3 Measureable Quantities 438 15.4 Instrumentation 441 15.5 Single Interface 442 15.6 Single Layer 448 15.7 Multilayer 454 15.8 Linear Grating 458 15.9 Conclusions 462 Acknowledgments 463 References 463 16 Excitonic Processes in Quantum Wells 465Jai Singh and I.-K. Oh 16.1 Introduction 465 16.2 Exciton–Phonon Interaction 466 16.3 Exciton Formation in QWs Assisted by Phonons 467 16.4 Nonradiative Relaxation of Free Excitons 474 16.4.1 Intraband Processes 475 16.4.2 Interband Processes 479 16.5 Quasi-2D Free-Exciton Linewidth 485 16.6 Localization of Free Excitons 491 16.7 Conclusions 499 References 500 17 Optoelectronic Properties and Applications of Quantum Dots 503Jørn M. Hvam 17.1 Introduction 503 17.2 Epitaxial Growth and Structure of Quantum Dots 504 17.2.1 Self-Assembled Quantum Dots 504 17.2.2 Site-Controlled Growth on Patterned Substrates 505 17.2.3 Natural or Interface Quantum Dots 506 17.2.4 Quantum Dots in Nanowires 507 17.3 Excitons in Quantum Dots 508 17.3.1 Quantum-Dot Bandgap 509 17.3.2 Optical Transitions 510 17.4 Optical Properties 513 17.4.1 Radiative Lifetime, Oscillator Strength, and Internal Quantum Efficiency 514 17.4.2 Linewidth, Coherence, and Dephasing 516 17.4.3 Transient Four-Wave Mixing 517 17.5 Quantum Dot Applications 520 17.5.1 Quantum Dot Lasers and Optical Amplifiers 520 17.5.1.1 Gain Dynamics 522 17.5.1.2 Homogeneous Broadening and Dephasing 524 17.5.1.3 Long-Wavelength Lasers 526 17.5.1.4 Nano Lasers 527 17.5.2 Single-Photon Emitters 527 17.5.2.1 Micropillars and Nanowires 530 17.5.2.2 Photonic Crystal Waveguide 531 17.6 Conclusions 533 Acknowledgments 534 References 534 18 Perovskites – Revisiting the Venerable ABX3 Family with Organic Flexibility and New Applications 537Junwei Xu, D.L. Carroll, K. Biswas, F. Moretti, S. Gridin, and R.T.Williams 18.1 Introduction 537 18.1.1 Review 537 18.1.2 The Structures 538 18.1.2.1 Simple Cubic Frameworks 538 18.1.2.2 The Multiplicity of Hybrids 539 18.1.2.3 Structural Variation 540 18.2 Hybrid Perovskites in Photovoltaics 544 18.2.1 Review 544 18.2.2 The Phenomena Characterized as “Defect Tolerance” 548 18.3 Light-Emitting Diodes Using Solution-Processed Lead Halide Perovskites 549 18.3.1 Review 549 18.3.2 Construction and Characterization of LEDs Utilizing CsPbBr3 Nano-Inclusions in Cs4PbBr6 as the Electroluminescent Medium 553 18.4 Ionizing Radiation Detectors Using Lead Halide Perovskite Materials: Basics, Progress, and Prospects 562 18.5 Conclusions 582 Acknowledgments 583 References 583 19 Optical Properties and Spin Dynamics of Diluted Magnetic Semiconductor Nanostructures 589Akihiro Murayama and Yasuo Oka 19.1 Introduction 589 19.2 Quantum Wells 591 19.2.1 Spin Injection 591 19.2.2 Study of Spin Dynamics by Pump-Probe Spectroscopy 594 19.3 Fabrication of Nanostructures by Electron-Beam Lithography 596 19.4 Self-Assembled Quantum Dots 599 19.5 Hybrid Nanostructures with Ferromagnetic Materials 604 19.6 Conclusions 607 Acknowledgments 608 References 609 20 Kinetics of the Persistent Photoconductivity in Crystalline III-V Semiconductors 611Ruben Jeronimo Freitas and Koichi Shimakawa 20.1 Introduction 611 20.2 A Review of PPC in III-V Semiconductors 613 20.3 Key Physical Terms Related to PPC 615 20.3.1 Dispersive Reaction 615 20.3.2 SEF and Power Law 616 20.3.3 Waiting Time Distribution 617 20.4 Kinetics of PPC in III-V Semiconductors 617 20.5 Conclusions 623 Acknowledgments 623 20.A On the Reaction Rate Under the Uniform Distribution 623 References 625 Index 627

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Book SynopsisExplains current co-design and co-optimization methodologies for building hardware neural networks and algorithms for machine learning applications This book focuses on how to build energy-efficient hardware for neural networks with learning capabilitiesand provides co-design and co-optimization methodologies for building hardware neural networks that can learn. Presenting a complete picture from high-level algorithm to low-level implementation details, Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design also covers many fundamentals and essentials in neural networks (e.g., deep learning), as well as hardware implementation of neural networks. The book begins with an overview of neural networks. It then discusses algorithms for utilizing and training rate-based artificial neural networks. Next comes an introduction to various options for executing neural networks, ranging from general-purpose processors to specializedTable of ContentsPreface xi Acknowledgment xix 1 Overview 1 1.1 History of Neural Networks 1 1.2 Neural Networks in Software 2 1.2.1 Artificial Neural Network 2 1.2.2 Spiking Neural Network 3 1.3 Need for Neuromorphic Hardware 3 1.4 Objectives and Outlines of the Book 5 References 8 2 Fundamentals and Learning of Artificial Neural Networks 11 2.1 Operational Principles of Artificial Neural Networks 11 2.1.1 Inference 11 2.1.2 Learning 13 2.2 Neural Network Based Machine Learning 16 2.2.1 Supervised Learning 17 2.2.2 Reinforcement Learning 20 2.2.3 Unsupervised Learning 22 2.2.4 Case Study: Action-Dependent Heuristic Dynamic Programming 23 2.2.4.1 Actor-Critic Networks 24 2.2.4.2 On-Line Learning Algorithm 25 2.2.4.3 Virtual Update Technique 27 2.3 Network Topologies 31 2.3.1 Fully Connected Neural Networks 31 2.3.2 Convolutional Neural Networks 32 2.3.3 Recurrent Neural Networks 35 2.4 Dataset and Benchmarks 38 2.5 Deep Learning 41 2.5.1 Pre-Deep-Learning Era 41 2.5.2 The Rise of Deep Learning 41 2.5.3 Deep Learning Techniques 42 2.5.3.1 Performance-Improving Techniques 42 2.5.3.2 Energy-Efficiency-Improving Techniques 46 2.5.4 Deep Neural Network Examples 50 References 53 3 Artificial Neural Networks in Hardware 61 3.1 Overview 61 3.2 General-Purpose Processors 62 3.3 Digital Accelerators 63 3.3.1 A Digital ASIC Approach 63 3.3.1.1 Optimization on Data Movement and Memory Access 63 3.3.1.2 Scaling Precision 71 3.3.1.3 Leveraging Sparsity 76 3.3.2 FPGA-Based Accelerators 80 3.4 Analog/Mixed-Signal Accelerators 82 3.4.1 Neural Networks in Conventional Integrated Technology 82 3.4.1.1 In/Near-Memory Computing 82 3.4.1.2 Near-Sensor Computing 85 3.4.2 Neural Network Based on Emerging Non-volatile Memory 88 3.4.2.1 Crossbar as a Massively Parallel Engine 89 3.4.2.2 Learning in a Crossbar 91 3.4.3 Optical Accelerator 93 3.5 Case Study: An Energy-Efficient Accelerator for Adaptive Dynamic Programming 94 3.5.1 Hardware Architecture 95 3.5.1.1 On-Chip Memory 95 3.5.1.2 Datapath 97 3.5.1.3 Controller 99 3.5.2 Design Examples 101 References 108 4 Operational Principles and Learning in Spiking Neural Networks 119 4.1 Spiking Neural Networks 119 4.1.1 Popular Spiking Neuron Models 120 4.1.1.1 Hodgkin-Huxley Model 120 4.1.1.2 Leaky Integrate-and-Fire Model 121 4.1.1.3 Izhikevich Model 121 4.1.2 Information Encoding 122 4.1.3 Spiking Neuron versus Non-Spiking Neuron 123 4.2 Learning in Shallow SNNs 124 4.2.1 ReSuMe 124 4.2.2 Tempotron 125 4.2.3 Spike-Timing-Dependent Plasticity 127 4.2.4 Learning Through Modulating Weight-Dependent STDP in Two-Layer Neural Networks 131 4.2.4.1 Motivations 131 4.2.4.2 Estimating Gradients with Spike Timings 131 4.2.4.3 Reinforcement Learning Example 135 4.3 Learning in Deep SNNs 146 4.3.1 SpikeProp 146 4.3.2 Stack of Shallow Networks 147 4.3.3 Conversion from ANNs 148 4.3.4 Recent Advances in Backpropagation for Deep SNNs 150 4.3.5 Learning Through Modulating Weight-Dependent STDP in Multilayer Neural Networks 151 4.3.5.1 Motivations 151 4.3.5.2 Learning Through Modulating Weight-Dependent STDP 151 4.3.5.3 Simulation Results 158 References 167 5 Hardware Implementations of Spiking Neural Networks 173 5.1 The Need for Specialized Hardware 173 5.1.1 Address-Event Representation 173 5.1.2 Event-Driven Computation 174 5.1.3 Inference with a Progressive Precision 175 5.1.4 Hardware Considerations for Implementing the Weight-Dependent STDP Learning Rule 181 5.1.4.1 Centralized Memory Architecture 182 5.1.4.2 Distributed Memory Architecture 183 5.2 Digital SNNs 186 5.2.1 Large-Scale SNN ASICs 186 5.2.1.1 SpiNNaker 186 5.2.1.2 TrueNorth 187 5.2.1.3 Loihi 191 5.2.2 Small/Moderate-Scale Digital SNNs 192 5.2.2.1 Bottom-Up Approach 192 5.2.2.2 Top-Down Approach 193 5.2.3 Hardware-Friendly Reinforcement Learning in SNNs 194 5.2.4 Hardware-Friendly Supervised Learning in Multilayer SNNs 199 5.2.4.1 Hardware Architecture 199 5.2.4.2 CMOS Implementation Results 205 5.3 Analog/Mixed-Signal SNNs 210 5.3.1 Basic Building Blocks 210 5.3.2 Large-Scale Analog/Mixed-Signal CMOS SNNs 211 5.3.2.1 CAVIAR 211 5.3.2.2 BrainScaleS 214 5.3.2.3 Neurogrid 215 5.3.3 Other Analog/Mixed-Signal CMOS SNN ASICs 216 5.3.4 SNNs Based on Emerging Nanotechnologies 216 5.3.4.1 Energy-Efficient Solutions 217 5.3.4.2 Synaptic Plasticity 218 5.3.5 Case Study: Memristor Crossbar Based Learning in SNNs 220 5.3.5.1 Motivations 220 5.3.5.2 Algorithm Adaptations 222 5.3.5.3 Non-idealities 231 5.3.5.4 Benchmarks 238 References 238 6 Conclusions 247 6.1 Outlooks 247 6.1.1 Brain-Inspired Computing 247 6.1.2 Emerging Nanotechnologies 249 6.1.3 Reliable Computing with Neuromorphic Systems 250 6.1.4 Blending of ANNs and SNNs 251 6.2 Conclusions 252 References 253 A Appendix 257 A.1 Hopfield Network 257 A.2 Memory Self-Repair with Hopfield Network 258 References 266 Index 269

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Book SynopsisOffers timely and comprehensive coverage of dynamic system reliability theory This book focuses on hot issues of dynamic system reliability, systematically introducing the reliability modeling and analysis methods for systems with imperfect fault coverage, systems with function dependence, systems subject to deterministic or probabilistic common-cause failures, systems subject to deterministic or probabilistic competing failures, and dynamic standby sparing systems. It presents recent developments of such extensions involving reliability modelling theory, reliability evaluation methods, and features numerous case studies based on real-world examples. The presented dynamic reliability theory can enable a more accurate representation of actual complex system behavior, thus more effectively guiding the reliable design of real-world critical systems. Dynamic System Reliability: Modelling and Analysis of Dynamic and Dependent Behaviors begins by describing theTable of ContentsForeword ix Preface xi Nomenclature xv 1 Introduction 1 References 4 2 Fundamental Reliability Theory 7 2.1 Basic Probability Concepts 7 2.1.1 Axioms of Probability 7 2.1.2 Conditional Probability 7 2.1.3 Total Probability Law 8 2.1.4 Bayes’ Theorem 9 2.1.5 Random Variables 9 2.2 Reliability Measures 10 2.2.1 Time to Failure 11 2.2.2 Failure Function 11 2.2.3 Reliability Function 11 2.2.4 Failure Rate 11 2.2.5 Mean Time to Failure 11 2.2.6 Mean Residual Life 12 2.3 Fault Tree Modeling 12 2.3.1 Static Fault Tree 13 2.3.2 Dynamic Fault Tree 13 2.3.3 Phased-Mission Fault Tree 14 2.3.4 Multi-State Fault Tree 15 2.4 Binary Decision Diagram 16 2.4.1 Basic Concept 17 2.4.2 ROBDD Generation 17 2.4.3 ROBDD Evaluation 18 2.4.4 Illustrative Example 19 2.5 Markov Process 20 2.6 Reliability Software 22 References 22 3 Imperfect Fault Coverage 27 3.1 Different Types of IPC 27 3.2 ELC Modeling 28 3.3 Binary-State System 29 3.3.1 BDD Expansion Method 29 3.3.2 Simple and Efficient Algorithm 32 3.4 Multi-State System 34 3.4.1 MMDD-Based Method for MSS Analysis 35 3.4.2 Illustrative Example 36 3.5 Phased-Mission System 37 3.5.1 Mini-Component Concept 37 3.5.2 PMS SEA 38 3.5.3 PMS BDD Method 40 3.5.4 Summary of PMS SEA 42 3.5.5 Illustrative Example 42 3.6 Summary 43 References 45 4 Modular Imperfect Coverage 49 4.1 Modular Imperfect Coverage Model 49 4.2 Non repairable Hierarchical System 51 4.3 Repairable Hierarchical System 55 4.4 Summary 58 References 58 5 Functional Dependence 61 5.1 Logic OR Replacement Method 61 5.2 Combinatorial Algorithm 63 5.2.1 Task 1: Addressing UFs of Independent Trigger Components 63 5.2.2 Task 2: Generating Reduced Problems Without FDEP 63 5.2.3 Task 3: Solving Reduced Reliability Problems 64 5.2.3.1 Expansion Process 64 5.2.3.2 Reduced FT Generation Procedure 65 5.2.3.3 Dual Trigger-Basic Event Handling 65 5.2.3.4 Evaluation of P(system fails|ITEi) 65 5.2.4 Task 4: Integrating to Obtain Final System Unreliability 66 5.2.5 Algorithm Summary 66 5.2.6 Algorithm Complexity 66 5.3 Case Study 1: Combined Trigger Event 67 5.4 Case Study 2: Shared Dependent Event 70 5.5 Case Study 3: Cascading FDEP 73 5.5.1 Evaluation of P(system fails|ITE1) 74 5.5.2 Evaluation of P(system fails|ITE2) 75 5.5.3 Evaluation of URsystem 76 5.6 Case Study 4: Dual Event and Cascading FDEP 76 5.6.1 Evaluation of P(system fails|ITE1) 78 5.6.2 Evaluation of URsystem 79 5.7 Summary 79 References 80 6 Deterministic Common-Cause Failure 83 6.1 Explicit Method 84 6.1.1 Two-Step Method 84 6.1.2 Illustrative Example 84 6.2 Efficient Decomposition and Aggregation Approach 85 6.2.1 Three-Step Method 86 6.2.2 Illustrative Example 87 6.3 Decision Diagram–Based Aggregation Method 89 6.3.1 Three-Step Method 89 6.3.2 Illustrative Example 91 6.4 Universal Generating Function–Based Method 94 6.4.1 System Model 94 6.4.2 u-Function Method for Series-Parallel Systems 95 6.4.3 u-Function Method for CCFs 97 6.4.4 Illustrative Example 99 6.5 Summary 104 References 104 7 Probabilistic Common-Cause Failure 107 7.1 Single-Phase System 107 7.1.1 Explicit Method 108 7.1.2 Implicit Method 110 7.1.3 Comparisons and Discussions 115 7.2 Multi-Phase System 115 7.2.1 Explicit Method 115 7.2.2 Implicit Method 119 7.2.3 Comparisons and Discussions 123 7.3 Impact of PCCF 124 7.4 Summary 125 References 125 8 Deterministic Competing Failure 127 8.1 Overview 127 8.2 PFGE Method 128 8.2.1 s-Independent LF and PFGE 128 8.2.2 s-Dependent LF and PFGE 128 8.2.3 Disjoint LF and PFGE 129 8.3 Single-Phase System with Single FDEP Group 129 8.3.1 Combinatorial Method 129 8.3.2 Case Study 131 8.4 Single-Phase System with Multiple FDEP Groups 135 8.4.1 Combinatorial Method 135 8.4.2 Case Study 137 8.5 Single-Phase System with PFs Having Global and Selective Effects 141 8.5.1 Combinatorial Method 141 8.5.2 Case Study 144 8.6 Multi-Phase System with Single FDEP Group 150 8.6.1 Combinatorial Method 150 8.6.2 Case Study 153 8.7 Multi-Phase System with Multiple FDEP Groups 158 8.7.1 CTMC-Based Method 158 8.7.2 Case Study 159 8.8 Summary 166 References 167 9 Probabilistic Competing Failure 169 9.1 Overview 169 9.2 System with Single Type of Component Local Failures 170 9.2.1 Combinatorial Method 170 9.2.2 Case Study 172 9.3 System with Multiple Types of Component Local Failures 181 9.3.1 Combinatorial Method 181 9.3.2 Case Study 182 9.4 System with Random Failure Propagation Time 190 9.4.1 Combinatorial Method 190 9.4.2 Case Study: WSN System 192 9.5 Summary 198 References 199 10 Dynamic Standby Sparing 201 10.1 Types of Standby Systems 201 10.2 CTMC-Based Method 202 10.2.1 Cold Standby System 203 10.2.2 Warm Standby System 204 10.3 Decision Diagram−Based Method 205 10.3.1 Cold Standby System 205 10.3.2 Warm Standby System 208 10.4 Approximation Method 211 10.4.1 Homogeneous Cold Standby System 212 10.4.2 Heterogeneous Cold Standby System 214 10.5 Event Transition Method 216 10.5.1 State-Space Representation of System Behavior 217 10.5.2 Basic Steps 218 10.5.3 Warm Standby System 218 10.6 Overview of Optimization Problems 220 10.7 Summary 222 References 222 Index 229

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Book SynopsisA guide to a multi-disciplinary approach that includes perspectives from noted experts in the energy and utilities fields Advances in Energy Systems offers a stellar collection of articles selected from the acclaimed journal Wiley Interdisciplinary Review: Energy and Environment. The journalcovers all aspects of energy policy, science and technology, environmental and climate change. The book covers a wide range of relevant issues related to the systemic changes for large-scale integration of renewable energy as part of the on-going energy transition. The book addresses smart energy systems technologies, flexibility measures, recent changes in the marketplace and current policies. With contributions from a list of internationally renowned experts, the book deals with the hot topic of systems integration for future energy systems and energy transition. This important resource: Contains contributions from noted experts in the field Table of ContentsList of Contributors ix Preface xi Part I: Energy System Challenges 1 1 Handling Renewable Energy Variability and Uncertainty in Power System Operation 3Ricardo Bessa, Carlos Moreira, Bernardo Silva and Manuel Matos 2 Short-Term Frequency Response of Power Systems with High Nonsynchronous Penetration Levels 27Lisa Ruttledge and Damian Flynn 3 Technical Impacts of High Penetration Levels of Wind Power on Power System Stability 47Damian Flynn, Zakir Rather, Atle Rygg Årdal, Salvatore D'Arco, Anca D. Hansen, Nicolaos A. Cutululis, Poul Sorensen, Ana Estanqueiro, Emilio Gómez-Lázaro, Nickie Menemenlis, Charles Smith and Ye Wang 4 Understanding Constraints to the Transformation Rate of Global Energy Infrastructure 67Joe L. Lane, Simon Smart, Diego Schmeda-Lopez, Ove Hoegh-Guldberg, Andrew Garnett, Chris Greig and Eric McFarland 5 Physical and Cybersecurity in a Smart Grid Environment 85Jing Xie, Alexandru Stefanov and Chen]Ching Liu 6 Energy Security: Challenges and Needs 111Benjamin K. Sovacool 7 Nuclear and Renewables: Compatible or Contradicting? 119Lutz Mez Part II: Perspectives on Grids 127 8 Smart-Grid Policies: An International Review 129Marilyn A. Brown and Shan Zhou 9 A View of Microgrids 149Joao A. P. Lopes, Andre G. Madureira and Carlos Moreira 10 New Electricity Distribution Network Planning Approaches for Integrating Renewables 167Fabrizio Pilo, Gianni Celli, Emilio Ghiani and Gian G. Soma 11 Transmission Planning for Wind Energy in the United States and Europe: Status and Prospects 187Charles Smith, Dale Osborn, Robert Zavadil, Warren Lasher, Emilio Gómez-Lázaro, Ana Estanqueiro, Thomas Trotscher, John Tande, Magnus Korpas, Frans Van Hulle, Hannele Holttinen, Antje Orths, Daniel Burke, Mark O’Malley, Jan Dobschinski, Barry Rawn, Madeline Gibescu and Lewis Dale 12 Opportunities and Barriers of High-Voltage Direct Current Grids: A State-of-the-Art Analysis 201Debora Coil]Mayor and Jürgen Schmid 13 Wireless Power Transmission: Inductive Coupling, Radio Wave, and Resonance Coupling 211Naoki Shinohara Part III: Flexibility Measures 221 14 The Role of Large]Scale Energy Storage Under High Shares of Renewable Energy 223Shin]ichi Inage 15 The Role of Electric Vehicles in Smart Grids 245Matthias D. Galus, Marina González Vayá, Thilo Krause and Göran Andersson 16 Use of Electric Vehicles or Hydrogen in the Danish Transport Sector in 2050? 265Klaus Skytte, Amalia Pizarro and Kenneth B. Karlsson 17 Comparison of Synthetic Natural Gas Production Pathways for the Storage of Renewable Energy 279Sebastian Fendt, Alexander Buttler, Matthias Gaderer and Hartmut Spliethoff 18 Storage and Demand]Side Options for Integrating Wind Power 303Aidan Tuohy, Ben Kaun and Robert Entriken 19 On the Long-Term Prospects of Power-to-Gas Technologies 321Amela Ajanovic and Reinhard Haas 20 Wind Integration: Experience, Issues, and Challenges 341Hannele Holttinen 21 Quantifying the Variability of Wind Energy 355Simon Watson 22 Capacity Value Assessments of Wind Power 369Michael Milligan, Bethany Frew, Eduardo Ibanez, Juha Kiviluoma, Hannele Holttinen and Lennart Söder 23 Hydropower Flexibility for Power Systems with Variable Renewable Energy Sources: An IEA Task 25 Collaboration 385Daniel Huertas]Hernando, Hossein Farahmand, Hannele Holttinen, Juha Kiviluoma, Erkka Rinne, Lennart Söder, Michael Milligan, Eduardo Ibanez, Sergio M. Martinez, Emilio Gómez-Lázaro, Ana Estanqueiro, Luis Rodrigues, Luis Carr, Serafin van Roon, Antje Orths, Peter B. Eriksen, Alain Forcione and Nickie Menemenlis 24 Contribution of Bulk Energy Storage to Integrating Variable Renewable Energies in Future European Electricity Systems 407Karl A. Zach and Hans Auer 25 Characterization of Demand Response in the Commercial, Industrial, and Residential Sectors in the United States 425Sila Kiliccote, Daniel Olsen, Michael D. Sohn and Mary A. Piette 26 Simplified Analysis of Balancing Challenges in Sustainable and Smart Energy Systems with 100% Renewable Power Supply 445Lennart Söder Part IV: Changing Electricity Markets 459 27 Who Gains from Hourly Time-of-Use Retail Prices on Electricity? An Analysis of Consumption Profiles for Categories of Danish Electricity Customers 461F. M. Andersen, H. V. Larsen, Lena Kitzing and P. E. Morthorst 28 Designing Electricity Markets for a High Penetration of Variable Renewables 479Jenny Riesz and Michael Milligan 29 Multivariate Analysis of Solar City Economics: Impact of Energy Prices, Policy, Finance, and Cost on Urban Photovoltaic Power Plant Implementation 491John Byrne, Job Taminiau, Kyung N. Kim, Joohee Lee and Jeongseok Seo 30 The Influence of Interconnection Capacity on the Market Value of Wind Power 507Carlo Obersteiner 31 Research with Disaggregated Electricity End-Use Data in Households: Review and Recommendations 517Ian H. Rowlands, Tobi Reid and Paul Parker 32 Household Electricity Consumers' Incentive to Choose Dynamic Pricing Under Different Taxation Schemes 531Jonas Katz, Lena Kitzing, Sascha T. Schröder, F. M. Andersen, P. E. Morthorst and Morten Stryg Index 545

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Book SynopsisA comprehensive review of the theory and practice for designing, operating, and optimizing electric distribution systems, revised and updated Now in its second edition, Electric Distribution Systems has been revised and updated and continues to provide a two-tiered approach for designing, installing, and managing effective and efficient electric distribution systems. With an emphasis on both the practical and theoretical approaches, the text is a guide to the underlying theory and concepts and provides a resource for applying that knowledge to problem solving. The authorsnoted experts in the fieldexplain the analytical tools and techniques essential for designing and operating electric distribution systems. In addition, the authors reinforce the theories and practical information presented with real-world examples as well as hundreds of clear illustrations and photos. This essential resource contains the information needed to design electric distribution Table of ContentsPreface xi Acknowledgments xiii Part I Fundamental Concepts Chapter 1 Introduction 3 1.1 Introduction and Background 3 1.2 Power System Structure 3 1.3 Distribution Level 5 1.4 General 7 Chapter 2 Distribution System Structure 9 2.1 Distribution Voltage Levels 9 2.2 Distribution System Configuration 9 2.3 General Comments 22 Chapter 3 Distribution System Planning 23 3.1 Duties of Distribution System Planners 23 3.2 Factors Affecting the Planning Process 25 3.3 Planning Objectives 31 3.4 Solutions for Meeting Load Forecasts 37 Chapter 4 Load Forecasting 41 4.1 Introduction 41 4.2 Important Factors for Forecasts 42 4.3 Forecasting Methodology 43 4.4 Spatial Load Forecasting (SLF) 56 4.5 End-Use Modeling 64 4.6 Spatial Load Forecast Methods 65 Part II Protection And Switchgear Chapter 5 Earthing Of Electric Distribution Systems 75 5.1 Basic Objectives 75 5.2 Earthing Electrical Equipment 76 5.3 System Earthing 93 5.4 MV Earthing Systems 99 5.5 Earthing Systems in LV Distribution Networks 104 Chapter 6 Short-Circuit Studies 111 6.1 Introduction 111 6.2 Short-Circuit Analysis 113 Chapter 7 Protection: Current-Based Schemes 163 7.1 Introduction 163 7.2 Types of Relay Construction 166 7.3 Overcurrent Protection 171 7.4 Directional Protection 187 7.5 Differential Protection 193 Chapter 8 Protection: Other Schemes 207 8.1 Overvoltage Protection 207 8.2 Thermal Protection 220 8.3 Reclosers, Sectionalizers, Fuses 223 Chapter 9 Switchgear Devices 235 9.1 Need for Switchgear 235 9.2 MV Switchgear Devices 237 9.3 LV Switchgear Devices 244 9.4 Protection Classes 250 9.5 Specifications and Implementation of Earthing 251 9.6 Assessment of Switchgear 253 9.7 Safety and Security of Installations 255 9.8 Application Trends in MV Switchgear 256 Chapter 10 Switchgear Installation 261 10.1 Steps for Installing Switchgear 261 10.2 Switchgear Layout 262 10.3 Dimensioning of Switchgear Installations 264 10.4 Civil Construction Requirements 275 10.5 ARC-Flash Hazards 282 Part III Power Quality Chapter 11 Electric Power Quality 297 11.1 Overview 297 11.2 Power Quality Problems 298 11.3 Cost of Power Quality 304 11.4 Solutions of Power Quality Problems 310 11.5 Solution Cycle for Power Quality Problems 317 Chapter 12 Voltage Variations 321 12.1 Voltage Quality 321 12.2 Methods of Voltage Drop Reduction 329 12.3 Voltage Sag Calculations 345 12.4 Estimation of Distribution Losses 356 Chapter 13 Power Factor Improvement 361 13.1 Background 361 13.2 Shunt Compensation 365 13.3 Need for Shunt Compensation 366 13.4 An Example 368 13.5 How to Determine Compensation 370 Chapter 14 Harmonics in Electric Distribution Systems 379 14.1 What Are Harmonics? 379 14.2 Sources of Harmonics 384 14.3 Disturbances Caused by Harmonics 391 14.4 Principles of Harmonic Distortion Indications and Measurement 396 14.5 Frequency Spectrum and Harmonic Content 398 14.6 Standards and Recommendations 400 Chapter 15 Harmonics Effect Mitigation 403 15.1 Introduction 403 15.2 First Class of Solutions 403 15.3 Second Class of Solutions 404 15.4 Third Class of Solutions 406 15.5 Selection Criteria 409 15.6 Case Studies 409 Part IV Management And Automation Chapter 16 Demand-Side Management And Energy Efficiency 431 16.1 Overview 431 16.2 DSM 432 16.3 Needs to Apply DSM 433 16.4 Means of DSM Programs 434 16.5 International Experience with DSM 437 16.6 Potential for DSM Application 438 16.7 The DSM Planning Process 439 16.8 Expected Benefits of Managing Demand 444 16.9 Energy Efficiency 444 16.10 Scenarios Used for Energy-Efficiency Application 445 16.11 Economic Benefits of Energy Efficiency 445 16.12 Application of Efficient Technology 445 Chapter 17 SCADA Systems 465 17.1 Introduction 465 17.2 Definitions 469 17.3 SCADA Components 470 17.4 SCADA Systems Architectures 473 17.5 SCADA Applications 480 17.6 SCADA and Grid Modernization 484 Part V Distributed Energy Resources And Microgrids Chapter 18 Distributed Generation 489 18.1 Power Systems and Distributed Generation 489 18.2 Performance of Distributed Generators 493 18.3 Case Study 518 Chapter 19 Electrical Energy Storage 535 19.1 Introduction 535 19.2 Electrical Energy Storage 535 19.3 Role of Electrical Energy Storage 538 19.4 Types of EES Systems 540 19.5 Energy Storage Application 550 Chapter 20 Microgrids And Smart Grids 553 20.1 Background 553 20.2 MG Benefits 555 20.3 MG Operation 556 20.4 Challenges 556 20.5 Handling the Challenges 557 20.6 Control Methodology 558 20.7 Case Study 560 20.8 Protection for MGs 570 20.9 Concluding Remarks on MGs 572 20.10 Smart Grids 572 Appendix A Data Of Microgrid Components 581 Appendix B Matlab Simulink Models 583 References 589 Index 601

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Book SynopsisCoal accounts for approximately one quarter of world energy consumption and of the coal produced worldwide approximately 65% is shipped to electricity producers and 33% to industrial consumers, with most of the remainder going to consumers in the residential and commercial sectors. The total share of total world energy consumption by coal is expected to increase to almost 30% in 2035. This book describes the challenges and steps by which electricity is produced form coal and deals with the challenges for removing the environmental objections to the use of coal in future power plants. New technologies are described that could virtually eliminate the sulfur, nitrogen, and mercury pollutants that are released when coal is burned for electricity generation. In addition, technologies for the capture greenhouse gases emitted from coal-fired power plants are described and the means of preventing such emissions from contributing to global warming concerns. Written by one of thTable of ContentsPreface xvii Part I: Origin and Properties 1 1 History, Occurrence, and Resources 3 1.1 Introduction 3 1.2 Origin of Coal 8 1.3 Occurrence 12 1.4 Coal Utilization and Coal Types 14 1.5 Resources 22 1.6 Reserves 26 1.7 Energy Independence 31 References 33 2 Classification 37 2.1 Introduction 37 2.2 Nomenclature of Coal 39 2.3 Classification Systems 43 2.4 Coal Petrography 59 2.5 Correlation of the Various Systems 62 References 65 3 Recovery, Preparation, and Transportation 67 3.1 Introduction 67 3.2 Coal Recovery 69 3.3 Coal Preparation 78 3.4 Size Reduction 87 3.5 Coal Cleaning 92 3.6 Coal Drying 98 3.7 Desulfurization 104 3.8 Transportation 105 References 109 4 Storage 113 4.1 Introduction 113 4.2 Stockpiling 115 4.4 Spontaneous Ignition 124 4.5 Mechanism of Spontaneous Ignition 134 4.6 Preventing Spontaneous Ignition 137 References 138 5 General Properties 143 5.1 Introduction 143 5.2 Sampling 149 5.3 Proximate Analysis 154 5.4 Ultimate Analysis 167 5.5 Calorific Value 174 5.6 Reporting Coal Analyses 176 References 180 6 Physical, Mechanical, Thermal, and Electrical Properties 187 6.1 Introduction 187 6.2 Physical Properties 190 6.3 Mechanical Properties 200 6.4 Thermal Properties 207 6.5 Electrical Properties 214 6.6 Epilog 217 References 217 Part II: Power Generation 223 7 Combustion 225 7.1 Introduction 225 7.2 General Aspects 230 7.3 Chemistry and Physics 232 7.4 Catalytic Combustion 249 7.5 Fuels 249 References 269 8 Combustion Systems 275 8.1 Introduction 275 8.2 Combustion Systems 278 8.3 Fuel Feeders 303 References 304 9 Gasification 307 9.1 Introduction 307 9.2 General Aspects 309 9.3 Chemistry and Physics 325 9.4 Catalytic Gasification 334 9.5 Plasma Gasification 335 9.6 Gaseous Products 336 9.7 Underground Gasification 341 References 344 10 Gasification Systems 349 10.1 Introduction 349 10.2 Gasifier Types 352 10.3 Fixed-Bed Processes 358 10.4 Fluidized-Bed Processes 367 10.5 Entrained-Bed Processes 381 10.6 Molten Salt Processes 386 10.7 Other Designs 390 10.8 Gasifier-Feedstock Compatibility 396 10.8.7 Propensity for Char Formation 400 10.8.8 Mineral Matter Content 400 10.8.9 Ash Yield 400 10.9 Energy Balance and Other Design Options 401 10.10 Underground Gasification 402 References 406 11 Electric Power Generation 409 11.1 Introduction 409 11.2 Electricity From Coal 412 11.3 Steam Generation 415 11.4 Control of Emissions 425 11.5 Power Plant Efficiency 428 11.6 Combined Cycle Generation 432 References 435 12 Gas Cleaning 437 12.1 Introduction 437 12.2 General Aspects 437 12.3 Air Pollution Control Devices 445 12.4 Particulate Matter Removal 449 12.5 Acid Gas Removal 458 12.6 Removal of Sulfur-Containing Gases 462 12.7 Removal of Nitrogen-Containing Gases 465 12.8 Environmental Legislation 467 References 469 13 Clean Coal Technologies for Power Generation 473 13.1 Introduction 473 13.2 Historical Perspectives 480 13.3 Modern Perspectives 481 13.4 Clean Coal Technology 483 13.5 Managing Wastes from Coal Use 504 13.6 Carbon Dioxide Capture and Sequestration 506 References 514 14 Environmental Issues 519 14.1 Introduction 519 14.2 Coal Preparation 521 14.3 Transportation and Storage 523 14.4 Combustion 525 14.5 Gasification 532 14.6 Power Plant Waste 536 14.7 The Future 553 References 556 Part III: Alternative Feedstocks and Energy Security 559 15 Alternate Feedstocks 561 15.1 Introduction 561 15.2 Viscous Feedstocks 562 15.3 Biomass 575 15.4 Waste 605 References 610 16 Combustion of Alternate Feedstocks 613 16.1 Introduction 613 16.2 Viscous Feedstocks 615 16.3 Biomass 619 16.4 Solid Waste 632 References 638 17 Gasification of Alternate Feedstocks 641 17.1 Introduction 641 17.2 Viscous Feedstocks 643 17.3 Biomass 651 17.4 Solid Waste 656 17.5 Process Products 667 References 673 18 Coal and Energy Security 679 18.1 Introduction 679 18.2 Energy Security 683 18.3 The Future of Coal 687 18.4 Sustainable Development 694 References 701 Conversion Factors 705 Glossary 709 Index 753 About the Author 759

