Electronics and communications engineering Books

Book SynopsisBattery technology is constantly changing, and the concepts and applications of these changes are rapidly becoming increasingly more important as more and more industries and individuals continue to make greener choices in their energy sources. As global dependence on fossil fuels slowly wanes, there is a heavier and heavier importance placed on cleaner power sources and methods for storing and transporting that power. Battery technology is a huge part of this global energy revolution. Zinc batteries are an advantageous choice over lithium-based batteries, which have dominated the market for years in multiple areas, most specifically in electric vehicles and other battery-powered devices. Zinc is the fourth most abundant metal in the world, which is influential in its lower cost, making it a very attractive material for use in batteries. Zinc-based batteries have been around since the 1930s, but only now are they taking center stage in the energy, automotive, and other industTable of ContentsPreface xiii 1 Carbon Nanomaterials for Zn-Ion Batteries 1Prasun Banerjee, Adolfo Franco Jr, Rajender Boddula, K. Chandra Babu Naidu and Ramyakrishna Pothu 1.1 Introduction 2 1.2 Co4N (CN) - Carbon Fibers Network (CFN) -Carbon Cloth (CC) 2 1.3 N-Doping of Carbon Nanofibers 2 1.4 NiCo2S4 on Nitrogen-Doped Carbon Nanotubes 4 1.5 3D Phosphorous and Sulfur Co-Doped C3N4 Sponge With C Nanocrystal 5 1.6 2D Carbon Nanosheets 6 1.7 N-Doped Graphene Oxide With NiCo2O4 6 1.8 Conclusions 7 Acknowledgements 8 References 8 2 Construction, Working, and Applications of Different Zn-Based Batteries 11G. Ranjith Kumar, K. Chandra Babu Naidu, D. Baba Basha, D. Prakash Babu, M.S.S.R.K.N. Sarma, Ramyakrishna Pothu, and Rajender Boddula 2.1 Introduction 12 2.2 History 13 2.3 Types of Batteries 14 2.3.1 Primary Battery 14 2.3.2 Secondary Battery 14 2.4 Zinc-Carbon Batteries 18 2.5 Zinc-Cerium Batteries 19 2.6 Zinc-Bromine Flow Batteries 20 References 21 3 Nickel and Cobalt Materials for Zn Batteries 25Sonal Singh, Rishabh Sharma and Manika Khanuja 3.1 Introduction 26 3.2 Zinc Batteries 27 3.3 Nickel-Zinc Battery 27 3.3.1 History 27 3.3.2 Basics 28 3.3.3 Materials and Cost 30 3.3.4 Reliability 30 3.3.5 Voltage Drop 30 3.3.6 Performance 31 3.4 Advantages 31 3.5 Challenges 32 3.6 Effect of Metallic Additives, Cobalt and Zinc, on Nickel Electrode 32 3.7 Conclusion 33 References 34 4 Manganese-Based Materials for Zn Batteries 37S. Ramesh, K. Chandrababu Naidu, K. Venkata Ratnam, H. Manjunatha, D. Baba Basha and A. Mallikarjauna 4.1 Introduction 37 4.2 History of the Zinc and Zinc Batteries 38 4.3 Characteristics of Batteries 41 4.3.1 Capacity 41 4.3.2 Current 41 4.3.3 Power Density 41 4.4 MN-Based Zn Batteries 42 4.5 Conclusion 44 References 47 5 Electrolytes for Zn-Ion Batteries 51Praveen Kumar Yadav, Sapna Raghav, Jyoti Raghav and S. S. Swarupa Tripathy 5.1 Introduction 52 5.2 Electrolytes for Rechargeable Zinc Ion Batteries (RZIBs) 53 5.2.1 Aqueous Electrolytes (AqEs) 54 5.2.1.1 Pros and Cons of AEs 55 5.2.1.2 Neutral or Mildly Acidic Electrolytes 58 5.2.2 Non-Aqueous Electrolytes 59 5.2.2.1 Solid Polymer Electrolytes 60 5.2.2.2 Hydrogel or Gel Electrolytes 61 5.2.2.3 Gel Polymer Electrolytes 63 5.2.3 Ionic Liquid Electrolytes 63 5.2.4 Bio-Electrolyte 65 5.3 Summary 65 Abbreviation Table 66 Acknowledgments 66 References 67 6 Anode Materials for Zinc-Ion Batteries 73Muhammad Mudassir Hassan, Muhammad Inam Khan, Abdur Rahim and Nawshad Muhammad 6.1 Introduction 73 6.2 Storage Mechanism 75 6.3 Zinc-Ion Battery Anodes 77 6.4 Future Prospects 81 6.5 Conclusion 81 References 82 7 Cathode Materials for Zinc-Air Batteries 85Seyedeh Maryam Mousavi and Mohammad Reza Rahimpour 7.1 Introduction 85 7.1.1 Cathode Definition 86 7.2 Zinc Cathode Structure 87 7.3 Non-Valuable Materials for Cathode Electrocatalytic 89 7.4 Electrochemical Specifications of Activated Carbon as a Cathode 92 7.4.1 Electrochemical Evaluation of Cathode Substances La1−XCaxCoO3 Zinc Batteries 92 7.5 Extremely Durable and Inexpensive Cathode Air Catalyst 93 7.5.1 Co3O4/Mno2 NPs Dual Oxygen Catalyst as Cathode for Zn-Air Rechargeable Battery 94 7.5.2 Carbon Nanotubes (CNT) Employing Nitrogen as Catalyst in the Zinc/Air Battery System 94 7.5.3 Magnesium Oxide NPs Modified Catalyst for the Use of Air Electrodes in Zn/Air Batteries 94 7.5.4 Silver-Magnesium Oxide Nanocatalysts as Cathode for Zn-Air Batteries 95 7.5.5 One-Step Preparation of C-N Ni/Co-Doped Nanotube Hybrid as Outstanding Cathode Catalysts for Zinc-Air Batteries 95 7.6 Hierarchical Co3O4 Nano-Micro Array With Superior Working Characteristics Using Cathode Ray on Pliable and Rechargeable Battery 96 7.7 Dual Function Oxygen Catalyst Upon Active Iron-Based Zn-Air Rechargeable Batteries 97 7.7.1 Co4N and NC Fiber Coupling Connected to a Free-Acting Binary Cathode for Strong, Efficient, and Pliable Air Batteries 98 7.8 Conclusion 98 Nomenclature 99 References 99 8 Anode Materials for Zinc-Air Batteries 103Abbas Ghareghashi and Ali Mohebbi 8.1 Introduction 104 8.2 Zinc Anodes 105 8.2.1 Downsizing of Zn Anodes 106 8.2.2 Design of Membrane Separators 107 8.2.3 The Use of ZnO Instead of Zn 108 8.2.4 Increase of Surface Area in Zn Anode Structure 110 8.2.5 Coating of Zn Anode 111 8.2.5.1 Bismuth Oxide-Based Glasses 112 8.2.5.2 Silica 114 8.2.5.3 Carbon Nanotubes 115 8.2.5.4 ZnO@C 116 8.2.5.5 Zn-Al LDHs 116 8.2.5.6 ZnO@C-ZnAl LDHs 118 8.2.5.7 Tapioca 119 8.2.5.8 TiO2 122 8.3 Conclusions 123 References 124 9 Safety and Environmental Impacts of Zn Batteries 131Saurabh Sharma, Abhishek Anand, Amritanshu Shukla and Atul Sharma 9.1 Introduction 131 9.2 Working Principle of Zinc-Based Batteries 132 9.2.1 Zinc-Air Batteries Basic Principle and Advances 133 9.2.2 Zinc Organic Polymer Batteries 135 9.2.3 Zinc-Ion Batteries 137 9.2.3.1 Zinc-Silver Batteries 137 9.2.3.2 Zinc-Nickel Batteries 138 9.2.3.3 Zinc-Manganese Battery 140 9.3 Batteries: Environment Impact, Solution, and Safety 141 9.3.1 Disposal of Batteries and Environmental Impact 143 9.3.2 Recycling of Zinc-Based Batteries 143 9.4 Conclusion 146 Acknowledgement 147 References 147 10 Basics and Developments of Zinc-Air Batteries 151Seyedeh Maryam Mousavi and Mohammad Reza Rahimpour 10.1 Introduction 151 10.1.1 Public Specifications 151 10.2 Zinc-Air Electrode Chemical Reaction 153 10.3 Zinc/Air Battery Construction 154 10.4 Primary Zn/Air Batteries 157 10.5 Principles of Configuration and Operation 159 10.6 Developments in Electrical Fuel Zn/Air Batteries 161 10.6.1 Zn/Air Versus Metal/Air Systems 161 10.7 Conclusion 162 References 164 11 History and Development of Zinc Batteries 167Pallavi Jain, Sapna Raghav, Ankita Dhillon and Dinesh Kumar 11.1 Introduction 167 11.2 Basic Concept 169 11.2.1 Components of Batteries 169 11.2.2 Classification of Batteries 171 11.2.2.1 Primary Batteries 171 11.2.2.2 Secondary or Rechargeable Batteries (RBs) 171 11.3 Cell Operation 172 11.3.1 Process of Discharge 172 11.3.2 Process of Charge 172 11.4 History 173 11.5 Different Types of Zinc Batteries 174 11.5.1 Zinc-Carbon Batteries 174 11.5.2 Zinc/Manganese Oxide Batteries (Alkaline Batteries) 174 11.5.3 Zinc/Silver Oxide Battery 174 11.5.4 Zn-Air (Zn-O2) Batteries 176 11.5.4.1 Mechanically Rechargeable Batteries (Zn-O2 Batteries) 177 11.5.4.2 Electrically Rechargeable Batteries (Zn-O2 Batteries) 178 11.5.5 Hybrid Zn-O2 Batteries 178 11.5.5.1 Hybrid Zn-Ni/O2 Batteries 178 11.5.5.2 Hybrid Zn-Co/O2 Batteries 179 11.5.6 Aqueous Zinc-Ion Rechargeable Batteries 180 11.5.6.1 Zn2+ Insertion/Extraction Mechanism 180 11.5.6.2 Chemical Conversion Mechanism 180 11.5.6.3 H+ and Zn2+ Insertion/Extraction Mechanism 181 11.6 Future Perspectives 181 11.7 Conclusion 182 Abbreviations 182 Acknowledgement 183 References 183 12 Electrolytes for Zinc-Air Batteries 187Zahra Farmani, Mohammad Amin Sedghamiz, and Mohammad Reza Rahimpour 12.1 Introduction 187 12.2 Aqueous Electrolytes 188 12.2.1 Alkaline Electrolytes 189 12.2.1.1 Dissolution of Zinc in Alkaline Systems 189 12.2.1.2 Insoluble Carbonates Precipitation 192 12.2.1.3 Effect of Water 193 12.2.1.4 Hydrogen Evolution 194 12.2.2 Neutral Electrolytes 195 12.2.3 Acidic Electrolytes 196 12.3 Electrolytes of Non-Aqueous 197 12.3.1 Non-Aqueous Electrolytes 199 12.3 Summary 203 References 206 13 Security, Storage, Handling, Influences and Disposal/Recycling of Zinc Batteries 215Manju Yadav and Dinesh Kumar 13.1 Introduction 215 13.2 Security of Zinc Battery 217 13.2.1 Modifications for Improving Performance 218 13.2.1.1 High Surface Area 218 13.2.1.2 Carbon-Based Electrode Additives 221 13.2.1.3 Discharge-Capturing Electrode Additives 221 13.2.1.4 Electrode Coatings 222 13.2.1.5 Electrolyte Additives 222 13.2.1.6 Heavy-Metals Electrode Additive 222 13.2.1.7 Polymeric Binders 223 13.2.2 Storage and Handling 224 13.3 Influence of Zinc Battery 224 13.3.1 Consumption of Natural Resources 225 13.3.2 Toxicity of Batteries to Humans 226 13.3.3 Toxicity of Batteries to the Aquatic Environment 226 13.4 Disposal/Recycling Options 227 Acknowledgement 228 References 228 14 Materials for Ni-Zn Batteries 235Vaishali Tomar and Dinesh Kumar 14.1 Introduction 235 14.1.1 Functioning Principles of Nickel-Zinc Battery 237 14.1.2 Ni-Zn Battery Design 238 14.2 Expansion of Ni-Zn Battery 239 14.2.1 Active Materials for the Battery 240 14.3 Application 241 14.4 Conclusion 242 Acknowledgement 243 References 243 Index 249

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Book SynopsisDiscover the most recent advances in electromagnetic vortices In Electromagnetic Vortices: Wave Phenomena and Engineering Applications, a team of distinguished researchers delivers a cutting-edge treatment of electromagnetic vortex waves, including their theoretical foundation, related wave properties, and several potentially transformative applications. The book is divided into three parts. The editors first include resources that describe the generation, sorting, and manipulation of vortex waves, as well as descriptions of interesting wave behavior in the infrared and optical regimes with custom-designed nanostructures. They then discuss the generation, multiplexing, and propagation of vortex waves at the microwave and millimeter-wave frequencies. Finally, the selected contributions discuss several representative practical applications of vortex waves from a system perspective. With coverage that incorporates demonstration examples from a wide range of relateTable of ContentsAbout the Editors xv List of Contributors xvii Preface xxi Part I Fundamentals and Basics of Electromagnetic Vortices 1 1 Fundamentals of Orbital Angular Momentum Beams: Concepts, Antenna Analogies, and Applications 3 Anastasios Papathanasopoulos and Yahya Rahmat-Samii 1.1 Electromagnetic Fields Carry Orbital Angular Momentum 3 1.2 OAM Beams; Properties and Analogies with Conventional Beams 4 1.2.1 Laguerre–Gaussian Modes 5 1.3 Communicating Using OAM: Potentials and Challenges 10 1.3.1 OAM Communication Link Scenarios and Technical Barriers 11 1.3.2 OAM Emerging Applications and Perspectives 14 1.3.2.1 Free-space Communications 14 1.3.2.2 Optical Fiber Communications 17 1.4 OAM Generation Methods 20 1.5 Summary and Perspectives 22 Appendix 1.A OAM Far-field Calculation 23 References 26 2 OAM Radio – Physical Foundations and Applications of Electromagnetic Orbital Angular Momentum in Radio Science and Technology 33 Bo Thidé and Fabrizio Tamburini 2.1 Introduction 33 2.2 Physics 34 2.2.1 The Classical Electromagnetic Field 34 2.2.2 Electrodynamic Observables 36 2.2.2.1 Behavior at Very Long Distances 41 2.3 Implementation 45 2.3.1 Wireless Information Transfer with Linear Momentum 46 2.3.2 Wireless Information Transfer with Angular Momentum 48 2.3.2.1 Spin Angular Momentum vs. Orbital Angular Momentum 50 2.3.2.2 Angular Momentum Transducers 50 2.3.2.3 Electric Hertzian Dipoles 52 2.3.3 Astronomy Applications 58 Appendix A 61 2.A.1 Theory 61 2.A.1.1 Classical Majorana-Oppenheimer Formalism and Its Affinity to First Quantization Formalism 61 2.A.1.1.1 Riemann–Silberstein Electromagnetic Potentials and Fields 63 A.1.1.1 Purely Electric Sources 66 A.1.1.2 Useful Approximations 67 A.1.2.1 The Paraxial Approximation 68 A.1.2.2 The Far-Zone Approximation 70 2.A.2 Poincaré Invariants and Conserved Quantities of the EM Field 74 A.2.1 Energy 74 A.2.2 Linear Momentum 76 A.2.2.1 Gauge Invariance 78 A.2.2.2 First Quantization Formalism 79 A.2.3 Angular Momentum 80 A.2.3.1 Gauge Invariance 82 A.2.3.2 First Quantization Formalism 83 References 84 Part II Physical Wave Phenomena of Electromagnetic Vortices 97 3 Generation of Microwave Vortex Beams Using Metasurfaces 99 Jia Yuan Yin and Tie Jun Cui 3.1 Introduction 99 3.2 Metasurfaces for Vortex-beam Generation 100 3.2.1 Reflective Metasurfaces for Vortex-beam Generation 101 3.2.2 Transmission Metasurfaces for Vortex-beam Generation 108 3.2.3 Planar Metasurfaces for Vortex-beam Generation 110 3.2.4 Metasurfaces for Modified Vortex-beam Generation 112 3.2.5 One-dimensional Metasurface for Vortex-beam Generation 113 3.3 Conclusion 114 Acknowledgments 114 References 115 4 Application of Transformation Optics and 3D Printing Technology in Vortex Wave Generation 121 Jianjia Yi, Shah Nawaz Burokur, and Douglas H. Werner 4.1 Introduction 121 4.2 Theoretical Basis of Transformation Optics and 3D Printing 121 4.2.1 The Concept and Development of Transformation Optics 121 4.2.2 An Overview of 3D Printing Techniques 125 4.3 Several Applications of Transformation Optics in Vortex Waves 128 4.3.1 All-Dielectric Transformed Material for the Generation of OAM Beams 128 4.3.2 All-dielectric Metamaterial Medium for Collimating OAM Vortex Waves 137 4.3.3 A Transformation Optics-Based Lens for Horizontal Radiation of OAM Vortex Waves 147 4.4 Conclusions 153 References 154 5 Millimeter-Wave Transmit-Arrays for High-Capacity and Wideband Generation of Scalar and Vector Vortex Beams 157 Zhi Hao Jiang, Lei Kang, Wei Hong, and Douglas H. Werner 5.1 Introduction 157 5.2 Vector Vortex Beams and Hybrid-Order PSs 159 5.3 Millimeter-Wave Transmit-Array Unit Cell Designs 161 5.3.1 Ka-Band CP Unit Cell Design 161 5.3.2 Q-Band CP Unit Cell Design 165 5.3.3 K-Band Dual-CP Unit Cell Design 166 5.4 Millimeter-Wave Transmit-Arrays for Vortex Beam Multiplexing 171 5.4.1 Far-Field Pattern Calculation for Transmit-Arrays 171 5.4.2 Multiplexing of Scalar Vortex Beams 172 5.4.3 Multiplexing of Vector Vortex Beams with Symmetry Constraints 176 5.4.4 Multiplexing of Vector Vortex Beams with Broken Symmetry 182 5.5 Conclusion 183 Acknowledgment 183 References 184 6 Twisting Light with Metamaterials 189 Natalia M. Litchinitser 6.1 Introduction 189 6.2 OAM Beams on the Nanoscale 194 6.3 Active OAM Sources 201 6.4 OAM Light in Engineered Nonlinear Colloidal Systems 206 6.5 Conclusion 214 References 214 7 Generation of Optical Vortex Beams 223 Yuanjie Yang and Cheng-Wei Qiu 7.1 Introduction 223 7.2 Basic Theory of Optical Vortex 224 7.3 Generation of Optical Vortex 225 7.3.1 Generation of Vortex Beams using Optical Elements 225 7.3.1.1 Spiral Phase Plate 225 7.3.1.2 Fork-grating Hologram 226 7.3.1.3 Spiral Zone Plate Holograms 226 7.3.2 Generation of Vortex Beams Using Digital Devices 227 7.3.3 Generation of Vortex Beams Based on Mode Conversion 229 7.3.4 Generation of Vortex Beams Based on the Superposition of Waves 230 7.3.5 Generation of Vortex Beams Based on Metasurfaces 231 7.4 Generation of Novel Vortex Beams 233 7.4.1 Perfect Vortex Beam 233 7.4.2 Fractional Vortex Beams 235 7.4.3 Anomalous Vortex Beam 237 7.4.4 Vortex Beams with Varying OAM 239 7.5 Conclusion 241 References 241 8 Orbital Angular Momentum Generation, Detection, and Angular Momentum Conservation with Second Harmonic Generation 245 Menglin L. N. Chen, Xiaoyan Y. Z. Xiong, Wei E. I. Sha, and Li Jun Jiang 8.1 Orbital Angular Momentum Generation and Detection 245 8.1.1 OAM Generation 246 8.1.1.1 Complementary Metasurfaces 247 8.1.1.2 Quasi-Continuous Metasurfaces 247 8.1.1.3 Photonic Crystals 250 8.1.2 OAM Detection 252 8.1.2.1 Modified Dynamic Mode Decomposition 252 8.1.2.2 Holographic Metasurfaces 254 8.2 AM Conservation: Nonlinear Optics 256 8.2.1 BEM for Nonlinear Optics 256 8.2.2 Verification of the Algorithm 258 8.2.3 Mixing of Spin and OAM 259 8.2.4 General Angular Momenta Conservation Law 261 8.3 Conclusion 263 References 264 Part III Engineering Applications of Electromagnetic Vortices 269 9 Orbital Angular Momentum Based Structured Radio Beams and its Applications 271 Xianmin Zhang, Shilie Zheng, Wei E. I. Sha, Li Jun Jiang, Xiaowen Xiong, Zelin Zhu, Zhixia Wang, Yuqi Chen, Jiayu Zheng, Xinyue Wang, and Menglin L. N. Chen 9.1 Introduction 271 9.2 PS–OAM Based Structured Beams 272 9.2.1 Plane Spiral OAM 272 9.2.2 Structured Radio Beam 273 9.3 Antennas for Structured Beams 276 9.3.1 Antennas for PS–OAM Waves 276 9.3.2 SIW-based Compact Antenna 279 9.3.3 Partial Arc Transmitting Scheme 284 9.4 Potential Applications 286 9.4.1 Radar Detection 286 9.4.2 MIMO System 287 9.4.3 Spatial Field Digital Modulation 289 9.5 Conclusion 291 References 291 10 OAM Multiplexing Using Uniform Circular Array and Microwave Circuit for Short-range Communication 295 Kentaro Murata and Naoki Honma 10.1 Introduction 295 10.2 OAM Multiplexing System and its Mechanism 297 10.2.1 Coaxial UCA Configuration 297 10.2.2 Circulant Channel Matrix 298 10.2.3 DFT/IDFT Beamformers 299 10.3 OAM Multiplexing for Short-range Communications 300 10.3.1 Achievable Rate 300 10.3.2 Array Topology 301 10.3.3 Optimal Array Radius 304 10.3.4 Butler Matrix 309 10.3.5 Performance Evaluation 312 10.4 Conclusion and Key Challenges 317 References 318 11 OAM Communications in Multipath Environments 321 Xiaoming Chen and Wei Xue 11.1 Introduction 321 11.1.1 Fading in Wireless Propagation 321 11.1.1.1 Pass Loss 322 11.1.1.2 Large-Scale Fading 322 11.1.1.3 Small-Scale Fading 322 11.1.2 Diversity and Multiplexing 323 11.1.3 MIMO Systems 324 11.2 OAM Communication in Line-of-sight Environment 325 11.2.1 Conventional OAM Multiplexing 325 11.2.2 OAM Multiplexing with Spatial Equalization 329 11.3 OAM Multiplexing in Multipath Environment 337 11.3.1 Specular Reflection 337 11.3.1.1 Intra-channel Interference 338 11.3.1.2 Inter-channel Interference 341 11.3.2 Indoor Environment 343 11.3.2.1 Inter-Symbol Interference (ISI) 343 11.3.2.2 Antenna misalignment 346 11.3.3 Highly Reverberant Environments 349 11.4 Conclusion 354 References 354 12 High-capacity Free-space Optical Communications Using Multiplexing of Multiple OAM Beams 357 Alan E. Willner, Runzhou Zhang, Kai Pang, Haoqian Song, Cong Liu, Hao Song, Xinzhou Su, Huibin Zhou, Nanzhe Hu, Zhe Zhao, Guodong Xie, Yongxiong Ren, Hao Huang, and Moshe Tur 12.1 Introduction 357 12.2 Challenges for an OAM Multiplexing Free-space Optical Communication System 359 12.2.1 Beam divergence 360 12.2.2 Misalignment 361 12.2.3 Atmospheric Turbulence Effects 362 12.2.4 Obstruction 364 12.2.5 Summary 364 12.3 Free-space Optical OAM Links 364 12.3.1 High-capacity OAM Multiplexed Communication Link Under Laboratory Conditions 365 12.3.2 OAM-based FSO Link Beyond Laboratory Distances 368 12.3.3 Summary 371 12.4 Inter-channel Crosstalk Mitigation Methods in OAM-multiplexed FSO Communications 371 12.4.1 Adaptive Optics for Crosstalk Mitigation 371 12.4.1.1 AO Using a Wavefront Sensor (WFS) and a Gaussian Probe Beam 372 12.4.1.2 AO Using WFS and Gaussian Probe Beam in a Quantum Communication Link 374 12.4.1.3 AO Using a Camera for Beam Intensity Measurement 376 12.4.2 Spatial Modes Manipulation for Crosstalk Mitigation 378 12.4.2.1 Turbulence Precompensation by OAM Mode Combination 378 12.4.2.2 Simultaneous Orthogonalizing and Shaping of Multiple LG Beams 380 12.4.3 Digital Signal Processing for Crosstalk Mitigation 381 12.4.3.1 MIMO Equalization for Crosstalk Mitigation in Laboratory 382 12.4.3.2 Turbulence-Resilient Beam Mixing for Crosstalk Mitigation 383 12.4.4 Summary 384 12.5 OAM Multiplexing for Unmanned Aerial Vehicle (UAV) Platforms 385 12.5.1 OAM System Design and Demonstrations for UAV Platforms 386 12.5.2 Multiple-Input-Multiple-Output (MIMO) Mitigation for Atmospheric Turbulence in UAV Platforms 389 12.5.3 Summary 390 12.6 OAM Multiplexing in Underwater Environments 391 12.6.1 Underwater Effects for OAM Beam Propagation 392 12.6.2 OAM Multiplexing Demonstrations in Underwater Environments 392 12.6.3 Multiple-Input-Multiple-Output (MIMO) Mitigation for Inter-Channel Crosstalk in Underwater Environments 394 12.6.4 Summary 394 12.7 Summary of this Chapter 394 Acknowledgment 396 References 396 Part IV Multidisciplinary Explorations of Electromagnetic Vortices 401 13 Theory of Vector Beams for Chirality and Magnetism Detection of Subwavelength Particles 403 Mina Hanifeh and Filippo Capolino 13.1 Characterization of Azimuthally and Radially Polarized Beams 403 13.2 Circular Dichroism for a Particle of Subwavelength Size 407 13.2.1 Helicity of an Azimuthally Radially Polarized Vector Beam 409 13.3 Photoinduced Force Microscopy at Nanoscale 411 13.3.1 Magnetic Photoinduced Force Microscopy by Using an APB 412 13.3.2 Chirality Photoinduced Force Microscopy 415 13.4 Conclusion 418 References 418 14 Quantum Applications of Structured Photons 423 Alessio D’Errico and Ebrahim Karimi 14.1 Introduction 423 14.2 Photonic Degrees of Freedom 424 14.3 Single Photon Source: SPDC 426 14.4 Generation and Detection of Structured Photon Quantum States 430 14.4.1 Generation of Structured Photon States 430 14.4.2 Detection of Structured Photons 433 14.5 Quantum Key Distribution 434 14.5.1 BB84 Protocol 436 14.5.2 Alignment-free QKD 437 14.5.3 High-dimensional QKD 438 14.6 Quantum Simulation with Quantum Walks 442 14.6.1 Quantum Walks in the OAM Space 443 14.6.2 Shaping the Walker Space: Cyclic Walks and Walks on 2D Lattices 444 14.6.3 Applications: Wavepacket Dynamics and Detection of Topological Phases 446 14.7 Outlook 450 References 450 Index 457

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Book SynopsisSPECTRUM SHARING IN COGNITIVE RADIO NETWORKS Discover the latest advances in spectrum sharing in wireless networks from two internationally recognized experts in the fieldSpectrum Sharing in Cognitive Radio Networks: Towards Highly Connected Environments delivers an in-depth and insightful examination of hybrid spectrum access techniques with advanced frame structures designed for efficient spectrum utilization. The accomplished authors present the energy and spectrum efficient frameworks used in high-demand distributed architectures by relying on the self-scheduled medium access control (SMC-MAC) protocol in cognitive radio networks.The book begins with an exploration of the fundamentals of recent advances in spectrum sharing techniques before moving onto advanced frame structures with spectrum accessing approaches and the role of spectrum prediction and spectrum monitoring to eliminate interference. The authors also cover spectrum mobility, interference,Table of ContentsPreface xiii Special Acknowledgements xxi List of Acronyms xxiii List of Figures xxvii List of Tables xxxiii List of Symbols xxxv 1 Introduction 1 1.1 Introduction 1 1.1.1 Connected Environments 2 1.1.2 Evolution of Wireless Communication 5 1.1.3 Third Generation Partnership Project 10 1.2 Cognitive Radio Technology 10 1.2.1 Spectrum Accessing/Sharing Techniques 13 1.2.1.1 Interweave Spectrum Access 14 1.2.1.2 Underlay Spectrum Access 17 1.2.1.3 Overlay Spectrum Access 17 1.2.1.4 Hybrid Spectrum Access 17 1.3 Implementation of CR Networks 20 1.4 Motivation 22 1.5 Organization of Book 23 1.6 Summary 27 References 27 2 Advanced Frame Structures in Cognitive Radio Networks 39 2.1 Introduction 39 2.2 Related Work 40 2.2.1 Frame Structures 40 2.2.2 Spectrum Accessing Strategies 41 2.3 Proposed Frame Structures for HSA Technique 43 2.4 Analysis of Throughput and Data Loss 45 2.5 Simulations and Results 47 2.6 Summary 50 References 51 3 Cognitive Radio Network with Spectrum Prediction and Monitoring Techniques 55 3.1 Introduction 55 3.2 Related Work 57 3.2.1 Spectrum Prediction 57 3.2.2 Spectrum Monitoring 58 3.3 System Models 59 3.3.1 System Model for Approach-1 59 3.3.2 System Model for Approach-2 60 3.4 Performance Analysis 61 3.4.1 Throughput Analysis Using Approach-1 61 3.4.2 Analysis of Performance Metrics of the Approach-2 65 3.5 Results and Discussion 67 3.5.1 Proposed Approach-1 67 3.5.2 Proposed Approach-2 69 3.6 Summary 72 References 72 4 Effect of Spectrum Prediction in Cognitive Radio Networks 77 4.1 Introduction 77 4.1.1 Spectrum Access Techniques 78 4.2 System Model 80 4.3 Throughput Analysis 87 4.4 Simulation Results and Discussion 89 4.5 Summary 93 References 94 5 Effect of Imperfect Spectrum Monitoring on Cognitive Radio Networks 97 5.1 Introduction 97 5.2 Related Work 99 5.2.1 Spectrum Sensing 99 5.2.2 Spectrum Monitoring 100 5.3 System Model 101 5.4 Performance Analysis of Proposed System Using Imperfect Spectrum Monitoring 102 5.4.1 Computation of Ratio of the Achieved Throughput to Data Loss 108 5.4.2 Computation of Power Wastage 108 5.4.3 Computation of Interference Efficiency 109 5.4.4 Computation of Energy Efficiency 109 5.5 Results and Discussion 110 5.6 Summary 115 References 116 6 Cooperative Spectrum Monitoring in Homogeneous and Heterogeneous Cognitive Radio Networks 121 6.1 Introduction 121 6.2 Background 122 6.3 System Model 124 6.4 Performance Analysis of Proposed CRN 126 6.4.1 Computation of Achieved Throughput and Data Loss 130 6.4.2 Computation of Interference Efficiency 131 6.4.3 Computation of Energy Efficiency 131 6.5 Results and Discussion 132 6.5.1 Homogeneous Cognitive Radio Network 132 6.5.2 Heterogeneous Cognitive Radio Networks 134 6.6 Summary 143 References 143 7 Spectrum Mobility in Cognitive Radio Networks Using Spectrum Prediction and Monitoring Techniques 147 7.1 Introduction 147 7.2 System Model 151 7.3 Performance Analysis 153 7.4 Results and Discussion 156 7.5 Summary 162 References 163 8 Hybrid Self-Scheduled Multichannel Medium Access Control Protocol in Cognitive Radio Networks 167 8.1 Introduction 167 8.2 Related Work 169 8.2.1 CR-MAC Protocols 169 8.2.2 Interference at PU 171 8.3 System Model and Proposed Hybrid Self-Scheduled Multichannel MAC Protocol 172 8.3.1 System Model 172 8.3.2 Proposed HSMC-MAC Protocol 173 8.4 Performance Analysis 174 8.4.1 With Perfect Spectrum Sensing 176 8.4.2 With Imperfect Spectrum Sensing 178 8.4.3 More Feasible Scenarios 180 8.5 Simulations and Results Analysis 182 8.5.1 With Perfect Spectrum Sensing 182 8.5.2 With Imperfect Spectrum Sensing 185 8.6 Summary 190 References 190 9 Frameworks of Non-Orthogonal Multiple Access Techniques in Cognitive Radio Networks 195 9.1 Introduction 195 9.1.1 Related Work 196 9.1.2 Motivation 199 9.1.3 Organization 199 9.2 CR Spectrum Accessing Strategies 199 9.3 Functions of NOMA System for Uplink and Downlink Scenarios 204 9.3.1 Downlink Scenario for Cellular-NOMA 204 9.3.2 Uplink Scenario for Cellular-NOMA 207 9.4 Proposed Frameworks of CR with NOMA 208 9.4.1 Framework-1 209 9.4.2 Framework-2 210 9.5 Simulation Environment and Results 212 9.6 Research Potentials for NOMA and CR-NOMA Implementations 213 9.6.1 Imperfect CSI 214 9.6.2 Spectrum Hand-off Management 215 9.6.3 Standardization 215 9.6.4 Less Complex and Cost-Effective Systems 215 9.6.5 Energy-Efficient Design and Frameworks 216 9.6.6 Quality-of-Experience Management 216 9.6.7 Power Allocation Strategy for CUs to Implement NOMA Without Interfering PU 217 9.6.8 Cooperative CR-NOMA 217 9.6.9 Interference Cancellation Techniques 217 9.6.10 Security Aspects in CR-NOMA 218 9.6.11 Role of User Clustering and Challenges 218 9.6.12 Wireless Power Transfer to NOMA 219 9.6.13 Multicell NOMA with Coordinated Multipoint Transmission 220 9.6.14 Multiple-Carrier NOMA 221 9.6.15 Cross-Layer Design 221 9.6.16 MIMO-NOMA-CR 222 9.7 Summary 222 References 223 10 Performance Analysis of MIMO-Based CR-NOMA Communication Systems 229 10.1 Introduction 229 10.2 Related Work for Several Combinations of CR, NOMA, and MIMO Systems 231 10.3 System Model 234 10.3.1 Downlink Scenarios 236 10.3.2 Uplink Scenario 238 10.4 Performance Analysis 238 10.4.1 Downlink Scenario 238 10.4.1.1 Throughput Computation for MIMO-CR-NOMA 239 10.4.1.2 Throughput Computation for CR-NOMA Systems 240 10.4.1.3 Sum Throughput for CR-OMA, CR-NOMA, CR-MIMO, and CR-NOMA-MIMO Frameworks 240 10.4.2 Uplink Scenario 241 10.4.2.1 Throughput Computation for MIMO-CR-NOMA 241 10.4.2.2 Throughput Calculation for CR-NOMA Systems 242 10.4.2.3 Sum Throughput for CR-OMA, CR-NOMA, CR-MIMO, and CR-NOMA-MIMO Frameworks 242 10.4.2.4 Computation of Interference Efficiency of CU-4 In Case of CR-MIMO-NOMA 243 10.5 Simulation and Results Analysis 243 10.5.1 Simulation Results for Downlink Scenario 243 10.5.2 Simulation Results for Uplink Scenario 245 10.6 Summary 249 References 250 11 Interference Management in Cognitive Radio Networks 255 11.1 Introduction 255 11.1.1 White space 257 11.1.2 Grey Spaces 257 11.1.3 Black Spaces 257 11.1.4 Interference Temperature 257 11.2 Interfering and Non-interfering CRN 258 11.2.1 Interfering CRN 258 11.2.2 Non-Interfering CRN 259 11.3 Interference Cancellation Techniques in the CRN 261 11.3.1 At the CU Transmitter 261 11.3.2 At the CR-Receiver 264 11.4 Cross-Layer Interference Mitigation in Cognitive Radio Networks 268 11.5 Interference Management in Cognitive Radio Networks via Cognitive Cycle Constituents 269 11.5.1 Spectrum Sensing 269 11.5.2 Spectrum Prediction 269 11.5.3 Transmission Below PUs’ Interference Tolerable Limit 271 11.5.4 Using Advanced Encoding Techniques 271 11.5.5 Spectrum Monitoring 272 11.6 Summary 274 References 274 12 Simulation Frameworks and Potential Research Challenges for Internet-of-Vehicles Networks 281 12.1 Introduction 281 12.1.1 Consumer IoT 283 12.1.2 Industrial IoT 283 12.2 Applications of CIoT 284 12.2.1 Smart Home and Automation 284 12.2.2 Smart Wearables 284 12.2.3 Home Security and Smart Domestics 285 12.2.4 Smart Farming 285 12.3 Applications of Industrial IoT 285 12.3.1 Smart Industry 286 12.3.2 Smart Grid/Utilities 286 12.3.3 Smart Communication 286 12.3.4 Smart City 287 12.3.5 Smart Energy Management 287 12.3.6 Smart Retail Management 288 12.3.7 Robotics 288 12.3.8 Smart Cars/Connected Vehicles 289 12.4 Communication Frameworks for IoVs 289 12.4.1 Vehicle-to-Vehicle (V2V) Communication 291 12.4.2 Vehicle to Infrastructure (V2I) Communication 292 12.4.3 Infrastructure to Vehicles (I2V) Communication 293 12.4.4 Vehicle-to-Broadband (V2B) Communication 293 12.4.5 Vehicle-to-Pedestrians (V2P) Communication 293 12.5 Simulation Environments for Internet-of-Vehicles 295 12.5.1 SUMO 296 12.5.2 Network Simulator (NetSim) 296 12.5.3 Ns-2 297 12.5.4 Ns-3 297 12.5.5 OMNeT++ 298 12.6 Potential Research Challenges 299 12.6.1 Social Challenges 299 12.6.2 Technical Challenges 300 12.7 Summary 302 References 302 13 Radio Resource Management in Internet-of-Vehicles 311 13.1 Introduction 311 13.1.1 Dedicated Short-Range Communication 313 13.1.2 Wireless Access for Vehicular Environments 314 13.1.3 Communication Access for Land Mobile (CALM) 314 13.2 Cellular Communication 315 13.2.1 3GPP Releases 315 13.2.2 Long-Term Evolution 317 13.2.3 New Radio 317 13.2.4 Dynamic Spectrum Access 318 13.3 Role of Cognitive Radio for Spectrum Management 319 13.4 Effect of Mobile Nature of Vehicles/Nodes on the Networking 320 13.5 Spectrum Sharing in IoVs 322 13.5.1 Spectrum Sensing Scenarios 322 13.5.2 Spectrum Sharing Scenarios 324 13.5.3 Spectrum Mobility/Handoff Scenarios 325 13.6 Frameworks of Vehicular Networks with Cognitive Radio 326 13.6.1 CR-Based IoVs Networks Architecture 327 13.7 Key Potentials and Research Challenges 328 13.7.1 Key Potentials 328 13.7.2 Research Challenges 329 13.8 Summary 333 References 333 Index 000

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Book SynopsisGet a firm handle on the engineering reliability process with this insightful and complete resourceNamed one of the Best Industrial Management eBooks of All Time by BookAuthorityAs featured on CNN, Forbes and Inc BookAuthority identifies and rates the best books in the world, based on recommendations by thought leaders and expertsThe newly and thoroughly revised 3rd Edition of Reliability Engineering delivers a comprehensive and insightful analysis of this crucial field. Accomplished author, professor, and engineer, Elsayed. A. Elsayed includes new examples and end-of-chapter problems to illustrate concepts, new chapters on resilience and the physics of failure, revised chapters on reliability and hazard functions, and more case studies illustrating the approaches and methodologies described within.The book combines analyses of system reliability estimation for time independent and time dependent models with the construction of the likeTable of ContentsPreface xi Prelude xv Chapter 1 Reliability and Hazard Functions 1 1.1 Introduction 1 1.2 Reliability Definition and Estimation 5 1.3 Hazard Functions 16 1.4 Multivariate Hazard Rate 57 1.5 Competing Risk Model and Mixture of Failure Rates 60 1.6 Discrete Probability Distributions 68 1.7 Mean Time to Failure 71 1.8 Mean Residual Life 74 1.9 Time of First Failure 76 Problems 79 References 91 Chapter 2 System Reliability Evaluation 95 2.1 Introduction 95 2.2 Reliability Block Diagrams 96 2.3 Series Systems 99 2.4 Parallel Systems 101 2.5 Parallel–Series, Series–Parallel, and Mixed-Parallel Systems 103 2.6 Consecutive-k-out-of-n:F System 113 2.7 Reliability of k-out-of-n Systems 121 2.8 Reliability of k-out-of-n Balanced Systems 123 2.9 Complex Reliability Systems 125 2.10 Special Networks 143 2.11 Multistate Models 144 2.12 Redundancy 150 2.13 Importance Measures of Components 154 2.14 Weighted Importance Measures of Components 165 Problems 167 References 182 Chapter 3 Time- and Failure-Dependent Reliability 185 3.1 Introduction 185 3.2 Nonrepairable Systems 185 3.3 Mean Time to Failure 194 3.4 Repairable Systems 204 3.5 Availability 215 3.6 Dependent Failures 223 3.7 Redundancy and Standby 228 Problems 238 References 247 Chapter 4 Estimation Methods of the Parameters 251 4.1 Introduction 251 4.2 Method of Moments 252 4.3 The Likelihood Function 260 4.4 Method of Least Squares 278 4.5 Bayesian Approach 284 4.6 Bootstrap Method 288 4.7 Generation of Failure Time Data 290 Problems 292 References 298 Chapter 5 Parametric Reliability Models 301 5.1 Introduction 301 5.2 Approach 1: Historical Data 302 5.3 Approach 2: Operational Life Testing 303 5.4 Approach 3: Burn-in Testing 303 5.5 Approach 4: Accelerated Life Testing 304 5.6 Types of Censoring 305 5.7 The Exponential Distribution 308 5.8 The Rayleigh Distribution 322 5.9 The Weibull Distribution 331 5.10 The Lognormal Distribution 343 5.11 The Gamma Distribution 350 5.12 The Extreme Value Distribution 357 5.13 The Half-Logistic Distribution 360 5.14 The Frechet Distribution 367 5.15 The Birnbaum–Saunders Distribution 369 5.16 Linear Models 372 5.17 Multicensored Data 374 Problems 378 References 389 Chapter 6 Accelerated Life Testing 393 6.1 Introduction 393 6.2 Types of Reliability Testing 394 6.3 Accelerated Life Testing 403 6.4 ALT Models 406 6.5 Statistics-Based Models: Nonparametric 420 6.6 Physics-Statistics-Based Models 437 6.7 Physics-Experimental-Based Models 446 6.8 Degradation Models 449 6.9 Statistical Degradation Models 453 6.10 Accelerated Life Testing Plans 459 Problems 463 References 476 Chapter 7 Physics of Failures 481 7.1 Introduction 481 7.2 Fault Tree Analysis 481 7.3 Failure Modes and Effects Analysis 488 7.4 Stress–Strength Relationship 490 7.5 PoF: Failure Time Models 492 7.6 PoF: Degradation Models 512 Problems 519 References 524 Chapter 8 System Resilience 527 8.1 Introduction 527 8.2 Resilience Overview 528 8.3 Multi-Hazard 528 8.4 Resilience Modeling 532 8.5 Resilience Definitions and Attributes 535 8.6 Resilience Quantification 536 8.7 Importance Measures 542 8.8 Cascading Failures 544 8.9 Cyber Networks 546 Problems 557 References 559 Chapter 9 Renewal Processes and Expected Number of Failures 563 9.1 Introduction 563 9.2 Parametric Renewal Function Estimation 564 9.3 Nonparametric Renewal Function Estimation 578 9.4 Alternating Renewal Process 588 9.5 Approximations of M(t) 591 9.6 Other Types of Renewal Processes 594 9.7 The Variance of the Number of Renewals 595 9.8 Confidence Intervals for the Renewal Function 601 9.9 Remaining Life at Time t 604 9.10 Poisson Processes 606 9.11 Laplace Transform and Random Variables 609 Problems 611 References 619 Chapter 10 Maintenance and Inspection 621 10.1 Introduction 621 10.2 Preventive Maintenance and Replacement Models: Cost Minimization 622 10.3 Preventive Maintenance and Replacement Models: Downtime Minimization 631 10.4 Minimal Repair Models 634 10.5 Optimum Replacement Intervals for Systems Subject to Shocks 639 10.6 Preventive Maintenance and Number of Spares 642 10.7 Group Maintenance 649 10.8 Periodic Inspection 653 10.9 Condition-Based Maintenance 663 10.10 On-Line Surveillance and Monitoring 665 Problems 669 References 676 Chapter 11 Warranty Models 679 11.1 Introduction 679 11.2 Warranty Models for Nonrepairable Products 681 11.3 Warranty Models for Repairable Products 701 11.4 Two-Dimensional Warranty 716 11.5 Warranty Claims 718 Problems 725 References 731 Chapter 12 Case Studies 733 12.1 Case 1: A Crane Spreader Subsystem 733 12.2 Case 2: Design of a Production Line 739 12.3 Case 3: An Explosive Detection System 746 12.4 Case 4: Reliability of Furnace Tubes 752 12.5 Case 5: Reliability of Smart Cards 757 12.6 Case 6: Life Distribution of Survivors of Qualification and Certification 760 12.7 Case 7: Reliability Modeling of Telecommunication Networks for the Air Traffic Control System 767 12.8 Case 8: System Design Using Reliability Objectives 776 12.9 Case 9: Reliability Modeling of Hydraulic Fracture Pumps 786 12.10 Case 10: Availability of Medical Information Technology System 791 12.11 Case 11: Producer and Consumer Risk in System of Systems 797 References 804 Appendices Appendix A Gamma Table 805 Appendix B Computer Program To Calculate the Reliability of a Consecutive-k-Out-of-n:F System 811 Appendix C Optimum Arrangement of Components In Consecutive-2-Out-of-N:F Systems 813 Appendix D Computer Program For Solving the Time-Dependent Equations 821 Appendix E The Newton–Raphson Method 823 Appendix F Coefficients of bi’s For i = 1, …, n 829 Appendix G Variance of θ∗2’s In Terms of θ22/n and K3/K∗2 843 Appendix H Computer Listing of the Newton–Raphson Method 849 Appendix I Coefficients (ai and bi) of the Best Estimates of the Mean (μ) and Standard Deviation (σ) In Censored Samples Up To n = 20 From a Normal Population 851 Appendix J Baker’s Algorithm 865 Appendix K Standard Normal Distribution 869 Appendix L Critical Values of χ2 875 Appendix M Solutions of Selected Problems 879 Author Index 887 Subject Index 895

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Book SynopsisTable of ContentsPreface xiii Acronyms xv 1 Introduction to Remote Sensing 1 1.1 How Remote Sensing Works 4 References 9 2 Satellite Orbits 11 2.1 Computation of Elliptical Orbits 15 2.2 Low Earth Orbits 16 2.3 Geosynchronous Orbits 23 2.4 Molniya Orbit 28 2.5 Satellite Orbit Prediction 29 2.6 Satellite Orbital Trade-offs 29 References 31 3 Infrared Sensing 33 3.1 Introduction 33 3.2 Radiometry 34 3.3 Radiometric Sensor Response 37 3.3.1 Derivation 37 3.3.2 Example Sensor Response Calculations 40 3.3.3 Response of a Sensor with a Partially-Filled FOV 40 3.4 Blackbody Radiation 41 3.4.1 Planck’s Radiation Law 41 3.4.2 Microwave Blackbody 42 3.4.3 Low-Frequency and High-Frequency Limits 43 3.4.4 Stefan–Boltzmann Law 43 3.4.5 Wein’s Displacement Law 44 3.4.6 Emissivity 44 3.4.7 Equivalent Blackbody Temperature 44 3.5 IR Sea Surface Temperature 45 3.5.1 Contributors to Infrared Measurements 45 3.5.2 Correction of Low-Altitude Infrared Measurements 46 3.5.3 Correction of High-Altitude Infrared Measurements 48 3.6 Atmospheric Radiative Transfer 49 3.7 Propagation in Seawater 54 3.8 Smooth Surface Reflectance 58 3.9 Rough Surface Reflectance 60 3.10 Ocean Thermal Boundary Layer 63 3.11 Operational SST Measurements 66 3.11.1 AVHRR Instrument 66 3.11.2 AVHRR Processing 68 3.11.3 AVHRR SST Algorithms 70 3.11.4 Example AVHRR Images 71 3.11.5 VIIRS Instrument 73 3.11.6 SST Accuracy 75 3.11.7 Applications 77 3.12 Land Temperature – Theory 77 3.13 Operational Land Temperature 80 3.14 Terrestrial Evapotranspiration 86 3.15 Geologic Remote Sensing 87 3.15.1 Linear Mixture Theory and Spectral Unmixing 90 3.16 Atmospheric Sounding 91 References 95 4 Optical Sensing – Ocean Color 99 4.1 Introduction to Ocean Color 99 4.2 Fresnel Reflection 103 4.3 Skylight 106 4.4 Water-Leaving Radiance 107 4.5 Water Column Reflectance 110 4.5.1 Pure Seawater 112 4.5.2 Case 1 Waters 113 4.5.3 Case 2 Waters 114 4.6 Remote Sensing Reflectance 115 4.7 Ocean Color Data – Case 1 Water 117 4.7.1 Other Uses of Ocean Color 118 4.8 Atmospheric Corrections 119 4.9 Ocean Color Satellite Sensors 124 4.9.1 General History 124 4.9.2 SeaWiFS 126 4.9.3 MODIS 130 4.9.4 VIIRS 133 4.10 Ocean Chlorophyll Fluorescence 135 References 140 5 Optical Sensing – Land Surfaces 143 5.1 Introduction 143 5.2 Radiation over a Lambertian Surface 143 5.3 Atmospheric Corrections 147 5.4 Scattering from Vegetation 147 5.5 Normalized Difference Vegetation Index 153 5.6 Vegetation Condition and Temperature Condition Indices 158 5.7 Vegetation Indices from Hyperspectral Data 159 5.8 Landsat Satellites 161 5.9 High-resolution EO sensors 164 5.9.1 Introduction 164 5.9.2 First-Generation Systems 164 5.9.3 Second-Generation Systems 168 5.9.4 Third-Generation Systems 172 5.9.5 Commercial Smallsat Systems 174 References 176 6 Microwave Radiometry 179 6.1 Introduction to Microwave Radiometry 179 6.2 Microwave Radiometers 180 6.3 Microwave Radiometry 181 6.3.1 Antenna Pattern 182 6.3.2 Antenna Temperature 184 6.3.3 Examples 185 6.4 Polarization 185 6.4.1 Basic Polarization 185 6.4.2 Jones Vector 187 6.4.3 Stokes Parameters 187 6.5 Passive Microwave Sensing of the Ocean 188 6.5.1 Atmospheric Transmission 189 6.5.2 Seawater Emissivity 189 6.5.3 Fresnel Reflection Coefficients, Emissivity, and Skin Depth 190 6.5.4 Sky Radiometric Temperature 191 6.5.5 Sea Surface Brightness Temperature 193 6.5.6 Wind Direction from Polarization 197 6.6 Satellite Microwave Radiometers 198 6.6.1 SMMR 198 6.6.2 SSM/I and SSMI/S 198 6.6.3 SSM/I Wind Algorithm 200 6.6.4 AMSR-E 203 6.6.5 WindSat 204 6.7 Microwave Radiometry of Sea Ice 207 6.8 Sea Ice Measurements 213 6.9 Microwave Radiometry of Land Surfaces 218 6.10 Atmospheric Sounding 222 References 226 7 Radar 229 7.1 Radar Range Equation 229 7.2 Radar Cross-Section 232 7.3 Radar Resolution 236 7.4 Pulse Compression 239 7.5 Types of Radar 244 7.6 Example Terrestrial Radars 245 7.6.1 Weather Radars 245 7.6.2 HF Surface Wave Radar 248 References 249 8 Altimeters 251 8.1 Introduction to Altimeters 251 8.2 Specular Scattering 254 8.3 Altimeter Wind Speed 257 8.4 Altimeter Significant Wave Height 260 8.5 Altimeter Sea Surface Height 263 8.5.1 Introduction 263 8.5.2 Pulse-limited vs Beam-limited Altimeter 263 8.5.3 Altimeter Pulse Timing Precision 264 8.5.4 Altimeter Range Corrections 264 8.6 Sea Surface Topography 268 8.7 Measuring Gravity and Bathymetry 274 8.8 Delay-Doppler Altimeter 275 References 278 9 Scatterometers 281 9.1 Ocean Waves 281 9.2 Bragg Scattering 287 9.3 RCS Dependence on Wind 291 9.4 Scatterometer Algorithms 293 9.5 Fan-Beam Scatterometers 297 9.6 Conical-Scan Pencil-Beam Scatterometers 300 9.7 Conical-Scan Fan-Beam Scatterometers 304 References 307 10 Synthetic Aperture Radar 309 10.1 Introduction to SAR 309 10.2 SAR Azimuth Resolution 313 10.2.1 Doppler Time History 313 10.2.2 Azimuth Extent, Integration Time, and Doppler Bandwidth 316 10.2.3 Azimuth Resolution 316 10.2.4 SAR Timing, Resolution, and Swath Limits 318 10.2.5 The Magic of SAR Exposed 319 10.3 SAR Image Formation and Image Quality 320 10.4 SAR Imaging of Moving Scatterers 322 10.5 Multimode SARs 325 10.6 Polarimetric SAR 326 10.6.1 Polarimetric Response of Canonical Targets 327 10.6.2 Decompositions 328 10.6.3 Compact Polarimetry 329 10.7 SAR Systems 330 10.7.1 Radarsat-1 332 10.7.2 Envisat 334 10.7.3 PALSAR 335 10.7.4 Radarsat-2 335 10.7.5 TerraSAR-X 335 10.7.6 COSMO-SkyMed 335 10.7.7 Sentinel-1 336 10.7.8 Radarsat Constellation Mission (RCM) 337 10.7.9 Military SARs 337 10.8 Advanced SARs 339 10.8.1 Cross-Track Interferometry 339 10.8.2 Along-Track Interferometry 341 10.8.3 Differential Interferometry 344 10.8.4 Tomographic Interferometry 344 10.8.5 High-Resolution, Wide-Swath SAR 344 10.9 SAR Applications 346 10.9.1 SAR Ocean Surface Waves 347 10.9.2 SAR Winds 353 10.9.3 SAR Bathymetry 360 10.9.4 SAR Ocean Internal Waves 364 10.9.5 SAR Sea Ice 370 10.9.6 SAR Oil Slicks and Ship Detection 374 10.9.7 SAR Land Mapping Applications and Distortions 380 10.9.8 SAR Agricultural Applications 386 References 388 11 Lidar 393 11.1 Introduction 393 11.2 Types of Lidar 393 11.2.1 Direct vs Coherent Detection 394 11.3 Processes Driving Lidar Returns 395 11.3.1 Elastic Scattering 395 11.3.2 Inelastic Scattering 396 11.3.3 Fluorescence 397 11.4 Lidar Range Equation 397 11.4.1 Point Scattering Target 397 11.4.2 Lambertian Surface 398 11.4.3 Elastic Volume Scattering 398 11.4.4 Bathymetric Lidar 398 11.5 Lidar Receiver Types 400 11.5.1 Linear (full waveform) Lidar 400 11.5.2 Single Photon Lidar 401 11.6 Lidar Altimetry 402 11.6.1 NASA Airborne Topographic Mapper 402 11.6.2 Space-Based Lidar Altimeters (IceSat-1 & 2) 403 11.6.3 Bathymetric Lidar 405 11.7 Lidar Atmospheric Sensing 405 11.7.1 ADM-Aeolus 405 11.7.2 NASA CALIOP 408 References 411 12 Other Remote Sensing and Future Missions 413 12.1 Other Types of Remote Sensing 413 12.1.1 GRACE 413 12.1.2 Limb Sounding 414 12.2 Future Missions 414 12.2.1 NASA Missions 415 12.2.2 ESA Missions 416 12.2.3 Summary 418 References 419 Appendix A Constants 421 Appendix B Definitions of Common Angles 423 Appendix C Example Radiometric Calculations 427 Appendix D Optical Sensors 433 D.1 Example Optical Sensors 435 D.1.1 Photodiodes 435 D.1.2 Charge-Coupled Devices 437 D.1.3 CMOS Image Sensors 439 D.1.4 Bolometers and Microbolometers 440 D.2 Optical Sensor Design Examples 442 D.2.1 Computing Exposure Times 442 D.2.2 Impact of Digitization and Shot Noise on Contrast Detection 444 References 445 Appendix E Radar Design Example 447 Appendix F Remote Sensing Resources on the Internet 455 F.1 Information and Tutorials 455 F.2 Data 455 F.3 Data Processing Tools 456 F.4 Satellite and Sensor Databases 456 F.5 Other 456 Appendix G Useful Trigonometric Identities 457 Index 459