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Book SynopsisProvides clear analysis on the development potentials and practical realization of solar, wind, wave, and geothermal renewable energy technologies Presented as a clear introduction to the topics of climate protection and renewable energy, this book demonstrates the correlations between use of energy, energy prices, and climate change. It evaluates and analyzes the current world situation (drawing on examples given from countries across the globe), whilst also giving essential and practical guidance on personal' climate protection. Each major type of renewable energy system is covered in detail and with an easy-to-read approach, making it an ideal manual for planning and realizing climate protection and renewable energy systems, while also being an informative textbook for those studying renewable energy and environment and sustainability courses. Renewable Energy and Climate Change, 2nd Edition starts by examining our hunger for energyhow much we need, how much we use, and how much Table of ContentsPreface to First Edition xi Preface to the Second Edition xiii 1 Our Hunger for Energy 1 1.1 Energy Supply – Yesterday and Today 2 1.1.1 From the French Revolution to the Early Twentieth Century 2 1.1.2 The Era of Black Gold 4 1.1.3 Natural Gas – The Newest Fossil Energy Source 7 1.1.4 Nuclear Power – Split Energy 8 1.1.5 The Century of Fossil Energy 12 1.1.6 The Renewables Century 13 1.2 Energy Needs – Who Needs What, Where, and How Much? 14 1.3 ‘Anyway’ Energy 17 1.4 Energy Reserves –Wealth for a Time 20 1.4.1 Non-Conventional Reserves – Prolongation of the Oil Age 21 1.4.2 An End in Sight 22 1.4.3 The End of Fission 24 1.5 High Energy Prices – the Key to Climate Protection 24 2 The Climate Before the Collapse 27 2.1 It Is Getting Warm – Climate Changes Today 27 2.1.1 Accelerated Ice Melt 27 2.1.2 More Frequent Natural Catastrophes 30 2.2 The Guilty Parties – Causes of Climate Change 33 2.2.1 The Greenhouse Effect 33 2.2.2 The Prime Suspect: Carbon Dioxide 34 2.2.3 Other Culprits 38 2.3 Outlook and Recommendations –What Lies Ahead? 40 2.3.1 Will it Be Bitterly Cold in Europe? 43 2.3.2 Recommendations for Effective Climate Protection 45 2.4 A Difficult Birth – Politics and Climate Change 48 2.4.1 German Climate Policy 48 2.4.2 International Climate Policy 49 2.5 Self-Help Climate Protection 51 3 From Wasting Energy to Saving Energy and Reducing Carbon Dioxide 53 3.1 Inefficiency 53 3.2 Personal Energy Needs – Savings at Home 56 3.2.1 Domestic Electricity – Money Wasted 56 3.2.2 Heat – Surviving the Winter with Almost No Heating 60 3.2.3 Transport – Getting Somewhere Using Less Energy 64 3.3 Industry and Commerce – Everyone Else is to Blame 66 3.4 Your Personal Carbon Dioxide Balance 67 3.4.1 Emissions Caused Directly by One’s Own Activities 67 3.4.2 Indirect Emissions 68 3.4.3 Total Emissions 71 3.5 The Sale of Ecological Indulgences 71 4 ‘Energiewende’ (Energy Transition) – The Way to a Better Future? 75 4.1 Coal and Nuclear Power Plants – Crutch Instead of Bridge 75 4.1.1 Energy and Automotive Companies Have Bet on the Wrong Horse 76 4.1.2 Lignite – A Climate Killer Made in Germany 78 4.1.3 Carbon Dioxide Sequestration – Out of Sight, Out of Mind 81 4.1.4 Nuclear Power Comeback Was Not a Radiant Success 83 4.2 Efficiency and CHP – A Good Double for Starters 84 4.2.1 Combined Heat and Power – Using Fuel Twice 84 4.2.2 Saving Energy – Achieving More with Less 85 4.3 Renewables – Energy Without End 87 4.4 Germany Is Becoming Renewable 88 4.4.1 All Sectors Are Important 89 4.4.2 Energy Transition in the Heat Sector 90 4.4.3 Energy Transition in the Transport Sector 93 4.4.4 Energy Transition in the Electricity Sector 94 4.4.5 Reliable Supply Using Renewables 97 4.4.6 Decentralized Instead of Centralized – Fewer Power Lines 100 4.5 Not So Expensive – The Myth of Unaffordability 101 4.6 Energy Revolution Instead of Half-Hearted Energy Transition 103 4.6.1 German Energy Policy – In the Shadow of Corporations 103 4.6.2 Energy Transition in the Hands of the Citizens – A Revolution Is Imminent 104 5 Photovoltaics – Energy from Sand 107 5.1 Structure and Function 107 5.1.1 Electrons, Holes, and Space-Charge Regions 107 5.1.2 Efficiency, Characteristics, and MPP 109 5.2 Production of Solar Cells – From Sand to Cell 111 5.2.1 Silicon Solar Cells – Power from Sand 111 5.2.2 From Cell to Module 113 5.2.3 Thin-Film Solar Cells 114 5.3 PV Systems – Grids and Islands 115 5.3.1 Sun Islands 115 5.3.2 Sun in the Grid 118 5.3.3 More Solar Independence 121 5.4 Planning and Design 124 5.4.1 Designing Stand-Alone Systems 124 5.4.2 Designing Grid-Connected Systems 126 5.4.3 Planned Autonomy 130 5.5 Economics 131 5.5.1 What Does It Cost? 131 5.5.2 Funding Programmes 132 5.5.3 Avoiding VAT 134 5.6 Ecology 135 5.7 PV Markets 136 5.8 Outlook and Development Potential 137 6 Solar Thermal Systems – Year-Round Heating from the Sun 141 6.1 Structure and Functionality 142 6.2 Solar Collectors – Collecting the Sun 145 6.2.1 Swimming Pool Absorbers 145 6.2.2 Flat-Plate Collectors 145 6.2.3 Air-Based Collectors 146 6.2.4 Vacuum-Tube Collectors 147 6.3 Solar Thermal Systems 149 6.3.1 Hot Water from the Sun 149 6.3.2 Heating with the Sun 152 6.3.3 Solar Communities 154 6.3.4 Cooling with the Sun 155 6.3.5 Swimming with the Sun 156 6.3.6 Cooking with the Sun 157 6.4 Planning and Design 158 6.4.1 Solar Thermal Heating of Domestic HotWater 158 6.4.2 Solar Thermal Auxiliary Heating 161 6.5 Economics 163 6.5.1 When Does It Pay off? 163 6.5.2 Funding Programmes 163 6.6 Ecology 164 6.7 Solar Thermal Markets 165 6.8 Outlook and Development Potential 167 7 Solar Power Plants – Even More Power from the Sun 169 7.1 Focusing on the Sun 169 7.2 Solar Power Plants 171 7.2.1 Parabolic Trough Power Plants 171 7.2.2 Solar Tower Power Plants 175 7.2.3 Dish-Stirling Power Plants 177 7.2.4 Solar Chimney Power Plants 178 7.2.5 Concentrating Photovoltaic Power Plants 179 7.2.6 Solar Chemistry 179 7.3 Planning and Design 180 7.3.1 Concentrating Solar Thermal Power Plants 181 7.3.2 Solar Chimney Power Plants 182 7.3.3 Concentrating Photovoltaic Power Plants 182 7.4 Economics 182 7.5 Ecology 183 7.6 Solar Power Plant Markets 184 7.7 Outlook and Development Potential 185 8 Wind Power Systems – Electricity from Thin Air 189 8.1 Gone with the Wind –Where the Wind Comes From 190 8.2 Utilizing Wind 192 8.3 Wind Turbines and Windfarms 196 8.3.1 Wind Chargers 196 8.3.2 Large, Grid-Connected Wind Turbines 197 8.3.3 Small Wind Turbines 201 8.3.4 Windfarms 202 8.3.5 Offshore Windfarms 203 8.4 Planning and Design 206 8.5 Economics 208 8.6 Ecology 210 8.7 Wind Power Markets 212 8.8 Outlook and Development Potential 213 9 Hydropower Plants –Wet Electricity 215 9.1 Tapping into the Water Cycle 215 9.2 Water Turbines 217 9.3 Hydropower Plants 220 9.3.1 Run-of-River Hydropower Plants 220 9.3.2 Storage Power Plants 222 9.3.3 Pumped-storage Hydropower Plants 222 9.3.4 Tidal Power Plants 224 9.3.5 Wave Power Plants 225 9.3.6 Ocean Current Power Plants 226 9.4 Planning and Design 227 9.5 Economics 228 9.6 Ecology 228 9.7 Hydropower Markets 230 9.8 Outlook and Development Potential 231 10 Geothermal Energy – Power from the Deep 233 10.1 Tapping into the Earth’s Heat 233 10.2 Geothermal Heat and Power Plants 237 10.2.1 Geothermal Heat Plants 237 10.2.2 Geothermal Power Plants 238 10.2.3 Geothermal HDR Power Plants 240 10.3 Planning and Design 241 10.4 Economics 242 10.5 Ecology 242 10.6 Geothermal Markets 243 10.7 Outlook and Development Potential 244 11 Heat Pumps – From Cold to Hot 245 11.1 Heat Sources for Low-Temperature Heat 245 11.2 Operating Principle of Heat Pumps 247 11.2.1 Compression Heat Pumps 248 11.2.2 Absorption Heat Pumps and Adsorption Heat Pumps 249 11.3 Planning and Design 250 11.4 Economics 253 11.5 Ecology 254 11.6 Heat Pump Markets 257 11.7 Outlook and Development Potential 257 12 Biomass – Energy from Nature 259 12.1 Origins and Use of Biomass 260 12.2 Biomass Heating 263 12.2.1 Wood as a Fuel 263 12.2.2 Open Fires and Woodburning Stoves 266 12.2.3 Log Boilers 266 12.2.4 Wood Pellet Heating 268 12.3 Biomass Heat and Power Plants 269 12.4 Biofuels 271 12.4.1 Bio-oil 271 12.4.2 Biodiesel 272 12.4.3 Bioethanol 273 12.4.4 BtL Fuels 274 12.4.5 Biogas 275 12.5 Planning and Design 276 12.5.1 Log Boilers 276 12.5.2 Wood Pellet Heating 277 12.6 Economics 279 12.7 Ecology 280 12.7.1 Solid Fuels 281 12.7.2 Biofuels 282 12.8 Biomass Markets 282 12.9 Outlook and Development Potential 284 13 Renewable Gas and Fuel Cells 285 13.1 Hydrogen as an Energy Source 287 13.2 Methanation 289 13.3 Transport and Storage of Renewable Gas 290 13.3.1 Transport and Storage of Hydrogen 290 13.3.2 Transport and Storage of Renewable Methane 291 13.4 Fuel Cells: Bearers of Hope 293 13.5 Economics 296 13.6 Ecology 297 13.7 Markets, Outlook, and Development Potential 298 14 Sunny Prospects – Examples of Sustainable Energy Supply 301 14.1 Climate-Compatible Living 301 14.1.1 Carbon-Neutral Standard Prefabricated Houses 301 14.1.2 Plus-Energy Solar House 302 14.1.3 Plus-Energy Housing Estate 303 14.1.4 Heating Only with the Sun 304 14.1.5 Zero Heating Costs After Redevelopment 305 14.2 Working and Producing in a Climate-friendly Manner 306 14.2.1 Offices and Shops in the ‘Sonnenschiff’ 306 14.2.2 Zero-Emissions Factory 306 14.2.3 Carbon-free Heavy Equipment Factory 307 14.2.4 Plus-Energy Head Office 307 14.3 Climate-Compatible Driving 309 14.3.1 Travelling Around the World in a Solar Car 309 14.3.2 Across Australia in 33 hours 310 14.3.3 Emission-free Deliveries 311 14.3.4 Electric Cars for All 312 14.4 Climate-Compatible Travel by Water or Air 313 14.4.1 Advanced Sailing 313 14.4.2 Solar Ferry on Lake Constance 314 14.4.3 World Altitude Record with a Solar Aeroplane 314 14.4.4 Flying Around the World in a Solar Plane 315 14.4.5 Flying for Solar Kitchens 316 14.5 Everything Becomes Renewable 317 14.5.1 A Village Becomes Independent 317 14.5.2 Hybrid Power Plant for Secure Renewable Supply 318 14.6 Everything will Turn Out Fine 319 A Appendix 321 A.1 Energy Units and Prefixes 321 A.2 Geographic Coordinates of Power Plants 322 A.3 Further Reading 325 References 327 Index 331

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Book SynopsisHow 5G technology can support the demands of multiple vertical industries Recent advances in technologyhave created new vertical industries that are highly dependent on the availability and reliability of data between multiple locations. The 5G system, unlike previous generations, will be entirely data drivenaddressing latency, resilience, connection density, coverage area, and other vertical industry criteria.Enabling 5G Communication Systems to Support Vertical Industriesdemonstrates how 5G communication systems can meet the needs unique to vertical industries for efficient, cost-effective delivery of service. Covering both theory and practice, this book explores solutions to problems in specific industrial sectors including smart transportation, smart agriculture, smart grid, environmental monitoring, and disaster management. The 5G communication system will have to provide customized solutions to accommodate each vertical industry's specific requirements. Whether an industry practiTable of ContentsAbout the Editors xi List of Contributors xiii Preface xvii 1 Enabling the Verticals of 5G: Network Architecture, Design and Service Optimization 1Andy Sutton 1.1 Introduction 1 1.2 Use Cases 3 1.3 5G Network Architecture 4 1.4 RAN Functional Decomposition 7 1.5 Designing a 5G Network 9 1.6 Network Latency 11 1.7 5G Network Architecture Design 13 1.8 Summary 20 Acknowledgements 21 References 21 2 Industrial Wireless Sensor Networks and 5G Connected Industries 23Mohsin Raza, Sajjad Hussain, Nauman Aslam, Hoa Le-Minh and Huan X. Nguyen 2.1 Overview 23 2.2 Industrial Wireless Sensor Networks 24 2.2.1 Wired and Wireless Networks in Industrial Environment 24 2.2.2 Transformation of WSNs for Industrial Applications 24 2.2.3 IWSN Architecture 25 2.3 Industrial Traffic Types and its Critical Nature 28 2.3.1 Safety/Emergency Traffic 28 2.3.2 Critical Control Traffic 28 2.3.3 Low-Risk Control Traffic 28 2.3.4 Periodic Monitoring Traffic 28 2.3.5 Critical Nature and Time Deadlines 29 2.4 Existing Works and Standards 30 2.4.1 Wireless Technologies 30 2.4.2 Industry-Related IEEE Standards 31 2.4.2.1 IEEE 802.15.4 31 2.4.2.2 IEEE 802.15.4e 32 2.5 Ultra-Reliable Low-Latency Communications (URLLC) in IWSNS 33 2.6 Summary 37 References 37 3 Haptic Networking Supporting Vertical Industries 41Luis Sequeira, Konstantinos Antona koglou, Maliheh Mahlouji and Toktam Mahmoodi 3.1 Tactile Internet Use Cases and Requirements 41 3.1.1 Quality of Service 42 3.1.2 Use Cases and Requirements 43 3.2 Teleoperation Systems 45 3.2.1 Classification of Teleoperation Systems 45 3.2.2 Haptic Control and Data Reduction 46 3.2.2.1 Performance of Teleoperation Control Schemes 48 3.2.2.2 Haptic Data Reduction 59 3.2.2.3 Kinesthetic Data Reduction 59 3.2.2.4 Tactile Data Reduction 62 3.2.3 Combining Control Schemes and Data Reduction 63 Acknowledgment 64 References 64 4 5G-Enhanced Smart Grid Services 75Muhammad Ismail, Islam Safak Bayram, Khalid Qaraqe and Erchin Serpedin 4.1 Introduction 75 4.2 Smart Grid Services and Communication Requirements 78 4.2.1 Smart Grid Fundamentals 78 4.2.1.1 Data Collection and Management Services 78 4.2.1.2 Control and Operation Services 81 4.2.2 Communication Requirements for Smart Grid Services 87 4.3 Smart Grid Services Supported by 5G Networks 90 4.3.1 Data Collection and Management Services 90 4.3.1.1 Data Collection Services 91 4.3.1.2 Data Management Services 95 4.3.2 Operation Decision-Making Services 96 4.3.2.1 Demand Side Management Services 96 4.3.2.2 Electric Vehicle Charging and Discharging Services 98 4.4 Summary and Future Research 99 Acknowledgment 100 References 100 5 Evolution of Vehicular Communications within the Context of 5G Systems 103Kostas Katsaros and Mehrdad Dianati 5.1 Introduction 103 5.2 Vehicular Connectivity 104 5.2.1 Cellular V2X 105 5.2.1.1 Release 14 – First C-V2X Services 105 5.2.1.2 Release 15 – First Taste of 5G 108 5.2.1.3 Release 16 – Fully-Fledged 5G 108 5.2.2 Dedicated Short Range Communication (DSRC) 110 5.2.2.1 Co-Existence 110 5.2.3 Advanced Technologies 111 5.2.3.1 Multi-Access Edge Computing 111 5.2.3.2 Network Slicing 113 5.3 Data Dissemination 114 5.3.1 Context-Aware Middleware 114 5.3.2 Heterogeneity and Interoperability 116 5.3.3 Higher Layer Communication Protocols 118 5.4 Towards Connected Autonomous Driving 121 5.4.1 Phase 1 – Awareness Driving Applications 122 5.4.2 Phase 2 – Collective Perception 122 5.4.3 Phase 3/4 – Trajectory/Manoeuvre Sharing 123 5.4.4 Phase 5 – Full Autonomy 123 5.5 Conclusions 123 References 124 6 State-of-the-Art of Sparse Code Multiple Access for Connected Autonomous Vehicle Application 127Yi Lu, Chong Han, Carsten Maple, Mehrdad Dianati and Alex Mouzakitis 6.1 Introduction 127 6.2 Sparse Code Multiple Access 130 6.3 State-of-the-Art 134 6.3.1 Codebook Design 134 6.3.2 Decoding/Detecting Techniques for SCMA 137 6.3.3 Other Research on Performance Evaluation of SCMA 138 6.4 Conclusion and Future Work 140 References 145 7 5G Communication Systems and Connected Healthcare 149David Soldani and Matteo Innocenti 7.1 Introduction 149 7.2 Use Cases and Technical Requirements 151 7.2.1 Wireless Tele Surgery 151 7.2.2 Wireless Service Robots 151 7.3 5G communication System 154 7.3.1 3GPP Technology Roadmap 154 7.3.2 5G Spectrum 155 7.3.3 5G Reference Architecture 155 7.3.4 5G Security Aspects 161 7.3.5 5G Enabling Technologies 161 7.3.5.1 5G design for Low-Latency Transmission 162 7.3.5.2 5G design for Higher-Reliability Transmission 166 7.3.6 5G Deployment Scenarios 168 7.4 Value Chain, Business Model and Business Case Calculation 170 7.4.1 Market Uptake for Robotic Platforms 171 7.4.2 Business Model and Value Chain 171 7.4.3 Business case for Service Providers 171 7.4.3.1 Assumptions 172 7.4.3.2 Business Cases Calculation 172 7.5 Conclusions 174 References 175 8 5G: Disruption in Media and Entertainment 179Stamos Katsigiannis, Wasim Ahmad and Naeem Ramzan 8.1 Multi-Channel Wireless Audio Systems for Live Production 179 8.2 Video 181 8.2.1 Video Compression Algorithms 181 8.2.1.1 HEVC: High Efficiency Video Coding 181 8.2.1.2 VP9 182 8.2.1.3 AV1: AO Media Video 1 183 8.2.2 Streaming Protocols 183 8.2.2.1 Apple HTTP Live Streaming (HLS) 183 8.2.2.2 Dynamic Adaptive Streaming over HTTP (DASH) 184 8.2.3 Video Streaming Over Mobile Networks 184 8.3 Immersive Media 185 8.3.1 Virtual Reality (VR) 186 8.3.2 Augmented Reality (AR) 186 8.3.3 360-Degree Video 187 8.3.4 Immersive Media Streaming 188 References 189 9 Towards Realistic Modelling of Drone-based Cellular Network Coverage 191Haneya Naeem Qureshi and Ali Imran 9.1 Overview of Existing Models for Drone-Based Cellular Network Coverage 192 9.2 Key Objectives and Organization of this Chapter 193 9.3 Motivation 194 9.4 System Model 194 9.5 UAV Coverage Model Development 196 9.5.1 Coverage Probability 196 9.5.2 Received Signal Strength 198 9.6 Trade-Offs between Coverage Radius, Beamwidth and Height 199 9.6.1 Coverage Radius Versus Beamwidth 199 9.6.2 Coverage Radius Versus Height 200 9.6.3 Height Versus Beamwidth 201 9.7 Impact of Altitude, Beamwidth and Radius on RSS 201 9.8 Analysis for Different Frequencies and Environments 203 9.9 Comparison of Altitude and Beamwidth to Control Coverage 204 9.10 Coverage Probability with Varying Tilt Angles and Asymmetric Beamwidths 206 9.11 Coverage Analysis with Multiple UAVs 207 9.12 Conclusion 211 Acknowledgment 211 References 211 Appendix A 213 10 Intelligent Positioning of UAVs for Future Cellular Networks 217João Pedro Battistella Nadas, Paulo Valente Klaine, Rafaela de Paula Parisotto and Richard D. Souza 10.1 Introduction 217 10.2 Applications of UAVs in Cellular Networks 218 10.2.1 Coverage in Rural Areas 218 10.2.2 Communication for Internet of Things 218 10.2.3 Flying Fronthaul /Backhaul 219 10.2.4 Aerial Edge Caching 219 10.2.5 Pop-Up Networks 219 10.2.6 Emergency Communication Networks 220 10.3 Strategies for Positioning UAVs in Cellular Network 221 10.4 Reinforcement Learning 222 10.4.1 Q-Learning 222 10.5 Simulations 223 10.5.1 Urban Model 223 10.5.2 The UAVs 224 10.5.3 Path loss 225 10.5.4 Simulation Scenario 225 10.5.5 Proposed RL Implementation 226 10.5.5.1 Simulation Results 228 10.6 Conclusion 229 References 230 11 Integrating Public Safety Networks to 5G: Applications and Standards 233Usman Raza, Muhammad Usman, Muhammad Rizwan Asghar, Imran Shafique Ansari and Fabrizio Granelli 11.1 Introduction 233 11.2 Public Safety Scenarios 235 11.2.1 In-Coverage Scenario 235 11.2.2 Out-of-Coverage Scenario 236 11.2.3 Partial-Coverage Scenario 236 11.3 Standardization Efforts 236 11.3.1 3rd Generation Partnership Project 237 11.3.1.1 Release 8 237 11.3.1.2 Release 9 237 11.3.1.3 Release 10 238 11.3.1.4 Release 11 238 11.3.1.5 Release 12 238 11.3.1.6 Release 13 240 11.3.1.7 Release 14 241 11.3.1.8 Release 15 241 11.3.2 Open Mobile Alliance 242 11.3.2.1 PTT over Cellular 242 11.3.2.2 Push to Communicate for Public Safety (PCPS) 242 11.3.3 Alliance for Telecommunication Industry Solutions 242 11.3.3.1 Energy and Utility Sector 243 11.3.3.2 Building Alarm Systems 243 11.3.3.3 PS Communications with Emergency Centers 243 11.3.3.4 Smart City Solutions 243 11.3.4 APCO Global Alliance 244 11.3.5 Groupe Speciale Mobile Association (GSMA) 244 11.4 Future Challenges and Enabling Technologies 245 11.4.1 Future challenges 246 11.4.1.1 Connectivity 246 11.4.1.2 Interoperability 246 11.4.1.3 Resource Scarceness 247 11.4.1.4 Security 247 11.4.1.5 Big Data 247 11.4.2 Enabling Technologies 248 11.4.2.1 Software-Defined Networking 248 11.4.2.2 Cognitive Radio Networks 248 11.4.2.3 Non-orthogonal Multiple Access 248 11.5 Conclusion 248 References 249 12 Future Perspectives 253Muhammad Ali Imran, Yusuf Abdulrahman Sambo and Qammer H. Abbasi 12.1 Enabling Rural Connectivity 253 12.2 Key Technologies for the Design of beyond 5G Networks 254 12.2.1 Blockchain 254 12.2.2 Terahertz Communication 255 12.2.3 LiFi 255 12.2.4 Wireless Power Transfer and Energy Harvesting 256 Index 257

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Book SynopsisThe comprehensive and authoritative guide to power electronics in renewable energy systems Power electronics plays a significant role in modern industrial automation and high- efficiency energy systems. With contributions from an international group of noted experts,Power Electronics in Renewable Energy Systems and Smart Grid: Technology and Applicationsoffers a comprehensive review of the technology and applications of power electronics in renewable energy systems and smart grids. The authors cover information on a variety of energy systems including wind, solar, ocean, and geothermal energy systems as well as fuel cell systems and bulk energy storage systems. They also examine smart grid elements, modeling, simulation, control, and AI applications. The book''s twelve chapters offer an application-oriented and tutorial viewpoint and also contain technology status review. In addition, the book contains illustrative examples of applications and discussionsTable of ContentsPreface xiii About the editor xix About the contributors xxi List of abbreviations xxxiii Chapter 1 Energy, Environment, Power Electronics, Renewable Energy Systems, and Smart Grid 1Bimal K. Bose and Fei (Fred) Wang 1.1 Introduction 1 1.2 Energy 1 1.3 Environment 4 1.3.1 Environmental Pollution by Fossil Fuels 4 1.3.2 Climate Change or Global Warming Problems 7 1.3.3 Several Beneficial Effects of Climate Change 11 1.3.4 The Kyoto Protocol and Carbon Emission Control 12 1.3.5 How Can We Solve or Mitigate Climate Change Problems? 13 1.4 Power Electronics 14 1.4.1 The Role of Power Electronics in Renewable Energy Systems and Grids 14 1.4.2 Fundamentals of Power Electronics 16 1.4.3 Power Electronics Applications 35 1.5 Renewable Energy Systems 48 1.5.1 Wind Energy Systems 50 1.5.2 PV Systems 52 1.5.3 Grid Energy Storage 53 1.6 Smart Grid 54 1.6.1 FACTS Technologies 54 1.6.2 HVDC Technologies 60 1.6.3 DC Grid and Supergrid 66 1.6.4 Power Electronics for Distribution Grids 73 1.7 Summary and Future Trends 76 Acknowledgments 78 References 78 Chapter 2 Power Semiconductor Devices for Smart Grid and Renewable Energy Systems 85Alex Q. Huang 2.1 Introduction 85 2.2 Power Semiconductor Device Operation in Power Converters 87 2.2.1 Commercially Available Power Semiconductor Devices 87 2.2.2 Modern Power Semiconductor Device Characteristics 90 2.3 State‐of‐the‐Art Power Semiconductors: A Comparison 101 2.3.1 Voltage Rating 102 2.3.2 Current Rating 103 2.3.3 Switching Frequency 108 2.3.4 Maximum Junction Temperature 114 2.4 Recent Innovations in SI Power Devices 117 2.4.1 Silicon Superjunction (SJ) MOSFET 117 2.4.2 Thin Wafer Field Stop IGBT (FS‐IGBT) 119 2.4.3 Reverse Conducting IGBT (RC‐IGBT) 123 2.4.4 Reverse Blocking IGBT 124 2.4.5 Integrated‐Gate‐Commutated Thyristor (IGCT) 124 2.5 Recent Innovations in WBG Power Devices 127 2.5.1 SiC and GaN Diodes 128 2.5.2 SiC MOSFET 131 2.5.3 Ultra High‐Voltage SiC Power Devices 135 2.5.4 GaN Heterojunction Field Effect Transistor 137 2.6 Smart Grid and Renewable Energy System Applications 138 2.7 Conclusions 144 References 144 Chapter 3 Multilevel Converters – Configuration of Circuits and Systems 153Hirofumi Akagi 3.1 Introduction 153 3.1.1 Historical Review of Multilevel Converters 153 3.1.2 Overview of Chapter 3 155 3.2 Multilevel NPC and NPP Inverters 155 3.2.1 Circuits of Three‐Level NPC and NPP Inverters 155 3.2.2 Principles of the Three‐Level NPC and NPP Inverters 156 3.2.3 Comparisons Between the Three‐Level NPC and NPP Inverters 158 3.2.4 Five‐Level NPC Inverters 160 3.3 Multilevel FLC Inverters and Hybrid FLC Inverters 161 3.3.1 Circuits of the Three‐Level and Four‐Level FLC Inverters 161 3.3.2 Principles of the Three‐Level FLC Inverter 162 3.3.3 Hybrid Four‐Level and Five‐Level FLC Inverters 162 3.4 Modular Multilevel Cascade Converters 164 3.4.1 Terminological Issue and Solution 164 3.4.2 Circuits and Individualities of Six Family Members 167 3.4.3 Topological Discussion on the DSBC and DSCC Converters 168 3.4.4 Comparisons among the Six MMCC Family Members 169 3.4.5 Circulating Current 170 3.5 Practical Applications of SSBC Inverters to Medium‐Voltage Motor Drives 171 3.6 Hierarchical Control of an SSBC‐Based STATCOM 173 3.6.1 Background and Motivation 173 3.6.2 Hierarchical Control 174 3.7 A Downscaled SSBC‐Based STATCOM With Phase‐Shifted‐Carrier PWM 176 3.7.1 System Configuration 177 3.7.2 Control Technique 179 3.7.3 Experimental Waveforms 181 3.8 Circulating Currents in DSCC Converters 183 3.8.1 Circulating Current in a Cycloconverter 184 3.8.2 Circulating Current in a Single‐Leg DSCC Inverter 185 3.8.3 Similarity and Difference in Circulating Current 186 3.9 A Downscaled DSCC‐Based BTB System 187 3.9.1 Circuit Configuration 187 3.9.2 Operating Performance under Transient States 189 3.10 Practical Applications of DSCC Converters to Grid Connections 192 3.11 Applications of DSCC and TSBC Converters to Motor Drives 193 3.11.1 DSCC‐based Motor Drive Systems 193 3.11.2 Experimental Motor Drives Using a DSCC Inverter and a TSBC Converter 195 3.11.3 Comparisons in Start‐up Performance when the 50 Hz Induction Motor was Driven 198 3.11.4 Operation of the DSCC‐Driven 50 Hz Motor and the TSBC‐Driven 38 Hz Motor at the Rated Frequency and Torque 202 3.11.5 Four‐Quadrant Operation of the TSBC‐driven 38 Hz Motor at No Load Torque 204 3.11.6 Discussion of the Two Motor Drives 204 3.12 Distributed Dynamic Braking of a DSCC‐FED Induction Motor Drive 204 3.12.1 Background and Motivation 206 3.12.2 Circuit and System Configurations 206 3.12.3 Experimental Verification 210 3.13 Practical Applications of DSCC Inverters to Medium‐Voltage Motor Drives 212 3.14 Future Scenarios and Conclusion 213 References 214 Chapter 4 Multilevel Converters – Control and Operation in Industrial Systems 219Jose I. Leon, Sergio Vazquez and Leopoldo G. Franquelo 4.1 Introduction 219 4.2 Summary of Multilevel Converter Topologies 221 4.3 Control Structure of Multilevel Power Converters 223 4.3.1 The Outer Control Loop (Stage 1) 225 4.3.2 The Inner Control Loop (Stage 2) 225 4.3.3 The Zero‐Sequence Injection (Stage 3) 226 4.3.4 The In‐phase Balancing Strategy (Stage 3) 227 4.4 Modulation Methods for Multilevel Power Converters (Stage 4) 227 4.4.1 Carrier‐Based Modulation Techniques 228 4.4.2 Space‐vector Based Modulation Methods 242 4.4.3 Pseudo‐Modulation Techniques and Control Methods with Implicit Modulator 243 4.5 Applications of Multilevel Power Converters 245 4.5.1 Grid‐connected Multilevel Converters for the Integration of Renewable Energy Sources 245 4.5.2 Power Quality Applications 248 4.5.3 Motor Drive Applications 250 4.5.4 HVDC Transmission Systems 251 4.6 Additional Practical Challenges of Multilevel Converters 257 4.7 Future Perspective of Multilevel Converters and Conclusions 258 References 259 Chapter 5 Flexible Transmission and Resilient Distribution Systems Enabled by Power Electronics 271Fang Z. Peng and Jin Wang 5.1 Introduction 271 5.2 FACTS Configurations in the Smart Grid 279 5.2.1 Shunt Compensation 281 5.2.2 Series Compensation 284 5.2.3 Shunt‐Series Configuration 285 5.2.4 Back‐to‐Back Configuration 286 5.3 RACDS Configurations in the Smart Grid 287 5.3.1 RACDS: Microgrids 287 5.3.2 RACDS: Controllable Distribution Network 289 5.3.3 RACDS: Meshed Distribution Systems 290 5.4 Evolution of FACTS and RACDS 291 5.4.1 Traditional FACTS and RACDS 291 5.4.2 Modern FACTS and RACDS 293 5.5 FACTS and RACDS Installations 298 5.5.1 Traditional FACTS Installations 298 5.5.2 Modern FACTS Installations 299 5.5.3 RACDS Installations 301 5.6 Future Perspectives 301 5.6.1 Transformerless Unified Power Flow Controller 301 5.6.2 Compact Dynamic Phase‐Angle Regulator 303 5.6.3 Distributed FACTS 303 5.6.4 Power Regulator for Parallel Feeders 305 5.6.5 High Power Density CMIs 307 5.7 Conclusion 309 Acknowledgments 310 References 310 Chapter 6 Renewable Energy Systems with Wind Power 315Frede Blaabjerg and Ke Ma 6.1 Overview of Wind Power Generation and Power Electronics 315 6.2 Technology Challenges and Driving Forces in this Field 318 6.2.1 Low Levelized Cost of Energy (LCOE) 318 6.2.2 Complex Mission Profiles 320 6.2.3 Strict Grid Codes 322 6.2.4 Increasing Reliability Requirements 325 6.3 Wind Turbine Concepts and Power Electronics Converters 326 6.3.1 Wind Turbine Concepts 326 6.3.2 Power Electronics Converters in Wind Power Applications 328 6.4 Control of Wind Turbine Systems 333 6.5 Power Electronics for Multiple Wind Turbines and Wind Farms 336 6.6 Conclusion 340 References 341 Chapter 7 Photovoltaic Energy Systems 347Mariusz Malinowski, Jose I. Leon and Haitham Abu‐Rub 7.1 Introduction 347 7.2 Thermal and PV Solar Energy Systems 351 7.3 The Solar Cell 354 7.4 Solar PV System Costs 357 7.4.1 Incentives for More Investments in PV Systems 361 7.5 General Scheme for a Solar PV System 362 7.6 Grid‐Connected PV Systems 363 7.6.1 Utility‐scale PV Power Plants 364 7.6.2 Residential and Industrial PV Applications 366 7.6.3 Low‐power PV Systems 371 7.7 Control of Grid‐Connected PV Systems 372 7.8 Stand‐Alone PV Systems 374 7.9 Energy Storage Systems for PV Applications 379 7.10 Operational Issues for PV Systems 381 7.11 Conclusions 385 References 386 Chapter 8 Ocean and Geothermal Renewable Energy Systems 391Annette von Jouanne and Ted K.A. Brekken 8.1 Introduction 391 8.2 Wave Energy 392 8.2.1 Resource Characteristics 392 8.2.2 Wave Energy Conversion Technologies and Resource Characterization 394 8.2.3 Power Electronics and Control 397 8.2.4 Autonomous Applications 401 8.2.5 Cost 403 8.2.6 Rotating Machines in Marine Energy Converters 405 8.2.7 Unique Testing Opportunity for Wave Energy Converters 406 8.3 Ocean Thermal Energy Conversion 411 8.3.1 Resource Characteristics 412 8.3.2 OTEC Technologies 413 8.3.3 Open‐cycle OTEC 414 8.3.4 Closed‐cycle OTEC 415 8.3.5 OTEC Generator Grid Interface 415 8.3.6 Cost 416 8.4 Tidal and Ocean Currents 417 8.4.1 Resource Characteristics 418 8.4.2 Tidal Barrage, Tidal Current, and Ocean Current Technologies 420 8.4.3 Power Electronics and Grid Interface 422 8.4.4 Cost 425 8.5 Geothermal Energy Systems 426 8.5.1 Resource Characteristics 428 8.5.2 Geothermal Power Plant Technologies 429 8.5.3 Dry Steam 431 8.5.4 Flash Steam 431 8.5.5 Binary Cycle 432 8.5.6 Geothermal Generator Grid Interface 432 8.5.7 Cost 433 8.6 Conclusion 434 Acknowledgment 435 References 435 Chapter 9 Fuel Cells and Their Applications in Energy Systems 443Jih‐Sheng (Jason) Lai and Michael W. Ellis 9.1 Introduction 443 9.2 Different Fuel Cell Technologies 446 9.2.1 Low‐temperature Fuel Cells 447 9.2.2 High‐temperature Fuel Cells 453 9.3 Fuel Cell Applications 457 9.3.1 Transportation Applications 457 9.3.2 Stationary Power Generation Applications 460 9.4 Electrical Characteristics 462 9.4.1 Steady‐state Operation 462 9.4.2 Dynamic Operation 465 9.4.3 Dynamic Operation with a Paralleled Ultracapacitor 468 9.5 Fuel Cell Power System Architecture 468 9.5.1 Balance‐of‐Plant 468 9.5.2 Fuel Cell DC Power Systems 469 9.5.3 Grounding Requirement for Fuel Cell AC Power Systems 471 9.6 Power Electronics for Fuel Cell Applications 472 9.6.1 DC‐DC Converters 472 9.6.2 DC‐AC Inverter 479 9.6.3 Double‐Line Frequency Issues 484 9.7 Summary 485 References 486 Chapter 10 Grid Energy Storage Systems 495Marcelo G. Molina 10.1 Introduction 495 10.2 Smart Grid Applications of Energy Storage 500 10.3 Energy Storage Technologies 506 10.3.1 Mechanical Energy Storage 507 10.3.2 Electrical Energy Storage 518 10.3.3 Electrochemical Energy Storage 529 10.3.4 Chemical Energy Storage 547 10.3.5 Thermal Energy Storage 552 10.4 Assessment of Energy Storage Technologies 555 10.5 Power Conditioning System for Interfacing Energy Storage Technologies with the Smart Grid 565 10.6 Conclusion 572 References 574 Chapter 11 Smart Grid Simulations and Control 585Aranya Chakrabortty and Anjan Bose 11.1 Introduction 585 11.2 Simulation Models 586 11.2.1 Synchronous Generators 588 11.2.2 Models of Renewable Energy Sources 589 11.2.3 Transmission Line Models 591 11.2.4 Load Models 591 11.3 Current Approach for Smart Grid Simulation 592 11.3.1 Power Flow Analysis 592 11.3.2 Dynamic Simulations 593 11.3.3 Economic Dispatch and OPF 593 11.3.4 Fault Analysis 594 11.3.5 Load Frequency Control 594 11.3.6 Operator Training Simulator 594 11.3.7 Reliability Modeling and Simulation 594 11.3.8 Simulation of Power Markets 595 11.4 Challenges for Grid Simulation 595 11.4.1 Structural Properties 596 11.4.2 Scalability 596 11.4.3 Model Validation 596 11.4.4 Model Aggregation 597 11.4.5 Role of Power Electronics 597 11.4.6 Co‐simulation of T&D Models 598 11.4.7 Co‐Simulation of Infrastructures 599 11.4.8 Cyber‐Physical Modeling and Simulations 601 11.5 Next‐Generation Grid Control Systems 605 11.5.1 Wide‐area Control 605 11.5.2 Cyber‐Physical Challenges for Wide‐area Control 608 11.5.3 Scheduling Protocols 612 11.5.4 Co‐designing Wide‐area Control in Tandem with Communication Protocols 613 11.5.5 Plug‐and‐play Control of DERs 615 11.5.6 Distributed Load Frequency Control 616 11.5.7 Inner‐loop + Outer‐loop Hierarchical Control 617 11.6 Experimental Testbeds for Simulations and Control 618 11.7 Conclusions 619 References 620 Chapter 12 Artificial Intelligence Applications in Renewable Energy Systems and Smart Grid – Some Novel Applications 625Bimal K. Bose 12.1 Introduction 625 12.2 Expert Systems 627 12.2.1 Expert System Principles 627 12.2.2 Expert System‐Based Control of Smart Grid 631 12.3 Fuzzy Logic 636 12.3.1 Fuzzy Inference System Principles 637 12.3.2 Fuzzy Logic Control of a Modern Wind Generation System 644 12.4 Neural Networks 650 12.4.1 Neural Network Principles 650 12.4.2 Neural Network Applications 662 12.5 Conclusion 672 Acknowledgment 673 References 673 Index 677

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Book SynopsisThe definitive leadership guide on safe practices The release of chemicals and other hazardous materials pose significant, potentially catastrophic threats worldwide. An alarming number of such events, all of which are preventable, occur too often. Reducing the frequency of serious incidents is a fundamental responsibility of leadership at all levels, from frontline managers and supervisors to C-suite executives and the board of directors as well.Process Safety Leadership from the Boardroom to the Frontlineis a practical, authoritative guide that clearly demonstrates how to create a viable culture of safety within an organization, implement and maintain disciplined management systems, and address the risks of process safety deficiencies. The most important factor in any management system is leadership. For chemical process safety management, effective and informed leadership provides direction, reinforces commitment, and drives responsibility. Written by experts from the Center for Table of ContentsAcronyms and Abbreviations xi Acknowledgements xiii Nomenclature and Style xv Preface xvii Executive Summary xix How to Use this Book xxv 1 The Business Case for Process Safety 1 1.1 Corporate Social Responsibility 2 1.2 Business Flexibility 4 1.3 Loss Prevention 5 1.4 Sustainable Growth 7 1.5 Leadership Excellence 9 1.6 Summary 9 1.7 References 10 1.8 Incidents Represented in Figure 1.2 12 2 Leading and Managing Process Safety 13 2.1 Process Safety Definition 13 2.2 How Process Safety Works: Risk Reduction and Risk Management to Eliminate Accidents 22 2.3 Learning from Incidents 25 2.4 Personal Leadership Accountability 30 2.5 Downturns and Boom Times: Special Process Safety Leadership Challenges 34 2.6 Compliance: Required but not Enough 39 2.7 Management Systems: Helpful but not Sufficient 43 2.8 References 44 3 Leadership Attributes 47 3.1 Creating a Shared Vision 48 3.1.1 Establish the Imperative for Process Safety 48 3.1.2 Reflect the Imperative in Your Words and Actions 51 3.1.3 Drive the Imperative Throughout the Organization 54 3.1.4 Earn the Social License to Operate 57 3.2 Develop and Maintain Knowledge and Competence 60 3.2.1 Personal Knowledge and Competence 60 3.2.2 Develop and Empower Others 64 3.3 Show Integrity and Commitment 71 3.3.1 Courage and Conviction 71 3.3.2 Accountability 73 3.3.3 Responsiveness 76 3.3.4 Consistency 78 3.4 Communicate with Inspiration 80 3.4.1 Stay Connected and Visible 80 3.4.2 Influence and Drive Process Safety Culture 83 3.5 References 91 4 Leadership of the Process Safety Management System 93 4.1 Identify Required Barriers 94 4.1.1 Start with Risk Criteria and a Risk Matrix 95 4.1.2 Analyze Hazards and Risks 98 4.1.3 Identify Required Barriers 101 4.2 Manage Barriers 102 4.2.1 Conduct of Operations and Operational Discipline 102 4.2.2 Standards 110 4.2.3 Asset Integrity and Mechanical Integrity 113 4.2.4 Operating Procedures and Safe Work Practices 116 4.2.5 Management of Change 118 4.2.6 Emergency Management – Preparation and Response 123 4.3 Manage Competency (Organizational Capability) 127 4.3.1 Competency 128 4.3.2 Effective Training 130 4.3.3 Process Knowledge Management 133 4.3.4 Contractor Management 135 4.4 Verify Performance and Improve 139 4.4.1 Audits 139 4.4.2 Metrics 141 4.4.3 Incident Investigation and Resulting Actions 143 4.4.4 Management Review and Continual Improvement 146 4.5 Build and Strengthen Culture 151 4.5.1 Introduction to Culture 151 4.5.2 Workforce Involvement 152 4.5.3 Stakeholder Outreach 155 4.6 Summary 158 4.7 References 159 5 Leadership Roles and Accountabilities 161 Table 5.1 Executive Leadership Role 164 Table 5.2 Operations Leadership Role 166 Table 5.3 Engineering Leadership Role 168 Table 5.4 EH & S Leadership Role 170 Table 5.5 Research and Development (R & D) Leadership Role 172 Table 5.6 Purchasing Leadership Role 174 Table 5.7 Human Resources Leadership Role 176 Table 5.8 Plant Superintendent Role 178 Table 5.9 Maintenance Leadership Role 180 Table 5.10 Plant Engineer Role 182 Table 5.11 Plant Operator Role 184 Table 5.12 Maintenance Technician Role 187 Table 5.13 Process Safety Specialist Role 189 6 Deploying Process Safety Leadership Accountability and Responsibility 191 Table 6.1 Corporate Process Safety Leadership Team RACI Matrix 193 Table 6.2 Operations Leadership Team RACI Matrix 197 7 Make it Happen 201 7.1 References 207 Index 209

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Book SynopsisBuild your knowledge of SAR/ISAR imaging with this comprehensive and insightful resource The newly revised Second Edition of Inverse Synthetic Aperture Radar Imaging with MATLAB Algorithms covers in greater detail the fundamental and advanced topics necessary for a complete understanding of inverse synthetic aperture radar (ISAR) imaging and its concepts. Distinguished author and academician, Caner Özdemir, describes the practical aspects of ISAR imaging and presents illustrative examples of the radar signal processing algorithms used for ISAR imaging. The topics in each chapter are supplemented with MATLAB codes to assist readers in better understanding each of the principles discussed within the book. This new edition incudes discussions of the most up-to-date topics to arise in the field of ISAR imaging and ISAR hardware design. The book provides a comprehensive analysis of advanced techniques like Fourier-based radar imaging algorithms, and motion comTable of ContentsPreface to the Second Edition xvi Acknowledgments xix Acronyms xx 1 Basics of Fourier Analysis 1 1.1 Forward and Inverse Fourier Transform 1 1.1.1 Brief History of FT 1 1.1.2 Forward FT Operation 2 1.1.3 IFT 3 1.2 FT Rules and Pairs 3 1.2.1 Linearity 3 1.2.2 Time Shifting 3 1.2.3 Frequency Shifting 4 1.2.4 Scaling 4 1.2.5 Duality 4 1.2.6 Time Reversal 4 1.2.7 Conjugation 4 1.2.8 Multiplication 4 1.2.9 Convolution 5 1.2.10 Modulation 5 1.2.11 Derivation and Integration 5 1.2.12 Parseval’s Relationship 5 1.3 Time-Frequency Representation of a Signal 5 1.3.1 Signal in the Time Domain 6 1.3.2 Signal in the Frequency Domain 6 1.3.3 Signal in the Joint Time-Frequency (JTF) Plane 7 1.4 Convolution and Multiplication Using FT 11 1.5 Filtering/Windowing 12 1.6 Data Sampling 14 1.7 DFT and FFT 16 1.7.1 DFT 16 1.7.2 FFT 17 1.7.3 Bandwidth and Resolutions 17 1.8 Aliasing 19 1.9 Importance of FT in Radar Imaging 19 1.10 Effect of Aliasing in Radar Imaging 23 1.11 Matlab Codes 26 References 33 2 Radar Fundamentals 35 2.1 Electromagnetic Scattering 35 2.2 Scattering from PECs 38 2.3 Radar Cross Section 39 2.3.1 Definition of RCS 40 2.3.2 RCS of Simple-Shaped Objects 43 2.3.3 RCS of Complex-Shaped Objects 44 2.4 Radar Range Equation 44 2.4.1 Bistatic Case 46 2.4.2 Monostatic Case 49 2.5 Range of Radar Detection 50 2.5.1 Signal-to-Noise Ratio 51 2.6 Radar Waveforms 53 2.6.1 Continuous Wave 53 2.6.2 Frequency-Modulated Continuous Wave 56 2.6.3 Stepped-Frequency Continuous Wave 59 2.6.4 Short Pulse 61 2.6.5 Chirp (LFM) Pulse 62 2.7 Pulsed Radar 69 2.7.1 Pulse Repetition Frequency 69 2.7.2 Maximum Range and Range Ambiguity 69 2.7.3 Doppler Frequency 70 2.8 Matlab Codes 74 References 82 3 Synthetic Aperture Radar 85 3.1 SAR Modes 86 3.2 SAR System Design 87 3.3 Resolutions in SAR 88 3.4 SAR Image Formation 91 3.5 Range Compression 92 3.5.1 Matched Filter 92 3.5.1.1 Computing Matched Filter Output via Fourier Processing 95 3.5.1.2 Example for Matched Filtering 96 3.5.2 Ambiguity Function 99 3.5.2.1 Relation to Matched Filter 100 3.5.2.2 Ideal Ambiguity Function 101 3.5.2.3 Rectangular-Pulse Ambiguity Function 102 3.5.2.4 LFM-Pulse Ambiguity Function 102 3.5.3 Pulse Compression 105 3.5.3.1 Detailed Processing of Pulse Compression 105 3.5.3.2 Bandwidth, Resolution, and Compression Issues for LFM Signal 109 3.5.3.3 Pulse Compression Example 110 3.6 Azimuth Compression 110 3.6.1 Processing in Azimuth 110 3.6.2 Azimuth Resolution 116 3.6.3 Relation to ISAR 117 3.7 SAR Imaging 118 3.8 SAR Focusing Algorithms 118 3.8.1 RDA 119 3.8.1.1 Range Compression in RDA 120 3.8.1.2 Azimuth Fourier Transform 126 3.8.1.3 Range Cell Migration Correction 128 3.8.1.4 Azimuth Compression 129 3.8.1.5 Simulated SAR Imaging Example 130 3.8.1.6 Drawbacks of RDA 133 3.8.2 Chirp Scaling Algorithm 133 3.8.3 The ω-kA 133 3.8.4 Back-Projection Algorithm 134 3.9 Example of a Real SAR Imagery 135 3.10 Problems in SAR Imaging 136 3.10.1 Range Migration and Range Walk 136 3.10.2 Motion Errors 137 3.10.3 Speckle Noise 140 3.11 Advanced Topics in SAR 140 3.11.1 SAR Interferometry 140 3.11.2 SAR Polarimetry 142 3.12 Matlab Codes 143 References 158 4 Inverse Synthetic Aperture Radar Imaging and Its Basic Concepts 162 4.1 SAR versus ISAR 162 4.2 The Relation of Scattered Field to the Image Function in ISAR 166 4.3 One-Dimensional (1D) Range Profile 167 4.4 1D Cross-Range Profile 172 4.5 Two-Dimensional (2D) ISAR Image Formation (Small Bandwidth, Small Angle) 176 4.5.1 Resolutions in ISAR 180 4.5.1.1 Range Resolution 181 4.5.1.2 Cross-Range Resolution: 181 4.5.2 Range and Cross-Range Extends 181 4.5.3 Imaging Multibounces in ISAR 182 4.5.4 Sample Design Procedure for ISAR 185 4.5.4.1 ISAR Design Example #1: “Aircraft Target” 189 4.5.4.2 ISAR Design Example #2: “Military Tank Target” 193 4.6 2D ISAR Image Formation (Wide Bandwidth, Large Angles) 197 4.6.1 Direct Integration 198 4.6.2 Polar Reformatting 201 4.7 3D ISAR Image Formation 205 4.7.1 Range and Cross-Range resolutions 209 4.7.2 A Design Example for 3D ISAR 210 4.8 Matlab Codes 217 References 243 5 Imaging Issues in Inverse Synthetic Aperture Radar 246 5.1 Fourier-Related Issues 246 5.1.1 DFT Revisited 246 5.1.2 Positive and Negative Frequencies in DFT 250 5.2 Image Aliasing 252 5.3 Polar Reformatting Revisited 255 5.3.1 Nearest Neighbor Interpolation 255 5.3.2 Bilinear Interpolation 258 5.4 Zero Padding 260 5.5 Point Spread Function 264 5.6 Windowing 269 5.6.1 Common Windowing Functions 269 5.6.1.1 Rectangular Window 269 5.6.1.2 Triangular Window 269 5.6.1.3 Hanning Window 272 5.6.1.4 Hamming Window 272 5.6.1.5 Kaiser Window 272 5.6.1.6 Blackman Window 276 5.6.1.7 Chebyshev Window 277 5.6.2 ISAR Image Smoothing via Windowing 277 5.7 Matlab Codes 280 References 304 6 Range-Doppler Inverse Synthetic Aperture Radar Processing 306 6.1 Scenarios for ISAR 306 6.1.1 Imaging Aerial Targets via Ground-Based Radar 307 6.1.2 Imaging Ground/Sea Targets via Aerial Radar 309 6.2 ISAR Waveforms for Range-Doppler Processing 312 6.2.1 Chirp Pulse Train 312 6.2.2 Stepped Frequency Pulse Train 314 6.3 Doppler Shift’s Relation to Cross-Range 316 6.3.1 Doppler Frequency Shift Resolution 317 6.3.2 Resolving Doppler Shift and Cross-Range 318 6.4 Forming the Range-Doppler Image 319 6.5 ISAR Receiver 320 6.5.1 ISAR Receiver for Chirp Pulse Radar 320 6.5.2 ISAR Receiver for SFCW Radar 321 6.6 Quadrature Detection 323 6.6.1 I-Channel Processing 324 6.6.2 Q-Channel Processing 324 6.7 Range Alignment 326 6.8 Defining the Range-Doppler ISAR Imaging Parameters 327 6.8.1 Image Frame Dimension (Image Extends) 327 6.8.2 Range and Cross-Range Resolution 328 6.8.3 Frequency Bandwidth and the Center Frequency 328 6.8.4 Doppler Frequency Bandwidth 328 6.8.5 Pulse Repetition Frequency 329 6.8.6 Coherent Integration (Dwell) Time 329 6.8.7 Pulse Width 330 6.9 Example of Chirp Pulse-Based Range-Doppler ISAR Imaging 331 6.10 Example of SFCW-Based Range-Doppler ISAR Imaging 336 6.11 Matlab Codes 339 References 347 7 Scattering Center Representation of Inverse Synthetic Aperture Radar 349 7.1 Scattering/Radiation Center Model 350 7.2 Extraction of Scattering Centers 352 7.2.1 Image Domain Formulation 352 7.2.1.1 Extraction in the Image Domain: The “CLEAN” Algorithm 352 7.2.1.2 Reconstruction in the Image Domain 355 7.2.2 Fourier Domain Formulation 362 7.2.2.1 Extraction in the Fourier Domain 362 7.2.2.2 Reconstruction in the Fourier Domain 364 7.3 Matlab Codes 368 References 382 8 Motion Compensation for Inverse Synthetic Aperture Radar 385 8.1 Doppler Effect Due to Target Motion 386 8.2 Standard MOCOMP Procedures 388 8.2.1 Translational MOCOMP 389 8.2.1.1 Range Tracking 389 8.2.1.2 Doppler Tracking 390 8.2.2 Rotational MOCOMP 390 8.3 Popular ISAR MOCOMP Techniques 392 8.3.1 Cross-Correlation Method 392 8.3.1.1 Example for the Cross-Correlation Method 394 8.3.2 Minimum Entropy Method 398 8.3.2.1 Definition of Entropy in ISAR Images 398 8.3.2.2 Example for the Minimum Entropy Method 399 8.3.3 JTF-Based MOCOMP 402 8.3.3.1 Received Signal from a Moving Target 403 8.3.3.2 An Algorithm for JTF-Based Rotational MOCOMP 404 8.3.3.3 Example for JTF-Based Rotational MOCOMP 406 8.3.4 Algorithm for JTF-Based Translational and RotationalMOCOMP 408 8.3.4.1 A Numerical Example 410 8.4 Matlab Codes 415 References 436 9 Bistatic ISAR Imaging 440 9.1 Why Bi-ISAR Imaging? 440 9.2 Geometry for Bi-Isar Imaging and the Algorithm 444 9.2.1 Bi-ISAR Imaging Algorithm for a Point Scatterer 444 9.2.2 Bistatic ISAR Imaging Algorithm for a Target 448 9.3 Resolutions in Bistatic ISAR 449 9.3.1 Range Resolution 449 9.3.2 Cross-Range Resolution 450 9.3.3 Range and Cross-Range Extends 451 9.4 Design Procedure for Bi-ISAR Imaging 452 9.5 Bi-Isar Imaging Examples 455 9.5.1 Bi-ISAR Design Example #1 455 9.5.2 Bi-ISAR Design Example #2 457 9.6 Mu-ISAR Imaging 465 9.6.1 Challenges in Mu-ISAR Imaging 467 9.6.2 Mu-ISAR Imaging Example 468 9.7 Matlab Codes 472 References 483 10 Polarimetric ISAR Imaging 484 10.1 Polarization of an Electromagnetic Wave 484 10.1.1 Polarization Type 485 10.1.2 Polarization Sensitivity 486 10.1.3 Polarization in Radar Systems 487 10.2 Polarization Scattering Matrix 488 10.2.1 Relation to RCS 490 10.2.2 Polarization Characteristics of the Scattered Wave 491 10.2.3 Polarimetric Decompositions of EM Wave Scattering 493 10.2.4 The Pauli Decomposition 494 10.2.4.1 Description of Pauli Decomposition 494 10.2.4.2 Interpretation of Pauli Decomposition 495 10.2.4.3 Polarimetric Image Representation Using Pauli Decomposition 496 10.3 Why Polarimetric ISAR Imaging? 497 10.4 ISAR Imaging with Full Polarization 497 10.4.1 ISAR Data in LP Basis 497 10.4.2 ISAR Data in CP Basis 498 10.5 Polarimetric ISAR Images 499 10.5.1 Pol-ISAR Image of a Benchmark Target 499 10.5.1.1 The “SLICY” Target 499 10.5.1.2 Fully Polarimetric EM Simulation of SLICY 499 10.5.1.3 LP Pol-ISAR Images of SLICY 500 10.5.1.4 CP Pol-ISAR Images of SLICY 502 10.5.1.5 Pauli Decomposition Image of SLICY 503 10.5.2 Pol-ISAR Image of a Complex Target 507 10.5.2.1 The “Military Tank” Target 507 10.5.2.2 Fully Polarimetric EM Simulation of “Tank” Target 508 10.5.2.3 LP Pol-ISAR Images of “Tank” Target 508 10.5.2.4 CP Pol-ISAR Images of “Tank” Target 510 10.5.2.5 Pauli Decomposition Image of “Tank” Target 512 10.6 Feature Extraction from Polarimetric Images 515 10.7 Matlab Codes 515 References 529 11 Near-Field ISAR Imaging 533 11.1 Definitions of Far and Near-Field Regions 534 11.1.1 The Far-Field Region 534 11.1.1.1 The Far-Field Definition Based on Target’s Cross-Range Extend 534 11.1.1.2 The Far-Field Definition Based on Target’s Range Extend 535 11.1.2 The Near-Field Region 537 11.2 Near-Field Signal Model for the Back-Scattered Field 537 11.3 Near-Field ISAR Imaging Algorithms 540 11.3.1 “Focusing Operator” Algorithm 540 11.3.2 Back-Projection Algorithm 541 11.3.2.1 Fourier Slice Theorem 542 11.3.2.2 BPA Formulation (3D Case) 543 11.3.2.3 BPA Formulation (2D Case) 544 11.4 Data Sampling Criteria and the Resolutions 546 11.5 Near-Field ISAR Imaging Examples 547 11.5.1 Point Scatterers in the Near-Field: Comparison of Far- and Near-Field Imaging Algorithms 547 11.5.2 Near-Field ISAR Imaging of a Large Object 552 11.5.3 Near-Field ISAR Imaging of a Small Object 555 11.6 Matlab Codes 560 References 569 12 Some Imaging Applications Based on SAR/ISAR 571 12.1 Imaging Subsurface Objects: GPR-SAR 572 12.1.1 The GPR Problem 572 12.1.2 B-Scan GPR in Comparison to Strip-Map SAR 577 12.1.3 Focused GPR Images Using SAR 577 12.1.3.1 GPR Focusing with ω-k Algorithm (ω-kA) 579 12.1.3.2 GPR Focusing with BPA 582 12.1.3.3 Other Popular GPR Focusing Techniques 589 12.2 Thru-the-Wall Imaging Radar Using SAR 590 12.2.1 Challenges in TWIR 591 12.2.2 Techniques to Improve Cross-Range Resolution in TWIR 591 12.2.3 The Use of SAR in TWIR 592 12.2.4 Example of SAR-Based TWIR 594 12.3 Imaging Antenna-Platform Scattering: ASAR 596 12.3.1 The ASAR Imaging Algorithm 597 12.3.2 Numerical Example for ASAR Imagery 603 12.4 Imaging Platform Coupling Between Antennas: ACSAR 605 12.4.1 The ACSAR Imaging Algorithm 606 12.4.2 Numerical Example for ACSAR 609 12.4.3 Applying ACSAR Concept to the GPR Problem 611 References 615 Appendix 619 Index 628

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Book SynopsisExplore Modern Communications and Understand Principles of Operations, Appropriate Technologies, and Elements of Design of Communication Systems Modern society requires a different set of communication systems than has any previous generation. To maintain and improve the contemporary communication systems that meet ever-changing requirements, engineers need to know how to recognize and solve cardinal problems. InEssentials of Modern Communications, readers will learn how modern communication has expanded and will discover where it is likely to go in the future. By discussing the fundamental principles, methods, and techniques used in various communication systems, this book helps engineers assess, troubleshoot, and fix problems that are likely to occur. In this reference, readers will learn about topics like: How communication systems respond in time and frequency domainsPrinciples of analog and digital modulationsApplication of spectral analysis to modern communication systems baseTable of ContentsAbout the Authors xxi Preface xxiii Acknowledgments xxvii 1 Modern Communications: What It Is? 1 Objectives and Outcomes of Chapter 1 1 1.1 What and Why of Modern Communications 4 Objectives and Outcomes of Section 1.1 4 1.1.1 What is Modern Communications? 5 1.1.2 General Block Diagram of a Communication System 6 1.1.3 Operation of a Communication System 7 1.1.4 Why DoWe Need Modern Communications? 8 1.1.5 From Today to Tomorrow – Two Examples 9 1.1.5.1 The Internet of Things (IoT) 10 1.1.5.2 Data Centers 12 Questions and Problems for Section 1.1 13 1.2 Communication Technology on a Fast Track 16 Objectives and Outcomes of Section 1.2 16 Sidebar 1.2.S.1 Brief Notes on History of Telegraph, Telephone, Radio, and Television 22 1.2.1 The Internet 28 1.2.1.1 Basics of Networks 28 1.2.1.2 The Internet: From a Point-to-Point Link to a Network of Networks 37 1.2.2 Optical Communications 42 1.2.2.1 Introduction to Optical Communications 43 1.2.2.2 Developments in Optical Communications: From First Inventions to Modern Advances 46 1.2.3 Wireless Communications 49 1.2.3.1 Introduction to Wireless Communications 49 1.2.3.2 Contemporary Wireless Communications Technologies 54 1.2.3.3 Mobile Cellular Communications 57 1.2.4 Satellite Communications 59 1.2.4.1 Historical Notes 59 1.2.4.2 Principle of Operation of Satellite Communication Systems 60 1.2.4.3 Satellite Orbits 62 Questions and Problems for Section 1.2 67 1.3 Fundamental Laws and Principles of Modern Communications 75 1.3.1 Fundamental Laws of Modern Communications 75 1.3.1.1 Hartley’s Information Law 75 1.3.1.2 Signal Bandwidth and Transmission Bandwidth from the Transmission Standpoint 76 1.3.1.3 Bandwidth and Bit Rate, Nyquist’s Formula, and Hartley’s Capacity Law 77 1.3.1.4 Shannon’s Law (Limit) 79 1.3.1.5 More Clarifications of the Shannon Law 82 1.3.1.6 The Shannon Law for Digital Communications 83 1.3.2 Fundamental Principles of Modern Communications 86 1.3.2.1 Channel Capacity, Bandwidth, and Carrier Frequency 86 1.3.2.2 Bandwidth-Length Product 90 1.3.2.3 Power-Bandwidth Trade-Off 91 1.3.2.4 Spectral Efficiency and Transmission Technology 92 1.3.2.5 Bit Rate vs. Bandwidth in Digital Transmission 93 1.3.3 Laws, Principles, and Models – Importance, Limitations, and Applications 94 1.3.3.1 Limitations and Applications of the Laws and Principles 94 1.3.3.2 Models 96 1.3.3.3 Modeling and Simulation 98 Questions and Problems for Section 1.3 99 2 Analog Signals and Analog Transmission 103 Objectives and Outcomes of Chapter 2 103 2.1 Analog Signals – Basics 104 Objectives and Outcomes of Section 2.1 104 2.1.1 Definitions 104 2.1.1.1 Waveforms 104 2.1.1.2 Analog and Digital Signals 108 2.1.2 Sinusoidal Signal 110 2.1.2.1 The Waveform of a Sinusoidal Signal 110 2.1.2.2 Period and Frequency 111 2.1.2.3 Frequency, Radian (Angular) Frequency and Angle 115 2.1.2.4 Phase Shift (Initial Phase) 117 2.1.2.5 Amplitude 121 Questions and Problems for Section 2.1 125 2.2 Analog Signals – Introduction 129 Objectives and Outcomes of Section 2.2 129 2.2.1 More About a Sinusoidal Signal 130 2.2.1.1 Considering All Three Parameters – the Formula for a Sinusoidal Signal 130 2.2.1.2 The Phase of a Sinusoidal Signal: a Detailed Look 132 2.2.1.3 Cosine and Sine Signals 138 Sidebar 2.2.S.1 Phasor and Sinusoidal Signal 139 Sidebar 2.2.S.2 Signal and Function 146 2.2.2 Frequency Domain and Bandwidth 151 2.2.2.1 Frequency Domain 151 2.2.2.2 Cosine and Sine Signals in Frequency Domain 151 2.2.2.3 Bandwidth 156 2.2.2.4 Bandwidth: a Sophisticated Entity 159 Questions and Problems for Section 2.2 162 2.3 Analog Signals – Advanced Study 167 Objectives and Outcomes of Section 2.3 167 2.3.1 Revisiting the Waveforms 168 2.3.1.1 More about Waveforms 168 2.3.1.2 Waveform and Signal’s Power 174 2.3.2 Waveforms and Phasors 178 2.3.2.1 Practically Realizable Waveforms 178 2.3.2.2 Phasors and Phasor Diagrams 178 2.3.2.3 Waveforms and Phasors for a Resistor, an Inductor, and a Capacitor 181 2.3.2.4 Impedances and Phasors 185 Questions and Problems for Section 2.3 189 2.3.A Mathematical Foundation of Phasor Presentation 191 2.3.A.1 Phasors and Complex Numbers 191 2.3.A.2 Applications of Phasor Presentation to the Analysis of Electronic Communications Circuitry 195 2.3.A.2.1 Summation of Signals 195 Optional: Questions and Problems for Appendix 2.3.A 200 3 Digital Signals and Digital Transmission 203 Objectives and Outcomes of Chapter 3 203 3.1 Digital Communications – Basics 203 Objectives and Outcomes of Section 3.1 203 3.1.1 Why Go to Digital Communications 204 3.1.1.1 Main Advantage of Digital Transmission over the Analog 204 3.1.1.2 Case Study 1: The Advantages of Using Digital Signals in Transmission 207 3.1.1.3 Case Study 2 of Digital Communications: Transmission with Integrated-Circuit Digital Logic Families 210 3.1.1.4 Why Go to Digital Communications: A Summary 214 3.1.2 How to Go to Digital Communications 215 3.1.2.1 From Characters to Bits 215 3.1.2.2 From Bits to Electrical Pulses 222 3.1.2.3 How to Go Digital Communications: A Summary 224 Questions and Problems for Section 3.1 225 3.1.A Brief History of Character Codes 229 3.1.A.1 International Morse Code 229 3.1.A.2 Baudot Code 230 3.2 Digital Signals and Digital Transmission – Introduction 232 Objectives and Outcomes of Section 3.2 232 3.2.1 Ideal Digital Signal and Characteristics of Digital Transmission 233 3.2.1.1 The Waveform of an Ideal Digital Signal 233 3.2.1.2 Pulse Interval and Transmission Rate; Bit Time and Bit Rate 235 3.2.1.3 Important Note: The Definition of Bit Time 237 3.2.1.4 Bit Rate and Channel (Shannon’s) Capacity 237 3.2.2 Parameters of a Real Digital Signal and the Characteristics of Digital Transmission 239 3.2.2.1 Waveform of an Actual Digital Signal 239 3.2.2.2 Amplitude and Pulse Width 240 3.2.2.3 Rise Time and Fall Time 241 3.2.2.4 Rise/Fall Time and Bit Rate 244 3.2.2.5 More on Timing Parameters of a Digital Signal: Bit Time Revisited 247 3.2.2.6 Duty Cycle 250 Questions and Problems for Section 3.2 253 4 Analog-to-Digital Conversion (ADC) and Digital-to-Analog Conversion (DAC) 259 Objectives and Outcomes of Chapter 4 259 4.1 Analog-to-Digital Conversion, ADC 259 Objectives and Outcomes of Section 4.1 259 4.1.1 The Need for ADC and DAC 261 4.1.2 Three Major Steps of ADC 263 4.1.3 Sample-and-Hold (S&H) Operation 263 4.1.3.1 Sampling (S&H) Technique and the Nyquist Theorem 263 4.1.3.2 Aliasing 267 4.1.4 Quantization in ADC 272 4.1.4.1 Quantization Process 272 4.1.4.2 Quantization Errors and Quantization Noise 284 4.1.5 Encoding 285 Questions and Problems for Section 4.1 291 4.1.A Decimal and Binary Numbering Systems 299 4.1.A.1 Decimal Numbering System 299 4.1.A.2 Binary Numbering System 300 4.1.A.3 Conversion from the Decimal Number System to the Binary 301 4.2 Digital-to-Analog Conversion, DAC, Pulse-Amplitude Modulation, PAM, and Pulse-Code Modulation, PCM 303 Objectives and Outcomes of Section 4.2 303 4.2.1 Digital-to-Analog Conversion, DAC 304 4.2.2 Pulse Amplitude Modulation, PAM 304 4.2.3 Pulse Code Modulation, PCM 306 4.2.3.1 PCM: Principle of Operation 306 4.2.3.2 PCM: Advantages and Drawbacks 308 4.2.3.3 PCM Applications 309 Questions and Problems for Section 4.2 309 4.2.A Modes of Digital Transmission 311 4.2.A.1 Simplex, Half Duplex and Full Duplex Transmission 311 4.2.A.2 Serial and Parallel Transmissions 312 4.2.A.3 The General Formula for Bit Rate 314 4.2.A.4 The Need for Synchronization in Digital Transmission 315 4.2.A.4.1 Digital Signals and Timing 315 4.2.A.4.2 Timing in Digital Transmission 316 4.2.A.4.3 Time Discrepancy Between Transmitter and Receiver Clocks 317 4.2.A.4.4 How Time Discrepancy Between Transmitter and Receiver Clocks Deteriorates the Quality of Digital Transmission 319 4.2.A.4.5 A Short Summary on Synchronization Issues 320 4.2.A.5 Asynchronous and Synchronous Transmission 320 4.2.A.5.1 Asynchronous Transmission 321 4.2.A.5.2 Synchronous Transmission 323 5 Filters 325 Objectives and Outcomes of Chapter 5 325 5.1 Filtering – Basics 326 Objectives and Outcomes of Section 5.1 326 5.1.1 Filtering: What and Why 327 5.1.2 RC Low-Pass Filter (LPF) 330 5.1.2.1 Frequency Responses of a Resistor, R, and a Capacitor, C 330 5.1.2.2 RC Low-Pass Filter: Principle of Operation 333 5.1.2.3 Output Waveforms of an RC LPF 334 5.1.2.4 An RC LPF: Formulas for Attenuation and Phase Shift 335 5.1.2.5 Frequency Response of an RC LPF 339 5.1.2.6 Cutoff (Critical) Frequency of an RC LPF 342 Sidebar 5.1.S Filter’s Characteristics in Absolute Values and in dB 345 5.1.3 Filter Operation in Time Domain and Frequency Domain 347 5.1.3.1 Waveform Change and Frequency Response 347 5.1.3.2 Bandwidth of an RC LPF 349 5.1.3.3 Characterization of an RC LPF 349 5.1.3.4 The Role of R and C Parameters in Characterization of an RC LPF 352 5.1.4 General Filter Specifications 354 5.1.4.1 Amplitude Specifications 354 5.1.4.2 Phase Specifications 359 Questions and Problems for Section 5.1 360 5.2 Filtering – Introduction 365 Objectives and Outcomes of Section 5.2 365 5.2.1 High-Pass Filter (HPF), Band-Pass Filter (BPF), and Band-Stop Filter (BSF) 366 5.2.1.1 High-Pass Filter (HPF) 367 5.2.1.2 Band-Pass Filter (BPF) 371 5.2.1.3 Band-Stop Filter (BSF) 378 5.2.1.4 Applications of RC Filters 380 5.2.1.5 Final Notes on RC Filters 380 5.2.2 Transfer Function of a Filter 381 5.2.2.1 Input and Output of a Filter 381 5.2.2.2 Transfer Function of an RC LPF 384 5.2.2.3 Graphical Presentation of a Transfer Function: Bode Plots 387 Questions and Problems for Section 5.2 394 5.2.A RL Filter and Resonance Circuits as Filters 400 5.2.A.1 RL Filter 400 5.2.A.2 Resonance Circuits as Filters 402 5.2.A.2.1 Resonance Circuits: A Review 402 5.2.A.2.2 Quality Factor 405 5.2.A.2.3 Resonance Circuit as a Band-Pass Filter 406 5.2.A.2.4 Resonance Circuit as a Band-Stop Filter 407 5.3 Active and Switched-Capacitor Filters 409 Objectives and Outcomes of Section 5.3 409 5.3.1 Active Filters 410 5.3.1.1 Drawbacks of Passive Filters 410 5.3.1.2 Operational Amplifier 413 5.3.1.3 Active Filters: Concept and Circuits 418 5.3.1.4 Transfer Functions of an Active Filter: General View 419 5.3.1.5 Specific Types of Active Filters 420 5.3.1.6 Concluding Remarks on Active Filters 424 5.3.2 Switched-Capacitor Filters 424 5.3.2.1 Switched-Capacitor Filters: Concept and Circuits 424 5.3.2.2 Applications of Switched-Capacitor Filters 428 Questions and Problems for Section 5.3 431 5.3.A Active BPF and BSF 436 5.3.A.1 Active BPF 436 5.3.A.2 Active BSF 439 5.4 Filter Prototypes and Filter Design 441 Objectives and Outcomes of Section 5.4 441 5.4.1 Filter Prototypes 444 5.4.1.1 The Problem in the Filter Design – The Need for the Filter Prototypes 444 5.4.1.2 Another Problem for Filter’s Designer: Relationship Between Amplitude and Phase Responses 445 5.4.1.3 Main Filter Prototypes – What and Why 446 5.4.1.4 Transfer Function of the Butterworth Filter 450 5.4.1.5 Amplitude Response of the Butterworth Filter 451 5.4.1.6 Amplitude Response of the Butterworth Filter in Logarithmic Scale 453 5.4.1.7 Phase Response (Shift) and Time Group Delay of the Butterworth Filter 456 5.4.1.8 Poles of the Butterworth Filter’s Transfer Function 457 5.4.2 Introduction to Filter Design 459 5.4.2.1 Two Main Steps in Filter Design 459 5.4.2.2 Automated Design Options 460 5.4.2.3 Design of a Second-order Butterworth Filter 462 5.4.2.4 Using the Poles of a Transfer Function 468 5.4.3 The Design Process: Key Questions, Answers, and Salient Points 469 5.4.3.1 Questions and Answers 469 5.4.3.2 Salient Points 470 5.4.3.3 Choosing Filter Technology 471 Questions and Problems for Section 5.4 472 5.4.A Tables of the Butterworth Polynomials 478 5.5 Digital Filters 479 Objectives and Outcomes of Section 5.5 479 5.5.1 What are Digital Filters? 479 5.5.1.1 Digital Filters – Principle of Operation 479 5.5.1.2 ADC and DAC Operations Revisited 481 5.5.1.3 Digital Filters – Difference Equation, Order, and Coefficients 484 5.5.1.4 Recursive (IIR) and Nonrecursive (FIR) Digital Filters and Their Difference Equations 486 5.5.1.5 Impulse Response of Digital Filters 487 5.5.1.6 Transfer Function of a Digital Filter 488 5.5.2 Conclusive Remarks on Digital and Analog Filters 491 5.5.2.1 Some Final Comments on Digital Filters 491 5.5.2.2 Adaptive Filters 491 5.5.2.3 Comparison of Analog and Digital Filters 492 5.5.2.4 Summary of Applications of Various Filter Technologies 492 Questions and Problems for Section 5.5 494 What are Digital Filters? 494 6 Spectral Analysis 1 – The Fourier Series in Modern Communications 497 Objectives and Outcomes of Chapter 6 497 6.1 Basics of Spectral Analysis 498 Objective and Outcomes of Section 6.1 498 6.1.1 Time Domain and Frequency Domain 498 6.1.1.1 Periodic and Nonperiodic Signals 498 6.1.1.2 Time Domain and Frequency Domain Revisited 500 6.1.1.3 Signal Spectrum 509 6.1.2 The Fourier Series 511 6.1.2.1 The Fourier Theorem 511 Sidebar 6.1.S.1 Calculating the Coefficients of a Fourier Series 515 6.1.2.2 Spectral Analysis – From the Whole to the Parts 519 6.1.3 Spectral Synthesis 520 6.1.3.1 Spectral Synthesis – From Parts to the Whole 520 Questions and Problems for Section 6.1 528 6.2 Introduction to Spectral Analysis 534 Objectives and Outcomes of Section 6.2 534 6.2.1 More About the Fourier Series 534 6.2.1.1 Coefficients of the Fourier Series 534 6.2.1.2 Amplitude and Phase Spectra 537 Sidebar 6.2.S.1 Using the Signal’s Symmetry for Finding the Fourier Series Coefficients 542 6.2.1.3 Finding the Fourier Series of Various Signals 544 6.2.2 Effect of Filtering on Signals 546 6.2.2.1 Statement of the Problem 546 6.2.2.2 Filtering a Single Harmonic 552 6.2.2.3 Filtering a Periodic Signal – Time and Frequency Domains 554 6.2.2.4 Filtering a Signal – The Entire Picture 560 6.2.2.5 A Final Note on Effect of Filtering on Signals 566 6.2.3 Harmonic Distortion 566 Questions and Problems for Section 6.2 572 6.3 Spectral Analysis of Periodic Signals: Advanced Study 578 Objectives and Outcomes of Section 6.3 578 6.3.1 Mathematical Foundation of the Fourier Series 579 6.3.1.1 The Fourier Series in Exponential and Phasor Forms 579 Sidebar 6.3.S.1 The Other Forms of an Exponential Fourier Series 587 6.3.1.2 Two-Sided and One-Sided Spectra and Three Equivalent Forms of the Fourier Series 588 6.3.2 Conditions for Application of the Fourier Series 591 Sidebar 6.3.S.2 Convergence of the Fourier Series 591 6.3.2.1 Gibbs Phenomenon 593 6.3.3 Power Spectrum of a Periodic Signal 594 6.3.3.1 Power and Energy Signals 594 6.3.3.2 Parseval’s Theorem 595 6.3.3.3 A Signal’s Bandwidth and Transmission Issues Associated with a Power Spectrum 598 Questions and Problems for Section 6.3 609 6.3.A Fourier Coefficients of a Two-sided and a One-sided Spectrum of the Periodic Pulse Train for Example 6.3.2. 613 7 Spectral Analysis 2 – The Fourier Transform in Modern Communications 615 Objectives and Outcomes of Chapter 7 615 7.1 Basics of the Fourier Transform 616 Objectives and Outcomes of Section 7.1 616 7.1.1 The Fourier Transform in Spectral Analysis 617 7.1.1.1 From a Periodic to a Nonperiodic Signal 617 7.1.1.2 From the Fourier Series to the Fourier Transform 628 7.1.1.3 The Fourier Transform Briefly Explained 629 7.1.2 First Examples of the Fourier Transform Applications 632 7.1.2.1 A Rectangular Pulse 632 7.1.2.2 Basics of the Spectral Analysis of a Nonperiodic Signal 635 7.1.2.3 Rayleigh Energy Theorem 639 Summary of Section 7.1 642 Questions and Problems for Section 7.1 643 7.2 Continuous-Time Fourier Transform: A Deeper Look 644 Objectives and Outcomes of Section 7.2 644 7.2.1 Definition and Existence of the Fourier Transform 645 7.2.2 The Concept of Function and the Transform 646 Sidebar 7.2.S.1 Dirac Delta Function 649 7.2.3 Table of the Fourier Transform 654 7.2.4 Properties of the Fourier Transform 656 7.2.4.1 Units 656 7.2.4.2 Linearity 657 7.2.4.3 Duality 657 7.2.4.4 Modulation 657 7.2.4.5 Convolution in Time and in Frequency and a Transfer Function 658 7.2.4.6 Time Differentiation 659 7.2.4.7 Other Properties of the Fourier Transform 659 7.2.5 Example of Using the Fourier Transform 659 Sidebar 7.2.S.2 The Impulse Response of an RC LPF 662 Sidebar 7.2.S.3 Alternative Methods of Finding a Transfer Function 667 7.3 The Fourier Transforms and Digital Signal Processing 670 Objectives and Outcomes of Section 7.3 670 7.3.1 Signals and the Fourier Transformations 671 Sidebar 7.3.S.1 A Word About DSP 677 7.3.2 Determining the Fourier Transform Required for DSP 681 7.3.3 Digital Signal Processing (DSP) and Discrete Fourier Transform (DFT) 681 7.3.3.1 The Problem: Choosing the Best Type of FT for DSP 681 7.3.3.2 How Discrete Fourier Transform (DFT)Works 682 7.3.3.3 Can DFT Work with Any Signal? 690 7.3.4 Relationship Among All Fourier Transforms 697 7.3.5 Fast Fourier Transform (FFT) 699 8 Analog Transmission with Analog Modulation 707 Objectives and Outcomes of Chapter 8 707 8.1 Basics of Analog Modulation 708 Objectives and Outcomes of Section 8.1 708 8.1.1 Why We Need Modulation: Baseband and Broadband Transmission 710 8.1.1.1 Baseband Transmission and Its Major Problems 710 8.1.1.2 Solution to the Problems of Baseband Transmission – Broadband Transmission 712 8.1.2 Basics of Amplitude Modulation 715 8.1.2.1 What Type of Analog Modulation Can We Have? 715 8.1.2.2 What is Amplitude Modulation (AM) 715 8.1.2.3 Modulation Index 719 8.1.2.4 Relationship Between Frequencies of Information and Carrier Signals 722 8.1.2.5 The Formula for an AM Signal and It Instantaneous Value 723 8.1.2.6 The Spectrum of an AM Signal 725 8.1.2.7 Power Distribution in an AM Signal 728 8.1.2.8 AM Modulation and Demodulation 730 8.1.2.9 The Main Drawback of Amplitude Modulation 732 8.1.3 Basics of Frequency Modulation (FM) 733 8.1.3.1 Frequency Modulation: Why and What 733 8.1.3.2 The Frequency of an FM Signal 734 8.1.3.3 Modulation Index of an FM Signal 738 8.1.3.4 The Spectrum and Bandwidth of an FM Signal 740 8.1.3.5 Relationship Between Parameters of Message and Carrier Signals in FM Transmission 746 8.1.3.6 FM Modulation and Demodulation 746 8.1.4 Basics of Phase Modulation (PM) 750 8.1.4.1 How to Generate a Phase-Modulated Signal 750 8.1.4.2 Instantaneous Value of a Sinusoidal PM Signal 754 Questions and Problems for Section 8.1 754 8.1.A Drawbacks of Baseband Transmission 759 8.2 Analog Modulation for Analog Transmission – An Advanced Study 762 Objectives and Outcomes of Section 8.2 762 8.2.1 Classification of Modulation Revisited 763 8.2.2 Advanced Consideration of Amplitude Modulation, AM, and Its Application in Analog Transmission 766 8.2.2.1 Full (Double-Sideband Transmitted Carrier, DSB-TC) Amplitude Modulation 766 8.2.2.2 Problems of Full AM Transmission 774 8.2.2.3 Double-Sideband Suppressed Carrier (DSB-SC) AM 774 8.2.2.4 Single-Sideband Suppressed Carrier (SSB-SC) AM 779 8.2.2.5 Full AM, DSB, or SSB – Which Type to Choose? 782 8.2.2.6 Applications of AM Transmission 784 8.2.3 Advanced Consideration of Angular (Phase and Frequency) Modulation and Its Application in Analog Transmission 784 8.2.3.1 Angular Modulation 784 8.2.3.2 Sinusoidal (Single-Tone) Frequency Modulation (FM) 788 8.2.3.3 The Spectrum of a Single-Tone FM Signal, the Main Properties of the Bessel Functions, and Narrowband and Wideband FM 790 8.2.3.4 The Bandwidth of a Single-Tone FM Signal 793 8.2.3.5 General Case of an FM Signal (An Arbitrary Message Signal) 799 8.2.3.6 Effect of Noise on an FM Signal 807 Questions and Problems for Section 8.2 810 8.2.A Finding the Spectrum of an FM Signal with MATLAB 814 9 Digital Transmission with Binary Modulation 823 Objectives and Outcomes of Chapter 9 823 9.1 Digital Transmission – Basics 824 Objectives and Outcomes of Section 9.1 824 9.1.1 Essentials of Digital Transmission Revisited 827 9.1.1.1 Block Diagram of a Communication System 827 9.1.1.2 Characteristics of a Transmitter, Tx 828 9.1.1.3 Characteristics of a Receiver, Rx 829 9.1.1.4 Characteristics of a Transmission Channel (Link) 830 9.1.1.5 The Model of Noise in Shannon’s Law 835 9.1.1.6 An Amplifier in a Transmission Channel: Internal Noise, SNR, and Noise Figure 839 9.1.2 Assessing the Quality of Digital Transmission: The Gaussian (Bell) Curve and the Probability Value 843 9.1.2.1 Gaussian (Bell) Normal Probability Distribution 843 9.1.2.2 Finding the Probability Value with the Bell Curve 844 9.1.2.3 Standard Normal Probability Distribution 847 9.1.2.4 The Gaussian Curve and Q-Function 850 9.1.3 Assessing the Quality of Digital Transmission: Bit Error Rate and More 852 9.1.3.1 Decision-Making Procedure in the Presence of Noise 852 9.1.3.2 The Probability of Error in Detecting the Received Signal: Bit Error Rate (Ratio) 855 9.1.3.3 BER: A Discussion 858 9.1.4 Eye Diagram 860 9.1.4.1 Eye Diagram: The Concept 860 9.1.4.2 Estimating Transmission Quality with an Eye Diagram 865 Questions and Problems for Section 9.1 869 9.2 Introduction to Digital Transmission – Binary Shift-Keying Modulation 878 Objectives and Outcomes of Section 9.2 878 9.2.1 Digital Signal over a Sinusoidal Carrier – Binary Shift-Keying Modulation 881 9.2.2 Binary Amplitude-Shift Keying (ASK) 881 9.2.2.1 ASK Concept and Waveform 881 9.2.2.2 Mathematical Description of ASK 883 9.2.2.3 ASK Spectrum 884 9.2.2.4 ASK Bandwidth 888 9.2.2.5 Bandwidth and Bit Rate of ASK 893 9.2.2.6 Bit Error Ratio, BER, of ASK System 895 9.2.2.7 ASK Advantages, Drawbacks, and Applications 898 9.2.2.8 Detection (Demodulation) of an ASK Signal 900 9.2.3 Binary Frequency-Shift Keying (FSK) 901 9.2.3.1 FSK Concept and Waveform 901 9.2.3.2 Mathematical Description of FSK 903 9.2.3.3 FSK Spectrum and Bandwidth with Square Wave Message 904 9.2.3.4 FSK Spectrum and Bandwidth with a Rectangular Pulse-Train Message 906 9.2.3.5 Bit Error Ratio, BER, and Remarks on our BFSK Discussion 908 9.2.3.6 Discontinuous-Phase FSK (DPFSK) and Continuous-Phase FSK (CPFSK) 910 9.2.3.7 Mathematical Description of a CPFSK Signal 911 9.2.3.8 Detection (Demodulation) of an FSK Signal 916 9.2.3.9 BFSK: Advantages, Drawbacks, and Applications 921 9.2.4 Binary Phase-Shift Keying (PSK) 922 9.2.4.1 PSK Concept and Waveform 922 9.2.4.2 PSK Mathematical Description; PSK Spectrum and Bandwidth with a Square Wave Message 925 9.2.4.3 Demodulation of a Binary PSK Signal 926 9.2.4.4 Bit Error Ratio, BER, of a BPSK Transmission 929 9.2.4.5 BPSK Advantages and Applications 932 9.2.4.6 Comparison of Binary ASK, FSK, and PSK 932 Questions and Problems for Section 9.2 932 9.2.A Jitter 940 10 Digital Transmission with Multilevel Modulation 943 Objectives and Outcomes of Chapter 10 943 10.1 Quadrature Modulation Systems 943 Objectives and Outcomes of Section 10.1 943 10.1.1 Multilevel (M-ary) Modulation Formats – What and Why 945 10.1.1.1 The Concept of Multilevel Modulation 945 10.1.1.2 Symbols and Bits 948 10.1.2 Quadrature Phase-Shift Keying, QPSK 951 10.1.2.1 Introduction to Quadrature Phase-Shift Keying, QPSK 951 10.1.2.2 QPSK Signal:Waveform and Constellation Diagram 953 10.1.2.3 Generating (Modulating) a QPSK Signal 957 10.1.3 Working with QPSK Signaling 964 10.1.3.1 Properties of a QPSK Signal 964 10.1.3.2 QPSK Demodulation 965 10.1.3.3 Assessing the Quality of QPSK Transmission 967 10.1.3.4 Offset QPSK, Differential QPSK, and Minimum SK 968 Questions and Problems for Section 10.1 970 10.2 Multilevel PSK and QAM Modulation 974 Objectives and Outcomes of Section 10.2 974 10.2.1 Multilevel (M-ary) PSK 975 10.2.1.1 Introduction to M-ary PSK 975 10.2.1.2 BER of M-ary PSK 977 10.2.2 Multilevel Quadrature Amplitude Modulation, M-QAM 981 10.2.2.1 The Concept of Multilevel Quadrature Amplitude Modulation, M-QAM 981 10.2.2.2 BER of M-QAM 984 10.2.3 Final Thoughts 991 10.2.3.1 Spectral Efficiency, Signal-to-Noise Ratio, and Multilevel Modulation 991 10.2.3.2 Bandwidth-Power Trade-off 994 10.2.3.3 Applications of Multilevel Signaling 995 Questions and Problems for Section 10.2 995 10.A Multiplexing 999 10.A.1 Multiplexing: Definition and Advantages 999 10.A.2 Time-Based Multiplexing Principles 1000 10.A.2.1 Synchronous Time-Division Multiplexing, sync-TDM 1000 Sidebar 10.A.2.S Two sync-TDM Systems: T and Synchronous Optical Network (SONET) 1002 10.A.2.2 Statistical (Asynchronous) Time-Division Multiplexing, stat-TDM 1008 10.A.3 Frequency-Based Multiplexing Techniques 1010 10.A.3.1 Frequency-Division Multiplexing, FDM 1010 10.A.3.2 Orthogonal Frequency Division Multiplexing, OFDM 1011 10.A.3.3 Wavelength-Division Multiplexing, WDM 1016 10.A.3.3.1 Why We Need WDM and How WDM Works 1016 10.A.3.3.2 WDM Technology 1018 10.A.3.4 CWDM and Other Types of Multiplexing in Optical Communications 1020 10.A.4 Code-Division Multiplexing, CDM 1023 10.A.4.1 CDM: The Principle of Operation 1023 10.A.4.2 Spread-Spectrum Technique 1024 10.A.4.3 CDM: Benefits and Applications 1026 Bibliography 1029 Specialized Bibliographies 1037 Index 1043