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Book SynopsisTable of ContentsAbout the Editors xvii List of Contributors xix Preface xxv Acknowledgments xxxiii 1 Fog, Edge and Pervasive Computing in Intelligent Internet of Things Driven Applications in Healthcare: Challenges, Limitations and Future Use 1Afroj Alam, Sahar Qazi, Naiyar Iqbal, and Khalid Raza 1.1 Introduction 1 1.2 Why Fog, Edge, and Pervasive Computing? 3 1.3 Technologies Related to Fog and Edge Computing 6 1.4 Concept of Intelligent IoT Application in Smart (Fog) Computing Era 9 1.5 The Hierarchical Architecture of Fog/Edge Computing 12 1.6 Applications of Fog, Edge and Pervasive Computing in IoT-based Healthcare 15 1.7 Issues, Challenges, and Opportunity 17 1.7.1 Security and Privacy Issues 18 1.7.2 Resource Management 19 1.7.3 Programming Platform 19 1.8 Conclusion 20 Bibliography 20 2 Future Opportunistic Fog/Edge Computational Models and their Limitations 27Sonia Singla, Naveen Kumar Bhati, and S. Aswath 2.1 Introduction 28 2.2 What are the Benefits of Edge and Fog Computing for the Mechanical Web of Things (IoT)? 32 2.3 Disadvantages 34 2.4 Challenges 34 2.5 Role in Health Care 35 2.6 Blockchain and Fog, Edge Computing 38 2.7 How Blockchain will Illuminate Human Services Issues 40 2.8 Uses of Blockchain in the Future 41 2.9 Uses of Blockchain in Health Care 42 2.10 Edge Computing Segmental Analysis 42 2.11 Uses of Fog Computing 43 2.12 Analytics in Fog Computing 44 2.13 Conclusion 44 Bibliography 44 3 Automating Elicitation Technique Selection using Machine Learning 47Hatim M. Elhassan Ibrahim Dafallaa, Nazir Ahmad, Mohammed Burhanur Rehman, Iqrar Ahmad, and Rizwan khan 3.1 Introduction 47 3.2 Related Work 48 3.3 Model: Requirement Elicitation Technique Selection Model 52 3.3.1 Determining Key Attributes 54 3.3.2 Selection Attributes 54 3.3.2.1 Analyst Experience 55 3.3.2.2 Number of Stakeholders 55 3.3.2.3 Technique Time 56 3.3.2.4 Level of Information 56 3.3.3 Selection Attributes Dataset 56 3.3.3.1 Mapping the Selection Attributes 57 3.3.4 k-nearest Neighbor Algorithm Application 57 3.4 Analysis and Results 60 3.5 The Error Rate 61 3.6 Validation 61 3.6.1 Discussion of the Results of the Experiment 62 3.7 Conclusion 62 Bibliography 65 4 Machine Learning Frameworks and Algorithms for Fog and Edge Computing 67Murali Mallikarjuna Rao Perumalla, Sanjay Kumar Singh, Aditya Khamparia, Anjali Goyal, and Ashish Mishra 4.1 Introduction 68 4.1.1 Fog Computing and Edge Computing 68 4.1.2 Pervasive Computing 68 4.2 Overview of Machine Learning Frameworks for Fog and Edge Computing 69 4.2.1 TensorFlow 69 4.2.2 Keras 70 4.2.3 PyTorch 70 4.2.4 TensorFlow Lite 70 4.2.4.1 Use Pre-train Models 70 4.2.4.2 Convert the Model 70 4.2.4.3 On-device Inference 71 4.2.4.4 Model Optimization 71 4.2.5 Machine Learning and Deep Learning Techniques 71 4.2.5.1 Supervised, Unsupervised and Reinforcement Learning 71 4.2.5.2 Machine Learning, Deep Learning Techniques 72 4.2.5.3 Deep Learning Techniques 75 4.2.5.4 Efficient Deep Learning Algorithms for Inference 77 4.2.6 Pros and Cons of ML Algorithms for Fog and Edge Computing 78 4.2.6.1 Advantages using ML Algorithms 78 4.2.6.2 Disadvantages of using ML Algorithms 79 4.2.7 Hybrid ML Model for Smart IoT Applications 79 4.2.7.1 Multi-Task Learning 79 4.2.7.2 Ensemble Learning 80 4.2.8 Possible Applications in Fog Era using Machine Learning 81 4.2.8.1 Computer Vision 81 4.2.8.2 ML- Assisted Healthcare Monitoring System 81 4.2.8.3 Smart Homes 81 4.2.8.4 Behavior Analyses 82 4.2.8.5 Monitoring in Remote Areas and Industries 82 4.2.8.6 Self-Driving Cars 82 Bibliography 82 5 Integrated Cloud Based Library Management in Intelligent IoT driven Applications 85Md Robiul Alam Robel, Subrato Bharati, Prajoy Podder, and M. Rubaiyat Hossain Mondal 5.1 Introduction 86 5.1.1 Execution Plan for the Mobile Application 86 5.1.2 Main Contribution 86 5.2 Understanding Library Management 87 5.3 Integration of Mobile Platform with the Physical Library- Brief Concept 88 5.4 Database (Cloud Based) - A Must have Component for Library Automation 88 5.5 IoT Driven Mobile Based Library Management - General Concept 89 5.6 IoT Involved Real Time GUI (Cross Platform) Available to User 93 5.7 IoT Challenges 98 5.7.1 Infrastructure Challenges 99 5.7.2 Security Challenges 99 5.7.3 Societal Challenges 100 5.7.4 Commercial Challenges 101 5.8 Conclusion 102 Bibliography 104 6 A Systematic and Structured Review of Intelligent Systems for Diagnosis of Renal Cancer 105Nikita, Harsh Sadawarti, Balwinder Kaur, and Jimmy Singla 6.1 Introduction 106 6.2 Related Works 107 6.3 Conclusion 119 Bibliography 119 7 Location Driven Edge Assisted Device and Solutions for Intelligent Transportation 123Saravjeet Singh and Jaiteg Singh 7.1 Introduction to Fog and Edge Computing 124 7.1.1 Need for Fog and Edge Computing 124 7.1.2 Fog Computing 125 7.1.2.1 Application Areas of Fog Computing 125 7.1.3 Edge Computing 126 7.1.3.1 Advantages of Edge Computing 127 7.1.3.2 Application Areas of Fog Computing 129 7.2 Introduction to Transportation System 129 7.3 Route Finding Process 131 7.3.1 Challenges Associated with Land Navigation and Routing Process 132 7.4 Edge Architecture for Route Finding 133 7.5 Technique Used 135 7.6 Algorithms Used for the Location Identification and Route Finding Process 137 7.6.1 Location Identification 137 7.6.2 Path Generation Technique 138 7.7 Results and Discussions 140 7.7.1 Output 140 7.7.2 Benefits of Edge-based Routing 143 7.8 Conclusion 145 Bibliography 146 8 Design and Simulation of MEMS for Automobile Condition Monitoring Using COMSOL Multiphysics Simulator 149Natasha Tiwari, Anil Kumar, Pallavi Asthana, Sumita Mishra, and Bramah Hazela 8.1 Introduction 149 8.2 Related Work 151 8.3 Vehicle Condition Monitoring through Acoustic Emission 151 8.4 Piezo-resistive Micro Electromechanical Sensors for Monitoring the Faults Through AE 152 8.5 Designing of MEM Sensor 153 8.6 Experimental Setup 153 8.6.1 FFT Analysis of Automotive Diesel Engine Sound Recording using MATLAB 155 8.6.2 Design of MEMS Sensor using COMSOL Multiphysics 155 8.6.3 Electrostatic Study Steps for the Optimized Tri-plate Comb Structure 156 8.7 Result and Discussions 157 8.8 Conclusion 158 Bibliography 158 9 IoT Driven Healthcare Monitoring System 161Md Robiul Alam Robel, Subrato Bharati, Prajoy Podder, and M. Rubaiyat Hossain Mondal 9.1 Introduction 161 9.1.1 Complementary Aspects of Cloud IoT in Healthcare Applications 162 9.1.2 Main Contribution 164 9.2 General Concept for IoT Based Healthcare System 164 9.3 View of the Overall IoT Healthcare System- Tiers Explained 165 9.4 A Brief Design of the IoT Healthcare Architecture-individual Block Explanation 166 9.5 Models/Frameworks for IoT use in Healthcare 168 9.6 IoT e-Health System Model 171 9.7 Process Flow for the Overall Model 172 9.8 Conclusion 173 Bibliography 175 10 Fog Computing as Future Perspective in Vehicular Ad hoc Networks 177Harjit Singh, Dr. Vijay Laxmi, Dr. Arun Malik, and Dr. Isha 10.1 Introduction 178 10.2 Future VANET: Primary Issues and Specifications 180 10.3 Fog Computing 181 10.3.1 Fog Computing Concept 183 10.3.2 Fog Technology Characterization 183 10.4 Related Works in Cloud and Fog Computing 185 10.5 Fog and Cloud Computing-based Technology Applications in VANET 186 10.6 Challenges of Fog Computing in VANET 188 10.7 Issues of Fog Computing in VANET 189 10.8 Conclusion 190 Bibliography 191 11 An Overview to Design an Efficient and Secure Fog-assisted Data Collection Method in the Internet of Things 193Sofia, Arun Malik, Isha, and Aditya Khamparia 11.1 Introduction 193 11.2 Related Works 194 11.3 Overview of the Chapter 196 11.4 Data Collection in the IoT 197 11.5 Fog Computing 197 11.5.1 Why fog Computing for Data Collection in IoT? 197 11.5.2 Architecture of Fog Computing 200 11.5.3 Features of Fog Computing 200 11.5.4 Threats of Fog Computing 202 11.5.5 Applications of Fog Computing with the IoT 203 11.6 Requirements for Designing a Data Collection Method 204 11.7 Conclusion 206 Bibliography 206 12 Role of Fog Computing Platform in Analytics of Internet of Things- Issues, Challenges and Opportunities 209Mamoon Rashid and Umer Iqbal Wani 12.1 Introduction to Fog Computing 209 12.1.1 Hierarchical Fog Computing Architecture 210 12.1.2 Layered Fog Computing Architecture 212 12.1.3 Comparison of Fog and Cloud Computing 213 12.2 Introduction to Internet of Things 214 12.2.1 Overview of Internet of Things 214 12.3 Conceptual Architecture of Internet of Things 216 12.4 Relationship between Internet of Things and Fog Computing 217 12.5 Use of Fog Analytics in Internet of Things 218 12.6 Conclusion 218 Bibliography 218 13 A Medical Diagnosis of Urethral Stricture Using Intuitionistic Fuzzy Sets 221Prabjot Kaur and Maria Jamal 13.1 Introduction 221 13.2 Preliminaries 223 13.2.1 Introduction 223 13.2.2 Fuzzy Sets 223 13.2.3 Intuitionistic Fuzzy Sets 224 13.2.4 Intuitionistic Fuzzy Relation 224 13.2.5 Max-Min-Max Composition 224 13.2.6 Linguistic Variable 224 13.2.7 Distance Measure In Intuitionistic Fuzzy Sets 224 13.2.7.1 The Hamming Distance 224 13.2.7.2 Normalized Hamming Distance 224 13.2.7.3 Compliment of an Intuitionistic Fuzzy Set Matrix 225 13.2.7.4 Revised Max-Min Average Composition of A and B (A Φ B) 225 13.3 Max-Min-Max Algorithm for Disease Diagnosis 225 13.4 Case Study 226 13.5 Intuitionistic Fuzzy Max-Min Average Algorithm for Disease Diagnosis 227 13.6 Result 228 13.7 Code for Calculation 229 13.8 Conclusion 233 13.9 Acknowledgement 234 Bibliography 234 14 Security Attacks in Internet of Things 237Rajit Nair, Preeti Sharma, and Dileep Kumar Singh 14.1 Introduction 238 14.2 Reference Model of Internet of Things (IoT) 238 14.3 IoT Communication Protocol 246 14.4 IoT Security 247 14.4.1 Physical Attack 248 14.4.2 Network Attack 252 14.4.3 Software Attack 254 14.4.4 Encryption Attack 255 14.5 Security Challenges in IoT 256 14.5.1 Cryptographic Strategies 256 14.5.2 Key Administration 256 14.5.3 Denial of Service 256 14.5.4 Authentication and Access Control 257 14.6 Conclusion 257 Bibliography 257 15 Fog Integrated Novel Architecture for Telehealth Services with Swift Medical Delivery 263Inderpreet Kaur, Kamaljit Singh Saini, and Jaiteg Singh Khaira 15.1 Introduction 264 15.2 Associated Work and Dimensions 266 15.3 Need of Security in Telemedicine Domain and Internet of Things (IoT) 267 15.3.1 Analytics Reports 268 15.4 Fog Integrated Architecture for Telehealth Delivery 268 15.5 Research Dimensions 269 15.5.1 Benchmark Datasets 269 15.6 Research Methodology and Implementation on Software Defined Networking 270 15.6.1 Key Tools and Frameworks for IoT, Fog Computing and Edge Computing 274 15.6.2 Simulation Analysis 276 15.7 Conclusion 282 Bibliography 282 16 Fruit Fly Optimization Algorithm for Intelligent IoT Applications 287Satinder Singh Mohar, Sonia Goyal, and Ranjit Kaur 16.1 An Introduction to the Internet of Things 287 16.2 Background of the IoT 288 16.2.1 Evolution of the IoT 288 16.2.2 Elements Involved in IoT Communication 288 16.3 Applications of the IoT 289 16.3.1 Industrial 290 16.3.2 Smart Parking 290 16.3.3 Health Care 290 16.3.4 Smart Offices and Homes 290 16.3.5 Augment Maps 291 16.3.6 Environment Monitoring 291 16.3.7 Agriculture 291 16.4 Challenges in the IoT 291 16.4.1 Addressing Schemes 291 16.4.2 Energy Consumption 292 16.4.3 Transmission Media 292 16.4.4 Security 292 16.4.5 Quality of Service (QoS) 292 16.5 Introduction to Optimization 293 16.6 Classification of Optimization Algorithms 293 16.6.1 Particle Swarm Optimization (PSO) Algorithm 293 16.6.2 Genetic Algorithms 294 16.6.3 Heuristic Algorithms 294 16.6.4 Bio-inspired Algorithms 294 16.6.5 Evolutionary Algorithms (EA) 294 16.7 Network Optimization and IoT 295 16.8 Network Parameters optimized by Different Optimization Algorithms 295 16.8.1 Load Balancing 295 16.8.2 Maximizing Network Lifetime 295 16.8.3 Link Failure Management 296 16.8.4 Quality of the Link 296 16.8.5 Energy Efficiency 296 16.8.6 Node Deployment 296 16.9 Fruit Fly Optimization Algorithm 297 16.9.1 Steps Involved in FOA 297 16.9.2 Flow Chart of Fruit Fly Optimization Algorithm 298 16.10 Applicability of FOA in IoT Applications 300 16.10.1 Cloud Service Distribution in Fog Computing 300 16.10.2 Cluster Head Selection in IoT 300 16.10.3 Load Balancing in IoT 300 16.10.4 Quality of Service in Web Services 300 16.10.5 Electronics Health Records in Cloud Computing 301 16.10.6 Intrusion Detection System in Network 301 16.10.7 Node Capture Attack in WSN 301 16.10.8 Node Deployment in WSN 302 16.11 Node Deployment Using Fruit Fly Optimization Algorithm 302 16.12 Conclusion 304 Bibliography 304 17 Optimization Techniques for Intelligent IoT Applications 311Priyanka Pattnaik, Subhashree Mishra, and Bhabani Shankar Prasad Mishra 17.1 Cuckoo Search 312 17.1.1 Introduction to Cuckoo 312 17.1.2 Natural Cuckoo 312 17.1.3 Artificial Cuckoo Search 313 17.1.4 Cuckoo Search Algorithm 313 17.1.5 Cuckoo Search Variants 314 17.1.6 Discrete Cuckoo Search 314 17.1.7 Binary Cuckoo Search 314 17.1.8 Chaotic Cuckoo Search 316 17.1.9 Parallel Cuckoo Search 317 17.1.10 Application of Cuckoo Search 317 17.2 Glow Worm Algorithm 317 17.2.1 Introduction to Glow Worm 317 17.2.2 Glow Worm Swarm Optimization Algorithm (GSO) 317 17.3 Wasp Swarm Optimization 321 17.3.1 Introduction to Wasp Swarm and Wasp Swarm Algorithm (WSO) 321 17.3.2 Fish Swarm Optimization (FSO) 322 17.3.3 Fruit Fly Optimization (FLO) 322 17.3.4 Cockroach Swarm Optimization 324 17.3.5 Bumblebee Algorithm 324 17.3.6 Dolphin Echolocation 325 17.3.7 Shuffled Frog-leaping Algorithm 326 17.3.8 Paddy Field Algorithm 327 17.4 Real World Applications Area 328 Summary 329 Bibliography 329 18 Optimization Techniques for Intelligent IoT Applications in Transport Processes 333Muzafer Saračević, Zoran Lončarević, and Adnan Hasanović 18.1 Introduction 333 18.2 Related Works 335 18.3 TSP Optimization Techniques 336 18.4 Implementation and Testing of Proposed Solution 338 18.5 Experimental Results 342 18.5.1 Example Test with 50 Cities 343 18.5.2 Example Test with 100 Cities 344 18.6 Conclusion and Further Works 346 Bibliography 347 19 Role of Intelligent IOT Applications in Fog paradigm: Issues, Challenges and Future Opportunities 351Priyanka Rajan Kumar and Sonia Goel 19.1 Fog Computing 352 19.1.1 Need of Fog computing 352 19.1.2 Architecture of Fog Computing 353 19.1.3 Fog Computing Reference Architecture 354 19.1.4 Processing on Fog 355 19.2 Concept of Intelligent IoT Applications in Smart Computing Era 355 19.3 Components of Edge and Fog Driven Algorithm 356 19.4 Working of Edge and Fog Driven Algorithms 357 19.5 Future Opportunistic Fog/Edge Computational Models 360 19.5.1 Future Opportunistic Techniques 361 19.6 Challenges of Fog Computing for Intelligent IoT Applications 361 19.7 Applications of Cloud Based Computing for Smart Devices 363 Bibliography 364 20 Security and Privacy Issues in Fog/Edge/Pervasive Computing 369Shweta Kaushik and Charu Gandhi 20.1 Introduction to Data Security and Privacy in Fog Computing 370 20.2 Data Protection/ Security 375 20.3 Great Security Practices In Fog Processing Condition 377 20.4 Developing Patterns in Security and Privacy 381 20.5 Conclusion 385 Bibliography 385 21 Fog and Edge Driven Security & Privacy Issues in IoT Devices 389Deepak Kumar Sharma, Aarti Goel, and Pragun Mangla 21.1 Introduction to Fog Computing 390 21.1.1 Architecture of Fog 390 21.1.2 Benefits of Fog Computing 392 21.1.3 Applications of Fog with IoT 393 21.1.4 Major Challenges for Fog with IoT 394 21.1.5 Security and Privacy Issues in Fog Computing 395 21.2 Introduction to Edge Computing 399 21.2.1 Architecture and Working 400 21.2.2 Applications and use Cases 400 21.2.3 Characteristics of Edge Computing 403 21.2.4 Challenges of Edge Computing 404 21.2.5 How to Protect Devices “On the Edge”? 405 21.2.6 Comparison with Fog Computing 405 Bibliography 406 Index 409

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Book SynopsisProvides comprehensive information on swing contracts for flexible reserve provision in wholesale power markets This book promotes a linked swing-contract market design for centrally-managed wholesale power markets to facilitate increased reliance on renewable energy resources and demand-side participation. The proposed swing contracts are firm or option two-part pricing contracts permitting resources to offer the future availability of dispatchable power paths (reserve) with broad types of flexibility in their power attributes. A New Swing-Contract Design for Wholesale Power Markets begins with a brief introduction to the subject, followed by two chapters that cover: general goals for wholesale power market design; history, operations, and conceptual concerns for current U.S. RTO/ISO-managed wholesale power markets; and the relationship of the present study to previous swing-contract research. The next eight chapters cover: a general swing-contract formulation for centrally-managed wholesale power markets; illustrative swing-contract reserve offers;inclusion of reserve offers with price swing; inclusion of price-sensitive reserve bids; and extension to a linked collection of swing-contract markets. Operations in current U.S. RTO/ISO-managed markets are reviewed in the following four chapters, and conceptual and practical advantages of the linked swing-contract market design are carefully considered. The book concludes with an examination of two key issues: How might current U.S. RTO/ISO-managed markets transition gradually to a swing-contract form? And how might independent distribution system operators, functioning as linkage entities at transmission and distribution system interfaces, make use of swing contracts to facilitate their participation in wholesale power markets as providers of ancillary services harnessed from distribution-side resources? In summary, this title: Addresses problems with current wholesale electric power markets by developing a new swing-contract market design from concept to practical implementationProvides introductory chapters that explain the general principles motivating the new market design, hence why a new approach is requiredDevelops a new type of swing contract suitable for wholesale power markets with increasing reliance on renewable energy and active demand-side participation A New Swing-Contract Design for Wholesale Power Markets is an ideal book for electric power system professionals and for students specializing in electric power systems.Table of ContentsPreface xiii Author Biography xiv Acknowledgments xv Chapter 1 Introduction 1 Chapter 2 US RTO/ISO-Managed Wholesale Power Markets: Overview 9 2.1 Chapter Preview 9 2.2 General Goals for Wholesale Power Market Design 9 2.3 US RTO/ISO-Managed Market Operations 10 2.4 Stresses Faced by Current US RTO/ISO-Managed Markets 14 Chapter 3 Motivation For Current Study 17 3.1 Chapter Preview 17 3.2 Problematic Design Aspects of US RTO/ISO-Managed Wholesale Power Markets 17 3.2.1 Artificial Distinction Between Energy and Reserve 17 3.2.2 Problematic use of Hedonic Pricing 18 3.2.3 Revenue Insufficiency and Incentive Problems 19 3.2.4 Computational Fragility of LMP Derivations 20 3.2.5 Performance Payment in Advance of Performance Delivery 22 3.2.6 Minimal Direct Representation of Retail Customer Interests 23 3.2.7 Reliance on Overly Simplistic Cost Conceptions 24 3.2.8 Use of Spot-Market Pricing for Forward Markets 26 3.3 Relation of Current Study to Previous Swing-Contract Work 26 Chapter 4 Swing Contracts For Iso-Managed Wholesale Power Markets 29 4.1 Swing Contract Overview 29 4.2 Swing Contracts: General Formulation 29 4.3 Swing Contracts in Firm or Option Form 31 Chapter 5 Illustrative Swing-Contract Reserve Offers 35 5.1 Chapter Preview 35 5.2 A Simple Energy-Block Swing Contract in Firm Form 37 5.3 An Energy-Block Swing Contract in Option Form 40 5.4 Swing-Contract Implementation of Standard Supply Offers 41 5.5 A Swing Contract Offering Continuous Swing (Flexibility) in Power and Ramp 47 5.6 A Swing Contract Offering Battery Services 49 5.7 Swing-Contract Facilitation of Private Bilateral Contracting 52 Chapter 6 Swing-Contract Market Design 55 6.1 Chapter Preview 55 6.2 General Swing-Contract Market Formulation 55 6.3 Financial and Physical Feasibility of Swing-Contract Offers 58 6.4 Reserve Bids 58 6.5 Handling of Fixed Reserve Bids and Non-Dispatched Power 60 6.6 Performance Penalties and Incentives 60 6.7 ISO Cost Allocation 61 Chapter 7 Swing-Contract Market Optimization: Base-Case Milp Formulation 67 7.1 Chapter Preview 67 7.2 General Assumptions and Notation 68 7.3 Discretization of the ISO’s Optimization Problem 69 7.4 ISO Objective Function 73 7.5 Complete Analytical MILP Formulation 74 7.6 Additional Discussion of Optimization Aspects 76 7.7 Five-Bus Test Case 78 7.8 Thirty Bus Test Case with Adaptive Reserve Zones 81 Chapter 8 Inclusion Of Reserve Offers With Price Swing 85 8.1 Chapter Preview 85 8.2 Cost Function Preliminaries 86 8.3 MILP Tractable form of Reserve Offers with Price Swing 87 Chapter 9 Inclusion Of Price-Sensitive Reserve Bids 93 9.1 Chapter Preview 93 9.2 Incorporation of Benefits 94 9.3 Modeling of Price-Sensitive Reserve Bids 96 9.3.1 Standard Demand Function Formulation 96 9.3.2 Reserve Bids with Time-of-Use Pricing 97 9.3.3 Reserve Bids with Price Swing 97 9.3.4 Reserve Bids Directly Expressed as Benefit Functions 99 9.4 MILP Tractable Approximation of Benefit Functions 100 Chapter 10 The Linked Swing-Contract Market Design 105 10.1 Chapter Preview 105 10.2 Multistage Optimization and Time Inconsistency 107 10.3 Settlement Time-Consistency of Swing-Contract Markets 109 10.4 Swing-Contract Long-Term Forward Markets 111 10.5 Swing-Contract Short-Term Forward Markets 112 10.6 Swing-Contract Very Short-Term Forward Markets 113 10.7 Swing-Contract Deployment in Real-Time Operations 114 Chapter 11 Illustration: Linked Day-Ahead And Hour-Ahead Swing-Contract Markets 117 11.1 Chapter Preview 117 11.2 Hour-Ahead Market with Reserve Offers Consisting of Swing-Contract Portfolios 117 11.3 SCED Solution for Hour-Ahead Swing-Contract Market 122 11.3.1 Overview 122 11.3.2 Power Balance 122 11.3.3 Coverage of the ISO’s Uncertainty Set 123 11.3.4 Constrained Minimization of Expected Cost 125 11.4 Linked Day-Ahead and Hour-Ahead Markets 126 Chapter 12 Standard Modeling Of A Competitive Market 131 12.1 Chapter Preview 131 12.2 Key Definitions 131 12.3 Standard Competitive Market Assumptions 132 12.4 Law of One Price for Commodities 132 12.5 Competitive Market: Basic Formulation 133 12.6 Net Surplus Extraction 136 12.7 Market Efficiency Metric 137 12.8 Market Efficiency and Pricing Rules 139 12.9 Strategic Trade Behavior and Trader Market Power 140 CHAPTER 13 US RTO/ISO-Managed Markets: Efficiency And Market Power 143 13.1 Chapter Preview 143 13.2 Daily Market Operations 144 13.3 Illustrative Analytical DAM Formulation 146 13.4 Net Surplus Extraction in the Illustrative DAM 147 13.5 Market Power in the Illustrative DAM: Type-I Error 152 13.6 Market Power in the Illustrative DAM: Type-II Error 156 13.7 Market Inefficiency in the Illustrative DAM 160 13.8 DAM Performance: General Assessment 163 13.9 Scheduling of Bilateral Contracts 165 Chapter 14 Comparisons With Swing-Contract Markets 167 14.1 Chapter Preview 167 14.2 Product Definition in US RTO/ISO-Managed Markets 168 14.3 Wholesale Power and the Law of One Price (Not) 170 14.4 Differential vs. Uniform Pricing 171 14.5 Comparison of SC and Current US DAM Designs 172 Chapter 15 Advantages Of The Linked Swing-Contract Market Design 175 15.1 Chapter Preview 175 15.2 SC Markets are Physically-Covered Insurance Markets 176 15.3 Longer-Term SC Markets Support New Investment 177 15.3.1 Energy-Only Market 179 15.3.2 Centrally Managed Capacity Market 181 15.3.3 LSE Bilateral Contract Obligations 182 15.4 SC Markets Ensure Revenue Sufficiency 183 15.5 SC Markets Ameliorate Merit-Order Concerns 184 15.6 SC Markets are Robust-Control Mechanisms 185 15.7 SC Markets Reduce Rule Complexity 186 15.8 SC Markets Reduce Gaming Opportunities 187 15.9 SC Markets have Smaller-Sized Optimizations 189 15.10 Additional Advantages of SC Markets 190 15.10.1 Ensure a Level Playing Field for Resource Participation 190 15.10.2 Permit Co-Optimization of Diverse Reserve 191 15.10.3 Appropriately Remunerate Diversity and Flexibility 191 15.10.4 Encourage Accurate Forecasting and Dispatch Following 191 15.10.5 Ensure Settlement Time-Consistency 191 Chapter 16 Gradual Transition To Linked Swing-Contract Markets 193 16.1 Chapter Preview 193 16.2 A DAM Formulation Permitting Gradual Transition 195 16.3 Cost Function Preliminaries for the Transitional DAM 197 16.4 MILP SCUC/SCED Optimization for the Transitional DAM 201 Chapter 17 Swing-Contract Support For Integrated Transmission And Distribution Systems 209 17.1 Chapter Preview 209 17.2 Transactive Energy System Design for ITD Systems 211 17.3 Role of Distribution Utilities 215 17.4 An IDSO-Managed Bid-Based TES Design for Households 216 17.5 IDSOs as Grid-Edge Resource Aggregators 219 17.6 Swing-Contract Support for IDSO Participation in Wholesale Power Markets 220 Chapter 18 Design Evaluation Via The ITD TES Platform 221 18.1 Chapter Preview 221 18.2 Design Readiness Levels 222 18.3 An ITD TES Platform Permitting TES Design Evaluation 223 18.4 Illustrative Test Cases: Overview 226 18.5 Illustrative Test Cases: Report 229 18.5.1 IDSO Peak-Load Reduction Capabilities 229 18.5.2 IDSO Load-Matching Capabilities 229 18.5.3 Household ITD Test Cases: Discussion 233 Chapter 19 Potential Future Research Directions 235 19.1 Effective use of Option Swing Contracts 235 19.2 Representation of Reserve Bids 236 19.3 Compensation for Storage Services 236 19.4 Compensation for Reliability Services 236 19.5 Representation of Power-Paths 237 19.6 Implementation of Contract-Clearing Optimizations for Swing-Contract Markets 237 19.7 Gradual Transition to a Swing-Contract Market 238 Chapter 20 Conclusion: The Dots Keep Connecting 239 Appendix A Appendices 241 References 249 Index 259

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Book SynopsisDiscover the foundations and nuances of electrical connectors in this comprehensive and insightful resource Electrical Connectors: Design, Manufacture, Test, and Selection delivers a comprehensive discussion of electrical connectors, from the components and materials that comprise them to their classifications and underwater, power, and high-speed signal applications. Accomplished engineer and author Michael G. Pecht offers readers a thorough explanation of the key performance and reliability concerns and trade-offs involved in electrical connector selection. Readers, both at introductory and advanced levels, will discover the latest industry standards for performance, reliability, and safety assurance. The book discusses everything a student or practicing engineer might require to design, manufacture, or select a connector for any targeted application. The science of contact physics, contact finishes, housing materials, andthe full connector assembly process are all discussed at length, as are test methods, performance, and guidelines for various applications. Electrical Connectors covers a wide variety of other relevant and current topics, like: A comprehensive description of all electrical connectors, including their materials, components, applications, and classificationsA discussion of the design and manufacture of all parts of a connectorApplication-specific criteria for contact resistance, signal quality, and temperature riseAn examination of key suppliers, materials used, and the different types of data providedA presentation of guidelines for end-users involved in connector selection and design Perfect for connector manufacturers who select, design, and assemble connectors for their products or the end users who concern themselves with operational reliability of the systemin which they're installed,Electrical Connectorsalso belongs on the bookshelves of students learning the basics of electrical contacts and those who seek a general reference with best-practice advice on how to choose and test connectors for targeted applications. Table of ContentsAbout the Editors xiii List of Contributors xv Preface xvii 1 What Is an Electrical Connector? 1Michael G. Pecht and San Kyeong 1.1 Challenges of Separable Connectors 1 1.2 Components of a Connector 2 1.2.1 Contact Springs 2 1.2.2 Contact Finishes 3 1.2.2.1 Noble Metal Contact Finishes 4 1.2.2.2 Non-noble Metal Contact Finishes 4 1.2.3 Connector Housing 4 1.2.4 Contact Interface 5 1.3 Connector Types 6 1.3.1 Board-to-Board Connectors 7 1.3.2 Wire/Cable-to-Wire/Cable Connectors 8 1.3.3 Wire/Cable-to-Board Connectors 10 1.4 Connector Terminology 11 References 14 2 Connector Housing 17Michael G. Pecht 2.1 Mechanical Properties 17 2.2 Electrical Properties 19 2.3 Flammability 21 2.4 Temperature Rating 22 2.5 Housing Materials 23 2.5.1 Thermoplastic Polymers 25 2.5.1.1 Polyesters 25 2.5.1.2 Polyimides, Polyamide-imides, and Polyetherimides 26 2.5.1.3 Polyphenylene Sulfides 26 2.5.1.4 Polyether Ether Ketones 26 2.5.1.5 Liquid-Crystalline Polymers 27 2.5.1.6 Comparison ofThermoplastic Polymers 27 2.5.2 Thermosetting Polymers 27 2.5.3 Additives to Housing Materials 29 2.5.4 Manufacturing of Housing Materials 29 References 30 3 Contact Spring 31Michael G. Pecht 3.1 Copper Alloys 31 3.1.1 Unified Number System (UNS) 31 3.1.2 Properties of Copper Alloys 33 3.2 Nickel Alloys 37 3.3 Conductive Elastomers 37 3.4 Contact Manufacturing 38 References 41 4 Contact Plating 43Michael G. Pecht 4.1 Noble Metal Plating 43 4.1.1 Gold 44 4.1.2 Palladium 46 4.1.3 Combination of Gold and Palladium 47 4.2 Non-noble Metal Plating 47 4.2.1 Silver 48 4.2.1.1 Characteristics of Silver as a Contact Finish 49 4.2.1.2 Potential Tarnish-Accelerating Factors 50 4.2.1.3 Use of Silver in Typical Connectors 53 4.2.1.4 Managing Silver Corrosion 54 4.2.2 Silver-Palladium Alloys 55 4.2.3 Nanocrystalline Silver Alloys 55 4.2.4 Silver-Bismuth Alloys 57 4.2.5 Tin 57 4.2.6 Nickel Contact Finishes 59 4.3 Underplating 59 4.4 Plating Process 60 4.4.1 Electrolytic Plating 61 4.4.1.1 Rack Plating 61 4.4.1.2 Barrel Plating 61 4.4.2 Electroless Plating 62 4.4.3 Cladding 63 4.4.4 Hot Dipping 63 References 63 5 Insertion and Extraction Forces 67Michael G. Pecht 5.1 Insertion and Extraction Forces 67 5.2 Contact Retention 70 5.3 Contact Force and Deflection 70 5.4 Contact Wipe 71 References 73 6 Contact Interface 75Michael G. Pecht and San Kyeong 6.1 Constriction Resistance 76 6.2 Contact Resistance 77 6.3 Other Factors Affecting Contact Resistance 79 6.4 Current Rating 81 6.5 Capacitance and Inductance 82 6.6 Bandpass and Bandwidth 86 References 87 7 The Back-End Connection 89Chien-Ming Huang, San Kyeong and Michael G. Pecht 7.1 Soldered Connection 89 7.2 Press-Fit Connection 93 7.3 Crimping Connection 95 7.4 Insulation Displacement Connection 98 References 98 8 Loads and Failure Mechanisms 103San Kyeong, Lovlesh Kaushik and Michael G. Pecht 8.1 Environmental Loads 104 8.1.1 Temperature 104 8.1.2 Vibration Load 105 8.1.3 Humidity 106 8.1.4 Contamination 107 8.1.5 Differential Pressure 108 8.2 Failure Mechanisms in Electrical Connectors 109 8.2.1 Silver Migration 110 8.2.2 Tin Whiskers 114 8.2.3 Corrosion Failure 119 8.2.3.1 Dry Corrosion 119 8.2.3.2 Galvanic Corrosion 120 8.2.3.3 Pore Corrosion 121 8.2.3.4 Creep Corrosion 121 8.2.3.5 Fretting Corrosion 123 8.2.4 Arc Formation 124 8.2.5 Creep Failure 128 8.2.6 Wear 131 8.2.6.1 Adhesive Wear 132 8.2.6.2 Abrasive Wear 133 8.2.6.3 Fatigue Wear 134 8.2.6.4 Corrosive Wear 134 8.2.6.5 Fretting Wear 135 8.2.7 Frictional Polymerization 136 8.3 Case Study by NASA: Electrical Connectors for Spacecraft 137 References 139 9 Fretting in Connectors 147Deepak Bondre and Michael G. Pecht 9.1 Mechanisms of Fretting Failure 149 9.1.1 Material Factors That Affect Fretting 152 9.1.1.1 Contact Materials 152 9.1.1.2 Hardness 155 9.1.1.3 Surface Finish 155 9.1.1.4 Frictional Polymerization 156 9.1.1.5 Grain Size 156 9.1.1.6 Oxides 157 9.1.1.7 Coefficient of Friction 158 9.1.1.8 Electrochemical Factor 158 9.1.2 Operating Factors That Affect Fretting 158 9.1.2.1 Contact Load 158 9.1.2.2 Fretting Frequency 159 9.1.2.3 Slip Amplitude 162 9.1.2.4 Electric Current 162 9.1.3 Environmental Factors That Affect Fretting 163 9.1.3.1 Humidity 164 9.1.3.2 Temperature 164 9.1.3.3 Dust 165 9.2 Reducing the Damage of Fretting 167 9.2.1 Lubrication 168 9.2.2 Improvement in Design 168 9.2.3 Coatings 169 References 170 10 Testing 173Bhanu Sood andMichael G. Pecht 10.1 Dielectric With standing Voltage Testing 173 10.2 Insulation Resistance Testing 174 10.3 Contact Resistance Testing 176 10.4 Current Rating 179 10.5 Electromagnetic Interference and Electromagnetic Compatibility Testing 180 10.6 Temperature Life Testing 181 10.7 Thermal Cycling Testing 182 10.8 Thermal Shock Testing 182 10.9 Steady-State Humidity Testing 183 10.10 Temperature Cycling with Humidity Testing 184 10.11 Corrosion 184 10.11.1 Dry Corrosion 185 10.11.2 Creep Corrosion 186 10.11.3 Moist Corrosion 187 10.11.4 Fretting Corrosion 187 10.12 Mixed Flowing Gas Testing 188 10.12.1 Battelle Labs MFG Test Methods 189 10.12.2 EIA MFG Test Methods: EIA 364-TP65A 190 10.12.3 IEC MFG Test Methods: IEC 68-2-60 Part 2 190 10.12.4 Telcordia MFG Test Methods: Telcordia GR-63-CORE Section 5.5 191 10.12.5 IBM MFG Test Methods: G1(T) 191 10.12.6 CALCE MFG Chamber Capability 192 10.13 Vibration 192 10.13.1 Mechanical Shock 193 10.13.2 Mating Durability 193 10.14 Highly Accelerated Life Testing 194 10.15 Environmental Stress Screening 194 References 195 11 Supplier Selection 197Michael H. Azarian, Diganta Das and Michael G. Pecht 11.1 Connector Reliability 197 11.2 Capability Maturity Models 198 11.3 Key Reliability Practices 198 11.3.1 Reliability Requirements and Planning 199 11.3.2 Training and Development 200 11.3.3 Reliability Analysis 200 11.3.4 Reliability Testing 201 11.3.5 Supply-Chain Management 201 11.3.6 Failure Data Tracking and Analysis 202 11.3.7 Verification and Validation 202 11.3.8 Reliability Improvement 203 11.4 Reliability Capability of an Organization 203 11.5 The Evaluation Process 204 References 205 12 Selecting the Right Connector 207Ilknur Baylakoglu and San Kyeong 12.1 Connector Requirements Based on Design and Targeted Application 207 12.2 Mating Cycles 208 12.3 Current and Power Ratings 209 12.4 Environmental Conditions 212 12.5 Termination Types 213 12.6 Materials 213 12.6.1 Connector Housing Materials 216 12.6.2 Connector Spring Materials 217 12.7 Contact Finishes 217 12.8 Reliability 218 12.9 Raw Cables and Assemblies 219 12.10 Supplier Reliability Capability Maturity 219 12.11 Connector Selection Team 220 12.12 Selection of Candidate Parts from a Preferred Parts Database 221 12.13 Electronic Product Manufacturers’ Parts Databases 221 12.14 Parts Procurement 223 12.15 Parts Availability 223 12.16 High-Speed Connector Selection 224 12.17 NASA Connector Selection 224 12.18 Harsh Environment Connector Selection 227 12.19 Fiber-Optic Interconnect Requirements by Market 229 12.20 High-Power Subsea Connector Selection 229 12.20.1 Undersea Connector Reliability 231 12.21 Screening Tests 232 12.22 Low-Voltage Automotive Single- and Multiple-Pole Connector Validation 236 12.23 Failure Modes, Mechanisms, and Effects Analysis for Connectors 236 12.24 Connector Experiments 242 12.25 Summary 246 References 246 13 Signal Connector Selection 251Michael G. Pecht 13.1 Issues Involving High-Speed Connectors 251 13.2 Signal Transmission Quality Considerations 252 13.2.1 Interconnect Delays 252 13.2.2 Signal Distortion 252 13.3 Electromagnetic Compatibility 253 13.4 Virtual Prototyping 254 13.4.1 TDR Impedance Measurements 255 13.4.1.1 Reflection Coefficient 255 13.4.1.2 TDR Resolution Factors 256 13.4.1.3 TDR Accuracy Factors 257 13.5 Vector Network Analyzer 259 13.6 Simulation Program with Integrated Circuit Emphasis (SPICE) 259 References 260 14 Advanced Technology Attachment Connectors 261Neda Shafiei, Kyle LoGiudice and Michael G. Pecht 14.1 ATA Connector and SATA Connector Overview 261 14.2 History of ATA and SATA 263 14.3 Physical Description of ATA Connectors, ATA Alternative Connectors, and SATA Connectors 264 14.4 ATA Standardization and Revisions 268 14.5 SATA Standardization and Revisions 270 14.6 SATA in the Future 272 References 273 15 Power Connectors 275Michael G. Pecht and San Kyeong 15.1 Requirements for Power Connectors 275 15.2 Power Connector Materials 276 15.3 Types of Power Connectors 277 15.4 Power Contact Resistance 280 15.5 Continuous, Transient, and Overload Current Capacities 282 15.5.1 Continuous Current Capacity 282 15.5.2 Transient Current Capacity 283 15.5.3 Overload Current Capacity 284 15.6 Current Rating Method 284 References 286 16 Electrical Connectors for Underwater Applications 289Flore Remouit, Jens Engström and Pablo Ruiz-Minguela 16.1 Background and Terminology 290 16.1.1 History 291 16.1.2 Terminology 291 16.2 Commercial Off-the-Shelf (COTS) Connectors 292 16.2.1 Rubber-Molded 292 16.2.2 Rigid-Shell or Bulkhead Assemblies 293 16.2.3 Fluid-Filled UnderwaterMateable 294 16.2.4 Inductive Coupling 295 16.2.5 Assemblies (Non-unmateable) 295 16.3 Connector Design 296 16.3.1 Thermal Design 296 16.3.2 Electrical Properties 297 16.3.3 Mechanical Properties 299 16.3.4 Material Choices 300 16.3.5 Specifications for Underwater Connectors 301 16.4 Connector Deployment and Operation 302 16.4.1 Connection Procedure 302 16.4.2 Connection Layout 303 16.4.3 Reliability 305 16.5 Discussion and Conclusion 305 References 306 17 Examples of Connectors 313Lei Su, Xiaonan Yu, San Kyeong andMichael G. Pecht 17.1 Amphenol ICC M-SeriesTM 56 Connectors 313 17.2 Amphenol ICC Paladin®Connectors 313 17.3 Amphenol ICC 3000W EnergyEdgeTM X-treme Card Edge Series 314 17.4 Amphenol ICC FLTStack Connectors 314 17.5 Amphenol ICC HSBridge Connector System 315 17.6 Amphenol ICC MUSBR Series USB 3.0 Type-A Connectors 315 17.7 Amphenol ICCWaterproof USB Type-CTM Connectors 316 17.8 Amphenol ICC NETBridgeTM Connectors 316 17.9 Amphenol Sine Systems DuraMateTM AHDP Circular Connectors 317 17.10 Amphenol Aerospace MIL-DTL-38999 Series III Connectors 318 17.11 Fischer Connectors UltiMateTM Series Connectors 318 17.12 Hirose Electric DF50 Series Connectors 319 17.13 Hirose Electric microSDTM Card Connectors 320 17.14 Molex SAS-3 and U.2 (SFF-8639) Backplane Connectors 320 17.15 Molex NeoPressTM Mezzanine Connectors 321 17.16 Molex ImpelTM Plus Backplane Connectors 321 17.17 Molex EXTreme GuardianTM Power Connectors 322 17.18 Molex ImperiumTM High Voltage/High Current Connectors 323 17.19 TE Connectivity Free Height Connectors 323 17.20 TE Connectivity STRADAWhisper Connectors 323 17.21 TE ConnectivityMULTI-BEAM High-Density (HD) Connectors 324 17.22 TE Connectivity HDMITM Connectors 325 17.23 TE Connectivity AMP CT Connector Series 325 17.24 TE ConnectivityMicro Motor Connectors 326 17.25 TE Connectivity AMPSEAL Connectors 326 17.26 TE Connectivity M12 X-Code Connectors 327 17.27 TE Connectivity SOLARLOK 2.0 Connectors 327 17.28 TE Connectivity Busbar Connectors 328 References 329 Appendix Standards 331 A.1 Standard References for Quality Management and Assurance 332 A.2 General Specifications for Connectors 332 A.3 Safety-Related Standards and Specifications 332 A.4 Standard References for Connector Manufacturing 333 A.5 Standard References for Socket Material Property Characterization 334 A.6 Standard References for Socket Performance Qualification 335 A.7 Standard References for Socket Reliability Qualification 336 A.8 Other Standards and Specifications 338 A.9 Telcordia 338 A.10 Society of Cable Telecommunications Engineers (SCTE) 339 A.11 Electronic Industries Alliance/Telecommunications Industry Association (EIA/TIA) 339 A.12 International Electrotechnical Commission (IEC) 340 A.12.1 IEC Standards 341 A.12.2 IEC Connectors 341 A.13 Military Standards (MIL-STD) 341 A.14 Standards for Space-Grade Connectors 342 References 345 Index 347

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Book SynopsisDiscover detailed insights into the methods, algorithms, and techniques for deep learning in sensor data analysis Sensor Data Analysis and Management: The Role of Deep Learning delivers an insightful and practical overview of the applications of deep learning techniques to the analysis of sensor data. The book collects cutting-edge resources into a single collection designed to enlighten the reader on topics as varied as recent techniques for fault detection and classification in sensor data, the application of deep learning to Internet of Things sensors, and a case study on high-performance computer gathering and processing of sensor data. The editors have curated a distinguished group of perceptive and concise papers that show the potential of deep learning as a powerful tool for solving complex modelling problems across a broad range of industries, including predictive maintenance, health monitoring, financial portfolio forecasting, and driver assistanTable of ContentsAbout the Editors vii List of Contributors ix Preface xiii 1 Efficient Resource Allocation Using Multilayer Neural Network in Cloud Environment 1N. Vijayaraj, G. Uganya, M. Balasaraswathi, V. Sivasankaran, Radhika Baskar, and A.S. Syed Fiaz 2 Internet of Things for Human-Activity Recognition Based on Wearable Sensor Data 19Dr. Vikram Rajpoot, Sudeep Ray Gaur, Aditya Patel, and Dr. Akash Saxena 3 Evaluation of Feature Selection Techniques in Intrusion Detection Systems Using Machine Learning Models in Wireless Ad Hoc Networks 33T.J. Nagalakshmi, M. Balasaraswathi, V. Sivasankaran, D. Ravikumar, S. Joseph Gladwin, and S. Pravin Kumar 4 Neuro-Fuzzy-Based Bidirectional and Biobjective Reactive Routing Schema for Critical Wireless Sensor Networks 73K.M. Karthick Raghunath and G.R. Anantha Raman 5 Feature Detection and Extraction Techniques for Real-Time Student Monitoring in Sensor Data Environments 97Dr. V. Saravanan and Dr (Ms). N. Shanmuga Priya 6 Deep Learning Analysis of Location Sensor Data for Human-Activity Recognition 103Hariprasath Manoharan, Ganesan Sivarajan, and Subramanian Srikrishna 7 A Quantum-Behaved Particle-Swarm-Optimization-Based KNN Classifier for Improving WSN Lifetime 117Ajmi Nader, Helali Abdelhamid, and Mghaieth Ridha 8 Feature Detection and Extraction Techniques for Sensor Data 131Dr. L. Priya, Ms. A. Sathya, and Dr. S. Thanga Revathi 9 Object Detection in Satellite Images Using Modified Pyramid Scene Parsing Networks 147Akhilesh Vikas Kakade, S Rajkumar (Corresponding Author), K Suganthi, and L Ramanathan 10 Coronary Illness Prediction Using the AdaBoost Algorithm 161G. Deivendran, S. Vishal Balaji, B. Paramasivan, S. Vimal (Corresponding Author) 11 Geographic Information Systems and Confidence Interval with Deep Learning Techniques for Traffic Management Systems in Smart Cities 173Prisilla Jayanthi Index 199