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Book SynopsisINTRODUCTION TO THE PHYSICS AND TECHNIQUES OF REMOTE SENSING DISCOVER CUTTING EDGE THEORY AND APPLICATIONS OF MODERN REMOTE SENSING IN GEOLOGY, OCEANOGRAPHY, ATMOSPHERIC SCIENCE, IONOSPHERIC STUDIES, AND MORE The thoroughly revised third edition of the Introduction to the Physics and Techniques of Remote Sensing delivers a comprehensive update to the authoritative textbook, offering readers new sections on radar interferometry, radar stereo, and planetary radar. It explores new techniques in imaging spectroscopy and large optics used in Earth orbiting, planetary, and astrophysics missions. It also describes remote sensing instruments on, as well as data acquired with, the most recent Earth and space missions. Readers will benefit from the brand new and up-to-date concept examples and full-color photography, 50% of which is new to the series. You'll learn about the basic physics of wave/matter interactions, techniques of remote sensing across the elTable of ContentsPreface xv 1 Introduction 1 1.1 Types and Classes of Remote Sensing Data 1 1.2 Brief History of Remote Sensing 6 1.3 Remote Sensing Space Platforms 13 1.4 Transmission Through the Earth and Planetary Atmospheres 15 References and Further Reading 18 2 Nature and Properties of Electromagnetic Waves 19 2.1 Fundamental Properties of Electromagnetic Waves 19 2.1.1 Electromagnetic Spectrum 19 2.1.2 Maxwell’s Equations 20 2.1.3 Wave Equation and Solution 21 2.1.4 Quantum Properties of Electromagnetic Radiation 21 2.1.5 Polarization 22 2.1.6 Coherency 25 2.1.7 Group and Phase Velocity 26 2.1.8 Doppler Effect 27 2.2 Nomenclature and Definition of Radiation Quantities 30 2.2.1 Radiation Quantities 30 2.2.2 Spectral Quantities 31 2.2.3 Luminous Quantities 32 2.3 Generation of Electromagnetic Radiation 32 2.4 Detection of Electromagnetic Radiation 34 2.5 Interaction of Electromagnetic Waves with Matter: Quick Overview 35 2.6 Interaction Mechanisms Throughout the Electromagnetic Spectrum 38 Exercises 42 References and Further Reading 43 3 Solid Surfaces Sensing in the Visible and Near Infrared 44 3.1 Source Spectral Characteristics 44 3.2 Wave–Surface Interaction Mechanisms 47 3.2.1 Reflection, Transmission, and Scattering 48 3.2.2 Vibrational Processes 51 3.2.3 Electronic Processes 54 3.2.4 Fluorescence 59 3.3 Signature of Solid Surface Materials 61 3.3.1 Signature of Geologic Materials 61 3.3.2 Signature of Biologic Materials 62 3.3.3 Depth of Penetration 67 3.4 Passive Imaging Sensors 70 3.4.1 Imaging Basics 70 3.4.2 Sensor Elements 71 3.4.3 Detectors 76 3.5 Types of Imaging Systems 81 3.6 Description of Some Visible/Infrared Imaging Sensors 84 3.6.1 Landsat Enhanced Thematic Mapper Plus (ETM+) 84 3.6.2 Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 87 3.6.3 Mars Orbiter Camera (MOC) 89 3.6.4 Mars Exploration Rover Panchromatic Camera (Pancam) 90 3.6.5 Cassini Imaging Instrument 91 3.6.6 Juno Imaging System 93 3.6.7 Europa Imaging System 93 3.6.8 Cassini Visual and Infrared Mapping Spectrometer (VIMS) 94 3.6.9 Chandrayaan Imaging Spectrometer M3 95 3.6.10 Sentinel Multispectral Imager 95 3.6.11 Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) 95 3.7 Active Sensors 96 3.8 Surface Sensing at Very Short Wavelengths 97 3.8.1 Radiation Sources 98 3.8.2 Detection 98 3.9 Image Data Analysis 99 3.9.1 Detection and Delineation 100 3.9.2 Classification 107 3.9.3 Identification 110 Exercises 113 References and Further Reading 117 4 Solid-Surface Sensing: Thermal Infrared 121 4.1 Thermal Radiation Laws 121 4.1.1 Emissivity of Natural Terrain 123 4.1.2 Emissivity from the Sun and Planetary Surfaces 124 4.2 Heat Conduction Theory 126 4.3 Effect of Periodic Heating 128 4.4 Use of Thermal Emission in Surface Remote Sensing 131 4.4.1 Surface Heating by the Sun 131 4.4.2 Effect of Surface Cover 133 4.4.3 Separation of Surface Units Based on Their Thermal Signature 135 4.4.4 Example of Application in Geology 135 4.4.5 Effects of Clouds on Thermal Infrared Sensing 135 4.5 Use of Thermal Infrared Spectral Signature in Sensing 137 4.6 Thermal Infrared Sensors 141 4.6.1 Heat Capacity Mapping Radiometer 143 4.6.2 Thermal Infrared Multispectral Scanner 145 4.6.3 ASTER Thermal Infrared Imager 145 4.6.4 Spitzer Space Telescope 149 4.6.5 2001 Mars Odyssey Thermal Emission Imaging System (THEMIS) 150 4.6.6 Advanced Very High Resolution Radiometer (AVHRR) 151 Exercises 154 References and Further Reading 156 5 Solid-Surface Sensing: Microwave Emission 159 5.1 Power-Temperature Correspondence 160 5.2 Simple Microwave Radiometry Models 161 5.2.1 Effects of Polarization 163 5.2.2 Effects of the Observation Angle 163 5.2.3 Effects of the Atmosphere 164 5.2.4 Effects of Surface Roughness 164 5.3 Applications and Use in Surface Sensing 165 5.3.1 Application in Polar Ice Mapping 165 5.3.2 Application in Soil Moisture Mapping 166 5.3.3 Measurement Ambiguity 170 5.4 Description of Microwave Radiometers 170 5.4.1 Antenna and Scanning Configuration for Real-Aperture Radiometers 171 5.4.2 Synthetic Aperture Radiometers 172 5.4.3 Receiver Subsystems 177 5.4.4 Data Processing 179 5.5 Examples of Developed Radiometers 180 5.5.1 Scanning Multichannel Microwave Radiometer (SMMR) 180 5.5.2 Special Sensor Microwave Imager (SSM/I) 181 5.5.3 Tropical Rainfall Mapping Mission Microwave Imager (TMI) 183 5.5.4 AMSR-E 184 5.5.5 SMAP Radiometer 185 Exercises 185 References and Further Reading 187 6 Solid-Surface Sensing: Microwave and Radio Frequencies 190 6.1 Surface Interaction Mechanism 190 6.1.1 Surface Scattering Models 192 6.1.2 Absorption Losses and Volume Scattering 197 6.1.3 Effects of Polarization 200 6.1.4 Effects of the Frequency 202 6.1.5 Effects of the Incidence Angle 205 6.1.6 Scattering from Natural Terrain 206 6.2 Basic Principles of Radar Sensors 209 6.2.1 Antenna Beam Characteristics 209 6.2.2 Signal Properties: Spectrum 213 6.2.3 Signal Properties: Modulation 216 6.2.4 Range Measurements and Discrimination 218 6.2.5 Doppler (Velocity) Measurement and Discrimination 221 6.2.6 High-Frequency Signal Generation 222 6.3 Imaging Sensors: Real Aperture Radars 224 6.3.1 Imaging Geometry 224 6.3.2 Range Resolution 225 6.3.3 Azimuth Resolution 225 6.3.4 Radar Equation 226 6.3.5 Signal Fading 227 6.3.6 Fading Statistics 229 6.3.7 Geometric Distortion 232 6.4 Imaging Sensors: Synthetic Aperture Radars 234 6.4.1 Synthetic Array Approach 234 6.4.2 Focused vs. Unfocused SAR 235 6.4.3 Doppler Synthesis Approach 237 6.4.4 SAR Imaging Coordinate System 239 6.4.5 Ambiguities and Artifacts 240 6.4.6 Point Target Response 243 6.4.7 Correlation with Point Target Response 246 6.4.8 Advanced SAR Techniques 248 6.4.9 Description of SAR Sensors and Missions 265 6.4.10 Applications of Imaging Radars 278 6.5 Nonimaging Radar Sensors: Scatterometers 295 6.5.1 Examples of Scatterometer Instruments 295 6.5.2 Examples of Scatterometer Data 303 6.6 Nonimaging Radar Sensors: Altimeters 304 6.6.1 Examples of Altimeter Instruments 307 6.6.2 Altimeter Applications 310 6.6.3 Imaging Altimetry 312 6.6.4 Wide Swath Ocean Altimeter 314 6.7 Nonconventional Radar Sensors 317 6.8 Subsurface Sounding 317 Exercises 320 References and Further Reading 323 7 Ocean Surface Sensing 334 7.1 Physical Properties of the Ocean Surface 334 7.1.1 Tides and Currents 335 7.1.2 Surface Waves 336 7.2 Mapping of the Ocean Topography 339 7.2.1 Geoid Measurement 339 7.2.2 Surface Wave Effects 343 7.2.3 Surface Wind Effects 345 7.2.4 Dynamic Ocean Topography 345 7.2.5 Ancillary Measurements 349 7.3 Surface Wind Mapping 351 7.3.1 Observations Required 352 7.3.2 Nadir Observations 355 7.4 Ocean Surface Imaging 356 7.4.1 Radar Imaging Mechanisms 356 7.4.2 Examples of Ocean Features on Radar Images 359 7.4.3 Imaging of Sea Ice 361 7.4.4 Ocean Color Mapping 363 7.4.5 Ocean Surface Temperature Mapping 365 7.4.6 Ocean Salinity Mapping 370 Exercises 371 References and Further Reading 372 8 Basic Principles of Atmospheric Sensing and Radiative Transfer 377 8.1 Physical Properties of the Atmosphere 377 8.2 Atmospheric Composition 380 8.3 Particulates and Clouds 381 8.4 Wave Interaction Mechanisms in Planetary Atmospheres 383 8.4.1 Resonant Interactions 383 8.4.2 Spectral Line Shape 387 8.4.3 Nonresonant Absorption 389 8.4.4 Nonresonant Emission 391 8.4.5 Wave Particle Interaction, Scattering 391 8.4.6 Wave Refraction 392 8.5 Optical Thickness 392 8.6 Radiative Transfer Equation 393 8.7 Case of a Nonscattering Plane Parallel Atmosphere 395 8.8 Basic Concepts of Atmospheric Remote Sounding 396 8.8.1 Basic Concept of Temperature Sounding 397 8.8.2 Basic Concept for Composition Sounding 399 8.8.3 Basic Concept for Pressure Sounding 399 8.8.4 Basic Concept of Density Measurement 399 8.8.5 Basic Concept of Wind Measurement 399 Exercises 400 References and Further Reading 401 9 Atmospheric Remote Sensing in the Microwave Region 403 9.1 Microwave Interactions with Atmospheric Gases 403 9.2 Basic Concept of Downlooking Sensors 404 9.2.1 Temperature Sounding 406 9.2.2 Constituent Density Profile: Case of Water Vapor 408 9.3 Basic Concept for Uplooking Sensors 411 9.4 Basic Concept for Limblooking Sensors 412 9.5 Inversion Concepts 415 9.6 Basic Elements of Passive Microwave Sensors 418 9.7 Surface Pressure Sensing 420 9.8 Atmospheric Sounding by Occultation 420 9.9 Microwave Scattering by Atmospheric Particles 424 9.10 Radar Sounding of Rain 424 9.11 Radar Equation for Precipitation Measurement 427 9.12 The Tropical Rainfall Measuring Mission (TRMM) 428 9.13 Rain Cube 429 9.14 CloudSat 429 9.15 Cassini Microwave Radiometer 433 9.16 Juno Microwave Radiometer (MWR) 433 Exercises 433 References and Further Reading 434 10 Millimeter and Submillimeter Sensing of Atmospheres 440 10.1 Interaction with Atmospheric Constituents 440 10.2 Downlooking Sounding 442 10.3 Limb Sounding 444 10.4 Elements of a Millimeter Sounder 447 10.5 Submillimeter Atmospheric Sounder 453 Exercises 455 References and Further Reading 456 11 Atmospheric Remote Sensing in the Visible and Infrared 458 11.1 Interaction of Visible and Infrared Radiation with the Atmosphere 458 11.1.1 Visible and Near-Infrared Radiation 458 11.1.2 Thermal Infrared Radiation 461 11.1.3 Resonant Interactions 463 11.1.4 Effects of Scattering by Particulates 463 11.2 Downlooking Sounding 466 11.2.1 General Formulation for Emitted Radiation 466 11.2.2 Temperature Profile Sounding 467 11.2.3 Simple Case Weighting Functions 469 11.2.4 Weighting Functions for Off-Nadir Observations 470 11.2.5 Composition Profile Sounding 471 11.3 Limb Sounding 472 11.3.1 Limb Sounding by Emission 472 11.3.2 Limb Sounding by Absorption 474 11.3.3 Illustrative Example: Pressure Modulator Radiometer 474 11.3.4 Illustrative Example: Fourier Transform Spectroscopy 476 11.4 Sounding of Atmospheric Motion 479 11.4.1 Passive Techniques 479 11.4.2 Passive Imaging of Velocity Field: Helioseismology 482 11.4.3 Multi-Angle Imaging SpectroRadiometer (MISR) 484 11.4.4 Multi-Angle Imager for Aerosols (MAIA) 488 11.4.5 Active Techniques 489 11.5 Laser Measurement of Wind 489 11.6 Atmospheric Sensing at Very Short Wavelengths 490 Exercises 491 References and Further Reading 492 12 Ionospheric Sensing 497 12.1 Properties of Planetary Ionospheres 497 12.2 Wave Propagation in Ionized Media 498 12.3 Ionospheric Profile Sensing by Topside Sounding 501 12.4 Ionospheric Profile by Radio Occultation 503 Exercises 505 References and Further Reading 506 Appendix A: Use of Multiple Sensors for Surface Observations 507 Appendix B: Summary of Orbital Mechanics Relevant to Remote Sensing 511 Appendix C: Simplified Weighting Functions 521 Appendix D: Compression of a Linear FM Chirp Signal 524 Index 528

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Book SynopsisBOW-TIE INDUSTRIAL RISK MANAGEMENT ACROSS SECTORS Explore an approachable but rigorous treatment of systematic barrier-based approaches to risk management and failure analysisIn Bow-Tie Industrial Risk Management Across Sectors: A Barrier-Based Approach, accomplished researcher and author Luca Fiorentini delivers a practical guide to risk management tools, with a particular emphasis on a systematic barrier-based approach called bow-tie. The book includes discussions of two barrier-based methods, Bow-Tie and Layers of Protection Analysis (LOPA), for risk assessment, and one barrier-based method for incident analysis, Barrier Failure Analysis (BFA). The author also describes a traditional methodRoot Cause Analysisand three quantitative methodsFMEA/FMECA, Fault Tree (FTA), and Event Tree (ETA) with a discussion about their link with barriers.Written from the ground up to be in full compliance with recent ISO 31000 standards on enterprise risk management, and Table of ContentsList of Figures List of Tables List of Acronyms Preface 1 Riccardo Ghini Preface 2 Bernardino Chiaia Preface 3 Luca Marmo Preface 4 Giuseppe Conti Preface 5 Claudio De Angelis Preface 6 Damiano Tranquilli Preface 7 Enzo Matticoli Preface 8 Salvatore Bagnato Author Preface Acknowledgements Chapter 1 Introduction to Risk and Risk Management 1.1 Risk Is Everywhere, and Risk Management Became a Critical Issue in Several Sectors 1.2 ISO 31000 Standard 1.3 ISO 31000 Risk Management Workflow 1.4 Uncertainty and the Human Factor 1.5 Enterprise Complexity and (Advanced) Risk Management (ERM) 1.6 Proactive and Reactive Culture of Organizations Dealing with Risk Management 1.7 A Systems Approach to Risk Management Chapter 2 Bow-Tie Method 2.1 Hazards and Risks 2.2 Methods of Risk Management 2.3 The Bow-Tie Method 2.4 The Bow-Tie Method and the Risk Management Workflow from ISO 31000 2.5 Application of Bow-Ties 2.6 Level of Abstraction 2.7 Building a Bow-Tie 2.8 Hazards 2.9 Top Events 2.10 Threats 2.11 Consequences 2.12 Barriers 2.13 Escalation Factors and Associated Barriers 2.14 Layer of Protection Analysis (LOPA): A Quantified Bow-Tie to Measure Risks 2.15 Bow-Tie as a Quantitative Method to Measure Risks and Develop a Dynamic Quantified Risk Register 2.16 Advanced Bow-Ties: Chaining and Combination Chapter 3 Barrier Failure Analysis 3.1 Accidents, Near-Misses, and Non-Conformities in Risk Management 3.2 The Importance of Operational Experience 3.3 Principles of Accident Investigation 3.4 The Barrier Failure Analysis (BFA) 3.5 From Root Cause Analysis (RCA) to BFA 3.6 BFA from Bow-Ties Chapter 4 Workflows and Case Studies 4.1 Bow-Tie Construction Workflow with a Step-by-Step Guide 4.2 LOPA Construction Workflow with a Step-by-Step Guide 4.3 BFA Construction Workflow with a Step-by-Step Guide 4.4 Worked Examples Conclusions Appendix 1 Bow-Tie Easy Guide Appendix 2 BFA Easy Guide Appendix 3 Human Error and Reliability Assessment (HRA) References and Further Reading Index

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Book SynopsisA comprehensive guide to Fog and Edge applications, architectures, and technologies Recent years have seen the explosive growth of the Internet of Things (IoT): the internet-connected network of devices that includes everything from personal electronics and home appliances to automobiles and industrial machinery. Responding to the ever-increasing bandwidth demands of the IoT, Fog and Edge computing concepts have developed to collect, analyze, and process data more efficiently than traditional cloud architecture. Fog and Edge Computing: Principles and Paradigms provides a comprehensive overview of the state-of-the-art applications and architectures driving this dynamic field of computing while highlighting potential research directions and emerging technologies. Exploring topics such as developing scalable architectures, moving from closed systems to open systems, and ethical issues rising from data sensing, this timely book addresses both the challTable of ContentsList of Contributors xix Preface xxiii Acknowledgments xxvii Part I Foundations 1 1 Internet of Things (IoT) and New Computing Paradigms 3 Chii Chang, Satish Narayana Srirama, and Rajkumar Buyya 1.1 Introduction 3 1.2 Relevant Technologies 6 1.3 Fog and Edge Computing Completing the Cloud 8 1.3.1 Advantages of FEC: SCALE 8 1.3.2 How FEC AchievesThese Advantages: SCANC 9 1.4 Hierarchy of Fog and Edge Computing 13 1.5 Business Models 16 1.6 Opportunities and Challenges 17 1.7 Conclusions 20 References 21 2 Addressing the Challenges in Federating Edge Resources 25 Ahmet Cihat Baktir, Cagatay Sonmez, CemErsoy, Atay Ozgovde, and Blesson Varghese 2.1 Introduction 25 2.2 The Networking Challenge 27 2.3 The Management Challenge 34 2.4 Miscellaneous Challenges 40 2.5 Conclusions 45 References 45 3 Integrating IoT + Fog + Cloud Infrastructures: System Modeling and Research Challenges 51 Guto Leoni Santos,Matheus Ferreira, Leylane Ferreira, Judith Kelner, Djamel Sadok, Edison Albuquerque, Theo Lynn, and Patricia Takako Endo 3.1 Introduction 51 3.2 Methodology 52 3.3 Integrated C2F2T Literature by Modeling Technique 55 3.4 Integrated C2F2T Literature by Use-Case Scenarios 65 3.5 Integrated C2F2T Literature by Metrics 68 3.6 Future Research Directions 72 3.7 Conclusions 73 Acknowledgments 74 References 75 4 Management and Orchestration of Network Slices in 5G, Fog, Edge, and Clouds 79 Adel Nadjaran Toosi, RedowanMahmud, Qinghua Chi, and Rajkumar Buyya 4.1 Introduction 79 4.2 Background 80 4.3 Network Slicing in 5G 83 4.4 Network Slicing in Software-Defined Clouds 87 4.5 Network Slicing Management in Edge and Fog 91 4.6 Future Research Directions 93 4.7 Conclusions 96 Acknowledgments 96 References 96 5 Optimization Problems in Fog and Edge Computing 103 Zoltán Ádám Mann 5.1 Introduction 103 5.2 Background / RelatedWork 104 5.3 Preliminaries 105 5.4 The Case for Optimization in Fog Computing 107 5.5 Formal Modeling Framework for Fog Computing 108 5.6 Metrics 109 5.6.5 Further Quality Attributes 112 5.7 Optimization Opportunities along the Fog Architecture 113 5.8 Optimization Opportunities along the Service Life Cycle 114 5.9 Toward a Taxonomy of Optimization Problems in Fog Computing 115 5.10 Optimization Techniques 117 5.11 Future Research Directions 118 5.12 Conclusions 119 Acknowledgments 119 References 119 Part II Middlewares 123 6 Middleware for Fog and Edge Computing: Design Issues 125 Madhurima Pore, Vinaya Chakati, Ayan Banerjee, and Sandeep K. S. Gupta 6.1 Introduction 125 6.2 Need for Fog and Edge Computing Middleware 126 6.3 Design Goals 126 6.4 State-of-the-Art Middleware Infrastructures 128 6.5 System Model 129 6.6 Proposed Architecture 131 6.7 Case Study Example 136 6.8 Future Research Directions 137 6.9 Conclusions 139 References 139 7 A Lightweight Container Middleware for Edge Cloud Architectures 145 David von Leon, LorenzoMiori, Julian Sanin, Nabil El Ioini, Sven Helmer, and Claus Pahl 7.1 Introduction 145 7.2 Background/RelatedWork 146 7.3 Clusters for Lightweight Edge Clouds 149 7.4 Architecture Management – Storage and Orchestration 152 7.5 IoT Integration 159 7.6 Security Management for Edge Cloud Architectures 159 7.7 Future Research Directions 165 7.8 Conclusions 166 References 167 8 Data Management in Fog Computing 171 Tina Samizadeh Nikoui, Amir Masoud Rahmani, and Hooman Tabarsaied 8.1 Introduction 171 8.2 Background 172 8.3 Fog Data Management 174 8.4 Future Research and Direction 186 8.5 Conclusions 186 References 188 9 Predictive Analysis to Support Fog Application Deployment 191 Antonio Brogi, Stefano Forti, and Ahmad Ibrahim 9.1 Introduction 191 9.2 Motivating Example: Smart Building 193 9.3 Predictive Analysis with FogTorch 197 9.4 Motivating Example (continued) 206 9.5 Related Work 207 9.6 Future Research Directions 214 9.7 Conclusions 216 References 217 10 Using Machine Learning for Protecting the Security and Privacy of Internet of Things (IoT) Systems 223 Melody Moh and Robinson Raju 10.1 Introduction 223 10.2 Background 234 10.3 Survey of ML Techniques for Defending IoT Devices 242 10.4 Machine Learning in Fog Computing 248 10.4.1 Introduction 248 10.5 Future Research Directions 252 10.6 Conclusions 252 References 253 Part III Applications and Issues 259 11 Fog Computing Realization for Big Data Analytics 261 Farhad Mehdipour, Bahman Javadi, AniketMahanti, and Guillermo Ramirez-Prado 11.1 Introduction 261 11.2 Big Data Analytics 262 11.3 Data Analytics in the Fog 267 11.4 Prototypes and Evaluation 272 11.4.1 Architecture 272 11.4.2 Configurations 274 11.5 Case Studies 277 11.6 Related Work 282 11.7 Future Research Directions 287 11.8 Conclusions 287 References 288 12 Exploiting Fog Computing in Health Monitoring 291 Tuan Nguyen Gia and Mingzhe Jiang 12.1 Introduction 291 12.2 An Architecture of a Health Monitoring IoT-Based System with Fog Computing 293 12.3 Fog Computing Services in Smart E-Health Gateways 297 12.4 System Implementation 304 12.5 Case Studies, Experimental Results, and Evaluation 308 12.6 Discussion of Connected Components 313 12.7 Related Applications in Fog Computing 313 12.8 Future Research Directions 314 12.9 Conclusions 314 References 315 13 Smart Surveillance Video Stream Processing at the Edge for Real-Time Human Objects Tracking 319 Seyed Yahya Nikouei, Ronghua Xu, and Yu Chen 13.1 Introduction 319 13.2 Human Object Detection 320 13.3 Object Tracking 327 13.4 Lightweight Human Detection 335 13.5 Case Study 337 13.6 Future Research Directions 342 13.7 Conclusions 343 References 343 14 Fog Computing Model for Evolving Smart Transportation Applications 347 M. Muzakkir Hussain,Mohammad Saad Alam, and M.M. Sufyan Beg 14.1 Introduction 347 14.2 Data-Driven Intelligent Transportation Systems 348 14.3 Mission-Critical Computing Requirements of Smart Transportation Applications 351 14.4 Fog Computing for Smart Transportation Applications 354 14.5 Case Study: Intelligent Traffic Lights Management (ITLM) System 359 14.6 Fog Orchestration Challenges and Future Directions 362 14.7 Future Research Directions 364 14.8 Conclusions 369 References 370 15 Testing Perspectives of Fog-Based IoT Applications 373 Priyanka Chawla and Rohit Chawla 15.1 Introduction 373 15.2 Background 374 15.3 Testing Perspectives 376 15.4 Future Research Directions 393 15.5 Conclusions 405 References 406 16 Legal Aspects of Operating IoT Applications in the Fog 411 G. Gultekin Varkonyi, Sz. Varadi, and Attila Kertesz 16.1 Introduction 411 16.2 RelatedWork 412 16.3 Classification of Fog/Edge/IoT Applications 413 16.4 Restrictions of the GDPR Affecting Cloud, Fog, and IoT Applications 414 16.5 Data Protection by Design Principles 425 16.6 Future Research Directions 430 16.7 Conclusions 430 Acknowledgment 431 References 431 17 Modeling and Simulation of Fog and Edge Computing Environments Using iFogSim Toolkit 433 Redowan Mahmud and Rajkumar Buyya 17.1 Introduction 433 17.2 iFogSim Simulator and Its Components 435 17.3 Installation of iFogSim 436 17.4 Building Simulation with iFogSim 437 17.5 Example Scenarios 438 17.6 Simulation of a Placement Policy 450 17.7 A Case Study in Smart Healthcare 461 17.8 Conclusions 463 References 464 Index 467