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Book SynopsisTable of ContentsPreface xxi Acknowledgements xxiii 1 Fundamentals of Electrical Machines 1 1.1 Preliminary Remarks 1 1.2 Basic Laws of Electrical Engineering 1 1.2.1 Ohm’s Law 1 1.2.2 Generalization of Ohm’s Law 2 1.2.2.1 Derivation of Eq. (1.6) 2 1.2.3 Ohm’s Law for Magnetic Circuits 3 1.2.4 Kirchhoff’s Laws for Magnetic Circuits 3 1.2.5 Lorentz Force Law 5 1.2.6 Biot-Savart Law 6 1.2.7 Ampere Circuital Law 17 1.2.8 Faraday’s Law 20 1.2.8.1 Motional emf 24 1.2.9 Flux Linkages and Induced Voltages 29 1.2.10 Induced Voltages 29 1.2.11 Induced Electric Fields 30 1.2.12 Reformulation of Faraday’s Law 31 1.3 Inductance 38 1.3.1 Application of Ampere’s Law to Find B in a Solenoid 39 1.3.2 Magnetic Field of a Toroid 40 1.3.3 The Inductance of Circular Air-Cored Toroid 40 1.3.4 Mutual Inductance 44 1.4 Energy 47 1.5 Overview of Electric Machines 49 1.6 Summary 58 Problems 58 References 67 2 Magnetic Circuits 69 2.1 Preliminary Remarks 69 2.2 Permeability 69 2.3 Classification of Magnetic Materials 70 2.3.1 Uniform Magnetic Field 72 2.3.2 Magnetic-Field Intensity 72 2.4 Hysteresis Loop 74 2.4.1 Hysteresis Loop for Soft Iron and Steel 76 2.5 Eddy-Current and Core Losses 78 2.6 Magnetic Circuits 82 2.6.1 The Magnetic Circuit Concept 82 2.6.2 Magnetic Circuits Terminology 82 2.6.2.1 Limitations of the Analogy Between Electric and Magnetic Circuits 86 2.6.3 Effect of Air Gaps 86 2.6.3.1 Magnetic Circuit with an Air Gap 86 2.6.3.2 Magnetic Forces Exerted by Electromagnets 89 2.7 Field Energy 100 2.7.1 Energy Stored in a Magnetic Field 100 2.7.1.1 The Magnetic Energy in Terms of the Magnetic Induction B 101 2.7.1.2 The Magnetic Energy in Terms of the Current Density J and the Vector Potential A 102 2.7.1.3 The Magnetic Energy in Terms of the Current I and of the Flux 𝛹m 103 2.7.1.4 The Magnetic Energy in Terms of the Currents and Inductances 103 2.8 The Magnetic Energy for a Solenoid Carrying a Current I 104 2.9 Energy Flow Diagram 106 2.9.1 Power Flow Diagram of DC Generator and DC Motor 106 2.9.1.1 Power Flow Diagram and Losses of Induction Motor 108 2.9.1.2 Rotational Losses 109 2.10 Multiple Excited Systems 110 2.11 Doubly Excited Systems 113 2.11.1 Torque Developed 116 2.11.1.1 Excitation Torque 117 2.11.1.2 Reluctance Torque 122 2.12 Concept of Rotating Magnetic Field 126 2.12.1 Rotating Magnetic Field due to Three-Phase Currents 126 2.12.1.1 Speed of Rotating Magnetic Field 130 2.12.1.2 Direction of Rotating Magnetic Field 131 2.12.2 Alternate Mathematical Analysis for Rotating Magnetic Field 131 2.13 Summary 134 Problems 135 References 144 3 Single-Phase and Three-Phase Transformers 147 3.1 Preliminary Remarks 147 3.2 Classification of Transformers 149 3.2.1 Classification Based on Number of Phases 149 3.2.1.1 Single-Phase Transformers 149 3.2.1.2 Three-Phase Transformers 149 3.2.1.3 Multi-Phase Transformers 150 3.2.2 Classification Based on Operation 150 3.2.2.1 Step-Up Transformers 150 3.2.2.2 Step-Down Transformers 151 3.2.3 Classification Based on Construction 151 3.2.3.1 Core-Type Transformers 151 3.2.3.2 Shell-Type Transformers 151 3.2.4 Classification Based on Number of Windings 153 3.2.4.1 Single-Winding Transformer 153 3.2.4.2 Two-Winding Transformer 153 3.2.4.3 Three-Winding Transformer 153 3.2.5 Classification Based on Use 153 3.2.5.1 Power Transformer 153 3.2.5.2 Distribution Transformer 154 3.3 Principle of Operation of the Transformer 154 3.3.1 Ideal Transformer 154 3.4 Impedance Transformation 157 3.5 DOT Convention 158 3.6 Real/Practical Transformer 158 3.7 Equivalent Circuit of a Single-Phase Transformer 160 3.8 Phasor Diagrams Under Load Condition 166 3.9 Testing of Transformer 170 3.9.1 Open-Circuit Test 171 3.9.2 Short-Circuit Test 172 3.10 Performance Measures of a Transformer 175 3.10.1 Voltage Regulation 175 3.10.1.1 Condition for Maximum Voltage Regulation 177 3.10.1.2 Condition for Zero Voltage Regulation 177 3.10.2 Efficiency of Transformer 180 3.10.3 Maximum Efficiency Condition 181 3.11 All-Day Efficiency or Energy Efficiency 185 3.12 Autotransformer 186 3.13 Three-Phase Transformer 190 3.13.1 Input (Y), Output (Δ) 192 3.13.2 Input Delta (Δ), Output Star (Y) 194 3.13.3 Input Delta (Δ), Output Delta (Δ) 195 3.13.4 Input Star (Y), Output Star (Y) 196 3.14 Single-Phase Equivalent Circuit of Three-Phase Transformer 197 3.15 Open-Delta Connection or V Connection 200 3.16 Harmonics in a Single-Phase Transformer 205 3.16.1 Excitation Phenomena in a Single-Phase Transformer 208 3.16.2 Harmonics in a Three-Phase Transformer 210 3.16.2.1 Star-Delta Connection with Grounded Neutral 213 3.16.2.2 Star-Delta Connection without Grounded Neutral 214 3.16.3 Summary 214 3.16.4 Star-Star with Isolated Neutral 214 3.17 Disadvantages of Harmonics in Transformer 215 3.17.1 Effect of Harmonic Currents 215 3.17.2 Electromagnetic Interference 215 3.17.3 Effect of Harmonic Voltages 215 3.17.4 Summary 216 3.17.5 Oscillating Neutral Phenomena 216 3.18 Open Circuit and Short-Circuit Conditions in a Three-Phase Transformer 217 3.19 Matlab/Simulink Model of a Single-Phase Transformer 219 3.20 Matlab/Simulink Model of Testing of Transformer 222 3.21 Matlab/Simulink Model of Autotransformer 223 3.22 Matlab/Simulink Model of Three-Phase Transformer 223 3.23 Supplementary Solved Problems 232 3.24 Summary 249 3.25 Problems 249 References 255 4 Fundamentals of Rotating Electrical Machines and Machine Windings 257 4.1 Preliminary Remarks 257 4.2 Generator Principle 257 4.2.1 Simple Loop Generator 257 4.2.2 Action of Commutator 259 4.2.3 Force on a Conductor 260 4.2.3.1 DC Motor Principle 260 4.2.3.2 Motor Action 261 4.3 Machine Windings 261 4.3.1 Coil Construction 261 4.3.1.1 Coil Construction: Distributed Winding 261 4.3.1.2 Coil Construction: Concentrated Winding 262 4.3.1.3 Coil Construction: Conductor Bar 262 4.3.2 Revolving (Rotor) Winding 262 4.3.3 Stationary (Stator) Winding 262 4.3.4 DC ArmatureWindings 262 4.3.4.1 Pole Pitch (Yp) 263 4.3.4.2 Coil Pitch or Coil Span (Ycs) 263 4.3.4.3 Back Pitch (Yb) 263 4.3.4.4 Front Pitch (Yf) 264 4.3.4.5 Resultant Pitch (Y) 264 4.3.4.6 Commutator Pitch (a) 264 4.3.5 Lap Winding 265 4.3.5.1 Lap Multiple or Parallel Windings 265 4.3.5.2 Formulas for Lap Winding 266 4.3.5.3 Multiplex, Single, Double, and Triple Windings 267 4.3.5.4 Meaning of the Term Re-entrant 268 4.3.5.5 Multiplex Lap Windings 268 4.3.6 WaveWinding 279 4.3.6.1 Formulas forWave Winding 281 4.3.6.2 MultiplexWave or Series-ParallelWinding 282 4.3.6.3 Formulas for Series-Parallel Winding 283 4.3.7 Symmetrical Windings 284 4.3.7.1 Possible SymmetricalWindings for DC Machines of a Different Number of Poles 284 4.3.8 Equipotential Connectors (Equalizing Rings) 284 4.3.9 Applications of Lap andWave Windings 286 4.3.10 Dummy or Idle Coils 310 4.3.10.1 Dummy Coils 310 4.3.11 Whole-CoilWinding and Half-CoilWinding 311 4.3.12 Concentrated Winding 312 4.3.13 Distributed Winding 312 4.4 Electromotive Force (emf) Equation 313 4.4.1 emf Equation of an Alternator [1] 313 4.4.1.1 Winding Factor (Coil Pitch and Distributed Windings) 313 4.4.2 Winding Factors 313 4.4.2.1 Pitch Factor or Coil Pitch (Pitch Factor (Kp) or Coil Span Factor [Kc]) 314 4.4.3 Distribution Factor (Breadth Factor (Kb) or Distribution Factor (Kd)) 315 4.4.3.1 Distribution Factor (Kd) 315 4.5 Magnetomotive Force (mmf) of ACWindings 316 4.5.1 mmf and Flux in Rotating Machine 316 4.5.2 Main Air-Gap Flux (Field Flux) 316 4.5.3 mmf of a Coil [5] 316 4.5.3.1 mmf 316 4.5.3.2 mmf of Distributed Windings 317 4.5.3.3 mmf SpaceWave of a Single Coil 317 4.5.3.4 mmf SpaceWave of One Phase of a Distributed Winding [6] 319 4.6 Harmonic Effect [7] 322 4.6.1 The Form Factor and the emf per Conductor 322 4.6.2 TheWave Form 323 4.6.3 Problem Due to Harmonics 324 4.6.4 Elimination or Suppression of Harmonics 324 4.6.4.1 Shape of Pole Face 324 4.6.4.2 Use of Several Slots per Phase per Pole 324 4.6.4.3 Use of Short-Pitch Windings 325 4.6.4.4 Effect of the Y- and Δ -Connection on Harmonics 327 4.6.4.5 Harmonics Produced by Armature Slots 328 4.7 Basic Principles of Electric Machines 330 4.7.1 AC Rotating Machines 331 4.7.1.1 The Rotating Magnetic Field 331 4.7.1.2 The Relationship between Electrical Frequency and the Speed of Magnetic Field Rotation 333 4.7.1.3 Reversing the Direction of the Magnetic Field Rotation 335 4.7.1.4 The Induced Voltage in AC Machines 335 4.7.1.5 The Induced Voltage in a Coil on a Two-Pole Stator 335 4.7.1.6 The Induced Voltage in a Three-Phase Set of Coils 337 4.7.1.7 The rms Voltage in a Three-Phase Stator 338 4.7.2 The Induced Torque in an AC Machine 338 4.8 Summary 339 Problems 339 References 340 5 DC Machines 341 5.1 Preliminary Remarks 341 5.2 Construction and Types of DC Generator 342 5.2.1 Construction of DC Machine 342 5.2.2 Types of DC Generator 343 5.3 Principle of Operation of DC Generator 345 5.3.1 Voltage Build-Up in a DC Generator 346 5.3.2 Function of Commutator 347 5.4 Commutation Problem and Solution 349 5.4.1 Brush Shifting 349 5.4.2 Commutating Poles 350 5.4.3 Compensating Windings 350 5.5 Types of Windings 351 5.6 emf Equations in a DC Generator 351 5.7 Brush Placement in a DC Machine 353 5.8 Equivalent Circuit of DC Generator 354 5.9 Losses of DC Generator 354 5.10 Armature Reaction 360 5.10.1 No-Load Operation 361 5.10.2 Loaded Operation 361 5.11 Principle of Operation of a DC Motor 362 5.11.1 Equivalent Circuit of a DC Motor 363 5.12 emf and Torque Equations of DC Motor 364 5.13 Types of DC Motor 364 5.13.1 Separately Excited DC Motor 364 5.13.2 Self-Excited DC Motor 365 5.13.2.1 Shunt DC Motor 365 5.13.2.2 Series DC Motor 366 5.14 Characteristics of DC Motors 367 5.14.1 Separately Excited and DC Shunt Motor 368 5.14.2 DC Series Motor 369 5.14.3 Compound Motor 370 5.15 Starting of a DC Motor 371 5.15.1 Design of a Starter for a DC Motor 372 5.15.2 Types of Starters 373 5.15.2.1 Three-Point Starter 373 5.15.2.2 Four-Point Starter 374 5.16 Speed Control of a DC Motor 374 5.16.1 Separately Excited and DC Shunt Motor 375 5.16.2 DC Series Motor 376 5.17 Solved Examples 378 5.18 Matlab/Simulink Model of a DC Machine 387 5.18.1 Matlab/Simulink Model of a Separately/ Shunt DC Motor 387 5.18.2 Matlab/Simulink Model of a DC Series Motor 387 5.18.3 Matlab/Simulink Model of a Compound DC Motor 388 5.19 Summary 392 Problems 392 Reference 399 6 Three-Phase Induction Machine 401 6.1 Preliminary Remarks 401 6.2 Construction of a Three-Phase Induction Machine 402 6.2.1 Stator 402 6.2.2 Stator Frame 403 6.2.3 Rotor 403 6.3 Principle Operation of a Three-Phase Induction Motor 404 6.3.1 Slip in an Induction Motor 406 6.3.2 Frequency of Rotor Voltage and Current 407 6.3.3 Induction Machine and Transformer 408 6.4 Per-phase Equivalent Circuit of a Three-Phase Induction Machine 408 6.5 Power Flow Diagram in a Three-Phase Induction Motor 415 6.6 Power Relations in a Three-Phase Induction Motor 416 6.7 Steps to Find Powers and Efficiency 417 6.8 Per-Phase Equivalent Circuit Considering Stray-Load Losses 420 6.9 Torque and Power using Thevenin’s Equivalent Circuit 421 6.10 Torque-Speed Characteristics 424 6.10.1 Condition for Maximum Torque 427 6.10.2 Condition for Maximum Torque at Starting 429 6.10.3 Approximate Equations 429 6.11 Losses in a Three-Phase Induction Machine 433 6.11.1 Copper Losses or Resistive Losses 433 6.11.2 Magnetic Losses 434 6.11.3 Mechanical Losses 434 6.11.4 Stray-Load Losses 434 6.12 Testing of a Three-Phase Induction Motor 435 6.12.1 No-Load Test 435 6.12.2 Blocked Rotor Test 436 6.12.3 DC Test 437 6.12.4 Load Test 438 6.12.5 International Standards for Efficiency of Induction Machines 441 6.12.6 International Standards for the Evaluation of Induction Motor Efficiency 442 6.13 Starting of a Three-Phase Induction Motor 443 6.13.1 Direct-on-Line Start 446 6.13.2 Line Resistance Start 447 6.13.3 Star-Delta Starter 448 6.13.4 Autotransformer Starter 449 6.14 Speed Control of Induction Machine 451 6.14.1 By Varying the Frequency of the Supply 451 6.14.2 Pole Changing Method 452 6.14.2.1 Multiple Numbers of Windings 453 6.14.2.2 Consequent Pole Method 453 6.14.3 Stator Voltage Control 454 6.14.3.1 Voltage/Frequency = Constant Control 455 6.14.3.2 Rotor Resistance Variation 456 6.14.3.3 Rotor Voltage Injection Method 456 6.14.3.4 Cascade Connection of Induction Machines 456 6.14.3.5 Pole-Phase Modulation for Speed Control 458 6.15 Matlab/Simulink Modelling of the Three-Phase Induction Motor 461 6.15.1 Plotting Torque-Speed Curve under Steady-State Condition 464 6.15.2 Dynamic Simulation of Induction Machine 464 6.16 Practice Examples 469 6.17 Summary 482 Problems 482 References 489 7 Synchronous Machines 491 7.1 Preliminary Remarks 491 7.2 Synchronous Machine Structures 492 7.2.1 Stator and Rotor 492 7.3 Working Principle of the Synchronous Generator 496 7.3.1 The Synchronous Generator under No-Load 498 7.3.2 The Synchronous Generator under Load 498 7.4 Working Principle of the Synchronous Motor 501 7.5 Starting of the Synchronous Motor 502 7.5.1 Starting by External Motor 502 7.5.2 Starting by using Damper Winding 503 7.5.3 Starting by Variable Frequency Stator Supply 503 7.6 Armature Reaction in Synchronous Motor 503 7.7 Equivalent Circuit and Phasor Diagram of the Synchronous Machine 506 7.7.1 Phasor Diagram of the Synchronous Generator 508 7.7.2 Phasor Diagram of the Synchronous Motor 510 7.8 Open-Circuit and Short-Circuit Characteristics 514 7.8.1 Open-Circuit Curve 514 7.8.2 Short-Circuit Curve 516 7.8.3 The Unsaturated Synchronous Reactance 517 7.8.4 The Saturated Synchronous Reactance 517 7.8.5 Short-Circuit Ratio 518 7.9 Voltage Regulation 520 7.9.1 Emf or Synchronous Method 521 7.9.2 The Ampere-Turn or mmf Method 522 7.9.3 Zero-Power Factor Method or Potier Triangle Method 526 7.9.3.1 Steps for Drawing Potier Triangles 526 7.9.3.2 Procedure to Obtain Voltage Regulation using the Potier Triangle Method 526 7.10 Efficiency of the Synchronous Machine 529 7.11 Torque and Power Curves 533 7.11.1 Real/Active Output Power of the Synchronous Generator 534 7.11.2 Reactive Output Power of the Synchronous Generator 535 7.11.3 Complex Input Power to the Synchronous Generator 536 7.11.4 Real/Active Input Power to the Synchronous Generator 536 7.11.5 Reactive Input Power to the Synchronous Generator 537 7.12 Maximum Power Output of the Synchronous Generator 537 7.13 Capability Curve of the Synchronous Machine 541 7.14 Salient Pole Machine 545 7.14.1 Phasor Diagram of a Salient Pole Synchronous Generator 547 7.14.2 Power Delivered by a Salient Pole Synchronous Generator 552 7.14.3 Maximum Active and Reactive Power Delivered by a Salient Pole Synchronous Generator 555 7.14.3.1 Active Power 555 7.14.3.2 Reactive Power 555 7.15 Synchronization of an Alternator with a Bus-Bar 558 7.15.1 Process of Synchronization 560 7.16 Operation of a Synchronous Machine Connected to an Infinite Bus-Bar (Constant Vt and f ) 562 7.16.1 Motor Operation of Change in Excitation at Fixed Shaft Power 562 7.16.2 Generator Operation for Change in Output Power at Fixed Excitation 565 7.17 Hunting in the Synchronous Motor 570 7.17.1 Role of the DamperWinding 572 7.18 Parallel Operation of Synchronous Generators 572 7.18.1 The Synchronous Generator Operating in Parallel with the Infinite Bus Bar 574 7.19 Matlab/Simulink Model of a Salient Pole Synchronous Machine 581 7.19.1 Results Motoring Mode 585 7.19.2 Results Generator Mode 585 7.20 Summary 586 Problems 587 Reference 591 8 Single-Phase and Special Machines 593 8.1 Preliminary Remarks 593 8.2 Single-phase Induction Machine 593 8.2.1 Field System in a Single-phase Machine 594 8.3 Equivalent Circuit of Single-phase Machines 597 8.3.1 Equivalent Circuit Analysis 599 8.3.1.1 Approximate Equivalent Circuit 600 8.3.1.2 Thevenin’s Equivalent Circuit 601 8.4 How to Make a Single-phase Induction Motor Self Starting 602 8.5 Testing of an Induction Machine 608 8.5.1 DC Test 609 8.5.2 No-load Test 609 8.5.3 Blocked-Rotor Test 610 8.6 Types of Single-Phase Induction Motors 612 8.6.1 Split-Phase Induction Motor 612 8.6.2 Capacitor-Start Induction Motor 612 8.6.3 Capacitor-Start Capacitor-Run Induction Motor (Two-Value Capacitor Method) 613 8.7 Single-Phase Induction Motor Winding Design 614 8.7.1 Split-Phase Induction Motor 617 8.7.2 Capacitor-Start Motors 618 8.8 Permanent Split-Capacitor (PSC) Motor 621 8.9 Shaded-Pole Induction Motor 622 8.10 Universal Motor 622 8.11 Switched-Reluctance Motor (SRM) 624 8.12 Permanent Magnet Synchronous Machines 624 8.13 Brushless DC Motor 625 8.14 Mathematical Model of the Single-phase Induction Motor 626 8.15 Simulink Model of a Single-Phase Induction Motor 627 8.16 Summary 633 Problems 633 Reference 637 9 Motors for Electric Vehicles and Renewable Energy Systems 639 9.1 Introduction 639 9.2 Components of Electric Vehicles 641 9.2.1 Types of EVs 641 9.2.1.1 Battery-Based EVs 642 9.2.1.2 Hybrid EVs 643 9.2.1.3 Fuel-Cell EVs 646 9.2.2 Significant Components of EVs 649 9.2.2.1 Battery Bank 649 9.2.2.2 DC-DC Converters 661 9.2.2.3 Power Inverter 662 9.2.2.4 Electric Motor 663 9.2.2.5 Transmission System or Gear Box 663 9.2.2.6 Other Components 663 9.3 Challenges and Requirements of Electric Machines for EVs 663 9.3.1 Challenges of Electric Machines for EVs 664 9.3.2 Requirements of Electric Machines for EVs 664 9.4 Commercially Available Electric Machines for EVs 667 9.4.1 DC Motors 667 9.4.2 Induction Motor 667 9.4.3 Permanent Magnet Synchronous Motors (PMSM) 668 9.4.4 Brushless DC Motors 668 9.4.5 Switched Reluctance Motors (SRMs) 669 9.5 Challenges and Requirements of Electric Machines for RES 669 9.6 Commercially Available Electric Machines for RES 671 9.6.1 DC Machine 671 9.6.2 Induction Machines 671 9.6.3 Synchronous Machines 674 9.6.4 Advanced Machines for Renewable Energy 675 9.7 Summary 676 References 677 10 Multiphase (More than Three-Phase) Machines Concepts and Characteristics 679 10.1 Preliminary Remarks 679 10.2 Necessity of Multiphase Machines 679 10.2.1 Evolution of Multiphase Machines 680 10.2.2 Advantages of Multiphase Machines 683 10.2.2.1 Better Space Harmonics Profile 683 10.2.2.2 Better Torque Ripple Profile 684 10.2.2.3 Improved Efficiency 686 10.2.2.4 Fault Tolerant Capability 686 10.2.2.5 Reduced Ratings of Semiconductor Switches and Better Power/Torque Distribution 688 10.2.2.6 Torque Enhancement by Injecting Lower-Order Harmonics into Stator Currents 688 10.2.3 Applications of Multiphase Machines 689 10.3 Working Principle 691 10.3.1 Multiphase Induction Machine 691 10.3.2 Multiphase Synchronous Machine 691 10.4 Stator-Winding Design 692 10.4.1 Three-PhaseWindings 695 10.4.1.1 Single-Layer Full-Pitch Winding 695 10.4.1.2 Single-Layer Short-Pitch Winding 698 10.4.1.3 Double-Layer Full-PitchWinding 699 10.4.1.4 Double-Layer Short-Pitch Winding 699 10.4.1.5 Fractional-Slot Winding 701 10.4.2 Five-PhaseWindings 701 10.4.3 Six-Phase Windings 706 10.4.3.1 Symmetrical Winding of Six-Phase Machine 707 10.4.3.2 Asymmetrical Winding 710 10.4.4 Nine-PhaseWindings 710 10.5 Mathematical Modelling of Multiphase Machines 715 10.5.1 Mathematical Modelling of Multiphase Induction Machines in Original Phase-Variable Domain 715 10.5.2 Transformation Matrix for Multiphase Machines 718 10.5.3 Modelling of Multiphase Induction Machines in Arbitrary Reference Frames 720 10.5.4 Commonly used Reference Frames 722 10.5.5 Modelling of a Multiphase Synchronous Machine 723 10.6 Vector Control Techniques for Multiphase Machines 725 10.6.1 Indirect Field-Oriented Control or Vector-Control Techniques for Multiphase Induction Machines 726 10.6.2 Vector Control for Multiphase Synchronous Machines 730 10.7 Matlab/Simulink Model of Multiphase Machines 731 10.7.1 Dynamic Model of the Nine-Phase Induction Machine 731 10.7.2 Dynamic Model of the Nine-Phase Synchronous Machine 734 10.8 Summary 741 Problems 741 References 742 11 Numerical Simulation of Electrical Machines using the Finite Element Method 745 11.1 Introduction 745 11.2 Methods of Solving EM Analysis 747 11.2.1 Analytical Techniques 749 11.2.2 Numerical Techniques 750 11.2.2.1 Finite Difference Method 752 11.2.2.2 Finite Element Method 753 11.2.2.3 Solution of Laplace Equation Using the Finite Element Method 753 11.3 Formulation of 2-Dimensional and 3-Dimensional Analysis 758 11.3.1 Maxwell Equations 759 11.3.1.1 Gauss Law 759 11.3.1.2 Gauss Law of Magnetism 760 11.3.1.3 Ampere’s Integral Law 761 11.3.1.4 Faraday’s Integral Law 761 11.3.1.5 Differential Form of Maxwell Equations 761 11.3.2 FEM Adaptive Meshing 763 11.3.3 FEM Variation Principle 764 11.4 Analysis and Implementation of FEM Machine Models 765 11.4.1 RMxprt Design to Implement a Maxwell Model of Machine 765 11.4.2 Power Converter Design in Simplorer 776 11.4.3 Integration of Power Converter with a Maxwell Model for Testing Drive 776 11.5 Example Model of Three-Phase IM in Ansys Maxwell 2D 778 11.6 Summary 793 References 793 Index 795

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Book SynopsisTable of ContentsPreface v List of Acronyms and Abbreviations ix Introduction 1 Challenges of Traditional Physical and Cyber Systems 1 Research Trends in Cyber-Physical Systems (CPSs) 3 Stability of CPSs 3 Reliability of CPSs 6 Opportunities for CPS Applications 7 Managing Reliability and Feasibility of CPSs 7 Ensuring Cybersecurity of CPSs 9 Fundamentals of CPSs 13 Models for Exploring CPSs 14 Control-Block-Diagram of CPSs 14 Control Signal in CPSs 14 Degraded Actuator and Sensor 14 Time-Varying Model of CPSs 15 Implementation in TrueTime Simulator 16 Introduction of TrueTime Simulator 16 Architecture of CPSs in TrueTime 17 Evaluation and Verification of CPSs 18 CPS Performance Evaluation 18 CPS Performance Index 18 Reliability Evaluation of CPSs 19 CPS Model Verification 20 CPS Performance Improvement 21 PSO-Based Reliability Enhancement 22 Optimal PID-Automatic Generation Control (AGC) 23 Stability Enhancement of CPSs 29 Integration of Physical and Cyber Models 30 Basics of Wide-Area Power Systems (WAPS) 30 Physical Layer 30 Cyber Layer 31 WAPS Realized in TrueTime 32 An Illustrative WAPS 33 Illustrative Physical Layer 33 Illustrative Cyber Layer 34 Illustrative Integrated System 36 Settings of Stability Analysis 36 Settings of Delay Predictions 37 Settings of Illustrative WAPS 37 Cases for Illustrative WAPS 38 Hidden Markov Model (HMM)-Based Stability Improvement 38 Online Smith Predictor 38 Initialization of Discrete HMM (DHMM) 39 Parameter Estimation of DHMM 41 Delay Prediction via DHMM 43 Smith Predictor Structure 44 Delay Predictions 44 Settings of DHMM 45 Prediction Comparison 46 Performance of Smith Predictor 47 Settings of Smith Predictor 47 Analysis of Case 1 47 Analysis of Case 2 48 Stability Enhancement of Illustrative WAPS 49 Eigenvalue Analysis and Delay Impact 49 Sensitivity Analysis of Network Parameters 49 Optimal AGC 50 Optimal Controller Performance 50 Scenario 1 Analysis 51 Scenario 2 Analysis 51 Scenario 3 Analysis 52 Scenario 4 Analysis 52 Robustness of Optimal AGC 52 Reliability Analysis of CPSs 65 Conceptual Distributed Generation Systems (DGSs) 65 Mathematical Model of Degraded Network 65 Model of Transmission Delay 66 Model of Packet Dropout 67 Scenarios of Degraded Network 68 Modeling and Simulation of DGSs 69 DGS Model 69 Preliminary Model 69 Power Source Model 70 Data Interpolation 71 Reliability Estimation Via Optimal Power Flow (OPF) 71 Data Prediction 71 Monte Carlo Simulation (MCS) of DGSs 73 OPF of DGSs 74 Actual Cost and Reliability Analysis 75 OPF of DGSs Against Unreliable Network 76 Settings of Networked DGSs 76 OPF Under Different Demand Levels 78 OPF Under Entire Period 79 Maintenance of Aging CPSs 87 Data-driven Degradation Model for CPSs 88 Degraded Control System 88 Parameter Estimation via EM Algorithm 89 Load Frequency Control (LFC) Performance Criteria 90 Maintenance Model and Cost Model 91 Performance Based Maintenance (PBM) Model 91 Cost Model 93 Applications to DGSs 94 Output of Aging Generators 94 Impact of Aging on DGSs 94 Settings of Aging DGSs 94 Validations of Generator Performance Indexes 95 Quantitative Aging Impact 96 Applications to Gas Turbine Plant 98 Settings of Networked DGS Sensitivity Analysis of PBM 98 Impact of Degradation on LFC 98 Numerical Sensitivity Analysis 98 Pictorial Sensitivity Analysis 99 Optimal Maintenance Strategy 100 Maintenance Models Comparison 100 Game Theory Based CPS Protection Plan 109 Vulnerability Model for CPSs 110 Multi-state Attack-Defence Game 111 Backgrounds of Game Model for CPSs 111 Mathematical Game Model 112 Attack Consequence and Optimal Defence 113 Damage Cost Model 113 Attack Uncertainty 114 Optimal Defence Plan 115 Applications to DGSs with Uncertain Cyber-Attacks 116 Settings of Game Model 116 Optimal Protection with Constant Resource Allocation 116 Impact Under Constant Case 116 Optimal Constant Resource Allocation Fraction 117 Optimal Protection with Dynamic Resource Allocation 118 Vulnerability Model Under Dynamic Case 119 Optimal Dynamic Resource Allocation Fraction 120 Optimization Results Justification 121 Bayesian Based Cyberteam Deployment 125 Poisson Distribution based Cyber-attacks 125 Impacts of DoS Attack 125 Poisson Arrival Model Verification 126 Average Arrival Attacks 127 Cost of Multi-node Bandit Model 128 Regret Function of Worst Case 128 Upper Bound on Cost 129 Thompson-Hedge Algorithm 130 Hedge Algorithm 130 Details of Thompson-Hedge Algorithm 131 Separation of Target Regret 132 Upper Bound of Λ_1 133 Upper Bound of Λ_2 133 Upper Bound of Regret R^TH 134 Applications to Smart Grids 135 Operation Cost of Smart Grid 135 Numerical Analysis of Cost Sequences 137 Performance of Thompson-Hedge Algorithm 137 Comparison Study Against R.EXP3 137 Sensitivity to the Variation 140 Recent Advances in CPS Modeling, Stability and Reliability 145 Modeling Techniques for CPS Components 145 Inverse Gaussian Process 145 Hitting Time to a Curved Boundary 146 Estimator Error 147 Theoretical Stability Analysis 148 Impacts of Uncertainties 148 Small Gain Theorem based Stability Criteria 149 Robust Stability Criteria 150 Game Model for CPSs 151 References 153 Index 177

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Book SynopsisTable of ContentsList of Contributors xvii 1 Introduction 1Yahya Rahmat-Samii and Erdem Topsakal 2 Ultraflexible Electrotextile Magnetic Resonance Imaging (MRI) Radio-Frequency Coils 11Daisong Zhang and Yahya Rahmat-Samii 2.1 Introduction to MRI and the Basic Antenna Considerations 11 2.2 Motivations, Challenges, and Strategies for MRI RF Coil Design 15 2.2.1 Design Motivations and Challenges for MRI RF Coils 15 2.2.2 Design Strategies and Roadmap of MRI RF Coils 18 2.3 Selection, Fabrication, and Characterization of Electrotextiles for RF Coils 20 2.3.1 Selection and Fabrication of Flexible Material Candidate 20 2.3.2 Characterization of Electrotextiles 22 2.4 Design of Single-Element Flexible RF Coil 26 2.4.1 RF Coil Element Design with a Rigid Material 26 2.4.2 RF Coil Element Design with Electrotextile Cloth 30 2.4.3 RF Coil Element Design with Tunable Circuitry 31 2.5 Design of Flexible RF Coil Array and System Integration with MRI Scanner 31 2.5.1 RF Coil Array Design and Characterization 32 2.5.2 RF Coil Array System Integration with MRI Scanner 33 2.6 Characterization of RF Coil Array 34 2.6.1 Characterization of RF Coil Array System with Phantom 35 2.6.2 Characterization of RF Coil Array System with Cadaver 38 2.7 Conclusion 38 References 38 3 Wearable Sensors for Motion Capture 43Vigyanshu Mishra and Asimina Kiourti 3.1 Introduction 43 3.2 The Promise of Motion Capture 45 3.2.1 Healthcare 45 3.2.2 Sports 47 3.2.3 Human–Machine Interfaces 47 3.2.4 Animation/Movies 48 3.2.5 Biomedical Research 48 3.3 Motion Capture in Contrived Settings 49 3.3.1 Camera-Based Motion Capture Laboratory 49 3.3.2 Electromagnetics-Based Sensors 52 3.3.2.1 RADAR Based 52 3.3.2.2 Wi-Fi Based 55 3.3.2.3 RFID Based 57 3.3.3 Magnetic Motion Capture System 59 3.3.4 Imaging Methods 60 3.3.5 Additional Sensors/Tools 60 3.3.5.1 Goniometers 61 3.3.5.2 Force Plates 62 3.4 Wearable Motion Capture (Noncontrived Settings) 63 3.4.1 Inertial Measurement Units (IMUs) 63 3.4.2 Bending/Deformation Sensors 65 3.4.2.1 Strain Based 65 3.4.2.2 Fiber Optics Based 68 3.4.3 Time-of-Flight (TOF) Sensors 70 3.4.3.1 Acoustic Based 70 3.4.3.2 Radio Based 71 3.4.4 Received Signal Strength-based Sensors 73 3.4.4.1 Antenna Based 73 3.4.4.2 Magnetoinductive Sensors/Electrically Small Loop Antennas 74 3.5 Conclusion 78 References 82 4 Antennas and Wireless Power Transfer for Brain-Implantable Sensors 91Leena Ukkonen, Lauri Sydänheimo, Toni Björninen and Shubin Ma 4.1 Introduction 91 4.2 Implantable Antennas for Wireless Biomedical Devices 92 4.3 Wireless Power Transfer Techniques for Implantable Devices 95 4.3.1 Inductive Power Transfer 95 4.3.2 Ultrasonic Power Transfer 97 4.3.3 Near-Field Capacitive Power Transfer 98 4.3.4 Far-Field Power Transfer 99 4.3.5 Computing the Fundamental Performance Indicators of Near-Field WPT Systems Using Two-Port Network Approach 100 4.4 Human Body Models for Implantable Antenna Development 107 4.4.1 Comparison of Human Head Phantoms with Different Complexities for Intracranial Implantable Antenna Development 110 4.5 Wirelessly Powered Intracranial Pressure Sensing System Integrating Near- and Far-Field Antennas 115 4.5.1 Far-Field Antenna for Data Transmission 116 4.5.2 Antenna for Near-Field Wireless Power Transfer 120 4.6 Far-Field RFID Antennas for Intracranial Wireless Communication 123 4.6.1 Split Ring Resonator-Based Spatially Distributed Implantable Antenna System 123 4.6.2 LC-Tank-Based Miniature Implantable RFID Antenna 127 4.6.3 Antenna Prototype and Wireless Measurement 132 4.7 Conclusion 135 References 136 5 In Vitro and In Vivo Testing of Implantable Antennas 145Ryan B. Green, Mary V. Smith and Erdem Topsakal 5.1 Introduction 145 5.2 Antenna Materials 146 5.2.1 Biocompatibility 146 5.2.2 Miniaturization 149 5.2.3 Biocompatible Conductors and Thin Films 150 5.2.4 Ports and Cables 153 5.3 Bench Top Testing 154 5.3.1 Ex Vivo Tissues 154 5.3.2 In Vitro Gels 154 5.3.2.1 Mixture and Characterization of Skin-Mimicking Material 156 5.3.2.2 Mixture and Characterization of Adipose-Mimicking Material 164 5.3.2.3 Mixture and Characterization of Muscle-Mimicking Material 166 5.4 In Vivo Testing 171 5.4.1 Different Animal Models for Different Frequency Bands 174 5.4.2 Dielectric Mismatch 177 5.4.3 Practical Testing Concerns 181 5.5 Conclusion 182 Acknowledgment 183 References 183 6 Wireless Localization for a Capsule Endoscopy: Techniques and Solutions 191Yongxin Guo and Guoliang Shao 6.1 Introduction 191 6.1.1 Visual-based Localization Method 194 6.1.2 Radio-frequency Localization 196 6.1.3 Microwave Imaging 198 6.1.4 Magnetic Localization 199 6.2 Static Magnetic Localization 201 6.2.1 Model of the Target Magnet 202 6.2.2 Noise Cancellation and Sensor Calibration 205 6.2.3 Solving the Inverse Problem 207 6.2.4 Sensors Distribution 212 6.2.5 Conclusion of the Static Magnetic Localization 215 6.3 Modulated Magnetic Localization 215 6.3.1 Static Field Modulation 215 6.3.2 Inductive-based Magnetic Localization 216 6.4 Conclusion 225 References 227 7 Study on Channel Characteristics and Performance of Liver-Implanted Wireless Communications 235Pongphan Leelatien, Koichi Ito and Kazuyuki Saito 7.1 Introduction 235 7.2 Study of In-Body Communications at Liver Area Using Simplified Multilayer Phantoms 238 7.2.1 UWB Antenna 239 7.2.2 Measurement Setup 239 7.2.3 Simulation Setup 239 7.2.4 Experimental and Numerical Results 243 7.2.4.1 S11 and S22 Results 243 7.2.4.2 S21 Results 244 7.3 Numerical Study of Liver-Implanted Channel Characteristics Using Digital Human Models 244 7.3.1 Simulation Setup 245 7.3.2 Return Loss Results 246 7.3.3 S21 Results 248 7.3.4 Path Loss Results 250 7.4 The Influence of Antenna Misalignment 252 7.4.1 Simulation Setup 252 7.4.2 Study Results and Analysis 252 7.5 Channel Characteristics for the In- to Off-Body Scenario 256 7.5.1 Simulation Setup 256 7.5.2 Return Loss Results 257 7.5.3 Path Loss Results for the In- to Off-Body Scenario 258 7.6 System Performance Evaluation 260 7.6.1 Link Budget Evaluation and Analysis 260 7.6.1.1 In- to On-Body Scenario 262 7.6.1.2 In- to Off-Body Scenario 263 7.7 Electromagnetic Compatibility Evaluations 263 7.7.1 Analysis 265 7.7.2 SAR Results 265 7.8 Conclusions 268 References 270 8 High-Efficiency Multicoil Wireless Power and Data Transfer for Biomedical Implants and Neuroprosthetics 277Manjunath Machnoor and Gianluca Lazzi 8.1 Introduction 277 8.2 Multicoil System to Achieve Efficient Power Transfer 279 8.2.1 Two-Coil WPT Systems 280 8.2.2 Conventional Three-Coil WPT System 284 8.2.3 Performance of the Two- and Three-Coil Systems as a Function of RX Coil Size 286 8.2.4 Description of the Proposed Three-Coil System 287 8.2.5 Efficient Use of Implanted Wire of the Coil in a Small RX Three-Coil System 292 8.2.5.1 Circuit Technique Description 292 8.2.5.2 Testing the Technique: Comparison 1 292 8.2.6 Reducing Power Dissipation in the Implanted RX 293 8.2.6.1 Circuit Technique Description 293 8.2.6.2 Testing the Technique: Comparison 2 295 8.2.7 Design Procedure and the Advantages of the Proposed Three-Coil System Over the Conventional Three-Coil System Design 298 8.2.7.1 Design Procedure 298 8.2.7.2 Tolerance to Load Changes 299 8.2.7.3 Advantage 2: Reducing Currents in the Secondary Coil 301 8.2.7.4 K12 and Cm for Optimization of System Performance: Layout Design Advantages 302 8.2.7.5 Effects of Tissue and Tissue Parameters on the Power Delivery 303 8.2.8 Experiments: Measurements and Results 304 8.3 Justifying the Advantages of Using Multicoil WPT Systems for Data Transfer 306 8.4 Conclusion 312 References 313 9 Wireless Drug Delivery Devices 319Yang Hao, Ahsan Noor Khan, Alexey Ermakov and Gleb Sukhorukov 9.1 Introduction 319 9.2 Active and Passive Drug Delivery Devices 320 9.3 Capsule-Mediated Active Drug Delivery Process 320 9.4 Transdermal and Implantable Devices 322 9.5 Micro- and Nanoscale Devices 322 9.6 Packaging and Integration of Components 323 9.7 Materials for Drug Delivery Devices 324 9.8 Organ-Specific Drug Delivery Devices 324 9.9 Wireless Communication for Drug Delivery Devices 325 9.9.1 Microchips-Mediated Drug Delivery Devices 326 9.9.2 Micropumps and Microvalves-Mediated Drug Delivery Devices 328 9.9.3 Microrobots-Mediated Drug Delivery 331 9.9.4 Material-Mediated Drug Delivery 332 9.10 Carrier Types for Drug Delivery 335 References 338 10 Minimally Invasive Microwave Ablation Antennas 345Hung Luyen, Yahya Mohtashami, James F. Sawicki, Susan C. Hagness and Nader Behdad 10.1 Introduction 345 10.1.1 Overview of Microwave Ablation Therapy 345 10.1.2 Historical Development and Current Landscape of Research on MWA Antennas 347 10.1.3 Impact of Frequency on MWA Performance 352 10.1.4 Focus of this Chapter 353 10.2 Toward Length Reduction for Ablation Antennas: Demonstration of Higher Frequency Microwave Ablation 354 10.2.1 Electromagnetic Evaluation of Microwave Ablation Antennas Operating in the 1.9–18-GHz Range 354 10.2.2 Performance of Higher Frequency Microwave Ablation in the Presence of Perfusion 355 10.3 Reduced-Diameter, Balun-Equipped Microwave Ablation Antenna Designs 359 10.3.1 Antennas with Conventional Coaxial Baluns Implemented on Air-Filled Coax Sections 361 10.3.2 Coax-Fed Antenna with a Tapered Slot Balun 364 10.4 Balun-Free Microwave Ablation Antenna Designs 367 10.4.1 High-Input Impedance Helical Monopole with an Integrated Impedance-Matching Section 368 10.4.2 Low-Input Impedance Helical Dipole Design 373 10.5 Toward More Flexibility and Customization in Microwave Ablation Treatment 377 10.5.1 Ex Vivo Performance of a Flexible Microwave Ablation Antenna 377 10.5.2 Hybrid Slot/Monopole Antenna with Directional Heating Patterns 380 10.5.3 Non-Coaxial-Based Microwave Ablation Antennas with Symmetric and Asymmetric Heating Patterns 383 10.6 Conclusions 387 References 389 11 Inkjet-/3D-/4D-Printed Nanotechnology-Enabled Radar, Sensing, and RFID Modules for Internet of Things, “Smart Skin,” and “Zero Power” Medical Applications 399Manos M. Tentzeris, Aline Eid, Tong-Hong Lin, Jimmy G.D. Hester, Yepu Cui, Ajibayo Adeyeye, Bijan Tehrani and Syed A. Nauroze 11.1 Introduction 399 11.2 Batteryless “Green” Powering Schemes for Perpetual Wearables 400 11.2.1 Wearable Rectennas Compatible with Legacy Wireless Networks 401 11.2.2 New Opportunities for Power Harvesting from 5G Cellular Networks 402 11.2.2.1 28-GHz Rotman Lens-Based Energy-Harvesting System 402 11.2.2.2 Integration of W-Band Zero-Bias Diode for Harvesting Applications 404 11.3 Additive Manufacturing Technologies for Low-Cost, Compact, and Wearable System 406 11.3.1 Wireless System Packaging for On-Body Devices 406 11.3.2 Energy-Autonomous System-on-Package Designs 407 11.4 Energy-Autonomous Communications for On-Body Sensing Networks 409 11.4.1 Energy-Autonomous Long-Range Wearable Sensor Networks 409 11.4.2 Radar and Backscatter Communications 414 11.4.2.1 FMCW Radar-Enabled Localizable Millimeter-Wave RFID 415 11.4.3 Flexible and Deployable 4D Origami-Inspired “Smart Walls” for EMI Shielding and Communication Applications 416 11.5 Low-Power Sensors for Wearable Wireless Sensing Systems 422 11.5.1 Carbon-Nanomaterials-Based Fully Inkjet-Printed Gas Sensors 422 11.5.2 Energy-Autonomous Micropump System for Wearable and IoT Microfluidic Sensing Devices 425 11.5.3 Fully Inkjet-Printed Encodable Flexible Microfluidic Chipless RFID Sensor 428 11.6 Conclusion 431 References 431 12 High-Density Electronic Integration for Wearable Sensing 435Shubhendu Bhardwaj, Raj Pulugurtha and John L. Volakis 12.1 Introduction 435 12.2 Brief Comparison of Flexible Conductor Technologies 435 12.3 Review and History of E-Fiber-Based RF Technology 437 12.4 Fabrication of Conductive Flexile E-Fiber Surfaces and Loss Performance 438 12.5 Antennas Using Embroidery-Based Conductive Surfaces 441 12.5.1 Patch Antenna for Wireless Power Transfer and Harvesting 442 12.5.2 Body-Worn Antenna for Wireless Communication 443 12.6 Circuits and Systems Using Embroidery-Based Conductive Surfaces 445 12.6.1 Far-Field Radio-Frequency Power Collection System on Clothing 445 12.6.2 Near-Zone Power Collection Using Fabric-Integrated Antennas 448 12.7 Voltage-Controlled Oscillator for Wound-Sensing Applications 449 12.8 High-Density Integration 451 12.8.1 Interconnect Features on Laminate Substrates 451 12.8.2 Interconnects on Flex Substrates 454 12.8.3 Device Assembly 455 12.8.4 3D Packaging 457 12.8.5 Applications of High-Density Packaging in RF and Sensing 459 12.8.6 High-Density RF Flex Packaging 461 12.8.7 Hybrid Flex Sensor-Processing-Communication Systems 462 References 462 13 Coupling-Independent Sensing Systems with Fully Passive Sensors 469Siavash Kananian, George Alexopoulos and Ada Poon 13.1 Introduction 469 13.2 Forced vs. Self-Oscillating Near-Field Readout 475 13.3 Readout Techniques 477 13.3.1 Forced Oscillation Techniques with Nonresonant Primary 477 13.3.2 Forced Oscillation Techniques with Resonant Primary 486 13.3.3 Self-Oscillating Techniques 498 13.4 Comparison of the State of the Art 507 13.5 Conclusion 516 References 517 14 Wireless and Wearable Biomarker Analysis 523Shuyu Lin, Bo Wang, Ryan Shih and Sam Emaminejad 14.1 Introduction 523 14.2 Sweat-Based Biomarkers 524 14.2.1 Metabolites 524 14.2.2 Electrolytes 525 14.2.3 Steroids 525 14.2.4 Proteins 526 14.2.5 Xenobiotics 526 14.3 Wearable Chemical Sensing Interfaces 527 14.3.1 Electroenzymatic Sensors 528 14.3.2 Ion-selective Sensing Interfaces 530 14.3.3 Bioaffinity-based Sensors 531 14.3.4 Synthetic Receptor-based Chemical Sensors 532 14.3.5 Recognition Element-free Sensors 533 14.4 Biofluid Accessibility 533 14.5 Microfluidic Interfaces 534 14.5.1 Types of Microfluidic Interfaces 535 14.5.2 Biofluid Manipulation in Microfluidic Interfaces 536 14.6 Electronic and Wireless Integration 538 References 539 Appendix A Antennas and Sensors for Medical Applications: A Representative Literature Review 547Lingnan Song and Yahya Rahmat-Samii Index 585

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Book SynopsisA straightforward demystification of electronics and the Internet of Things A Geek Girl''s Guide to Electronics and the Internet of Things breaks down and simplifies electronics and the Internet of Things for the layperson. Written by a leading technical school instructor with a talent for bringing complex topics to everyday people, this book provides concrete examples and practical advice for anyone interested in building, repairing, or studying electronics and functional Internet of Things (IoT) devices. A Geek Girl''s Guide to Electronics and the Internet of Things explores a wide range of topics including, among others: Ohm''s and Watt''s Law Series and Parallel Circuits Diodes, transistors, capacitors and relays Motors and Pulse with Modulation Using light to control electricity Photovoltaic Cells and Transducers Enhancing circuits with Arduino Connecting circuits to nTable of ContentsIntroduction xxiii Part I IoT and Electricity Basics 1 Chapter 1 IoT and Electronics 3 IoT in a Nutshell 4 Parts of an IoT System 4 Devices 4 Sensors 5 Circuits, Software, and Microprocessors 6 Communication 7 Levels 7 Protocols and Standards 7 Data Analytics and Management 8 The User Experience 8 Challenges in Implementing IoT 9 IoT into the Future 9 Chapter 2 Electricity: Its Good and Bad Behavior 11 Try This: Creating Some Static 11 Levitate a Styrofoam Plate 12 Bend Water 12 Creating Light with Static 12 Magically Move a Styrofoam Ball 13 Electricity at an Atomic Level 14 Conductors and Insulators 15 Characteristics of Electricity 17 Current 18 Voltage 18 Resistance 19 Induction and Conduction 19 Try This: Creating a Simple Breadboard Circuit 21 Light-Emitting Diodes 28 Jumper Wires 28 Building the Circuit 29 The Basic Circuit 31 Ohm’s Law 31 Resistor Values and Voltage Dividers 32 Opens and Shorts 35 Circuit Protection Devices 36 Fuses 36 Circuit Breakers 37 Bigger is Not Better 38 Chapter 3 Symbols and Diagrams 39 Types of Diagrams 39 Schematic Symbols 41 So Many Switches! 43 Drawing Your Circuit 48 Try This: Adding a Switch and Creating a Schematic 48 Chapter 4 Introduction to the Arduino Uno 53 What is Arduino? 53 The Arduino Board 54 Analog vs. Digital 60 The Arduino IDE 62 Try This: Creating a Simple Arduino-Controlled Circuit 65 What Went Wrong? 69 What Does the Code Mean? 69 Setup 70 Void 71 Try This: Changing Pins 71 Try This: Creating Arduino Running Lights 72 Try This: Adding a Switch to Your Circuit 74 Try This: Using the Serial Monitor 78 Chapter 5 Dim the Lights 83 Using a Multimeter 84 Try This: Repurposing a Power Supply 86 Measuring Voltage, Current, and Resistance 88 Measuring Voltage 89 Measuring Current 89 Measuring Resistance 90 Continuity 90 Try This: Dimming the Lights 91 Try This: Measuring Circuit Values 93 Using Arduino to Measure Electricity 95 Try This: Using an Arduino Voltmeter 95 Try This: Using an Arduino Ohmmeter 100 Try This: Using an Arduino Ammeter 102 Try This: Using an Arduino Continuity Tester 107 Try This: Building a Dimmable Arduino Camp Light 109 Soldering, Perfboards, and Shrink Tubing 115 Soldering 115 Perfboards 117 Shrink Tubing 118 Chapter 6 Feel the Power 121 Watt’s Law and the Power Wheel 121 Datasheets 122 The Power Wheel 123 Watts and Horsepower 123 Horsepower 124 Efficiency 124 Battery Power 124 The Other Resistor Value 125 Wattmeters 126 Wattmeter 126 Power Distribution 127 Try This: Using an Arduino Wattmeter 128 Setting Up the LCD Screen 129 Component Connections 130 The Test Sketch 132 Troubleshooting 132 Building the Wattmeter 133 Building the Wattmeter 133 Building the Test Circuit 134 Configuring the LCD 135 Programming the Meter 138 Chapter 7 Series and Parallel Circuits 143 Series, Parallel, and Complex Circuits 143 Try This: Testing Series and Parallel Configurations 144 Calculating Values in Series and in Parallel 147 Current 147 Voltage 148 Resistance 149 Power 149 Resistance of a Conductor 150 Sources in Series and Parallel 152 Sources in Series 152 Sources in Parallel 152 Aiding and Opposing Sources 153 Try This: Calculating Circuit Values 155 Calculating the Series Circuit 155 What Went Wrong 156 Calculating the Parallel Circuit 156 What Size Resistor is Needed? 156 Calculating the Complex Circuit 157 Part II Using Common Components 161 Chapter 8 Diodes: The One-Way Street Sign 163 Try This: Creating a Simple Polarity Tester 163 Determining Polarity Tester Maximum Voltage 165 Determining Resistor Needs 166 Typical LED Voltages 167 Putting It on a Perfbord 167 LED Features 168 The Inner Workings of Diodes 169 Determining Anode and Cathode 171 Types of Diodes 172 Diode Uses 172 Try This: Using a Seven-Segment LED 175 Seven-Segment LED 176 Bar LED 181 Chapter 9 Transistors 187 Try This: Using a Transistor as an Amplifier 187 The Purpose of Transistors 192 Types of Transistors 192 Distinguishing Transistor Types 193 Determining Transistor Connections 193 Bipolar Junction Transistors 193 Field Effect Transistors 194 Try This: Using a Transistor as a Switch 196 Verifying the Data 196 Building the Circuit 198 Troubleshooting 200 Chapter 10 Capacitors 201 A Quick Look at Capacitors 201 Try This: Creating a Time Delay Circuit 205 Capacitor Uses 209 Try This: Creating an Astable Multivibrator 210 Try This: Using Capacitors in Series and Parallel 213 Capacitors in Parallel 214 Capacitors in Series 215 Chapter 11 The Magic of Magnetism 217 The Electricity/Magnetism Relationship 218 Magnetism 218 Magnetism’s Relationship with Electricity 220 Try This: Building an Electromagnet 221 Magnetism in Circuits 223 Motors and Generators 224 Inductors 225 Doorbells 227 Relays 229 Parts of a Relay 230 Try This: Building a Relay Oscillator 231 Connecting the Coil 231 Connecting the Controlled Circuit 233 Try This: Setting Up an Emergency Lighting System 234 Connecting the Mains Circuit 236 Connecting the Backup Circuit 237 Chapter is Electricity’s Changing Forms 239 Try This: Creating a Water Alarm 239 Common Transducers 243 Speakers and Microphones 243 Light 245 Light-Controlled Devices 245 Light Output Devices 247 Laser Light 250 Other Transducers 251 Try This: Creating a Night-Light Circuit 252 Try This: Creating an Arduino Laser Security System 255 Building the Circuit 255 How the Voltage Divider Works 260 Other Considerations 262 Chapter 13 Integrated Circuits and Digital Logic 263 Integrated Circuits 263 Try This: Creating an Astable Multivibrator 265 Determining Circuit Timing 266 Examining the IC 267 Building the Circuit 268 Operational Amplifiers 272 Digital Logic 272 Logic Chip Construction 273 The Binary Number System 274 Logic Gates 275 Try This: Exploring AND and OR Gates 277 The AND Gate 278 The OR Gate 280 Logic Probes and Oscilloscopes 281 Part III More Please 285 Chapter 14 Pulse Width Modulation 287 Pulse Width Modulation Explained 287 Try This: Using a PWM LED Dimmer 289 PWM vs. Potentiometer 290 Building the Circuit 291 Observing the Changing Duty Cycle 295 Try This: Using a PWM Motor Control 295 Try This: Trying PWM and an Arduino 299 Chapter 15 Sources of Electricity 307 Chemical Reactions 307 Simple Experiment: Making a Voltaic Cell 308 Types of Batteries 309 Try This: Making a Thermocouple 311 Light 312 Try This: Displaying PV Output on an Arduino 315 Friction 323 Magnetism 324 Pressure 326 Wrapping It Up 326 Chapter 16 Transformers and Power Distribution 327 What is a Transformer? 327 Phase Relationships 330 Power and Turns Ratio 331 Transformer Losses 332 Taps, Autotransformers, and Variacs 334 Try This: Verifying Transformer Output 335 Alternating Current Values 342 Power Distribution Using Transformers 343 Chapter 17 Inverters and Rectifiers 345 Inverters vs. Rectifiers and Their Uses 345 Inverters and PV Systems 346 Other Inverter Uses 347 Rectifier Uses 348 Construction of Inverters 349 Try This: Filtering a Circuit 350 Setting Up the Circuit 351 Filtering the Circuit 353 Construction of Rectifiers 355 Single-Phase vs. Three-Phase Power 357 Try This: Building a Small Variable Power Supply 357 Chapter 18 Radio Waves and Tuned Circuits 363 Radio Waves 363 Try This: Building a Radio Receiver 364 Making Waves 369 Transmitting Radio Waves 369 Receiving Radio Waves 370 AM vs. FM 371 Try This: Building an Arduino FM Radio 371 The Shield 372 The Libraries 373 Verifying the Radio Works 375 Adding Station Tuning 377 Tuned Circuits 381 Part IV Putting the I in IoT 385 Chapter 19 Connecting Your Circuits to the Cloud 387 The Arduino IoT Cloud 387 Try This: Setting Up Your Device 389 Try This: Using Things, Properties, and Widgets 391 Chapter 20 Just for Fun 405 Electronic Fabrics and Wearables 405 Try This: Lighting Up a Teddy Bear 408 Paper Circuits 413 Try This: Creating a Conductive Paint Circuit 414 Try This: Creating a Copper Tape Circuit 416 Try This: Building Squishy Circuits 418 Chapter 21 What’s Next? 423 The World is Your Oyster 423 Recommended Reading and Resources 424 Words of Encouragement 425 Index 427

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Book SynopsisAdvances in Hyperspectral Image Processing Techniques Authoritative and comprehensive resource covering recent hyperspectral imaging techniques from theory to applications Advances in Hyperspectral Image Processing Techniques is derived from recent developments of hyperspectral imaging (HSI) techniques along with new applications in the field, covering many new ideas that have been explored and have led to various new directions in the past few years. The work gathers an array of disparate research into one resource and explores its numerous applications across a wide variety of disciplinary areas. In particular, it includes an introductory chapter on fundamentals of HSI and a chapter on extensive use of HSI techniques in satellite on-orbit and on-board processing to aid readers involved in these specific fields. The book's content is based on the expertise of invited scholars and is categorized into six parts. Part I provides general theory. Part II presents various Band Selection tecTable of ContentsEDITOR BIOGRAPHY vii LIST OF CONTRIBUTORS viii PREFACE x PART I GENERAL THEORY 1 1 Introduction: Two Fundamental Principles Behind Hyperspectral Imaging 3Chein-I Chang 2 Overview of Hyperspectral Imaging Remote Sensing from Satellites 41Shen-En Qian 3 Efficient Hardware Implementation for Hyperspectral Anomaly and Target Detection 67Jie Lei, Weiying Xie, Jiaojiao Li, Keyan Wang, Kai Liu, and Yunsong Li PART II BAND SELECTION FOR HYPERSPECTRAL IMAGING 107 4 Constrained Band Selection for Hyperspectral Imaging 109Chein-I Chang 5 Band Subset Selection for Hyperspectral Imaging 147Chein-I Chang 6 Progressive Band Selection Processing for Hyperspectral Image Classification 179Chunyan Yu, Meiping Song, and Chein-I Chang PART III COMPRESSIVE SENSING FOR HYPERSPECTRAL IMAGING 205 7 Restricted Entropy and Spectrum Properties for Hyperspectral Imaging 207Chein-I Chang and Bernard Lampe 8 Endmember Finding in Compressively Sensed Band Domain 228Chein-I Chang and Adam Bekit 9 Hyperspectral Image Classification in Compressively Sensed Band Domain 252Charles J. Della-Porta and Chein-I Chang PART IV FUSION FOR HYPERSPECTRAL IMAGING 279 10 Hyperspectral and LiDAR Data Fusion 281Qian Du, Wei Li, and Chiru Ge 11 Hyperspectral Data Fusion Using Multidimensional Information 293Lifu Zhang, Xia Zhang, Mingyuan Peng, Xuejian Sun, and Xiaoyang Zhao 12 Fusion of Band Selection Methods for Hyperspectral Imaging 341Yulei Wang, Lin Wang, and Chein-I Chang PART V HYPERSPECTRAL DATA UNMIXING 363 13 Model-Inspired Deep Neural Networks for Hyperspectral Unmixing 365Yuntao Qian, Fengchao Xiong, Minchao Ye, and Jun Zhou 14 Analytical Fully Constrained Least Squares Linear Spectral Mixture Analysis 404Chein-I Chang and Hsiao-Chi Li 15 Swarm Intelligence Optimization-Based Spectral Unmixing 422Lianru Gao, Xu Sun, Zhu Han, Lina Zhuang, Wenfei Luo, and Bing Zhang 16 Spectral-Spatial Robust Nonnegative Matrix Factorization for Hyperspectral Unmixing 453Risheng Huang, Xiaorun Li, and Liaoying Zhao PART VI HYPERSPECTRAL IMAGE CLASSIFICATION 483 17 Sparse Representation-Based Hyperspectral Image Classification 485Haoyang Yu, Jun Li, Wei Li, and Bing Zhang 18 Collaborative Classification Based on Hyperspectral Images 506Junping Zhang, Xiaochen Lu, and Tong Li 19 Class Feature-Weighted Hyperspectral Image Classification 543Shengwei Zhong, Jiaojiao Li, Xiaodi Shang, Shuhan Chen, and Chein-I Chang 20 Target Detection Approaches to Hyperspectral Image Classification 565Chein-I Chang, Bai Xue, and Chunyan Yu INDEX 586