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Book Synopsis5G Physical Layer Technologies Written in a clear and concise manner, this book presents readers with an in-depth discussion of the 5G technologies that will help move society beyond its current capabilities. It perfectly illustrates how the technology itself will benefit both individual consumers and industry as the world heads towards a more connected state of being. Every technological application presented is modeled in a schematic diagram and is considered in depth through mathematical analysis and performance assessment. Furthermore, published simulation data and measurements are checked. Each chapter of 5G Physical Layer Technologies contains texts, mathematical analysis, and applications supported by figures, graphs, data tables, appendices, and a list of up to date references, along with an executive summary of the key issues. Topics covered include: the evolution of wireless communications; full duplex communications and full dimension MIMO technologies; network virtualizaTable of ContentsPreface xvii Acknowledgements xix List of Mathematical Notation xxi List of Wireless Network Symbols xxiii List of Abbreviations xxv Structure of the Book xxix 1 Introduction 1 1.1 Motivations 1 1.2 Overview of Contemporary Cellular Wireless Networks 4 1.3 Evolution of Wireless Communications in 3GPP Releases 7 1.3.1 3GPP Release 8 7 1.3.2 3GPP Release 9 8 1.3.3 3GPP Release 10 8 1.3.4 3GPP Release 11 8 1.3.5 3GPP Release 12 9 1.3.6 3GPP Release 13 9 1.3.7 3GPP Release 14 9 1.3.8 3GPP Release 15 (5G phase 1) 10 1.3.9 3GPP Release 16 (5G phase 2) 10 1.4 Multiuser Wireless Network Capacity Regions 10 1.4.1 The Capacity Region for Multiuser Channel 12 1.4.2 Analysis of Degraded BC with Superposition Coding 12 1.4.3 The Capacity Region for Multiuser MIMO Channel 14 1.4.4 The MIMO MAC Capacity Region 14 1.4.5 The MIMO BC Capacity Region 17 1.5 Fading Wireless Channels 19 1.6 Multicell MIMO Channels 20 1.7 Green Wireless Communications for the Twenty-First Century 20 1.7.1 Network Power Consumption Model 22 1.7.2 Antenna Interface Losses 22 1.7.3 Power Amplifier (PA) 22 1.8 BS Power Model 25 1.8.1 Small-Signal RF Transceiver 25 1.8.2 Baseband (BB) Unit 25 1.8.3 Power Supply and Cooling 25 1.8.4 BS Power Consumption at Variable Load 26 1.9 Green Cellular Networks 28 1.10 Green Heterogeneous Networks 30 1.11 Summary 31 1.A Tutorials on Theory and Techniques of Optimization Mathematics: Basics 33 1.A.1 Optimization of Unconstrained Function with a Single Variable 33 1.A.2 Optimization of Unconstrained Function with Multiple Variables 34 1.A.3 The Hessian Matrix 35 1.B Theory of Optimization Mathematics 36 1.B.1 Constrained Optimization 37 1.B.2 Bordered Hessian Matrix HB 37 1.C Karush–Kuhn–Tucker (KKT) Conditions 39 References 41 2 5G Enabling Technologies: Small Cells, Full-Duplex Communications, and Full-Dimension MIMO Technologies 43 2.1 Introduction 43 2.2 The Rationale for 5G Enabling Technologies 45 2.3 Network Densification 46 2.4 Cloud-Based Radio Access Network (C-RAN) 49 2.4.1 Resource Management Between Macrocells and Small Cells 51 2.4.2 BBU-RRH Switching Schemes 53 2.4.3 Mobile Small Cells 54 2.4.4 Automatic Self-Organising Network (SON) 56 2.5 Cache-Enabled Small-Cell Networks (CE-SCNs) 57 2.5.1 File Delivery Performance Analysis of CE-SCN 58 2.5.2 Outage Probability and Average File Delivery Rate in CE-SC System 59 2.6 Full-Duplex (FD) Communications 61 2.6.1 Analysis of FD Communication 63 2.6.2 FD Transmission Between Two Nodes 64 2.6.3 Principles of Self-Interference 65 2.6.4 Theoretical Example Analysis of Antenna Cancellation 67 2.6.5 Infrastructure for FD Transmission 68 2.6.6 Full-Duplex MAC (FD-MAC) Protocol 71 2.7 Review of Reference Signals, Antenna Ports, and Channels 74 2.7.1 DL and UL Physical Channels 75 2.7.2 DL Reference Signals and Antenna Ports 75 2.7.3 UL Reference Signals 76 2.7.3.1 UL Reference Signal Sequence Generation 76 2.7.3.2 Demodulation Reference Signal for PUSCH 77 2.7.3.3 Demodulation Reference Signal for PUCCH 78 2.7.3.4 Sounding Reference Signal SRS 78 2.7.3.5 Random-Access Channel Preambles 78 2.8 Full-Dimension MIMO Technology 79 2.8.1 Full-Dimension MIMO (FD-MIMO) Analysis 81 2.8.2 FD-MIMO System Design Issues 82 2.8.3 3GPP Development of 3D Model for FD-MIMO System 82 2.8.3.1 Antenna Array Elements Radiation Patterns 82 2.8.3.2 Antenna Configurations 83 2.8.3.3 FD-MIMO Development 84 2.8.4 Beamformed CSI-RS Transmission 85 2.8.5 CSI Feedback for FD-MIMO Systems 86 2.9 Summary 88 2.A Notes on Machine Learning Algorithms 89 2.A.1 The Algorithm 89 2.B Outage Probability in CE-SC Networks 91 2.B.1.1 Analysis of Term i: 91 2.C Signal Power at the Receive Antenna after Antenna Cancellation of Self-Interference 94 References 95 Further Reading 98 3 5G Enabling Technologies: Network Virtualization and Wireless Energy Harvesting 99 3.1 Introduction 99 3.2 Network Sharing and Virtualization of Wireless Resources 100 3.2.1 Earlier Network Sharing 100 3.2.2 Functional Description of Network Sharing Nodes 102 3.2.2.1 User Equipment (UE) Functions 102 3.2.2.2 Radio Network Controller (RNC) Functions 103 3.2.2.3 Evolved Node B (eNB) Functions 103 3.2.2.4 Base Station Controller (BSC) Functions 103 3.2.2.5 Mobile Switching Centre (MSC) Functions 103 3.2.2.6 Mobility Management Entity (MME) Functions 104 3.2.3 Single BS Shared by a Set of Operators 104 3.3 Evolved Resource Sharing 107 3.3.1 Principle of Cellular Network Evolved Resource Sharing 109 3.3.2 Single-Level Resource Allocation Among Operators 109 3.3.3 Opportunistic Sharing-Based Resource Allocation 112 3.4 Network Functions Virtualization (NFV) 113 3.4.1 Virtualized Network Functions 116 3.4.2 Principles of the Network Functions Virtualization Infrastructure (NFVI) 116 3.5 vRAN Supporting Fronthaul 117 3.5.1 Splitting the Architecture 118 3.5.1.1 Downlink (DL) 118 3.5.1.2 Uplink (UL) 118 3.6 Virtual Evolved Packet Core (vEPC) 119 3.7 Virtualized Switches 121 3.8 Auction in Resource Provision 121 3.9 Hierarchical Combinatorial Auction Models 122 3.10 Energy-Harvesting Techniques 125 3.10.1 Fundamentals of Wireless Energy Harvesting 126 3.10.2 Wireless Powered Communications 129 3.10.3 Full-Duplex Wireless-Powered Communication Network 131 3.10.4 Wireless Power Transfer in Cellular Networks 133 3.10.4.1 The Outage Constraint at BSs 134 3.10.4.2 The Power Outage Constraint at PBs 135 3.10.4.3 Hybrid Network Mobiles with Large Energy Storage 135 3.10.4.4 Hybrid Network Mobiles with Small Energy Storage 135 3.10.5 Harvested Energy Calculation 136 3.10.5.1 Energy Harvested from a FD BS (configuration 1) 136 3.10.5.2 Energy Harvested from PBs (configuration 2) 137 3.11 Integrated Energy and Spectrum Harvesting for 5G Communications 138 3.12 Energy and Spectrum Harvesting Cooperative Sensing Multiple Access Control (MAC) Protocol 140 3.13 Millimetre Wave (mmWave) Energy Harvesting 141 3.13.1 mmWave Network Model 141 3.13.2 mmWave Channel Model 142 3.13.3 Antenna Model 143 3.14 Analysis of mmWave Energy-Harvesting Technique 144 3.14.1 Connected User Case 145 3.15 Summary 145 References 146 Further Reading 148 4 5G Enabling Technologies: Narrowband Internet of Things and Smart Cities 151 4.1 Introduction to the Internet of Things (IoT) 151 4.2 IoT Architecture 152 4.2.1 Provisioning and Authentication 153 4.2.2 Configuration and Control 153 4.2.3 Monitoring and Diagnostics 153 4.2.4 Software Updates and Maintenance 154 4.3 Layered IoT Architecture 154 4.4 IoT Security Issues 155 4.5 Narrowband IoT 155 4.5.1 NB-IoT Modes of Operation 155 4.5.2 NB-IoT Transmission Options 156 4.5.2.1 DL Transmission Method 156 4.5.2.2 UL Transmission Method 156 4.6 DL Narrowband Physical Channels and Reference Signals 156 4.6.1 DL Physical Broadcast Channel (DPBCH) 156 4.6.2 Repetition Code SNR Gain Analysis 158 4.6.3 Narrowband Physical DL Shared Channel (NPDSCH) and Control Channel (NPDCCH) 159 4.6.4 Narrowband Reference Signal (NRS) 160 4.6.5 NB-IoT Primary Synchronization Signal (NPSS) 160 4.6.6 NB-IoT Secondary Synchronization Signal (NSSS) 163 4.6.7 Narrowband Positioning Reference Signal (NPRS) 165 4.7 UL Narrowband Physical Channels and Reference Signals 169 4.7.1 Narrowband Physical UL Shared Channel (NPUSCH) 169 4.7.2 Narrowband Physical Random-Access Channel (NPRACH) 170 4.7.3 Demodulation Reference Signals 172 4.7.3.1 DMRS Sequence for NPUSCH Format1 172 4.7.3.2 DMRS Sequence for NPUSCH Format2 173 4.8 NB-IoT System Design 174 4.8.1 LTE System Specifications 174 4.8.2 Bandwidth Perspective-Effective BW 175 4.8.2.1 Capacity Extension Consideration 175 4.8.2.2 Coverage Extension Consideration 176 4.8.3 Battery Usage Efficiency 177 4.9 Smart Cities 179 4.10 EU Smart City Model 180 4.10.1 Smart Economy 180 4.10.2 Smart Mobility 180 4.10.3 Smart Environment 181 4.10.4 Smart People 181 4.10.5 Smart Living 182 4.10.6 Smart Governance 183 4.11 Summary 184 4.A Minimum Time Required to Transmit Message M When B→∞ 185 References 186 Further Reading 188 5 Millimetre Wave Massive MIMO Technology 189 5.1 Introduction 189 5.2 Capacity of Point-to-Point MIMO Systems 190 5.2.1 Capacity of SIMO/MISO Links 190 5.2.2 Capacity of MIMO Links 190 5.3 Outage of Point-to-Point MIMO Links 193 5.4 Diversity-Multiplexing Tradeoffs 194 5.5 Multi-User-MIMO (MU-MIMO) Single-Cell Systems 195 5.5.1 UL Channel Capacity 196 5.5.2 DL Channel Capacity 196 5.6 Multi-User MIMO Multi-Cell System Representation 197 5.7 Sum Capacity of Broadcast Channels 198 5.7.1 Degraded BC 198 5.7.2 Nondegraded Gaussian Vector BC 200 5.7.3 MIMO BC Sum Capacity Using DPC 201 5.7.4 DPC Scheme Research Development for Application in the MIMO BC 205 5.7.5 Review of the DPC Scheme for Massive MIMO Systems 206 5.8 mmWave Massive MIMO Systems 206 5.8.1 Introduction 206 5.8.2 Reciprocity Model for Point-to-Point Links 208 5.8.3 Reciprocity Analysis 208 5.8.4 Reciprocity Analysis Extension to Multiple Users 209 5.8.5 Reciprocity and Pilot Contamination 210 5.9 MIMO Beamforming Schemes 210 5.9.1 Introduction to Beamforming 210 5.9.2 Analysis of Beamforming 210 5.10 BF Schemes 212 5.10.1 The Delay and Sum BF 212 5.10.2 Null Steering Beamformers 213 5.10.3 Beamformer Using a Reference Signal 214 5.11 mmWave BF Systems 215 5.11.1 Introduction 215 5.11.2 Hybrid Digital and Analogue BF for mmWave Antenna Arrays 216 5.12 Massive MIMO Hardware 221 5.13 mmWave Market and Choice of Technologies 226 5.14 Summary 227 5.A Derivation of Eq. (5.14) for M = 3, N = 2 229 5.B MUSIC Algorithm Used in Estimating the Direction of Signal Arrival 230 5.B.1 Introduction 230 5.B.2 MUSIC Algorithm for Estimating 1D Array AOAs 230 5.B.3 MUSIC Algorithm for Estimating 1D Linear Hybrid Array AOAs 233 5.B.4 MUSIC Algorithm for Estimating 2D Array AOAs. 234 References 236 6 mmWave Propagation Modelling: Atmospheric Gaseous and Rain Losses 241 6.1 Introduction 241 6.2 Contemporary Radio Wave Propagation Models 242 6.2.1 AT&T Propagation Model 243 6.2.2 Stanford University Interim (SUI) Propagation Model 244 6.2.3 Modified SUI Model for mmWave Propagation 245 6.3 Atmospheric Gaseous Losses 249 6.3.1 Introduction 249 6.3.2 Attenuation by Atmospheric Gases 250 6.3.3 ITU Recommendations for Modelling Atmospheric Gaseous Attenuation 252 6.3.4 Temperature and Pressure 254 6.3.5 Water-Vapour Pressure 254 6.4 Dry Atmosphere for Attenuation Calculations 256 6.5 Calculation of Atmospheric Gaseous Attenuation Using ITU-R Recommendations 256 6.6 Rain Attenuation at mmWave Frequency Bands 257 6.6.1 Introduction 257 6.6.2 Research Development 258 6.7 The Physical Rain (EXCELL) Capsoni Model 259 6.7.1 Model Cells 260 6.7.2 Monoaxial Cell and Biaxial Cell Models 261 6.7.3 Fitting the Model to the Local Meteorological Data 261 6.7.4 Development of the Capsoni EXCELL Model 263 6.8 ITU Recommendations on Rainfall Rate Conversion 265 6.8.1 Introduction 265 6.8.2 Recommendations ITU–R P.530-17 and ITU-R P.838-3 266 6.8.2.1 Linear and Circular Polarization 266 6.8.3 Recommendations ITU-R P.1144-6 and ITU-R P.837-7 269 6.8.4 Recommendation ITU R P.1510-1 271 6.9 Attenuation from Snow and Hail 272 6.9.1 EM Propagation Properties Through Snow 272 6.9.2 Transmission Model for Ice Slab 277 6.9.3 Empirical Model for Snow Attenuation 278 6.9.4 Strong Fluctuation Theory 281 6.10 Snow Dielectric Constant Formulation Using Strong Fluctuation Theory 281 6.11 Summary 282 6.A Bilinear Interpolation 283 References 285 7 mmWave Propagation Modelling –Weather, Vegetation, and Building Material Losses 289 7.1 Introduction 289 7.2 Attenuation Due to Clouds and Fog 290 7.3 The Microphysical Modelling 290 7.4 Modified Gamma Droplets Size Distribution 292 7.4.1 Analysis of the Size Distribution 292 7.4.2 Skewness and Kurtosis of Modified Gamma Distribution 294 7.5 Rayleigh and Mie Scattering Distributions 297 7.6 ITU Empirical Model for Clouds and Fog Attenuation Calculation 298 7.7 Building Material Attenuation 300 7.7.1 Penetration Losses for Various Building Materials 300 7.7.2 Penetration Losses for Indoor Obstructions in an Office Environment at 28 GHz 301 7.7.3 The Penetration Loss for the Exterior of the House 301 7.8 Modelling the Penetration Loss for Building Materials 302 7.9 Modelling the Penetration Loss for Indoor Environments 302 7.10 Attenuation of Propagated Radio Waves in Vegetation 303 7.10.1 Foliage Propagation Path Models 303 7.10.2 Review of Horizontal Empirical Models 304 7.10.3 Weissberger MED Vegetation Loss Model 304 7.10.4 Recommendation ITU Vegetation Loss Model 305 7.10.5 The Maximum Attenuation (MA) Vegetation Loss Model 305 7.10.6 The Modified and Fitted ITU-R (MITU-R) and (FITU-R) Vegetation Loss Models 307 7.10.7 The COST235 Model 308 7.10.8 The Nonzero Gradient (NZG) Vegetation Loss Model 308 7.10.9 The Dual-Gradient (DG) Vegetation Loss Model 310 7.10.10 Indoor Vegetation Attenuation Measurement 312 7.11 Review of Vegetation Loss Using Empirical Models for Slant Propagation Path 312 7.12 Microphysical Modelling of Vegetation Attenuation 315 7.13 Attenuation in Vegetation Due to Diffraction 321 7.14 Recommendation ITU-R 526-7 321 7.15 Propagation Modes Connected with the Vegetation Foliage 322 7.15.1 Calculation of the Attenuation of the Top Diffracted Component 323 7.15.2 Attenuation Components Due to Side Diffraction 324 7.15.3 Attenuation of the Ground Reflection Component 325 7.15.4 Attenuation of the ‘Through’ or Scattered Component 326 7.15.5 Combination of the Individual Attenuation Components 326 7.16 Radiative Energy Transfer (RET)Theory 327 7.16.1 Introduction 327 7.16.2 RET Attenuation Prediction Model 329 7.16.2.1 Scattering Loss for Slant Radiation 331 7.16.2.2 Scattering Loss for Normal Radiation 332 7.16.3 Determination of the Medium-Dependent Parameters from Measurement Data 333 7.17 Summary 336 7.A Lognormal Distributed Random Numbers 336 7.B Derivation of Cloud Water Droplets Mode Radius 338 7.C The Complex Relative Permittivity and the Complex Relative Refractive Index Relationship 339 7.D Step-by-Step Tutorial to Calculate the Excess Through (Scatter) Loss in Vegetation 340 References 342 8 Wireless Channel Modelling and Array Mutual Coupling 347 8.1 Key Parameters in Wireless Channel Modelling 347 8.1.1 Doppler Spread 347 8.1.2 Coherence Time 348 8.1.3 Delay Spread 349 8.1.4 Coherence Bandwidth 350 8.2 Signal Fading 351 8.2.1 Small-Scale Fading Channels 351 8.2.1.1 Slow Fading 351 8.2.1.2 Fast Fading 351 8.2.1.3 Frequency Selective Fading 352 8.2.2 Large-Scale Fading Channels 352 8.2.3 Statistics of Wireless Channel 352 8.3 MIMO Channel Models 353 8.3.1 MIMO Channel Model Based on Perfect CSIT or CSIR 353 8.3.2 MIMO Channel Model Based on Perfect CSIR and CDIT 353 8.3.3 MIMO Channel Model Based on Perfect CDIT and CDIR 354 8.4 Massive MIMO Channel Models 355 8.4.1 i.i.d. Rayleigh Channel Model 355 8.5 Correlation Inspired Channel Models 356 8.5.1 Introduction 356 8.5.2 Formation of Kronecker Channel Model 359 8.6 Weichselberger Channel Model 360 8.6.1 Introduction 360 8.6.2 Formulation of Weichselberger Channel Model 362 8.7 Virtual Channel Representation 365 8.8 Mutual Coupling in Wireless Antenna Systems 367 8.8.1 Array Mutual Coupling 367 8.8.2 Mutual Coupling of Antenna Arrays Operating in Transmit and Receive Modes 368 8.8.3 BS Antennas Mutual Coupling in MIMO Systems 369 8.8.4 Total Power Collected by the Receiving Array 370 8.9 Mutual Coupling Constrained on Transmit Radiated Power 372 8.10 Analysis Voltage Induced at the Receive Antenna Port 372 8.11 MIMO Channel Capacity of Mutually Coupled Wireless Systems 374 8.11.1 Interference Consideration 374 8.11.2 Users Receiver Noise Consideration 375 8.11.3 Formulation of MIMO Channel Capacity 376 8.12 Summary 378 8.A S-Parameters 380 8.B Power Collected by the Receive Array is Maximum When S11 = SHRR 382 References 384 Further Reading 386 9 Massive Array Configurations and 3D Channel Modelling 387 9.1 Massive Antenna Array Configurations at BS 387 9.2 Uniform Linear Arrays 387 9.3 Rectangular Planar Arrays 388 9.4 Circular Arrays 388 9.5 Cylindrical Arrays 390 9.6 Spherical Antenna Arrays 391 9.7 Microstrip Patch Antennas 394 9.8 EU WINNER Projects 398 9.9 Spatial MIMO Channel Model in 3GPP Release 6 399 9.9.1 BS and MS Antenna Patterns 400 9.9.2 Per-Path BS and MS Angle Spread (AS) 400 9.9.3 Per-Path BS and MS Power Azimuth Spectrum 400 9.9.4 Definitions of BS and MS Angle Parameters for a Scattering Environment 402 9.10 The Scattering Environments 403 9.11 Large-Scale Parameters (LSPs) 403 9.11.1 Correlation Between Channel Parameters in 3GPP Release 6 405 9.11.2 Generation of Values of DS, AS, SF 405 9.12 2D Spatial Channel Models (SCMs) 407 9.12.1 Spatial Channel Models with No Antennas Polarization 407 9.12.2 Path Loss (PL) 407 9.12.3 2D Channel Coefficients 408 9.12.4 Generating Channel Parameters for Urban, Suburban Macrocell, and Urban Microcell Environments 408 9.13 2D Spatial Channel Models (SCMs) with Antenna Polarization 411 9.13.1 2D Spatial Channel Model (SCMs) with Polarized Antennas 412 9.14 3D Channel Models in 3GPP Release 14 413 9.14.1 Coordinate Systems 413 9.14.2 Local and Global Coordinate Systems 413 9.14.3 Scenarios Descriptions 416 9.14.4 Antenna Modelling 417 9.14.5 Probability of LOS 418 9.14.6 Estimate of the LOS Probability Using Ray Tracing 419 9.14.7 LOS Probability in 3GPP Release 14 420 9.14.8 Path Loss 422 9.14.8.1 UMacell Path Loss 422 9.14.8.2 LOS Channel Environment 422 9.14.8.3 Non-Line-of-Sight (NLOS) 422 9.14.9 Fast-Fading Model for 3D Channels 422 9.14.10 Large-Scale Parameters 424 9.14.11 Small-Scale Parameters 428 9.14.11.1 Channel Coefficients for NLOS Channel Environment 431 9.14.11.2 Channel Coefficients for LOS Channel Environment 432 9.14.11.3 Oxygen Absorption 433 9.14.11.4 Blockage Loss 433 9.15 Blockage Modelling 434 9.15.1 Blockages Modelling Using Random Shape Theory 434 9.15.2 Analysis Using Random Shape Theory to Model Buildings 436 9.15.3 Distance to Closest BS with Building Blockage 436 9.16 Summary 437 9.A Laplace Random Variables Distribution 438 9.B Spherical Coordinates 439 9.C Wrapped Gaussian Distribution 440 References 440 10 Massive MIMO Channel Estimation Schemes 443 10.1 Introduction 443 10.1.1 Cellular MIMO Channels 443 10.2 Massive MIMO Channels Definition 445 10.2.1 Massive MIMO UL Definition 445 10.3 Time-Division Duplexing (TDD) Transmission Protocol 447 10.4 Massive MIMO Channel Estimation in Noncooperative TDD Networks 447 10.4.1 Uplink Pilots’ Transmission Using the Aligned Pilot Scheme 448 10.4.2 SINR for Uplink Data Transmission 449 10.4.3 SINR for Downlink Data Transmission 450 10.4.4 Massive MIMO Channels Estimation Using Time-Shifted Pilot Scheme (TSPS) 451 10.5 Channel Estimation Using Coordinated Cells in MIMO System 454 10.5.1 Bayesian Estimation of Uplink for All Users 455 10.5.2 Bayesian Desired Channel Estimation with Full Pilot Reuse 458 10.6 Bayesian Estimation of UL in a Massive MIMO System 460 10.6.1 Rule of Coordinated Pilot Allocation 461 10.6.2 Evaluation of the Coordinated Pilot Assignment Protocol 461 10.7 Arbitrary Correlated Rician Fading Channel 465 10.7.1 Estimation of Correlated Rician Channels Using MMSE Approach 465 10.7.2 Pilot Sequence Optimization for Channel Matrix Estimation 467 10.7.3 Optimal Length of Pilot Sequences 468 10.8 Massive MIMO Antennas Calibration 469 10.8.1 Argos Method 470 10.8.2 Mutual Coupling Calibration Antennas Method 473 10.9 Pre-precoding/Post-precoding Channel Calibration 479 10.10 Summary 481 10.A Noncooperative TDD Networks: Derivation of the Asymptotic Normalization Factor Equation 482 10.B Beamforming Vectors for Time-Shifted Pilot Scheme 483 10.C Derivation of equations (10.48b) and (10.49b) 484 References 486 11 Linear Precoding Strategies for Multi-User Massive MIMO Systems 489 11.1 Introduction 489 11.2 Group-Level and Symbol-Level Precoding 490 11.3 Linear Precoding Schemes 491 11.4 SU-MIMO Model 492 11.5 Multi-User MIMO Precoding System Model 493 11.5.1 Broadcast Channel (BC) System Model 493 11.5.2 Multiple Access Channels (MAC) System Model with Non-Equal Antennas at Each User 494 11.5.3 Linear Precoding for Massive MIMO MAC with Equal Antennas at Each User 495 11.6 Linear Multi-User Transmit Channel Inversion Precoding for BC 496 11.7 Zero-Forcing Precoding using the Wiesel et al. Method 497 11.7.1 Multi-User Linear Zero-Forcing (ZF) Precoding for BC 497 11.7.2 ZF Precoder Design with Total Transmit Power Constraint 498 11.7.3 Optimal ZF Precoding with per-Antenna Power Constraint 499 11.8 The Outage Probability 500 11.9 Precoding for MIMO Channels with Johan et al. Method 502 11.9.1 Introduction 502 11.9.2 ZF Transmit Filter F Matrix 503 11.9.3 ZF Receive Filter E Matrix 504 11.9.4 ZF Outage Probability for Minimum Transmit Power 505 11.9.5 ZF Precoder Design to Allocate Unequal Power 505 11.9.6 ZF Outage Probability for Unequal Power Allocation across Transmit Antennas 506 11.10 Matched Filter (MF) Precoding 507 11.10.1 Transmit MF F Matrix 507 11.10.2 Receive MF E Matrix 507 11.11 Wiener Filter (WF) Precoding 509 11.11.1 Transmit WF F Matrix 509 11.11.2 Receive WF Matrix 510 11.12 Regularized Zero-Forcing (RZF) Precoding 511 11.13 Block Diagonalization (BD) 514 11.13.1 Multi-User BD Precoding 514 11.13.2 BD Transmit Filter and Receive Filter Matrices 515 11.14 Transmit MF Precoding Filters and MMSE Receive Filters in MIMO Broadcast Channel 519 11.15 Linear Precoding Based on Truncated Polynomial Expansion 520 11.15.1 Introduction 520 11.15.2 Modelling the TPE Precoding for BC 521 11.16 Summary 525 11.A Derivation of the Scaling Factor 𝛽ZF 527 11.B ZF Precoder Design Optimum User Power in Unequal Power Allocation 527 11.C Transmit Matched Filter (MF) Precoding 529 11.D Wiener Filter (WF) Precoding 530 11.E MMSE Matrix 532 11.F SINR for MMSE Receiver for MF the Transmit Precoding 534 References 535 Index 539

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Book SynopsisAVERAGE CURRENT-MODE CONTROL OF DC-DC POWER CONVERTERS An authoritative one-stop guide to the analysis, design, development, and control of a variety of power converter systems Average Current-Mode Control of DC-DC Power Converters provides comprehensive and up-to-date information about average current-mode control (ACMC) of pulse-width modulated (PWM) dc-dc converters. This invaluable one-stop resource covers both fundamental and state-of-the-art techniques in average current-mode control of power electronic converters???featuring novel small-signal models of non-isolated and isolated converter topologies with joint and disjoint switching elements and coverage of frequency and time domain analysis of controlled circuits. The authors employ a systematic theoretical framework supported by step-by-step derivations, design procedures for measuring transfer functions, challenging end-of-chapter problems, easy-to-follow diagrams and illustrations, numerous exaTable of ContentsList of Symbols xiii About the Authors xvii Preface xix Acknowledgments xxi 1 Introduction 1 1.1 Principle of Operation of Conventional Average Current-Mode Control Technique 3 1.2 Principle of Operation of Modified Average Current-Mode Control Technique 6 1.3 Steady-State Operation 7 2 Average Current-Mode Control of Buck DC–DC Converter 9 2.1 Circuit Description, DC Characteristics, and Design 10 2.1.1 Circuit Description 10 2.1.2 DC Model 10 2.1.3 Design Example 12 2.2 Large-Signal and Small-Signal Models of PWM Buck Converter in CCM 13 2.3 Power Stage Transfer Functions 15 2.3.1 Duty Cycle-to-Output Voltage Transfer Function Tp 16 2.3.2 Duty Cycle-to-Inductor Current Transfer Function Tpi 18 2.3.3 Input Voltage-to-Output Voltage Transfer Function M 𝑣 20 2.3.4 Input Voltage-to-Inductor Current Transfer Function M 𝑣 i 21 2.3.5 Reverse Current Gain A i 22 2.3.6 Open-Loop Input Impedance Z i 24 2.3.7 Open-Loop Output Impedance Zo 26 2.4 Inner-Current Loop 27 2.4.1 Transfer Function of Filter and Non-inverting Amplifier Tf 29 2.4.2 Transfer Function of Pulse-Width Modulator Tm 30 2.4.3 Uncompensated Loop Gain Tki 30 2.4.4 Transfer Function of Control Circuit for Inner-Current Loop Tci 31 2.4.5 Compensated Loop Gain of Inner-Current Loop Ti 33 2.5 Closed-Loop Transfer Functions for Inner-Current Loop 34 2.5.1 Reference Voltage-to-Inductor Current Transfer Function Ticl 35 2.5.2 Reference Voltage-to-Output Voltage Transfer Function Tpicl 35 2.5.3 Input Voltage-to-Inductor Current Transfer Function Micl 36 2.5.4 Input Voltage-to-Output Voltage Transfer Function M𝑣icl 37 2.5.5 Input Impedance Ziicl 39 2.5.6 Output Impedance Zoicl 40 2.6 Outer-Voltage Loop 42 2.6.1 Transfer Function of Feedback Network 𝛽 42 2.6.2 Uncompensated Loop Gain for Outer-Voltage Loop Tk𝑣 42 2.6.3 Transfer Function of Control Circuit for Outer-Voltage Loop Tc𝑣 43 2.6.4 Compensated Loop Gain of Outer-Voltage Loop T𝑣 46 2.7 Closed-Loop Transfer Functions for Outer-Voltage Loop 46 2.7.1 Reference Voltage-to-Output Voltage Transfer Function Tpcl 46 2.7.2 Input Voltage to Duty-Cycle Transfer Function Md𝑣 47 2.7.3 Input Voltage-to-Output Voltage Transfer Function M𝑣cl 49 2.7.4 Input Impedance Zi𝑣cl 50 2.7.5 Output Impedance Zo𝑣cl 52 2.8 Comparison of Closed-Loop and Open-Loop Step Responses 55 2.8.1 Response of Output Voltage to Step Change in Input Voltage 55 2.8.2 Response of Output Voltage to Step Change in Duty Cycle, Current-Loop reference Voltage, and Voltage-Loop Reference Voltage 55 2.8.3 Response of Input Current to Step Change in Input Voltage 56 2.8.4 Response of Output Voltage to Step Change in Load Current 57 2.9 Summary 58 3 Average Current-Mode Control of Boost DC–DC Converter 61 3.1 Circuit Description, DC Characteristics, and Design 62 3.1.1 Circuit Description 62 3.1.2 DC Model 62 3.1.3 Design Example 65 3.2 Large-Signal and Small-Signal Models of PWM Boost Converter for CCM 66 3.3 Power-Stage Transfer Functions 67 3.3.1 Duty Cycle-to-Output Voltage Transfer Function Tp 68 3.3.2 Duty Cycle-to-Inductor Current Transfer Function Tpi 74 3.3.3 Input Voltage-to-Output Voltage Transfer Function M𝑣 80 3.3.4 Input Voltage-to-Inductor Current Transfer Function M𝑣i 81 3.3.5 Reverse Current Gain Ai 82 3.3.6 Open-Loop Input Impedance Zi 84 3.3.7 Open-Loop Output Impedance Zo 85 3.4 Inner-Current Loop 88 3.4.1 Transfer Function of Filter and Non-inverting Amplifier Tf 89 3.4.2 Transfer Function of Pulse-Width Modulator Tm 90 3.4.3 Uncompensated Loop Gain Tki 90 3.4.4 Transfer Function of Control Circuit Tci 91 3.4.5 Loop Gain of Inner-Current Loop Ti 93 3.5 Closed-Loop Transfer Functions for Inner-Current Loop 94 3.5.1 Reference Voltage-to-Inductor Current Transfer Function Ticl 94 3.5.2 Reference Voltage-to-Output Voltage Transfer Function Tpicl 95 3.5.3 Input Voltage-to-Inductor Current Transfer Function Micl 96 3.5.4 Input Voltage-to-Output Voltage Transfer Function M𝑣icl 98 3.5.5 Input Voltage-to-Duty Cycle Transfer Function Mdi 99 3.5.6 Input Impedance Ziicl 100 3.5.7 Output Impedance Zoicl 102 3.6 Outer-Voltage Loop 103 3.6.1 Transfer Function of Feedback Network 𝛽 104 3.6.2 Uncompensated Loop Gain for Outer-Voltage Loop Tk𝑣 105 3.6.3 Transfer Function of Control Circuit for Outer-Voltage Loop Tc𝑣 105 3.6.4 Compensated Loop Gain of Outer-Voltage Loop T𝑣 107 3.7 Closed-Loop Transfer Functions for Outer-Voltage Loop 107 3.7.1 Reference Voltage-to-Output Voltage Transfer Function Tpcl 108 3.7.2 Input Voltage-to-Duty Cycle Transfer Function Md𝑣 109 3.7.3 Input Voltage-to-Output Voltage Transfer Function M𝑣cl 110 3.7.4 Input Impedance Zi𝑣cl 112 3.7.5 Output Impedance Zo𝑣cl 114 3.8 Comparison of Closed-Loop and Open-Loop Step Responses 116 3.8.1 Response of Output Voltage to Step Change in Input Voltage 116 3.8.2 Response of Output Voltage to Step Change in Duty Cycle, Current-Loop Reference Voltage, and Voltage-Loop Reference Voltage 117 3.8.3 Response of Input Current to Step Change in Input Voltage 118 3.8.4 Response of Output Voltage to Step Change in Load Current 119 3.9 Summary 120 4 Average Current-Mode Control of Buck-Boost DC–DC Converter 121 4.1 Circuit Description, DC Model, and Design 122 4.1.1 Circuit Description 122 4.1.2 DC Model 122 4.1.3 Design Example 125 4.2 Large-Signal and Small-Signal Models of PWM Buck-Boost Converter in CCM 125 4.3 Power-Stage Transfer Functions 128 4.3.1 Duty Cycle-to-Output Voltage Transfer Function Tp 129 4.3.2 Duty Cycle-to-Inductor Current Transfer Function Tpi 134 4.3.3 Input Voltage-to-Output Voltage Transfer Function M𝑣 139 4.3.4 Input Voltage-to-Inductor Current Transfer Function M𝑣i 142 4.3.5 Reverse Current Gain Ai 143 4.3.6 Open-Loop Input Impedance Zi 145 4.3.7 Open-Loop Output Impedance Zo 147 4.4 Inner-Current Loop 150 4.4.1 Transfer Function of Filter Tf 152 4.4.2 Transfer Function of Pulse-Width Modulator Tm 153 4.4.3 Uncompensated Loop Gain Tki 154 4.4.4 Transfer Function of Compensation Circuit Tci 155 4.4.5 Compensated Loop Gain Ti 156 4.5 Closed-Inner Loop Transfer Functions 158 4.5.1 Reference Voltage-to-Inductor Current Transfer Function Ticl 160 4.5.2 Reference Voltage-to-Output Voltage Transfer Function Tpicl 161 4.5.3 Input Voltage-to-Inductor Current Transfer Function Micl 162 4.5.4 Input Voltage-to-Output Voltage Transfer Function M𝑣icl 163 4.5.5 Input Voltage-to-Duty Cycle Transfer Function Mdi 166 4.5.6 Input Impedance Ziicl 166 4.5.7 Output Impedance Zoicl 168 4.6 Outer-Voltage Loop 170 4.6.1 Transfer Function of Feedback Network 𝛽 172 4.6.2 Uncompensated Loop Gain Tk𝑣 173 4.6.3 Transfer Function of Control Circuit for Outer-Voltage Loop Tc𝑣 174 4.6.4 Compensated Loop Gain T𝑣 176 4.7 Closed-Loop Transfer Functions for Outer-Voltage Loop 176 4.7.1 Reference Voltage-to-Output Voltage Transfer Function Tpcl 177 4.7.2 Input Voltage-to-Duty Cycle Transfer Function Md𝑣 177 4.7.3 Input Voltage-to-Output Voltage Transfer Function M𝑣cl 179 4.7.4 Input Impedance Zi𝑣cl 181 4.7.5 Output Impedance Zo𝑣cl 183 4.8 Comparison of Closed-Loop and Open-Loop Step Responses 186 4.8.1 Response of Output Voltage to Step Change in Input Voltage 186 4.8.2 Response of Output Voltage to Step Change in Duty Cycle, Current-Loop reference Voltage, and Voltage-Loop Reference Voltage 187 4.8.3 Response of Input Current to Step Change in Input Voltage 188 4.8.4 Response of Output Voltage to Step Change in Load Current 188 4.9 Summary 189 5 Average Current-Mode Control of Flyback DC–DC Converter 191 5.1 Circuit Description, DC Model, and Design 192 5.1.1 Circuit Description 192 5.1.2 DC Model 193 5.1.3 Derivation of Equivalent Averaged Resistance 197 5.1.4 Design Example 200 5.2 Large-Signal and Small-Signal Models of PWM Flyback Converter in CCM 200 5.3 Power-Stage Transfer Functions 204 5.3.1 Duty Cycle-to-Output Voltage Transfer Function Tp 206 5.3.2 Duty Cycle-to-Inductor Current Transfer Function Tpi 214 5.3.3 Input Voltage-to-Output Voltage Transfer Function M𝑣 220 5.3.4 Input Voltage-to-Inductor Current Transfer Function M𝑣i 221 5.3.5 Reverse Current Gain Ai 223 5.3.6 Open-Loop Input Impedance Zi 226 5.3.7 Open-Loop Output Impedance Zo 228 5.4 Inner-Current Loop 229 5.4.1 Transfer Function of Filter and Non-inverting Amplifier Tf 231 5.4.2 Transfer Function of Pulse-Width Modulator Tm 233 5.4.3 Uncompensated Loop Gain Tki 233 5.4.4 Transfer Function of Compensation Circuit Tci 234 5.4.5 Compensated Loop Gain Ti 236 5.5 Closed-Loop Transfer Functions for Inner-Current Loop 238 5.5.1 Reference Voltage-to-Inductor Current Transfer Function Ticl 239 5.5.2 Reference Voltage-to-Output Voltage Transfer Function Tpicl 240 5.5.3 Input Voltage-to-Inductor Current Transfer Function Micl 241 5.5.4 Input Voltage-to-Output Voltage Transfer Function M𝑣icl 243 5.5.5 Input Voltage-to-Duty Cycle Transfer Function Mdi 244 5.5.6 Input Impedance Ziicl 245 5.5.7 Output Impedance Zoicl 246 5.6 Outer-Voltage Loop 248 5.6.1 Transfer Function of Feedback Network 𝛽 250 5.6.2 Uncompensated Loop Gain Tk𝑣 250 5.6.3 Transfer Function of Compensation Circuit Tc𝑣 251 5.6.4 Compensated Loop Gain T𝑣 253 5.7 Closed-Loop Transfer Functions for Outer-Voltage Loop 253 5.7.1 Reference Voltage-to-Output Voltage Transfer Function Tpcl 254 5.7.2 Input Voltage-to-Duty Cycle Transfer Function Md𝑣 254 5.7.3 Input Voltage-to-Output Voltage Transfer Function M𝑣cl 257 5.7.4 Input Impedance Zi𝑣cl 259 5.7.5 Output Impedance Zo𝑣cl 261 5.8 Comparison of Closed-Loop and Open-Loop Step Responses 262 5.8.1 Response of Output Voltage to Step Change in Input Voltage 262 5.8.2 Response of Output Voltage to Step Change in Duty Cycle, Current-Loop Reference Voltage, and Voltage-Loop Reference Voltage 264 5.8.3 Response of Input Current to Step Change in Input Voltage 265 5.8.4 Response of Output Voltage to Step Change in Load Current 266 5.9 Summary 266 References 269 Appendix A Design Equations for Continuous-Conduction Mode 275 A.1 Common Equations Needed for the Design of Converters 275 A.1.1 DC Output Power 275 A.1.2 DC Voltage Transfer Function 275 A.2 Specific Expressions for the Design of Converters in CCM 275 Appendix B MOSFET Parameters 277 Appendix C Diode Parameters 279 Appendix D Selected MOSFETs’ Spice Models 281 D.1 IRF430 281 D.2 IRF520 281 D.3 IRF150 281 D.4 IRF142 281 D.5 IRF840 282 D.6 IRF740 282 Appendix E Selected Diodes’ Spice Models 283 E.1 MUR1560 283 E.2 MBR10100 283 E.3 MBR1060 283 E.4 MUR2510 283 E.5 MBR2540 283 E.6 MBR4040 284 Appendix F Simulation Tools 285 F.1 SPICE Model of Power MOSFETs 285 F.1.1 SPICE NMOS Syntax 286 F.1.2 SPICE NMOS Model Syntax 286 F.1.3 SPICE PMOS Model Syntax 287 F.1.4 SPICE Subcircuit Model Syntax 287 F.2 Introduction to SPICE 288 F.2.1 Passive Components: Resistors, Capacitors, and Inductors 288 F.2.2 Transformer 288 F.2.3 Temperature 288 F.2.4 Independent DC Sources 288 F.2.5 DC Sweep Analysis 289 F.2.6 Independent Pulse Source for Transient Analysis 289 F.2.7 Transient Analysis 289 F.2.8 Independent AC Sources for Frequency Response 289 F.2.9 Independent Sinusoidal AC Sources for Transient Analysis 289 F.2.10 AC Frequency Analysis 290 F.2.11 Operating Point 290 F.2.12 Starting the SPICE Program 290 F.2.13 Example Program: Diode I–V Characteristics 290 F.3 Introduction to MATLAB® 290 F.3.1 Getting Started 291 F.3.2 Generating an x-Axis Data 291 F.3.3 Semi-logarithmic Scale 291 F.3.4 Log–Log Scale 291 F.3.5 Generate an y-Axis Data 292 F.3.6 Multiplication and Division 292 F.3.7 Symbols and Units 292 F.3.8 x-Axis and y-Axis Labels 292 F.3.9 x-Axis and y-Axis Limits 292 F.3.10 Greek Symbols 292 F.3.11 Plot Commands 293 F.3.12 3D Plot Commands 293 F.3.13 Bode Plots 293 F.3.14 Step Response 293 F.3.15 To Save Figure 293 F.3.16 Example Program 294 F.3.17 Polynomial Curve Fitting 294 F.3.18 Bessel Functions 294 F.3.19 Modified Bessel Functions 294 F.3.20 Example MATLAB Code 294 F.4 Introduction to SABER Circuit Simulator 301 F.4.1 Setting Up a Circuit on SABER 301 F.4.2 Performing TRANSIENT Analysis on the Designed Circuit 302 F.4.3 Plotting 303 F.4.4 Printing 303 Index 305

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Book SynopsisAn authoritative guide to the most up-to-date information on power system dynamics The revised third edition ofPower System Dynamics and Stabilitycontains a comprehensive, state-of-the-art review of information on the topic. The third edition continues the successful approach of the first and second editions by progressing from simplicity to complexity. It places the emphasis first on understanding the underlying physical principles before proceeding to more complex models and algorithms. The book is illustrated by a large number of diagrams and examples. The third edition ofPower System Dynamics and Stabilityexplores the influence of wind farms and virtual power plants, power plants inertia and control strategy on power system stability. The authorsnoted experts on the topiccover a range of new and expanded topics including: Wide-area monitoring and control systems. Improvement of power system stability by optimizationTable of ContentsAbout the Authors xix List of Symbols & Abbreviations xxi Part I Introduction to Power Systems 1 1 Introduction 3 1.1 Stability and Control of a Dynamic System 3 1.2 Classification of Power System Dynamics 5 1.3 Two Pairs of Important Quantities 7 1.4 Stability of a Power System 8 1.5 Security of a Power System 9 2 Power System Components 13 2.1 Introduction 13 2.2 Structure of the Electric Power System 14 2.3 Generating Units 17 2.4 Substations 33 2.5 Transmission and Distribution Network 34 2.6 Protection 49 2.7 Wide Area Measurement Systems 53 3 The Power System in the Steady State 57 3.1 Transmission Lines 57 3.2 Transformers 64 3.3 Synchronous Generators 68 3.4 Power System Loads 101 3.5 Network Equations 110 3.6 Power Flows in Transmission Networks 114 Part II Introduction to Power System Dynamics 123 4 Electromagnetic Phenomena 125 4.1 Fundamentals 125 4.2 Three-phase Short Circuit on a Synchronous Generator 130 4.3 Phase-to-phase Short Circuit 153 4.4 Switching Operations 164 4.5 Subsynchronous Resonance 191 5 Electromechanical Dynamics – Small Disturbances 195 5.1 Swing Equation 195 5.2 Damping Power 195 5.3 Equilibrium Points 199 5.4 Steady-state Stability of Unregulated System 200 5.5 Steady-state Stability of the Regulated System 219 6 Electromechanical Dynamics – Large Disturbances 229 6.1 Transient Stability 229 6.2 Swings in Multi-machine Systems 243 6.3 Direct Method for Stability Assessment 246 6.4 Synchronization 262 6.5 Asynchronous Operation and Resynchronization 264 6.6 Out-of-step Protection System 269 7 Wind Power 283 7.1 Wind Turbines 283 7.2 Generator Systems 287 7.3 Induction Machine Equivalent Circuit 291 7.4 Induction Generator Coupled to the Grid 294 7.5 Induction Generators with Slightly Increased Speed Range via External Rotor Resistance 297 7.6 Induction Generators with Significantly Increased Speed Range 299 7.7 Fully Rated Converter Systems (Wide Speed Control) 307 7.8 Peak Power Tracking of Variable Speed Wind Turbines 309 7.9 Connections of Wind Farms 309 7.10 Fault Behavior of Induction Generators 310 7.11 Influence of Wind Generators on Power System Stability 312 8 Voltage Stability 315 8.1 Network Feasibility 315 8.2 Stability Criteria 320 8.3 Critical Load Demand and Voltage Collapse 325 8.4 Static Analyses 332 8.5 Dynamic Analysis 342 8.6 Prevention of Voltage Collapse 348 8.7 Self-excitation of a Generator Operating on a Capacitive Load 349 9 Frequency Stability and Control 355 9.1 Automatic Generation Control 355 9.2 Stage I – Rotor Swings in the Generators 368 9.3 Stage II – Frequency Drop 371 9.4 Stage III – Primary Control 373 9.5 Stage IV – Secondary Control 378 9.6 Simplified Simulation Models 387 9.7 Series FACTS Devices in Tie-lines 392 9.8 Static Analysis by Snapshots of Power Flow 404 10 Stability Enhancement 407 10.1 Excitation Control System 408 10.2 Turbine Control System 415 10.3 Braking Resistors 419 10.4 Generator Tripping 421 10.5 Shunt FACTS Devices 423 10.6 Series Compensators 442 10.7 Unified Power Flow Controller 449 10.8 HVDC Links in Transmission Network 455 Part III Advanced Topics in Power System Dynamics 467 11 Advanced Power System Modeling 469 11.1 Synchronous Generator 469 11.2 Excitation Systems 496 11.3 Turbines and Turbine Governors 505 11.4 Wind Turbine Generator Systems and Wind Farms 522 11.5 Photovoltaic Power Plants 544 11.6 HVDC Links 548 11.7 Facts Devices 557 11.8 Dynamic Load Models 559 12 Steady-state Stability of Multi-machine Systems 561 12.1 Mathematical Background 561 12.2 Steady-state Stability of Unregulated System 580 12.3 Steady-state Stability of the Regulated System 589 13 Power System Dynamic Simulation 601 13.1 Numerical Integration Methods 602 13.2 The Partitioned Solution 606 13.3 The Simultaneous Solution Methods 618 13.4 Comparison Between the Methods 619 13.5 Modeling of Unbalanced Faults 620 13.6 Evaluation of Power System Dynamic Response 622 14 Stability Studies in Power System Planning 625 14.1 Purposes and Kinds of Analyses 625 14.2 Planning Criteria 629 14.3 Automation of Analyses and Reporting 641 15 Optimization of Control System Parameters 643 15.1 Grid Code Requirements 643 15.2 Optimization Methods 644 15.3 Linear Regulators 647 15.4 Optimal Regulators LQG, LQR, and LQI 681 15.5 Robust Regulators H2, h∞ 685 15.6 Nonlinear Regulators 693 15.7 Adaptive Regulators 694 15.8 Real Regulators and Field Tests 700 16 Wide-Area Monitoring and Control 709 16.1 Wide Area Measurement Systems 709 16.2 Examples of WAMS Applications 718 17 Impact of Renewable Energy Sources on Power System Dynamics 735 17.1 Renewable Energy Sources 735 17.2 Inertia in the Electric Power System 742 17.3 Virtual Inertia 758 18 Power System Model Reduction – Equivalents 775 18.1 Types of Equivalents 775 18.2 Network Transformation 776 18.3 Aggregation of Generating Units 784 18.4 Equivalent Model of External Subsystem 785 18.5 Coherency Recognition 786 18.6 Properties of Coherency Based Equivalents 790 Appendix 809 A.1 Per-unit System 809 A.1.1 Stator Base Quantities 809 A.1.2 Power Invariance 811 A.1.3 Rotor Base Quantities 811 A.1.4 Power System Base Quantities 814 A.1.5 Transformers 815 A.2 Partial Inversion 816 A.3 Linear Ordinary Differential Equations 817 A.3.1 Fundamental System of Solutions 817 A.3.2 Real and Distinct Roots 819 A.3.3 Repeated Real Roots 820 A.3.4 Complex and Distinct Roots 821 A.3.5 Repeated Complex Roots 825 A.3.6 First-order Complex Differential Eq. 825 A.4 Prony Analysis 826 A.5 Limiters and Symbols in Block Diagrams 832 A.5.1 Addition, Multiplication, and Division 832 A.5.2 Simple Integrator 833 A.5.3 Simple Time Constant 833 A.5.4 Lead–lag Block 834 References 835 Index 847

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Book SynopsisLearn how to apply cognitive principlesto the problems of computer vision Computational Models for Cognitive Visionformulates the computational models forthecognitive principlesfound inbiologicalvision,and applies those modelsto computer visiontasks.Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few.The author'sultimate goalis toprovide a framework forcreation of amachine vision systemwith thecapability and versatility ofthe human vision. Written by Dr.HiranmayGhosh, the book takes readers through the basicprinciplesand the computational modelsforcognitive vision, Bayesian reasoning for perception and cognition, and otherrelatedtopics, beforeestablishing therelationship ofcognitive visionwiththemulti-disciplinaryfield broadly referred to as artificial intelligence.The principles are illustrated with diverse application examples in computer vision, such as computational photography, digital heTable of ContentsAbout the Author ix Acknowledgments xi Preface xiii Acronyms xv 1 Introduction 1 1.1 What Is Cognitive Vision 2 1.2 Computational Approaches for Cognitive Vision 3 1.3 A Brief Review of Human Vision System 4 1.4 Perception and Cognition 6 1.5 Organization of the Book 7 2 Early Vision9 2.1 Feature Integration Theory 9 2.2 Structure of Human Eye 10 2.3 Lateral Inhibition 13 2.4 Convolution: Detection of Edges and Orientations 14 2.5 Color and Texture Perception 17 2.6 Motion Perception 19 2.6.1 Intensity-Based Approach 19 2.6.2 Token-Based Approach 20 2.7 Peripheral Vision 21 2.8 Conclusion 24 3 Bayesian Reasoning for Perception and Cognition 25 3.1 Reasoning Paradigms 26 3.2 Natural Scene Statistics 27 3.3 Bayesian Framework of Reasoning 28 3.4 Bayesian Networks 32 3.5 Dynamic Bayesian Networks 34 3.6 Parameter Estimation 36 3.7 On Complexity of Models and Bayesian Inference 38 3.8 Hierarchical Bayesian Models 39 3.9 Inductive Reasoning with Bayesian Framework 41 3.9.1 Inductive Generalization 41 3.9.2 Taxonomy Learning 45 3.9.3 Feature Selection 46 3.10 Conclusion 47 4 Late Vision 51 4.1 Stereopsis and Depth Perception 51 4.2 Perception of Visual Quality 53 4.3 Perceptual Grouping 55 4.4 Foreground–Background Separation 59 4.5 Multi-stability 60 4.6 Object Recognition 61 4.6.1 In-Context Object Recognition 62 4.6.2 Synthesis of Bottom-Up and Top-Down Knowledge 64 4.6.3 Hierarchical Modeling 65 4.6.4 One-Shot Learning 66 4.7 Visual Aesthetics 67 4.8 Conclusion 69 5 Visual Attention 71 5.1 Modeling of Visual Attention 72 5.2 Models for Visual Attention 75 5.2.1 Cognitive Models 75 5.2.2 Information-Theoretic Models 77 5.2.3 Bayesian Models 78 5.2.4 Context-Based Models 79 5.2.5 Object-Based Models 81 5.3 Evaluation 82 5.4 Conclusion 84 6 Cognitive Architectures 87 6.1 Cognitive Modeling 88 6.1.1 Paradigms for Modeling Cognition 88 6.1.2 Levels of Abstraction 91 6.2 Desiderata for Cognitive Architectures 92 6.3 Memory Architecture 94 6.4 Taxonomies of Cognitive Architectures 97 6.5 Review of Cognitive Architectures 99 6.5.1 STAR: Selective Tuning Attentive Reference 100 6.5.2 LIDA: Learning Intelligent Distribution Agent 102 6.6 Biologically Inspired Cognitive Architectures 105 6.7 Conclusions 106 7 Knowledge Representation for Cognitive Vision 109 7.1 Classicist Approach to Knowledge Representation 109 7.1.1 First Order Logic 111 7.1.2 Semantic Networks 113 7.1.3 Frame-Based Representation 114 7.2 Symbol Grounding Problem 117 7.3 Perceptual Knowledge 118 7.3.1 Representing Perceptual Knowledge 119 7.3.2 Structural Description of Scenes 120 7.3.3 Qualitative Spatial and Temporal Relations 122 7.3.4 Inexact Spatiotemporal Relations 124 7.4 Unifying Conceptual and Perceptual Knowledge 127 7.5 Knowledge-Based Visual Data Processing 128 7.6 Conclusion 129 8 Deep Learning for Visual Cognition 131 8.1 A Brief Introduction to Deep Neural Networks 132 8.1.1 Fully Connected Networks 132 8.1.2 Convolutional Neural Networks 134 8.1.3 Recurrent Neural Networks 137 8.1.4 Siamese Networks 140 8.1.5 Graph Neural Networks 140 8.2 Modes of Learning with DNN 142 8.2.1 Supervised Learning 142 8.2.1.1 Image Segmentation 142 8.2.1.2 Object Detection 144 8.2.2 Unsupervised Learning with Generative Networks 144 8.2.3 Meta-Learning: Learning to Learn 146 8.2.3.1 Reinforcement Learning 148 8.2.3.2 One-Shot and Few-Shot Learning 148 8.2.3.3 Zero-Shot Learning 150 8.2.3.4 Incremental Learning 150 8.2.4 Multi-task Learning 152 8.3 Visual Attention 154 8.3.1 Recurrent Attention Models 155 8.3.2 Recurrent Attention Model for Video 158 8.4 Bayesian Inferencing with Neural Networks 159 8.5 Conclusion 160 9 Applications of Visual Cognition 163 9.1 Computational Photography 163 9.1.1 Color Enhancement 164 9.1.2 Intelligent Cropping 166 9.1.3 Face Beautification 167 9.2 Digital Heritage 168 9.2.1 Digital Restoration of Images 168 9.2.2 Curating Dance Archives 170 9.3 Social Robots 172 9.3.1 Dynamic and Shared Spaces 173 9.3.2 Recognition of Visual Cues 174 9.3.3 Attention to Socially Relevant Signals 175 9.4 Content Re-purposing 177 9.5 Conclusion 179 10 Conclusion 181 10.1 “What Is Cognitive Vision” Revisited 181 10.2 Divergence of Approaches 183 10.3 Convergence on the Anvil? 185 References 187 Index 215