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Book SynopsisA guide to the physical and mathematical-statistical approaches to personal and mobile wireless communication networks Wireless Networks Technologies offers an authoritative account of several current and modern wireless networks and the corresponding novel technologies and techniques. The text explores the main aspects of the physical layer of the technology. The authors?noted experts on the topic?examine the well-known networks (from 2-G to 3-G) in a historical perspective. They also illuminate the physical layer of networks while presenting polarization diversity analysis and positioning of any subscriber located in areas of service both for land-to-land and land-to-atmosphere communication links. The book includes clear descriptions of planning techniques for different integrated femto/pico/micro/macrocell deployments. The authors also examine new technologies of time and frequency dispersy and multiple-input and multiple-output (MIMO) modern network design iTable of ContentsAcknowledgements xi Preface xiii Acronyms xix Part I Objective 1 1 Overview of Wireless Networks – From 2G to 4G 3 References 6 2 Terrestrial Wireless Networks Based on Standard 2G and 3G Technologies 9 2.1 Bluetooth-WPAN Networks 9 2.2 Wi-Fi–WLAN Networks 11 2.2.1 Integrated WLAN and WPAN Networks 13 2.2.2 Enhancement of the WLAN Technology 14 2.3 WiMAX Networks and 802.16 Technologies 15 2.3.1 Integrated Wi-Fi–WiMAX Networks 17 2.4 LTE Current Technologies 20 References 24 Part II Physical Layer of Wireless Networks Beyond 4G 33 3 Link Budget Design in Terrestrial Communication Networks 35 3.1 Total Path Loss and Link Budget – Physical Layer of Any Network 35 3.1.1 White Noise 36 3.1.2 Slow Fading 36 3.1.3 Fast Fading 37 3.1.4 Antenna Gain 38 3.1.5 Average Attenuation 38 3.1.5.1 Line of sight 38 3.1.5.2 Non-line-of-sight 39 3.2 The Terrain Propagating Models for Total Path Loss Prediction 40 3.2.1 Hata–Okumura Model 40 3.2.2 Bertoni Multidiffraction Model 42 3.2.3 Walfisch—Ikegami Model (COST 231 Standard) Based on Analytical Bertoni Model 43 3.2.4 Stochastic multiparametric model 44 3.2.4.1 Parameters of the model 44 3.2.4.2 Effect of buildings’ overlap profile 45 3.2.4.3 Signal intensity distribution 46 3.3 Validation of Most Suitable Models via the Recent Experiments 47 3.4 Link Budget Design in Land–Atmosphere and Atmosphere–Land Communication Networks 50 3.4.1 Content and Main Parameters of the Troposphere 51 3.4.1.1 The content 51 3.4.1.2 Main parameters of troposphere 52 3.4.2 Effects of Tropospheric Features on Signal Propagation 54 3.4.2.1 Main features occurring in the troposphere 54 3.4.2.2 Molecular–Gaseous absorption 55 3.4.2.3 Effects of rain 57 3.4.2.4 Effects of clouds 60 3.4.2.5 Effects of turbulence 62 3.5 Link Budget Design 67 3.5.1 Path Loss in Free Space 67 3.5.2 Link Budget Design 67 References 70 4 Polarization Diversity Analysis for Networks Beyond 4G 73 4.1 Depolarization Phenomena in Terrain Channels 73 4.2 Model by Stocks Parameters 74 4.3 The Multiparametric Stochastic Model Application for Polarization Parameters Prediction 77 4.4 Numerical Analysis of Probability Functions for Parameters of the Spatial Polarization Ellipse 81 4.4.1 Mixed-residential Areas 81 4.4.2 Suburban and Urban Areas 83 4.5 Analysis of Polarization Ellipse Energetic Parameters 85 4.5.1 The Ratio Δ vs. the BS Height 85 4.5.2 The Δ Ratio vs. the Distance Between BS and MS Antennas 89 4.6 Analysis of the Loss Characteristics 89 4.6.1 Horizontal Component of the Total Elliptically Polarized Field 91 4.6.2 Vertical Component of the Total Field 91 4.7 Path Loss Factor Due to Depolarization Phenomena 92 4.8 Conclusions 95 References 97 5 Theoretical Framework for Positioning of Any Subscriber in Land–Land and Atmosphere–Land Multiuser Links 99 5.1 Signal Power Distribution in the Space, AOA, TOA, and Frequency Domains for Prediction of Operative Parameters of Sectorial and Multibeam Antennas 101 5.1.1 Signal Intensity Distribution in Space Domain. According to 3-D Stochastic Approach 101 5.1.2 Signal Energy Distribution in Angle-of-Arrival (AOA) and Time-of-Arrival (AOA) Domains 102 5.1.3 Signal Power Spectrum in the Frequency and Doppler-Shift (DS) Domains 106 5.2 Localization of Any Subscriber in Land Built-Up Areas 109 5.2.1 3-D Stochastic Model for Different Scenarios of Buildings’ Layout 109 5.2.2 Analysis of the Accuracy of MS Localization in Predefined Urban Scenarios 113 5.2.2.1 Example 1: The statistical model vs. ray-tracing simulation according to the topographic map 113 5.2.2.2 Example 2: MS and BS antennas are below the rooftop level 113 5.2.2.3 Example 3: MS antenna is below and BS antenna is above the rooftop level 115 5.2.2.4 Example 4: Multiple MS locations 116 5.3 Positioning of Any Subscriber in Multiuser Land–Atmosphere Communication Links 122 5.3.1 Signal Distribution in the Time-Delay Domain 122 5.3.2 Signal Distribution in the Doppler-Shift Domain 124 References 126 Part III Advanced Integrated-Cell Technologies for Modern 4G and 5G Networks 129 6 Femto/Pico/Micro/Macrocell Network Deployments for Fourth and Fifth Generations 131 6.1 Channel Capacity Models in Integrated Femtocell–Microcell/Macrocell Networks 133 6.1.1 Shared Spectrum Assignment (SSA) with Closed Subscriber Group (CSG) 134 6.1.2 Shared Spectrum Assignment (SSA) with (OSG) 134 6.1.3 Dedicated Spectrum Assignment (DSA) with Closed Subscriber Group (CSG) 135 6.1.4 Dedicated spectrum assignment (DSA) with open subscriber group (OSG) 135 6.2 Analysis of Femto/Pico/Micro/Macrocell Networks Based on Propagation Phenomena 136 6.2.1 Propagation Aspects in Integrated Indoor and Outdoor Communication Links 136 6.2.1.1 Outdoor propagation model 137 6.2.1.2 Indoor propagation model 139 6.2.2 Experimental Verification of the Total Path Loss in Femtocell–Picocell Areas 143 6.3 Different Integrated Femto/Pico/Micro/Macrocell Network Deployments 145 6.3.1 Femtocells Integrated into Microcell Network Pattern 145 6.3.2 Femto/Pico/Microcell Configuration Deployment 149 6.3.2.1 Results of the numerical computations 153 References 157 Part IV Mega-Cell Satellite Networks–Current and Advanced 161 7 Advanced Multicarrier Diversity in Networks Beyond 4G 163 7.1 Advanced Multicarrier-diversity Techniques 163 7.2 Advanced Frequency Multicarrier-diversity Techniques 165 7.3 Advanced OFDM and OFDMA Technologies 167 7.3.1 Orthogonal Frequency-Division Multiplexing 168 7.3.2 Orthogonal Frequency-Division Multiple Access 173 7.4 Advanced Time Multicarrier-diversity Techniques 175 References 178 8 MIMO Modern Networks Design in Space and Time Domains 181 8.1 Main Principles of MIMO 181 8.2 Modeling of MIMO Channel Capacity 184 8.3 Fading Correlation in Space–Time Doman in Urban Environment with Dense Building Layout 187 8.4 Correlation Coefficient Analysis in Urban Scene 188 8.5 MIMO Channel Capacity Estimation 189 8.6 Analysis of MIMO Channel Capacity in Predefined Urban Scenario 190 References 192 9 MIMO Network Based on Adaptive Multibeam Antennas Integrated with Modern LTE Releases 197 9.1 Problems in LTE Releases Deployment 197 9.2 Multibeam MIMO with Adaptive Antennas Against Fading Phenomena in LTE Networks 199 9.3 Analysis of the Multibeam Effect for a Specific Environment 201 9.4 Summary 206 References 208 10 Satellite Communication Networks 211 10.1 Overview of Satellite Types 211 10.2 Signal Types in LSC Links 212 10.3 Overview of Experimentally Approbated Models 214 10.3.1 Lutz Pure Statistical Model 215 10.3.2 Physical–Statistical Approach 216 10.3.2.1 Saunders–Evans physical–statistical model 217 10.3.2.2 Multiparametric stochastic model 219 10.4 Comparison Between Saunders–Evans and the Stochastic MultiparametricModel 223 10.5 Land–Satellite Networks – Current and Advanced Beyond 4G 225 10.5.1 Current Land–Satellite Networks 225 10.5.1.1 Inmarsat 225 10.5.1.2 North American MSAT system 226 10.5.1.3 Australian mobile satellite system (OPTUS) 227 10.5.1.4 Japanese n-star mobile communications system 227 10.5.1.5 Other mobile–satellite systems 228 10.5.2 Advanced Satellite Networks Performance 229 10.5.2.1 Iridium 229 10.5.2.2 Globalstar 231 10.5.2.3 ICO-global 233 10.5.2.4 European inmarsat BGAN 234 10.5.2.5 Advanced GSM–satellite network 235 10.5.3 Operational Parameters Prediction in Advanced Land–Satellite Networks 235 10.6 Summary 238 References 239 Index 241

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Book SynopsisPresents an overview of CubeSat antennas designed at the Jet Propulsion Laboratory (JPL) CubeSatsnanosatellites built to standard dimensions of 10cm x 10 cm x cmare making space-based Earth science observation and interplanetary space science affordable, accessible, and rapidly deployable for institutions such as universities and smaller space agencies around the world. CubeSat Antenna Design is an up-to-date overview of CubeSat antennas designed at NASA's Jet Propulsion Laboratory (JPL), covering the systems engineering knowledge required to design these antennas from a radio frequency and mechanical perspective. This authoritative volume features contributions by leading experts in the field, providing insights on mission-critical design requirements for state-of-the-art CubeSat antennas and discussing their development, capabilities, and applications. The text begins with a brief introduction to CubeSats, followed by a detailed survey of low-gain, medium-gain, and high-gain antennas. Subsequent chapters cover topics including the telecommunication subsystem of Mars Cube One (MarCO), the enabling technology of Radar in a CubeSat (RainCube), the development of a one-meter mesh reflector for telecommunication at X- and Ka-band for deep space missions, and the design of multiple metasurface antennas. Written to help antenna engineers to enable new CubeSate NASA missions, this volume: Describes the selection of high-gain CubeSat antennas to address specific mission requirements and constraints for instruments or telecommunicationHelps readers learn how to develop antennas for future CubeSat missionsProvides key information on the effect of space environment on antennas to inform design stepsCovers patch and patch array antennas, deployable reflectarray antennas, deployable mesh reflector, inflatable antennas, and metasurface antennas CubeSat Antenna Design is an important resource for antenna/microwave engineers, aerospace systems engineers, and advanced graduate and postdoctoral students wanting to learn how to design and fabricate their own antennas to address clear mission requirements.Table of ContentsPreface xi Editor Biography xiii Notes on Contributors xv 1 Introduction 1 1.1 Description of CubeSats 1 1.1.1 Introduction 1 1.1.2 Form Factors 3 1.1.3 Brief Introduction to CubeSat Subsystems 3 1.1.3.1 Attitude Control 3 1.1.3.2 Propulsion 6 1.1.3.3 Power 8 1.1.3.4 Telecommunication 9 1.1.4 CubeSat Antennas 11 1.1.4.1 Low Gain Antennas 11 1.1.4.2 Medium Gain Antennas 14 1.1.4.3 High Gain Antennas 15 1.1.5 Effect of Space Environment on Antennas 26 1.1.5.1 Radiation 26 1.1.5.2 Material Outgassing 27 1.1.5.3 Temperature Change 28 1.1.5.4 Multipaction Breakdown 29 1.2 Conclusion 30 2 Mars Cube One 35 2.1 Mission Description 35 2.2 Iris Radio 38 2.3 X-Band Subsystem 43 2.3.1 Frequency Allocation 43 2.3.2 Near Earth Communications Using Low Gain Antennas 43 2.3.2.1 Antenna Requirements 43 2.3.2.2 Antenna Solution and Performance 44 2.3.3 Mars-to-Earth Communications 46 2.3.3.1 Telecommunication Description: Uplink and Downlink from Mars 46 2.3.3.2 Mars Low Gain Antennas 48 2.3.3.3 High Gain Antenna 49 2.4 Entry, Descent, and Landing UHF Link 67 2.4.1 State-of-the-Art of UHF Deployable CubeSat Antennas 68 2.4.1.1 Four Monopole Antenna 68 2.4.1.2 Helical Antenna 68 2.4.1.3 Patch Antenna 70 2.4.2 Circularly Polarized Loop Antenna Concept 70 2.4.2.1 Loop Antenna Radiation and Polarization 70 2.4.2.2 Infinite Baluns Design and Shielded Loop 72 2.4.2.3 Feeding Structure 73 2.4.3 Mechanical Configuration and Deployment Scheme 74 2.4.4 Simulations and Measurements 78 2.4.5 In-Flight Performance 82 2.5 Conclusions 84 3 Radar in a CubeSat: RainCube 91 3.1 Mission Description 91 3.2 Deployable High-Gain Antenna 94 3.2.1 State of the Art 94 3.2.1.1 Inflatable Antennas 95 3.2.1.2 Deployable Reflectarray Antennas 95 3.2.1.3 Deployable Mesh Reflector Antennas 96 3.2.2 Parabolic Reflector Antenna Design 101 3.2.2.1 Paraboloidal Reflector 101 3.2.2.2 Dual-Reflector Antennas 102 3.2.3 RainCube High-Gain Antenna 104 3.2.3.1 Antenna Choice: Cassegrain Reflector 104 3.2.3.2 Antenna Description 104 3.2.3.3 Perfect Paraboloid Antenna 105 3.2.3.4 Unfurlable Paraboloid with Ribs and Mesh Structures 110 3.2.3.5 Antenna Measurement Results 119 3.2.4 Mechanical Deployment 122 3.2.5 Design and Testing for the Space Environment 127 3.2.6 In-Flight Performance 131 3.3 Telecommunication Challenge 131 3.4 Conclusion 134 4 One Meter Reflectarray Antenna: OMERA 139 4.1 Introduction 139 4.2 Reflectarray Antennas 141 4.2.1 Introductions to Reflectarray 141 4.2.2 Advantages of Reflectarray 141 4.2.3 Drawbacks of Reflectarray 142 4.2.4 State of the Art 142 4.3 OMERA 143 4.3.1 Antenna Description 143 4.3.2 Deployable Feed 146 4.3.3 Reflectarray Design 147 4.3.4 Deployment Accuracy 153 4.3.5 Effect of Struts 156 4.3.6 Predicted Gain and Efficiency 157 4.3.7 Prototype and Measurements 158 4.4 Conclusion 161 5 X/Ka-Band One Meter Mesh Reflector for 12U-Class CubeSat 163 5.1 Introduction 163 5.2 Mechanical Design 167 5.2.1 Trade Studies 167 5.2.1.1 Design Goals 167 5.2.1.2 Rigid 167 5.2.1.3 Elastic Composite 167 5.2.1.4 Mesh 168 5.2.2 Structural Design of the Reflector 168 5.2.2.1 Ribs 170 5.2.2.2 Hub 171 5.2.2.3 Battens 171 5.2.2.4 Nets 171 5.2.2.5 Perimeter Truss 174 5.2.3 Deployment 174 5.2.3.1 Boom Design and Deployment 174 5.2.3.2 Reflector Deployment 176 5.2.3.3 Deployment Issues 177 5.3 X/Ka RF Design 177 5.3.1 Antenna Configuration and Simulation Model 177 5.3.2 X-Band Feed and Mesh Reflector 179 5.3.3 Ka-Band Mesh Reflector 187 5.3.4 X/Ka-band Mesh Reflector 193 5.4 Conclusion 194 6 Inflatable Antenna for CubeSat 197 6.1 Introduction 197 6.2 Inflatable High Gain Antenna 199 6.2.1 State of the Art 199 6.2.1.1 History of Inflatable Antennas Research and Experiments 199 6.2.1.2 History of the Inflatable Antenna for CubeSat Concept 201 6.2.2 Inflatable Antenna Design at X-Band 207 6.2.2.1 Inflatable Antenna at X-Band: Initial Design and Lessons Learned 207 6.2.2.2 Inflatable Antenna at X-Band Final Design: Reflector and Feed Placement 208 6.2.2.3 Antenna Measurements 212 6.2.3 Structural Design 215 6.2.4 Inflation and On-Orbit Rigidization 220 6.3 Spacecraft Design Challenges 226 6.4 Conclusion 229 7 High Aperture Efficiency All-Metal Patch Array 233 7.1 Introduction 233 7.2 State of the Art 235 7.3 Dual-Band Circularly Polarized 8 × 8 Patch Array 240 7.3.1 Requirements 240 7.3.2 Unit Cell Optimization 240 7.3.3 8 × 8 Patch Array 244 7.3.4 Comparison With State-of-the-Art 247 7.3.5 Other Array Configurations 249 7.4 Conclusion 251 8 Metasurface Antennas: Flat Antennas for Small Satellites 255 8.1 Introduction 255 8.2 Modulated Metasurface Antennas 256 8.2.1 State of the Art: Pros and Cons 256 8.2.2 Design of Modulated Metasurface Antennas 260 8.2.3 300 GHz Silicon Micro-Machined MTS Antenna 269 8.2.3.1 Objective 269 8.2.3.2 Design Methodology: Modulation 270 8.2.3.3 MTS Element 270 8.2.3.4 Antenna Design, Fabrication, and Test 271 8.2.3.5 Improvement Using Anisotropic Surface 274 8.2.3.6 Conclusion 275 8.2.4 Ka-band Metal-Only Telecommunication Antenna 276 8.2.4.1 Objective 276 8.2.4.2 Synthesis of the Modulated Metasurface Antenna 277 8.2.4.3 Metallic Metasurface Elements 278 8.2.4.4 Antenna Design 279 8.2.4.5 Fabrication 280 8.2.4.6 Measurements 281 8.2.4.7 Toward a 20 cm Diameter Antenna 284 8.3 Beam Synthesis Using Holographic Metasurface Antennas 286 8.3.1 Introduction 286 8.3.2 Examples Holographic Metasurface Antennas 290 8.3.3 W-Band Pillbox Beam Steering Metasurface Antenna 294 8.3.4 Toward an Active Beam Steering Antenna 302 8.4 Conclusion 304 Acknowledgments 308 References 308 Index 315

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Book SynopsisCELLULAR V2X FOR CONNECTED AUTOMATED DRIVING A unique examination of cellular communication technologies for connected automated driving, combining expert insights from telecom and automotive industries as well as technical and scientific knowledge from industry and academia Cellular vehicle-to-everything (C-V2X) technologies enable vehicles to communicate both with the network, with each other, and with other road users using reliable, responsive, secure, and high-capacity communication links. Cellular V2X for Connected Automated Driving provides an up-to-date view of the role of C-V2X technologies in connected automated driving (CAD) and connected road user (CRU) services, such as advanced driving support, improved road safety, infotainment, over-the-air software updates, remote driving, and traffic efficiency services enabling the future large-scale transition to self-driving vehicles. This timely book discusses where C-V2X technology is situated within the increasingly interconnected ecosystems of the mobile communications and automotive industries. An expert contributor team from both industry and academia explore potential applications, business models, standardization, spectrum and channel modelling, network enhancements, security and privacy, and more. Broadly divided into two partsintroductory and advanced materialthe text first introduces C-V2X technology and introduces a variety of use cases and opportunities, requiring no prerequisite technical knowledge. The second part of the book assumes a basic understanding of the field of telecommunications, presenting technical descriptions of the radio, system aspects, and network design for the previously discussed applications. This up-to-date resource: Provides technical details from the finding of the European Commission H2020 5G PPP 5GCAR project, a collaborative research initiative between the telecommunications and automotive industries and academic researchersElaborates on use cases, business models, and a technology roadmap for those seeking to shape a start-up in the area of automated and autonomous drivingProvides up to date descriptions of standard specifications, standardization and industry organizations and important regulatory aspects for connected vehiclesProvides technical insights and solutions for the air interface, network architecture, positioning and security to support vehicles at different automation levelsIncludes detailed tables, plots, and equations to clarify concepts, accompanied by online tutorial slides for use in teaching and seminars Thanks to its mix of introductory content and technical information, Cellular V2X for Connected Automated Driving is a must-have for industry and academic researchers, telecom and automotive industry practitioners, leaders, policymakers, and regulators, and university-level instructors and students. Additional resources available at the following site:Cellular V2X for Connected Automated Driving 5GCARTable of ContentsList of Contributors xiii Forewords xvii Preface xxv List of Abbreviations xxix 1 Introduction 1 1.1 Background and Motivation for C-V2X 2 1.1.1 Intelligent Transport Systems 2 1.1.2 Connected Automated Driving 3 1.1.3 Connected Road User Services 4 1.2 Toward a Joint Telecom and Automotive Roadmap for CAD 4 1.2.1 Telecom’s Ambitions for Connected Driving 4 1.2.2 Automotive’s Ambitions for Automated Driving 6 1.2.3 Joint Roadmap for CAD 7 1.3 Communication Technologies for CAD 8 1.3.1 Standardization of IEEE V2X 10 1.3.2 Standardization and Regulation Aspects of C-V2X 12 1.3.2.1 Available C-V2X Releases and Regulations 12 1.3.2.2 Future Requirements for C-V2X Releases and Regulations 13 1.4 Structure of this Book 14 References 18 2 Business Models 21 2.1 Current Market Analysis 22 2.2 Services Definition for CAD and CRU 23 2.2.1 Existing CAD and CRU Services 24 2.2.1.1 Emergency Call 24 2.2.1.2 Remote Diagnostics 24 2.2.1.3 Car Sharing 25 2.2.1.4 OTA Software Updates 25 2.2.1.5 Predictive Maintenance 25 2.2.1.6 Real-Time Road Traffic Management and Vehicle Guidance 25 2.2.2 Emerging CAD Services 25 2.2.2.1 Perception by Wireless Connectivity and Sensor Sharing 26 2.2.2.2 High-Definition Maps 26 2.2.3 Emerging CRU Services 26 2.2.3.1 Video Streaming and Gaming 26 2.2.3.2 Parking Reservations and Payment 26 2.3 Technical Components 27 2.4 Practicalities 28 2.4.1 Profile and SIM Card Provisioning 28 2.4.2 Routing Strategy 28 2.4.3 Roaming and Inter-operator Cooperation 29 2.4.4 Possible Business Model Evolution 29 2.4.4.1 OTA Software Updates 30 2.4.4.2 CAD Services and Related Automation Levels 31 2.5 Business Market Opportunities for V2X 34 2.5.1 CAD Business Model Enabled by 5G 34 2.5.1.1 Passive Infrastructure Sharing 37 2.5.1.2 Active Infrastructure Sharing, Excluding Spectrum Sharing 37 2.5.1.3 Active Infrastructure Sharing, Including Spectrum Sharing 37 2.5.2 Security Provision 38 2.5.2.1 The PKI Workflow 38 2.5.2.2 Enrollment of an ITS Station 39 2.5.2.3 Use of Authorizations Tokens 40 2.5.2.4 The Cost Hypothesis 40 2.5.3 OTA Software Updates 41 2.6 Business Model Analysis of 5G V2X Technical Components 44 2.6.1 Positioning 45 2.6.2 V2X Radio Design 46 2.6.2.1 Predictor Antenna 46 2.6.2.2 Beam-Forming 46 2.6.2.3 Efficiency 49 2.6.2.4 Reliability 49 2.6.2.5 Sidelink Out of Coverage 49 2.6.2.6 Sidelink in Coverage 49 2.6.3 Network Procedures 49 2.6.3.1 Local Standalone Network Procedures 51 2.6.3.2 Network Service Relationship Enhancement 51 2.6.3.3 Multi-Operator Solutions for V2X Communications 53 2.6.3.4 Network Orchestration and Management 53 2.6.4 End-to-End Security 54 2.6.5 Edge Computing Enhancements 55 2.6.6 Summary 58 2.7 Conclusions 58 References 60 3 Standardization and Regulation 63 3.1 Standardization Process Overview 64 3.1.1 General Aspects 64 3.1.2 Standardization and Regulation Bodies Relevant to ITS Specifications 64 3.1.2.1 International Telecommunication Union 65 3.1.2.2 Regional Standards Developing Organizations 66 3.1.2.3 3GPP, IEEE, and SAE 67 3.1.2.4 5G PPP and EATA 67 3.1.2.5 5GAA 68 3.1.3 3GPP Structure and Standardization Process 69 3.2 Regulatory Aspects and Spectrum Allocation 70 3.2.1 C-V2X Policy and Regulations in Europe 71 3.2.2 Radio Frequency Spectrum Allocation for V2X Communications 71 3.2.2.1 Spectrum Allocation for IMT Systems and 3GPP Technologies 71 3.2.2.2 Dedicated Spectrum for ITS Applications 72 3.2.2.3 Worldwide Spectrum Harmonization 73 3.3 Standardization of V2X Communication Technology Solutions 73 3.3.1 A Brief History of V2X Communication 74 3.3.2 Overview of DSRC/C-V2X Specifications Around the Globe 75 3.3.2.1 Europe 75 3.3.2.2 The Americas 76 3.3.2.3 Asia 77 3.3.3 C-V2X Standardization in 3GPP: Toward and Within 5G 79 3.3.3.1 C-V2X in 4G 80 3.3.3.2 C-V2X Supported by 5G 82 3.3.3.3 Future Plans 83 3.4 Application Aspects 84 3.4.1 EU Standardization 86 3.4.2 US Standardization 87 3.5 Summary 87 References 88 4 Spectrum and Channel Modeling 91 4.1 Spectrum and Regulations for V2X Communications 91 4.1.1 Spectrum Bands in Europe 92 4.1.1.1 ITS Spectrum at 5.9 GHz 92 4.1.1.2 5.8 GHz Frequency for Toll Collection 93 4.1.1.3 60 GHz ITS Band 93 4.1.1.4 IMT Bands in Europe 93 4.1.2 Spectrum Bands in Other Regions 94 4.1.2.1 United States 94 4.1.2.2 China 95 4.1.2.3 Other Regions of the World 96 4.1.3 Spectrum Auctions Worldwide 96 4.1.3.1 Europe 96 4.1.3.2 United States 104 4.1.3.3 Asia 105 4.1.3.4 Summary of Auctions and Cost Comparison Worldwide 108 4.1.4 Spectrum Harmonization Worldwide 111 4.1.4.1 Europe and Digital Single Market 111 4.1.4.2 World Radiocommunication Conference 2019 111 4.1.5 Summary 112 4.2 Channel Modeling 113 4.2.1 Propagation Environments 114 4.2.1.1 Link Types 114 4.2.1.2 Environments 114 4.2.2 Channel-Modeling Framework and Gap Analysis 116 4.2.3 Path-Loss Models 116 4.2.3.1 Path-Loss for V2V LOS Links 116 4.2.3.2 Shadow-Fading Models 121 4.2.3.3 Fast-Fading Parameters 122 4.2.3.4 Summary 123 4.2.4 Recent V2X Channel Measurements and Models 124 4.2.4.1 V2V Measurements in cmWave and mmWave 124 4.2.4.2 mmWave V2V (Sidelink) Channel Modeling 124 4.2.4.3 Multi-Link Shadowing Extensions 132 4.2.5 Summary 134 References 135 5 V2X Radio Interface 137 5.1 Beamforming Techniques for V2X Communication in the mm-Wave Spectrum 138 5.1.1 Beam Refinement for Mobile Multi-User Scenarios 139 5.1.1.1 Algorithm Description 140 5.1.1.2 Illustrative Performance Results 140 5.1.2 Beamformed Multicasting 143 5.1.3 Beam-Based Broadcasting 147 5.2 PHY and MAC Layer Extensions 152 5.2.1 Channel State Information Acquisition and MU-MIMO Receiver Design 152 5.2.1.1 The Importance and Challenges of Channel State Information Acquisition in MU-MIMO Systems 152 5.2.1.2 Interplay Between CSIR Acquisition and MU-MIMO Receiver Design 153 5.2.1.3 Novel Approaches to Near-Optimal MU-MIMO Linear Receiver Design and the Impact of CSIR Errors 156 5.2.1.4 Performance Modeling and Numerical Results in Multi-Antenna Cellular Vehicle Scenarios 157 5.2.2 Reference Signal Design 159 5.2.2.1 Challenges to CSI Acquisition in V2V Sidelink Communication 159 5.2.2.2 Reference Signal Design for V2V Sidelink 160 5.2.2.3 Performance Evaluation 163 5.2.3 Synchronization 164 5.2.4 Scheduling and Power Control 168 5.3 Technology Features Enabled by Vehicular Sidelink 172 5.3.1 UE Cooperation for Enhancing Reliability 173 5.3.1.1 Communication Scenario 173 5.3.1.2 Reliability Analysis – Channels with Equal Power 174 5.3.1.3 Evaluation 176 5.3.1.4 System Design Aspects 178 5.3.2 Full Duplex 181 5.3.2.1 Advantages of Full-Duplex Radio for C-V2X 182 5.4 Summary 184 References 185 6 Network Enhancements 191 6.1 Network Slicing 192 6.1.1 Network Slicing and 3GPP 192 6.1.2 Network Slicing and V2X 194 6.2 Role of SDN and NFV in V2X 196 6.3 Cloudified Architecture 199 6.4 Local End-to-End Path 200 6.5 Multi-Operator Support 202 6.6 Summary 205 References 205 7 Enhancements to Support V2X Application Adaptations 207 7.1 Background 208 7.2 Enhanced Application-Network Interaction for Handling V2X Use Cases 210 7.2.1 C-V2X Connectivity Negotiation 210 7.2.2 Use-Case-Aware Multi-RAT Multi-Link Connectivity 212 7.2.3 Location-Aware Scheduling 214 7.3 Redundant Scheduler for Sidelink and Uu 215 7.3.1 Application or Facilities Layer 216 7.3.2 Transport Level 219 7.3.3 RRC Level 220 7.4 Summary 221 References 221 8 Radio-Based Positioning and Video-Based Positioning 223 8.1 Radio-Based Positioning 225 8.1.1 Use Cases and Requirements 225 8.1.2 Radio-Based Positioning in New Radio Release 16 226 8.1.3 Radio-Based Positioning Beyond Release 16 228 8.1.3.1 The mmWave Channel 228 8.1.3.2 Signal Design 229 8.1.3.3 The Measurement Process 230 8.1.3.4 Localization, Mapping, and Tracking 231 8.1.4 Technology Component Complementation 233 8.1.5 Limitations of Radio-Based Positioning 235 8.1.6 Summary 236 8.2 Video-Based Positioning 237 8.2.1 Vehicle Positioning System Setup 237 8.2.2 Multi-Camera Calibration 239 8.2.3 Vehicle Detection 240 8.2.4 Vehicle Tracking 241 8.2.5 Vehicle Localization 241 8.2.6 Accuracy Evaluation 242 8.2.7 Summary 245 8.3 Conclusions 246 References 246 9 Security and Privacy 251 9.1 V2N Security 252 9.1.1 Security Challenges 253 9.1.2 Isolation Challenges 254 9.1.2.1 System Isolation (Between ECUs) 254 9.1.2.2 Network Isolation (Between Network Slices) 254 9.1.3 Software-Defined Vehicular Networking Security 255 9.1.3.1 Principles and Architecture 255 9.1.3.2 Security Benefits and Threats 255 9.2 V2V/V2I Security 256 9.2.1 Privacy 257 9.2.2 European Union Security Architecture 258 9.2.3 US Security Architecture 260 9.3 Alternative Approaches 261 9.4 Conclusion 262 References 262 10 Status, Recommendations, and Outlook 265 10.1 Future Prospects of C-V2X and the CAD Ecosystem 265 10.1.1 Future Needs for R&D and Standardization in C-V2X 266 10.1.2 Broader Aspects of CAD and CRU Services 268 10.2 Recommendations to Stakeholders 270 10.2.1 Mobile Network Operators 271 10.2.1.1 Network-Sharing Alternatives 271 10.2.1.2 New Business Models for Connected Vehicle Services 271 10.2.1.3 Roaming and Inter-Operator Cooperation 272 10.2.2 Original Equipment Manufacturers 272 10.2.2.1 Connecting Off-Board Sensors 272 10.2.2.2 Vehicle Processing Platforms Supported by Networks 273 10.2.2.3 Automotive Standardization 274 10.2.3 Regulators 274 10.2.3.1 Deployment, Coverage, and Road Infrastructure 274 10.2.3.2 Simplifying and Harmonizing Regulation 275 10.2.3.3 Data Sharing and Monetization 276 10.2.3.4 Spectrum Aspects 276 10.2.4 Suppliers and Certification 277 10.3 Outlook 278 References 279 Index 281

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Book SynopsisTable of ContentsPreface and Text Organization ix List of Notations xiii About the Companion Website xv 1 Antenna Circuit Model. Antenna Matching. Antenna Bandwidth 1 Section 1 Lumped Circuit Model of an Antenna. Antenna Input Impedance 1 Section 2 Antenna with Transmission Line. Antenna Reflection Coefficient. Antenna Matching. VSWR 18 2 Receiving Antenna: Received Voltage, Power, and Transmission Coefficient 31 Section 1 Analytical Model for the Receiving Antenna 31 Section 2 Model of a Two-Port Network for TX/RX Antennas 44 3 Antenna Radiation 55 Section 1 Maxwell Equations and Boundary Conditions 55 Section 2 Solution for Maxwell’s Equations in Terms of Electric and Magnetic Potentials 63 Section 3 Antenna Radiation 71 Section 4 Antenna Directivity and Gain 84 4 Antenna Balun. Antenna Reflector. Method of Images 101 Section 1 Antenna Balun 101 Section 2 Antenna Reflector 116 5 Dipole Antenna Family: Broadband Antennas that Operate as Dipoles at Low Frequencies 135 Section 1 Broadband Dipoles and Monopoles 135 Section 2 Biconical, Wide Blade, and Vivaldi Antennas 141 6 Loop Antennas 155 Section 1 Loop Antenna vs. Dipole Antenna 155 7 Small Antennas 171 Section 1 Fundamental Limits on Antenna Bandwidth 171 Section 2 Practical Antenna Matching and Tuning for a Predefined (50 Ω) Impedance 185 8 Patch and PIFA Antennas 197 Section 1 Patch Antennas 197 Section 2 Planar Inverted F (PIFA) Antenna. Bandwidth Estimations 219 9 Traveling Wave Antennas 233 Section 1 Long Wire Antenna and Yagi-Uda Antenna 233 Section 2 Helical and Spiral Antennas 241 10 Antenna Designer Including Circularly Polarized Antennas 251 Section 1 Fast Analysis and Design of Individual Antennas 251 Section 2 Meaning of Circular Polarization and Proper Antenna Orientation 259 11 Antenna Arrays 271 Section 1 Array Types. Array Factor. Concept of a Scanning Array 271 Section 2 Linear Arrays 287 Section 3 Planar Arrays 303 Index 317

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Book SynopsisExplore thefoundational and advancedsubjects associated with proportional-integral-derivative controllers fromleading authors in the field InPID Passivity-Based Control of Nonlinear Systems with Applications,expert researchers and authors Drs. Romeo Ortega, Jose GuadalupeRomero,Pablo Borja,andAlejandro Donairedelivera comprehensive and detailed discussion of the most crucial and relevant conceptsin the analysis and design ofproportional-integral-derivative controllersusing passivity techniques. The accomplished authors present a formal treatment of the recentresearch in the area and offer readers practical applications of the developed methods to physical systems, including electrical, mechanical, electromechanical, power electronics, and process control. The book offers the material with minimal mathematical background, making it relevant to a wide audience. Familiarity withthe theoretical tools reported in the control systems literature is not necessaryTable of ContentsAuthor Biographies xv Preface xix Acknowledgments xxiii Acronyms xxv Notation xxix 1 Introduction 1 2 Motivation and Basic Construction of PID Passivity-based Control 5 2.1 L2-Stability and Output Regulation to Zero 6 2.2 Well-Posedness Conditions 9 2.3 PID-PBC and the Dissipation Obstacle 10 2.3.1 Passive systems and the dissipation obstacle 11 2.3.2 Steady-state operation and the dissipation obstacle 12 2.4 PI-PBC with y0 and Control by Interconnection 14 3 Use of Passivity for Analysis and Tuning of PIDs: Two Practical Examples 19 3.1 Tuning of the PI Gains for Control of Induction Motors 21 3.1.1 Problem formulation 23 3.1.2 Change of coordinates 27 3.1.3 Tuning rules and performance intervals 30 3.1.4 Concluding remarks 35 3.2 PI-PBC of a Fuel Cell System 36 3.2.1 Control problem formulation 41 3.2.2 Limitations of current controllers and the role of passivity 46 3.2.3 Model linearization and useful properties 48 3.2.4 Main result 50 3.2.5 An asymptotically stable PI-PBC 54 3.2.6 Simulation results 57 3.2.7 Concluding remarks and future work 58 4 PID-PBC for Nonzero Regulated Output Reference 61 4.1 PI-PBC for Global Tracking 63 4.1.1 PI global tracking problem 63 4.1.2 Construction of a shifted passive output 65 4.1.3 A PI global tracking controller 67 4.2 Conditions for Shifted Passivity of General Nonlinear Systems 68 4.2.1 Shifted passivity definition 69 4.2.2 Main results 70 4.3 Conditions for Shifted Passivity of port-Hamiltonian Systems 73 4.3.1 Problems formulation 74 4.3.2 Shifted passivity 75 4.3.3 Shifted passifiability via output-feedback 77 4.3.4 Stability of the forced equilibria 78 4.3.5 Application to quadratic pH systems 79 4.4 PI-PBC of Power Converters 81 4.4.1 Model of the power converters 81 4.4.2 Construction of a shifted passive output 82 4.4.3 PI stabilization 85 4.4.4 Application to a quadratic boost converter 86 4.5 PI-PBC of HVDC Power Systems 89 4.5.1 Background 89 4.5.2 Port-Hamiltonian model of the system 91 4.5.3 Main result 93 4.5.4 Relation of PI-PBC with Akagi’s PQ method 95 4.6 PI-PBC of Wind Energy Systems 96 4.6.1 Background 96 4.6.2 System model 98 4.6.3 Control problem formulation 102 4.6.4 Proposed PI-PBC 104 4.7 Shifted Passivity of PI-Controlled Permanent Magnet Synchronous Motors 107 4.7.1 Background 107 4.7.2 Motor models 108 4.7.3 Problem formulation 111 4.7.4 Main result 113 4.7.5 Conclusions and future research 114 5 Parameterization of All Passive Outputs for port-Hamiltonian Systems 115 5.1 Parameterization of all Passive Outputs 116 5.2 Some Particular Cases 118 5.3 Two Additional Remarks 120 5.4 Examples 121 5.4.1 A level control system 121 5.4.2 A microelectromechanical optical switch 123 6 Lyapunov Stabilization of port-Hamiltonian Systems 125 6.1 Generation of Lyapunov Functions 127 6.1.1 Basic PDE 128 6.1.2 Lyapunov stability analysis 129 6.2 Explicit Solution of the PDE 131 6.2.1 The power shaping output 132 6.2.2 A more general solution 133 6.2.3 On the use of multipliers 135 6.3 Derivative Action on Relative Degree Zero Outputs 137 6.3.1 Preservation of the port-Hamiltonian Structure of I-PBC 138 6.3.2 Projection of the new passive output 140 6.3.3 Lyapunov stabilization with the new PID-PBC 141 6.4 Examples 142 6.4.1 A microelectromechanical optical switch (continued) 143 6.4.2 Boost converter 144 6.4.3 2-dimensional controllable LTI systems 146 6.4.4 Control by Interconnection vs PI-PBC 148 6.4.5 The use of the derivative action 150 7 Underactuated Mechanical Systems 153 7.1 Historical Review and Chapter Contents 153 7.1.1 Potential energy shaping of fully actuated systems 154 7.1.2 Total energy shaping of underactuated systems 156 7.1.3 Two formulations of PID-PBC 157 7.2 Shaping the Energy with a PID 158 7.3 PID-PBC of port-Hamiltonian Systems 161 7.3.1 Assumptions on the system 161 7.3.2 A suitable change of coordinates 163 7.3.3 Generating new passive outputs 165 7.3.4 Projection of the total storage function 167 7.3.5 Main stability result 169 7.4 PID-PBC of Euler-Lagrange Systems 172 7.4.1 Passive outputs for Euler-Lagrange systems 173 7.4.2 Passive outputs for Euler-Lagrange systems in Spong’s normal form 175 7.5 Extensions 176 7.5.1 Tracking constant speed trajectories 176 7.5.2 Removing the cancellation of Va(qa) 178 7.5.3 Enlarging the class of integral actions 179 7.6 Examples 180 7.6.1 Tracking for inverted pendulum on a cart 180 7.6.2 Cart-pendulum on an inclined plane 182 7.7 PID-PBC of Constrained Euler-Lagrange Systems 190 7.7.1 System model and problem formulation 191 7.7.2 Reduced purely differential model 195 7.7.3 Design of the PID-PBC 196 7.7.4 Main stability result 199 7.7.5 Simulation Results 200 7.7.6 Experimental Results 202 8 Disturbance Rejection in port-Hamiltonian Systems 207 8.1 Some Remarks On Notation and Assignable Equilibria 209 8.1.1 Notational simplifications 209 8.1.2 Assignable equilibria for constant d 210 8.2 Integral Action on the Passive Output 211 8.3 Solution Using Coordinate Changes 214 8.3.1 A feedback equivalence problem 214 8.3.2 Local solutions of the feedback equivalent problem 217 8.3.3 Stability of the closed–loop 219 8.4 Solution Using Nonseparable Energy Functions 221 8.4.1 Matched and unmatched disturbances 222 8.4.2 Robust matched disturbance rejection 225 8.5 Robust Integral Action for Fully Actuated Mechanical Systems 230 8.6 Robust Integral Action for Underactuated Mechanical Systems 237 8.6.1 Standard interconnection and damping assignment PBC 239 8.6.2 Main result 241 8.7 A New Robust Integral Action for Underactuated Mechanical Systems 244 8.7.1 System model 244 8.7.2 Coordinate transformation 245 8.7.3 Verification of requisites 246 8.7.4 Robust integral action controller 248 8.8 Examples 248 8.8.1 Mechanical systems with constant inertia matrix 249 8.8.2 Prismatic robot 250 8.8.3 The Acrobot system 255 8.8.4 Disk on disk system 260 8.8.5 Damped vertical take-off and landing aircraft 265 A Passivity and Stability Theory for State-Space Systems 269 A.1 Characterization of Passive Systems 269 A.2 Passivity Theorem 271 A.3 Lyapunov Stability of Passive Systems 273 B Two Stability Results and Assignable Equilibria 275 B.1 Two Stability Results 275 B.2 Assignable Equilibria 276 C Some Differential Geometric Results 279 C.1 Invariant Manifolds 279 C.2 Gradient Vector Fields 280 C.3 A Technical Lemma 281 D Port-Hamiltonian Systems 283 D.1 Definition of port-Hamiltonian Systems and Passivity Property 283 D.2 Physical Examples 284 D.3 Euler-Lagrange Models 286 D.4 Port-Hamiltonian Representation of GAS Systems 288 Index 309

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Book SynopsisTable of ContentsAbout the Authors xix Preface xxi Acknowledgments xxv List of Acronyms xxvii 1 Field Programmable Gate Arrays 1 1.1 Overview 1 1.1.1 FPGA Hardware Architecture 2 1.1.2 Configurable Logic Block 3 1.1.3 Block RAM 4 1.1.4 Digital Signal Processing Slice 4 1.2 Multiprocessing System-on-Chip Architecture 6 1.3 Communication 7 1.4 HIL Emulation 9 1.4.1 Vivado® High-Level Synthesis Tool 9 1.4.2 Vivado® Top-Level Design 11 1.4.3 Number Representation and Operations 13 1.4.4 FPGA Design Schemes 14 1.4.4.1 Pipeline Design Architecture 14 1.4.4.2 Parallel Design Architecture 14 1.4.5 FPGA Experiment 15 1.5 Summary 16 2 Hardware Emulation Building Blocks for Power System Components 17 2.1 Overview 17 2.2 Concept of HEBB 18 2.3 Numerical Integration 18 2.4 Linear Lumped Passive Elements 20 2.4.1 Model Formulation 20 2.4.1.1 Resistance R 20 2.4.1.2 Inductance L 20 2.4.1.3 Capacitance C 22 2.4.1.4 RL Branch 23 2.4.1.5 LC Branch 23 2.4.1.6 RLCG Branch 24 2.4.2 Hardware Emulation of Linear Lumped Passive Elements 26 2.5 Sources 27 2.5.1 Hardware Emulation of Sources 28 2.6 Switches 30 2.6.1 Hardware Emulation of Switches 30 2.7 Transmission Lines 32 2.7.1 Traveling Waves 32 2.7.2 Traveling Wave Model 35 2.7.2.1 Modal Transformation 36 2.7.3 Hardware Emulation of the TWM 39 2.7.3.1 Transformation Unit 39 2.7.3.2 Update Unit 39 2.7.4 Frequency Dependent Line Model 41 2.7.5 Hardware Emulation of FDLM 46 2.7.5.1 Convolution Unit 46 2.7.5.2 Update Unit 47 2.7.6 Universal Line Model 48 2.7.6.1 Frequency-Domain Formulation 48 2.7.6.2 Time-Domain Formulation 49 2.7.7 Hardware Emulation of the ULM 51 2.7.7.1 Update x Unit 52 2.7.7.2 Convolution Unit 52 2.7.7.3 Interpolation Unit 54 2.8 Network Solver 54 2.8.1 Hardware Emulation of Network Solver 55 2.8.2 Paralleled EMT Solution Algorithm 55 2.8.3 Main Control Module 58 2.8.4 Real-Time Emulation Case Study 59 2.9 Nonlinear Elements: Iterative Real-Time EMT Solver 63 2.9.1 Compensation Method 64 2.9.2 Newton–Raphson Method 65 2.9.3 Hardware Emulation of Nonlinear Solver 67 2.9.3.1 Nonlinear Function Evaluation 68 2.9.3.2 Parallel Calculation of J and F(ikm) 68 2.9.3.3 Parallel Gauss–Jordan Elimination 71 2.9.3.4 Computing vc 71 2.9.4 Case Studies 71 2.10 Summary 77 3 Power Transformers 79 3.1 Overview 79 3.2 Nonlinear Admittance-Based Real-Time Transformer Model 80 3.2.1 Linear Model Formulation 80 3.2.2 Linear Module Hardware Design 82 3.2.3 Inode Unit Module 84 3.2.4 Nonlinear Model Solution 85 3.2.4.1 Preisach Hysteresis Model 88 3.2.4.2 Nonlinear Module Hardware Design 89 3.2.5 Frequency-Dependent Eddy Current Model 90 3.2.6 Hardware Emulation of Power Transformer 91 3.2.7 Real-Time Emulation Case Studies 94 3.2.7.1 Case I 94 3.2.7.2 Case II 99 3.3 Nonlinear Magnetic Equivalent Circuit Based Real-time Multi-Winding Transformer Model 100 3.3.1 Topological ST EMT Model 102 3.3.1.1 ST Operating Principle 102 3.3.1.2 Tap-selection Algorithm 102 3.3.1.3 High-Fidelity Nonlinear MEC-Based ST Model 102 3.3.1.4 Iron Core Hysteresis and Eddy Currents 107 3.3.2 High-Fidelity Nonlinear MEC-Based ST Hardware Emulation 109 3.3.2.1 Network Transient Emulation with Embedded ST 109 3.3.3 Real-Time Emulation Case Studies 112 3.3.3.1 Finite Element Modeling and Validation 112 3.3.3.2 Case Studies 112 3.4 Real-Time Finite-Element Model of Power Transformer 123 3.4.1 Magnetodynamic Problem Formulation 123 3.4.1.1 Refined TLM Solution 126 3.4.1.2 Field-Circuit Coupling 130 3.4.2 Hardware Emulation of Finite Element Model 132 3.4.3 Case Studies 136 3.4.3.1 Results and Validation 137 3.4.3.2 Speed-up and Scalability 140 3.5 Summary 141 4 Rotating Machines 143 4.1 Overview 143 4.2 Lumped Universal Machine (UM) Model 144 4.2.1 UM Model Formulation 144 4.2.2 Interfacing UM Model with Network 146 4.2.3 UM HEBB 148 4.2.3.1 Speed & Angle Unit 149 4.2.3.2 FrmTran Unit 150 4.2.3.3 Compidq0 Unit 151 4.2.3.4 Flux & Torque Unit 151 4.2.3.5 Update & CompVc Unit 151 4.2.4 Real-Time Emulation Case Study 152 4.2.5 Overall Power System HEBB for Real-Time EMT Emulation 154 4.3 General Framework for State-Space Electrical Machine Emulation 158 4.3.1 FPGA Design Approaches for Electrical Machine Emulation 159 4.3.2 State-Space Representation of Machine Models 160 4.3.3 System Configuration on FPGA 161 4.3.3.1 Number Representation 161 4.3.3.2 Floating-Point Implementation by VHDL 162 4.3.3.3 Fixed-Point Implementation by Schematic 167 4.3.4 Evaluation of Designed Architectures 170 4.3.4.1 Real-Time Emulation Accuracy Assessment 170 4.3.4.2 Off-line Validation 171 4.3.4.3 Hardware Resource Utilization 172 4.3.5 Real-Time Emulation Case Studies 174 4.3.5.1 Case I: Induction Motor Transients 174 4.3.5.2 Case II: Synchronous Generator Transients 174 4.3.5.3 Case III: Line Start-Permanent Magnet Synchronous Motor Transients 176 4.3.5.4 Case IV: DC Motor Transients 177 4.4 Nonlinear Magnetic Equivalent Circuit Based Induction Machine Model 178 4.4.1 Magnetic Circuit 179 4.4.2 Interfacing of Magnetic and Electric Circuits 181 4.4.3 Electric Circuit 182 4.4.4 Nonlinear Solution of Detailed MEC 182 4.4.5 Hardware Emulation of Nonlinear MEC 183 4.4.5.1 Parallel Gauss–Jordan Elimination Unit 185 4.4.5.2 Parallel Computational Unit for Residual Vector 187 4.4.5.3 Nonlinear Evaluation Unit 187 4.4.6 Evaluation of Real-Time Emulation of Induction Machine 187 4.5 Summary 190 5 Protective Relays 193 5.1 Overview 193 5.2 Hardware Emulation of Multifunction Protection System 195 5.2.1 Signal Processing HEBB 196 5.2.1.1 CORDIC HEBB 196 5.2.1.2 Symmetrical Components HEBB 198 5.2.1.3 DFT HEBB 198 5.2.1.4 Zero-Crossing Detection HEBB 199 5.2.2 Multifunction Protective System HEBB 203 5.2.2.1 Fault Detection HEBB 203 5.2.2.2 Directional Overcurrent Protection HEBB 205 5.2.2.3 Over/Under Voltage Protection HEBB 205 5.2.2.4 Distance Protection HEBB 205 5.2.2.5 Under/Over Frequency Protection HEBB 209 5.3 Test Setup and Real-Time Results 209 5.3.1 Case I 210 5.3.2 Case II 213 5.4 Summary 214 6 Adaptive Time-Stepping Based Real-Time EMT Emulation 217 6.1 Overview 217 6.2 Nonlinear Solution and Adaptive Time-Stepping Schemes 219 6.2.1 Nonlinear Element Solution Methods 219 6.2.1.1 Newton–Raphson Method 219 6.2.1.2 Piecewise Linearization (PWL) Method 219 6.2.1.3 Piecewise N-R Method 220 6.2.2 Adaptive Time-Stepping Schemes 220 6.2.2.1 Local Truncation Error Method 220 6.2.2.2 Iteration Count Method 221 6.2.2.3 DVDT or DIDT Method 221 6.2.3 Combinations of Adaptive Time-Stepping Schemes 222 6.2.3.1 Measurements and Restrictions for Real-Time Emulation 222 6.2.4 Case Studies 223 6.2.4.1 Diode Full-Bridge Circuit 224 6.2.4.2 Power Transmission System 225 6.2.4.3 FPGA Implementation 229 6.2.4.4 Real-Time Emulation Results 234 6.3 Adaptive Time-Stepping Universal Line Model and Universal Machine Model for Real-Time Hardware Emulation 236 6.3.1 Subsystem-Based Adaptive Time-Stepping Scheme 237 6.3.2 Adaptive Time-Stepping ULM and UM Models 238 6.3.2.1 ULM Computation 238 6.3.2.2 Universal Machine Model Computation 242 6.3.3 Real-Time Emulation Case Study 243 6.3.3.1 Hardware Implementation 243 6.3.3.2 Latency and Hardware Resource Utilization 246 6.3.4 Results and Validation 247 6.3.4.1 Validation of the ULM Model 247 6.3.4.2 Real-Time Emulation Results 248 6.4 Summary 252 7 Power Electronic Switches 253 7.1 Overview 253 7.2 IGBT/Diode Nonlinear Behavioral Model 255 7.2.1 Power Diode 256 7.2.1.1 Mathematical Model 256 7.2.1.2 Hardware Module Architecture 257 7.2.2 IGBT 259 7.2.2.1 Model Formulation 259 7.2.2.2 Hardware Module Architecture 263 7.2.2.3 Multiple Parallel Devices 265 7.2.3 Electro-Thermal Network 267 7.2.4 Hardware Emulation Results 268 7.3 Physics-Based Nonlinear IGBT/Diode Model 270 7.3.1 Physics-Based Nonlinear p–i–n Diode Model 271 7.3.1.1 Model Formulation 271 7.3.1.2 Model Discretization and Linearization 272 7.3.1.3 Hardware Emulation on FPGA 274 7.3.2 Physics-Based Nonlinear IGBT Model 276 7.3.2.1 Model Formulation 276 7.3.2.2 Model Discretization and Linearization 279 7.3.2.3 Hardware Emulation on FPGA 281 7.3.3 Hardware Emulation Results 285 7.3.3.1 Test circuit 285 7.3.3.2 Results and comparison 286 7.4 IGBT/Diode Curve-Fitting Model 292 7.4.1 Linear Static Curve-fitting Model 293 7.4.1.1 Static Characteristics 293 7.4.1.2 Switching Transients 293 7.4.2 Nonlinear Dynamic Curve-fitting Model 296 7.4.3 Hardware Emulation Results 298 7.5 Summary 300 8 AC–DC Converters 301 8.1 Overview 301 8.2 Detailed Model 303 8.2.1 Detailed Equivalent Circuit Model 304 8.3 Equivalenced Device-Level Model 305 8.3.1 Power Loss Calculation 307 8.3.2 Thermal Network Calculation 309 8.3.3 Hardware Emulation of SM Model on FPGA 311 8.3.4 MMC System Hardware Emulation 314 8.3.5 Real-Time Emulation Results 316 8.3.5.1 Test Circuit and Hardware Resource Utilization 316 8.3.5.2 Results and Comparison for Single-Phase Five-Level MMC 318 8.3.5.3 Results for Three-Phase Nine-Level MMC 324 8.4 Virtual-Line-Partitioned Device-Level Models 324 8.4.1 TLM-Link Partitioning 326 8.4.2 Hardware Design on FPGA 328 8.4.2.1 Hardware Platform 329 8.4.2.2 Controller Emulation 329 8.4.2.3 MMC Emulation on FPGA 330 8.4.3 Real-Time Emulation Results 335 8.4.3.1 MMC 335 8.4.3.2 Induction Machine Driven by Five-Level MMC 342 8.5 MMC Partitioned by Coupled Voltage–Current Sources 344 8.5.1 V–I Coupling 344 8.5.2 Hardware Emulation Case of NBM-Based MMC 346 8.5.2.1 Power Converter HIL Emulation 346 8.5.2.2 HIL Emulation Results and Validation 347 8.5.2.3 Islanded MMC Performance 348 8.5.2.4 MMC–MVDC Performance 355 8.6 Clamped Double Submodule MMC 355 8.6.1 Operation Principles of CDSM 357 8.6.2 Device-Level Modeling Scheme 359 8.6.2.1 Temperature-Dependent Electrical Interface Parameter Calculation 359 8.6.2.2 Device-Level Linearized Transient Waveform Calculation 361 8.6.3 SM-Level Modeling Scheme 362 8.6.4 Converter-Level Modeling Scheme 362 8.6.5 Case Study and Hardware Implementation 363 8.6.5.1 Design Partition 365 8.6.5.2 Latency and Resource Consumption 367 8.6.6 Real-Time Emulation Results and Analysis 368 8.6.6.1 Steady-State Results 368 8.6.6.2 DC Power Flow Control 368 8.6.6.3 DC Fault Transient Results 371 8.7 Summary 374 9 DC-DC Converters 377 9.1 Overview 377 9.2 Buck–Boost Converter 379 9.2.1 System-Level Modeling 379 9.2.2 Hardware Implementation 380 9.3 Solid-State Transformer Modeling 381 9.3.1 MMC Arm Models 382 9.3.1.1 TLM-Stub Model (TLM-S) 382 9.3.1.2 Nonlinear Switch-Based Model (NSM) 383 9.3.1.3 Hybrid Arm Model 384 9.3.2 Three-Phase Saturable Transformer Model 385 9.3.3 SST EMT Model 385 9.3.4 SST HIL Emulation 386 9.3.5 SST Real-Time HIL Emulation Results 390 9.3.5.1 Device-Level Behavior 390 9.3.5.2 Converter Performance 391 9.3.5.3 System Tests 392 9.4 Summary 394 10 DC Circuit Breakers 397 10.1 Overview 397 10.2 HHB in MTDC System 399 10.2.1 MTDC Test System Schematic 399 10.2.2 DC Line Protection 401 10.2.2.1 Voltage Derivative Protection 401 10.2.2.2 Over Current Protection 401 10.3 Proactive Hybrid HVDC Breaker 402 10.3.1 HHB EMT Model 403 10.3.2 Varistor Model 404 10.3.3 General HHB Unit Model 406 10.3.4 Two-Node IGBT Models 407 10.3.5 IGBT Low-Order Nonlinear Behavioral Model 409 10.3.5.1 IGBT Fourth-Order Behavioral Model 409 10.3.5.2 Parameters Extraction 409 10.3.5.3 Sensitivity Analysis 410 10.3.5.4 Model Parallelization 411 10.3.6 Electro-Thermal Network 412 10.3.7 HHB Hardware Implementation on FPGA 412 10.3.8 HHB HIL Emulation Results 416 10.3.8.1 Device-Level Performance 416 10.3.8.2 System-Level Performance 424 10.4 Ultrafast Mechatronic Circuit Breaker 426 10.4.1 Nonlinear Device-Level Thyristor Model 426 10.4.1.1 Basic Device Characteristics 426 10.4.1.2 Scalable Cascaded Thyristor Model 428 10.4.2 UFMCB Modeling 431 10.4.3 Relaxed Scalar Newton–Raphson (RSNR) 433 10.4.4 UFMCB Hardware Design 435 10.4.5 UFMCB Real-Time Tests and Validation 438 10.4.5.1 Four-Terminal DC Grid Test Case 438 10.4.5.2 UFMCB Design Evaluation by HIL System 438 10.4.5.3 UFMCB in HVDC Grid 442 10.5 Summary 444 11 Large-Scale AC and DC Networks 447 11.1 Overview 447 11.2 Spatial Decomposition and Parallelism 449 11.2.1 Functional Decomposition for Large-Scale Real-Time Emulation 449 11.2.2 Hardware Module Parallelism 451 11.3 Multi-FPGA Hardware Design for Real-Time EMT Emulation 453 11.3.1 Case I: 3-FPGA Hardware Design 454 11.3.2 Case II: 10-FPGA Hardware Design 457 11.3.3 Performance and Scalability of the Real-Time EMT Emulator 460 11.4 CIGRÉ DC Grid Hybrid Modeling Methodology 465 11.4.1 Network Topology 467 11.4.2 Control Scheme 467 11.4.3 Hybrid Modeling Methodology 468 11.4.3.1 Device-Level Electrothermal Model 469 11.4.3.2 Equivalent Circuit Model 469 11.4.3.3 Average Value Model 471 11.4.3.4 Transmission Line Model 471 11.4.4 Real-Time MPSoC-FPGA Based DC Grid Emulator 471 11.4.4.1 System Decomposition 471 11.4.4.2 Hardware Resource Allocation and Task Partitioning 472 11.4.4.3 Design and Implementation 474 11.4.5 Real-Time Emulation Results and Validation 475 11.4.5.1 Steady-State Operation 475 11.4.5.2 Power Flow Command Change 477 11.4.5.3 DC Fault 477 11.5 Real-Time Co-Emulation Framework for Cyber-Physical Systems 479 11.5.1 Communication Network Simulation and Co-Simulation 481 11.5.2 Real-Time Co-Emulation Framework 484 11.5.2.1 RTCE Hardware Architecture 484 11.5.3 Hardware Implementation of RTCE 487 11.5.3.1 Multi-Board EMT Emulation 488 11.5.3.2 Communication Protocol and Implementation 489 11.5.4 Real-Time Emulation Results and Verification 491 11.5.4.1 Processing Delay and Hardware Resource Cost 491 11.5.4.2 Case Study 1: Over-Current Fault 492 11.5.4.3 Case Study 2: Communication Link Failure 493 11.6 Faster-Than-Real-Time Hybrid Dynamic-EMT Emulation of AC–DC Grids 495 11.6.1 Flexible Time-Stepping Algorithm for Dynamic Emulation 496 11.6.1.1 Transient Stability Emulation Methodology 496 11.6.1.2 Local Equipment Based Flexible Time-stepping 497 11.6.2 AC–DC Grid Component Modeling 498 11.6.2.1 AC–DC Grid Interface 498 11.6.2.2 AC Grid Modeling 499 11.6.2.3 DC Grid Modeling 501 11.6.3 FTRT Emulation on FPGAs 503 11.6.4 FTRT Emulation Results and Validation 505 11.6.4.1 Three-Phase-to-Ground Fault 506 11.6.4.2 Generator Outage and Sudden Load Change 507 11.7 Summary 510 Bibliography 513 Appendix A Parameters for Case Studies 531 A.1 Chapter 2 531 A.1.1 Case in Section 2.7 531 A.1.2 Cases in Section 2.8 531 A.2 Chapter 3 531 A.2.1 Cases in Section 3.2 531 A.2.1.1 Cases Study I 531 A.2.1.2 Cases Study II 532 A.2.2 Cases in Section 3.3 532 A.2.2.1 Transformer 532 A.2.2.2 System 532 A.2.3 Cases in Section 3.4 532 A.3 Chapter 4 533 A.3.1 UM Case in Section 4.2 533 A.3.2 Cases in Section 4.3 534 A.3.2.1 State-Space Matrices of Rotating Machines 534 A.3.2.2 Parameters of Rotating Machines 538 A.3.3 MEC Case in Section 4.4 538 A.4 Chapter 5 538 A.5 Chapter 6 539 A.5.1 Cases in Section 6.2 539 A.5.2 Cases in Section 6.3 540 A.6 Chapter 7 540 A.7 Chapter 8 541 A.7.1 Equivalenced Device-Level Model in Section 8.3 541 A.7.2 MMC-IM Case in Section 8.4 541 A.7.3 MVDC Case in Section 8.5 541 A.7.4 MTDC Case in Section 8.6 541 A.8 Chapter 9 541 A.9 Chapter 10 542 A.9.1 HHB Case 542 A.9.2 UFMCB Case 542 A.10 Chapter 11 543 A.10.1 CIGRÉ B4 DC Grid Test System 543 Index 545

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Book SynopsisBackscattering and RF Sensing for Future Wireless Communication Discover what lies ahead in wireless communication networks with this insightful and forward-thinking book written by experts in the fieldBackscattering and RF Sensing for Future Wireless Communication delivers a concise and insightful picture of emerging and future trends in increasing the efficiency and performance of wireless communication networks. The book shows how the immense challenge of frequency saturation could be met via the deployment of intelligent planar electromagnetic structures. It provides an in-depth coverage of the fundamental physics behind these structures and assesses the enhancement of the performance of a communication network in challenging environments, like densely populated urban centers. The distinguished editors have included resources from a variety of leading voices in the field who discuss topics such as the engineering of metasurfaces at a large scale, the electromagnetic analysis of pTable of Contents 1. Intelligent Reflective Surfaces – State of the art Jalil ur Rehman Kazim, Hasan T. Abbas, Muhammad A. Imran, Qammer H. Abbasi 2. Signal Modulation Schemes in Backscatter Communications Yuan Ding, George Goussetis, Ricardo Correia, Nuno Borges Carvalho, Romwald Lihakanga, and Chaoyun Song 3. Electromagnetic Waves Scattering Characteristics of Metasurfaces Muhammad Ali Babar Abbasi, Dmitry E. Zelenchuk, Abdul Quddious 4. Metasurfaces Based on Huygen’s Wave Front Manipulation: A review Abubakar Sharif, Jun Ouyang, Ayman Abdulhadi Althuwayb, Kamran Arshad, Muhammad A. Imran, Qammer H. Abbasi 5. Metasurface: An Insight into Its Applications Fahad Ahmed and Nosherwan Shoaib 6. The Role of Smart Metasurfaces in Smart Grid Energy Management I. Safak Bayram, Muhammad Ismail, and Raka Jovanovic 7. Passive UHF RFID Tag Antennas Based Sensing for Internet of Things Paradigm Abubakar Sharif, Jun Ouyang, Kamran Arshad, Muhammad A. Imran, Qammer H. Abbasi 8. RF Sensing for Healthcare Applications Syed Aziz Shah, Hasan Abbas, Muhammad A. Imran and Qammer H. Abbasi 9. Electromagnetic Wave Manipulation with Metamaterials and Metasurfaces for Future Communication Technologies Muhammad Qasim Mehmood, Junsuk Rho, and Muhammad Zubair 10. Conclusion Qammer H. Abbasi, Hasan T. Abbas, Akram Alomainy, and Muhammad A. Imran

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Book SynopsisIndustry 4.0 Vision for the Supply of Energy and Materials Explore the impact of Industry 4.0 technologies on the supply chain with this authoritative text written by a leader in his field In Industry 4.0 Vision for the Supply of Energy and Materials, distinguished researcher and editor, Dr. Mahdi Sharifzadeh, delivers thematic, analytic, and applied discussions of the Industry 4.0 vision for supply chain design and operation. The book compiles all current aspects and emerging notions of Industry 4.0 into clusters of enablers and analytics of Supply Chain 4.0. Their multifaceted and highly interconnected nature is discussed at length, as are their diverse range of applications. You will discover uses of these new technologies ranging from the supply of conventional energy networks to renewables, pharmaceuticals, and additive manufacturing. You will also learn about their implications for economic prosperity and environmental sustainability. Table of ContentsPreface vii Part I Industry 4.0 Drivers 1 1 Connectivity through Wireless Communications and Sensors 3 2 Blockchain and Smart Contracts 59 3 Robotics: A Key Driver of Industry 4.0 73 4 Cloud Computing and Its Impact on Industry 4.0: An Overview 99 5 Applications of Artificial Intelligence and Big Data in Industry 4.0 Technologies 121 Part II Industry 4.0 Technologies 159 6 Multi-Vector Internet of Energy (IoE): A Key Enabler for the Integration of Conventional and Renewable Power Generation 161 7 The Economic Implication of Integrating Investment Planning and Generation Scheduling: The Application of Big Data Analytics and Machine Learning 189 8 A Systematic Method for Wireless Sensor Placement: A Fault-Tolerant Communi cation Solution for Monitoring Water Distribution Networks 221 9 An Overview of the Evolution of Oil and Gas 4.0 241 10 Electrification of Transportation: Transition Toward Energy Sustainability 269 11 Computer-Aided Molecular Design: Accelerating the Commercialization Cycle 297 12 Pharmaceutical Industry: Challenges and Opportunities for Establishing Pharma 4.0 313 13 Additive Manufacturing: A Game-Changing Paradigm in Manufacturing and Supply Chains 339 Glossary 359 Index 371

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Book SynopsisTable of ContentsBiographies xv Contributors List xvii Foreword xxi Preface xxiii Section 1 Sociotechnical System Types 1 1 Introduction to the Human Systems Engineering Framework 3Holly A. H. Handley 1.1 Introduction 3 1.2 Human-Centered Disciplines 3 1.3 Human Systems Engineering 4 1.4 Development of the HSE Framework 5 1.5 HSE Applications 7 1.6 Conclusion 9 References 9 2 Human Interface Considerations for Situational Awareness 11Christian G. W. Schnedler and Michael Joy 2.1 Introduction 11 2.2 Situational Awareness: A Global Challenge 12 2.3 Putting Situational Awareness in Context: First Responders 13 2.4 Deep Dive on Human Interface Considerations 14 2.5 Putting Human Interface Considerations in Context: Safe Cities 15 2.6 Human Interface Considerations for Privacy-Aware SA 16 Reference 17 3 Utilizing Artificial Intelligence to Make Systems Engineering More Human 19Philip S. Barry and Steve Doskey 3.1 Introduction 19 3.2 Changing Business Needs Drive Changes in Systems Engineering 20 3.3 Epoch 4: Delivering Capabilities in the Sociotechnical Ecosystem 21 3.3.1 A Conceptual Architecture for Epoch 4 22 3.3.2 Temporal Sociotechnical Measures 22 3.3.3 Systems Engineering Frameworks 23 3.3.3.1 Sociotechnical Network Models 23 3.3.3.2 Digital Twins 23 3.4 The Artificial Intelligence Opportunity for Building Sociotechnical Systems 24 3.5 Using AI to Track and Interpret Temporal Sociotechnical Measures 25 3.6 AI in Systems Engineering Frameworks 25 3.7 AI in Sociotechnical Network Models 26 3.8 AI-Based Digital Twins 27 3.9 Discussion 27 3.10 Case Study 30 3.11 Systems Engineering Sociotechnical Modeling Approach 31 3.11.1 Modeling the Project 33 3.12 Results 36 3.13 Summary 38 References 39 4 Life Learning of Smart Autonomous Systems for Meaningful Human-Autonomy Teaming 43Kate J. Yaxley, Keith F. Joiner, Jean Bogais, and Hussein A. Abbass 4.1 Introduction 43 4.2 Trust in Successful Teaming 45 4.3 Meaningful Human-Autonomy Teaming 46 4.4 Systematic Taxonomy for Iterative Through-Life Learning of SAS 47 4.5 Ensuring Successful SAS 51 4.6 Developing Case Study: Airborne Shepherding SAS 53 4.7 Conclusion 57 Acknowledgment 58 References 58 Section 2 Domain Deep Dives 63 5 Modeling the Evolution of Organizational Systems for the Digital Transformation of Heavy Rail 65Grace A. L. Kennedy, William R. Scott, Farid Shirvani, and A. Peter Campbell 5.1 Introduction 65 5.2 Organizational System Evolution 66 5.2.1 Characteristics of Organizational Systems 66 5.2.2 The Organization in Flux 67 5.2.3 Introducing New Technologies 68 5.3 Model-Based Systems Engineering 70 5.4 Modeling Approach for the Development of OCMM 71 5.4.1 Technology Specification 72 5.4.2 Capture System Change 73 5.4.3 Capture Organizational Changes 73 5.4.4 Manage Organization Change 73 5.4.5 Analyze Emergent System 73 5.5 Implementation 74 5.5.1 User Portals 75 5.5.2 OCMM Metamodel 75 5.6 Case Study: Digital Transformation in the Rail Industry 78 5.6.1 Technology Specification 79 5.6.2 Capture System Change 79 5.6.3 Capture Organization Changes 80 5.6.4 Organization Change Management 84 5.6.5 Analyze Emergent System 85 5.6.5.1 Situation Awareness 85 5.6.5.2 Workload Analysis 90 5.7 OCMM Reception 91 5.8 Summary and Conclusions 94 References 94 6 Human Systems Integration in the Space Exploration Systems Engineering Life Cycle 97George Salazar and Maria Natalia Russi-Vigoya 6.1 Introduction 97 6.2 Spacecraft History 98 6.2.1 Mercury/Gemini/Apollo 98 6.2.2 Space Shuttle 100 6.2.3 International Space Station 101 6.2.4 Orion Spacecraft 101 6.3 Human Systems Integration in the NASA Systems Engineering Process 103 6.3.1 NASA Systems Engineering Process and HSI 103 6.4 Mission Challenges 108 6.4.1 Innovation and Future Vehicle Designs Challenge 108 6.4.2 Operations Challenges 109 6.4.3 Maintainability and Supportability Challenges 110 6.4.4 Habitability and Environment Challenges 110 6.4.5 Safety Challenges 110 6.4.6 Training Challenges 111 6.5 Conclusions 111 References 112 7 Aerospace Human Systems Integration: Evolution over the Last 40 Years 113Guy André Boy 7.1 Introduction 113 7.2 Evolution of Aviation: A Human Systems Integration Perspective 114 7.3 Evolution with Respect to Models, Human Roles, and Disciplines 116 7.3.1 From Single-Agent Interaction to Multi-agent Integration 116 7.3.2 Systems Management and Authority Sharing 117 7.3.3 Human-Centered Disciplines Involved 118 7.3.4 From Automation Issues to Tangibility Issues 119 7.4 From Rigid Automation to Flexible Autonomy 120 7.5 How Software Took the Lead on Hardware 122 7.6 Toward a Human-Centered Systemic Framework 123 7.6.1 System of Systems, Physical and Cognitive Structures and Functions 123 7.6.2 Emergent Behaviors and Properties 125 7.6.3 System of Systems Properties 126 7.7 Conclusion and Perspectives 126 References 127 Section 3 Focus on Training and Skill Sets 129 8 Building a Socio-cognitive Evaluation Framework to Develop Enhanced Aviation Training Concepts for Gen Y and Gen Z Pilot Trainees 131Alliya Anderson, Samuel F. Feng, Fabrizio Interlandi, Michael Melkonian, Vladimir Parezanović, M. Lynn Woolsey, Claudine Habak, and Nelson King 8.1 Introduction 131 8.1.1 Gamification Coupled with Cognitive Neuroscience and Data Analysis 132 8.1.2 Generational Differences in Learning 133 8.2 Virtual Technologies in Aviation 134 8.2.1 Potential Approaches for Incorporating Virtual Technologies 135 8.3 Human Systems Engineering Challenges 136 8.4 Potential Applications Beyond Aviation Training 137 8.5 Looking Forward 137 Acknowledgement 137 References 138 9 Improving Enterprise Resilience by Evaluating Training System Architecture: Method Selection for Australian Defense 143Victoria Jnitova, Mahmoud Efatmaneshnik, Keith F. Joiner, and Elizabeth Chang 9.1 Introduction 143 9.2 Defense Training System 144 9.2.1 DTS Conceptualization 144 9.2.2 DTS as an Extended Enterprise Systems 144 9.2.3 Example: Navy Training System 145 9.2.3.1 Navy Training System as a Part of DTS 145 9.2.3.2 Navy Training System as a Part of DoD 145 9.3 Concept of Resilience in the Academic Literature 147 9.3.1 Definition of Resilience: A Multidisciplinary and Historical View 147 9.3.2 Definition of Resilience: Key Aspects 147 9.3.2.1 What? (Resilience Is and Is Not) 147 9.3.2.2 Why? (Resilience Triggers) 159 9.3.2.3 How? (Resilience Mechanisms and Measures) 160 9.4 DTS Case Study Methodology 169 9.4.1 DTS Resilience Measurement Methodology 169 9.4.2 DTS Architecture 169 9.4.3 DTS Resilience Survey 172 9.4.3.1 DTS Resilience Survey Design 172 9.4.3.2 DTS Resilience Survey Conduct 172 9.5 Research Findings and Future Directions 176 References 177 10 Integrating New Technology into the Complex System of Air Combat Training 185Sarah M. Sherwood, Kelly J. Neville, Angus L. M. T. McLean, III, Melissa M. Walwanis, and Amy E. Bolton 10.1 Introduction 185 10.2 Method 187 10.2.1 Data Collection 187 10.2.2 Data Analysis 188 10.3 Results and Discussion 190 10.3.1 Unseen Aircraft Within Visual Range 191 10.3.2 Unexpected Virtual and Constructive Aircraft Behavior 193 10.3.3 Complacency and Increased Risk Taking 194 10.3.4 Human–Machine Interaction 195 10.3.5 Exercise Management 196 10.3.6 Big Picture Awareness 197 10.3.7 Negative Transfer of Training to the Operational Environment 198 10.4 Conclusion 199 Acknowledgments 202 References 202 Section 4 Considering Human Characteristics 205 11 Engineering a Trustworthy Private Blockchain for Operational Risk Management: A Rapid Human Data Engineering Approach Based on Human Systems Engineering 207Marius Becherer, Michael Zipperle, Stuart Green, Florian Gottwalt, Thien Bui-Nguyen, and Elizabeth Chang 11.1 Introduction 207 11.2 Human Systems Engineering and Human Data Engineering 207 11.3 Human-Centered System Design 208 11.4 Practical Issues Leading to Large Complex Blockchain System Development 208 11.4.1 Human-Centered Operational Risk Management 208 11.4.2 Issues Leading to Risk Management Innovation Through Blockchain 209 11.4.3 Issues in Engineering Trustworthy Private Blockchain 209 11.5 Framework for Rapid Human Systems–Human Data Engineering 210 11.6 Human Systems Engineering for Trustworthy Blockchain 210 11.6.1 Engineering Trustworthy Blockchain 210 11.6.2 Issues and Challenges in Trustworthy Private Blockchain 212 11.6.3 Concepts Used in Trustworthy Private Blockchain 213 11.6.4 Prototype Scenario for Trusted Blockchain Network 214 11.6.5 Systems Engineering of the Chain of Trust 214 11.6.6 Design Public Key Infrastructure (PKI) for Trust 215 11.6.6.1 Design of Certificate Authority (CA) 215 11.6.6.2 Design the Trusted Gateways 216 11.6.6.3 Involving Trusted Peers and Orderers 217 11.6.6.4 Facilitate Trust Through Channels 217 11.7 From Human System Interaction to Human Data Interaction 219 11.8 Future Work for Trust in Human Systems Engineering 219 11.8.1 Software Engineering of Trust for Large Engineered Complex Systems 219 11.8.2 Human-Centered AI for the Future Engineering of Intelligent Systems 220 11.8.3 Trust in the Private Blockchain for Big Complex Data Systems in the Future 220 11.9 Conclusion 221 Acknowledgment 222 References 222 12 Light’s Properties and Power in Facilitating Organizational Change 225Pravir Malik 12.1 Introduction 225 12.2 Implicit Properties and a Mathematical Model of Light 226 12.3 Materialization of Light 230 12.3.1 The Electromagnetic Spectrum 231 12.3.2 Quantum Particles 232 12.3.3 The Periodic Table and Atoms 233 12.3.4 A Living Cell 235 12.3.5 Fundamental Capacities of Self 237 12.4 Leveraging Light to Bring About Organizational Change 239 12.5 Summary and Conclusion 243 References 243 Section 5 From the Field 245 13 Observations of Real-Time Control Room Simulation 247Hugh David with an editor introduction by Holly A. H. Handley 13.1 Introduction 247 13.1.1 What Is a “Real-Time Control Room Simulator”? 247 13.1.2 What Is It Used For? 247 13.1.3 What Does It Look Like? 248 13.1.4 How Will They Develop? 249 13.2 Future General-Purpose Simulators 249 13.2.1 Future On-Site Simulators 250 13.3 Operators 251 13.4 Data 252 13.5 Measurement 252 13.5.1 Objective Measures 253 13.5.1.1 Recommended 253 13.5.1.2 Not Recommended 253 13.5.2 Subjective Measures 254 13.5.2.1 Recommended 255 13.5.2.2 Not Recommended 255 13.6 Conclusion 257 Disclaimer 257 References 257 14 A Research Agenda for Human Systems Engineering 259Andreas Tolk 14.1 The State of Human Systems Engineering 259 14.2 Recommendations from the Chapter Contributions 260 14.2.1 Data and Visualization Challenges 260 14.2.2 Next-Generation Computing 261 14.2.3 Advanced Methods and Tools 262 14.2.4 Increased Integration of Social Components into System Artifacts 263 14.3 Uniting the Human Systems Engineering Stakeholders 263 14.3.1 Transdisciplinary Approach 264 14.3.2 Common Formalisms 265 14.3.3 Common Metrics 266 14.4 Summary 266 Disclaimer 267 References 267 Index 271

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Book SynopsisDiscover the latest advances in spintronic materials, devices, and applications In Spintronics: Materials, Devices and Applications, a team of distinguished researchers delivers a holistic introduction to spintronic effects within cutting-edge materials and applications. Containing the perfect balance of academic research and practical application, the book discusses the potentialand the key limitations and challengesof spintronic devices. The latest title in the Wiley Series in Materials for Electronic and Optoelectronic Applications, Spintronics: Materials, Devices and Applications explores giant magneto-resistance (GMR) and tunneling magnetic resistance (TMR) materials, spin-transfer torque and spin-orbit torque materials, spin oscillators, and spin materials for use in artificial neural networks. Applications in multi-ferroelectric and antiferromagnetic materials are presented as well. This book also includes: A thorough introduction to recent research developments in the fields of spintronic materials, devices, and applicationsComprehensive explorations of skymions, magnetic semiconductors, and antiferromagnetic materialsPractical discussions of spin-transfer torque materials and devices for magnetic random-access memoryIn-depth examinations of giant magneto-resistance materials and devices for magnetic sensors Perfect for advanced students and researchers in materials science, physics, electronics, and computer science, Spintronics: Materials, Devices and Applications will also earn a place in the libraries of professionals working in the manufacture of optics, photonics, and nanometrology equipment.Table of ContentsList of Contributors xi Series Preface xiii Preface xv 1 Introduction 1Kaiyou Wang 2 Giant Magnetoresistance (GMR) Materials and Devices for Biomedical and Industrial Applications 3Kai Wu, Diqing Su, Renata Saha, and Jian-Ping Wang 2.1 Introduction 3 2.2 Giant Magnetoresistance (GMR) Effect 4 2.3 Different Types of GMR Sensors 7 2.3.1 Rigid GMR Sensors 7 2.3.1.1 Long-strip GMR Sensors 7 2.3.1.2 Large-area GMR Sensors 8 2.3.2 Flexible GMR Sensors 9 2.3.3 Printable GMR Sensors 11 2.3.4 Granular GMR Sensors (Thin Film- and Solution-based) 11 2.4 GMR Sensors: Surface Modification and Auxiliary Tools 12 2.4.1 GMR Sensor Surface Modification for Biomedical Applications 12 2.4.2 Integration of a Magnetic Flux Concentrator (MFC) 14 2.4.2.1 Superconducting MFC 14 2.4.2.2 Soft-ferromagnetic Material-based MFC 14 2.4.3 Integration of Microfluidic Channels 16 2.5 GMR-based Biomedical Applications 16 2.5.1 GMR-based Immunoassays 16 2.5.1.1 Wash-free and Non-wash-free Immunoassays 17 2.5.1.2 Different Immunoassay Methods 17 2.5.1.3 GMR for Disease Diagnosis 19 2.5.1.4 GMR-based Point-of-Care (POC) Devices 24 2.5.2 GMR-based Genotyping 25 2.5.3 GMR-based Bio-magnetic Field Recording 28 2.5.4 GMR-based Food and Drug Safety Supervision 32 2.6 GMR-based Industrial Applications 34 2.6.1 GMR for Position Sensing 34 2.6.2 GMR for Current Sensing 35 2.6.3 GMR for Material Defect Inspection 37 2.7 Conclusions and Outlook 39 References 40 3 Tunneling Magnetoresistance (TMR) Materials and Devices for Magnetic Sensors 51Zitong Zhou, Kun Zhang, and Qunwen Leng 3.1 Principle of Tunneling Magnetoresistance Effect 52 3.1.1 Tunneling Process 52 3.1.2 Spin-dependent Tunneling Process 53 3.1.3 The Julliére Model 54 3.1.4 Typical Structure of the Magnetic Sensing Unit 56 3.2 Material and Process 56 3.2.1 TMR Barrier Materials 56 3.2.2 Ferromagnetic Layers in TMR 59 3.2.3 TMR Film Stack 61 3.2.4 Perpendicular Magnetic Anisotropy (PMA) in TMR 65 3.2.5 Material Fabrication and Pattern Process 65 3.2.5.1 Magnetron Sputtering 66 3.2.5.2 Ion Beam Deposition (IBD) 67 3.2.5.3 Evaporation 67 3.2.5.4 Chemical Vapor Deposition (CVD) 67 3.2.5.5 Photolithography 69 3.2.5.6 Etching 69 3.3 The Noise of TMR Sensors 70 3.3.1 The Source of Noise from TMR Sensors 70 3.3.2 Methods to Suppress the Noise 72 3.3.2.1 Increase the Number of MTJs in TMR Device 72 3.3.2.2 Optimize Free Layer Volume 73 3.3.2.3 Flux Concentrator 73 3.3.2.4 Applying a Bias Magnetic Field 74 3.4 TMR Sensors and Applications 75 3.4.1 TMR Read Heads 75 3.4.2 The TMR Angle Sensors 76 3.4.3 Geomagnetic Measurement 79 3.4.4 Spin-MEMS Combined Application 80 3.4.5 Nondestructive Testing (NDT) 82 3.4.6 Ultra-low Magnetic Field Detection: Biosensor 83 3.5 Conclusion 85 References 86 4 Spin-Transfer Torque Materials and Devices for Magnetic Random-Access Memory (STT-MRAM) 93Yan Cui and Jun Luo 4.1 The Background and Mechanism of STT-MRAM 93 4.1.1 The Background of STT-MRAM 93 4.1.2 The Mechanism of STT-MRAM 93 4.1.2.1 LLGS Equation 93 4.1.2.2 The Write Mechanism of STT-MRAM 94 4.1.2.3 The Magnetism of STT-MTJ 97 4.1.2.4 The Switching Properties of STT-MTJ 99 4.2 The Integrated Process of STT-MRAM 102 4.2.1 CMP Technology 102 4.2.2 Magnetic Film Deposition Technology 103 4.2.3 Photolithography Technology 103 4.2.4 Etching Technology 103 4.2.5 Dielectric Isolation Technology 104 4.2.6 Contact Technology 104 4.2.7 Passivation Deposition 104 4.3 Testing of the STT-MTJ Device 105 4.4 The Development Status of STT-MRAM 105 References 107 5 Spin-Orbit Torque (SOT) Materials and Devices 113Yucai Li, Kevin William Edmonds, and Kaiyou Wang 5.1 Spin-Orbit Coupling in Materials 113 5.2 Manipulation of Magnetic Materials by SOT 116 5.2.1 The Mechanism of SOT in Ferromagnets 116 5.2.2 Measurement Techniques of SOT 117 5.2.3 Field-Free SOT Magnetization Switching in Ferromagnets 119 5.2.4 Domain Wall and Skyrmion Motion Driven by SOT 121 5.2.5 Manipulation of Antiferromagnets by SOT 122 5.3 SOT Materials 123 5.3.1 Traditional Materials 123 5.3.2 Interfacial Engineering 124 5.3.3 Oxide Heterostructures 125 5.3.4 The van der Waals Materials and Topological Materials 125 5.4 Devices and Application 128 5.4.1 SOT-MTJ and SOT-MRAM 128 5.4.2 In-memory Computing 129 5.4.3 SOT Artificial Intelligence Device 130 5.4.4 Internet of Things 131 5.5 Conclusion 131 References 132 6 Spin Oscillators 139Huayao Tu and Zhongming Zeng 6.1 Introduction 139 6.2 Fundamental Physics 140 6.2.1 Spin Transfer Torque and Magnetization Dynamics 140 6.2.2 Spin Hall Effect (SHE) and Spin-Orbit Torque (SOT) 141 6.2.3 Operation Principle of SO 142 6.3 Device Classification 143 6.3.1 Geometries 143 6.3.2 Magnetic Equilibrium States 145 6.3.3 Material Structures 145 6.3.3.1 Spin Valves 145 6.3.3.2 Magnetic Tunnel Junctions 146 6.3.3.3 Bilayer 146 6.3.3.4 Single Layer 147 6.4 Emerging Spin-torque Oscillators Based on Magnetic Solitons 148 6.4.1 Vortex 148 6.4.2 Skyrmion 149 6.5 Functional Properties 150 6.5.1 Frequency 150 6.5.1.1 Modulation Properties 152 6.5.2 Output Power 152 6.5.3 Linewidth 155 6.5.4 Phase-locking and Synchronization 157 6.6 Applications 159 6.6.1 Microwave Source 159 6.6.2 Spin Wave Emitter 160 6.6.3 Microwave Detector and Energy Harvester 160 6.6.4 Magnetic Field Detector 163 6.6.5 Neuromorphic Computing 164 6.7 Summary and Outlook 166 References 167 7 Magnetic Tunnel Junctions for Artificial Neural Network 179Meiyin Yang, Tengzhi Yang, and Jun Luo 7.1 Introduction of Neural Computing 179 7.2 Hardware Requirements for an Artificial Intelligence Neural Network 182 7.3 Introduction to Magnetic Tunnel Junction Devices 183 7.4 Magnetic Tunnel Junction for Neuron Hardware 185 7.4.1 Introduction of STT-MTJ and SOT-MTJ 185 7.4.2 Different MTJ-Based Neuron Hardware 186 7.4.2.1 Step Function 187 7.4.2.2 Nonlinear Activation Function 188 7.4.2.3 Spike or Probability Based Neuron 189 7.5 Magnetic Tunnel Junctions for Synaptic Devices 192 7.6 Learning Methods Suitable for MTJs 194 7.7 Summary and Outlook 195 References 195 8 Three-Dimensional Magnetic Structures of B20 Chiral Magnets 203Kejing Ran, Dongsheng Song, Weiwei Wang, Haifeng Du, and Shilei Zhang 8.1 Theoretical Development 203 8.2 Observation Technique 206 8.2.1 Electron Holography 206 8.2.1.1 Historical Survey 206 8.2.1.2 Experimental Setup 207 8.2.2 Resonant Elastic X-ray Scattering 209 8.2.2.1 Historical Survey 209 8.2.2.2 Theoretical Treatment 210 8.2.2.3 Experimental Setup 212 8.3 Experimental Results 214 8.3.1 Magnetic Bobbers 214 8.3.2 Surface Twists 216 References 217 9 Multiferroelectric Materials 221Xiaobin Guo and Li Xi 9.1 Electric Field-driven Magnetization Switching 222 9.2 Electric Field-driven Exchange Bias Reversal and Antiferromagnetic Domain Wall Motion 229 9.3 Electric Field-driven Antiferromagnetic Vector Switching 237 Acknowledgements 239 References 240 10 Robust Manipulation of Magnetic Properties in (Ga,Mn)As 243Hailong Wang and Jianhua Zhao 10.1 Background and Introduction 243 10.2 Electric Field Effects on the Magnetic Properties of (Ga,Mn)As 245 10.3 Manipulation of the Magnetism in (Ga,Mn)As by Light and Strain 256 10.4 Giant Modulation of Magnetism via Organic Molecules 257 10.5 Conclusion and Outlook 260 Acknowledgements 262 References 262 11 Antiferromagnetic Materials and Their Manipulations 271Xionghua Liu and Kaiyou Wang 11.1 Introduction 271 11.2 Antiferromagnetic Materials 272 11.2.1 Metallic Antiferromagnets 272 11.2.2 Insulating Antiferromagnets 273 11.2.3 Semiconducting and Semimetallic Antiferromagnets 274 11.3 Manipulations of Antiferromagnetic States 275 11.3.1 Magnetic Control of Antiferromagnets 275 11.3.2 Strain Control of Antiferromagnets 277 11.3.3 Optical Control of Antiferromagnets 279 11.3.4 Electrical Control of Antiferromagnets 281 11.4 Topological Antiferromagnetic Spintronics 283 11.5 Summaries and Prospects 286 References 286 12 Prospects 295Meiyin Yang and Kaiyou Wang Index 299

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Book SynopsisTable of ContentsPreface xi Acknowledgments xix About the Authors xxi 1 Introduction: Multi-agent Coordination by Reinforcement Learning and Evolutionary Algorithms 1 1.1 Introduction 2 1.2 Single Agent Planning 4 1.2.1 Terminologies Used in Single Agent Planning 4 1.2.2 Single Agent Search-Based Planning Algorithms 10 1.2.2.1 Dijkstra’s Algorithm 10 1.2.2.2 A∗ (A-star) Algorithm 11 1.2.2.3 D∗ (D-star) Algorithm 15 1.2.2.4 Planning by STRIPS-Like Language 15 1.2.3 Single Agent RL 17 1.2.3.1 Multiarmed Bandit Problem 17 1.2.3.2 DP and Bellman Equation 20 1.2.3.3 Correlation Between RL and DP 21 1.2.3.4 Single Agent Q-Learning 21 1.2.3.5 Single Agent Planning Using Q-Learning 24 1.3 Multi-agent Planning and Coordination 25 1.3.1 Terminologies Related to Multi-agent Coordination 25 1.3.2 Classification of MAS 26 1.3.3 Game Theory for Multi-agent Coordination 28 1.3.3.1 Nash Equilibrium 31 1.3.3.2 Correlated Equilibrium 36 1.3.3.3 Static Game Examples 38 1.3.4 Correlation Among RL, DP, and GT 40 1.3.5 Classification of MARL 40 1.3.5.1 Cooperative MARL 42 1.3.5.2 Competitive MARL 56 1.3.5.3 Mixed MARL 59 1.3.6 Coordination and Planning by MAQL 84 1.3.7 Performance Analysis of MAQL and MAQL-Based Coordination 85 1.4 Coordination by Optimization Algorithm 87 1.4.1 PSO Algorithm 88 1.4.2 Firefly Algorithm 91 1.4.2.1 Initialization 92 1.4.2.2 Attraction to Brighter Fireflies 92 1.4.2.3 Movement of Fireflies 93 1.4.3 Imperialist Competitive Algorithm 93 1.4.3.1 Initialization 94 1.4.3.2 Selection of Imperialists and Colonies 95 1.4.3.3 Formation of Empires 95 1.4.3.4 Assimilation of Colonies 96 1.4.3.5 Revolution 96 1.4.3.6 Imperialistic Competition 97 1.4.4 Differential Evolution Algorithm 98 1.4.4.1 Initialization 99 1.4.4.2 Mutation 99 1.4.4.3 Recombination 99 1.4.4.4 Selection 99 1.4.5 Off-line Optimization 99 1.4.6 Performance Analysis of Optimization Algorithms 99 1.4.6.1 Friedman Test 100 1.4.6.2 Iman–Davenport Test 100 1.5 Summary 101 References 101 2 Improve Convergence Speed of Multi-Agent Q-Learning for Cooperative Task Planning 111 2.1 Introduction 112 2.2 Literature Review 116 2.3 Preliminaries 118 2.3.1 Single Agent Q-learning 119 2.3.2 Multi-agent Q-learning 119 2.4 Proposed MAQL 123 2.4.1 Two Useful Properties 124 2.5 Proposed FCMQL Algorithms and Their Convergence Analysis 128 2.5.1 Proposed FCMQL Algorithms 129 2.5.2 Convergence Analysis of the Proposed FCMQL Algorithms 130 2.6 FCMQL-Based Cooperative Multi-agent Planning 131 2.7 Experiments and Results 134 2.8 Conclusions 141 2.9 Summary 143 2.A More Details on Experimental Results 144 2.A.1 Additional Details of Experiment 2.1 144 2.A.2 Additional Details of Experiment 2.2 159 2.A.3 Additional Details of Experiment 2.4 161 References 162 3 Consensus Q-Learning for Multi-agent Cooperative Planning 167 3.1 Introduction 167 3.2 Preliminaries 169 3.2.1 Single Agent Q-Learning 169 3.2.2 Equilibrium-Based Multi-agent Q-Learning 170 3.3 Consensus 171 3.4 Proposed CoQL and Planning 173 3.4.1 Consensus Q-Learning 173 3.4.2 Consensus-Based Multi-robot Planning 175 3.5 Experiments and Results 176 3.5.1 Experimental Setup 176 3.5.2 Experiments for CoQL 177 3.5.3 Experiments for Consensus-Based Planning 177 3.6 Conclusions 179 3.7 Summary 180 References 180 4 An Efficient Computing of Correlated Equilibrium for Cooperative Q-Learning-Based Multi-Robot Planning 183 4.1 Introduction 183 4.2 Single-Agent Q-Learning and Equilibrium-Based MAQL 186 4.2.1 Single Agent Q-Learning 187 4.2.2 Equilibrium-Based MAQL 187 4.3 Proposed Cooperative MAQL and Planning 188 4.3.1 Proposed Schemes with Their Applicability 189 4.3.2 Immediate Rewards in Scheme-I and -II 190 4.3.3 Scheme-I-Induced MAQL 190 4.3.4 Scheme-II-Induced MAQL 193 4.3.5 Algorithms for Scheme-I and II 200 4.3.6 Constraint ΩQL-I/ΩQL-II(CΩQL-I/CΩQL-II) 201 4.3.7 Convergence 201 4.3.8 Multi-agent Planning 207 4.4 Complexity Analysis 209 4.4.1 Complexity of CQL 210 4.4.1.1 Space Complexity 210 4.4.1.2 Time Complexity 210 4.4.2 Complexity of the Proposed Algorithms 210 4.4.2.1 Space Complexity 211 4.4.2.2 Time Complexity 211 4.4.3 Complexity Comparison 213 4.4.3.1 Space Complexity 213 4.4.3.2 Time Complexity 214 4.5 Simulation and Experimental Results 215 4.5.1 Experimental Platform 215 4.5.1.1 Simulation 215 4.5.1.2 Hardware 216 4.5.2 Experimental Approach 217 4.5.2.1 Learning Phase 217 4.5.2.2 Planning Phase 217 4.5.3 Experimental Results 218 4.6 Conclusion 226 4.7 Summary 226 4.A Supporting Algorithm and Mathematical Analysis 227 References 228 5 A Modified Imperialist Competitive Algorithm for Multi-Robot Stick-Carrying Application 233 5.1 Introduction 234 5.2 Problem Formulation for Multi-Robot Stick-Carrying 239 5.3 Proposed Hybrid Algorithm 242 5.3.1 An Overview of ICA 242 5.3.1.1 Initialization 242 5.3.1.2 Selection of Imperialists and Colonies 243 5.3.1.3 Formation of Empires 243 5.3.1.4 Assimilation of Colonies 244 5.3.1.5 Revolution 244 5.3.1.6 Imperialistic Competition 245 5.4 An Overview of FA 247 5.4.1 Initialization 247 5.4.2 Attraction to Brighter Fireflies 247 5.4.3 Movement of Fireflies 248 5.5 Proposed ICFA 248 5.5.1 Assimilation of Colonies 251 5.5.1.1 Attraction to Powerful Colonies 251 5.5.1.2 Modification of Empire Behavior 251 5.5.1.3 Union of Empires 252 5.6 Simulation Results 254 5.6.1 Comparative Framework 254 5.6.2 Parameter Settings 254 5.6.3 Analysis on Explorative Power of ICFA 254 5.6.4 Comparison of Quality of the Final Solution 255 5.6.5 Performance Analysis 258 5.7 Computer Simulation and Experiment 265 5.7.1 Average Total Path Deviation (ATPD) 265 5.7.2 Average Uncovered Target Distance (AUTD) 265 5.7.3 Experimental Setup in Simulation Environment 265 5.7.4 Experimental Results in Simulation Environment 266 5.7.5 Experimental Setup with Khepera Robots 268 5.7.6 Experimental Results with Khepera Robots 269 5.8 Conclusion 270 5.9 Summary 272 5.A Additional Comparison of ICFA 272 References 275 6 Conclusions and Future Directions 281 6.1 Conclusions 281 6.2 Future Directions 283 Index 285

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Book SynopsisTable of ContentsAbout the Author xi Preface xiii Acknowledgments xv 1 Introduction 1 1.1 Scope 1 1.2 Background 2 2 Pole Structures 7 2.1 General 7 2.2 Wood Pole Strength 8 2.3 Loads 13 2.4 Embedment Depth 15 2.5 Guying 17 2.6 Column Buckling 19 2.7 Grounding and Bonding 22 3 Pole Installation and Maintenance 23 3.1 Pole Placement 23 3.2 Guys and Anchors 24 3.3 Pole Maintenance 26 4 Wires, Conductors, and Cables 31 4.1 Categories 31 4.2 Messenger Wire/Strand 31 4.3 Electric Supply (Power) Cables 33 4.4 Communications Cables 35 4.5 Wireless Attachments 38 5 Cable Installation 39 5.1 Conductor and Cable Placement 39 5.2 Lashing Operation 40 5.3 Overlashing 41 6 NESC® Requirements (Strength and Loading) 45 6.1 National Electrical Safety Code (NESC) 45 6.2 Loading Requirements 46 6.3 Strength Requirements 49 6.4 Wire Tensions 52 6.5 Guyed Poles 53 6.6 Extreme Wind Loads (“60 ft Limit”) 54 6.7 Allowable Deterioration 56 6.8 Overlashed Cables 57 6.9 Software Tools and Pole Loading Analysis 60 7 NESC® Requirements (Clearances) 63 7.1 Clearances 63 7.2 Clearance Zones 63 7.3 Clearances Above Surfaces and Buildings 66 7.4 Clearances Between Wires 67 7.5 Overlashed Cables 67 8 Principles of Wire Sag 71 8.1 Catenary 71 8.2 Initial and Final Sag 72 8.3 Sag–Tension Relationship 72 8.4 Determining Change in Sag (and Tension) 73 8.5 Ruling Span 76 8.6 Point Load 77 9 General Order 95 (California) 81 9.1 General Order 95 (GO 95) 81 9.2 Loading Requirements 81 9.3 Strength Requirements 83 9.4 Clearances 84 10 Examples 85 10.1 Purpose 85 10.2 Tangent Line 85 10.3 Line Angle 88 10.4 Line Angle – Buckling Consideration 90 10.5 Additional Attachment 94 10.6 Summary 96 Appendix A Properties of Messenger Strands 99 Appendix B Wireless Attachments 101 Appendix C Extreme Wind and Extreme Ice Loadings 103 Appendix D Solution of Cubic Equation 107 Appendix E Point Load 109 E.1 Parabolic Model 109 E.2 Intersecting Straight Lines Model 111 Glossary 115 References 121 Index 123

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Book SynopsisExplore an insightful summary of the major self-containedaiding technologies for pedestrian navigation from established and emerging leaders in the field Pedestrian Inertial Navigation with Self-Contained Aidingdeliversa comprehensive and broad treatment ofself-contained aiding techniques in pedestrian inertial navigation. The book combines an introduction to the general concept of navigationand major navigation and aiding techniques with more specific discussions of topics central to the field, as well as an exploration of the future of the future of the field: Ultimate Navigation Chip (uNavChip) technology. The most commonly used implementation of pedestrian inertial navigation, strapdown inertial navigation, is discussed at length, as are the mechanization, implementation, error analysis, and adaptivity of zero-velocity update aided inertial navigation algorithms.The book demonstrates the implementation of ultrasonic sensors, ultra-wide band (UWB) sensTable of ContentsAuthor Biographies xi List of Figures xiii List of Tables xix 1 Introduction 1 1.1 Navigation 1 1.2 Inertial Navigation 2 1.3 Pedestrian Inertial Navigation 5 1.3.1 Approaches 6 1.3.2 IMU Mounting Positions 7 1.3.3 Summary 8 1.4 Aiding Techniques for Inertial Navigation 9 1.4.1 Non-self-contained Aiding Techniques 9 1.4.1.1 Aiding Techniques Based on Natural Signals 9 1.4.1.2 Aiding Techniques Based on Artificial Signals 10 1.4.2 Self-contained Aiding Techniques 11 1.5 Outline of the Book 13 References 13 2 Inertial Sensors and Inertial Measurement Units 17 2.1 Accelerometers 17 2.1.1 Static Accelerometers 17 2.1.2 Resonant Accelerometers 19 2.2 Gyroscopes 21 2.2.1 Mechanical Gyroscopes 21 2.2.2 Optical Gyroscopes 22 2.2.2.1 Ring Laser Gyroscopes 22 2.2.2.2 Fiber Optic Gyroscopes 23 2.2.3 Nuclear Magnetic Resonance Gyroscopes 24 2.2.4 MEMS Vibratory Gyroscopes 24 2.2.4.1 Principle of Operation 25 2.2.4.2 Mode of Operation 25 2.2.4.3 Error Analysis 27 2.3 Inertial Measurement Units 28 2.3.1 Multi-sensor Assembly Approach 28 2.3.2 Single-Chip Approach 29 2.3.3 Device Folding Approach 30 2.3.4 Chip-Stacking Approach 31 2.4 Conclusions 32 References 32 3 Strapdown Inertial Navigation Mechanism 37 3.1 Reference Frame 37 3.2 Navigation Mechanism in the Inertial Frame 38 3.3 Navigation Mechanism in the Navigation Frame 40 3.4 Initialization 41 3.4.1 Tilt Sensing 42 3.4.2 Gyrocompassing 43 3.4.3 Magnetic Heading Estimation 44 3.5 Conclusions 45 References 45 4 Navigation Error Analysis in Strapdown Inertial Navigation 47 4.1 Error Source Analysis 47 4.1.1 Inertial Sensor Errors 48 4.1.2 Assembly Errors 51 4.1.3 Definition of IMU Grades 53 4.1.3.1 Consumer Grade 54 4.1.3.2 Industrial Grade 54 4.1.3.3 Tactical Grade 55 4.1.3.4 Navigation Grade 55 4.2 IMU Error Reduction 55 4.2.1 Six-Position Calibration 55 4.2.2 Multi-position Calibration 57 4.3 Error Accumulation Analysis 57 4.3.1 Error Propagation in Two-Dimensional Navigation 58 4.3.2 Error Propagation in Navigation Frame 61 4.4 Conclusions 62 References 63 5 Zero-Velocity Update Aided Pedestrian Inertial Navigation 65 5.1 Zero-Velocity Update Overview 65 5.2 Zero-Velocity Update Algorithm 68 5.2.1 Extended Kalman Filter 68 5.2.2 EKF in Pedestrian Inertial Navigation 70 5.2.3 Zero-Velocity Update Implementation 70 5.3 Parameter Selection 73 5.4 Conclusions 76 References 76 6 Navigation Error Analysis in the ZUPT-Aided Pedestrian Inertial Navigation 79 6.1 Human Gait Biomechanical Model 79 6.1.1 Foot Motion in Torso Frame 80 6.1.2 Foot Motion in Navigation Frame 80 6.1.3 Parameterization of Trajectory 81 6.2 Navigation Error Analysis 83 6.2.1 Starting Point 83 6.2.2 Covariance Increase During Swing Phase 84 6.2.3 Covariance Decrease During the Stance Phase 87 6.2.4 Covariance Level Estimation 88 6.2.5 Observations 92 6.3 Verification of Analysis 93 6.3.1 Numerical Verification 93 6.3.1.1 Effect of ARW 93 6.3.1.2 Effect of VRW 95 6.3.1.3 Effect of RRW 95 6.3.2 Experimental Verification 96 6.4 Limitations of the ZUPT Aiding Technique 99 6.5 Conclusions 100 References 101 7 Navigation Error Reduction in the ZUPT-Aided Pedestrian Inertial Navigation 103 7.1 IMU-Mounting Position Selection 104 7.1.1 Data Collection 105 7.1.2 Data Averaging 105 7.1.3 Data Processing Summary 107 7.1.4 Experimental Verification 109 7.2 Residual Velocity Calibration 110 7.3 Gyroscope G-Sensitivity Calibration 115 7.4 Navigation Error Compensation Results 117 7.5 Conclusions 119 References 119 8 Adaptive ZUPT-Aided Pedestrian Inertial Navigation 121 8.1 Floor Type Detection 121 8.1.1 Algorithm Overview 122 8.1.2 Algorithm Implementation 123 8.1.2.1 Data Partition 123 8.1.2.2 Principal Component Analysis 124 8.1.2.3 Artificial Neural Network 125 8.1.2.4 Multiple Model EKF 127 8.1.3 Navigation Result 129 8.1.4 Summary 130 8.2 Adaptive Stance Phase Detection 130 8.2.1 Zero-Velocity Detector 131 8.2.2 Adaptive Threshold Determination 131 8.2.3 Experimental Verification 135 8.2.4 Summary 136 8.3 Conclusions 138 References 139 9 Sensor Fusion Approaches 141 9.1 Magnetometry 141 9.2 Altimetry 142 9.3 Computer Vision 143 9.4 Multiple-IMU Approach 145 9.5 Ranging Techniques 146 9.5.1 Introduction to Ranging Techniques 147 9.5.1.1 Time of Arrival 147 9.5.1.2 Received Signal Strength 147 9.5.1.3 Angle of Arrival 148 9.5.2 Ultrasonic Ranging 149 9.5.2.1 Foot-to-Foot Ranging 150 9.5.2.2 Directional Ranging 150 9.5.3 Ultrawide Band Ranging 153 9.6 Conclusions 154 References 154 10 Perspective on Pedestrian Inertial Navigation Systems 159 10.1 Hardware Development 159 10.2 Software Development 161 10.3 Conclusions 161 References 162 Index 163