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Book SynopsisOxide Electronics Multiple disciplines converge in this insightful exploration of complex metal oxides and their functions and propertiesOxide Electronics delivers a broad and comprehensive exploration of complex metal oxides designed to meet the multidisciplinary needs of electrical and electronic engineers, physicists, and material scientists. The distinguished author eschews complex mathematics whenever possible and focuses on the physical and functional properties of metal oxides in each chapter. Each of the sixteen chapters featured within the book begins with an abstract and an introduction to the topic, clear explanations are presented with graphical illustrations and relevant equations throughout the book. Numerous supporting references are included, and each chapter is self-contained, making them perfect for use both as a reference and as study material. Readers will learn how and why the field of oxide electronics is a key area of research and exploitation in materials scTable of ContentsSeries Preface xiii Preface xv List of Contributors xvii 1 Graphene Oxide for Electronics 1Fenghua Liu, Lifeng Zhang, Lijian Wang, Binyuan Zhao and WeipingWu 1.1 Introduction 1 1.2 Synthesis and Characterizations of Graphene Oxide 2 1.2.1 Chemical Reduction of Graphene Oxide (GO) 2 1.2.2 Microwave Method 2 1.2.3 Plasma Method 3 1.2.4 Laser Method 4 1.3 Energy Harvest Applications of Graphene Oxide 5 1.3.1 Solar Cells 5 1.3.2 Solar Thermal Energy Harvest Devices 7 1.4 Energy Storage Applications of Graphene Oxide 7 1.4.1 Supercapacitors 7 1.4.2 Batteries 10 1.5 Electronic Device Applications of Graphene Oxide 12 1.6 Large Area Electronics Applications of Graphene Oxide 13 References 16 2 Flexible and Wearable Graphene-Based E-Textiles 21Nazmul Karim, Shaila Afroj, Damien Leech and Amr M. Abdelkader 2.1 Introduction to Wearable E-Textiles 21 2.2 Synthesis of Graphene Derivatives 22 2.2.1 Graphene Oxide 22 2.2.2 Reduced Graphene Oxide 24 2.3 Graphene-BasedWearable E-Textiles 25 2.3.1 Graphene-Based Textile Fibres 26 2.3.2 Graphene-Coated Textiles 27 2.3.3 Graphene-PrintedWearable E-Textiles 28 2.3.3.1 Screen Printing 30 2.3.3.2 Inkjet Printing 30 2.4 Surface Pre- and Post-Treatment of Substrates 32 2.5 Applications 34 2.5.1 Sensors 34 2.5.2 Supercapacitor 36 2.5.3 Rechargeable Batteries 38 2.5.4 Optoelectronics 39 2.6 Challenges and Outlook 40 References 41 3 Magnetic Interactions in the Cubic Mott Insulators NiO, MnO, and CoO and the Related Oxides CuO and FeO 51David J. Lockwood andMichael G. Cottam 3.1 Introduction 51 3.2 Spin–Spin Interactions 52 3.2.1 Magnetic Ordering Below TN 52 3.2.2 Magnetostriction 53 3.2.3 Magnetic and Electronic Excitations 54 3.3 Spin–Phonon Interactions 59 3.3.1 Phonon and Magnon Temperature Dependences 60 3.3.2 Phonon Mode Splitting Below TN 62 3.4 Other Related Materials 64 3.4.1 Cupric Oxide 64 3.4.2 Iron Monoxide 65 3.5 Conclusions 68 Acknowledgments 68 References 68 4 High-𝜿 Dielectric Oxides for Electronics 75Tong Zhang, Xiaoyang Zhang, Yi Yang and WeipingWu 4.1 Introduction of High-𝜅 Dielectric Oxides 75 4.1.1 Group IIIA Dielectric Oxides 77 4.1.2 Group IIIB High-𝜅 Dielectric Oxides 77 4.1.3 Group IVB High-𝜅 Dielectric Oxides 77 4.2 The Deposition of High-𝜅 Oxide Dielectrics 78 4.3 High-𝜅 Dielectric Oxides for Field-Effect Transistors 80 4.3.1 High-𝜅 Dielectric Oxides for the MOSFETs 80 4.3.2 High-𝜅 Dielectric Oxides for Tunnel Field-Effect Transistors 84 4.4 High-𝜅 Dielectric Oxides for Memory Devices 85 4.4.1 High-𝜅 Dielectric Oxides for DRAM 85 4.4.2 High-𝜅 Dielectric Oxides for ReRAM 87 References 88 5 Low Temperature Growth of Germanium Oxide Nanowires by Template Based Self Assembly and their Raman Characterization 93Raisa Fabiha, Abigail Casey, Gregory Triplett and Supriyo Bandyopadhyay 5.1 Introduction 93 5.2 Synthesis 93 5.3 Characterization 96 5.4 Raman Measurements 96 5.5 Conclusion 98 References 99 6 Electronic Phenomena, Electroforming, Resistive Switching, and Defect Conduction Bands in Metal-Insulator-Metal Diodes 101ThomasW. Hickmott 6.1 Introduction 101 6.2 Experimental 103 6.3 Electroforming, Electroluminescence, and Electron Emission 104 6.3.1 Electroforming of Al-Al2O3-Ag Diodes 104 6.3.2 Electroluminescence from Al-Al2O3-Ag Diodes 104 6.3.3 Electron Emission from Al-Al2O3-Ag Diodes 105 6.3.4 VCNR, EL, and EM in Other Insulators 107 6.3.5 Temperature Dependence of EM 108 6.4 Electrode Effects in Resistive Switching of Nb-Nb2O5-Metal Diodes 109 6.4.1 Resistive Switching in Nb-Nb2O5-Metal Diodes 109 6.4.2 Resistive Switching at Low Temperatures 109 6.4.3 Structure in I-V Curves of Electroformed Nb-Nb2O5-Metal Diodes 110 6.5 Conduction, Electroluminescence, and Photoconductivity Before Electroforming MIM Diodes 112 6.5.1 Conduction in Nb-Nb2O5-Au Diodes 112 6.5.2 Electroluminescence in Nb-Nb2O5-Au Diodes 112 6.5.3 Conduction and Electroluminescence in MIM Diodes with TiO2 and Ta2O5 115 6.5.4 Photoconductivity in MIM Diodes 115 6.6 Discussion 118 6.6.1 Defect Conduction Bands in Amorphous Al2O3 119 6.6.2 Defect Conduction Bands in Amorphous Nb2O5 121 6.6.3 Defect Conduction Bands in Amorphous Insulators 123 6.7 Summary and Conclusions 125 References 125 7 Lead Oxide as Material of Choice for Direct Conversion Detectors 129Alla Reznik and Oleksii Semeniuk 7.1 Introduction 129 7.2 Crystal Structure and Electronic Properties of PbO 130 7.2.1 Crystal Structure of Tetragonal PbO (𝛼-PbO) 131 7.2.2 Crystal Structure of Orthorhombic PbO (𝛽-PbO) 132 7.2.3 Electronic Properties of 𝛼- and 𝛽-PbO 133 7.3 Deposition Process of PbO Layers 135 7.4 Charge Transport Mechanism in Lead Oxide 147 7.4.1 Electron Transport in poly-PbO 148 References 151 8 ZnO Varistors: From Grain Boundaries to Power Applications 157Felix Greuter 8.1 Introduction 157 8.2 Manufacturing Process of ZnO Varistors 160 8.3 Microstructure and Grain Boundaries 162 8.4 Grain Boundary Potential Barriers 168 8.5 The ‘Double Schottky Barrier Defect Model’ 174 8.6 Hot Electron Effects Controlling the Breakdown Region 181 8.7 Hot Electron Effects and Dynamic Response 185 8.8 From Single Grain Boundaries to Microstructures and Varistor Devices 196 8.9 Ageing and Long-Term Stability of Varistor Materials 207 8.10 Energy Absorption Capability and High Current Impulse Stresses 218 8.11 Summary and Outlook 223 Acknowledgements 226 References 226 9 Fundamental Properties and Power Electronic Device Progress of Gallium Oxide 235Xuanhu Chen, Chennupati Jagadish and Jiandong Ye 9.1 Introduction 235 9.2 Electronic Properties and Defects of Ga2O3 236 9.2.1 Bulk Crystals, Epitaxy, and n–type Doping 237 9.2.2 Electronic Band Structure and Feasibility of p–type Doping 240 9.2.3 Defect Behaviour in Bulk Crystals and Epitaxial Films 245 9.3 Basic Device Characteristics 250 9.3.1 Metal-Semiconductor Contact 250 9.3.1.1 Barrier Formation 250 9.3.1.2 Image-Force Lowering 252 9.3.1.3 Carrier Transport and Breakdown 254 9.3.2 Physics of Deep Depletion Ga2O3 MOSFETs 257 9.3.2.1 Metal-Insulator-Semiconductor Capacitors 257 9.3.2.2 Basic Device Characteristics of DepletionMode MOSFETs Based on Ga2O3 270 9.3.2.3 Approaches to Enhancement-Mode 𝛽-Ga2O3 MOSFETs 280 9.3.3 Relevant Figure of Merit in Ga2O3 282 9.4 Ga2O3 Schottky Rectifiers 286 9.4.1 Edge Terminations 287 9.4.2 Ga2O3 Schottky Rectifiers 295 9.4.3 Ga2O3 p-n Heterojunction Diodes 301 9.5 Ga2O3 Transistors 307 9.5.1 Ohmic Contacts to Ga2O3 307 9.5.2 Dielectric Materials for Ga2O3 and MOSCaps 308 9.5.3 Lateral Ga2O3 FETs 313 9.5.4 𝛽-Ga2O3 MODFETs 324 9.5.5 Vertical Ga2O3 MOSFETs 330 9.6 Summary 335 References 336 10 Emerging Trends, Challenges, and Applications in Solid-State Laser Cooling 353Jyothis Thomas, LauroMaia, Yannick Ledemi, YounesMessaddeq and Raman Kashyap 10.1 Introduction 353 10.2 Theory 355 10.3 Experimental Design Considerations for Cooling 357 10.3.1 Experimental Setups Used for Solid-state Laser Cooling 357 10.3.1.1 Crystals 357 10.3.1.2 Glasses 358 10.3.1.3 Silica Glass Optical Fibres 360 10.3.1.4 Semiconductor Nanoribbons 361 10.3.2 Techniques to Analyse Background Absorption (𝛼b) Coefficient 361 10.3.3 Temperature Measurement Techniques in Solid-State Laser Cooling 362 10.3.3.1 Thermal Imaging 362 10.3.3.2 Photoluminescence (PL)Thermometry 363 10.3.3.3 Temperature Measurement Using Fibre Bragg Gratings 363 10.3.3.4 Thermocouples 364 10.3.3.5 Photothermal Deflection Spectroscopy (PTDS) 364 10.3.3.6 Interferometric Technique 364 10.4 Laser Cooling Materials and Properties 365 10.4.1 Crystals 366 10.4.2 Semiconductors 368 10.4.3 Optical Fibres 370 10.4.4 Nanocrystalline Powders 371 10.5 Oxyfluoride Glass-Ceramics: Recent Developments in Solid-State Laser Cooling 373 10.5.1 Earth-Doped Oxyfluoride Pseudo-Binary Glasses and Glass-Ceramics for Optical Refrigeration 375 10.5.1.1 Materials and Methods 376 10.5.1.2 Results and Discussion 376 10.5.1.3 Summary on Pseudo-Binary Oxyfluoride Glass Ceramics 381 10.6 Optical Cryocooler Devices 382 10.7 Future Prospects and Conclusions 386 Acknowledgements 388 References 388 11 ElectrodeMaterials for Sodium Ion Rechargeable Batteries 397TaniaMajumder, Anwesa Mukherjee, Debasish Das and S.B.Majumder 11.1 Introduction – Review of the Constituents Used in Na – Ion Cells 397 11.2 Cathode Materials for Na Ion Rechargeable Cells 397 11.2.1 Transition Metal Oxides with Layered Structure 397 11.2.2 Prussian Blue Analogue 398 11.2.3 Sodium Superionic Conductors (NASICON) 399 11.2.4 Other Cathodes 400 11.3 Current Collectors, Binder, and Electrolyte 400 11.4 Anode Materials for Na Ion Rechargeable Cells 401 11.4.1 Carbonaceous Materials 401 11.4.2 Alloying Type Anodes 401 11.4.3 Conversion Type Anodes 402 11.4.4 Other Anodes 402 11.5 Outstanding Research Issues and Statement of the Problem 402 11.6 Synthesis and Electrochemical Characterization of Electrodes 404 11.6.1 Ilmenite NiTiO3 as Anode 404 11.6.1.1 Synthesis and Characterization 404 11.6.2 Electrochemical Characterization 404 11.6.3 Electrophoretic Deposition of NiTiO3-Based Anode 406 11.6.4 Electrochemical Performance of EPD Grown NTO Anodes 408 11.7 Na2Ti3O7 as Anode 409 11.7.1 Synthesis and Characterization 409 11.7.2 Electrochemical Characterization of Pristine NaTO 410 11.7.3 Electrochemical Performance of Carbon-Coated NaTO Anode 411 11.7.4 Electrochemical Performance of NaTO/rGO Composite Anode 413 11.8 PBA as Cathode 414 11.8.1 Nickel Hexacyanoferrate (NiHCF) 415 11.8.2 Iron Hexacyanoferrate (FeHCF) 417 11.9 Summary and Conclusions 418 Acknowledgement 419 References 419 12 Perovskites for Photovoltaics 423Hooman Mehdizadeh Rad, David Ompong and Jai Singh 12.1 Introduction 423 12.2 Diffusion Length 424 12.2.1 Methodology 425 12.2.2 Results of Simulated Diffusion Length and Discussions 427 12.3 Open-Circuit Voltage 432 12.3.1 Results of Open-Circuit Voltage and Discussions 433 12.3.2 Bimolecular Recombination 436 12.4 Influence of Density of Tail States at Interfaces 437 12.4.1 Methods 437 12.4.2 Results of Density of States and Discussions 441 12.5 Conclusions 444 References 447 13 Advanced Characterizations of Oxides for Optoelectronic Applications 453U. Onwukwe, L. Anguilano and P. Sermon 13.1 A Brief History of Optoelectronic Devices 453 13.1.1 Semiconductors 454 13.1.1.1 n-Type Extrinsic Semiconductors 455 13.1.1.2 p-Type Extrinsic Semiconductors 456 13.2 Interaction of Semiconductors and the Optoelectronic Phenomenon 457 13.2.1 Direct Band Gap Semiconductors 457 13.2.1.1 Indirect Band Gap Semiconductors 458 13.2.2 Oxides for Optoelectronics: Introduction 459 13.2.3 Major Types of MO for Optoelectronics 460 13.2.3.1 ITO 460 13.2.3.2 ZnO 460 13.2.3.3 AZO 461 13.2.3.4 IGZO 461 13.2.3.5 Perovskite Oxides 462 13.2.3.6 Reduced Graphene Oxide-Miscellaneous Materials 463 13.2.4 Method of Preparation of Optoelectronic Structures 467 13.2.4.1 Nanowires/Nanorods 467 13.2.4.2 Thin Films 467 13.2.4.3 Mixed Morphologies Fabrication 468 13.3 Characterization Techniques and their Use for Metal Oxide Optoelectronics 470 13.3.1 Rutherford Backscattering Spectrometry (RBS) 470 13.3.2 Fourier-Transform Infra-Red (FTIR) 471 13.3.2.1 Raman Spectroscopy 473 13.3.3 Scanning Electron Microscopy (SEM) 475 13.3.4 Transmission Electron Microscope (TEM) 477 13.3.5 Luminescence Techniques 480 13.3.6 X-Ray Diffraction 482 13.4 Facilities and Case Studies 484 13.4.1 Case Study I – Leaf Biotemplate Derived TiO2 485 References 488 14 Future Tuning Optoelectronic Oxides from the Inside: Sol-Gel (TiO2)x-(SiO2)100-x 497M.P.Worsley, J.G. Leadley, R.M.A. MacGibbon, T. Salvesen, P.A. Sermon and J.M. Charnock 14.1 Introduction and Background 497 14.1.1 Photons and Wavetrains 497 14.1.2 Optoelectronic Oxides and Devices 497 14.1.3 TiO2 498 14.1.4 TiO2-SiO2 498 14.1.5 Alkoxide and Sol-Gel Routes to TiO2-SiO2 500 14.1.6 Miscibility and the % TiO2 (x) Added in TiO2-SiO2 500 14.1.7 Doping of TiO2-SiO2 501 14.1.8 Local Structure in TiO2-SiO2 501 14.2 Hypothesis 503 14.3 Experimental 504 14.3.1 Materials 504 14.3.2 Preparations 504 14.3.3 Characterization Methods 504 14.4 Characterization Results 505 14.5 Discussion on Future Automated CALPHAD Design, Dip-Coating Mechanical, and High-Throughput Screening of Novel Optoelectronic Oxides and Devices 510 14.6 Conclusions on TiO2-SiO2 Use 510 Acknowledgements 513 References 513 15 Binary Calcia-Alumina Thin Films: Synthesis and Properties and Applications 525Asim K. Ray 15.1 Introduction 525 15.2 Structural and Physical Properties of C12A7 526 15.2.1 Thermal Stability 528 15.2.2 Ionic Conductivity and Mechanisms of Oxide–Ion Migration 529 15.3 Atomic and Electronic Structure 530 15.3.1 Synthesis of C12A7 531 15.3.2 Single Powders 531 15.3.3 Single Crystal 532 15.3.4 Polycrystalline Bulk 533 15.3.5 Thin Film 535 15.3.6 Ion Doping in C12A7 536 15.3.6.1 Heat Treatment in H2 Atmosphere 537 15.3.6.2 Thermoelectricity 537 15.4 Optical Properties 540 15.4.1 Reflectivity 541 15.4.2 Luminescence 542 15.5 Applications of C12A7 543 15.6 Summary 545 Acknowledgements 546 References 546 16 Oxide Cathodes 553Ian Alberts 16.1 Historical Aspects 553 16.1.1 The Edison Effect 555 16.1.2 ArthurWehnelt 555 16.1.3 Thermionic Emission Research in the Early Twentieth Century 556 16.1.4 Oxide Cathodes for the CRT 556 16.2 Physics of Thermionic Emission 557 16.2.1 Derivation of the Richardson-Dushman Equation 558 16.2.2 Space Charge and the Child-Langmuir Law 559 16.3 Oxide Cathode Development 560 16.3.1 The Barium-Coated Cathode 561 16.3.2 The Rise and Subsequent Fall of the Impregnated Cathode 562 16.3.3 Cermet Cathodes 565 16.3.4 State of the Art 565 16.4 Future Trends and Ongoing Applications 567 16.4.1 Vacuum X-Ray Tubes 568 16.4.2 Military Telecommunications 568 16.4.3 Klystrons 570 16.4.4 Gyrotron 571 16.4.5 Thermionic Energy Conversion 571 16.4.6 Triboelectric Nanogenerators 573 16.4.7 Frontiers in Thermionic Research: Vacuum Nanoelectronics 575 16.4.8 Field Emission Displays (FED) 575 16.5 Conclusion 577 References 577 Index 583

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Book SynopsisCovers experiment planning, execution, analysis, and reporting This single-source resource guides readers in planning and conducting credible experiments for engineering, science, industrial processes, agriculture, and business. The text takes experimenters all the way through conducting a high-impact experiment, from initial conception, through execution of the experiment, to a defensible final report. It prepares the reader to anticipate the choices faced during each stage. Filled with real-world examples from engineering science and industry, Planning and Executing Credible Experiments: A Guidebook for Engineering, Science, Industrial Processes, Agriculture, and Business offers chapters that challenge experimenters at each stage of planning and execution and emphasizes uncertainty analysis as a design tool in addition to its role for reporting results. Tested over decades at Stanford University and internationally, the text employs two powerful, free, Table of ContentsAbout the Authors xxi Preface xxiii Acknowledgments xxvii About the Companion Website xxix 1 Choosing Credibility 1 1.1 The Responsibility of an Experimentalist 2 1.2 Losses of Credibility 2 1.3 Recovering Credibility 3 1.4 Starting with a Sharp Axe 3 1.5 A Systems View of Experimental Work 4 1.6 In Defense of Being a Generalist 5 Panel 1.1 The Bundt Cake Story 6 References 6 Homework 6 2 The Nature of Experimental Work 7 2.1 Tested Guide of Strategy and Tactics 7 2.2 What Can Be Measured and What Cannot? 8 2.2.1 Examples Not Measurable 8 2.2.2 Shapes 9 2.2.3 Measurable by the Human Sensory System 10 2.2.4 Identifying and Selecting Measurable Factors 11 2.2.5 Intrusive Measurements 11 2.3 Beware Measuring Without Understanding: Warnings from History 12 2.4 How Does Experimental Work Differ from Theory and Analysis? 13 2.4.1 Logical Mode 13 2.4.2 Persistence 13 2.4.3 Resolution 13 2.4.4 Dimensionality 15 2.4.5 Similarity and Dimensional Analysis 15 2.4.6 Listening to Our Theoretician Compatriots 16 Panel 2.1 Positive Consequences of the Reproducibility Crisis 17 Panel 2.2 Selected Invitations to Experimental Research, Insights from Theoreticians 18 Panel 2.3 Prepublishing Your Experiment Plan 21 2.4.7 Surveys and Polls 22 2.5 Uncertainty 23 2.6 Uncertainty Analysis 23 References 24 Homework 25 3 An Overview of Experiment Planning 27 3.1 Steps in an Experimental Plan 27 3.2 Iteration and Refinement 28 3.3 Risk Assessment/Risk Abatement 28 3.4 Questions to Guide Planning of an Experiment 29 Homework 30 4 Identifying the Motivating Question 31 4.1 The Prime Need 31 Panel 4.1 There’s a Hole in My Bucket 32 4.2 An Anchor and a Sieve 33 4.3 Identifying the Motivating Question Clarifies Thinking 33 4.3.1 Getting Started 33 4.3.2 Probe and Focus 34 4.4 Three Levels of Questions 35 4.5 Strong Inference 36 4.6 Agree on the Form of an Acceptable Answer 36 4.7 Specify the Allowable Uncertainty 37 4.8 Final Closure 37 Reference 38 Homework 38 5 Choosing the Approach 39 5.1 Laying Groundwork 39 5.2 Experiment Classifications 40 5.2.1 Exploratory 40 5.2.2 Identifying the Important Variables 40 5.2.3 Demonstration of System Performance 41 5.2.4 Testing a Hypothesis 41 5.2.5 Developing Constants for Predetermined Models 41 5.2.6 Custody Transfer and System Performance Certification Tests 42 5.2.7 Quality-Assurance Tests 42 5.2.8 Summary 43 5.3 Real or Simplified Conditions? 43 5.4 Single-Sample or Multiple-Sample? 43 Panel 5.1 A Brief Summary of “Dissertation upon Roast Pig” 44 Panel 5.2 Consider a Spherical Cow 44 5.5 Statistical or Parametric Experiment Design? 45 5.6 Supportive or Refutative? 47 5.7 The Bottom Line 47 References 48 Homework 48 6 Mapping for Safety, Operation, and Results 51 6.1 Construct Multiple Maps to Illustrate and Guide Experiment Plan 51 6.2 Mapping Prior Work and Proposed Work 51 6.3 Mapping the Operable Domain of an Apparatus 53 6.4 Mapping in Operator’s Coordinates 57 6.5 Mapping the Response Surface 59 6.5.1 Options for Organizing a Table 59 6.5.2 Options for Presenting the Response on a Scatter-Plot-Type Graph 61 Homework 64 7 Refreshing Statistics 65 7.1 Reviving Key Terms to Quantify Uncertainty 65 7.1.1 Population 65 7.1.2 Sample 66 7.1.3 Central Value 67 7.1.4 Mean, μ or Ȳ 67 7.1.5 Residual 67 7.1.6 Variance, σ2 or S2 68 7.1.7 Degrees of Freedom, Df 68 7.1.8 Standard Deviation, σY or SY 68 7.1.9 Uncertainty of the Mean, δμ 69 7.1.10 Chi‐Squared, χ2 69 7.1.11 p‐Value 70 7.1.12 Null Hypothesis 70 7.1.13 F‐value of Fisher Statistic 71 7.2 The Data Distribution Most Commonly Encountered The Normal Distribution for Samples of Infinite Size 71 7.3 Account for Small Samples: The t‐Distribution 72 7.4 Construct Simple Models by Computer to Explain the Data 73 7.4.1 Basic Statistical Analysis of Quantitative Data 73 7.4.2 Model Data Containing Categorical and Quantitative Factors 75 7.4.3 Display Data Fit to One Categorical Factor and One Quantitative Factor 76 7.4.4 Quantify How Each Factor Accounts for Variation in the Data 76 7.5 Gain Confidence and Skill at Statistical Modeling Via the R Language 77 7.5.1 Model and Plot Results of a Single Variable Using the Example Data diceshoe.csv 77 7.5.2 Evaluate Alternative Models of the Example Data hiloy.csv 78 7.5.2.1 Inspect the Data 78 7.5.3 Grand Mean 78 7.5.4 Model by Groups: Group‐Wise Mean 78 7.5.5 Model by a Quantitative Factor 78 7.5.6 Model by Multiple Quantitative Factors 78 7.5.7 Allow Factors to Interact (So Each Group Gets Its Own Slope) 79 7.5.8 Include Polynomial Factors (a Statistical Linear Model Can Be Curved) 80 7.6 Report Uncertainty 80 7.7 Decrease Uncertainty (Improve Credibility) by Isolating Distinct Groups 81 7.8 Original Data, Summary, and R 82 References 83 Homework 83 8 Exploring Statistical Design of Experiments 87 8.1 Always Seeking Wiser Strategies 87 8.2 Evolving from Novice Experiment Design 87 8.3 Two‐Level and Three‐Level Factorial Experiment Plans 88 8.4 A Three‐Level, Three‐Factor Design 89 8.5 The Plackett–Burman 12‐Run Screening Design 93 8.6 Details About Analysis of Statistically Designed Experiments 95 8.6.1 Model Main Factors to Original Raw Data 95 8.6.2 Model Main Factors to Original Data Around Center of Each Factor 96 8.6.3 Model Including All Interaction Terms 97 8.6.4 Model Including Only Dominant Interaction Terms 97 8.6.5 Model Including Dominant Interaction Term Plus Quadratic Term 98 8.6.6 Model All Factors of Example 2, Centering Each Quantitative Factor 99 8.6.7 Refine Model of Example 2 Including Only Dominant Terms 100 8.7 Retrospect of Statistical Design Examples 101 8.8 Philosophy of Statistical Design 101 8.9 Statistical Design for Conditions That Challenge Factorial Designs 102 8.10 A Highly Recommended Tool for Statistical Design of Experiments 103 8.11 More Tools for Statistical Design of Experiments 103 8.12 Conclusion 103 Further Reading 104 Homework 104 9 Selecting the Data Points 107 9.1 The Three Categories of Data 107 9.1.1 The Output Data 107 9.1.2 Peripheral Data 108 9.1.3 Backup Data 108 9.1.4 Other Data You May Wish to Acquire 108 9.2 Populating the Operating Volume 109 9.2.1 Locating the Data Points Within the Operating Volume 109 9.2.2 Estimating the Topography of the Response Surface 109 9.3 Example from Velocimetry 109 9.3.1 Sharpen Our Approach 110 9.3.2 Lessons Learned from Velocimetry Example 111 9.4 Organize the Data 112 9.4.1 Keep a Laboratory Notebook 112 9.4.2 Plan for Data Security 112 9.4.3 Decide Data Format 112 9.4.4 Overview Data Guidelines 112 9.4.5 Reasoning Through Data Guidelines 113 9.5 Strategies to Select Next Data Points 114 9.5.1 Overview of Option 1: Default Strategy with Intensive Experimenter Involvement 115 9.5.1.1 Choosing the Data Trajectory 115 9.5.1.2 The Default Strategy: Be Bold 115 9.5.1.3 Anticipate, Check, Course Correct 116 9.5.1.4 Other Aspects to Keep in Mind 116 9.5.1.5 Endpoints 117 9.5.2 Reintroducing Gosset 118 9.5.3 Practice Gosset Examples (from Gosset User Manual) 119 9.6 Demonstrate Gosset for Selecting Data 120 9.6.1 Status Quo of Experiment Planning and Execution (Prior to Selecting More Samples) 120 9.6.1.1 Specified Motivating Question 120 9.6.1.2 Identified Pertinent Candidate Factors 121 9.6.1.3 Selected Initial Sample Points Using Plackett–Burman 121 9.6.1.4 Executed the First 12 Runs at the PB Sample Conditions 122 9.6.1.5 Analyzed Results. Identified Dominant First-Order Factors. Estimated First-Order Uncertainties of Factors 123 9.6.1.6 Generated Draft Predictive Equation 124 9.6.2 Use Gosset to Select Additional Data Samples 125 9.6.2.1 Example Gosset Session: User Input to Select Next Points 125 9.6.2.2 Example Gosset Session: How We Chose User Input 126 9.6.2.3 Example Gosset Session: User Input Along with Gosset Output 128 9.6.2.4 Example Gosset Session: Convert the Gosset Design to Operator Values 131 9.6.2.5 Results of Example Gosset Session: Operator Plots of Total Experiment Plan 132 9.6.2.6 Execute Stage Two of the Experiment Plan: User Plus Gosset Sample Points 132 9.7 Use Gosset to Analyze Results 133 9.8 Other Options and Features of Gosset 133 9.9 Using Gosset to Find Local Extrema in a Function of Several Variables 134 9.10 Summary 137 Further Reading 137 Homework 137 10 Analyzing Measurement Uncertainty 143 10.1 Clarifying Uncertainty Analysis 143 10.1.1 Distinguish Error and Uncertainty 144 10.1.1.1 Single-Sample vs. Multiple-Sample 145 10.1.2 Uncertainty as a Diagnostic Tool 146 10.1.2.1 What Can Uncertainty Analysis Tell You? 146 10.1.2.2 What is Uncertainty Analysis Good For? 148 10.1.2.3 Uncertainty Analysis Can Redirect a Poorly Conceived Experiment 148 10.1.2.4 Uncertainty Analysis Improves the Quality of Your Work 148 10.1.2.5 Slow Sampling and “Randomness” 149 10.1.2.6 Uncertainty Analysis Makes Results Believable 150 10.1.3 Uncertainty Analysis Aids Management Decision-Making 150 10.1.3.1 Management’s Task: Dealing with Warranty Issues 150 10.1.4 The Design Group’s Task: Setting Tolerances on Performance Test Repeatability 152 10.1.5 The Performance Test Group’s Task: Setting the Tolerances on Measurements 152 10.2 Definitions 153 10.2.1 True Value 153 10.2.2 Corrected Value 153 10.2.3 Data Reduction Program 153 10.2.4 Accuracy 153 10.2.5 Error 154 10.2.6 XXXX Error 154 10.2.7 Fixed Error 154 10.2.8 Residual Fixed Error 154 10.2.9 Random Error 154 10.2.10 Variable (but Deterministic) Error 155 10.2.11 Uncertainty 155 10.2.12 Odds 155 10.2.13 Absolute Uncertainty 155 10.2.14 Relative Uncertainty 155 10.3 The Sources and Types of Errors 156 10.3.1 Types of Errors: Fixed, Random, and Variable 156 10.3.2 Sources of Errors: The Measurement Chain 156 10.3.2.1 The Undisturbed Value 158 10.3.2.2 The Available Value 158 10.3.2.3 The Achieved Value 158 10.3.2.4 The Observed Value 159 10.3.2.5 The Corrected Value 159 10.3.3 Specifying the True Value 160 10.3.3.1 If the Achieved Value is Taken as the True Value 160 10.3.3.2 If the Available Value is Taken as the True Value 163 10.3.3.3 If the Undisturbed Value is Taken as the True Value 166 10.3.3.4 If the Mixed Mean Gas Temperature is Taken as the True Value 167 10.3.4 The Role of the End User 167 10.3.4.1 The End-Use Equations Implicitly Define the True Value 167 10.3.5 Calibration 168 10.4 The Basic Mathematics 170 10.4.1 The Root-Sum-Squared (RSS) Combination 170 10.4.2 The Fixed Error in a Measurement 171 10.4.3 The Random Error in a Measurement 172 10.4.4 The Uncertainty in a Measurement 173 10.4.5 The Uncertainty in a Calculated Result 174 10.4.5.1 The Relative Uncertainty in a Result 176 10.5 Automating the Uncertainty Analysis 178 10.5.1 The Mathematical Basis 178 10.5.2 Example of Uncertainty Analysis by Spreadsheet 179 10.6 Single-Sample Uncertainty Analysis 181 10.6.1 Assembling the Necessary Inputs 184 10.6.2 Calculating the Uncertainty in the Result 185 10.6.3 The Three Levels of Uncertainty: Zeroth-, First-, and Nth-Order 185 10.6.3.1 Zeroth-Order Replication 186 10.6.3.2 First-Order Replication 187 10.6.3.3 Nth-Order Replication 188 10.6.4 Fractional-Order Replication for Special Cases 188 10.6.5 Summary of Single-Sample Uncertainty Levels 189 10.6.5.1 Zeroth-Order 189 10.6.5.2 First-Order 190 10.6.5.3 Nth-Order 190 References 190 Further Reading 191 Homework 191 11 Using Uncertainty Analysis in Planning and Execution 197 11.1 Using Uncertainty Analysis in Planning 197 11.1.1 The Physical Situation and Energy Analysis 198 11.1.2 The Steady‐State Method 199 11.1.3 The Transient Method 200 11.1.4 Reflecting on Assumptions Made During DRE Derivations 201 11.2 Perform Uncertainty Analysis on the DREs 202 11.2.1 Uncertainty Analysis: General Form 202 11.2.2 Uncertainty Analysis of the Steady‐State Method 203 11.2.3 Uncertainty Analysis – Transient Method 204 11.2.4 Compare the Results of Uncertainty Analysis of the Methods 205 11.2.5 What Does the Calculated Uncertainty Interval Mean? 206 11.2.6 Cross‐Checking the Experiment 207 11.2.7 Conclusions 207 11.3 Using Uncertainty Analysis in Selecting Instruments 208 11.4 Using Uncertainty Analysis in Debugging an Experiment 209 11.4.1 Handling Overall Scatter 209 11.4.2 Sources of Scatter 210 11.4.3 Advancing Toward Calibration 211 11.4.4 Selecting Thresholds 212 11.4.5 Iterating Analysis 212 11.4.6 Rechecking Situational Uncertainty 212 11.5 Reporting the Uncertainties in an Experiment 213 11.5.1 Progress in Uncertainty Reporting 214 11.6 Multiple‐Sample Uncertainty Analysis 214 11.6.1 Revisiting Single‐Sample and Multiple‐Sample Uncertainty Analysis 214 11.6.2 Examples of Multiple‐Sample Uncertainty Analysis 215 11.6.3 Fixed Error and Random Error 216 11.7 Coordinate with Uncertainty Analysis Standards 216 11.7.1 Describing Fixed and Random Errors in a Measurement 217 11.7.2 The Bias Limit 217 11.7.2.1 Fossilization 218 11.7.2.2 Bias Limits 218 11.7.3 The Precision Index 219 11.7.4 The Number of Degrees of Freedom 220 11.8 Describing the Overall Uncertainty in a Single Measurement 220 11.8.1 Adjusting for a Single Measurement 220 11.8.2 Describing the Overall Uncertainty in a Result 221 11.8.3 Adding the Overall Uncertainty to Predictive Models 222 11.9 Additional Statistical Tools and Elements 222 11.9.1 Pooled Variance 222 11.9.1.1 Student’s t‐Distribution – Pooled Examples 223 11.9.2 Estimating the Standard Deviation of a Population from the Standard Deviation of a Small Sample: The Chi‐Squared χ2 Distribution 223 References 225 Homework 226 12 Debugging an Experiment, Shakedown, and Validation 231 12.1 Introduction 231 12.2 Classes of Error 231 12.3 Using Time-Series Analysis in Debugging 232 12.4 Examples 232 12.4.1 Gas Temperature Measurement 232 12.4.2 Calibration of a Strain Gauge 233 12.4.3 Lessons Learned from Examples 234 12.5 Process Unsteadiness 234 12.6 The Effect of Time-Constant Mismatching 235 12.7 Using Uncertainty Analysis in Debugging an Experiment 236 12.7.1 Calibration and Repeatability 236 12.7.2 Stability and Baselining 238 12.8 Debugging the Experiment via the Data Interpretation Program 239 12.8.1 Debug the Experiment via the DIP 239 12.8.2 Debug the Interface of the DIP 239 12.8.3 Debug Routines in the DIP 240 12.9 Situational Uncertainty 241 13 Trimming Uncertainty 243 13.1 Focusing on the Goal 243 13.2 A Motivating Question for Industrial Production 243 13.2.1 Agreed Motivating Questions for Industrial Example 244 13.2.2 Quick Answers to Motivating Questions 244 13.2.3 Challenge: Precheck Analysis and Answers 245 13.3 Plackett–Burman 12-Run Results and Motivating Question #3 245 13.4 PB 12-Run Results and Motivating Question #1 247 13.4.1 Building a Predictive Model Equation from R-Language Linear Model 248 13.4.2 Parsing the Dual Predictive Model Equation 249 13.4.3 Uncertainty of the Intercept in the Dual Predictive Model Equation 250 13.4.4 Mapping an Answer to Motivating Question #1 251 13.4.5 Tentative Answers to Motivating Question #1 252 13.5 Uncertainty Analysis of Dual Predictive Model and Motivating Question #2 252 13.5.1 Uncertainty of the Constant in the Dual Predictive Model Equation 252 13.5.2 Uncertainty of Other Factors in the Dual Predictive Model Equation 253 13.5.3 Include All Coefficient Uncertainties in the Dual Predictive Model Equation 254 13.5.4 Overall Uncertainty from All Factors in the Predictive Model Equation 254 13.5.5 Improved Tentative Answers to Motivating Questions, Including Uncertainties 256 13.5.6 Search for Improved Predictive Models 256 13.6 The PB 12-Run Results and Individual Machine Models 256 13.6.1 Individual Machine Predictive Model Equations 258 13.6.2 Uncertainty of the Intercept in the Individual Predictive Model Equations 258 13.6.3 Uncertainty of the Constant in the Individual Predictive Model Equations 259 13.6.4 Uncertainty of Other Factors in the Individual Predictive Model Equation 259 13.6.4.1 Uncertainties of Machine 1 259 13.6.4.2 Uncertainties of Machine 2 260 13.6.4.3 Including Instrument and Measurement Uncertainties 260 13.6.5 Include All Coefficient Uncertainties in the Individual Predictive Model Equations 260 13.6.6 Overall Uncertainty from All Factors in the Individual Predictive Model Equations 261 13.6.7 Quick Overview of Individual Machine Performance Over the Operating Map 262 13.7 Final Answers to All Motivating Questions for the PB Example Experiment 263 13.7.1 Answers to Motivating Question #1 263 13.7.2 Answers to Motivating Question #2 263 13.7.3 Answers to Motivating Question #3 (Expanded from Section 13.3) 263 13.7.4 Answers to Motivating Question #4 264 13.7.5 Other Recommendations (to Our Client) 264 13.8 Conclusions 265 Homework 266 14 Documenting the Experiment: Report Writing 269 14.1 The Logbook 269 14.2 Report Writing 269 14.2.1 Organization of the Reports 270 14.2.2 Who Reads What? 270 14.2.3 Picking a Viewpoint 271 14.2.4 What Goes Where? 271 14.2.4.1 What Goes in the Abstract? 272 14.2.4.2 What Goes in the Foreword? 272 14.2.4.3 What Goes in the Objective? 273 14.2.4.4 What Goes in the Results and Conclusions? 273 14.2.4.5 What Goes in the Discussion? 274 14.2.4.6 References 274 14.2.4.7 Figures 275 14.2.4.8 Tables 276 14.2.4.9 Appendices 276 14.2.5 The Mechanics of Report Writing 276 14.2.6 Clear Language Versus “JARGON” 277 Panel 14.1 The Turbo-Encabulator 278 14.2.7 “Gobbledygook”: Structural Jargon 279 Panel 14.2 U.S. Code, Title 18, No. 793 279 14.2.8 Quantitative Writing 281 14.2.8.1 Substantive Versus Descriptive Writing 281 Panel 14.3 The Descriptive Bank Statement 281 14.2.8.2 Zero-Information Statements 281 14.2.8.3 Change 282 14.3 International Organization for Standardization, ISO 9000 and other Standards 282 14.4 Never Forget. Always Remember 282 Appendix A: Distributing Variation and Pooled Variance 283 A.1 Inescapable Distributions 283 A.1.1 The Normal Distribution for Samples of Infinite Size 283 A.1.2 Adjust Normal Distributions with Few Data: The Student’s t-Distribution 283 A.2 Other Common Distributions 286 A.3 Pooled Variance (Advanced Topic) 286 Appendix B: Illustrative Tables for Statistical Design 289 B.1 Useful Tables for Statistical Design of Experiments 289 B.1.1 Ready-made Ordering for Randomized Trials 289 B.1.2 Exhausting Sets of Two-Level Factorial Designs (≤ Five Factors) 289 B.2 The Plackett–Burman (PB) Screening Designs 289 Appendix C: Hand Analysis of a Two-Level Factorial Design 293 C.1 The General Two-Level Factorial Design 293 C.2 Estimating the Significance of the Apparent Factor Effects 298 C.3 Hand Analysis of a Plackett–Burman (PB) 12-Run Design 299 C.4 Illustrative Practice Example for the PB 12-Run Pattern 302 C.4.1 Assignment: Find Factor Effects and the Linear Coefficients Absent Noise 302 C.4.2 Assignment: Find Factor Effects and the Linear Coefficients with Noise 303 C.5 Answer Key: Compare Your Hand Calculations 303 C.5.1 Expected Results Absent Noise (compare C.4.1) 303 C.5.2 Expected Results with Random Gaussian Noise (cf. C.4.2) 304 C.6 Equations for Hand Calculations 305 Appendix D: Free Recommended Software 307 D.1 Instructions to Obtain the R Language for Statistics 307 D.2 Instructions to Obtain LibreOffice 308 D.3 Instructions to Obtain Gosset 308 D.4 Possible Use of RStudio 309 Index 311