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Book Synopsis

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Book SynopsisThis new edition of the definitive arc flash reference guide, fully updated to align with the IEEE''s updated hazard calculations An arc flash, an electrical breakdown of the resistance of air resulting in an electric arc, can cause substantial damage, fire, injury, or loss of life. Professionals involved in the design, operation, or maintenance of electric power systems require thorough and up-to-date knowledge of arc flash safety and prevention methods. Arc Flash Hazard Analysis and Mitigation is the most comprehensive reference guide available on all aspects of arc flash hazard calculations, protective current technologies, and worker safety in electrical environments. Detailed chapters cover protective relaying, unit protection systems, arc-resistant equipment, arc flash analyses in DC systems, and many more critical topics. Now in its second edition, this industry-standard resource contains fully revised material throughout, including a new chapter oTable of ContentsForeword xix Preface to Second Edition xxi Preface to First Edition xxiii Acknowledgement xxv About the Author xxvii 1 Arc Flash Hazards and Their Analyses 1 1.1 Electrical Arcs 2 1.1.1 Arc as a Heat Source 3 1.1.2 Arcing Phenomena in a Cubicle 3 1.2 Arc Flash Hazard and Personal Safety 4 1.3 Time Motion Studies 5 1.4 Arc Flash Hazards 5 1.5 Arc Blast 6 1.6 Electrical Shock Hazard 9 1.6.1 Resistance of Human Body 11 1.7 Fire Hazard 13 1.8 Arc Flash Hazard Analysis 15 1.8.1 Ralph Lee’s and NFPA Equations 17 1.8.2 IEEE 1584 Guide Equations 17 1.9 Personal Protective Equipment 21 1.10 Hazard Boundaries 23 1.10.1 Working Distance 24 1.10.2 Arc Flash Labels 24 1.11 Maximum Duration of an Arc Flash Event and Arc Flash Boundary 25 1.11.1 Arc Flash Hazard with Equipment Doors Closed 25 1.12 Reasons for Internal Arcing Faults 27 1.13 Arc Flash Hazard Calculation Steps 28 1.13.1 NFPA Table 130.7(C)(15)(a) 29 1.14 Examples of Calculations 30 1.15 Reducing Arc Flash Hazard 33 1.15.1 Reduction 34 1.15.2 Arc Flash Labels 37 Review Questions 38 References 38 2 Safety and Prevention Through Design: A New Frontier 41 2.1 Electrical Standards and Codes 42 2.2 Prevention through Design 44 2.3 Limitations of Existing Codes, Regulations, and Standards 45 2.4 Electrical Hazards 46 2.5 Changing the Safety Culture 49 2.6 Risk Analysis for Critical Operation Power Systems 49 2.6.1 Existing Systems 50 2.6.2 New Facilities 50 2.7 Reliability Analysis 51 2.7.1 Data for Reliability Evaluations 52 2.7.2 Methods of Evaluation 53 2.7.3 Reliability and Safety 53 2.8 Maintenance and Operation 54 2.8.1 Maintenance Strategies 55 2.8.2 Reliability-Centered Maintenance (RCM) 56 2.9 Safety Integrity Level and Safety Instrumented System 56 2.10 Electrical Safety in the Workplaces 58 2.10.1 Risk Assessment 58 2.10.2 Responsibility 58 2.10.3 Risk Parameters 58 2.11 Risk Reduction 61 2.12 Risk Evaluation 62 2.13 Risk Reduction Verification 63 2.14 Risk Control 63 Review Questions 64 References 64 3 Calculations According To IEEE Guide 1584, 2018 68 3.1 Model for Incident Energy Calculations 68 3.2 Electrode Configuration 69 3.3 Impact of System Grounding 69 3.4 Intermediate Average Arcing Current 70 3.5 Arcing Current Variation Factor 71 3.6 Calculation of Intermediate Incident Energy 73 3.7 Intermediate Arc Flash Boundary (AFB) 75 3.8 Enclosure Size Correction Factor 77 3.8.1 Shallow and Typical Enclosures 77 3.9 Determine Equivalent Height and Width 77 3.10 Determine Enclosure Size Correction Factor 77 3.11 Determination of Iarc, E, and AFB (600 V < Voc ≤ 15,000 V) 78 3.11.1 Arcing Current 78 3.11.2 Incident Energy (E) 78 3.11.3 Arc Flash Boundary (AFB) 79 3.12 Determination of Iarc, E, and AFB (Voc ≤ 600 V) 80 3.12.1 Arcing Current 80 3.12.2 Incident Energy 80 3.12.3 Arc Flash Boundary (AFB) 80 3.13 A Flow Chart for the Calculations 80 3.14 Examples of Calculations 81 References 82 4 Arc Flash Hazard and System Grounding 84 4.1 System and Equipment Grounding 84 4.1.1 Solidly Grounded Systems 85 4.2 Low Resistance Grounding 89 4.3 High Resistance Grounded Systems 89 4.3.1 Fault Detection, Alarms, and Isolation 92 4.4 Ungrounded Systems 96 4.5 Reactance Grounding 97 4.6 Resonant Grounding 97 4.7 Corner of Delta-Grounded Systems 97 4.8 Surge Arresters 98 4.9 Artificially Derived Neutrals 99 4.10 Multiple Grounded Systems 102 4.10.1 Comparison of Grounding Systems 102 4.11 Arc Flash Hazard in Solidly Grounded Systems 102 4.12 Protection and Coordination in Solidly Grounded Systems 107 4.12.1 Self-Extinguishing Ground Faults 110 4.12.2 Improving Coordination in Solidly Grounded Low Voltage Systems 113 4.13 Ground Fault Coordination in Low Resistance Grounded Medium Voltage Systems 116 4.13.1 Remote Tripping 119 4.13.2 Ground Fault Protection of Industrial Bus-Connected Generators 119 4.13.3 Directional Ground Fault Relays 124 4.14 Monitoring of Grounding Resistors 125 4.15 Selection of Grounding Systems 126 Review Questions 127 References 128 5 Short-Circuit Calculations According To ANSI/IEEE Standards For Arc Flash Analysis 130 5.1 Types of Calculations 131 5.1.1 Assumptions: Short-Circuit Calculations 131 5.1.2 Short-Circuit Currents for Arc Flash Calculations 132 5.2 Rating Structure of HV Circuit Breakers 132 5.3 Low-Voltage Motors 135 5.4 Rotating Machine Model 136 5.5 Calculation Methods 136 5.5.1 Simplified Method X/R ≤ 17 136 5.5.2 Simplified Method X/R > 17 137 5.5.3 E/Z Method for AC and DC Decrement Adjustments 137 5.6 Network Reduction 140 5.7 Calculation Procedure 140 5.7.1 Analytical Calculation Procedure 141 5.8 Capacitor and Static Converter Contributions to Short-Circuit Currents 143 5.9 Typical Computer-Based Calculation Results 143 5.9.1 First-Cycle or Momentary Duty Calculations 143 5.9.2 Interrupting Duty Calculations 146 5.9.3 Low Voltage Circuit Breaker Duty Calculations 146 5.10 Examples of Calculations 146 5.10.1 Calculation of Short-Circuit Duties 152 5.10.2 K-Rated 15 kV Circuit Breakers 152 5.10.3 4.16-kV Circuit Breakers and Motor Starters 157 5.10.4 Transformer Primary Switches and Fused Switches 157 5.10.5 Low Voltage Circuit Breakers 161 5.11 Thirty-Cycle Short-Circuit Currents 161 5.12 Unsymmetrical Short-Circuit Currents 162 5.12.1 Single Line-to-Ground Fault 163 5.12.2 Double Line-to-Ground Fault 165 5.12.3 Line-to-Line Fault 168 5.13 Computer Methods 171 5.13.1 Line-to-Ground Fault 172 5.13.2 Line-to-Line Fault 173 5.13.3 Double Line-to-Ground Fault 173 5.14 Short-Circuit Currents for Arc Flash Calculations 175 Review Questions 176 References 176 6 Accounting For Decaying Short-Circuit Currents In Arc Flash Calculations 178 6.1 Short Circuit of a Passive Element 178 6.2 Systems with No AC Decay 181 6.3 Reactances of a Synchronous Machine 182 6.3.1 Leakage Reactance 182 6.3.2 Subtransient Reactance 183 6.3.3 Transient Reactance 183 6.3.4 Synchronous Reactance 183 6.3.5 Quadrature-Axis Reactances 183 6.3.6 Negative Sequence Reactance 184 6.3.7 Zero Sequence Reactance 184 6.4 Saturation of Reactances 184 6.5 Time Constants of Synchronous Machines 184 6.5.1 Open-Circuit Time Constant 184 6.5.2 Subtransient Short-Circuit Time Constant 184 6.5.3 Transient Short-Circuit Time Constant 185 6.5.4 Armature Time Constant 185 6.6 Synchronous Machine Behavior on Terminal Short Circuit 185 6.6.1 Equivalent Circuits during Fault 186 6.6.2 Fault Decrement Curve 190 6.7 Short Circuit of Synchronous Motors and Condensers 194 6.8 Short Circuit of Induction Motors 194 6.9 A New Algorithm for Arc Flash Calculations with Decaying Short-Circuit Currents 197 6.9.1 Available Computer-Based Calculations 198 6.9.2 Accumulation of Energy from Multiple Sources 198 6.9.3 Comparative Calculations 200 6.10 Crowbar Methods 203 Review Questions 204 References 205 7 Protective Relaying 206 7.1 Protection and Coordination from Arc Flash Considerations 206 7.2 Classification of Relay Types 210 7.3 Design Criteria of Protective Systems 210 7.3.1 Selectivity 211 7.3.2 Speed 211 7.3.3 Reliability 211 7.3.4 Backup Protection 212 7.4 Overcurrent Protection 212 7.4.1 Overcurrent Relays 213 7.4.2 Multifunction Overcurrent Relays 215 7.4.3 IEC Curves 217 7.5 Low Voltage Circuit Breakers 219 7.5.1 Molded Case Circuit Breakers (MCCBs) 219 7.5.2 Current-Limiting MCCBs 225 7.5.3 Insulated Case Circuit Breakers (ICCBs) 227 7.5.4 Low Voltage Power Circuit Breakers (LVPCBs) 228 7.5.5 Short-Time Bands of LVPCBs Trip Programmers 230 7.6 Short-Circuit Ratings of Low Voltage Circuit Breakers 231 7.6.1 Single-Pole Interrupting Capability 235 7.6.2 Short-Time Ratings 235 7.7 Series-Connected Ratings 236 7.8 Fuses 237 7.8.1 Current-Limiting Fuses 238 7.8.2 Low Voltage Fuses 240 7.8.3 High Voltage Fuses 240 7.8.4 Electronic Fuses 241 7.8.5 Interrupting Ratings 242 7.9 Application of Fuses for Arc Flash Reduction 243 7.9.1 Low Voltage Motor Starters 243 7.9.2 Medium Voltage Motor Starters 243 7.9.3 Low Voltage Switchgear 244 7.10 Conductor Protection 247 7.10.1 Load Current Carrying Capabilities of Conductors 248 7.10.2 Conductor Terminations 249 7.10.3 Considerations of Voltage Drops 249 7.10.4 Short-Circuit Considerations 249 7.10.5 Overcurrent Protection of Conductors 251 7.11 Motor Protection 252 7.11.1 Coordination with Motor Thermal Damage Curve 253 7.12 Generator 51-V Protection 261 7.12.1 Arc Flash Considerations 262 Review Questions 265 References 265 8 Unit Protection Systems 267 8.1 Overlapping the Zones of Protection 269 8.2 Importance of Differential Systems for Arc Flash Reduction 271 8.3 Bus Differential Schemes 272 8.3.1 Overcurrent Differential Protection 272 8.3.2 Partial Differential Schemes 273 8.3.3 Percent Differential Relays 273 8.4 High Impedance Differential Relays 274 8.4.1 Sensitivity for Internal Faults 277 8.4.2 High Impedance Microprocessor-Based Multifunction Relays 278 8.5 Low Impedance Current Differential Relays 278 8.5.1 CT Saturation 282 8.5.2 Comparison with High Impedance Relays 282 8.6 Electromechanical Transformer Differential Relays 283 8.6.1 Harmonic Restraint 285 8.7 Microprocessor-Based Transformer Differential Relays 286 8.7.1 CT Connections and Phase Angle Compensation 287 8.7.2 Dynamic CT Ratio Corrections 290 8.7.3 Security under Transformer Magnetizing Currents 293 8.8 Pilot Wire Protection 294 8.9 Modern Line Current Differential Protection 296 8.9.1 The Alpha Plane 297 8.9.2 Enhanced Current Differential Characteristics 299 8.10 Examples of Arc Flash Reduction with Differential Relays 300 Review Questions 303 References 303 9 Arc Fault Detection Relays 305 9.1 Principle of Operation 306 9.2 Light Intensity 306 9.3 Light Sensor Types 307 9.4 Other Hardware 312 9.5 Selective Tripping 313 9.6 Supervision with Current Elements 315 9.7 Applications 315 9.7.1 Medium Voltage Systems 315 9.7.2 Low Voltage Circuit Breakers 317 9.7.3 Self-Testing of Sensors 317 9.8 Examples of Calculation 317 9.9 Arc Vault™ Protection for Low Voltage Systems 317 9.9.1 Detection System 321 Review Questions 323 References 323 10 Overcurrent Coordination 325 10.1 Standards and Requirements 326 10.2 Data for the Coordination Study 326 10.3 Computer-Based Coordination 328 10.4 Initial Analysis 328 10.5 Coordinating Time Interval 329 10.5.1 Relay Overtravel 329 10.6 Fundamental Considerations for Coordination 329 10.6.1 Settings on Bends of Time–Current Coordination Curves 331 10.7 Coordination on Instantaneous Basis 331 10.7.1 Selectivity between Two Series-Connected Current-Limiting Fuses 333 10.7.2 Selectivity of a Current-Limiting Fuse Downstream of Noncurrent-Limiting Circuit Breaker 333 10.7.3 Selectivity of Current-Limiting Devices in Series 337 10.8 NEC Requirements of Selectivity 340 10.8.1 Fully Selective Systems 342 10.8.2 Selection of Equipment Ratings and Trip Devices 343 10.9 The Art of Compromise 346 Review Questions 356 References 357 11 Transformer Protection 358 11.1 NEC Requirements 358 11.2 Arc Flash Considerations 360 11.3 System Configurations of Transformer Connections 361 11.3.1 Auto-Transfer of Bus Loads 366 11.4 Through Fault Current Withstand Capability 366 11.4.1 Category I 367 11.4.2 Category II 367 11.4.3 Category III and IV 367 11.4.4 Observation on Faults during Life Expectancy of a Transformer 369 11.4.5 Dry-Type Transformers 370 11.5 Constructing the through Fault Curve Analytically 374 11.5.1 Protection with Respect to Through Fault Curves 374 11.6 Transformer Primary Fuse Protection 375 11.6.1 Variations in the Fuse Characteristics 375 11.6.2 Single Phasing and Ferroresonance 377 11.6.3 Other Considerations of Fuse Protection 377 11.7 Overcurrent Relays for Transformer Primary Protection 377 11.8 Listing Requirements 379 11.9 Effect of Transformer Winding Connections 383 11.10 Requirements of Ground Fault Protection 385 11.11 Through Fault Protection 385 11.11.1 Primary Fuse Protection 385 11.11.2 Primary Relay Protection 387 11.12 Overall Transformer Protection 387 11.13 A Practical Study for Arc Flash Reduction 388 11.13.1 System Configuration 388 11.13.2 Coordination Study and Observations 388 11.13.3 Arc Flash Calculations: High Hazard Risk Category (HRC) Levels 393 11.13.4 Reducing HRC Levels with Main Secondary Circuit Breakers 395 11.13.5 Maintenance Mode Switches on Low Voltage Trip Programmers 395 11.13.6 Addition of Secondary Relay 401 Review Questions 404 References 405 12 Current Transformers 406 12.1 Accuracy Classification of CTs 407 12.1.1 Metering Accuracies 407 12.1.2 Relaying Accuracies 407 12.1.3 Relaying Accuracy Classification X 408 12.1.4 Accuracy Classification T 409 12.2 Constructional Features of CTs 409 12.3 Secondary Terminal Voltage Rating 411 12.3.1 Saturation Voltage 412 12.3.2 Saturation Factor 412 12.4 CT Ratio and Phase Angle Errors 412 12.5 Interrelation of CT Ratio and C Class Accuracy 415 12.6 Polarity of Instrument Transformers 417 12.7 Application Considerations 418 12.7.1 Select CT Ratio 418 12.7.2 Make a Single-Line Diagram of the CT Connections 420 12.7.3 CT Burden 420 12.7.4 Short-Circuit Currents and Asymmetry 420 12.7.5 Calculate Steady-State Performance 420 12.7.6 Calculate Steady-State Errors 421 12.8 Series and Parallel Connections of CTs 425 12.9 Transient Performance of the CTs 425 12.9.1 CT Saturation Calculations 426 12.9.2 Effect of Remanence 427 12.10 Practicality of Application 428 12.11 CTs for Low Resistance-Grounded Medium Voltage Systems 430 12.12 Future Directions 430 Review Questions 433 References 433 13 Arc-Resistant Equipment 435 13.1 Calculations of Arc Flash Hazard in Arc-Resistant Equipment 436 13.1.1 Probability of Arcing Fault 436 13.2 Qualifications in IEEE Guide 437 13.3 Accessibility Types 438 13.3.1 Type 1 438 13.3.2 Type 2 438 13.3.3 Suffix B 438 13.3.4 Suffix C 438 13.3.5 Suffix D 439 13.4 IEC Accessibility Types 439 13.5 Arc-Resistant Ratings 440 13.5.1 Duration Ratings 440 13.5.2 Device-Limited Ratings 441 13.5.3 Effect of Cable Connections 444 13.6 Testing According to IEEE Guide 444 13.6.1 Criterion 1 444 13.6.2 Criterion 2 445 13.6.3 Criterion 3 445 13.6.4 Criterion 4 445 13.6.5 Criterion 5 445 13.6.6 Maintenance 446 13.7 Pressure Relief 446 13.8 Venting and Plenums 448 13.8.1 Venting into Surrounding Area 448 13.8.2 Plenums 450 13.9 Cable Entries 450 Review Questions 452 References 452 14 Recent Trends and Innovations 454 14.1 Statistical Data of Arc Flash Hazards 454 14.2 Zone-Selective Interlocking 456 14.2.1 Low Voltage ZSI Systems 456 14.2.2 Zone Interlocking in Medium Voltage Systems 463 14.3 Microprocessor-Based Low Voltage Switchgear 466 14.3.1 Microprocessor-Based Switchgear Concept 466 14.3.2 Accounting for Motor Contributions 467 14.3.3 Faults on the Source Side 469 14.3.4 Arc Flash Hazard Reduction 470 14.4 Low Voltage Motor Control Centers 470 14.4.1 Desirable MCC Design Features 471 14.4.2 Recent Design Improvements 471 14.4.3 Higher Short-Circuit Withstand MCCs 478 14.5 Maintenance Mode Switch 478 14.6 Infrared Windows and Sight Glasses 480 14.7 Fault Current Limiters 483 14.8 Partial Discharge Measurements 487 14.8.1 Online versus Offline Measurements 488 14.8.2 Test Methods 489 14.8.3 Current Signature Analysis: Rotating Machines 491 14.8.4 Dissipation Factor Tip-Up 491 Review Questions 493 References 494 15 Arc Flash Hazard Calculations In Dc Systems 496 15.1 Calculations of the Short-Circuit Currents in DC Systems 497 15.2 Sources of DC Short-Circuit Currents 497 15.3 IEC Calculation Procedures 498 15.4 Short Circuit of a Lead Acid Battery 501 15.5 Short Circuit of DC Motors and Generators 505 15.6 Short-Circuit Current of a Rectifier 510 15.7 Short Circuit of a Charged Capacitor 515 15.8 Total Short-Circuit Current 516 15.9 DC Circuit Breakers and Fuses 517 15.9.1 DC Circuit Breakers 517 15.9.2 DC Rated Fuses 520 15.10 Arcing in DC Systems 520 15.11 Equations for Calculation of Incident Energy in DC Systems 525 15.12 Protection of the Semiconductor Devices 527 15.12.1 Controlled Converters 529 Review Questions 530 References 531 16 Application of Ethernet and IEC 61850 Communications 533 16.1 IEC 61850 Protocol 534 16.2 Modern IEDs 535 16.3 Substation Architecture 536 16.4 IEC 61850 Communication Structure 537 16.5 Logical Nodes 539 16.6 Ethernet Connection 539 16.7 Networking Media 543 16.7.1 Copper Twisted Shielded and Unshielded 543 16.7.2 Fiber Optic Cable 544 16.8 Network Topologies 545 16.8.1 Prioritizing GOOSE Messages 547 16.8.2 Technoeconomical Justifications 547 16.9 Application to Arc Flash Relaying and Communications 549 Review Questions 549 References 549 Appendix A Statistics and Probability Applied to Electrical Engineering 551 A.1 Mean Mode and Median 551 A.2 Mean and Standard Deviation 552 A.3 Skewness and Kurtosis 553 A.4 Normal or Gaussian Distribution 554 A.5 Curve Fitting: Least Square Line 556 References 559 Appendix B Tables for Quick Estimation of Incident Energy and PPE in Electrical Systems 560 Index 588

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Book SynopsisHigh-Density and De-Densified Smart Campus Communications Design, deliver, and implement high-density communications solutions High-density campus communications are critical in the operation of densely populated airports, stadiums, convention centers, shopping malls, classrooms, hospitals, dense smart cities, and more. They also drive Smart City and Smart Building use cases as High-Density Communications (HDC) become recognized as an essential fourth utility. However, the unique requirements and designs demanded by HDC make implementation challenging. In High-Density and De-Densified Smart Campus Communications: Technologies, Integration, Implementation and Applications, a team of experienced technology strategists delivers a one-of-a-kind treatment of the requirements, technologies, designs, solutions, and trends associated with HDC. From the functional requirements for HDC and emerging data/Wi-Fi 6/internet access/5G cellular/OTT video, and IoT automaTable of ContentsPreface xi About the Authors xiii Acknowledgments xv 1 Background and Functional Requirements for High‐Density Communications 1 1.1 Background 1 1.2 Requirements for High‐Density Communications 4 1.2.1 Pre‐pandemic/Long‐term Requirements for Airports 5 1.2.2 Pre‐pandemic/Long‐term Requirements for Stadiums 7 1.2.3 Pre‐pandemic/Long‐term Requirements for Convention Centers 7 1.2.4 Pre‐pandemic/Long‐term Requirements for Open Air Gatherings and Amusement Parks 10 1.2.5 Pre‐pandemic/Long‐term Requirements for Classrooms 11 1.2.6 Pre‐pandemic/Long‐term Requirements for Train and Subway Stations 12 1.2.7 Pre‐pandemic/Long‐term Requirements for Dense Office Environments 12 1.2.8 Ongoing Requirements for Dense Smart Warehouses and Distribution Centers 14 1.2.9 Pre‐pandemic/Long‐term Requirements for Dense Smart Cities 14 1.3 Pandemic‐Driven Social Distancing 16 1.3.1 Best Practices 16 1.3.2 Heuristic Density for the Pandemic Era 20 1.4 The Concept of a Wireless SuperNetwork 20 References 22 2 Traditional WLAN Technologies 26 2.1 Overview 26 2.2 WLAN Standards 28 2.3 WLAN Basic Concepts 29 2.3.1 PHY Layer Operation 32 2.3.2 MAC Layer Operation 36 2.4 Hardware Elements 40 2.5 KEY IEEE 802.11ac Mechanisms 42 2.5.1 Downlink Multi‐User MIMO (DL‐MU‐MIMO) 42 2.5.2 Beamforming 45 2.5.3 Dynamic Frequency Selection 45 2.5.4 Space–Time Block Coding 46 2.5.5 Product Waves 48 2.6 Brief Preview of IEEE 802.11ax 48 References 49 3 Traditional DAS Technologies 51 3.1 Overview 51 3.2 Frequency Bands of Cellular Operation 56 3.2.1 Traditional RF Spectrum 56 3.2.2 Citizens Broadband Radio Service (CBRS) 60 3.2.3 Freed‐up Satellite C‐Band 62 3.2.4 5G Bands 64 3.2.5 Motivations for Additional Spectrum 65 3.2.6 Private LTE/Private CBRS 66 3.2.7 5G Network Slicing 68 3.2.8 Supportive Technologies 68 3.3 Distributed Antenna Systems (DASs) 70 3.3.1 Technology Scope 70 3.3.2 More Detailed Exemplary Arrangement 76 3.3.3 Traffic‐aware DAS 81 3.3.4 BBU and DAS/RRU Connectivity 82 3.3.5 Ethernet/IP Transport Connectivity of DAS 84 References 84 4 Traditional Sensor Networks/IoT Services 87 4.1 Overview and Environment 87 4.2 Architectural Concepts 93 4.3 Wireless Technologies for the IoT 96 4.3.1 Pre‐5G Wireless Technologies for the IoT 100 4.3.2 NB‐IoT 104 4.3.3 Lte‐m 105 4.3.4 5G Technologies for the IoT 106 4.3.5 WAN‐Oriented IoT Connectivity Migration Strategies 108 4.4 Examples of Seven‐Layer IoT Protocol Stacks 109 4.4.1 UPnP 109 4.4.2 ZigBee 115 4.4.3 Bluetooth 116 4.5 Gateway‐Based IoT Operation 117 4.6 Edge Computing in the IoT Ecosystem 118 4.7 Session Establishment Example 121 4.8 IoT Security 121 4.8.1 Challenges 121 4.8.2 Applicable Security Mechanisms 125 4.8.3 Hardware Considerations 127 4.8.4 Other Approaches: Blockchains 132 References 132 5 Evolved Campus Connectivity 139 5.1 Advanced Solutions 140 5.1.1 802.11ax Basics 143 5.1.2 Key 802.11ax Processes 154 5.1.3 Summary 156 5.2 Voice Over Wi‐Fi (VoWi‐Fi) 158 5.3 5G Technologies 163 5.3.1 Emerging Services 164 5.3.2 New Access and Core Elements 165 5.3.3 New 5GC Architecture 168 5.3.4 Frequency Spectrum and Propagation Challenges 169 5.3.5 Resource Management 170 5.3.6 Requirements for Small Cells 175 5.3.7 Comparison to Wi‐Fi 6 178 5.4 IoT 178 5.5 5G DAS Solutions 179 5.6 Integrated Solutions 179 References 181 6 De‐densification of Spaces and Work Environments 184 6.1 Overview 184 6.2 Basic Approaches 189 6.3 RTLS Methodologies and Technologies 194 6.3.1 RFID Systems 202 6.3.2 Wi‐Fi‐based Positioning System (WPS) 205 6.3.3 Bluetooth 206 6.3.4 Uwb 207 6.3.5 Automatic Vehicle Location (AVL) 207 6.4 Standards 207 6.5 Applications 209 References 212 7 UWB‐Based De‐densification of Spaces and Work Environments 222 7.1 Review of UWB Technology 223 7.2 Carriage of Information in UWB 226 7.2.1 Pulse Communication 226 7.2.2 UWB Modulation 228 7.3 UWB Standards 232 7.4 IoT Applications for UWB 237 7.5 UWB Applications for Smart Cities and for Real‐Time Locating Systems 239 7.5.1 Applications for Smart Cities 239 7.5.2 UWB Applications to Real‐Time Location Systems 240 7.6 OSD/ODCMA Applications 248 References 253 8 RTLSs and Distance Tracking Using Wi‐Fi, Bluetooth, and Cellular Technologies 258 8.1 Overview 258 8.2 RF Fingerprinting Methods 260 8.3 Wi‐Fi RTLS Approaches 261 8.3.1 Common Approach 261 8.3.2 Design Considerations 266 8.3.3 Drawbacks and Limitations 267 8.3.4 Potential Enhancements 267 8.3.5 Illustrative Examples 269 8.4 Ble 271 8.4.1 Bluetooth and BLE Background 271 8.4.2 RTLS Applications 273 8.4.3 BLE‐Based Contact Tracing 278 8.4.4 Illustrative Examples 280 8.5 Cellular Approaches 283 8.6 Summary 286 References 288 9 Case Study of an Implementation and Rollout of a High‐Density High‐Impact Network 291 9.1 Thurgood Marshall BWI Airport Design Requirements 292 9.1.1 Broad Motivation 293 9.1.2 Status Quo Challenges 294 9.1.3 RFP Requirements 295 9.2 Overview of the Final Design 298 9.2.1 DAS Solutions 300 9.2.2 Broadband, BLE, IoT 305 10 The Age of Wi‐Fi and Rise of the Wireless SuperNetwork (WiSNET) TM 312 10.1 What Preceded the WiSNET 312 10.2 What Comes Next 313 10.3 The Super‐Integration Concept of a Wireless SuperNetwork (WiSNET) 314 10.4 The Multidimensionality of a SuperNetwork (WiSNET) 317 10.5 The Genesis of the WiSNET Concept Defined in this Text 317 10.6 The Definition and Characterization of a WiSNET 320 10.6.1 Architectural Aspects of a WiSNET 321 10.6.2 Technology Aspects of a WiSNET 325 10.6.3 Management Aspects of a WiSNET 328 10.7 Economic Advantages of a WiSNET System 331 10.8 5G Slice Capabilities 332 10.8.1 Motivations and Approaches for 5G Network Slicing 332 10.8.2 Implementation 335 10.8.3 Wi-Fi Slicing 335 10.9 Conclusion 335 References 336 Index 337

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Book SynopsisElectronics in Advanced Research Industries A one-of-a-kind examination of the latest developments in machine control In Electronics in Advanced Research Industries: Industry 4.0 to Industry 5.0 Advances, accomplished electronics researcher and engineer Alessandro Massaro delivers a comprehensive exploration of the latest ways in which people have achieved machine control, including automated vision technologies, advanced electronic and micro-nano sensors, advanced robotics, and more. The book is composed of nine chapters, each containing examples and diagrams designed to assist the reader in applying the concepts discussed within to common issues and problems in the real-world. Combining electronics and mechatronics to show how they can each be implemented in production line systems, the book presents insightful new ways to use artificial intelligence in production line machines. The author explains how facilities can upgrade their systems to an Industry Table of ContentsPreface xiii About the Author xv 1 State of the Art and Technology Innovation 1 1.1 State of the Art of Flexible Technologies in Industry 2 1.1.1 Sensors and Actuators Layer: I/O Layer 3 1.1.2 Agent/Firmware Layer: User Interface Layer 9 1.1.3 Gateway and Enterprise Service Bus Layer 9 1.1.4 IoT Middleware 10 1.1.5 Processing Layer 11 1.1.6 Application Layer 11 1.1.7 File Transfer Protocols 11 1.2 State of the Art of Scientific Approaches Oriented on Process Control and Automatisms 14 1.2.1 Architectures Integrating AI 14 1.2.2 AI Supervised and Unsupersived Algorithms 15 1.2.3 AI Image Processing 18 1.2.4 Production Process Mapping 20 1.2.5 Technologies of Industry 4.0 and Industry 5.0: Interconnection and Main Limits 21 1.2.6 Infrared Thermography in Monitoring Process 26 1.2.7 Key Parameters in Supply Chain and AI Improving Manufacturing Processes 27 1.3 Intelligent Automatic Systems in Industries 30 1.4 Technological Approaches to Transform the Production in Auto-Adaptive Control and Actuation Systems 31 1.5 Basic Concepts of Artificial Intelligence 33 1.6 Knowledge Upgrading in Industries 41 References 45 2 Information Technology Infrastructures Supporting Industry 5.0 Facilities 51 2.1 Production Process Simulation and Object Design Approaches 52 2.1.1 Object Design of a Data Mining Algorithm: Block Functions and Parameter Setting 55 2.1.2 Example 1: BPM Modeling of Wheat Storage Process for Pasta Production 59 2.1.3 Example 2: Block Diagram Design of a Servo Valve Control and Actuation System 61 2.1.4 Example 3: Block Diagram of a Liquid Production System 61 2.1.5 Example 4: UML Design of a Programmable Logic Controller System 62 2.1.6 Example 5: Electronic Logic Timing Diagram 64 2.1.7 Example 6: AR System in Kitchen Production Process 64 2.1.8 Example 7: Intelligent Canned Food Production Line 70 2.2 Electronic Logic Design Oriented on Information Infrastructure of Industry 5.0 71 2.3 Predictive Maintenance: Artificial Intelligence Failure Predictions and Information Infrastructure Layout in the Temperature Monitoring Process 74 2.4 Defect Estimation and Prediction by Artificial Neural Network 77 2.4.1 Other Methodologies to Map and Read Production Failures and Defects 79 2.5 Defect Clustering and Classification: Combined Use of the K-Means Algorithm with Infrared Thermography for Predictive Maintenance 82 2.6 Facilities of a Prototype Network Implementing Advanced Technology: Example of an Advanced Platform Suitable for Industry 5.0 Integrating Predictive Maintenance 84 2.7 Predictive Maintenance Approaches 86 2.7.1 Preventive Maintenance and Predictive Maintenance Operations in the Railway Industry 90 2.8 Examples of Advanced Infrastructures Implementing AI 93 2.9 Examples of Telemedicine Platforms Integrating Advanced Facilities 94 2.9.1 Advanced Telecardiology Platform 94 2.9.2 Advanced Teleoncology Platform 96 2.9.3 Multipurpose E-Health Platform 97 References 99 3 Human–Machine Interfaces 103 3.1 Mechatronic Machine Interface Architectures Integrating Sensor Systems 104 3.1.1 Multiple Mechatronic Boards Managing Different Production Stages 104 3.1.2 Mechatronic Boards Managing Component Processing 104 3.2 Machine-to-Machine Interfaces: New Concepts of Industry 5.0 106 3.3 Production Line Command and Actuation Interfaces in Upgraded Systems 111 3.3.1 PLC, PAC, Industrial PC, and Improvements 111 3.3.2 SCADA Systems for Centralization of Data Production 115 3.4 McCulloch–Pitts Neurons and Logic Port for Automatic Decision-Making Setting Thresholds 123 3.5 Programmable Logic Controller I/O Ports Interfacing with AI Engine 132 3.6 Human–Machine Interface for Data Transfer and AI Data Processing 134 3.7 Example of Interface Configuration of Temperature Control 135 3.8 AI Interfaces Oriented on Cybersecurity Attack Detection 136 3.9 AI Interfaces Oriented on Database Security 139 3.10 Cybersecurity Platform and AI Control Interface 148 References 151 4 Internet of Things Solutions in Industry 155 4.1 Cloud Computing IoT 156 4.1.1 IoT Agent 156 4.1.2 IoT Gateway in Smart Environments 158 4.1.3 Basic Elements of a Smart Industry Environment Controlling Production 160 4.1.3.1 Feedback Control: Basic Concepts 167 4.1.4 Augmented Reality Hardware and Cloud Computing Processing 169 4.1.5 Real-Time Control and Actuation 171 4.1.6 Localization Technologies in an Industrial Environment 175 4.1.7 GPU Processing Units 176 4.1.7.1 Performance of GPUs by Processing Binary Matrices 176 4.2 IoT and External Artificial Intelligence Engines 180 4.2.1 Artificial Engines and Server Location: Artificial Intelligence and Adaptive Production 180 4.2.2 IoT Security Systems in the Working Environment and Implementation Aspects 182 4.2.3 Example of Energy Power Control and Actuation: Energy Routing and Priority Load Management for Energy Efficiency 182 4.2.4 Online Configurators: Cloud DSS 186 4.3 Blockchain and IoT Data Storage Systems 194 4.3.1 Blockchain Implementation Rules 194 4.3.2 Blockchain and IoT Production Traceability 197 4.4 Mechatronic Machine Interface Architectures Integrating Sensor Systems 199 4.5 Multiple Mechatronic Boards Managing Different Production Stages 200 References 202 5 Advanced Robotics 203 5.1 Collaborative Robotics in Industry and Protocols 204 5.1.1 Data Protocols 206 5.1.2 Basic Concepts of Robotic Arms and Control Improvement 206 5.1.3 Collaborative Exoskeleton Communication System Protocols 212 5.1.4 Advanced Robotics and Intelligent Automation in Manufacturing: Logic Conditions and PLC Programming 213 5.2 Artificial Intelligence in Advanced Robotics and Auto-Adaptive Movement 218 5.2.1 General Technological Aspects about Auto-Adaptive Motion in Advanced Robotics 218 5.2.1.1 Main Aspects of Electrostatic Actuators 219 5.2.1.2 Microelectromechanical System Electrostatic Actuators 220 5.2.1.3 Piezoelectric Actuators 221 5.2.1.4 DC Motor Actuation 222 5.2.1.5 Intelligent Control Integrating AI: Speed Regulation 227 5.2.2 Improvement of Collaborative Exoskeletons by Auto-Adaptive Solutions Implementing Artificial Intelligence 231 5.3 Human–Robot Self-Learning Collaboration in Industrial Applications and Electronic Aspects 232 5.3.1 DC–DC Converter 232 5.3.2 Voltage Source Inverter 233 5.3.3 Current-Source Inverter 237 5.3.4 DC Voltage Source 238 5.3.5 Capacitor and Reactor Effects on Signal Control 238 5.3.6 Human-Robot System and Learning Approaches 239 5.3.6.1 Example of PID Implementation of Self-Adapting Gains 243 5.3.7 Unsupervised Learning Approaches 244 5.3.8 Soft Robotics for Intelligent Collaborative Robotics 245 5.4 Robotics in Additive Manufacturing 246 5.4.1 Additive Manufacturing in Industrial Production and Spray Technique 246 5.4.2 Artificial Intelligence Applications in Additive Manufacturing 247 5.4.3 Advanced Electronic for Design-to-Product Transformation: Laser Texturing Manufacturing and Artificial Intelligence 248 References 249 6 Advanced Optoelectronic and Micro-/Nanosensors 253 6.1 Nanotechnology Laboratories in Industries 254 6.1.1 Facilities for Micro-/Nanosensor Fabrication and Characterization 254 6.2 Micro- and Nanosensors as Preliminary Prototypes for Industry Research 260 6.2.1 Nanocomposite Optoelectronic Sensors and Optoelectronic Circuits for Pressure Sensors 260 6.2.1.1 Optical Fiber Nanocomposite Tip 260 6.2.2 Plasmonic Probes 266 6.2.3 Nanocomposite Pressure Sensor 273 6.2.4 Nanocomposite Sensor for Liquid Detection Systems and Fluid Loss Systems 277 6.2.4.1 Nanocomposite Sensor for Liquid Detection Systems Based on a Pillar-Type Layout 278 6.2.4.2 Micro- and Nanosensors in the Monitoring of Production Processes: Leakage Monitoring 285 6.2.5 Examples of Digital MEMS/NEMS Sensors: Technological Aspects and Applications 286 6.2.5.1 Thin Film MEMS 286 6.2.5.2 Nanoprobes for Medical Imaging 288 6.2.5.3 Diamond Thin Film Devices: Sensing Improvements 293 6.3 Multisensor Systems and Big Data Synchronization of Micro-/Nanoprobes 295 References 296 7 Image Vision Advances 301 7.1 Defect Classification by Artificial Intelligence and Data Processor Units 302 7.1.1 Artificial Intelligence Algorithms and Automatism for Defect Classification: Case Study of Tire Production 302 7.1.2 Welding Classification and Nondestructive Testing Suitable for the Quality Check 304 7.1.2.1 Watershed Image Segmentation and Automatic Welding Defect Classification 307 7.1.3 Encoding and Decoding Circuits in Artificial Intelligence Data Processing 309 7.1.4 Electronic Logic Port Implementations: Pixel Matrix Logic Condition 314 7.2 Image Vision Architectures and Electronic Design 314 7.2.1 Infrared Thermography Monitoring Industrial Processes 315 7.2.1.1 Welding Image Vision Processing and Architecture Design: Radiometric Post Processing 315 7.2.2 Electronic and Firmware for Inline Image Monitoring Systems: Hole Precision in Milling Quality Processes 316 7.2.3 Image Vision and Predictive Maintenance by Artificial Intelligence 319 7.2.3.1 Profilometer for Image Vision 319 7.2.3.2 In-Line 3D Image Vision AI System Integrating Profilometer and Image Processing 321 7.2.4 Augmented Reality Systems and Artificial Neural Networks: Image Vision Supporting Production Processes 323 7.2.5 Infrared Thermography Circuit Design and Automated System 324 7.3 Image Segmentation and Image Clustering 327 7.3.1 Electronic and Firmware for In-Line Monitoring Systems: Camera Connection 327 7.3.2 Image Segmentation and Clustering Techniques: Automated In-Line Monitoring Systems 327 7.3.3 Circuit Timing In-Line Monitoring and Data Storage Systems 328 7.3.4 Image Segmentation in Product Quality Monitoring: Snake Contour Approach 329 7.3.5 Advanced Image Clustering: K-Means Applied to Radiometric Images 331 7.4 Image Segmentation for Food Defect Detection 333 7.5 Random Forest Pixel Classification 335 References 339 8 Electronic and Reverse Engineering 341 8.1 Reverse Engineering Systems and Mechanical Precision 342 8.1.1 Reverse Engineering Platform: Tools, Approaches, and Facilities 344 8.2 Working Processing and Adaptation 349 8.2.1 Process Simulations 349 8.2.2 Process Mining Actuation and Digital Aspects Concerning Decision Support Systems Implemented by Data Mining Algorithms 350 8.3 Reverse Engineering and Self-Learning Automatic Working Piece Classification 354 8.4 Tools Supporting RE: AR and Image Processing for Size Measurement 356 8.5 RE in Micrometric Scale: RE Approach for Photonic Crystals 357 8.6 RE for the Production of Pipeline Components 361 8.7 RE in the Precision Manufacturing Process for Thin Film Devices 363 8.7.1 Ring MEMS Manufacturing 363 8.7.2 Thin Film Diamond Antenna 369 8.8 Advanced RE Processes in Industry 5.0 372 8.9 RE in Nanocomposite Production Processes 374 8.10 RE in Electronic Board Production 376 8.10.1 Transfer of the Master to the Copper Plate 378 8.10.2 Chemical Attack of Copper 378 8.10.3 Drilling and Finishing Processes 379 References 379 9 Rapid Prototyping 381 9.1 Rapid Prototyping Tools and Microscale Electronic Systems: Methodological Approaches 382 9.1.1 Photonic Crystal Pillars for Filtering and Optical Resonance 382 9.1.2 Thin Film Microelectromechanical System Prototyping and Photolithography Approach 387 9.1.3 Thin Film GHz Microstructures by the Photolithography Approach 387 9.1.4 Gas Sensing Homemade Experimental Setup for Rapid Prototyping 390 9.2 Examples of Antenna and Detection System Rapid Prototyping 392 9.2.1 GPR Antenna Design for UAV Integration System 392 9.2.2 Example of an Underground Water Leakage Detection System Integrating GPR, UAV, and Infrared Thermal Imaging: System Prototyping 397 9.2.3 Integrated Diamond Patch-Type Antennas and Applications 400 9.3 Principles of Mechanical Piece Rapid Prototyping and Innovative Materials 411 9.3.1 Example of Diamond Material Implementations 413 9.4 Rapid Prototyping and Artificial Intelligence Upgrade 415 9.5 Rapid Prototyping Oriented Toward Patent Development 418 9.5.1 Prototyping of Devices Implementing Nanoparticles 418 9.5.2 Prototyping of an Optoelectronic Device Based on a Nanocomposite Tip 418 9.5.3 DNA Lab-on-Chip 418 9.6 Nanocomposite Artificial Skin Rapid Prototyping Process 437 References 439 10 Scientific Research in Industry 445 10.1 Guidelines to Construct an Advanced Research Unit in Industry in the Electronic and Mechatronic Field 446 10.2 Guidelines to Formulate a Patent 448 10.3 Guideline to Propose Technological Advances for Public Entities and in Industry 5.0 Research Project 449 10.3.1 Setting of a Research Project of Underground Water Leakage 449 10.3.2 Setting a Research Project Involving Technologies for Hydrogeological Risk Monitoring 456 10.3.3 Setting a Research Project in Mechatronics: Production of a Diagnostic Machine by Means of Industry 5.0 Facilities 468 10.4 Innovation Process Projects: Example of a Smart Wine Factory 483 10.5 Guideline for Project Management 485 References 506 Abbreviations and Acronyms 507 Index 515

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Book SynopsisA deep dive into wireless energy transfer technologies for IoT networks In Wireless Energy Transfer: Towards Sustainable Zero-Energy IoT Networks, distinguished researchers Onel L. A. López and Hirley Alves deliver a robust discussion of massive wireless energy transfer and zero-energy, low-cost, Internet of Things networks. Moving beyond the basic theoretical background of the subject, the authors offer a deep analysis of the scenarios and requirements of wireless energy transfer. The book details novel powering schemes recently proposed to face the challenging requirements of the future Internet of Things, as well as a comprehensive review of sustainable IoT wireless networks. Wireless Energy Transfer explains why novel energy efficient solutions will be needed to address the sheer volume of devices currently forecasted to be used in the near future. It explores the challenges technologists and users will face as well as proposed solutionsTable of ContentsPreface ix Acknowledgments xi Acronyms xii Mathematical Notation xvi About the Companion Website xviii 1 Massive IoT 1 1.1 Selected Use-cases and Scenarios 4 1.2 Key Technologies 6 1.3 Requirements and KPIs 10 1.4 Key Enablers 12 1.4.1 Holistic and Globally Scalable Massive IoT 12 1.4.2 Sustainable Connectivity 13 1.5 Final Remarks and Discussions 17 2 Wireless RF Energy Transfer: An Overview 20 2.1 Energy Harvesting 20 2.1.1 EH Sources 20 2.1.2 RF Energy Transfer 22 2.2 RF–EH Performance 24 2.2.1 Analytical Models 24 2.2.2 State-of-the-art on RF EH 26 2.3 RF–EH IoT 30 2.3.1 Architectures of IoT RF EH Networks 30 2.3.2 Green WET 31 2.3.3 WIT-WET Layouts 32 2.3.4 RF EH in IoT Use Cases 32 2.4 Enabling Efficient RF-WET 35 2.4.1 Energy Beamforming 35 2.4.2 CSI-limited Schemes 35 2.4.3 Distributed Antenna System 37 2.4.4 Enhancements in Hardware and Medium 37 2.4.5 New Spectrum Opportunities 39 2.4.6 Resource Scheduling and Optimization 40 2.4.7 Distributed Ledger Technology 41 2.5 Final Remarks 41 3 Ambient RF EH 43 3.1 Motivation and Overview 43 3.1.1 Hybrid of RF–EH and Power Grid 45 3.1.2 Energy Usage Protocols 46 3.1.3 On Efficient Ambient RF–RH Designs 48 3.2 Measurement Campaigns 51 3.2.1 Greater London (2012) 52 3.2.2 Diyarbakir (2014) 52 3.2.3 Flanders (2017-2019) 53 3.2.4 Other Measurements 54 3.3 Energy Arrival Modeling 55 3.3.1 Based on Arbitrary Distributions 56 3.3.2 Based on Stochastic Geometry 56 3.4 A Stochastic Geometry-based Study 57 3.4.1 System Model and Assumptions 57 3.4.2 Energy Coverage Probability 59 3.4.3 Average Harvested Energy 62 3.4.4 Meta-distribution of Harvested Energy 63 3.4.5 Numerical Results 64 3.5 Final Considerations 67 4 Efficient Schemes for WET 68 4.1 EH from Dedicated WET 68 4.2 Energy Beamforming 68 4.2.1 Low-complexity EB Design 71 4.2.2 CSI-limited Energy Beamforming 74 4.2.3 Performance Analysis 76 4.3 CSI-free Multi-antenna Techniques 80 4.3.1 System Model and Assumptions 81 4.3.2 Positioning-agnostic CSI-free WET 82 4.3.3 Positioning-aware CSI-free WET 94 4.4 On the Massive WET Performance 96 4.5 Final Considerations 98 5 Multi-PB Massive WET 99 5.1 On the PBs Deployment 99 5.1.1 Positioning-aware Deployments 99 5.1.2 Positioning-agnostic Deployments 104 5.2 Multi-antenna Energy Beamforming 109 5.2.1 Centralized Energy Beamforming 110 5.2.2 Distributed Energy Beamforming 111 5.2.3 Available RF Energy 111 5.3 Distributed CSI-free WET 113 5.3.1 SA, AA–IS and RPS–EMW 113 5.3.2 AA–SS 114 5.3.3 RAB 117 5.3.4 Positioning-aware CSI-free Schemes 118 5.3.5 Numerical Examples 118 5.4 On the Deployment Costs 120 5.5 Final Remarks 123 6 Wireless-powered Communication Networks 125 6.1 WPCN Models 125 6.2 Reliable Single-user WPCN 127 6.2.1 Harvest-then-transmit (HTT) 127 6.2.2 Allowing Energy Accumulation 130 6.2.3 HTT versus FEIPC 135 6.3 Multi-user Resource Allocation 139 6.3.1 Signal Model 140 6.3.2 Problem Formulation 141 6.3.3 Optimization Framework 142 6.3.4 TDMA versus SDMA 143 6.4 Cognitive MAC 145 6.4.1 Time Sharing and Scheduling 148 6.4.2 MAC Protocol at the Device Side 150 6.4.3 MAC Protocol at the HAP Side 151 6.5 Final Remarks 152 7 Simultaneous Wireless Information and Power Transfer 155 7.1 SWIPT Schemes 155 7.2 Separate EH and ID Receivers 156 7.2.1 Problem Formulation 157 7.2.2 Optimal Solution 158 7.2.3 Performance Results 159 7.3 Co-located EH and ID Receivers 160 7.3.1 Time Switching 162 7.3.2 Power splitting 165 7.3.3 TS versus PS 167 7.4 Enablers for Efficient SWIPT 171 7.4.1 Waveform Optimization 171 7.4.2 Multicarrier SWIPT 174 7.4.3 Cooperative Relaying 175 7.4.4 Interference Exploitation 176 7.4.5 Artificial Intelligence 177 7.5 Final Considerations 177 8 Final Notes 179 8.1 Summary 179 8.2 Future Research Directions 182 A A Brief Overview on Finite Block Length Coding 187 A.1 Finite Block Length Model 187 B Distribution of Transferred RF Energy Under CSI-free WET 191 B.1 Proof of Theorem 4.2 191 B.2 Proof of Theorem 4.4 192 C Clustering Algorithms 198 C.1 Partitioning Methods 198 C.1.1 K-Means 199 C.1.2 K-Medoids 199 C.1.3 K-Modes 199 C.2 Hierarchical Methods 200 C.3 Other Methods 200 C.4 Pre-processing 201 D Required SNR for a Target Decoding Error Probability (Proof of Theorem 6.1) 202 D.1 On the Convergence of Algorithm 3 203 Bibliography 205 Index 226

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Book SynopsisTable of ContentsPreface xiii About the Companion Website xv 1 Frequency Spectra of Digital Signals 1 1.1 EMC Units 1 1.1.1 Logarithm and Decibel Definition 1 1.1.2 Power and Voltage (Current) Gain in dB 1 1.1.3 EMC dB Units 3 1.2 Fourier Series Representation of Periodic Signals 6 1.3 Spectrum of a Clock Signal 7 1.4 Effect of the Rise Time, Signal Amplitude, Fundamental Frequency, and Duty Cycle on the Signal Spectrum 15 1.4.1 Effect of the Rise Time 15 1.4.2 Effect of the Signal Amplitude 15 1.4.3 Effect of the Fundamental Frequency 18 1.4.4 Effect of the Duty Cycle 20 1.5 Laboratory Exercises 22 1.5.1 Spectrum of a Digital Clock Signal 22 1.5.2 Laboratory Equipment and Supplies 22 1.5.3 Measured Spectrum vs. Calculated Spectrum 23 1.5.4 Effect of the Rise Time 27 1.5.5 Effect of the Signal Amplitude 31 1.5.6 Effect of the Fundamental Frequency 33 1.5.7 Effect of the Duty Cycle 37 References 43 2 EM Coupling Mechanisms 45 2.1 Wavelength and Electrical Dimensions 45 2.1.1 Concept of a Wave 45 2.1.2 Uniform Plane EM Wave in Time Domain 46 2.1.3 Uniform Plane EM Wave in Frequency Domain 47 2.2 EMC Interference Problem 50 2.3 Capacitive Coupling 53 2.3.1 Shielding to Reduce Capacitive Coupling 56 2.4 Inductive Coupling 59 2.4.1 Shielding to Reduce Inductive Coupling 61 2.5 Crosstalk Between PCB Traces 66 2.6 Common-Impedance Coupling 70 2.7 Laboratory Exercises 72 2.7.1 Crosstalk Between PCB Traces 72 References 76 3 Non-Ideal Behavior of Passive Components 77 3.1 Resonance in RLC Circuits 77 3.1.1 “Pure” Series Resonance – Non-Ideal Capacitor Model 77 3.1.2 “Pure” Parallel Resonance – Ferrite Bead Model 81 3.1.3 “Hybrid” Series Resonance – Non-Ideal Resistor Model 83 3.1.4 “Hybrid” Parallel Resonance – Non-Ideal Inductor Model 85 3.2 Non-Ideal Behavior of Resistors 87 3.2.1 Circuit Model and Impedance 87 3.2.2 Parasitic Capacitance Estimation – Discrete Components 89 3.2.3 Parasitic Capacitance Estimation – PCB Components 94 3.3 Non-Ideal Behavior of Capacitors 97 3.3.1 Circuit Model and Impedance 97 3.3.2 Parasitic Inductance Estimation – Discrete Components 99 3.3.3 Parasitic Inductance Estimation – PCB Components 101 3.4 Non-Ideal Behavior of Inductors 104 3.4.1 Circuit Model and Impedance 104 3.4.2 Parasitic Capacitance Estimation – Discrete Components 106 3.4.3 Parasitic Capacitance Estimation – PCB Components 108 3.5 Non-Ideal Behavior of a PCB Trace 111 3.5.1 Circuit Model and Impedance 111 3.6 Impact of the PCB Trace Length on Impedance of the Passive Components 114 3.6.1 Impedance of a Resistor – Impact of the PCB Trace 114 3.6.2 Impedance of a Capacitor – Impact of the PCB Trace 114 3.6.3 Impedance of an Inductor – Impact of the PCB Trace 114 3.6.4 Impedance of an Inductor vs. Impedance of the PCB Trace 118 3.7 Laboratory Exercises 118 3.7.1 Non-Ideal Behavior of Capacitors and Inductors, and Impact of the PCB Trace Length on Impedance 118 3.7.2 Laboratory Equipment and Supplies 119 3.7.3 Laboratory Procedure – Non-Ideal Behavior of Capacitors and Inductors 121 3.7.4 Laboratory Procedure – Impact of the PCB Trace Length on Impedance 122 References 122 4 Power Distribution Network 125 4.1 CMOS Inverter Switching 125 4.2 Decoupling Capacitors 125 4.2.1 Decoupling Capacitor Impact – Measurements 130 4.2.2 Decoupling Capacitor Configurations 137 4.3 Decoupling Capacitors and Embedded Capacitance 147 4.3.1 Decoupling Capacitors and Closely vs. Not Closely Spaced Power and Ground Planes 147 4.3.2 Impact of the Number and Values of the Decoupling Capacitors 156 4.4 Laboratory Exercises 168 4.4.1 Decoupling Capacitors 168 4.4.2 Embedded Capacitance and Decoupling Capacitors 172 References 176 5 EMC Filters 177 5.1 Insertion Loss Definition 177 5.2 Basic Filter Configurations 177 5.3 Source and Load Impedance Impact 177 5.4 What Do We Mean by Low or High Impedance? 179 5.5 LC and CL Filters 181 5.5.1 LC Filter 181 5.5.2 CL Filter 186 5.5.3 LC Filter vs. CL Filter 189 5.6 Pi and T Filters 195 5.6.1 Pi Filter 195 5.6.2 T Filter 196 5.6.3 Pi Filter vs. T Filter 197 5.7 LCLC and CLCL Filters 202 5.7.1 LCLC Filter 202 5.7.2 CLCL Filter 205 5.7.3 LCLC Filter vs. CLCL Filter 206 5.8 Laboratory Exercises 212 5.8.1 Input Impedance and Insertion Loss of EMC Filters 212 5.8.2 Laboratory Equipment and Supplies 212 5.8.3 Laboratory Procedure 214 References 217 6 Transmission Lines – Time Domain 219 6.1 Introduction 219 6.1.1 Transmission Line Effects 219 6.1.2 When a Line Is not a Transmission Line 219 6.1.3 Transmission Line Equations 226 6.2 Transient Analysis 229 6.2.1 Reflections at a Resistive Load 229 6.2.2 Reflections at a Resistive Discontinuity 236 6.2.3 Reflections at a Shunt Resistive Discontinuity 239 6.2.4 Reflections with Transmission Lines in Parallel 241 6.2.5 Reflections at a Reactive Load 245 6.2.6 Reflections at a Shunt Reactive Discontinuity 258 6.3 Eye Diagram 266 6.3.1 Fundamental Concepts 266 6.3.2 Impact of Driver, HDMI Cable, and Receiver 271 6.4 Laboratory Exercises 275 6.4.1 Transmission Line Reflections 275 6.4.2 Laboratory Equipment and Supplies 275 6.4.3 Reflections at a Resistive Load 278 6.4.4 Bounce Diagram 281 6.4.5 Reflections at a Resistive Discontinuity 282 References 285 7 Transmission Lines – Frequency Domain 287 7.1 Frequency-Domain Solution 287 7.1.1 The Complete Circuit Model – Voltage, Current, and Input Impedance along the Transmission Line 290 7.1.2 Frequency-Domain Solution – Example 307 7.2 Smith Chart and Input Impedance to the Transmission Line 316 7.2.1 Smith Chart Fundamentals 316 7.2.2 Input Impedance to the Transmission Line 326 7.3 Standing Waves and VSWR 332 7.4 Laboratory Exercises 336 7.4.1 Input Impedance to Transmission Line – Smith Chart 336 7.4.2 Laboratory Procedure – Smith Chart 336 References 337 8 Antennas and Radiation 339 8.1 Bridge Between the Transmission Line Theory and Antennas 339 8.2 Electric (Hertzian) Dipole Antenna 340 8.2.1 Wave Impedance and Far-Field Criterion 343 8.2.2 Wave Impedance in the Near Field 344 8.3 Magnetic Dipole Antenna 345 8.3.1 Wave Impedance and Far-Field Criterion 346 8.3.2 Wave Impedance in the Near Field 347 8.4 Half-Wave Dipole and Quarter-Wave Monopole Antennas 348 8.4.1 Half-Wave Dipole Antenna 348 8.4.2 Quarter-Wave Monopole Antenna 351 8.5 Balanced–Unbalanced Antenna Structures and Baluns 351 8.5.1 Balanced and Unbalanced Half-Wave Dipole Antenna 352 8.5.2 Sleeve (Bazooka) Balun 355 8.5.3 Input Impedance to the Transmission Line 357 8.5.4 Quarter-Wavelength Sleeve Balun 358 8.6 Sleeve Dipole Antenna Design and Build 360 8.6.1 Symmetrically Driven Half-Wave Dipole Antenna 360 8.6.2 Asymmetrically Driven Dipole Antenna and a Sleeve Dipole 361 8.6.3 Sleeve Dipole Antenna Design 362 8.6.4 Sleeve Dipole Antenna Design Through Simulation 362 8.6.5 Construction and Tuning of a Sleeve Dipole 364 8.7 Antennas Arrays 368 8.8 Log-Periodic Antenna 368 8.9 Biconical Antenna 372 8.10 Antenna Impedance and VSWR 373 8.11 Laboratory Exercises 375 8.11.1 Log-Periodic and Bicon Antenna Impedance and VSWR Measurements 376 8.11.2 Loop Antenna Construction 377 References 381 9 Differential- and Common-Mode Currents and Radiation 383 9.1 Differential- and Common-Mode Currents 383 9.1.1 Common-Mode Current Creation 385 9.2 Common-Mode Choke 387 9.3 Differential-Mode and Common-Mode Radiation 391 9.3.1 Differential-Mode Radiation 395 9.3.2 Common-Mode Radiation 397 9.4 Laboratory Exercises 399 9.4.1 Differential-Mode and Common-Mode Current Measurement 399 9.4.2 Laboratory Equipment and Supplies 399 9.4.3 Laboratory Procedure – Differential-Mode and Common-Mode Current Measurements 399 References 406 10 Return-Current Path, Flow, and Distribution 407 10.1 Return-Current Path 407 10.2 Return-Current Flow 412 10.3 Return-Current Distribution 415 10.3.1 Microstrip Line PCB 415 10.3.2 Stripline PCB 422 10.4 Laboratory Exercises 430 10.4.1 Path of the Return Current 430 References 438 11 Shielding to Prevent Radiation 439 11.1 Uniform Plane Wave 439 11.1.1 Skin Depth 442 11.1.2 Current Density in Conductors 443 11.1.3 Reflection and Transmission at a Normal Boundary 444 11.2 Far-Field Shielding 447 11.2.1 Shielding Effectiveness – Exact Solution 450 11.2.2 Shielding Effectiveness – Approximate Solution – Version 1 454 11.2.3 Shielding Effectiveness – Approximate Solution – Version 2 456 11.2.4 Shielding Effectiveness – Simulations 458 11.3 Near-Field Shielding 463 11.3.1 Electric Field Sources 463 11.3.2 Magnetic Field Sources 465 11.3.3 Shielding Effectiveness – Simulations 466 11.3.4 Shielding Effectiveness – Measurements 470 11.4 Laboratory Exercises 477 11.4.1 Shielding Effectiveness – Simulations 477 11.4.2 Shielding Effectiveness – Measurements 477 References 481 12 SMPS Design for EMC 483 12.1 Basics of SMPS Operation 483 12.1.1 Basic SMPS Topology 483 12.1.2 Basic SMPS Design 486 12.2 DC/DC Converter Design with EMC Considerations 491 12.2.1 Switching Frequency 491 12.2.2 Output Inductor 493 12.2.3 Output Capacitor 494 12.2.4 Catch Diode 495 12.2.5 Input Capacitor 495 12.2.6 Bootstrap Capacitor 496 12.2.7 Undervoltage Lockout 496 12.2.8 Feedback Pin 496 12.2.9 Compensation Network 497 12.2.10 Complete Regulator Circuitry 498 12.2.11 EMC Considerations 498 12.3 Laboratory Exercises 500 12.3.1 SMPS Design and Build 500 12.3.2 Laboratory Equipment and Supplies 500 12.3.3 Laboratory Procedure 501 References 502 A Evaluation of EMC Emissions and Ground Techniques on 1- and 2-Layer PCBs with Power Converters 503 A. 1 Top-Level Description of the Design Problem 503 A.. 1 Functional Block Details 503 A.1. 2 One-Layer Board Topologies 506 A.1. 3 Two-Layer Board Topologies 507 A. 2 DC/DC Converter – Baseline EMC Emissions Evaluation 509 A.2. 1 CISPR 25 Radiated Emissions Test Results 510 A.. 2 CISPR 25 Conducted Emissions (Voltage Method) Test Results 512 A.2. 3 CISPR 25 Conducted Emissions (Current Method) Test Results 515 A. 3 DC/DC Converter – EMC Countermeasures – Radiated Emissions Results 515 A.3. 1 EMC-A and EMC-E Input and Output Capacitor Impact 515 A.3. 2 EMC-A Input Inductor Impact 518 A.. 3 EMC-C Switching Inductor Impact 519 A.3. 4 EMC-B and EMC-D Snubber Impact 521 A.3. 5 EMC-A, EMC-E – Conducted Emissions Countermeasures Impact 523 A.3. 6 Impact of the Shield Frame 524 A. 4 DC/DC Converter – EMC Countermeasures – Conducted Emissions Results – Voltage Method 528 A.4. 1 EMC-A and EMC-E Input and Output Capacitor Impact 528 A.4. 2 EMC-A Input Inductor Impact 529 A.4. 3 EMC-A Additional Input Capacitors Impact 530 A.. 4 EMC-A Input Inductor Impact 531 A.4. 5 EMC-C Switching Inductor Impact 532 A.4. 6 EMC-B and EMC-D Snubber Impact 533 A. 5 DC/DC Converter – EMC Countermeasures – Conducted Emissions Results – Current Method 535 A.5. 1 EMC-A, EMC-C, and EMC-E Input and Output Capacitor and Inductor Impact 535 A.5. 2 EMC-B and EMC-D Snubber Impact 536 A. 6 PCB Layout Considerations 537 A.6. 1 Introduction 537 A.6. 2 Visualizing Complete Forward and Return Paths 538 A.6. 3 Return-Plane Split in AC–DC Converter 543 A. 7 AC/DC Converter Design with EMC Considerations 544 A.7. 1 AC/DC Converter Schematics and Design Requirements 544 A.7. 2 EMC Considerations 546 A. 8 AC/DC Converter – Baseline EMC Emissions Evaluation 548 A.8. 1 Radiated Emissions Test Results 548 A.8. 2 Conducted Emissions Test Results 551 A. 9 AC/DC Converter – EMC Countermeasures – Conducted and Radiated Emissions Results 552 A.9. 1 Conducted Emissions Test Results 553 A.9. 2 Radiated Emissions Test Results 555 A. 10 Complete System – Conducted and Radiated Emissions Results 557 A.0. 1 Complete System and Board Topologies 557 A.10. 2 Conducted Emissions Results 558 A.10. 3 Radiated Emissions Results 562 A.10. 4 Conclusions 564 References 565 Index 567

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Book SynopsisExplore the diverse electrical engineering application of polymer composite materials with this in-depth collection edited by leaders in the field Polymer Composites for Electrical Engineering delivers a comprehensive exploration of the fundamental principles, state-of-the-art research, and future challenges of polymer composites. Written from the perspective of electrical engineering applications, like electrical and thermal energy storage, high temperature applications, fire retardance, power cables, electric stress control, and others, the book covers all major application branches of these widely used materials. Rather than focus on polymer composite materials themselves, the distinguished editors have chosen to collect contributions from industry leaders in the area of real and practical electrical engineering applications of polymer composites. The book?s relevance will only increase as advanced polymer composites receive more attention and interest in the area of advanced Table of ContentsList of Contributors xv Preface xix 1 Polymer Composites for Electrical Energy Storage 1 Yao Zhou 1.1 Introduction 1 1.2 General Considerations 1 1.3 Effect of Nanofiller Dimension 3 1.4 Orientation of Nanofillers 7 1.5 Surface Modification of Nanofillers 11 1.6 Polymer Composites with Multiple Nanofillers 13 1.7 Multilayer-structured Polymer Composites 16 1.8 Conclusion 19 References 21 2 Polymer Composites for Thermal Energy Storage 29 Jie Yang, Chang-Ping Feng, Lu Bai, Rui-Ying Bao, Ming-Bo Yang, and Wei Yang 2.1 Introduction 29 2.2 Shape-stabilized Polymeric Phase Change Composites 32 2.2.1 Micro/Nanoencapsulated Method 33 2.2.2 Physical Blending 35 2.2.3 Porous Supporting Scaffolds 36 2.2.4 Solid–Solid Composite PCMs 37 2.3 Thermally Conductive Polymeric Phase Change Composites 39 2.3.1 Metals 40 2.3.2 Carbon Materials 41 2.3.3 Ceramics 41 2.4 Energy Conversion and Storage Based on Polymeric Phase Change Composites 42 2.4.1 Electro-to-Heat Conversion 42 2.4.2 Light-to-Heat Conversion 45 2.4.3 Magnetism-to-Heat Conversion 47 2.4.4 Heat-to-Electricity Conversion 48 2.5 Emerging Applications of Polymeric Phase Change Composites 48 2.5.1 Thermal Management of Electronics 49 2.5.2 Smart Textiles 50 2.5.3 Shape Memory Devices 51 2.6 Conclusions and Outlook 51 Acknowledgments 52 References 52 3 Polymer Composites for High-Temperature Applications 63 Sen Niu, Lixue Zhu, Qiannan Cai, and Yunhe Zhang 3.1 Application of Polymer Composite Materials in High-Temperature Electrical Insulation 63 3.1.1 High-Temperature-Resistant Electrical Insulating Resin Matrix 63 3.1.1.1 Silicone Resins 64 3.1.1.2 Polyimide 64 3.1.1.3 Polyether Ether Ketone 65 3.1.1.4 Polybenzimidazole 65 3.1.1.5 Polyphenylquinoxaline 65 3.1.1.6 Benzoxazine 66 3.1.2 Modification of Resin Matrix with Reinforcements 66 3.1.2.1 Mica 66 3.1.2.2 Glass Fiber 66 3.1.2.3 Inorganic Nanoparticles 67 3.1.3 Modifications in the Thermal Conductivity of Resin Matrix 67 3.1.3.1 Mechanism of Thermal Conductivity 68 3.1.3.2 Intrinsic High Thermal Conductivity Insulating Material 68 3.1.3.3 Filled High Thermal Conductivity Insulating Material 69 3.2 High-Temperature Applications for Electrical Energy Storage 70 3.2.1 General Considerations for High-Temperature Dielectrics 70 3.2.2 High-Temperature-Resistant Polymer Matrix 71 3.2.3 Polymer Composites for High-Temperature Energy Storage Applications 71 3.2.4 Surface Modification of Nanocomposite for High-Temperature Applications 72 3.2.5 Sandwich Structure of Nanoparticles for High-Temperature Applications 75 3.3 Application of High-Temperature Polymer in Electronic Packaging 77 3.3.1 Synthesis of Low Dielectric Constant Polymer Materials Through Molecular Structure Design 80 3.3.1.1 Fluorine-Containing Low Dielectric Constant Polymer 80 3.3.1.2 Low Dielectric Constant Polymer Material Containing Nonpolar Rigid Bulk Group 81 3.3.2 High-Temperature-Resistant Low Dielectric Constant Polymer Composite Material 82 3.3.2.1 Low Dielectric Constant Polyoxometalates/Polymer Composite 83 3.3.2.2 Low Dielectric Constant POSS/Polymer Composite 85 3.4 Application of Polymer Composite Materials in the Field of High-Temperature Wave-Transmitting and Wave-Absorbing Electrical Fields 86 3.4.1 Wave-Transmitting Materials 88 3.4.1.1 The High-Temperature Resin Matrix 88 3.4.1.2 Reinforced Materials 89 3.4.2 Absorbing Material 89 3.4.2.1 The High-Temperature Resin Matrix 90 3.4.2.2 Inorganic Filler 90 3.5 Summary 91 References 92 4 Fire-Retardant Polymer Composites for Electrical Engineering 99 Zhi Li, En Tang, and Xue-Meng Cao 4.1 Introduction 99 4.2 Fire-Retardant Cables and Wires 100 4.2.1 Fundamental Overview 100 4.2.2 Understanding of Fire-Retardant Cables and Wires 101 4.2.2.1 Polyethylene Composites 101 4.2.2.2 Ethylene-Vinyl Acetate (EVA) Copolymer 103 4.2.2.3 Polyvinyl Chloride Composites 105 4.2.2.4 Other Polymers 108 4.3 Fire-Retardant Polymer Composites for Electrical Equipment 109 4.3.1 Fundamental Overview 109 4.3.2 Understanding of Fire-Retardant Polymer Composites for Electrical Equipment 110 4.3.2.1 HIPS and ABS Composites 110 4.3.2.2 PC/ABS Composites 112 4.3.2.3 PC Composites 115 4.3.2.4 PBT Composites 116 4.4 Fire-Retardant Fiber Reinforced Polymer Composites 117 4.4.1 Fundamental Overview 117 4.4.2 Understanding of Fire-Retardant Fiber Reinforced Polymer Composites 118 4.4.2.1 Reinforced PBT and PET Composites 118 4.5 Conclusion and Outlook 118 References 119 5 Polymer Composites for Power Cable Insulation 123 Yoitsu Sekiguchi 5.1 Introduction 123 5.2 Trend in Nanocomposite Materials for Cable Insulation 125 5.2.1 Overview 125 5.2.2 Polymer Materials as Matrix Resin 125 5.2.3 Fillers 128 5.2.4 Nanocomposites 130 5.2.4.1 XLPE Nanocomposites 131 5.2.4.2 PP Nanocomposites 131 5.2.4.3 Nanocomposite with Cluster/Cage Molecule 131 5.2.4.4 Copolymer and Polymer Blend 131 5.3 Factors Influencing Properties 138 5.4 Issues in Nanocomposite Insulation Materials Research 139 5.5 Understanding Dielectric and Insulation Phenomena 140 5.5.1 Electromagnetic Understanding 140 5.5.2 Understanding Space Charge Behavior by Q(t) Method 141 References 146 6 Semi-conductive Polymer Composites for Power Cables 153 Zhonglei Li, Boxue Du, Yutong Zhao, and Tao Han 6.1 Introduction 153 6.1.1 Function of Semi-conductive Composites 153 6.1.2 Development of Semi-conductive Composites 154 6.2 Conductive Mechanism of Semi-conductive Polymer Composites 155 6.2.1 Percolation Theory 157 6.2.2 Tunneling Conduction Theory 157 6.2.3 Mechanism of Positive Temperature Coefficient 158 6.3 Effect of Polymer Matrix on Semi-conductivity 159 6.3.1 Thermoset Polymer Matrix 159 6.3.2 Thermoplastic Polymer Matrix 162 6.3.3 Blended Polymer Matrix 163 6.4 Effect of Conductive Fillers on Semi-conductivity 165 6.4.1 Carbon Black 165 6.4.2 Carbonaceous Fillers with One- and Two-Dimensions 166 6.4.3 Secondary Filler for Carbon Black Filled Composites 167 6.5 Effect of Semi-conductive Composites on Space Charge Injection 169 6.6 Conclusions 172 References 173 7 Polymer Composites for Electric Stress Control 179 Muneaki Kurimoto 7.1 Introduction 179 7.2 Functionally Graded Solid Insulators and Their Effect on Reducing Electric Field Stress 179 7.3 Practical Application of ε-FGMs to GIS Spacer 181 7.4 Application to Power Apparatus 182 References 188 8 Composite Materials Used in Outdoor Insulation 191 Wang Xilin, Jia Zhidong, and Wang Liming 8.1 Introduction 191 8.2 Overview of SIR Materials 192 8.2.1 RTV Coatings 193 8.2.2 Composite Insulators 195 8.2.3 Liquid Silicone Rubber (LSR) 196 8.2.4 Aging Mechanism and Condition Assessment of SIR Materials 197 8.3 New External Insulation Materials 198 8.3.1 Anti-icing Semiconductor Materials 199 8.3.2 Hydrophobic CEP 201 8.4 Summary 202 References 203 9 Polymer Composites for Embedded Capacitors 207 Shuhui Yu, Suibin Luo, Riming Wang, and Rong Sun 9.1 Introduction 207 9.1.1 Development of Embedded Technology 207 9.1.2 Dielectric Materials for Commercial Embedded Capacitors 210 9.2 Researches on the Polymer-Based Dielectric Nanocomposites 213 9.2.1 Filler Particles 213 9.2.2 Epoxy Matrix 216 9.2.2.1 Modification to Improve Dielectric Properties 219 9.2.2.2 Modification to Improve Mechanical Properties 221 9.3 Fabrication Process of Embedded Capacitors 224 9.4 Reliability Tested of Embedded Capacitor Materials 229 9.5 Conclusions and Perspectives 230 References 230 10 Polymer Composites for Generators and Motors 235 Hirotaka Muto, Takahiro Umemoto, and Takahiro Mabuchi 10.1 Introduction 235 10.2 Polymer Composite in High-Voltage Rotating Machines 236 10.3 Ground Wall Insulation 237 10.3.1 Mica/Epoxy Insulation 237 10.3.2 Electrical Defect in the Insulation of Rotating Machines and Degradation Mechanism 238 10.3.3 Insulation Design and V-t Curve 239 10.4 Polymer Nanocomposite for Rotating Machine 240 10.4.1 Partial Discharge Resistance and a Treeing Lifetime of Nanocomposite as Material Property 241 10.4.1.1 PD Resistance 241 10.4.1.2 Electrical Treeing Lifetime 242 10.4.2 Breakdown Lifetime Properties of Realistic Insulation Defect in Rotating Machine 244 10.4.2.1 Voltage Endurance Test of Void Defect 245 10.4.2.2 Voltage Endurance Test in Mica/Epoxy Nanocomposite-Layered Structure 247 10.4.2.3 V-t Curves in Coil Bar Model with Mica/Epoxy Nanocomposite Insulation 248 10.5 Stress-Grading System of Rotating Machines 252 10.5.1 Silicon Carbide Particle-Loaded Nonlinear-Resistive Materials 252 10.5.2 End-turn Stress-Grading System of High-Voltage Rotating Machines 253 References 255 11 Polymer Composite Conductors and Lightning Damage 259 Xueling Yao 11.1 Lightning Environment and Lightning Damage Threat to Composite-Based Aircraft 259 11.1.1 The Lightning Environment 259 11.1.1.1 Formation of Lightning 259 11.1.2 Lightning Test Environment of Aircrafts 261 11.1.2.1 Zone 1 262 11.1.2.2 Zone 2 263 11.1.2.3 Zone 3 263 11.1.2.4 Current Component A – First Return Strike 264 11.1.2.5 Current Component Ah – Transition Zone First Return Strike 264 11.1.2.6 Current Component B – Intermediate Current 264 11.1.2.7 Current Component C – Continuing Current 264 11.1.2.8 Component C* – Modified Component C 264 11.1.2.9 Current Component D – Subsequent Strike Current 266 11.1.3 Waveform Combination in Different Lightning Zones for Lightning Direct Effect Testing 269 11.1.4 Application of CFRP Composites in Aircraft 269 11.2 The Dynamic Conductive Characteristics of CFRP 271 11.2.1 A Review of the Research on the Conductivity of CFRP 271 11.2.2 The Testing Methods 272 11.2.2.1 Specimens 272 11.2.2.2 The Test Fixture 273 11.2.2.3 Lightning Impulse Generator and Lightning Waveforms 274 11.2.3 The Experimental Results of the Dynamic Impedance of CFRP 275 11.2.3.1 The Nondestructive Lightning Current Test 275 11.2.3.2 The Applied Lightning Current Impulse and the Response Voltage Impulse 278 11.2.3.3 Equivalent Conductivity of CFRP Laminates Under Different Lightning Impulses 280 11.2.3.4 Equivalent Conductivity of CFRP Laminates with Different Laminated Structures 282 11.2.4 The Discussion of the Dynamic Conductive Characteristics of CFRP 282 11.2.4.1 The Conduction Path of the CFRP Laminate Under a Lightning Current Impulse 282 11.2.4.2 Dynamic Conductance of CFRP Laminate 284 11.2.4.3 The Inductive Properties of CFRP Laminates 286 11.2.4.4 Equivalent Conductivity of CFRP Laminates Subjected to Lightning Current Impulses with Higher Intensity 288 11.3 The Lightning Strike-Induced Damage of CFRP Strike 289 11.3.1 Introduction of the Lightning Damage of CFRP 289 11.3.2 Single Lightning Strike-Induced Damage 290 11.3.2.1 Experimental Setup for Single Lightning Strike Test 290 11.3.2.2 Experimental Results of Single Lightning Strike-Induced Damage 292 11.3.2.3 Evaluation for Single Lightning Strike-Induced Damage 297 11.3.3 Multiple Lightning Strikes-Induced Damage 300 11.3.3.1 Experimental Method for Multiple Consecutive Lightning Strike Tests 300 11.3.3.2 Experimental Results of Multiple Lightning Damage 303 11.3.3.3 Multiple Lightning Damage Areas and Depths of CFRP Laminates 308 11.3.3.4 Analysis for Multiple Lightning Damage of CFRP Laminates 309 11.3.3.5 Evaluation for Multiple Lightning Damage of CFRP Laminates 313 11.4 The Simulation of Lightning Strike-Induced Damage of CFRP 319 11.4.1 Overview of Lightning Damage Simulation Researches 319 11.4.2 Establishment of the Coupled Thermal-Electrical Model 321 11.4.2.1 Finite Element Model 321 11.4.2.2 Simulated Lightning Component A 322 11.4.2.3 Pyrolysis Degree Calculation 322 11.4.2.4 Dynamic Conductive Properties 322 11.4.2.5 Pyrolysis-Dependent Material Parameters 323 11.4.3 Simulation Physical Fields of Lightning Current on CFRP Laminates 323 11.4.3.1 Temperature and Pyrolysis Fields 323 11.4.3.2 Mechanical Analysis 325 11.4.4 Simulated Lightning Damage Results 325 11.4.4.1 Numerical Criterion for Lightning Damage 325 11.4.4.2 In-Plane Lightning Damage Evaluation 327 11.4.4.3 In-Depth Lightning Damage Evaluation 331 References 331 12 Polymer Composites for Switchgears 339 Takahiro Imai 12.1 Introduction 339 12.2 History of Switchgear 340 12.3 Typical Insulators in Switchgears 342 12.3.1 Epoxy-based Composite Insulators 342 12.3.2 Insulator-Manufacturing Process 343 12.3.2.1 Vacuum Casting Method 344 12.3.2.2 Automatic Pressure Gelation Method 344 12.3.2.3 Vacuum Pressure Impregnation Method 345 12.4 Materials for Epoxy-based Composites 345 12.4.1 Epoxy Resins 345 12.4.2 Hardeners 346 12.4.3 Inorganic Fillers and Fibers 347 12.4.4 Silane Coupling Agents 348 12.4.5 Fabrication of Epoxy-based Composites 349 12.5 Properties of Epoxy-based Composites 351 12.5.1 Necessary Properties of Epoxy-based Composites for Switchgears 351 12.5.2 Resistance to Thermal Stresses 352 12.5.2.1 Glass Transition Temperature 352 12.5.2.2 Coefficient of Thermal Expansion (CTE) 354 12.5.3 Resistances to Electrical Stresses 356 12.5.3.1 Short-term Insulation Breakdown 356 12.5.3.2 Long-term Insulation Breakdown (V-t Characteristics) 357 12.5.3.3 Relative Permittivity and Resistivity 359 12.5.4 Resistances to Ambient Stresses 360 12.5.4.1 Resistance to SF6 Decomposition Gas 360 12.5.4.2 Water Absorption 361 12.5.5 Resistances to Mechanical Stresses 362 12.5.5.1 Flexural and Tensile Strength 362 12.5.5.2 Creep 363 12.5.6 International Standards for Evaluation of Composites 363 12.6 Advances of Epoxy-based Composites for Switchgear 365 12.6.1 Nanocomposites 365 12.6.2 High Thermal Conductive Composites 366 12.6.3 Biomass Material-Based Composites 367 12.6.4 Functionally Graded Materials 368 12.6.5 Estimate of Remaining Life of Composites 370 12.7 Conclusion 372 References 373 13 Glass Fiber-Reinforced Polymer Composites for Power Equipment 377 Yu Chen 13.1 Overview 377 13.2 Glass Fiber-Reinforced Polymer Composites 378 13.2.1 Fibers 378 13.2.1.1 Chemical Description 378 13.2.1.2 Classification of Glass Fibers 380 13.2.1.3 Properties of Glass Fiber 380 13.2.1.4 Glass Fabrics 380 13.2.1.5 Advantages and Disadvantages 381 13.2.1.6 Common Manufacturing Methods 383 13.2.1.7 Applications of Glass Fiber in Various Industries 384 13.2.2 Polymers 386 13.2.2.1 Epoxy 386 13.2.2.2 Polyester (Thermosetting) 386 13.2.2.3 Phenolic 387 13.2.3 Manufacturing Methods 388 13.2.4 Specifications of Several Kinds of GFRP Materials 393 13.2.4.1 Rigid Laminated Sheets 393 13.2.4.2 Industrial Rigid Round Laminated Rolled Tubes 394 13.2.4.3 Insulated Pipe 394 13.2.4.4 Insulated Pull Rod 394 13.3 Application of Glass Fiber-Reinforced Polymer Composites 396 13.3.1 Laminated Sheets 396 13.3.2 Composite Long Rod Insulators 398 13.3.3 UHV-Insulated Pull Rod for GIS 400 13.3.4 Composite Pole 403 13.3.5 Aluminum Conductor Composite Core in an Overhead Conductor 404 13.3.6 Composite Station Post Insulators 405 13.3.7 Composite Hollow Insulators 407 13.3.8 Composite Crossarms 407 Bibliography 414 Index 419

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Book Synopsis

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Book SynopsisTable of ContentsPreface vii 1. Introduction 1 1.1 Introduction 2 1.2 A History of Control Systems 4 1.3 System Configurations 6 1.4 Analysis and Design Objectives 9 Case Study 11 1.5 The Design Process 14 1.6 Computer-Aided Design 19 1.7 The Control Systems Engineer 20 Summary 21 Review Questions 22 Cyber Exploration Laboratory 22 Bibliography 23 2. Modeling In The Frequency Domain 25 2.1 Introduction 26 2.2 Laplace Transform Review 27 2.3 The Transfer Function 36 2.4 Electrical Network Transfer Functions 39 2.5 Translational Mechanical System Transfer Functions 53 2.6 Rotational Mechanical System Transfer Functions 61 2.7 Transfer Functions for Systems with Gears 65 2.8 Electromechanical System Transfer Functions 69 2.9 Electric Circuit Analogs 75 2.10 Nonlinearities 78 2.11 Linearization 79 Case Studies 84 Summary 87 Review Questions 87 Cyber Exploration Laboratory 88 Hardware Interface Laboratory 91 Bibliography 93 3. Modeling In The Time Domain 95 3.1 Introduction 96 3.2 Some Observations 96 3.3 The General State-Space Representation 100 3.4 Applying the State-Space Representation 102 3.5 Converting a Transfer Function to State Space 110 3.6 Converting from State Space to a Transfer Function 116 3.7 Linearization 118 Case Studies 121 Summary 125 Review Questions 126 Cyber Exploration Laboratory 126 Bibliography 128 4. Time Response 130 4.1 Introduction 131 4.2 Poles, Zeros, and System Response 131 4.3 First-Order Systems 135 4.4 Second-Order Systems: Introduction 137 4.5 The General Second-Order System 142 4.6 Underdamped Second-Order Systems 146 4.7 System Response with Additional Poles 155 4.8 System Response with Zeros 159 4.9 Effects of Nonlinearities upon Time Response 165 4.10 Laplace Transform Solution of State Equations 167 4.11 Time Domain Solution of State Equations 171 Case Studies 175 Summary 181 Review Questions 182 Cyber Exploration Laboratory 183 Hardware Interface Laboratory 186 Bibliography 192 5. Reduction of Multiple Subsystems 194 5.1 Introduction 195 5.2 Block Diagrams 195 5.3 Analysis and Design of Feedback Systems 204 5.4 Signal-Flow Graphs 207 5.5 Mason’s Rule 210 5.6 Signal-Flow Graphs of State Equations 213 5.7 Alternative Representations in State Space 215 5.8 Similarity Transformations 224 Case Studies 231 Summary 237 Review Questions 237 Cyber Exploration Laboratory 238 Bibliography 240 6. Stability 242 6.1 Introduction 243 6.2 Routh-Hurwitz Criterion 246 6.3 Routh-Hurwitz Criterion: Special Cases 248 6.4 Routh-Hurwitz Criterion: Additional Examples 254 6.5 Stability in State Space 261 Case Studies 264 Summary 266 Review Questions 266 Cyber Exploration Laboratory 267 Bibliography 268 7. Steady-State Errors 270 7.1 Introduction 271 7.2 Steady-State Error for Unity Feedback Systems 274 7.3 Static Error Constants and System Type 280 7.4 Steady-State Error Specifications 283 7.5 Steady-State Error for Disturbances 286 7.6 Steady-State Error for Nonunity-Feedback Systems 288 7.7 Sensitivity 291 7.8 Steady-State Error for Systems in 0State Space 294 Case Studies 297 Summary 300 Review Questions 301 Cyber Exploration Laboratory 302 Bibliography 303 8. Root Locus Techniques 305 8.1 Introduction 306 8.2 Defining the Root Locus 310 8.3 Properties of the Root Locus 312 8.4 Sketching the Root Locus 314 8.5 Refining the Sketch 319 8.6 An Example 328 8.7 Transient Response Design via Gain Adjustment 331 8.8 Generalized Root Locus 335 8.9 Root Locus for Positive-Feedback Systems 337 8.10 Pole Sensitivity 339 Case Studies 341 Summary 346 Review Questions 347 Cyber Exploration Laboratory 347 Hardware Interface Laboratory 349 Bibliography 356 9. Design Via Root Locus 358 9.1 Introduction 359 9.2 Improving Steady-State Error via Cascade Compensation 362 9.3 Improving Transient Response via Cascade Compensation 371 9.4 Improving Steady-State Error and Transient Response 383 9.5 Feedback Compensation 396 9.6 Physical Realization of Compensation 404 Case Studies 409 Summary 413 Review Questions 414 Cyber Exploration Laboratory 415 Hardware Interface Laboratory 417 Bibliography 419 10. Frequency Response Techniques 421 10.1 Introduction 422 10.2 Asymptotic Approximations: Bode Plots 427 10.3 Introduction to the Nyquist Criterion 446 10.4 Sketching the Nyquist Diagram 451 10.5 Stability via the Nyquist Diagram 456 10.6 Gain Margin and Phase Margin via the Nyquist Diagram 460 10.7 Stability, Gain Margin, and Phase Margin via Bode Plots 462 10.8 Relation Between Closed-Loop Transient and Closed-Loop Frequency Responses 466 10.9 Relation Between Closed- and Open-Loop Frequency Responses 469 10.10 Relation Between Closed-Loop Transient and Open-Loop Frequency Responses 474 10.11 Steady-State Error Characteristics from Frequency Response 478 10.12 Systems with Time Delay 482 10.13 Obtaining Transfer Functions Experimentally 487 Case Study 491 Summary 492 Review Questions 493 Cyber Exploration Laboratory 494 Bibliography 496 11. Design Via Frequency Response 498 11.1 Introduction 499 11.2 Transient Response via Gain Adjustment 500 11.3 Lag Compensation 503 11.4 Lead Compensation 508 11.5 Lag-Lead Compensation 514 Case Studies 523 Summary 525 Review Questions 525 Cyber Exploration Laboratory 526 Bibliography 527 12. Design Via State Space 528 12.1 Introduction 529 12.2 Controller Design 530 12.3 Controllability 537 12.4 Alternative Approaches to Controller Design 540 12.5 Observer Design 546 12.6 Observability 553 12.7 Alternative Approaches to Observer Design 556 12.8 Steady-State Error Design via Integral Control 563 Case Study 567 Summary 572 Review Questions 573 Cyber Exploration Laboratory 574 Bibliography 575 13. Digital Control Systems 577 13.1 Introduction 578 13.2 Modeling the Digital Computer 581 13.3 The z-Transform 584 13.4 Transfer Functions 589 13.5 Block Diagram Reduction 593 13.6 Stability 596 13.7 Steady-State Errors 603 13.8 Transient Response on the z-Plane 607 13.9 Gain Design on the z-Plane 609 13.10 Cascade Compensation via the s-Plane 612 13.11 Implementing the Digital Compensator 616 Case Studies 619 Summary 623 Review Questions 624 Cyber Exploration Laboratory 625 Bibliography 627 Problems P-1 Appendix A1 List of Symbols A-1 Appendix A2 Antenna Azimuth Position Control System A-5 Appendix A3 Unmanned Free-Swimming Submersible Vehicle A-7 Appendix A4 Key Equations A-8 Glossary G-1 Answers To Selected Problems ANS-1 Index I-1 Appendix B Matlab Tutorial (Available in e-text for students) Appendix C Simulink Tutorial (Available in e-text for students) Appendix D LabVIEW Tutorial (Available in e-text for students) Appendix E MATLAB’s GUI Tools Tutorial (Available in e-text for students) Appendix F MATLAB’s Symbolic Math Toolbox Tutorial (Available in e-text for students) Appendix G Matrices, Determinants, and Systems of Equations (Available in e-text for students) Appendix H Control System Computational Aids (Available in e-text for students) Appendix I Derivation of a Schematic for a DC Motor (Available in e-text for students) Appendix J Derivation of the Time Domain Solution of State Equations (Available in e-text for students) Appendix K Solution of State Equations for t0 ≠ 0 (Available in e-text for students) Appendix L Derivation of Similarity Transformations (Available in e-text for students) Appendix M Root Locus Rules: Derivations (Available in e-text for students)

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Book SynopsisTable of ContentsAbout the Author xv Preface xvii 1 A Brief History of Reference Frame Theory 1 References 3 2 Tesla’s Rotating Magnetic Field 5 2.1 Introduction 5 2.2 Rotating Magnetic Field for Symmetrical Two-Phase Stator Windings 5 2.3 Rotating Magnetic Field for Symmetrical Three-Phase Stator Windings 11 2.4 Rotating Magnetic Field for Symmetrical Two-Phase Rotor Windings 13 2.5 Rotating Magnetic Field for Symmetrical Three-Phase Rotor Windings 15 2.6 Closing Comments 17 References 17 3 Tesla’s Rotating Magnetic Field and Reference Frame Theory 19 3.1 Introduction 19 3.2 Transformation of Two-Phase Symmetrical Stator Variables to the Arbitrary Reference Frame 20 3.3 Transformation of Two-Phase Symmetrical Rotor Variables to the Arbitrary Reference Frame 24 3.4 Transformation of Three-Phase Stator and Rotor Variables to the Arbitrary Reference Frame 26 3.5 Balanced Steady-State Stator Variables Viewed from Any Reference Frame 31 3.6 Closing Comments 35 References 35 4 Equivalent Circuits for the Symmetrical Machine 37 4.1 Introduction 37 4.2 Flux-Linkage Equations for a Magnetically Linear Two-Phase Symmetrical Machine 37 4.3 Flux-Linkage Equations in the Arbitrary Reference Frame 39 4.4 Torque Expression in Arbitrary Reference Frame 41 4.5 Instantaneous and Steady-State Phasors 42 4.6 Flux-Linkage Equations for a Magnetically Linear Three-Phase Symmetrical Machine and Equivalent Circuit 45 4.7 Closing Comments 49 References 50 5 Synchronous Machines 51 5.1 Introduction 51 5.2 Synchronous Machine 51 5.3 Equivalent Circuit For Three-Phase Synchronous Generator 53 5.4 Closing Comment 57 Reference 57 6 Brushless dc Drive with Field Orientation 59 6.1 Introduction 59 6.2 The Permanent-Magnet ac Machine 59 6.3 Instantaneous and Steady-State Phasors 62 6.4 Field Orientation of a Brushless dc Drive 65 6.5 Torque Control of a Brushless dc Drive 75 6.6 Closing Comments 78 References 79 7 Field Orientation of Induction Machine Drives 81 7.1 Introduction 81 7.2 Field Orientation of a Symmetrical Machine 81 7.3 Torque Control of Field-Orientated Symmetrical Machine 86 7.4 Closing Comments 89 References 89 8 Additional Applications of Reference Frame Theory 91 8.1 Introduction 91 8.2 Neglecting Stator Transients 91 8.3 Symmetrical Components Derived by Reference Frame Theory 93 8.4 Multiple Reference Frames 97 8.5 Closing Comments 97 References 97 Index 99

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Book SynopsisTable of ContentsList of Contributors xiii Preface xvii 1 Biofuels: Classification, Conversion Technologies, Optimization Techniques and Applications 1 Sakthivel R, Abbhijith H, Harshini G V, Musunuri Shanmukha Vardhan and Krushna Prasad Shadangi 1.1 Introduction 2 1.2 Classification of Biofuels 5 1.2.1 First-Generation Biofuels 5 1.2.2 Second-Generation Biofuels 7 1.2.3 Third-Generation Algal Biofuels 9 1.3 Commonly Used Conversion Technologies 10 1.3.1 Gasification 10 1.3.1.1 Factors Influencing Gasification 12 1.3.2 Pyrolysis 13 1.3.2.1 Production of Bio-Oil from Pyrolysis 13 1.3.3 Hydrothermal Processes 15 1.3.3.1 Hydrothermal Carbonization 16 1.3.3.2 Hydrothermal Liquefaction 16 1.3.3.3 Hydrothermal Gasification 16 1.3.4 Transesterification 17 1.4 Commonly Used Optimization Techniques 19 1.4.1 Response Surface Methodology 19 1.4.2 Genetic Algorithm 22 1.5 Application of Biofuels in Transportation Sector 24 1.5.1 Automobile Sector 24 1.5.2 Aviation Sector 25 Conclusion 27 References 27 2 Technical Challenges and Prospects of Renewable Fuel Generation and Utilization at a Global Scale 31 Rajesh K. Srivastava 2.1 Introduction 32 2.2 Biofuel Synthesis 33 2.2.1 Biomass Energy 34 2.2.2 Biofuels 36 2.2.3 Biodiesel 39 2.3 Challenges for Bioenergy Generation 44 2.3.1 Operation Challenges in Biomass Energy Process 44 2.3.2 Economic Challenges in Biomass Energy Process 48 2.3.3 Social Challenges in Biomass Energy Processes 48 2.3.3.1 Conflicting Decision on Utility of Biomass Resources 48 2.3.3.2 Land Use Issue or Problems on Biomass Cultivation or Utilization 49 2.3.3.3 Environmental Impact of Biomass Resources 49 2.3.4 Policy and Regulatory Challenges for Biomass Energy Utility 49 2.4 Conclusions 50 Abbreviations 50 References 51 3 Engineered Microbial Systems for the Production of Fuels and Industrially Important Chemicals 59 Sushma Chauhan, Balasubramanian Velramar, Sneha Kumari, Anushri Keshri, Shalini Pandey, Shivam Pandey, Tanushree Baldeo Madavi, Vargobi Mukherjee, Meenakshi Jha and Pamidimarri D. V. N. Sudheer 3.1 Introduction 60 3.2 Microbial Systems for Biofuels and Chemicals Production 62 3.2.1 Microbial Systems for Genetic Engineering and Cellular Fabrication 64 3.2.2 Engineering of Microbial Cell Systems for Biofuels Production 65 3.2.2.1 Alcohols 65 3.2.3 Engineering of Microbial Cell Systems for Chemical Synthesis 73 3.2.3.1 Organic Acids 73 3.2.3.2 Fatty Alcohols 76 3.2.3.3 Bioplastic 77 3.3 Conclusions 78 References 87 4 Production of Biomethane and Its Perspective Conversion: An Overview 93 Rajesh K. Srivastava and Prakash Kumar Sarangi 4.1 Introduction 93 4.1.1 Sources of Methane 95 4.1.2 Methane from Human Activity 96 4.1.3 Impact of Methane on Climatic Change and Future 96 4.1.4 Advancements and Challenges 97 References 100 5 Microalgal Biomass Synthesized Biodiesel: A Viable Option to Conventional Fuel Energy in Biorefinery 105 Neha Bothra, P. Maniharika and Rajesh K. Srivastava 5.1 Introduction 106 5.2 Diesel 109 5.2.1 Biodiesel 112 5.3 Production of Biodiesel 113 5.3.1 Origin of Biofuels 113 5.3.2 Biodiesel Production from Algae 114 5.3.3 Intensity of Radiant Light 116 5.3.4 Lipid Content 117 5.3.5 Biomass Culturing Conditions 117 5.3.5.1 Temperature of Cultivation 118 5.3.5.2 pH of Cultivation 119 5.3.5.3 Duration Period of Light of Cultivation 119 5.3.5.4 Carbon Uptake of Cultivation 119 5.3.5.5 Oxygen Generation in Cultivation 119 5.3.5.6 Mixing Rates of Cultivation 120 5.3.5.7 Nutrient Uptake of Cultivation 120 5.4 Harvesting of Microalgae 120 5.4.1 Extraction of Oil 120 5.4.1.1 Varying n-Hexane to Algae Ratio 122 5.4.1.2 Varying the Algal Biomass Size 123 5.4.1.3 Varying Contact Time between n-Hexane and Algae Biomass 123 5.4.2 Transesterification 125 5.5 Conclusion 125 Abbreviations 125 References 126 6 Algae Biofuel Production Techniques: Recent Advancements 131 Trinath Biswal, Krushna Prasad Shadangi and Prakash Kumar Sarangi 6.1 Introduction 131 6.2 Technologies for Conversion if Algal Biofuels 133 6.2.1 Thermochemical Conversion of Microalgae Biomass into Biofuel 133 6.2.1.1 Gasification 133 6.2.1.2 Thermochemical Liquefaction 134 6.2.1.3 Pyrolysis 134 6.2.1.4 Direct Combustion 136 6.2.2 Biochemical Conversion 136 6.2.2.1 Anaerobic Digestion 138 6.2.2.2 Alcoholic Fermentation 139 6.2.2.3 Photobiological Hydrogen Production 139 6.3 Production of Biodiesel from Algal Biomass 140 6.3.1 Transesterification 141 6.4 Genetic Engineering Toward Biofuels Production 142 6.5 Summary 143 References 144 7 Technologies of Microalgae Biomass Cultivation for Bio-Fuel Production: Challenges and Benefits 147 Trinath Biswal, Krushna Prasad Shadangi and Prakash Kumar Sarangi 7.1 Introduction 148 7.2 Challenges Towards Algae Biofuel Technology 149 7.3 Biology Related with Algae 150 7.4 Algae Biofuels 153 7.5 Benefits of Microalgal Biofuels 154 7.6 Technologies for Production of Microalgae Biomass 160 7.6.1 Photoautotrophic Production 161 7.6.1.1 Open Pond Production Systems 161 7.6.1.2 Closed Photobioreactor Systems 163 7.6.1.3 Hybrid Production Systems 165 7.6.2 Heterotrophic Method Production 166 7.6.3 Mixotrophic Production 166 7.6.4 Photoheterotrophic Cultivation 168 7.7 Impact of Microalgae on the Environment 169 7.8 Advantages of Utilizing Microalgae Biomass for Biofuels 171 7.9 Conclusion 172 References 172 8 Agrowaste Lignin as Source of High Calorific Fuel and Fuel Additive 179 Harit Jha and Neha Namdeo 8.1 Agrowaste 179 8.2 Lignin 180 8.2.1 Structure of Lignin 181 8.2.2 Types of Lignin 183 8.2.3 Applications of Lignin 184 8.3 Lignin as Fuel 186 8.3.1 Bioethanol Production 189 8.3.2 Bio-Oil Production 191 8.3.3 Syngas Production 192 8.4 As Fuel Additive 192 8.5 Conclusion 193 References 194 9 Fly Ash Derived Catalyst for Biodiesel Production 203 Trinath Biswal, Krushna Prasad Shadangi and Prakash Kumar Sarangi 9.1 Introduction 204 9.2 Coal Fly Ash: Resources and Utilization 205 9.3 Composition of Coal Fly Ash 209 9.4 Economic Perspective of Biodiesel 212 9.5 Biodiesel from Fly Ash Derived Catalyst 214 9.5.1 Coal Fly Ash-Derived Sodalite as a Heterogeneous Catalyst 214 9.5.1.1 Zeolite Synthesis from Coal Fly Ash 215 9.5.1.2 Production of Biodiesel through Heterogeneous Transesterification 215 9.5.2 CaO/Fly Ash Catalyst for Transesterification of Palm Oil in Production of Biodiesel 216 9.5.2.1 Production of Biodiesel 217 9.5.2.2 Transesterification Reaction 218 9.5.3 Biodiesel Production Catalysed by Sulphated Fly-Ash 218 9.5.4 Composite Catalyst of Palm Mill Fly Ash-Supported Calcium Oxide (Eggshell Powder) 220 9.5.4.1 Preparation of the CaO/PMFA Catalyst 221 9.5.5 Kaliophilite-Fly Ash Based Catalyst for Production of Biodiesel 221 9.5.5.1 Synthesis of Kaliophilite 223 9.5.6 Fly-Ash Derived Zeolites for Production of Biodiesel 223 Conclusion 225 References 226 10 Emerging Biomaterials for Bone Joints Repairing in Knee Joint Arthroplasty: An Overview 233 Shankar Swarup Das 10.1 Introduction 234 10.2 Resources and Selecting Criteria 234 10.3 Reasons for Bone Defects of Tibia Plateau 235 10.4 Classification of Bone Defects of Medial Tibia Plateau 236 10.5 Different Biomaterials for Tibial Plateau Bone Defects 237 10.6 New Biomaterials to Repair Bone Defects in Tibia Plateau 243 10.7 Conclusion 244 References 245 About the Editor 253 Index 255

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Book SynopsisReviews recent advances in catalytic biodiesel synthesis, highlighting various nanocatalysts and nano(bio)catalysts developed for effective biodiesel production Nano- and Biocatalysts for Biodiesel Production delivers an essential reference for academic and industrial researchers in biomass valorization and biofuel industries. The book covers both nanocatalysts and biocatalysts, bridging the gap between homogenous and heterogenous catalysis. Readers will learn about the techno-economical and environmental aspects of biodiesel production using different feedstocks and catalysts. They will also discover how nano(bio)catalysts can be used as effective alternatives to conventional catalysts in biodiesel production due to their unique properties, including reusability, high activation energy and rate of reaction, easy recovery, and recyclability. Readers will benefit from the inclusion of: Introductions to CaO nanocatalysts, zeolite nanocatTable of ContentsPreface xv List of Contributors xix 1 Biodiesel: Different Feedstocks, Conventional Methods, and Factors Affecting its Production 1Hossein Esmaeili and Sajad Tamjidi 1.1 Introduction 1 1.2 Different Feedstocks for Biodiesel Production 3 1.2.1 Vegetable Sources 3 1.2.2 Waste Oils 3 1.2.3 Animal Fats 5 1.2.4 Microalga Oil 6 1.3 Conventional Methods of Biodiesel Production 8 1.3.1 Microemulsion 8 1.3.2 Pyrolysis or Thermal Cracking 8 1.3.3 Transesterification 8 1.4 Catalysts Used in Biodiesel Production 9 1.4.1 Homogeneous Catalysts 9 1.4.1.1 Homogeneous Alkaline Catalysts 9 1.4.1.2 Homogeneous Acidic Catalysts 9 1.4.2 Heterogeneous Catalysts 10 1.4.2.1 Heterogeneous Alkaline Catalysts 10 1.4.2.2 Heterogeneous Acid Catalysts 10 1.4.3 Enzymatic Catalysts 11 1.4.4 Nanocatalysts 12 1.5 Effects of Different Factors on Biodiesel Production Yield 15 1.5.1 Reaction Temperature 15 1.5.2 Alcohol to Oil Molar Ratio 16 1.5.3 Reaction Time 17 1.5.4 Catalyst Dosage 17 1.5.5 pH 17 1.5.6 Mixing Rate 17 1.5.7 Fatty Acids 18 1.5.8 Water Content 18 1.6 Physical Properties of Biodiesel 18 1.7 Conclusions 19 References 20 2 Nano(Bio)Catalysts: An Effective Tool to Utilize Waste Cooking Oil for the Biodiesel Production 31Rushikesh Fopase, Swati Sharma and Lalit M. Pandey 2.1 Introduction 31 2.2 Waste Cooking Oils 33 2.3 Pretreatment of WCOs 33 2.4 Transesterification Process 34 2.4.1 Kinetics of Transesterification 36 2.5 Enzymatic Biocatalysts 37 2.5.1 Lipases 38 2.5.1.1 Extracellular Lipases 38 2.5.1.2 Intracellular Lipases 39 2.6 Enzyme Immobilization Techniques 41 2.7 Physical Methods 42 2.7.1 Adsorption 42 2.7.2 Encapsulation 45 2.7.3 Entrapment 46 2.8 Chemical Methods 47 2.8.1 Covalent Bonding 47 2.8.2 Cross-Linking 49 2.8.3 Summary 50 2.9 Conclusions 50 References 51 3 A Review on the Use of Bio/Nanostructured Heterogeneous Catalysts in Biodiesel Production 59Samuel Santos, Jaime Puna, João Gomes and Jorge Marchetti 3.1 Introduction 59 3.2 Use of Micro- and Nanostructured Heterogeneous Catalysts in Biodiesel Production 62 3.2.1 Microstructured Heterogeneous Catalysts 62 3.2.1.1 Solid Acid Catalysts 62 3.2.1.2 Solid Base Catalysts 63 3.2.2 Nanostructured Heterogeneous Catalysts 65 3.2.2.1 Gas Condensation 65 3.2.2.2 Vacuum Deposition 65 3.2.2.3 Chemical Deposition 66 3.2.2.4 Sol-Gel Method 66 3.2.2.5 Impregnation 67 3.2.2.6 Nanogrinding 68 3.2.2.7 Calcination-Hydration-Dehydration 68 3.3 Enzymatic Catalysis 69 3.3.1 Heterogeneous Biocatalysts (Lipases) and Their Immobilization 69 3.3.1.1 Physical Adsorption 70 3.3.1.2 Entrapment 70 3.3.1.3 Covalent Bonding 71 3.3.1.4 Cross-Linking 72 3.3.2 Nano(Bio)Catalysts: Immobilization of Enzymes on Nanosupports 73 3.3.2.1 Nanoparticles 73 3.3.2.2 Carbon Nanotubes 75 3.3.2.3 Nanofibers 76 3.3.2.4 Nanocomposites 76 3.4 Conclusions 77 References 78 4 Calcium-Based Nanocatalysts in Biodiesel Production 93Priti R. Pandit and Archit Mohapatra 4.1 Introduction 93 4.2 Nanocatalysts 94 4.3 CaO-Based Nanocatalysts for Biodiesel Production 95 4.3.1 Synthesis and Characterization of CaO-Based Nanocatalysts Using Waste Material 99 4.3.2 CaO Nanocatalysts Supported with Metal Oxides for Biodiesel Production 102 4.4 Effects of Different Parameters on Biodiesel Production 105 4.4.1 Reaction Time 105 4.4.2 Temperature 105 4.4.3 Methanol to Oil Molar Ratio 106 4.4.4 Catalyst Load 106 4.5 Reusability and Leaching of Nanocatalysts 106 4.6 Conclusions 107 References 107 5 Titanium Dioxide-Based Nanocatalysts in Biodiesel Production 115Elijah Olawale Ajala, Mary Adejoke Ajala and Harvis Bamidele Saka 5.1 Introduction 115 5.2 Natural Occurrences of Titania 117 5.2.1 Rutile 117 5.2.2 Anatase 118 5.2.3 Rhombic Brookite 118 5.2.4 Kaolin Clays 118 5.2.5 Ilmenites or Manaccanite 120 5.3 Precursors Used for the Synthesis of TiO2 NPs 120 5.3.1 Titanium Tetrachloride 121 5.3.2 Titanium Tetraisopropoxide 121 5.3.3 Titanium Butoxide 122 5.4 Methods for the Synthesis of TiO2 NPs 122 5.4.1 Physical Methods 122 5.4.1.1 Ball Milling 122 5.4.1.2 Laser Ablation/Photoablation 123 5.4.1.3 Sputtering 123 5.4.2 Chemical Methods 123 5.4.2.1 Microemulsion 123 5.4.2.2 Precipitation 124 5.4.2.3 Sol-Gel 124 5.4.2.4 Hydrothermal 125 5.4.2.5 Solvothermal 125 5.4.2.6 Electrochemical/Deposition 125 5.4.2.7 Sonochemical 126 5.4.2.8 Direct Oxidation 126 5.4.3 Biological Methods 126 5.4.3.1 Green Synthesis Using Plant Extracts 126 5.4.3.2 Microbial Synthesis 128 5.4.3.3 Enzyme-Mediated Synthesis 129 5.5 Methods for the Synthesis of TiO2-Based Nanocatalysts 130 5.5.1 Wet Impregnation 130 5.5.2 Dry Impregnation 131 5.6 TiO2-Based Nanocatalysts for Biodiesel Production 131 5.6.1 Sulfated TiO2 Nanocatalysts 131 5.6.2 Alkaline TiO2 Nanocatalysts 133 5.6.3 Co-Transition TiO2 Nanocatalysts 133 5.6.4 Alkali TiO2 Nanocatalysts 134 5.6.5 Bimetallic TiO2 Nanocatalysts 135 5.6.5.1 TiO2-Pd-Ni 135 5.6.5.2 TiO2-Au-Cu 135 5.7 Other TiO2 Nanocomposite Catalysts 135 5.8 Conclusions 136 References 136 6 Zinc-Based Nanocatalysts in Biodiesel Production 143Avinash P. Ingle 6.1 Introduction 143 6.2 Feedstocks Used for Biodiesel Production 144 6.2.1 Vegetable Oils 144 6.2.2 Microbial Oils 145 6.2.3 Animal Fats 145 6.2.4 Waste Oils 145 6.2.5 Biomass 146 6.3 Conventional Methods of Biodiesel Production 146 6.3.1 Pyrolysis 146 6.3.2 Transesterification 146 6.3.2.1 Homogeneous Acid and Base (Alkali)-Catalyzed Transesterification 146 6.3.2.2 Heterogeneous Acid and Base (Alkali)-Catalyzed Transesterification 147 6.3.2.3 Enzymatic Transesterification 147 6.4 Nanotechnology in Biodiesel Production 148 6.5 Zinc-Based Nanocatalysts in Biodiesel Production 148 6.6 Conclusions 151 References 152 7 Carbon-Based Nanocatalysts in Biodiesel Production 157Rahul Bhagat, Harris Panakkal, Indarchand Gupta and Avinash P. Ingle 7.1 Introduction 157 7.2 Feedstocks Used for Biodiesel Production 158 7.2.1 Vegetable Oils 158 7.2.2 Algae 159 7.2.3 Animal Fats 160 7.2.4 Waste Cooking Oils 160 7.3 Conventional Heterogeneous Catalysts 160 7.4 Carbon-Based Heterogeneous Nanocatalysts 164 7.4.1 Carbon Nanotubes 166 7.4.2 Sulfonated Carbon Nanotubes 167 7.4.3 Graphene/Graphene Oxide-Based Nanocatalysts 168 7.4.4 Carbon Nanofibers and Carbon Dots 169 7.4.5 Carbon Nanohorns 170 7.4.6 Other Carbon-Based Nanocatalysts 171 7.5 Conclusions 174 References 174 8 Functionalized Magnetic Nanocatalysts in Biodiesel Production 183Kalyani Rajkumari and Lalthazuala Rokhum 8.1 Introduction 183 8.2 Relevance of Heterogeneous Catalysis in Biodiesel Production 185 8.3 Surface Modification and Functionalization of NPs 186 8.4 Applications of Functionalized Magnetic Nanocatalysts in Biodiesel Production 186 8.4.1 Acid-Functionalized Magnetic Nanocatalysts 186 8.4.2 Base-Functionalized Magnetic Nanocatalysts 189 8.4.3 Magnetic Nanocatalysts Functionalized withWaste Materials 190 8.4.4 Ionic Liquid-Immobilized Magnetic Nanocatalysts 192 8.5 Conclusions 194 References 195 9 Bio-Based Catalysts in Biodiesel Production 201Umer Rashid, Shehu-Ibrahim Akinfalabi, Naeemah A. Ibrahim and Chawalit Ngamcharussrivichai 9.1 Introduction 201 9.2 Biodiesel: A Potential Source of Renewable Energy 204 9.2.1 Progress in Biodiesel Development 204 9.2.2 Development of Biodiesel in Malaysia 205 9.2.3 Biodiesel Feedstocks 206 9.2.3.1 PFAD as a Biodiesel Feedstock 207 9.2.4 Common Methods Used for Biodiesel Reaction 208 9.2.4.1 Esterification 209 9.2.4.2 Transesterification 210 9.3 Homogeneous Catalysis in Biodiesel Production 211 9.4 Heterogeneous Catalysis in Biodiesel Production 213 9.5 Catalyst Supports 215 9.5.1 Alumina 216 9.5.2 Silicate 216 9.5.3 Zirconium Oxide 217 9.5.4 Activated Carbon 217 9.6 Heterogeneous Bio-Based Acid Catalysts 217 9.7 Synthesis of Bio-Based Solid Acid Catalysts 218 9.7.1 Palm Tree Fronds and Spikelets 219 9.7.2 Jatropha curcas 219 9.7.3 Coconut Shells 220 9.7.4 Rice Husks 220 9.7.5 Bamboo 221 9.7.6 Cocoa Pod Husks 221 9.7.7 Hardwoods 222 9.7.8 Peanut Hulls 222 9.7.9 Wood Mixtures 223 9.7.10 Palm Kernel Shells 223 9.8 Magnetic Bio-Based Catalysts for Biodiesel Production 224 9.9 Characterization of Bio-Based Catalysts 228 9.9.1 Field Emission Scanning Electron Microscopy (FESEM) 228 9.9.2 Fourier Transform Infrared (FT-IR) 229 9.9.3 X-Ray Diffraction (XRD) 229 9.9.4 Thermogravimetric Analysis (TGA) 230 9.9.5 Temperature-Programmed Desorption – Ammonia (TPD-NH3) 231 9.9.6 Brunauer–Emmett–Teller (BET) Analysis 231 9.10 Reaction Parameters Affecting Biodiesel Production 232 9.10.1 Reaction Time 232 9.10.2 Catalyst Concentration 232 9.10.3 Methanol to Fat/Oil Molar Ratio 232 9.10.4 Reaction Temperature 233 9.10.5 Mixing Rate 235 9.11 Conclusions 235 References 236 10 Heterogeneous Nanocatalytic Conversion of Waste to Biodiesel 249Nilutpal Bhuyan, Manash J. Borah, Neelam Bora, Dipanka Saikia, Dhanapati Deka and Rupam Kataki 10.1 Introduction 249 10.2 Role of Catalysts in Biodiesel Production 250 10.3 Feedstocks for Biodiesel Production 251 10.3.1 First-Generation Feedstocks or Edible Oils 251 10.3.2 Second-Generation Feedstocks or Non-Edible Oils 252 10.3.3 Third-Generation Feedstocks or Algae 252 10.3.4 Other Feedstocks 253 10.4 Biodiesel Production Process 253 10.4.1 Acid-Catalyzed Transesterification 254 10.4.1.1 Mechanism of Acid-Catalyzed Transesterification 256 10.4.2 Alkali- or Base-Catalyzed Transesterification 256 10.4.2.1 Mechanism of Alkali- or Base-Catalyzed Transesterification 258 10.4.3 Other Types of Transesterification 258 10.5 Variables Affecting Transesterification 259 10.6 Heterogeneous Nanocatalysts for Biodiesel Production 260 10.7 Characterization of Nanoparticles Used for Biodiesel Production 262 10.7.1 X-Ray Diffraction (XRD) 262 10.7.2 Scanning Electron Microscopy (SEM) 262 10.7.3 Energy Dispersive X-Ray Analysis (EDX) 262 10.7.4 Transmission Electron Microscopy (TEM) 264 10.7.5 Atomic Force Microscopy (AFM) 264 10.7.6 Raman Spectroscopy 264 10.7.7 Fourier Transform Infrared Spectroscopy (FT-IR) 264 10.7.8 X-Ray Photoelectron Spectroscopy (XPS) 264 10.7.9 Thermogravimetric Analysis (TGA) 265 10.8 Influence of Nanoparticle Properties on Biodiesel Production 265 10.9 Safety Issues Around the Application of Nanocatalysts in Biodiesel Production 267 10.10 Future Perspectives 267 10.11 Conclusions 268 References 269 11 Application of Rare Earth Cation-Exchanged Nanozeolite as a Support for the Immobilization of Fungal Lipase and their Use in Biodiesel Production 279Guilherme de Paula Guarnieri, Adriano de Vasconcellos, Fábio Rogério de Moraes and José Geraldo Nery 11.1 Introduction 279 11.2 Case Study 282 11.2.1 Origins of Materials and Enzymes 282 11.2.2 Preparation of Na-FAU Nanozeolites 282 11.2.3 Ion-Exchange Experiments 283 11.2.4 Enzyme Immobilization on to Nanozeolitic Supports 283 11.2.5 Physicochemical Characterization of As-Synthesized Nanozeolites and Nanozeolite–Enzyme Complexes 284 11.2.6 Synthesis of FAAEs 286 11.2.7 FAEE Yields Obtained with Nanozeolite Complexes 287 11.2.8 Model of Lipase Immobilization on to Zeolite Supports 287 11.3 Conclusions 290 References 290 12 Lipase-Immobilized Magnetic Nanoparticles: Promising Nanobiocatalysts for Biodiesel Production 295Tooba Touqeer, Muhammad Waseem Mumtaz and Hamid Mukhtar 12.1 Introduction 295 12.2 Transesterification for Biodiesel Production 296 12.2.1 Homogenous Catalysts 296 12.2.2 Heterogeneous Catalysts 297 12.2.3 Enzymatic Catalysts 297 12.3 Advantages of Using Magnetic Nanobiocatalysts 297 12.3.1 High Enzyme Loading and Surface Area to Volume Ratio 298 12.3.2 Low Mass Transfer Restriction and High Brownian Movement 299 12.3.3 Effortless Recovery and Reusability 299 12.3.4 Stability 299 12.4 Synthesis of Nanobiocatalysts 299 12.4.1 Preparation and Functionalization of Nanostructures 299 12.4.2 Immobilizing Enzymes on Nanomaterials 300 12.4.2.1 Adsorption Immobilization 300 12.4.2.2 Covalent Immobilization 301 12.5 Techniques for the Characterization of Nanobiocatalysts 302 12.6 Transesterification Using Magnetic Nanobiocatalysts 303 12.7 Factors Affecting Enzymatic Transesterification 304 12.7.1 Type of Alcohol Used 304 12.7.2 Solvent 305 12.7.3 Reaction Temperature 306 12.7.4 Water Content 306 12.7.5 Alcohol to Oil Molar Ratio 306 12.7.6 Source of Lipase 306 12.8 Conclusions 307 References 307 13 Technoeconomic Analysis of Biodiesel Production Using Different Feedstocks 313Shemelis Nigatu Gebremariam 13.1 Introduction 313 13.2 Biodiesel Production Technologies 315 13.3 Feedstock Types for Biodiesel Production 317 13.4 Technical Performance Evaluation of Biodiesel Production 318 13.4.1 Fuel Properties of Biodiesel 319 13.4.1.1 Flash Point 319 13.4.2 Cold Flow Properties 319 13.4.2.1 Cloud Point 320 13.4.2.2 Pour Point 320 13.4.2.3 Cold Filter Plugging Point (CFPP) 321 13.4.3 Cetane Number 321 13.4.4 Density 322 13.4.5 Viscosity 323 13.4.6 Oxidation Stability 323 13.4.7 Biodiesel Quality Standards 324 13.5 Economic Performance Evaluation of the Biodiesel Production Process 324 13.5.1 Fixed Capital Investment Cost 326 13.5.2 Working Capital (Operating) Cost 329 13.6 Conclusions 330 References 331 Index 339