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Book SynopsisThe most complete, one-stop reference for fiber optic sensor theory and application Optical Fiber Sensors: Fundamentals for Development of Optimized Devices constitutes the most complete, comprehensive, and up-to-date reference on the development of optical fiber sensors. Edited by two respected experts in the field and authored by experienced engineers and scientists, the book acts as a guide and a reference for an audience ranging from graduate students to researchers and engineers in the field of fiber optic sensors. The book discusses the fundamentals and foundations of fiber optic sensor technology and provides real-world examples to illuminate and illustrate the concepts found within. In addition to the basic concepts necessary to understand this technology, Optical Fiber Sensors includes chapters on: Distributed sensing with Rayleigh, Raman and Brillouin scattering methods Biomechanical sensing Gas and volatileTable of ContentsList of Contributors xv Acknowledgment xix About the Editors xxi 1 Introduction 1Ignacio R. Matias and Ignacio Del Villar References 14 2 Propagation of Light Through Optical Fibre 17Ignacio Del Villar 2.1 Geometric Optics 17 2.2 Wave Theory 22 2.2.1 Scalar Analysis 23 2.2.2 Vectorial Analysis 26 2.3 Fibre Losses and Dispersion 32 2.4 Propagation in Microstructured Optical Fibre 35 2.5 Propagation in Specialty Optical Fibres Focused on Sensing 37 2.6 Conclusion 45 References 46 3 Optical Fibre Sensor Set-Up Elements 49Minghong Yang and Dajuan Lyu 3.1 Introduction 49 3.2 Light Sources 50 3.2.1 Light-Emitting Diodes 52 3.2.1.1 Surface Light-Emitting Diode 52 3.2.1.2 Side Light-Emitting Diode 52 3.2.2 Laser Diode 53 3.2.2.1 Single-Mode Laser Diode Structure 54 3.2.2.2 Quantum Well Laser Diode 56 3.2.3 Superluminescent Diodes (SLD) 56 3.2.4 Amplified Spontaneous Emission Sources 59 3.2.5 Narrow Line Broadband Sweep Source 62 3.2.6 Broadband Sources 62 3.3 Optical Detectors 63 3.3.1 Basic Principles of Optical Detectors 64 3.3.1.1 PN Photodetector 64 3.3.1.2 PIN Photodetector 65 3.3.1.3 Avalanche Photodiode (APD) 66 3.3.2 Main Characteristics of Optical Detectors 66 3.3.2.1 Operating Wavelength Range and Cut-Off Wavelength 66 3.3.2.2 Quantum Efficiency and Responsiveness 67 3.3.2.3 Response Time 68 3.3.2.4 Materials and Structures of Semiconductor Photodiodes 69 3.3.3 Optical Spectrometers 70 3.4 Light Coupling Technology 71 3.4.1 Coupling of Fibre and Light Source 71 3.4.1.1 Coupling of Semiconductor Lasers and Optical Fibres 71 3.4.1.2 Coupling Loss of Semiconductor Light-Emitting Diodes and Optical Fibres 72 3.4.2 Multimode Fibre Coupled Through Lens 72 3.4.3 Direct Coupling of Fibre and Fibre 73 3.5 Fibre-Optic Device 74 3.5.1 Fibre Coupler 74 3.5.2 Optical Isolator 74 3.5.3 Optical Circulator 76 3.5.4 Fibre Attenuator 76 3.5.5 Fibre Polarizer 76 3.5.6 Optical Switch 77 3.6 Optical Modulation and Interrogation of Optical Fibre-Optic Sensors 77 3.6.1 Intensity-Modulated Optical Fibre Sensing Technology 78 3.6.1.1 Reflective Intensity Modulation Sensor 78 3.6.1.2 Transmissive Intensity Modulation Sensor 80 3.6.1.3 Light Mode (Microbend) Intensity Modulation Sensor 80 3.6.1.4 Refractive Index Intensity-Modulated Fibre-Optic Sensor 80 3.6.2 Wavelength Modulation Optical Fibre Sensing Technology 81 3.6.2.1 Direct Demodulation System 81 3.6.2.2 NarrowBand Laser Scanning System 82 3.6.2.3 Broadband Source Filter Scanning System 83 3.6.2.4 Linear Sideband Filtering Method 84 3.6.2.5 Interference Demodulation System 84 3.6.3 Phase Modulation Optical Fibre Sensing Technology 86 References 87 4 Basic Detection Techniques 91Daniele Tosi and Carlo Molardi 4.1 Introduction 91 4.2 Overview of Interrogation Methods 93 4.3 Intensity-Based Sensors 97 4.3.1 Macrobending 97 4.3.2 In-Line Fibre Coupling 99 4.3.3 Bifurcated Fibre Bundle 100 4.3.4 Smartphone Sensors 100 4.4 Polarization-Based Sensors 102 4.4.1 Pressure and Force Detection 102 4.4.2 Lossy Mode Resonance for Refractive Index Sensing 104 4.5 Fibre-Optic Interferometers 105 4.5.1 Fabry–Pérot Interferometer (FPI)-Based Fibre Sensors 106 4.5.1.1 Extrinsic FPI for Pressure Sensing 107 4.5.1.2 In-Line FPI for Temperature Sensing 108 4.5.2 Mach–Zehnder Interferometer (MZI)-Based Fibre Sensors 109 4.5.3 Single-Multi-Single Mode (SMS) Interferometer-Based Fibre Sensors 109 4.6 Grating-Based Sensors 111 4.6.1 Fibre Bragg Grating (FBG) 111 4.6.2 FBG Arrays 113 4.6.3 Tilted and Chirped FBG 115 4.6.4 Long-Period Grating (LPG) 117 4.6.5 FBG Fabrication 118 4.7 Conclusions 121 References 121 5 Structural Health Monitoring Using Distributed Fibre-Optic Sensors 125Alayn Loayssa 5.1 Introduction 125 5.2 Fundamentals of Distributed Fibre-Optic Sensors 126 5.2.1 Raman DTS 128 5.2.2 Brillouin DTSS 129 5.3 DFOS in Civil and Geotechnical Engineering 130 5.3.1 Bridges 133 5.3.2 Tunnels 134 5.3.3 Geotechnical Structures 137 5.4 DFOS in Hydraulic Structures 141 5.5 DFOS in the Electric Grid 143 5.6 Conclusions 145 References 146 6 Distributed Sensors in the Oil and Gas Industry 151Arthur H. Hartog 6.1 The Late Life Cycle of a Hydrocarbon Molecule 153 6.1.1 Upstream 154 6.1.1.1 Exploration 154 6.1.1.2 Well Construction 155 6.1.1.3 Formation and Reservoir Evaluation 157 6.1.1.4 Production 158 6.1.1.5 Production of Methane Hydrates 159 6.1.1.6 Well Abandonment 160 6.1.2 Midstream: Transportation 160 6.1.3 Downstream: Refinery and Distribution 161 6.2 Challenges in the Application of Optical Fibres to the Hydrocarbon 161 6.2.1 Conditions 161 6.2.2 Conveyance Methods 162 6.2.2.1 Temporary Installations (Intervention Services) 163 6.2.2.2 Permanent Fibre Installations 163 6.2.3 Fibre Reliability 165 6.2.4 Fibre Types 166 6.3 Applications and Take-Up 168 6.3.1 Steam-Assisted Recovery; SAGD 168 6.3.2 Flow Allocation: Conventional Wells 171 6.3.3 Injector Monitoring 174 6.3.4 Thermal Tracer Techniques 175 6.3.5 Water Flow Between Wells 176 6.3.6 Gas-Lift Valves 176 6.3.7 Vertical Seismic Profiling (VSP) 177 6.3.8 Hydraulic Fracturing Monitoring (HFM) 184 6.3.9 Sand Production 185 6.4 Summary 186 References 186 7 Biomechanical Sensors 193Cicero Martelli, Jean Carlos Cardozo da Silva, Alessandra Kalinowski, José Rodolfo Galvão, and Talita Paes 7.1 Optical Fibre Sensors in Biomechanics: Introduction and Review 193 7.2 Optical Fibre Sensors: From Experimental Phantoms to In Vivo Applications 198 7.2.1 Experimental Phantoms and Models 198 7.2.1.1 Joints 199 7.2.1.2 Bones and Muscles 199 7.2.1.3 Teeth, Lower Jaw (Mandible), and Upper Jaw (Maxilla) 200 7.2.1.4 Prosthesis and Extracorporeal Devices 200 7.2.1.5 Sole and Insoles 201 7.2.1.6 Smart Fabrics 201 7.2.1.7 Blood Vessels 202 7.2.1.8 Respiratory Monitoring 203 7.2.2 In Vitro 203 7.2.3 Ex Vivo 204 7.2.3.1 Joints 204 7.2.3.2 Bones and Muscles 205 7.2.3.3 Teeth, Lower Jaw (Mandible), and Upper Jaw (Maxilla) 205 7.2.3.4 Blood Vessels 205 7.2.3.5 Mechanical Properties of Tissues 207 7.2.4 In Vivo 207 7.2.4.1 Joints 207 7.2.4.2 Bones and Muscles 207 7.2.4.3 Teeth, Lower Jaw (Mandible) and Upper Jaw (Maxilla) 208 7.2.4.4 Blood Vessels 208 7.2.4.5 Respiratory Monitoring 208 7.2.5 In Situ 208 7.2.5.1 Joints 209 7.2.5.2 Bones and Muscles 209 7.2.5.3 Prostheses and Extracorporeal Devices 210 7.2.5.4 Soles and Insoles 210 7.2.5.5 Cardiac Monitoring 211 7.2.5.6 Respiratory Monitoring 211 7.3 FBG Sensors Integrated into Mechanical Systems 213 7.3.1 FBG Sensors Glued with Polymer 214 7.3.2 Polymer-Integrated FBG Sensor 215 7.3.3 Smart Fibre Reinforced Polymer (SFRP) 218 7.4 Future Perspective 222 Acknowledgment 223 References 224 8 Optical Fibre Chemical Sensors 239T. Hien Nguyen and Tong Sun 8.1 Introduction 239 8.2 Principles and Mechanisms of Fibre-Optic-Based Chemical Sensing 240 8.2.1 Principle of Chemical Sensor Response 240 8.2.2 Absorption-Based Sensors 242 8.2.3 Luminescence-Based Sensors 243 8.2.4 Surface Plasmon Resonance (SPR)-Based Sensors 245 8.3 Sensor Design and Applications 247 8.3.1 Optical Fibre pH Sensors 247 8.3.1.1 Principle of Fluorescence-Based pH Measurements 248 8.3.1.2 pH Sensor Design 249 8.3.1.3 Set-Up of a pH Sensor System 253 8.3.1.4 Evaluation of the pH Sensor Systems 254 8.3.1.5 Comments 260 8.3.2 Optical Fibre Mercury Sensor 261 8.3.2.1 Sensor Design and Mechanism 262 8.3.2.2 Evaluation of the Mercury Sensor System 265 8.3.2.3 Comments 271 8.3.3 Optical Fibre Cocaine Sensor 271 8.3.3.1 Sensing Methodology 272 8.3.3.2 Design and Fabrication of a Cocaine Sensor System 273 8.3.3.3 Evaluation of the Cocaine Sensor System 275 8.3.3.4 Comments 280 8.4 Conclusions and Future Outlook 281 Acknowledgements 282 References 282 9 Application of Nanotechnology to Optical Fibre Sensors: Recent Advancements and New Trends 289Armando Ricciardi, Marco Consales, Marco Pisco, and Andrea Cusano 9.1 Introduction 289 9.2 A View Back 292 9.3 Nanofabrication Techniques on the Fibre Tip for Biochemical Applications 293 9.3.1 Direct Approaches 294 9.3.2 Indirect Approaches 301 9.3.3 Self-Assembly 305 9.3.4 Smart Materials Integration 307 9.4 Nanofabrication Techniques on the Fibre Tip for Optomechanical Applications 309 9.5 Conclusions 317 References 320 10 From Refractometry to Biosensing with Optical Fibres 331Francesco Chiavaioli, Ambra Giannetti, and Francesco Baldini 10.1 Basic Sensing Concepts and Parameters for OFSs 332 10.1.1 Parameters of General Interest 335 10.1.1.1 Uncertainty 335 10.1.1.2 Accuracy and Precision 335 10.1.1.3 Sensor Drift and Fluctuations 336 10.1.1.4 Repeatability 336 10.1.1.5 Reproducibility 336 10.1.1.6 Response Time 336 10.1.2 Parameters Related to Volume RI Sensing 337 10.1.2.1 Refractive Index Sensitivity 337 10.1.2.2 Resolution 338 10.1.2.3 Figure of Merit (FOM) 339 10.1.3 Parameters Related to Surface RI Sensing 339 10.1.3.1 Sensorgram and Calibration Curve 340 10.1.3.2 Limit of Detection (LOD) and Limit of Quantification (LOQ) 341 10.1.3.3 Specificity (or Selectivity) 345 10.1.3.4 Regeneration (or Reusability) 345 10.2 Optical Fibre Refractometers 347 10.2.1 Optical Interferometers 348 10.2.2 Grating-Based Structures 348 10.2.3 Other Resonance-Based Structures 350 10.3 Optical Fibre Biosensors 352 10.3.1 Immuno-Based Biosensors 353 10.3.2 Oligonucleotide-Based Biosensors 354 10.3.3 Whole Cell/Microorganism-Based Biosensors 357 10.4 Fibre Optics Towards Advanced Diagnostics and Future Perspectives 360 References 361 11 Humidity, Gas, and Volatile Organic Compound Sensors 367Diego Lopez-Torres and César Elosua 11.1 Introduction 367 11.2 Optical Fibre Sensor Specific Features for Gas and VOC Detection 368 11.3 Sensing Materials 370 11.3.1 Organic Chemical Dyes 370 11.3.2 Metal–Organic Framework (MOF) Materials 372 11.3.3 Metallic Oxides 374 11.3.4 Graphene 378 11.4 Detection of Single Gases 379 11.5 Relative Humidity Measurement 383 11.6 Devices for VOC Sensing and Identification 384 11.7 Artificial Systems for Complex Mixtures of VOCs: Optoelectronic Noses 387 11.8 Conclusions 391 References 392 12 Interaction of Light with Matter in Optical Fibre Sensors: A Biomedical Engineering Perspective 399Sillas Hadjiloucas 12.1 Introduction 399 12.2 Energy Content in Light and Its Effect in Chemical Processes 399 12.3 Relevance of Wien’s Law to Physicochemical Processes 402 12.4 Absorption of Light Molecules 403 12.5 The Role of Electron Spin and State Multiplicity in Spectroscopy 404 12.6 Molecular Orbitals, Bond Conjugation, and Photoisomerization 406 12.7 De-excitation Processes Through Competing Pathways: Their Effect on Lifetimes and Quantum Yield 407 12.8 Energy Level Diagrams and Vibrational Sublevels 412 12.9 Distinction Between Absorption and Action Spectra 413 12.10 Light Scattering Processes 414 12.10.1 Elastic Scattering 414 12.10.2 Inelastic Scattering 416 12.11 Induction of Non-linear Optical Processes 418 12.12 Concentrating Fields to Maximize Energy Exchange in the Measurement Process Using Slow Light 419 12.12.1 Slow Light Using Atomic Resonances and Electromagnetically Induced Transparency 419 12.12.2 Slow Light Using Photonic Resonances 424 12.13 Field Enhancement and Improved Sensitivity Through Whispering Gallery Mode Structures 427 12.14 Emergent Technological Trends Facilitating Multi-parametric Interactions of Light with Matter 429 12.14.1 Integration of Optical Fibres with Microfluidic Devices and MEMS 429 12.14.2 Pump–Probe Spectroscopy 430 12.15 Prospects of Molecular Control Using Femtosecond Fibre Lasers 430 12.15.1 Femtosecond Pulse Shaping 430 12.15.2 New Opportunities for Coherent Control of Molecular Processes 432 12.15.3 Developments in Evolutionary Algorithms for Molecular Control 434 References 436 13 Detection in Harsh Environments 441Kamil Kosiel and Mateusz Śmietana 13.1 Introduction 441 13.2 Optical Fibre Sensors for Harsh Environments 442 13.3 Need for Harsh Environment Sensing Based on Optical Fibres 443 13.4 General Requirements for Harsh Environment OFSs 449 13.5 Silica Glass Optical Fibres for Harsh Environment Sensing 451 13.6 Polymer Optical Fibres for Harsh Environment Sensing 461 13.7 Chalcogenide Glass and Polycrystalline Silver Halide Optical Fibres for Harsh Environment Sensing 464 13.8 Monocrystalline Sapphire Optical Fibres for Harsh Environment Sensing 467 13.9 Future Trends in Optical Fibre Sensing 469 References 470 14 Fibre-Optic Sensing: Past Reflections and Future Prospects 477Brian Culshaw and Marco N. Petrovich 14.1 Introductory Comments 477 14.2 Reflections on Achievements to Date 478 14.3 Photonics: How is It Changing? 484 14.4 Some Future Speculation 486 14.4.1 Photonic Integrated and Plasmonic Circuits 487 14.4.2 Metamaterials in Sensing 490 14.4.3 More Variations on the Nano Story 492 14.4.4 Improving the Signal-to-Noise Ratio 493 14.4.5 Quantum Sensing, Entanglement, and the Like 494 14.4.6 The Many Prospects in Fibre Design and Fabrication 495 14.4.7 Technologies Other than Photonics 500 14.4.8 Societal Aspirations in Sensor Technology 501 14.4.9 The Future and a Quick Look at the Sensing Alternatives 501 14.4.10 So What Has Fibre Sensing Achieved to Date 503 14.5 Concluding Observations 504 References 504 Index 511

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Book SynopsisPresents the normal kinematic and dynamic equations for robots, including mobile robots, with coordinate transformations and various control strategies This fully updated edition examines the use of mobile robots for sensing objects of interest, and focus primarily on control, navigation, and remote sensing. It also includes an entirely new section on modeling and control of autonomous underwater vehicles (AUVs), which exhibits unique complex three-dimensional dynamics. Mobile Robots: Navigation, Control and Sensing, Surface Robots and AUVs, Second Edition starts with a chapter on kinematic models for mobile robots. It then offers a detailed chapter on robot control, examining several different configurations of mobile robots. Following sections look at robot attitude and navigation. The application of Kalman Filtering is covered. Readers are also provided with a section on remote sensing and sensors. Other chapters discuss: target tracking, including multiple targets with multiple Table of ContentsPreface xi About the Authors xiii Introduction 1 1 Kinematic Models for Mobile Robots 5 1.1 Introduction 5 1.2 Vehicles with Front-Wheel Steering 5 1.3 Vehicles with Differential-Drive Steering 8 Exercises 11 References 12 2 Mobile Robot Control 13 2.1 Introduction 13 2.2 Front-Wheel Steered Vehicle, Heading Control 13 2.3 Front-Wheel Steered Vehicle, Speed Control 22 2.4 Heading and Speed Control for the Differential-Drive Robot 23 2.5 Reference Trajectory and Incremental Control, Front-Wheel Steered Robot 26 2.6 Heading Control of Front-Wheel Steered Robot Using the Nonlinear Model 31 2.7 Computed Control for Heading and Velocity, Front-Wheel Steered Robot 34 2.8 Heading Control of Differential-Drive Robot Using the Nonlinear Model 36 2.9 Computed Control for Heading and Velocity, Differential-Drive Robot 37 2.10 Steering Control Along a Path Using a Local Coordinate Frame 38 2.11 Optimal Steering of Front-Wheel Steered Vehicle 49 2.12 Optimal Steering of Front-Wheel Steered Vehicle, Free Final Heading Angle 67 Exercises 68 References 69 3 Robot Attitude 71 3.1 Introduction 71 3.2 Definition of Yaw, Pitch, and Roll 71 3.3 Rotation Matrix for Yaw 72 3.4 Rotation Matrix for Pitch 74 3.5 Rotation Matrix for Roll 75 3.6 General Rotation Matrix 77 3.7 Homogeneous Transformation 78 3.8 Rotating a Vector 82 Exercises 83 References 84 4 Robot Navigation 85 4.1 Introduction 85 4.2 Coordinate Systems 85 4.3 Earth-Centered Earth-Fixed Coordinate System 85 4.4 Associated Coordinate Systems 88 4.5 Universal Transverse Mercator Coordinate System 91 4.6 Global Positioning System 93 4.7 Computing Receiver Location Using GPS, Numerical Methods 97 4.7.1 Computing Receiver Location Using GPS via Newton’s Method 97 4.7.2 Computing Receiver Location Using GPS via Minimization of a Performance Index 105 4.8 Array of GPS Antennas 111 4.9 Gimbaled Inertial Navigation Systems 114 4.10 Strap-Down Inertial Navigation Systems 118 4.11 Dead Reckoning or Deduced Reckoning 123 4.12 Inclinometer/Compass 125 Exercises 127 References 131 5 Application of Kalman Filtering 133 5.1 Introduction 133 5.2 Estimating a Fixed Quantity Using Batch Processing 133 5.3 Estimating a Fixed Quantity Using Recursive Processing 134 5.4 Estimating the State of a Dynamic System Recursively 139 5.5 Estimating the State of a Nonlinear System via the Extended Kalman Filter 150 Exercises 165 References 169 6 Remote Sensing 171 6.1 Introduction 171 6.2 Camera-Type Sensors 171 6.3 Stereo Vision 181 6.4 Radar Sensing: Synthetic Aperture Radar 185 6.5 Pointing of Range Sensor at Detected Object 190 6.6 Detection Sensor in Scanning Mode 195 Exercises 199 References 200 7 Target Tracking Including Multiple Targets with Multiple Sensors 203 7.1 Introduction 203 7.2 Regions of Confidence for Sensors 203 7.3 Model of Target Location 211 7.4 Inventory of Detected Targets 215 Exercises 220 References 221 8 Obstacle Mapping and Its Application to Robot Navigation 223 8.1 Introduction 223 8.2 Sensors for Obstacle Detection and Geo-Registration 223 8.3 Dead Reckoning Navigation 225 8.4 Use of Previously Detected Obstacles for Navigation 229 8.5 Simultaneous Corrections of Coordinates of Detected Obstacles and of the Robot 233 Exercises 236 References 237 9 Operating a Robotic Manipulator 239 9.1 Introduction 239 9.2 Forward Kinematic Equations 239 9.3 Path Specification in Joint Space 242 9.4 Inverse Kinematic Equations 242 9.5 Path Specification in Cartesian Space 248 9.6 Velocity Relationships 249 9.7 Forces and Torques 255 Exercises 261 References 262 10 Remote Sensing via UAVs 263 10.1 Introduction 263 10.2 Mounting of Sensors 263 10.3 Resolution of Sensors 264 10.4 Precision of Vehicle Instrumentation 264 10.5 Overall Geo-Registration Precision 265 Exercise 267 References 267 11 Dynamics Modeling of AUVs 269 11.1 Introduction 269 11.2 Motivation 269 11.3 Full Dynamic Model 270 11.4 Hydrodynamic Model 273 11.5 Reduced-Order Longitudinal Dynamics 274 11.6 Computation of Steady Gliding Path in the Longitudinal Plane 276 11.7 Scaling Analysis 279 11.8 Spiraling Dynamics 281 11.9 Computation of Spiral Path 286 Exercises 288 References 289 12 Control of AUVs 291 12.1 Introduction 291 12.2 Longitudinal Gliding Stabilization 291 12.2.1 Longitudinal Dynamic Model Reduction 292 12.2.2 Passivity-Based Controller Design 295 12.2.3 Simulation Results 297 12.3 Yaw Angle Regulation 298 12.3.1 Problem Statement 298 12.3.2 Sliding Mode Controller Design 300 12.3.3 Simulation Results 303 12.4 Spiral Path Tracking 307 12.4.1 Steady Spiral and Its Differential Geometric Parameters 307 12.4.2 Two Degree-of-Freedom Control Design 310 12.4.3 Simulation Results 314 Exercises 321 References 322 Appendix A Demonstrations of Undergraduate Student Robotic Projects 323 Index 327

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Book SynopsisGo in-depth with this comprehensive discussion of distributed energy management Distributed Energy Management of Electrical Power Systems provides the most complete analysis of fully distributed control approaches and their applications for electric power systems available today. Authored by four respected leaders in the field, the book covers the technical aspects of control, operation management, and optimization of electric power systems. In each chapter, the book covers the foundations and fundamentals of the topic under discussion. It then moves on to more advanced applications. Topics reviewed in the book include: System-level coordinated controlOptimization of active and reactive power in power gridsThe coordinated control of distributed generation, elastic load and energy storage systems Distributed Energy Management incorporates discussions of emerging and future technologies and their potential effects on electrical power systems. The increased impact of renewable energy sTable of ContentsAbout the Authors xiii Preface xv Acknowledgment xix List of Figures xxi List of Tables xxxi 1 Background 1 1.1 Power Management 1 1.2 Traditional Centralized vs. Distributed Solutions to Power Management 4 1.3 Existing Distributed Control Approaches 5 2 Algorithm Evaluation 9 2.1 Communication Network Topology Configuration 9 2.1.1 Communication Network Design for Distributed Applications 9 2.1.2 N −1 Rule for Communication Network Design 11 2.1.3 Convergence of Distributed Algorithms with Variant Communication Network Typologies 13 2.2 Real-Time Digital Simulation 16 2.2.1 Develop MAS Platform Using JADE 16 2.2.2 Test-Distributed Algorithms Using MAS 18 2.2.2.1 Three-Agent System on the Same Platform 18 2.2.2.2 Two-Agent System with Different Platforms 19 2.2.3 MAS-Based Real-Time Simulation Platform 20 References 22 3 Distributed Active Power Control 23 3.1 Subgradient-Based Active Power Sharing 23 3.1.1 Introduction 24 3.1.2 Preliminaries - Conventional Droop Control Approach 26 3.1.3 Proposed Subgradient-Based Control Approach 27 3.1.3.1 Introduction of Utilization Level-Based Coordination 27 3.1.3.2 Fully Distributed Subgradient-Based Generation Coordination Algorithm 28 3.1.3.3 Application of the Proposed Algorithm 31 3.1.4 Control of Multiple Distributed Generators 33 3.1.4.1 DFIG Control Approach 33 3.1.4.2 Converter Control Approach 34 3.1.4.3 Pitch Angle Control Approach 35 3.1.4.4 PV Generation Control Approach 36 3.1.4.5 Synchronous Generator Control Approach 36 3.1.5 Simulation Analyses 37 3.1.5.1 Case 1 – Constant Maximum Available Renewable Generation and Load 38 3.1.5.2 Case 2 – Variable Maximum Available Renewable Generation and Load 41 3.1.6 Conclusion 45 3.2 Distributed Dynamic Programming-Based Approach for Economic Dispatch in Smart Grids 46 3.2.1 Introduction 46 3.2.2 Preliminary 49 3.2.3 Graph Theory 49 3.2.4 Dynamic Programming 49 3.2.5 Problem Formulation 49 3.2.6 Economic Dispatch Problem 50 3.2.7 Discrete Economic Dispatch Problem 50 3.2.8 Proposed Distributed Dynamic Programming Algorithm 51 3.2.9 Distributed Dynamic Programming Algorithm 52 3.2.10 Algorithm Implementation 53 3.2.11 Simulation Studies 54 3.2.12 Four-generator System: Synchronous Iteration 54 3.2.12.1 Minimum Generation Adjustment Δpi = 2.5MW 54 3.2.12.2 Minimum Generation Adjustment Δpi = 1.25MW 57 3.2.13 Four-Generator System: Asynchronous Iteration 59 3.2.13.1 Missing Communication with Probability 59 3.2.13.2 Gossip Communication 60 3.2.14 IEEE 162-Bus System 61 3.2.15 Hardware Implementation 63 3.2.16 Conclusion 64 3.3 Constrained Distributed Optimal Active Power Dispatch 65 3.3.1 Introduction 65 3.3.2 Problem Formulation 67 3.3.3 Distributed Gradient Algorithm 68 3.3.4 Distributed Gradient Algorithm 68 3.3.5 Inequality Constraint Handling 70 3.3.6 Numerical Example 72 3.3.6.1 Case 1 72 3.3.6.2 Case 2 74 3.3.7 Control Implementation 75 3.3.8 Communication Network Design 76 3.3.9 Generator Control Implementation 76 3.3.10 Simulation Studies 77 3.3.11 Real-Time Simulation Platform 78 3.3.12 IEEE 30-Bus System 78 3.3.12.1 Constant Loading Conditions 80 3.3.12.2 Variable Loading Conditions 82 3.3.12.3 With Communication Channel Loss 84 3.3.13 Conclusion and Discussion 86 3.A Appendix 86 References 87 4 Distributed Reactive Power Control 97 4.1 Q-Learning-Based Reactive Power Control 97 4.1.1 Introduction 98 4.1.2 Background 99 4.1.3 Algorithm Used to Collect Global Information 99 4.1.4 Reinforcement Learning 101 4.1.5 MAS-Based RL Algorithm for ORPD 101 4.1.6 RL Reward Function Definition 102 4.1.7 Distributed Q-Learning for ORPD 103 4.1.8 MASRL Implementation for ORPD 104 4.1.9 Simulation Results 106 4.1.10 Ward–Hale 6-Bus System 106 4.1.10.1 Learning from Scratch 108 4.1.10.2 Experience-Based Learning 110 4.1.10.3 IEEE 30-Bus System 112 4.1.10.4 IEEE 162-Bus System 114 4.1.11 Conclusion 115 4.2 Sub-gradient-Based Reactive Power Control 116 4.2.1 Introduction 116 4.2.2 Problem Formulation 119 4.2.3 Distributed Sub-gradient Algorithm 120 4.2.4 Sub-gradient Distribution Calculation 122 4.2.4.1 Calculation of 𝜕f ∕𝜕Qci for Capacitor Banks 122 4.2.4.2 Calculation of 𝜕f ∕𝜕Vgi for a Generator 124 4.2.4.3 Calculation of 𝜕f ∕𝜕tti for a Transformer 124 4.2.5 Realization of Mas-Based Solution 126 4.2.5.1 Computation of Voltage Phase Angle Difference 127 4.2.5.2 Generation Control for ORPC 128 4.2.6 Simulation and Tests 129 4.2.6.1 Test of the 6-BusWard–Hale System 129 4.2.6.2 Test of IEEE 30-Bus System 134 4.2.7 Conclusion 141 References 141 5 Distributed Demand-Side Management 147 5.1 Distributed Dynamic Programming-Based Solution for Load Management in Smart Grids 148 5.1.1 System Description and Problem Formulation 150 5.1.2 Problem Formulation 151 5.1.3 Distributed Dynamic Programming 153 5.1.3.1 Abstract Framework of Dynamic Programming (DP) 153 5.1.3.2 Distributed Solution for Dynamic Programming Problem 154 5.1.4 Numerical Example 157 5.1.5 Implementation of the LM System 158 5.1.6 Simulation Studies 160 5.1.6.1 Test with IEEE 14-bus System 160 5.1.6.2 Large Test Systems 166 5.1.6.3 Variable Renewable Generation 168 5.1.6.4 With Time Delay/Packet Loss 170 5.1.7 Conclusion and Discussion 171 5.2 Optimal Distributed Charging Rate Control of Plug-in Electric Vehicles for Demand Management 172 5.2.1 Background 175 5.2.2 Problem Formulation of the Proposed Control Strategy 175 5.2.3 Proposed Cooperative Control Algorithm 180 5.2.3.1 MAS Framework 180 5.2.3.2 Design and Analysis of Distributed Algorithm 180 5.2.3.3 Algorithm Implementation 181 5.2.3.4 Simulation Studies 183 5.3 Conclusion 190 References 191 6 Distributed Social Welfare Optimization 197 6.1 Introduction 197 6.2 Formulation of OEM Problem 200 6.2.1 SocialWelfare Maximization Model 200 6.2.2 Market-Based Self-interest Motivation Model 203 6.2.3 Relationship Between Two Models 204 6.3 Fully Distributed MAS-Based OEM Solution 207 6.3.1 Distributed Price Updating Algorithm 207 6.3.2 Distributed Supply–Demand Mismatch Discovery Algorithm 209 6.3.3 Implementation of MAS-Based OEM Solution 210 6.4 Simulation Studies 212 6.4.1 Tests with a 6-bus System 212 6.4.1.1 Test Under the Constant Renewable Generation 214 6.4.1.2 Test Under Variable Renewable Generation 217 6.4.2 Test with IEEE 30-bus System 218 6.5 Conclusion 221 References 221 7 Distributed State Estimation 225 7.1 Distributed Approach for Multi-area State Estimation Based on Consensus Algorithm 225 7.1.1 Problem Formulation of Multi-area Power System State Estimation 227 7.1.2 Distributed State Estimation Algorithm 228 7.1.3 Approximate Static State Estimation Model 231 7.1.4 Regarding Implementation of Distributed State Estimation 233 7.1.5 Case Studies 234 7.1.5.1 With the Accurate Model 235 7.1.5.2 Comparisons Between Accurate Model and Approximate Model 238 7.1.5.3 With Variable Loading Conditions 239 7.1.6 Conclusion and Discussion 241 7.2 Multi-agent System-Based Integrated Solution for Topology Identification and State Estimation 242 7.2.1 Measurement Model of the Multi-area Power System 244 7.2.2 Distributed Subgradient Algorithm for MAS-Based Optimization 245 7.2.3 Distributed Topology Identification 248 7.2.3.1 Measurement Modeling 248 7.2.3.2 Distributed Topology Identification 251 7.2.3.3 Statistical Test for Topology Error Identification 252 7.2.4 Distributed State Estimation 253 7.2.5 Implementation of the Integrated MAS-Based Solution for TI and SE 254 7.2.6 Simulation Studies 255 7.2.6.1 IEEE 14-bus System 255 7.2.6.2 Large Test Systems 263 7.3 Conclusion and Discussion 266 References 267 8 Hardware-Based Algorithms Evaluation 271 8.1 Steps of Algorithm Evaluation 271 8.2 Controller Hardware-In-the-Loop Simulation 273 8.2.1 PC-Based C-HIL Simulation 274 8.2.2 DSP-Based C-HIL Simulation 277 8.3 Power Hardware-In-the-Loop Simulation 279 8.4 Hardware Experimentation 281 8.4.1 Test-bed Development 281 8.4.2 Algorithm Implementation 284 8.5 Future Work 288 9 Discussion and Future Work 291 References 296 Index 297

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Book SynopsisA guide to the various models and methods to multicriteria decision-making in conditions of uncertainty presented in a systematic approach Multicriteria Decision-Making under Conditions of Uncertaintypresents approaches that help to answer the fundamental questions at the center of all decision-making problems: What to do? and How to do it? The book explores methods of representing and handling diverse manifestations of the uncertainty factor and a multicriteria nature of problems that can arise in system design, planning, operation, and control. The authorsnoted experts on the topicand their book covers essential questions, including notions and fundamental concepts of fuzzy sets, models and methods of multiobjective as well as multiattribute decision-making, the classical approach to dealing with uncertainty of information and its generalization for analyzing multicriteria problems in condition of uncertainty, and more. This comprehensive book contains Table of ContentsPreface xi 1 Decision-Making in Problems of System Design, Planning, Operation, and Control: Motivation, Objectives, and Basic Notions 1 1.1 Decision-Making and Its Support 1 1.2 Problems of Optimization and Decision-Making 7 1.3 Uncertainty Factor and Its Consideration 11 1.4 Multicriteria Decision-Making: Multiobjective and Multiattribute Problems 12 1.5 Group Decision-Making: Basic Notions 15 1.6 Fuzzy Sets in Problems of Decision-Making 19 1.7 Conclusions 23 References 24 2 Notions and Concepts of Fuzzy Sets: An Introduction 29 2.1 Sets and Fuzzy Sets: A Fundamental Departure from the Principle of Dichotomy 29 2.2 Interpretation of Fuzzy Sets 33 2.3 Membership Functions and Classes of Fuzzy Sets 35 2.4 Information Granules and Granular Computing 37 2.4.1 Image Processing 38 2.4.2 Processing and Interpretation of Time Series 38 2.4.3 Granulation of Time 38 2.4.4 Data Summarization 39 2.4.5 Design of Software Systems 39 2.5 Formal Platforms of Information Granularity 39 2.5.1 Symbolic Perspective 41 2.5.2 Numeric Perspective 42 2.6 Intervals and Calculus of Intervals 42 2.6.1 Set-Theoretic Operations 43 2.6.2 Algebraic Operations on Intervals 44 2.6.3 Distance Between Intervals 45 2.7 Fuzzy Numbers and Intervals 45 2.8 Linguistic Variables 46 2.9 A Generic Characterization of Fuzzy Sets: Some Fundamental Descriptors 48 2.10 Coverage of Fuzzy Sets 58 2.11 Matching Fuzzy Sets 59 2.12 Geometric Interpretation of Sets and Fuzzy Sets 60 2.13 Fuzzy Set and Its Family of α-Cuts 61 2.14 Fuzzy Sets of Higher Type and Fuzzy Order 64 2.14.1 Fuzzy Sets of Type −2 64 2.14.2 Fuzzy Sets of Order-2 65 2.15 Operations on Fuzzy Sets 65 2.16 Triangular Norms and Triangular Conorms as Models of Operations on Fuzzy Sets 68 2.17 Negations 70 2.18 Fuzzy Relations 71 2.19 The Concept of Relations 71 2.20 Fuzzy Relations 74 2.21 Properties of the Fuzzy Relations 76 2.21.1 Domain and Codomain of Fuzzy Relations 76 2.21.2 Representation of Fuzzy Relations 76 2.21.3 Equality of Fuzzy Relations 76 2.21.4 Inclusion of Fuzzy Relations 77 2.21.5 Operations on Fuzzy Relations 77 2.21.6 Union of Fuzzy Relations 77 2.21.7 Intersection of Fuzzy Relations 77 2.21.8 Complement of Fuzzy Relations 78 2.21.9 Transposition of Fuzzy Relations 78 2.21.10 Cartesian Product of Fuzzy Relations 78 2.21.11 Projection of Fuzzy Relations 78 2.21.12 Cylindrical Extension 80 2.21.13 Reconstruction of Fuzzy Relations 81 2.21.14 Binary Fuzzy Relations 81 2.21.15 Transitive Closure 82 2.21.16 Equivalence and Similarity Relations 83 2.21.17 Compatibility and Proximity Relations 84 2.22 Conclusions 85 Exercises 85 References 89 3 Design and Processing Aspects of Fuzzy Sets 91 3.1 The Development of Fuzzy Sets: Elicitation of Membership Functions 91 3.1.1 Semantics of Fuzzy Sets: Some General Observations 92 3.1.2 Fuzzy Set as a Descriptor of Feasible Solutions 93 3.1.3 Fuzzy Set as a Descriptor of the Notion of Typicality 95 3.1.4 Vertical and Horizontal Schemes of Membership Function Estimation 96 3.1.5 Saaty’s Priority Approach of Pairwise Membership Function Estimation 99 3.1.6 Fuzzy Sets as Granular Representatives of Numeric Data – The Principle of Justifiable Granularity 103 3.1.7 From Type-0 to Type-1 Information Granules 107 3.2 Weighted Data 108 3.3 Inhibitory Data 109 3.3.1 Design of Fuzzy Sets Through Fuzzy Clustering: From Data to Their Granular Abstraction 110 3.4 Quality of Clustering Results 116 3.4.1 Cluster Validity Indexes 117 3.4.2 Classification Error 118 3.4.3 Reconstruction Error 118 3.5 From Numeric Data to Granular Data 119 3.5.1 Unlabeled Data 119 3.5.2 Labeled Data 119 3.5.3 Fuzzy Equalization as a Way of Building Fuzzy Sets Supported by Experimental Evidence 121 3.5.4 Several Design Guidelines for the Formation of Fuzzy Sets 122 3.6 Aggregation Operations 123 3.6.1 Averaging Operations 124 3.7 Transformations of Fuzzy Sets 125 3.7.1 The Extension Principle 125 3.7.2 Fuzzy Numbers and Fuzzy Arithmetic 128 3.7.3 Interval Arithmetic and α-Cuts 130 3.7.4 Fuzzy Arithmetic and the Extension Principle 131 3.7.5 Computing with Triangular Fuzzy Numbers 136 3.7.6 Addition 136 3.7.7 Multiplication 138 3.7.8 Division 139 3.8 Conclusions 140 Exercises 140 References 144 4 <X, F> Models of Multicriteria Decision-Making and Their Analysis 147 4.1 Models of Multiobjective Decision-Making 147 4.2 Pareto Optimal Solutions 148 4.3 Approaches to Incorporating Decision-Maker Information 150 4.4 Methods of Multiobjective Decision-Making 152 4.4.1 Normalization of Objective Functions 152 4.4.2 Choice of the Principle of Optimality 152 4.4.3 Consideration of Priorities of Objective Functions 152 4.5 Bellman–Zadeh Approach to Decision-Making in a Fuzzy Environment and Its Application to Multicriteria Decision-Making 159 4.6 OWA Operator Applied to Multiobjective Decision-Making 162 4.7 Multiobjective Allocation of Resources and Their Shortages 166 4.7.1 Model 1: Allocation of Available Resources 170 4.7.2 Model 2: Allocation of Resource Shortages with Unlimited Cuts 170 4.7.3 Model 3: Allocation of Resource Shortages with Limited Cuts 171 4.8 Practical Examples of Analyzing Multiobjective Problems 178 4.9 Conclusions 189 Exercises 190 References 192 5 <X, R> Models of Multicriteria Decision-Making and Their Analysis 199 5.1 Introduction to Preference Modeling with Binary Fuzzy Relations 200 5.2 Construction of Fuzzy Preference Relations 205 5.3 Preference Formats 215 5.3.1 Ordering of Alternatives 216 5.3.2 Utility Values 216 5.3.3 Fuzzy Estimates 219 5.3.4 Multiplicative Preference Relations 220 5.4 Transformation Functions and Their Application to Unifying Different Preference Formats 222 5.4.1 Transformation of the Ordered Array into the Additive Reciprocal Fuzzy Preference Relation 223 5.4.2 Transformation of the Utility Values into the Additive Reciprocal Fuzzy Preference Relation 224 5.4.3 Transformation of the Multiplicative Preference Relation into the Additive Reciprocal Fuzzy Preference Relation 225 5.4.4 Transformation of the Nonreciprocal Fuzzy Preference Relation into the Additive Reciprocal Fuzzy Preference Relation 226 5.4.5 Transformation of the Additive Reciprocal Fuzzy Preference Relation into the Nonreciprocal Fuzzy Preference Relation 228 5.4.6 Transformation of the Ordered Array into the Nonreciprocal Fuzzy Preference Relation 229 5.4.7 Transformation of the Utility Values into the Nonreciprocal Fuzzy Preference Relation 230 5.4.8 Transformation of the Multiplicative Preference Relation into the Nonreciprocal Fuzzy Preference Relation 232 5.4.9 Transformation of the Quantitative Information into the Fuzzy Preference Relation 232 5.5 Optimization Problems with Fuzzy Coefficients and Their Analysis 233 5.6 <X, R> Models of Multicriteria Decision-Making 241 5.7 Techniques for Analyzing <X, R> Models 242 5.8 Practical Examples of Analyzing <X, R> Models 251 5.9 Conclusions 264 Exercises 265 References 268 6 Dealing with Uncertainty of Information: A Classic Approach 275 6.1 Characterization of the Classic Approach to Dealing with Uncertainty of Information 275 6.2 Payoff Matrices and Characteristic Estimates 276 6.3 Choice Criteria and Their Application 281 6.4 Elements of Constructing Representative Combinations of Initial Data, States of Nature, or Scenarios 283 6.5 Application Example 285 6.6 Conclusions 288 Exercises 288 References 290 7 Generalization of the Classic Approach to Dealing with Uncertainty of Information and General Scheme of Multicriteria Decision-Making under Conditions of Uncertainty 291 7.1 Generalization of the Classic Approach to Dealing with Uncertainty of Information in Multicriteria Decision Problems 292 7.2 Consideration of Choice Criteria of the Classic Approach to Dealing with Uncertainty of Information as Objective Functions within the Framework of <X, F> Models 299 7.3 Construction of Objectives and Elaboration of Representative Combination of Initial Data, States of Nature, or Scenarios using Qualitative Information 309 7.3.1 Elicitation of Preferences 310 7.3.2 Representation of Preferences Within Multiplicative Preference Relations 312 7.3.3 Definition of Preference Vectors on the Basis of Applying the AHP 314 7.3.4 Aggregation of Preferences and Generation of Representative Combinations of Initial Data, States of Nature, or Scenarios 314 7.4 General Scheme of Multicriteria Decision-Making under Conditions of Uncertainty 315 7.5 Application Studies 317 7.6 Conclusions 333 Exercises 333 References 335 Index 339

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Book SynopsisA comprehensive review of the life cycle processes, methods, and techniques used to develop and modify software-enabled systems Systems Engineering of Software-Enabled Systemsoffers an authoritative review of the most current methods and techniques that can improve the links between systems engineering and software engineering. The authora noted expert on the topicoffers an introduction to systems engineering and software engineering and presents the issues caused by the differences between the two during development process. The book reviews the traditional approaches used by systems engineers and software engineers and explores how they differ. The book presents an approach to developing software-enabled systems that integrates the incremental approach used by systems engineers and the iterative approach used by software engineers. This unique approach is based on developing system capabilities that will provide the features, behaviors, and quality attrTable of ContentsPreface xv Part I Systems Engineering and Software Engineering 1 1 Introduction and Overview 3 1.1 Introduction 3 1.2 The Evolution of Engineering 5 1.3 Characterizations of Systems 8 1.3.1 Open and Closed Systems 9 1.3.2 Static and Dynamic Systems 9 1.3.3 System Boundaries 10 1.3.4 Naturally Occurring Systems 12 1.3.5 Engineered Systems 13 1.3.6 Systems of Systems 17 1.4 Systems Engineering 18 1.4.1 The Systems Engineering Profession 19 1.5 Applications of Systems Engineering 21 1.5.1 Systems Engineering of Products 23 1.5.2 Systems Engineering of Service Provision 23 1.5.3 Systems Engineering for Enterprises 23 1.5.4 Systems Engineering for Systems of Systems 23 1.6 Specialty Engineering 24 1.7 Related Disciplines 25 1.7.1 Industrial Engineering 25 1.7.2 Project Management 26 1.8 Software Engineering 26 1.8.1 The Software Engineering Profession 27 1.9 Applications of Software Engineering 27 1.9.1 Application Packages 28 1.9.2 System Software and Software Utilities 28 1.9.3 Software Tools 29 1.9.4 Software-Intensive Systems 29 1.9.5 Software-Enabled Systems 29 1.10 Physical Systems Engineers and Software Systems Engineers 29 1.11 Key Points 31 Exercises 32 References 34 2 Systems Engineering and Software Engineering 37 2.1 Introduction 37 2.2 Categories of Systems 37 2.3 Common Attributes of PhSEs and SwSEs 39 2.4 Ten Things PhSEs Need to Know About Software and Software Engineering 40 2.4.1 Systems Engineering and Software Engineering are Distinct Disciplines 41 2.4.2 Software is a Logical Medium 41 2.4.3 Exhaustive Testing of Software is Not Feasible 43 2.4.4 Software is Highly Complex 44 2.4.5 Software Conformity Must Be Exact 45 2.4.6 Software is an Invisible Medium 47 2.4.7 Software Appears to Be Easily Changed 48 2.4.8 Software Development is a Team-Oriented, Intellect-Intensive Endeavor 49 2.4.9 Software Developers use Mostly Iterative Processes 52 2.4.10 Software Engineering Metrics and Models are Different in Kind 54 2.5 Ten Things Software Engineers Need to Know About Systems Engineering 55 2.5.1 Most PhSEs Have Traditional Engineering Backgrounds 55 2.5.2 Systems Engineers’Work Activities are Technical and Managerial 56 2.5.3 The Scope of Systems Engineering Work is Diverse 56 2.5.4 Systems Engineers Apply Holistic and Reductionist Thinking 57 2.5.5 Systems Engineering Covers the Full Spectrum of Life-Cycle Processes 57 2.5.6 System Engineers Plan and Coordinate the Work of Interdisciplinary Teams 60 2.5.7 Current Systems Engineering Development Processes are Mostly Incremental 61 2.5.8 Systems Engineering is Transitioning to a Model-Based Approach 61 2.5.9 Some Who Perform Systems Engineering Tasks are Not Called Systems Engineers 62 2.5.10 Most PhSEs View Software Engineers as Disciplinary Engineers or Specialty Engineers 62 2.6 Key Points 63 Exercises 63 References 65 3 Issues and Opportunities for Improvements 67 3.1 Introduction 67 3.2 Some Background 67 3.3 Professional Literacy 69 3.3.1 System Engineering Literacy 69 3.3.1.1 Opportunities for Improving Systems Engineering Literacy of Systems Engineers and Software Engineers 70 3.3.2 Software Engineering Literacy 72 3.3.2.1 Opportunities for Improving Software Engineering Literacy of Systems Engineers and Software Engineers 73 3.4 Differences in Terminology 76 3.4.1 Hierarchical Decomposition 76 3.4.1.1 System Hierarchy 77 3.4.1.2 Software Hierarchy 78 3.4.2 UML Classes and SysML Blocks 79 3.4.3 Performance 80 3.4.4 Prototype 80 3.4.5 Model-Based Engineering 81 3.4.6 Implementation, Construction, and Realization 82 3.4.7 Specialty Engineering and Supporting Processes 83 3.4.8 Opportunities for Improving Usage of Terminology 84 3.5 Differences in Problem-Solving Styles 84 3.5.1 Opportunities for Improving Styles of Problem Solving 86 3.6 Holistic and Reductionist Problem Solving 88 3.6.1 Opportunities for Improving Holistic and Reductionist Thinking 89 3.7 Logical and Physical Design 89 3.7.1 Opportunities for Improving Logical Design and Physical Design Activities 90 3.8 Differences in Process Models and Technical Processes 91 3.8.1 Opportunities for Improving Process Models and Technical Processes 91 3.9 Workplace Respect 91 3.9.1 Opportunities for Improving Workplace Respect 92 3.10 Key Points 93 Exercises 94 References 95 Part II Systems Engineering for Software-Enabled Physical Systems 97 4 Traditional Process Models for System Development 99 4.1 Introduction 99 4.2 Characteristics of Physical Elements and Software Elements 100 4.3 Development Process Foundations 104 4.4 Linear and Vee Development Models 106 4.4.1 The Linear One-Pass Development Model 107 4.4.2 A Linear-Revisions Development Model 108 4.4.3 The Vee Development Model 108 4.4.4 Incremental Vee Development Models 109 4.5 Iterative Development Models 111 4.5.1 Iterative Fabrication of Physical Elements 111 4.5.2 Iterative Construction of Software Elements 112 4.6 The ATM Revisited 115 4.7 Key Points 116 Exercises 117 References 118 5 The Integrated-Iterative-Incremental System Development Model 121 5.1 Introduction 121 5.2 Capabilities-Based System Development 121 5.2.1 Issues and Ameliorations 128 5.3 The I3 System Development Model 129 5.3.1 Systems Engineering During the I3 System Development Phases 130 5.3.2 Synchronizing Realization of Physical Elements and Software Elements 134 5.3.3 Mapping the I3 Development Model to the Technical Processes of 15288 and 12207 135 5.4 Key Points 137 Exercises 139 References 140 6 The I3 System Definition Phase 141 6.1 Introduction 141 6.2 Performing Business or Mission Analysis 141 6.2.1 Business Analysis for the RC-DSS Project 145 6.2.2 RFPs, SOWs, and MOUs 146 6.2.2.1 An RC-DSS MOU 147 6.3 Identifying Stakeholders’ Needs and Defining Their Requirements 149 6.3.1 Identifying System Stakeholders 150 6.3.1.1 Some Clarifying Terminology 151 6.3.1.2 Identifying RC-DSS Stakeholders 153 6.3.2 Eliciting, Categorizing, and Prioritizing Stakeholder Requirements 154 6.3.2.1 Eliciting Stakeholders’ Requirement 154 6.3.2.2 Categorizing Stakeholders’ Requirements 155 6.3.2.3 Prioritizing Stakeholders’ Requirements 157 6.3.3 Defining RC-DSS Stakeholders’ Requirements 158 6.3.3.1 Specifying RC-DSS User Features 158 6.3.3.2 Specifying RC-DSS Quality Attributes 162 6.3.3.3 Specifying RC-DSS Design Constraints 162 6.3.4 The Concept of Operations 163 6.3.4.1 The RC-DSS ConOps 163 6.4 Identifying and Prioritizing System Capabilities 165 6.4.1 Identifying RC-DSS System Capabilities 165 6.4.2 Prioritizing RC-DSS Capabilities 166 6.5 Determining Technical Feasibility 167 6.5.1 Determining RC-DSS Technical Feasibility 168 6.6 Establishing and Maintaining Traceability 170 6.7 Key Points 170 Exercises 171 References 172 7 System Requirements Definition 175 7.1 Introduction 175 7.2 The System Requirements Definition Process 177 7.3 A Requirements Taxonomy 178 7.3.1 Stakeholders’ Requirements and System Capabilities 178 7.3.2 System Requirements 180 7.3.2.1 Primary System Requirements 180 7.3.2.2 Derived System Requirements 181 7.3.2.3 System Design Constraints 182 7.3.2.4 System Design Goals 182 7.3.2.5 System Quality Requirements 183 7.3.2.6 System Interface Requirements 184 7.4 Verifying and Validating System Requirements 187 7.4.1 Verifying System Requirements 188 7.4.1.1 Verifying Implementation Feasibility 189 7.4.1.2 Verifying Coverage of System Capabilities 189 7.4.2 Validating System Requirements 193 7.5 System Requirements for the RC-DSS Case Study 195 7.5.1 RC-DSS Operational Requirements 195 7.6 Key Points 196 Exercises 197 References 199 8 Architecture Definition and Design Definition 201 8.1 Introduction 201 8.2 Principles of Architecture Definition 202 8.2.1 Activities of Architecture Definition 205 8.3 Defining System Architectures 205 8.3.1 Defining System Structure 206 8.3.1.1 Allocating System Requirements to System Architecture 207 8.3.2 Defining System Behavior 208 8.3.2.1 Analyzing System Behavior 209 8.4 Architecture Evaluation Criteria 210 8.5 Selecting the Architecture 212 8.6 Principles of Design Definition 213 8.6.1 Design Evaluation Criteria 214 8.6.2 Logical Design and Physical Design 215 8.6.3 Activities of Design Definition 215 8.6.4 Buying or Building 217 8.6.5 Verifying and Validating the System Design 218 8.7 RC-DSS Architecture Definition 221 8.7.1 RC-DSS Architecture Evaluation 225 8.7.2 RC-DSS Interface Definition 226 8.8 RC-DSS Design Definition 227 8.9 Controlling the Complexity of System Architecture and System Design 228 8.10 Key Points 231 Exercises 232 8.A The System Modeling Language (SysML) 233 8.A.1 SysML Structure Diagrams 234 8.A.2 SysML Behavior Diagrams 235 8.A.3 SysML Crosscutting Diagrams 238 References 239 9 SystemImplementation and Delivery 241 9.1 Introduction 241 9.2 I3 Phases 5 and 6 241 9.3 I3 System Implementation 244 9.3.1 Subphase Planning 250 9.3.2 Realization, Integration, Verification, and Validation of System Capabilities 252 9.4 I3 System Delivery 252 9.5 Key Points 253 Exercises 254 References 255 Part III Technical Management of Systems Engineering 257 10 Planning and Estimating the Technical Work 259 10.1 Introduction 259 10.2 Documenting the Technical Work Plan (SEMP) 260 10.2.1 Documenting Other Technical Processes 262 10.2.2 Developing the Initial Plan 267 10.3 The Estimation Process 268 10.3.1 An Inverse Estimation Process 271 10.3.2 Making an Initial Estimate 272 10.4 Estimation Techniques 273 10.4.1 Rule of Thumb Estimation 273 10.4.2 Estimation by Analogy 274 10.4.3 Expert Judgment 275 10.4.4 The Delphi Method 276 10.4.5 Wideband Delphi Estimation 277 10.4.6 Regression-Based Estimation Models 278 10.4.7 Monte Carlo Estimation 279 10.4.8 Bottom-Up Estimation 281 10.5 Documenting an Estimate 283 10.5.1 An Estimation Template 286 10.6 Key Points 287 Exercises 288 References 289 11 Assessing, Analyzing, and Controlling Technical Work 291 11.1 Introduction 291 11.2 Assessing and Analyzing Process Parameters 292 11.2.1 Assessing and Analyzing Effort 293 11.2.2 Assessing and Analyzing Binary Progress 295 11.2.3 Estimating Future Status 297 11.2.4 Assessing and Analyzing Technical Debt 299 11.2.5 Assessing and Analyzing Earned Value 301 11.2.6 Assessing and Controlling Risk 307 11.3 Assessing and Analyzing System Parameters 316 11.3.1 Direct and Indirect Measures 319 11.3.2 Surrogate Measures 321 11.3.3 Technical Performance Measurement 321 11.4 Corrective Action 322 11.4.1 Acceptable Corrective Action 322 11.4.2 Unacceptable Corrective Action 323 11.4.3 Inhibitors of Corrective Action 323 11.5 Key Points 325 Exercises 227 References 328 12 Organizing, Leading, and Coordinating 329 12.1 Introduction 329 12.2 Managing Versus Leading 330 12.3 The Influence of Corporate Culture 331 12.4 Responsibility and Authority 334 12.4.1 Responsibility 334 12.4.2 Authority 334 12.5 Teams and Teamwork 335 12.5.1 Lone Wolves 336 12.5.2 Teamicide 337 12.5.2.1 Defensive Management 337 12.5.2.2 Mindless Bureaucracy 338 12.5.2.3 Unrealistic Deadlines 339 12.5.2.4 Physical Separation 339 12.5.2.5 Fragmentation of Time 340 12.5.2.6 Clique Control 341 12.5.2.7 Quality Reduction 341 12.6 Maintaining Motivation and Morale 342 12.7 Can’t Versus Won’t 344 12.8 Fourteen Guidelines for Organizing and Leading Engineering Teams 345 12.8.1 Use the Best People You Can Find 346 12.8.1.1 Develop a Key Personnel Plan 347 12.8.2 Treat Engineers as Assets Rather than Costs 349 12.8.3 Provide a Balance Between Job Specialization and Job Variety 349 12.8.4 Keep Team Members Together 349 12.8.5 Limit the Size of Each Team 350 12.8.6 Differentiate the Role of Team Leader 351 12.8.7 Each Team Leader Should Be the Team’s Quality Control Agent 351 12.8.8 Safeguard Individual Productivity and Quality Data 352 12.8.9 Decompose Tasks into Manageable Units of Work 353 12.8.10 Set Performance Goals for Each Team 353 12.8.11 Adopt a Contractual Model for Commitments 354 12.8.12 Ensure Daily Interactions with Team Leaders and Team Members 355 12.8.13 Conduct Weekly Status Review Meetings 355 12.8.13.1 Maintain Weekly Top-N Lists at All Levels of a Systems Project 356 12.8.13.2 Conduct Retrospective and Planning Meetings 359 12.8.14 Structure Large Projects as Collections of Highly Cohesive, Loosely Coupled Small Projects 359 12.8.14.1 A Rule of Thumb 360 12.9 Summary of the Guidelines 362 12.10 Key Points 363 Exercises 364 References 365 Appendix A The Northwest Hydroelectric System 367 A.1 Background 367 A.2 Purpose 369 A.3 Challenges 371 A.4 Systems Engineering Practices 372 A.4.1 Product Provisioning 372 A.4.2 Service Provisioning 373 A.4.3 Enterprise Provisioning 374 A.4.4 System-of-Systems Provisioning 374 A.5 Lessons Learned 375 References 375 Appendix B Automobile Embedded Real-Time Systems 377 B.1 Introduction 377 B.2 Electronic Control Units 378 B.3 ECU Domains 382 B.4 The Powertrain Domain (Engine and Transmission) 383 B.5 The Chassis Domain 384 B.6 The Body Domain 384 B.7 The Infotainment Domain 385 B.8 An Emerging Domain 385 B.9 The ECU Network 386 B.10 Automotive Network Domains 386 B.11 Network Protocols 387 B.12 Summary 388 References 389 Glossary of Terms 391 Index 397

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Book SynopsisMULTIFUNCTIONAL ANTENNAS AND ARRAYS FOR WIRELESS COMMUNICATION SYSTEMS Offers an up-to-date discussion of multifunctional antennas and arrays for wireless communication systemsMultifunctional Antennas and Arrays for Wireless Communication Systems is a comprehensive reference on state-of-the-art reconfigurable antennas and 4G/5G communication antennas. The book gives a unique perspective while giving a comprehensive overview of the following topics:Frequency reconfigurable antennasPattern reconfigurable antennasPolarization reconfigurable antennasReconfigurable antennas using Liquid Metal, Piezoelectric, and RF MEMSMIMO and 4G/5G wireless communication antennasMetamaterials and metasurfaces in reconfigurable antennasMultifunctional antennas for user equipments (UEs)Defense related antennas and applicationsFlat panel phased array antennasThe book is a valuable resource for the practicing engineer as well as for those within the research field. As wireless communications continuously evolTable of ContentsList of Contributors xi Preface xii Acknowledgements xv 1 Introduction 1Satish K. Sharma and Jia-Chi S. Chieh 1.1 Introduction 1 1.2 Antenna: an Integral Component of Wireless Communications 1 1.3 Antenna Performance Parameters 2 1.4 Antenna Types 2 1.5 Multifunctional Antennas 3 1.6 Reconfigurable Antennas 6 1.7 Frequency Agile/Tunable Antenna 13 1.8 Antenna Measurements 17 1.9 Conclusion 18 References 18 2 Frequency Reconfigurable Antennas 19Saeed I. Latif and Satish K. Sharma 2.1 Introduction 19 2.2 Mechanism of Frequency Reconfigurability 20 2.3 Types of FRAs 21 2.3.1 Frequency Reconfigurability by Switches/Tunable Components 21 2.3.1.1 Electrical Switches 22 2.3.1.2 Varactor Diodes 31 2.3.1.3 Micro-Electro-Mechanical-System (MEMS) Switches 40 2.3.1.4 Optical Switches 40 2.3.1.5 Ground Plane Membrane Deflection 43 2.3.2 Frequency Reconfigurability Using Special Materials 43 2.3.2.1 Liquid Crystals 45 2.3.2.2 Graphene 47 2.3.3 Frequency Reconfigurability by Mechanical Changes 49 2.3.3.1 Actuators 49 2.3.3.2 Motors 50 2.3.4 Frequency Reconfigurability Using Special Shapes 53 2.3.4.1 Origami Antennas 53 2.3.4.2 Fractal Shapes 54 2.4 FRAs in the Future: Applications in Emerging Technologies 58 2.5 Conclusion 59 References 59 3 Radiation Pattern Reconfigurable Antennas 67Sima Noghanian and Satish K. Sharma 3.1 Introduction 67 3.2 Pattern Reconfigurable by Electronically Changing Antenna Elements 67 3.3 Pattern Reconfigurable by Electronically Changing Feeding Network 88 3.4 Mechanically Controlled Pattern Reconfigurable Antennas 90 3.5 Arrays and Optimizations 98 3.6 Reconfigurable Wearable and Implanted Antennas 110 3.7 Conclusion 119 References 119 4 Polarization Reconfigurable Antennas 122Behrouz Babakhani and Satish K. Sharma 4.1 Introduction 122 4.2 Polarization Reconfiguration Mechanism Using RF Switches 124 4.3 Solid-State RF Switch-Based Polarization Reconfigurable Antenna 125 4.4 Mechanical and Micro-electro-mechanical (MEMS) RF Switch-Based Antennas 140 4.5 Switchable Feed Network-Based Polarization Reconfiguration 148 4.6 Polarization Reconfigurable Antennas Using Metasurface 157 4.7 Other Methods to Create Polarization Reconfigurable Antennas 162 4.8 Conclusion 169 References 169 5 Liquid Metal, Piezoelectric, and RF MEMS-Based Reconfigurable Antennas 172Jia-Chi S. Chieh and Satish K. Sharma 5.1 Introduction 172 5.2 Liquid Metal – Frequency Reconfigurable Antennas 172 5.3 Liquid Metal – Pattern Reconfigurable Antennas 175 5.4 Liquid Metal – Directivity Reconfigurable Antennas 182 5.5 Piezoelectric – Pattern Reconfigurable Array 184 5.6 RF MEMS – Frequency Reconfigurable 189 5.7 RF MEMS – Polarization Reconfigurable 191 5.8 RF MEMS – Pattern Reconfigurable 194 5.9 Conclusion 196 References 197 6 Compact Reconfigurable Antennas 198Sima Noghanian and Satish K. Sharma 6.1 Introduction 198 6.2 Reconfigurable Pixel Antenna 199 6.3 Compact Reconfigurable Antennas Using Fluidic 209 6.4 Compact Reconfigurable Antennas Using Ferrite and Magnetic Materials 213 6.5 Metamaterials and Metasurfaces 224 6.6 Conclusion 229 References 229 7 Reconfigurable MIMO Antennas 232Kumud R. Jha and Satish K. Sharma 7.1 Introduction 232 7.2 Reconfigurable Antennas for MIMO Applications 234 7.3 Isolation Techniques in MIMO Antennas 237 7.3.1 Decoupling Network 237 7.3.2 Neutralization Lines 238 7.3.3 Using Artificial Material 240 7.3.4 Defected Ground Plane 241 7.4 Pattern Diversity Scheme 241 7.5 Reconfigurable Polarization MIMO Antenna 244 7.6 MIMO Antenna Performance Parameters 254 7.6.1 Envelope Correlation Coefficient (ECC) 254 7.6.2 Total Active Reflection Coefficient (TARC) 255 7.6.3 Mean Effective Gain (MEG) 256 7.6.4 Diversity Gain 257 7.7 Some Reconfigurable MIMO Antenna Examples 258 7.8 Conclusion 274 References 274 8 Multifunctional Antennas for 4G/5G Communications and MIMO Applications 279Kumud R. Jha and Satish K. Sharma 8.1 Introduction 279 8.2 MIMO Antennas in Multifunctional Systems 281 8.3 MIMO Antennas in Radar Systems 284 8.4 MIMO Antennas in Communication Systems 290 8.5 MIMO Antennas for Sensing Applications 290 8.6 MIMO Antennas for 5G Systems 292 8.7 Massive MIMO Array 293 8.8 Dielectric Lens for Millimeter Wave MIMO 298 8.9 Beamforming in Massive MIMO 301 8.10 MIMO in Imaging Systems 303 8.11 MIMO Antenna in Medical Applications 306 8.11.1 Ex-VIVO Applications 306 8.11.2 MIMO Antenna for Medical Imaging 309 8.11.3 Wearable MIMO Antenna 309 8.11.4 MIMO Indigestion Capsule 310 8.11.5 Reconfigurable Antennas in Bio-Medical Engineering 313 8.12 Conclusion 316 References 317 9 Metamaterials in Reconfigurable Antennas 321Saeed I. Latif and Satish K. Sharma 9.1 Introduction 321 9.2 Metamaterials in Antenna Reconfigurability 321 9.3 Metamaterial-Inspired Reconfigurable Antennas 322 9.3.1 Metamaterial-Based Frequency Reconfigurability 323 9.3.2 Metamaterial-Based Pattern Reconfigurability 325 9.3.3 Metamaterial-Based Polarization Reconfigurability 328 9.4 Metasurface-Inspired Reconfigurable Antennas 333 9.5 Conclusion 336 References 337 10 Multifunctional Antennas for User Equipments (UEs) 341Satish K. Sharma and Sonika P. Biswal 10.1 Introduction 341 10.2 Lower/ Sub-6 GHz 5G Band Antennas 342 10.3 5G mm-Wave Antenna Arrays 353 10.4 Collocated Sub-6 GHz and mm-Wave 5G Array Antennas 360 10.5 RF and EMF Exposure Limits 369 10.6 Conclusion 374 References 374 11 DoD Reconfigurable Antennas 378Jia-Chi S. Chieh and Satish K. Sharma 11.1 Introduction 378 11.2 TACAN 378 11.2.1 TACAN Antenna 379 11.2.2 Course Bearing 382 11.2.3 Fine Bearing 382 11.3 Sea-Based X-Band Radar 1 (SBX-1) 383 11.4 The Advanced Multifunction RF Concept (AMRFC) 384 11.5 Integrated Topside (InTop) 390 11.5.1 Wavelength Scaled Arrays 390 11.5.2 Low-Cost Multichannel Microwave Frequency Phased Array Chipsets on Si and SiGe 394 11.6 DARPA Arrays of Commercial Timescales (ACT) 400 11.7 AFRL Transformational Element Level Array (TELA) 405 11.8 Conclusion 406 References 408 12 5G Silicon RFICs-Based Phased Array Antennas 409Jia-Chi S. Chieh and Satish K. Sharma 12.1 Introduction 409 12.2 Silicon Beamformer Technology 409 12.3 LO-Based Phase Shifting 413 12.4 IF-Based Phase Shifting 414 12.5 RF-Based Phase Shifting 415 12.6 Ku-Band Phased Arrays Utilizing Silicon Beamforming Chipsets 422 12.7 Ku-Band Phased Arrays on ROHACELL Utilizing Silicon Beamforming Chipsets 425 12.8 Ku-Band Phased Arrays with Wide Axial Ratios Utilizing Silicon Beamforming Chipsets 431 12.9 28GHz Phased Arrays Utilizing Silicon Beamforming Chipsets 433 12.10 Phased Array Reflectors Utilizing Silicon Beamforming Chipsets 438 12.11 Conclusion 442 References 443 Index 445

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Book SynopsisThis is the most comprehensive and in-depth study of the theory and practical applications of a new and groundbreaking method for the energy industry to go green with renewable and alternative energy sources. The global warming phenomenon as a significant sustainability issue is gaining worldwide support for development of renewable energy technologies. The term polygeneration is referred to as an energy supply system, which delivers more than one form of energy to the final user. For example, electricity, cooling and desalination can be delivered from a polygeneration process. The polygeneration process in a hybrid solar thermal power plant can deliver electricity with less impact on the environment compared to a conventional fossil fuel-based power generating system. It is also THE next generation energy production technique with the potential to overcome the undesirable intermittence of renewable energy systems. In this study, the polygeneration process simulTable of ContentsContents Foreword ix Preface xi 1. Introduction 1 1.1. Global Scenario on Renewable Energy 3 1.2. Indian Scenario on Renewable Energy 6 Exercise 8 References 9 2. State-of-the-Art Concentrated Solar Thermal Technologies for End Use Applications 11 2.1. Solar Thermal Technologies for Low Grade Heat Applications 11 2.1.1. Flat Plate Collector System 12 2.1.2. Built-In Storage Solar Water Heating System 15 2.1.3. Evacuated Tubular Collector System 16 ETC Water Heating System Specification 18 2.1.4. Cumulative Growth of SWHS Installation Capacity 20 2.1.5. Performance Evaluation of SWHs 20 2.1.6. Cost Benefits Analysis 23 2.2. Solar Cooking 25 2.2.1. Thermal Performance of Solar Box Type Cooker 30 2.3. Solar Thermal Cooling 35 2.4. Desalination System 38 2.5. Industrial Process Heat applications 45 2.6. Solar Thermal Technologies for Power Generation 49 2.6.1. Parabolic Trough Collector 49 2.6.2. Linear Fresnel Reflector 51 2.6.3. Central Solar Tower 53 2.6.4. Parabolic Dish 54 2.7. Cooling with Process Heat in Cogeneration Process for Industrial Applications 57 2.7.1. System Description 58 Exercise 61 References 62 3. Resource Assessment of Solar and Biomass for Hybrid Thermal Power Plant 69 3.1. Apparent Solar Time 70 3.2. Solar Angles 71 3.3. Solar Resources (DNI) In India 76 3.3.1. Solar DNI from Satellite and Ground Measured Data 76 3.3.2. DNI Assessment at NISE 78 3.4. Biomass Resources in India 81 3.5. Analysis of Solar DNI And Biomass Resources for Hybrid Power Plants 83 Exercise 106 References 106 4. Solar Thermal Power Plant 109 4.1. A Case Study of 1 MWe Solar Thermal Power Plant 122 4.2. Major Components 124 4.2.1. Parabolic Trough Collector 124 4.2.2. Linear Fresnel Reflector 125 4.2.3. Storage 127 4.2.4. Nitrogen Blanketing System 129 4.2.5. Heat Exchanger 129 4.2.6. Power Block 132 4.2.7. Balance of Plant-Utility Systems 134 4.3. Performance of the Plant 136 Exercise 161 References 162 5. Modeling and Simulation of Hybrid Solar and Biomass Thermal Power Plant 163 5.1. Modeling Approach of a Hybrid Solar-Biomass Thermal Power Plant 167 5.2. Thermodynamic Evaluation 168 5.2.1. Energy Evaluation 169 5.2.2. Exergy Evaluation 174 5.3. Analysis of Hybrid Solar and Biomass Thermal Power Plant 177 Exercise 181 References 182 6. Modeling, Simulation, Optimization and Cost Analysis of a Polygeneration Hybrid Solar Biomass System 187 6.1. Modeling Approach of Polygeneration Process in an HSB Thermal Power Plant 191 6.2. Thermodynamic Evaluation 193 6.2.1. Energy Evaluation 193 6.2.2. Exergy Evaluation 201 6.3. Primary Energy Savings on the Polygeneration Process in an HSB Thermal Power Plant 206 6.4. Optimization 207 6.4.1. Objective Functions 207 6.4.2. Decision Variable and Constraints 207 6.4.3. Genetic Algorithm (GA) 207 6.5. Cost Analysis 209 6.6. Analysis Of Polygeneration Process in an HSB Thermal Power Plant for Power, Cooling, and Desalination 211 6.7. Optimization of the Polygeneration System 216 6.8. Cost Analysis of a Polygeneration System 220 Exercise 224 References 226 Appendix 1 231 Nomenclature 231 Greek 233 Subscripts 233 Acronyms 234 Appendix 2. 237 EES Software Coding 237 Appendix 3. 253 Multiple Choice Questions (MCQ) with Answers. 253 Answers 274 About the Author 275 Index 277

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Book SynopsisThe definitive reference work with comprehensive analysis and review of peer production Peer production is no longer the sole domain of small groups of technical or academic elites. The internet has enabled millions of people to collectively produce, revise, and distribute everything from computer operating systems and applications to encyclopedia articles and film and television databases. Today, peer production has branched out to include wireless networks, online currencies, biohacking, and peer-to-peer urbanism, amongst others. The Handbook of Peer Production outlines central concepts, examines current and emerging areas of application, and analyzes the forms and principles of cooperation that continue to impact multiple areas of production and sociality. Featuring contributions from an international team of experts in the field, this landmark work maps the origins and manifestations of peer production, discusses the factors and conditions that are enabling, advancing, and co-opTable of ContentsPreface Author biographies Chapter summaries List of tables List of figures Part I – Introduction Chapter 01 – The Duality of Peer Production: Infrastructure for the Commons, Free Labor for Firms (Mathieu O�Neil, Sophie Toupin & Christian Pentzold) Part II – Concepts: Explaining Peer Production Chapter 02 – Grammar of Peer Production (Vasilis Kostakis & Michel Bauwens) Chapter 03 – Political Economy of Peer Production (Benjamin Birkinbine) Chapter 04 – Social Norms and Rules of Peer Production (Christian Pentzold) Chapter 05 – Cultures of Peer Production (Michael Stevenson) Chapter 06 (reprint) – Commons-Based Peer Production and Virtue (Yochai Benkler & Helen Nissenbaum) Part III – Conditions: Enabling Peer Production Chapter 07 – Prophets and Advocates (George Dafermos) Chapter 08 – Virtue, Efficiency, and the Sharing Economy (Margie Borschke) Chapter 09 – Openness and Licensing (Mélanie Dulong de Rosnay) Chapter 10 – User Motivations in Peer Production (Sebastian Spaeth & Sven Niederhöfer) Chapter 11 – Governing for Growth in Scope: Cultivating a Dynamic Understanding of How Peer Production Collectives Evolve (Rebecca Karp, Amisha Miller & Siobhan O�Mahony) Part IV – Cases: Realizing Peer Production Chapter 12 – Free & Open Source Software (Stéphane Couture) Chapter 13 – Wikipedia and Wikis (Jutta Haider & Olof Sundin) Chapter 14 – Hacker Cartography: Participatory Mapmaking and Technological Power (Adam Fish) Chapter 15 – Peer Learning (Panayotis Antoniadis & Alekos Pantazis) Chapter 16 – Biohacking (Morgan Meyer) Chapter 17 – Makers (Yana Boeva & Peter Troxler) Chapter 18 – Blockchain (Pablo Velasco Gonzáles & Nate Tkacz) Chapter 19 – Wireless Community Networks (Gwen Shaffer) Chapter 20 – Urban Commons (Nicholas Anastasopoulos) Part V – Conflicts: Peer Production and the World Chapter 21 – Peer Production and Social Change (Mathieu O�Neil & Sébastien Broca) Chapter 22 – Peer Production and Collective Action (Stefania Milan) Chapter 23 – Feminist Peer Production (Sophie Toupin) Chapter 24 – Postcolonial Peer Production (Maitrayee Deka) Chapter 25 – Gaps in Peer Design (Francesca Musiani) Chapter 26 – Makerspaces and Peer Production: Spaces of Possibility, Tension, Post-Automation, or Liberation? (Kat Braybrooke & Adrian Smith) Chapter 27 – Peer Production and State Theory: Envisioning a Cooperative Partner State (Alex Pazaitis & Wolfgang Drechsler) Part VI – Conversions: Advancing Peer Production Chapter 28 – Making a Case for Peer Production: Interviews with Peter Bloom, Mariam Mecky, Ory Okolloh, Abraham Taherivand & Stefano Zacchiroli Chapter 29 – What�s Next? Peer Production Studies? (Mathieu O�Neil, Sophie Toupin & Christian Pentzold) Chapter 30 – Be Your Own Peer! Principles and Policies for the Commons (Mathieu O�Neil, Sophie Toupin & Christian Pentzold)

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Book SynopsisA guide to the applications of holographic techniques for microwave and millimeter wave imaging Real-Time Three-Dimensional Imaging of Dielectric Bodies Using Microwave/Millimeter Wave Holography offers an authoritative guide to the field of microwave holography for the specific application of imaging dielectric bodies. The authorsnoted experts on the topicreview the early works in the area of optical and microwave holographic imaging and explore recent advances of the microwave and millimeter wave imaging techniques. These techniques are based on the measurement of both magnitude and phase over an aperture and then implementing digital image reconstruction. The book presents developments in the microwave holographic techniques for near-field imaging applications such as biomedical imaging and non-destructive testing of materials. The authors also examine novel holographic techniques to gain super-resolution or quantitative images. The book also includesTable of ContentsPreface xi Acknowledgments xiii 1 Introduction 1 1.1 Some Emerging Applications of MMI 2 1.2 Quantitative Versus Qualitative MMI 7 1.3 Advantages of Holographic MMI Techniques 10 1.4 Chronological Developments in the Holographic MMI Techniques 11 1.5 Future Outlook for Holographic MMI for Real-Time 3D Imaging Applications 14 2 Microwave/Millimeter Wave Holography Based on the Concepts of Optical Holography 17 2.1 Microwave Hologram Formation 18 2.2 Microwave Detectors and Sampling Methods for Intensity Hologram Measurements 20 2.3 Wave Front Reconstruction 22 2.4 Recent Indirect Holographic Imaging Techniques 24 2.4.1 Producing Reference Signal with a Linear Phase Shift 25 2.4.2 Sample Imaging Results 28 3 Direct and Quasi-Microwave/Millimeter-Wave Holography for Far-Field Imaging Applications 33 3.1 Using Microwave and Millimeter-Wave Holography for Concealed Weapon Detection 33 3.2 Monostatic 2D SAR Imaging 34 3.3 Development of 3D Quasi-Holographic Imaging as a Combination of Monostatic 2D SAR Imaging and True 2D Holographic Imaging 37 3.3.1 Single-Frequency Holographic 2D Imaging 37 3.3.2 Wideband Holographic 3D Imaging with Data Collected over Rectangular Apertures 40 3.3.2.1 Spatial and Frequency Sampling 43 3.3.2.2 Range and Cross-Range Resolution 44 3.3.2.3 Sample Experimental Images 46 3.3.3 Wideband Holographic 3D Imaging with Data Collected over Cylindrical Apertures 52 3.3.3.1 Image Reconstruction Technique 52 3.3.3.2 Sampling Criteria and Spatial Resolution 55 3.3.3.3 Image Reconstruction Results 56 4 Microwave/Millimeter-Wave Holography for Near-Field Imaging Applications 63 4.1 2D Near-Field Holographic Imaging 63 4.1.1 Using All Reflection and Transmission S-Parameters 65 4.1.2 Localization of the Object Along the Range 66 4.1.3 Image Reconstruction Results 69 4.2 3D Near-Field Holographic Imaging Using Incident Field and Green’s Function 71 4.2.1 Image Reconstruction Results 75 4.2.2 Suppressing Artifacts Along Range 79 4.3 Microwave Holographic Imaging Employing Forward-Scattered Waves Only 82 4.3.1 Resolution in a Two-Antenna Configuration 83 4.3.2 Multiple Receiver Setup 88 4.3.3 Holographic Image Reconstruction 89 4.4 Microwave Holographic Imaging Employing PSF of the Imaging System 91 4.4.1 Using Measured PSF in Holographic Reconstruction 91 4.4.2 Using Multiple Receivers in 3D Reconstruction 92 4.4.3 Simulated Image Reconstruction Results 93 4.4.4 Experimental Results with Open-Ended Waveguides 95 4.4.5 3D Imaging of Small Objects with the Bow-Tie Array 99 4.4.6 Imaging of Large Objects with the Bow-Tie Array 102 4.5 3D Near-Field Holographic Imaging with Data Acquired over Cylindrical Apertures 102 4.5.1 Imaging Results 107 4.6 Three-Dimensional Holographic Imaging Using Single-Frequency Microwave Data 109 4.7 Microwave Holographic Imaging Using the Antenna Phaseless Radiation Pattern 110 4.7.1 Using Phaseless Antenna Pattern in Holographic Reconstruction 111 4.7.2 Image Reconstruction Results 113 5 Increasing the Resolution and Accuracy of Microwave/Millimeter-Wave Holography 119 5.1 Imaging Beyond the Diffraction Limit by Applying a SOF 119 5.1.1 Design of 1D and 2D SOFs 119 5.1.2 Application of the SOF to Overcome the Diffraction-Limited Resolution 121 5.1.3 Sample Image Reconstruction Results 122 5.2 Use of Resonant Scatterers in the Proximity of the Imaged Objects 122 5.3 Quantitative Reconstruction Based on Microwave Holography 124 5.4 Modifications on Holographic Imaging Improving Stability and Range Resolution 128 5.4.1 Forward Model in Terms of the Open-Circuit Voltage at the Terminals of Probe Antenna 129 5.4.2 Applying an Auxiliary Equation for Numerical Stability 132 5.4.3 Phase Compensation Method 132 5.4.4 Numerical Low-Pass Filter in Spatial-Frequency Domain 134 5.4.5 Simulation Results 136 6 Conclusion 139 Appendix: Diffraction Limit for the Spatial Resolution in Far-Field Imaging 141 References 143 Index 153

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