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Book SynopsisTable of ContentsPreface xvi 1 Introduction 1 1.1 Historical Perspective 1 1.1.1 Need for Fiber-Optic Communications 2 1.1.2 Evolution of Lightwave Systems 4 1.2 Basic Concepts 8 1.2.1 Analog and Digital Signals 8 1.2.2 Channel Multiplexing 11 1.2.3 Modulation Formats 13 1.3 Optical Communication Systems 16 1.4 Lightwave System Components 18 1.4.1 Optical Fibers as a Communication Channel 18 1.4.2 Optical Transmitters 18 1.4.3 Optical Receivers 19 Problems 20 References 21 2 Optical Fibers 24 2.1 Geometrical-Optics Description 24 2.1.1 Step-Index Fibers 25 2.1.2 Graded-Index Fibers 27 2.2 Wave Propagation 29 2.2.1 Maxwell’s Equations 29 2.2.2 Fiber Modes 31 2.2.3 Single-Mode Fibers 34 2.3 Dispersion in Single-Mode Fibers 37 2.3.1 Group-Velocity Dispersion 38 2.3.2 Material Dispersion 39 2.3.3 Waveguide Dispersion 40 2.3.4 Higher-Order Dispersion 41 2.3.5 Polarization-Mode Dispersion 43 2.4 Dispersion-Induced Limitations 44 2.4.1 Basic Propagation Equation 45 2.4.2 Chirped Gaussian Pulses 46 2.4.3 Limitations on the Bit Rate 49 2.5 Fiber Losses 52 2.5.1 Attenuation Coefficient 52 2.5.2 Material Absorption 53 2.5.3 Rayleigh Scattering 54 2.5.4 Waveguide Imperfections 55 2.6 Nonlinear Optical Effects 56 2.6.1 Stimulated Light Scattering 56 2.6.2 Nonlinear Phase Modulation 60 2.6.3 Four-Wave Mixing 63 2.7 Fiber Design and Fabrication 64 2.7.1 Silica Fibers 64 2.7.2 Plastic Optical Fibers 67 2.7.3 Cables and Connectors 69 Problems 70 References 72 3 Optical Transmitters 75 3.1 Semiconductor Laser Physics 75 3.1.1 Spontaneous and Stimulated Emissions 76 3.1.2 Nonradiative Recombination 77 3.1.3 Optical Gain 78 3.1.4 Feedback and Laser Threshold 80 3.1.5 Laser Structures and Modes 81 3.2 Single-Mode Semiconductor Lasers 83 3.2.1 Distributed Feedback Lasers 83 3.2.2 Coupled-Cavity Semiconductor Lasers 85 3.2.3 Tunable Semiconductor Lasers 86 3.2.4 Vertical-Cavity Surface-Emitting Lasers 88 3.3 Semiconductor Laser Characteristics 89 3.3.1 CW Characteristics 89 3.3.2 Modulation Bandwidth 92 3.3.3 Relative Intensity Noise 94 3.3.4 Spectral Linewidth 97 3.4 Modulation Techniques 98 3.4.1 Direct Modulation 99 3.4.2 External Modulation 100 3.5 Light-Emitting Diodes 103 3.5.1 LED Characteristics 104 3.5.2 LED Structures 106 3.6 Transmitter Design 108 3.6.1 Source–Fiber Coupling 108 3.6.2 Driving Circuitry 110 3.6.3 Reliability and Packaging 111 Problems 113 References 115 4 Optical Receivers 119 4.1 Basic Concepts 119 4.1.1 Responsivity and Quantum Efficiency 119 4.1.2 Rise Time and Bandwidth 121 4.2 Common Photodetectors 122 4.2.1 p–n Photodiodes 122 4.2.2 p–i–n Photodiodes 124 4.2.3 Avalanche Photodiodes 127 4.2.4 MSM Photodetectors 133 4.3 Receiver Design 135 4.3.1 The Front End 135 4.3.2 The Linear Channel 137 4.3.3 Data-Recovery Section 138 4.3.4 Integrated Receivers 139 4.4 Receiver Noise 141 4.4.1 Noise Mechanisms 141 4.4.2 SNR of p–i–n Receivers 143 4.4.3 SNR of APD Receivers 144 4.5 Coherent Detection 148 4.5.1 Local Oscillator 148 4.5.2 Homodyne Detection 149 4.5.3 Heterodyne Detection 150 4.5.4 Signal-to-Noise Ratio 150 4.6 Receiver Sensitivity 151 4.6.1 Bit-Error Rate 151 4.6.2 Minimum Received Power 154 4.6.3 Quantum Limit of Photodetection 156 4.7 Sensitivity Degradation 157 4.7.1 Extinction Ratio 157 4.7.2 Intensity Noise 158 4.7.3 Timing Jitter 160 4.8 Receiver Performance 162 Problems 164 References 166 5 Lightwave Systems 170 5.1 System Architectures 170 5.1.1 Point-to-Point Links 170 5.1.2 Distribution Networks 172 5.1.3 Local-Area Networks 173 5.2 Design Guidelines 175 5.2.1 Loss-Limited Lightwave Systems 175 5.2.2 Dispersion-Limited Lightwave Systems 176 5.2.3 Power Budget 177 5.2.4 Rise-Time Budget 179 5.3 Long-Haul Systems 181 5.3.1 Performance-Limiting Factors 181 5.3.2 Terrestrial Lightwave Systems 183 5.3.3 Undersea Lightwave Systems 186 5.4 Sources of Power Penalty 188 5.4.1 Modal Noise 188 5.4.2 Mode-Partition Noise 190 5.4.3 Reflection Feedback and Noise 191 5.4.4 Dispersive Pulse Broadening 194 5.4.5 Frequency Chirping 195 5.4.6 Eye-Closure Penalty 197 5.5 Forward Error Correction 198 5.5.1 Error-Correcting Codes 198 5.5.2 Coding Gain 199 5.6 Computer-Aided Design 200 Problems 202 References 204 6 Multichannel Systems 208 6.1 WDM Systems and Networks 208 6.1.1 High-Capacity Point-to-Point Links 209 6.1.2 Wide-Area and Metro-Area Networks 212 6.1.3 Multiple-Access WDM Networks 215 6.2 WDM Components 216 6.2.1 Optical Filters 217 6.2.2 Multiplexers and Demultiplexers 222 6.2.3 Add–Drop Multiplexers 224 6.2.4 Star Couplers 227 6.2.5 Wavelength Routers 228 6.2.6 WDM Transmitters and Receivers 230 6.3 System Performance Issues 233 6.3.1 Linear Crosstalk 233 6.3.2 Raman-Induced Nonlinear Crosstalk 235 6.3.3 XPM-Induced Nonlinear Crosstalk 237 6.3.4 FWM-Induced Nonlinear Crosstalk 239 6.3.5 Other Design Issues 240 6.4 Time-Division Multiplexing 241 6.4.1 Time-Domain Multiplexing 242 6.4.2 Time-Domain Demultiplexing 243 6.4.3 Performance of OTDM Systems 245 6.5 Subcarrier Multiplexing 246 6.5.1 Analog and Digital SCM Systems 246 6.5.2 Orthogonal Frequency-Division multiplexing 248 6.6 Code-Division Multiplexing 250 6.6.1 Time-Domain Encoding 251 6.6.2 Frequency-Domain Encoding 253 Problems 255 References 257 7 Loss Management 264 7.1 Compensation of Fiber Losses 264 7.1.1 Periodic Amplification Scheme 265 7.1.2 Lumped Versus Distributed Amplification 267 7.1.3 Bidirectional Pumping Scheme 268 7.2 Erbium-Doped Fiber Amplifiers 269 7.2.1 Pumping and Gain Spectrum 269 7.2.2 Two-Level Model 270 7.2.3 Amplifier Noise 273 7.2.4 Multichannel Amplification 275 7.3 Raman Amplifiers 277 7.3.1 Raman Gain and Bandwidth 278 7.3.2 Raman-Induced Signal Gain 279 7.3.3 Multiple-Pump Raman Amplification 281 7.3.4 Noise Figure of Raman Amplifiers 283 7.4 Optical Signal-To-Noise Ratio 285 7.4.1 Lumped Amplification 285 7.4.2 Distributed Amplification 287 7.5 Electrical Signal-To-Noise Ratio 288 7.5.1 ASE-Induced Current Fluctuations 288 7.5.2 Impact of ASE on SNR 290 7.5.3 Noise Buildup in an Amplifier Chain 291 7.6 Receiver Sensitivity and Q Factor 292 7.6.1 Bit-Error Rate 292 7.6.2 Relation between Q Factor and Optical SNR 294 7.7 Role of Dispersive and Nonlinear Effects 295 7.7.1 Noise Growth through Modulation Instability 295 7.7.2 Noise-Induced Signal Degradation 297 7.7.3 Noise-Induced Energy Fluctuations 299 7.7.4 Noise-Induced Timing Jitter 300 7.8 Periodically Amplified Lightwave Systems 300 7.8.1 Numerical Approach 301 7.8.2 Optimum Launched Power 304 Problems 306 References 307 8 Dispersion Management 310 8.1 Dispersion Problem and Its Solution 310 8.2 Dispersion-Compensating Fibers 312 8.2.1 Conditions for Dispersion Compensation 312 8.2.2 Dispersion Maps 313 8.2.3 DCF Designs 315 8.3 Fiber Bragg Gratings 317 8.3.1 Constant-Period Gratings 318 8.3.2 Chirped Fiber Gratings 320 8.3.3 Sampled Gratings 322 8.4 Dispersion-Equalizing Filters 325 8.4.1 Gires–Tournois Filters 325 8.4.2 Mach–Zehnder and Other Filters 327 8.5 Optical Phase Conjugation 329 8.5.1 Principle of Operation 330 8.5.2 Compensation of Self-Phase Modulation 331 8.5.3 Generation of Phase-Conjugated Signal 332 8.6 Advanced Techniques 335 8.6.1 Tunable Dispersion Compensation 335 8.6.2 Higher-Order Dispersion Management 338 8.6.3 PMD Compensation 340 8.7 Electronic Dispersion Compensation 343 8.7.1 Pre-compensation at the Transmitter 343 8.7.2 Post-Compensation at the Receiver 347 Problems 349 References 351 9 Control of Nonlinear Effects 355 9.1 Impact of Fiber Nonlinearity 355 9.1.1 System Design Issues 356 9.1.2 Semianalytic Approach 359 9.1.3 Soliton and Pseudo-linear Regimes 361 9.2 Solitons in Optical Fibers 363 9.2.1 Properties of Optical Solitons 364 9.2.2 Loss-Managed Solitons 367 9.2.3 Dispersion-Managed Solitons 370 9.2.4 Timing Jitter 374 9.3 Pseudo-linear Lightwave Systems 378 9.3.1 Origin of Intrachannel Nonlinear Effects 378 9.3.2 Intrachannel Cross-Phase Modulation 380 9.3.3 Intrachannel Four-Wave Mixing 384 9.4 Management of Nonlinear Effects 387 9.4.1 Optimization of Dispersion Maps 387 9.4.2 Phase-Alternation Technique 390 9.4.3 Polarization Bit Interleaving 392 9.4.4 Optical Phase Conjugation 393 9.4.5 Phase-Sensitive Amplification 395 Problems 396 References 398 10 Coherent Lightwave Systems 402 10.1 Coherent Transmitters 403 10.1.1 Encoding of Optical Signals 403 10.1.2 Amplitude and Phase Modulators 405 10.1.3 Quadrature modulator 406 10.2 Coherent Receivers 408 10.2.1 Synchronous Heterodyne Demodulation 408 10.2.2 Asynchronous Heterodyne Demodulation 410 10.2.3 Optical Delay Demodulation 411 10.2.4 Phase Diversity and Polarization Diversity 413 10.3 Noise and Bit-Error Rate 415 10.3.1 Synchronous Heterodyne Receivers 415 10.3.2 Asynchronous Heterodyne Receivers 418 10.3.3 Receivers with Optical Delay Demodulation 419 10.4 Sources of Performance Degradation 421 10.4.1 Intensity Noise of Lasers 421 10.4.2 Phase Noise of Lasers 422 10.4.3 Effects of Fiber’s Dispersion 424 10.5 Management of Nonlinear Effects 425 10.5.1 Nonlinear Phase Noise 426 10.5.2 Compensation of Nonlinear Phase Noise 429 10.5.3 Nonlinear Interference Noise 432 10.6 Digital Signal Processing 435 10.6.1 Removal of Intermediate Frequency and Phase fluctuations 435 10.6.2 Compensation of GVD and PMD 437 10.6.3 Digital Backward Propagation 440 10.7 Experimental Progress 442 10.7.1 DPSK and DQPSK formats 442 10.7.2 QPSK and QAM formats 445 10.7.3 Coherent Orthogonal FDM 448 10.7.4 Optical Superchannels 450 10.8 Channel Capacity 452 Problems 454 References 455 11 Space-Division Multiplexing 462 11.1 SDM Technique 462 11.2 Modes of Optical Fibers 464 11.2.1 Step-Index Fibers 464 11.2.2 Graded-Index Fibers 467 11.2.3 Multicore Fibers 469 11.3 SDM Components 471 11.3.1 Design of SDM Fibers 471 11.3.2 Spatial Multiplexers and Demultiplexers 474 11.3.3 Multicore/Multimode Fiber Amplifiers 479 11.3.4 Other SDM Components 481 11.4 Modeling of SDM Systems 482 11.4.1 Multimode Coupled Nonlinear Equations 483 11.4.2 Averaged Multimode Nonlinear Equations 486 11.4.3 Nonlinear Effects in MCFs 488 11.4.4 Nonlinear Effects in MMFs 491 11.5 Experimental Progress 494 11.5.1 MCF-Based SDM Systems 494 11.5.2 MMF-Based SDM Systems 496 11.5.3 High-Capacity SDM Systems 498 Problems 499 References 500 12 Advanced Topics 505 12.1 Optical Signal Processing 506 12.1.1 Nonlinear Optical Loop Mirrors 506 12.1.2 Parametric Amplifiers 510 12.1.3 Semiconductor Optical Amplifiers 513 12.1.4 Bistable Optical Devices 516 12.1.5 Optical Flip–Flops 518 12.2 Wavelength Conversion 522 12.2.1 XPM-Based Wavelength Converters 522 12.2.2 FWM-Based Wavelength Converters 525 12.2.3 Semiconductor Waveguides 528 12.2.4 SOA-Based Wavelength Converters 530 12.3 Ultrafast Optical Switching 532 12.3.1 Time-Domain Demultiplexing 532 12.3.2 Packet Switching 536 12.3.3 Format Conversion 538 12.4 Optical Regeneration 540 12.4.1 2R Regenerators 541 12.4.2 3R Regenerators 545 12.4.3 Regeneration of Phase-Encoded Signals 549 12.5 Nonlinear Frequency-Division Multiplexing 552 12.5.1 Nonlinear Fourier Transform 552 12.5.2 Practical Implementation 554 Problems 556 References 557 A System of Units 566 B Acronyms 568 C Formula for Pulse Broadening 572 D Nyquist Pulses 574 References 575 Index 576

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Book SynopsisFlight Simulation Software Explains the many aspects of flight simulator design, including open source tools for developing an engineering flight simulator Flight simulation is an indispensable technology for civil and military aviation and the aerospace industry. Real-time simulation tools span across all aspects of aircraft development, from aerodynamics and flight dynamics to avionics and image generation systems. Knowledge of flight simulation software is vital for aerospace engineering professionals, educators, and students. Flight Simulation Software contains comprehensive and up-to-date coverage of the computer tools required to design and develop a flight simulator. Written by a noted expert with decades of experience developing flight simulators in academia, this highly practical resource enables readers to develop their own simulations with readily available open source software rather than relying on costly commercial simulation packages. The bTable of ContentsPreface xiii Aerospace Series Preface xvii Glossary xix About the Author xxiii About the Companion Website xxv 1 Design of an Engineering Flight Simulator 1 1.1 The Evolution of Flight Simulation 1 1.2 Structure of a Flight Simulator 3 1.3 Real-time Flight Simulation 6 1.3.1 The Concept of Real-time Computing 6 1.3.2 Operating Systems 8 1.3.3 Latency 9 1.4 Distributed Computing 10 1.5 Processes and Threads 15 1.5.1 Multi-tasking 15 1.5.2 Semaphores 16 1.5.3 Asynchronous Input 18 1.5.4 Real-time Scheduling 21 1.6 Software Partitioning 22 1.7 Simulator Data 24 1.8 Input and Output 29 1.8.1 Data Acquisition 29 1.8.2 Digital-to-Analogue Conversion 30 1.8.3 Analogue-to-Digital Conversion 31 1.8.4 Multiplexing 33 1.8.5 Encoders 33 1.8.6 Digital Input/Output 34 1.8.7 Signal Conditioning 35 1.8.8 Embedded Systems 36 1.8.9 USB Interfacing 40 References 42 2 Software Methods in Simulation 45 2.1 The Laplace Transform 45 2.2 Transfer Functions 47 2.3 Discrete-event Systems 54 2.4 Data Fitting 58 2.4.1 Data Sources 58 2.4.2 Least-squares Method 60 2.4.3 Spline Methods 63 2.4.4 Extrapolation 70 2.4.5 Observations on Data Fitting 72 2.5 Numerical Methods 72 2.6 Numerical Stability and Accuracy 80 2.6.1 Numerical Stability 80 2.6.2 Numerical Accuracy 82 2.7 Timing Analysis 84 2.8 Simulation Packages 87 References 92 3 Aircraft Equations of Motion 93 3.1 Atmospheric Model 93 3.1.1 The Atmosphere 93 3.1.2 Wind 96 3.1.3 Turbulence 96 3.1.4 Wind Shear 98 3.2 Axes 99 3.2.1 Body Axes 99 3.2.2 Stability Axes 101 3.2.3 Local Frame 101 3.2.4 Earth-centred Earth-fixed Frame 104 3.2.5 Rotating Earth Frame 104 3.3 Quaternions 105 3.4 Aerodynamics 108 3.4.1 Performance and Handling 109 3.4.2 Coefficient of Lift 110 3.4.3 Coefficient of Drag 112 3.4.4 Coefficient of Side Force 113 3.4.5 Pitching Moment Coefficients 114 3.4.6 Rolling Moment Coefficients 115 3.4.7 Yawing Moment Coefficients 115 3.4.8 Mach Number 116 3.4.9 Observations 117 3.5 Equations of Motion 118 3.5.1 Forces 120 3.5.2 Moments 122 3.5.3 Long-Range Navigation 125 3.6 Propulsion 126 3.6.1 Piston Engines 127 3.6.2 Turbofans 134 3.7 Landing Gear 137 References 144 4 Flight Control Systems 147 4.1 Automatic Flight Control 147 4.2 Development of Flight Control Laws 148 4.2.1 The Case for Offline Development and Testing 148 4.2.2 SimPlot 150 4.2.3 Trimming 152 4.3 PID Control 154 4.4 Automatic Modes 157 4.4.1 Turn Coordinator 157 4.4.2 Yaw Damper 158 4.4.3 Pitch Rate Controller 160 4.4.4 Auto-throttle 163 4.4.5 Vertical Speed Hold 165 4.4.6 Altitude Hold 165 4.4.7 Heading Hold 166 4.4.8 Observations on Automatic Modes 170 4.5 Airbus Control Laws 170 4.5.1 Pitch Normal Law 171 4.5.2 Roll Rate Law 173 4.6 Tracking 174 4.7 Auto-land 177 4.8 Flight Director 180 4.9 Flight Management Systems 181 4.9.1 Flight Control Unit 182 4.9.2 Flight Management Systems Simulation 182 References 187 5 Navigation Systems 189 5.1 The Earth 189 5.1.1 Gravity 189 5.1.2 Magnetic Variation 190 5.2 Sensor Modelling 191 5.3 Navigation Principles 192 5.3.1 Position 192 5.3.2 Airspeed 194 5.3.3 Altitude 195 5.3.4 Heading 195 5.3.5 Distance and Bearing 197 5.4 Navigation Databases 199 5.5 Map Projections and Charts 203 5.6 Navigation Computations 207 5.7 Radio Navigation Aids 212 5.7.1 Automatic Direction Finding (ADF) 212 5.7.2 VHF Omni-directional Range 214 5.7.3 Distance Measuring Equipment 217 5.7.4 Instrument Landing System 218 5.8 Traffic Collision Avoidance Systems 221 5.9 Inertial Navigation Systems 223 5.10 Satellite Navigation 230 References 241 6 Aircraft Displays 243 6.1 OpenGL 243 6.1.1 The Development of OpenGL 243 6.1.2 Legacy OpenGL 244 6.1.3 OpenGL Version 4 245 6.2 glib – A 2D Graphics Library for Flight Simulation 253 6.2.1 GPU Software Interface 254 6.2.2 Dots, Vectors and Triangles 256 6.2.3 Textures 260 6.2.4 Fonts 264 6.2.5 Matrix Transformations 273 6.2.6 Summary of glib Functions 275 6.3 Graphics Libraries 275 6.3.1 GLFW 277 6.3.2 cglm 278 6.3.3 PngLib 278 6.3.4 FreeImage 279 6.3.5 FreeType 281 6.3.6 Compiling, Linking and Loading Shader Programs 281 6.3.7 Svg 281 6.4 Design Considerations 284 6.4.1 Absolute and Relative Rendering 284 6.4.2 Memory Organisation 286 6.5 EFIS Displays 287 6.5.1 Primary Flight Display 288 6.5.2 Navigation Flight Display 292 6.5.3 EICAS Display 294 6.6 Flight Instruments 296 6.7 Soft Panels 303 References 308 7 Image Generation Systems 309 7.1 IG Pipeline 309 7.2 Visual Databases 311 7.2.1 Constructing Visual Databases 311 7.2.2 Visual Database Standards 313 7.2.3 Visual Database Editing Tools 314 7.2.4 Representative Visual Databases 316 7.2.5 Visual Database Organisation 319 7.2.6 Binary-spaced Partition Trees 322 7.3 OpenSceneGraph 323 7.4 X-Plane 11 329 7.4.1 X-Plane 11 API 329 7.4.2 An X-Plane 11 Plug-in 330 7.4.3 OSG versus X-Plane 11 333 7.5 Head-up Displays 335 7.6 Digital Terrain Elevation Data 337 7.7 Visualisation 343 7.8 Observations 343 References 345 8 Sound Generation 347 8.1 Sound Waveforms 347 8.2 Sound Generation Methods 350 8.2.1 WAV Format 351 8.2.2 Fast Fourier Transform 352 8.2.3 FFTW 354 8.2.4 Filters 356 8.3 OpenAL 359 8.3.1 OpenAL Application Programming Interface 359 8.3.2 Loading Sound Files 360 8.3.3 Dynamic Sounds 363 8.4 Tones 364 8.4.1 Outer Marker 365 8.4.2 Middle Marker 367 8.4.3 Morse Code 367 8.4.4 Warnings 368 8.4.5 Background Sounds 369 8.4.6 Turbofan Sounds 369 8.4.7 Real-time Sound Generation 371 8.5 Recordings 372 8.5.1 Airspeed-related Sound 372 8.5.2 Turbofan Engines 373 8.6 Observations 373 References 374 9 The Instructor Station 375 9.1 Requirements 375 9.1.1 User Interfaces 375 9.1.2 Instructor Station Requirements 377 9.2 GUIs 380 9.2.1 User Inputs 380 9.2.2 Colour 381 9.2.3 Prototyping 381 9.2.4 User Actions 384 9.2.5 Software Considerations 384 9.3 Design of the User Interface 387 9.3.1 Classification of Operations 387 9.3.2 Design and Implementation of Menus 390 9.3.3 Widgets 395 9.3.4 Mouse Events 400 9.4 Real-time Operation 402 9.5 Charts and Maps 405 9.6 Flight Data Recording 408 9.6.1 Data Recording 409 9.6.2 Data Display 411 9.7 Scripting 411 9.7.1 A Simple Scripting Language 413 9.7.2 A Stack Machine 414 References 421 10 Validation 423 10.1 Software Verification 423 10.2 Static Validation 424 10.2.1 I/O Systems 425 10.2.2 Control Loading Systems 426 10.2.3 Weather Module 427 10.2.4 Navigation Systems 428 10.2.5 Display Modules 428 10.2.6 Visual Systems 430 10.2.7 The Instructor Station 432 10.2.8 Networking 433 10.3 Aircraft Performance 435 10.3.1 Taxiing 436 10.3.2 Take-off 436 10.3.3 Level Flight 436 10.3.4 Climbing Flight 440 10.3.5 Approach and Touchdown 440 10.3.6 Turning Flight 442 10.3.7 Sideslip 444 10.3.8 Observations 445 10.4 Dynamic Response 445 10.4.1 Longitudinal Dynamics 445 10.4.2 Lateral Dynamics 447 10.4.3 Engine Failure 449 10.4.4 Observations 450 10.5 Octave and MATLAB 451 10.5.1 Longitudinal Model 452 10.5.2 Lateral Model 456 10.6 Simulator Qualification 459 10.6.1 Aeroplane Flight Simulator Evaluation Handbook – Volume I 461 10.6.2 Aeroplane Flight Simulator Evaluation Handbook – Volume II 462 References 463 Appendix 465 A1 System-wide #include files 465 A2 Libraries 466 A3 Boeing 747-100 466 A4 Cessna- 172 468 A5 Supporting Files 469 A6 SimPlot 470 A7 Raspberry Pi 470 A8 Diagnostics 471 A9 MSYS2 471 A10 Miscellaneous 472 Index 473

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Book SynopsisVoltage-Enhanced Processing of Biomass and Biochar A detailed introduction to voltage-enhanced processing of carbonaceous materials While there are many well-established biomass processing techniques that are suitable for a variety of different situations, the utilization of voltage-driven techniques for the processing of biomass and biochar has been shown to have advantages for certain applications. Specifically, the field of thermal plasma gasificationwhere plasma provides the conversion energyis relied upon in certain commercial equipment that is already available on the market. Crucially, however, the field of non-thermal plasma pyrolysis and gasificationchemical reactions are intensified by the presence of the plasma dischargeis still a developing subject with a great scope for innovation in research and development. A timely book considering its potential applications in a greener market, Voltage-Enhanced Processing of Biomass and Biochar helpfully provides a detailed description of voltage-enhanced processing of carbonaceous materials. The book explains aspects of this processing method in thermal and non-thermal plasmas, as well as describing the effects of Joule heating as part of the temperature distribution and conversion rate. In many ways, this book presents a detailed description of different processes and plasma discharges currently available, with the provision of experimental and simulation results gathered over years of research and development. Importantly, it also offers many methods by which we can be environmentally friendly when working with biomass and biochar. Voltage-Enhanced Processing of Biomass and Biochar readers will also find: Simulation results of Joule heating of biomass, biochar, and pyrolytic graphite Descriptions of thermal plasma torches currently available in the marketAccounts of the experimental results of conversion utilizing steam plasmaComparison of results against provided numerical models that predict synthesis gas composition under the presence of thermal plasma discharge Voltage-Enhanced Processing of Biomass and Biochar is a useful reference for researchers and practitioners working on applications of plasma for the conversion of biomass and biochar, as well as graduate students studying mechanical, electrical, and chemical engineering.Table of ContentsContributors xi Preface xiii Acknowledgments xv Acronyms xvii Introduction xix 1 Carbonaceous Material Characterization 1 1.1 Material Characterization 2 1.1.1 Thermophysical properties 3 1.1.2 Moisture Content 3 1.1.3 Ultimate and Proximate analysis 4 1.1.4 Dielectric and electrical properties 4 1.2 Biomass 6 1.3 Biochar 7 1.3.1 Surface area, cation exchange capacity, and pH 9 1.4 Activated carbon 11 1.5 Pyrolytic graphite 11 Bibliography 12 2 Conventional Processing Methods 21 2.1 Biomass Processing 22 2.1.1 Biomass Pyrolysis 23 2.1.2 Biomass Gasification 26 2.2 Biochar production and post processing 28 2.2.1 Biochar Activation 34 Bibliography 44 3 Introduction to Plasmas 49 3.1 Thermal Plasmas 50 3.1.1 Mathematical model 53 3.2 Non-thermal Plasmas 56 3.2.1 DC non-thermal electrical discharges 59 3.2.2 Dielectric barrier discharge 64 3.2.3 Pulsed discharges 65 3.2.4 Gliding arc 66 3.2.5 Microwave-induced discharges 67 3.3 Impedance matching 68 3.4 Discharges in liquids 71 3.4.1 Contact glow discharge electrolysis 72 3.4.2 Plasma electrolysis with AC power 76 3.4.3 Gliding arc in glycerol for hydrogen generation 77 Bibliography 78 4 Voltage-Enhanced Processing of Biomass 85 4.1 Biomass gasification with thermal plasma 86 4.1.1 Plasma parameters 87 4.1.2 Syngas composition 88 4.1.3 Energy balance 92 4.1.4 Temperature decay in plasma/biomass discharge 95 4.2 Dielectric breakdown of biomass 97 4.2.1 Biomass-in-the-loop 98 4.3 Biomass gasification with non-thermal plasma 99 4.3.1 Tar breakdown 100 4.3.2 Circuit configuration 104 4.3.3 Scaling up of the technology 107 Bibliography 107 5 Voltage-Enhanced Processing of Biochar 113 5.1 DC Power Applied to Biochar 114 5.1.1 Joule heating of biochar 114 5.1.2 Joule heating of activated carbon 118 5.1.3 Recent Trends in Mathematical modelling 150 5.2 Physical activation of biochar with non-thermal plasma 159 5.2.1 Plasma-steam activation 160 Bibliography 162 6 Numerical simulations 167 6.1 Background 167 6.2 Modeling approaches 168 6.2.1 Kinetic approach 169 6.2.2 Fluid model approach 172 6.3 Examples of non-thermal plasma modeling 175 6.3.1 Cathode fall of a DC glow discharge 176 6.3.2 RF plasma discharge 179 6.3.3 Plasma chemistry 185 Bibliography 191 7 Control of plasma systems 195 7.1 Control of thermal plasma torches 196 7.1.1 Dynamics 198 7.1.2 Control 201 7.2 Control of nonthermal plasma discharges 207 7.2.1 Plasma diagnostics 208 7.2.2 AI-based control 209 Bibliography 214

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Book SynopsisEnergy Global energy demand has more than doubled since 1970. The use of energy is strongly related to almost every conceivable aspect of development: wealth, health, nutrition, water, infrastructure, education and even life expectancy itself are strongly and significantly related to the consumption of energy per capita. Many development indicators are strongly related to per-capita energy consumption. Fossil fuel is the most conventional source of energy but also increases greenhouse gas emissions. The economic development of many countries has come at the cost of the environment. However, it should not be presumed that a reconciliation of the two is not possible. The nexus concept is the interconnection between the resource energy, water, food, land, and climate. Such interconnections enable us to address trade-offs and seek synergies among them. Energy, water, food, land, and climate are essential resources of our natural environment and support our quality oTable of ContentsPreface or Foreword? 1. Energy crisis and climate change: global concerns and their solutionsSandeepa Singh 2. Advances in Alternative Sources of Energy - Opening new doors for Energy SustainabilityJyoti Tyagi 3. Recent advances in alternative sources of energyMaya Verma,a Ambikab and Pradeep Pratap Singhc* 4. Energy and Development in the 21st Century - A road towards a Sustainable Future: An Indian PerspectiveShikha Menani* and Kiran Yadav 5. Energy Development as a Driver of Economic Growth: Evidence from Developing Nations1Dr Md Rashid Farooqi2Dr Md Akhlaqur Rahman3Dr Md Faiz Ahmad4Supriya 6. Pathways of Energy Transition and its Impact on Economic Growth: A Case Study of BrazilPooja Sharma* 7. Renewable energy: sources, importance and prospects for sustainable futureSHACHI AGRAWAL1 AND RENU SONI*2 8. Clean Energy Sources for A Better and Sustainable Environment of Future GenerationsAPARNA NAUTIYAL1* AND AYYAGARI RAMLAL2 9. Sustainable energy policies of India to address air pollution and climate changePrem Lata Meena1*, Vinay2, Anirudh Sehrawat2 10. A Regime Complex and Technological Innovation in Energy System: A Brazilian ExperiencePooja Sharma* 11. Opportunities in the Living Lights: Special reference to Bioluminescent FungiPramod Kumar Mahish1*, Nagendra Kumar Chandrawanshi2*, Shriram Kunjam3 and S. K. Jadhav2 12. Production of Liquid Biofuels from Lignocellulosic BiomassManoj Kumar Singh1, Sumit Sahni2, Anita Narang3 13. Sustainable Solution for Future Energy Challenges through MicrobesSumit Sahni1*, Manoj Kumar Singh2, Anita Narang3 14. Fungal Microbial Fuel Cells, an opportunity for energy sources: Current Perspective and future challengesSudakshina Tiwari1, Deepali1, Anjali Kosre1, Pramod Kumar Mahish2, S.K. Jadhav1 and Nagendra Kumar Chandrawanshi1* 15. Current Perspective of Sustainable Utilization of Agro-Waste and Biotransformation of Energy in MushroomAnjali Kosre1*, Deepali1 , Pramod Kumar Mahish2 and Nagendra Kumar Chandrawanshi1 Index

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Book SynopsisApplied Smart Health Care Informatics Explores how intelligent systems offer new opportunities for optimizing the acquisition, storage, retrieval, and use of information in healthcare Applied Smart Health Care Informatics explores how health information technology and intelligent systems can be integrated and deployed to enhance healthcare management. Edited and authored by leading experts in the field, this timely volume introduces modern approaches for managing existing data in the healthcare sector by utilizing artificial intelligence (AI), meta-heuristic algorithms, deep learning, the Internet of Things (IoT), and other smart technologies. Detailed chapters review advances in areas including machine learning, computer vision, and soft computing techniques, and discuss various applications of healthcare management systems such as medical imaging, electronic medical records (EMR), and drug development assistance. Throughout the text, the authors propose new reTable of ContentsPreface xiii About the Editors xix List of Contributors xxv 1 An Overview of Applied Smart Health Care Informatics in the Context of Computational Intelligence 1Sourav De and Rik Das 1.1 Introduction 1 1.2 Big Data Analytics in Healthcare 2 1.3 AI in Healthcare 3 1.4 Cloud Computing in Healthcare 4 1.5 IoT in Healthcare 4 1.6 Conclusion 5 References 5 2 A Review on Deep Learning Method for Lung Cancer Stage Classification Using PET-CT 9Kaushik Pratim Das, Chandra J, and Dr Nachamai M 2.1 Introduction 9 2.1.1 Scope of the Research 10 2.1.2 TNM Staging 11 2.1.2.1 TNM Descriptors for Staging per IASLC Guidelines 11 2.1.2.2 PET-CT Scan in Lung Cancer Imaging 12 2.2 Related Works 12 2.2.1 Artificial Intelligence in Medical Imaging 14 2.2.2 Classification for Medical Imaging 14 2.2.2.1 Deep Learning 15 2.2.2.2 Image Classification Using Deep-learning Techniques 15 2.3 Methods 15 2.3.1 Transfer Learning 15 2.3.2 AlexNet 16 2.3.3 AlexNet Architecture 16 2.3.4 Experimental Setup 17 2.3.4.1 Image Processing 18 2.3.4.2 Data Augmentation 19 2.3.4.3 Training and Validation 19 2.4 Results and Discussion 19 2.4.1 Primary Tumor (T) 19 2.4.2 Metastasis (M) 21 2.4.3 Lymph Node (N) 21 2.4.4 Classification Accuracy of AlexNet 24 2.4.5 Comparative Analysis 25 2.4.6 Limitations 26 2.5 Conclusion 26 References 27 3 Formal Methods for the Security of Medical Devices 31Srinivas Pinisetty, Nathan Allen, Hammond Pearce, Mark Trew, Manoj Singh Gaur, and Partha Roop 3.1 Introduction 31 3.1.1 Pacemaker Security 33 3.1.2 Overview 34 3.2 Background: Cardiac Pacemakers 34 3.2.1 Pacemakers 35 3.2.1.1 Operation of a DDD Mode Pacemaker 36 3.2.2 The Cardiac System 37 3.2.2.1 Electrograms and Electrocardiograms 38 3.3 State of the Art, Formal Verification Techniques 39 3.3.1 Formal Verification Techniques 40 3.3.1.1 Static Verification Techniques 41 3.3.1.2 Dynamic Verification Techniques 42 3.3.2 Runtime Verification 43 3.3.2.1 A Brief Overview of Some Runtime Verification Frameworks 44 3.3.3 Correcting Execution of a System at Runtime (Runtime Enforcement) 45 3.3.3.1 Runtime Enforcement of Untimed Properties 46 3.3.3.2 Runtime Enforcement Approaches for Timed Properties 46 3.4 Formal Runtime-Based Approaches for Medical Device Security 47 3.4.1 Overview of the Approach 47 3.4.2 Mapping EGM Properties to ECG Properties 48 3.4.3 Security of Pacemakers Using Runtime Verification 49 3.4.3.1 Timed Words, Timed Languages, and Defining Timed Properties 50 3.4.3.2 Runtime Verification Monitor 51 3.4.3.3 Architecture of the Monitoring System 53 3.4.3.4 Implementation of the ECG Processing and RV Monitor Modules 53 3.4.3.5 Summary of Experiments and Results 54 3.4.4 Securing Pacemakers with Runtime Enforcement Hardware 54 3.4.4.1 Preliminaries: Words, Languages, and Defining Properties as DTA 55 3.4.4.2 Runtime Enforcement Monitor 56 3.4.4.3 Verification of the Enforcer Hardware 58 3.4.4.4 How Does the Enforcer Prevent Security Attacks? 58 3.4.4.5 Summary of Experiments and Results 59 3.5 Summary 59 References 60 4 Integrating Two Deep Learning Models to Identify Gene Signatures in Head and Neck Cancer from Multi-Omics Data 67Suparna Saha, Sumanta Ray, and Sanghamitra Bandyopadhyay 4.1 Introduction 67 4.2 Related Work 68 4.3 Materials and Methods 70 4.3.1 A Brief Introduction of the Capsule Network 70 4.3.2 An Introduction to Autoencoders 71 4.4 Results 72 4.4.1 Data Set Details 72 4.4.1.1 Gene Expression Data (Illumina Hiseq) 72 4.4.1.2 Human Methylation 450K 73 4.4.2 Architecture of Autoencoder Model 73 4.4.3 Architecture of the Proposed Capsule Network Model 74 4.4.4 Validation of Two Deep Learning Models 75 4.4.5 Gene Signatures from Primary Capsules 76 4.5 Discussion 77 Acknowledgments 78 References 79 5 A Review of Computational Learning and IoT Applications to High-Throughput Array-Based Sequencing and Medical Imaging Data in Drug Discovery and Other Health Care Systems 83Soham Choudhuri, Saurav Mallik, Bhaswar Ghosh, Tapas Si, Tapas Bhadra, Ujjwal Maulik, and Aimin Li 5.1 Introduction 83 5.2 Biological Terms 84 5.3 Single-Cell Sequencing (scRNA-seq) Data 86 5.3.1 Computational Methods for Interpreting scRNA-seq Data 86 5.3.1.1 Visualizing and Clustering Cells 86 5.3.1.2 Inference and Branching Analysis of Cellular Trajectory 86 5.3.1.3 Identifying Highly Variable Genes 86 5.3.1.4 Identifying Marker and Differentially Expressed Genes 90 5.4 Methods of Multi-Omic Data Integration 90 5.4.1 Unsupervised Data Integration Methods 91 5.4.1.1 Matrix Factorization Methods 91 5.4.1.2 Bayesian Methods 91 5.4.1.3 Network-Based Methods 94 5.4.1.4 Multi-Step Analysis and Multiple Kernel Learning 94 5.4.2 Supervised Data Integration 95 5.4.2.1 Network-Based Methods 95 5.4.2.2 Multiple Kernel Learning 95 5.4.2.3 Multi-Step Analysis 95 5.4.3 Semi-Supervised Data Integration 95 5.4.3.1 GeneticInterPred 97 5.5 AI Drug Discovery 97 5.5.1 AI Primary Drug Screening 97 5.5.1.1 Cell Sorting and Classification with Image Analysis 97 5.5.2 AI Secondary Drug Screening 99 5.5.2.1 Physical Properties Predictions 99 5.5.2.2 Predictions of Bio-Activity 99 5.5.2.3 Prediction of Toxicity 99 5.5.3 AI in Drug Design 99 5.5.3.1 Prediction of Target Protein 3D Structures 99 5.5.3.2 Predicting Drug-Protein Interactions 100 5.5.4 Planning Chemical Synthesis with AI 100 5.5.4.1 Retro-Synthesis Pathway Prediction 100 5.5.4.2 Reaction Yield Predictions and Reaction Mechanism Insights 100 5.6 Medical Imaging Data Analysis 100 5.6.1 Analysis: Radio-Mic Quantification 101 5.6.2 Analysis: Bio-Marker Identification 101 5.7 Applying IoT (Internet of Things) to Biomedical Research 102 5.7.1 IoT and IoMT Applications for Healthcare and Well-Being 102 5.7.1.1 Wireless Medical Devices 102 5.8 Conclusions 102 Acknowledgments 102 References 102 6 Association Rule Mining Based on Ethnic Groups and Classification using Super Learning 111Md Faisal Kabir and Simone A. Ludwig 6.1 Introduction 111 6.2 Background 112 6.3 Motivation and Contribution 114 6.4 Data Analysis 115 6.4.1 Data Description 115 6.4.2 Data Preprocessing 115 6.4.3 Further Preprocessing for Ethnic Group Rule Discovery with Multiple Consequences 115 6.4.3.1 Transaction-Like Database for Association Rule 115 6.4.4 Classification Data Set 116 6.5 Methodology 117 6.5.1 Association Rule Mining 117 6.5.2 Super Learning 118 6.5.2.1 Ensemble or Super Learner Set-Up 118 6.6 Experiments and Results 119 6.6.1 Rules Discovery 120 6.6.1.1 Rules of Breast Cancer Patients Based on Ethnic Groups 120 6.6.1.2 Interpreting Rules 120 6.6.2 Evaluation Criteria of Classification Model 121 6.6.2.1 Super Learner Results 124 6.6.3 Discussion 125 6.7 Conclusion and Future Work 126 References 127 7 Neuro-Rough Hybridization for Recognition of Virus Particles from TEM Images 131Debamita Kumar and Pradipta Maji 7.1 Introduction 131 7.2 Existing Approaches for Virus Particle Classification 132 7.3 Proposed Algorithm 134 7.3.1 Extraction of Local Textural Features 135 7.3.2 Selection of Class-Pair Relevant Features 135 7.3.3 Extraction of Discriminating Features 138 7.3.4 Classification 139 7.4 Experimental Results and Discussion 140 7.4.1 Experimental Setup 140 7.4.2 Methods Compared 140 7.4.3 Database Considered 141 7.4.4 Effectiveness of Proposed Approach 141 7.4.5 Comparative Performance Analysis 143 7.4.5.1 Comparison with Deep Architectures 144 7.4.5.2 Comparison with Existing Approaches 145 7.5 Conclusion 146 References 147 8 Neural Network Optimizers for Brain Tumor Image Detection 151T. Kalaiselvi and S.T. Padmapriya 8.1 Introduction 151 8.2 Related Works 152 8.3 Background 153 8.3.1 Types of Neural Networks 153 8.3.2 Tunable Elements of Neural Networks 154 8.3.2.1 Basic Parameters 154 8.3.2.2 Hyperparameters 154 8.3.2.3 Regularization Techniques 155 8.3.2.4 Neural Network Optimizers 156 8.4 Case Study - Brain Tumor Detection 157 8.4.1 Methodology 157 8.4.2 Data Sets and Metrics 157 8.4.3 Results and Discussion 159 8.5 Conclusion 162 References 162 9 Abnormal Slice Classification from MRI Volumes using the Bilateral Symmetry of Human Head Scans 165N. Kalaichelvi, T. Kalaiselvi, and K. Somasundaram 9.1 Introduction 165 9.1.1 MRIs of the Human Brain 165 9.1.2 Normal and Abnormal Slices 166 9.1.3 Background 167 9.1.3.1 Decision Tree Classifiers 167 9.1.3.2 K-Nearest Neighbours (KNN) Classifiers 168 9.1.3.3 Support Vector Machine (SVM) 168 9.1.3.4 Naive Bayes 169 9.1.3.5 Artificial Neural Network (ANN) 169 9.1.3.6 Back-Propagation Neural Network (BPN) 170 9.1.3.7 Random Forest Classifiers 170 9.2 Literature Review 171 9.3 Methodology 172 9.3.1 Preprocessing 173 9.3.2 Feature Extraction 174 9.3.3 Feature Selection 175 9.3.4 Classification 177 9.3.5 Cross-Validation 177 9.3.6 Training Validation and Testing 178 9.4 Materials and Metrics 179 9.4.1 Confusion Matrix 179 9.5 Results and Discussion 180 9.6 Conclusion 182 References 183 10 Conclusion 187Siddhartha Bhattacharyya References 188 Index 191

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Book SynopsisE-PAPER DISPLAYS An in-depth introduction to a promising technology, curated by one of its pioneering inventors Electronic paper (e-paper) has one of the most promising futures in technology. E-paper's potential is unlimited, as the displays require extremely low power and imitate the aesthetic of ink on the page. This allows e-paper devices to have a wider range of viewing angles than traditional LED products and are capable of being viewed in direct sunlightand without any additional power. As a result, e-paper displays create less eye strain, have a greater flexibility in their use, and have the potential to be used in place of paper for billboard advertising, educational applications, and transport signage, and more. In E-Paper Displays, editor Bo-Ru Yang and his team of experts present a detailed view into the important technologies involved in e-paper displays, with a particlular emphasis on how this technology's unique properties make possible a wTable of ContentsList of Contributors xi Series Editor's Foreword xiii Editor's Preface xv 1 The Rise, and Fall, and Rise of Electronic Paper 1Paul S. Drzaic, Bo-Ru Yang, and Anne Chiang 1.1 Introduction 1 1.2 Why Electronic Paper? 2 1.3 Brightness, Color, and Resolution 2 1.4 Reflectivity and Viewing Angle 4 1.5 Translating Print-on-Paper into Electronic Paper 5 1.6 The Allure of Electronic Paper vs. the Practicality of LCDs 10 1.7 The Evolution of Electrophoretic Display-Based Electronic Paper 11 1.8 Initial Wave of Electrophoretic Display Development 12 1.9 The Revival of EPDs 17 1.10 Developing a Commercial Display 18 1.11 Enhancing Brightness and Contrast 19 1.12 Microencapsulation Breakthrough 20 1.13 Image Retention 21 1.14 Active-Matrix Compatibility 23 1.15 Electronic Book Products, and E Ink Merger 25 1.16 Summary 26 2 Fundamental Mechanisms of Electrophoretic Displays 31Bo-Ru Yang and Kristiaan Neyts 2.1 General View of Electronic Ink Operation 31 2.2 Charging Mechanism with Inverse Micelle Dynamics 33 2.3 Drift and Diffusion of Charged Inverse Micelles 35 2.4 Motion of Charged Inverse Micelles Under External Field Driving 38 2.5 Stern Layer Formation 41 2.6 Charging Mechanism with Particles and Additives 44 2.7 Observations on a Single Particle 44 2.8 Rheological Effects During Driving 47 2.9 Bistability After Removing External Fields 48 2.10 Full Color E-Paper 49 2.11 Conclusion 50 3 Driving Waveforms and Image Processing for Electrophoretic Displays 53Zong Qin and Bo-Ru Yang 3.1 Driving Waveforms of EPDs 53 3.2 Image Processing 61 3.3 Advanced Driving Methods for Future E-Papers 69 4 Fast-Switching Mode with CLEARInk Structure 75Robert J. Fleming 4.1 Introduction 75 4.2 CLEARink Display Optics 78 4.3 CLEARink Reflective Color Displays 85 4.4 Electrophoretic Displays with CLEARink Structure 89 4.5 CLEARink Device Architecture 93 4.6 Manufacturing and Supply Chain 96 4.6.1 Status of Technology and Future Projections 96 Acknowledgments 97 5 Bistable Cholesteric Liquid Crystal Displays -- Review and Writing Tablets 99Clinton Braganza and Mauricio Echeverri 5.1 Introduction 99 5.2 Materials and Optical Properties 99 5.3 Image Creation Using Cholesteric Liquid Crystals 104 5.4 Applications 108 5.5 Writing Tablets 109 5.6 Conclusions 126 6 The Zenithal Bistable Display: A Grating Aligned Bistable Nematic Liquid Crystal Device 131Guy P. Bryan-Brown and J. Cliff Jones 6.1 Introduction 131 6.2 Operating Principles and Geometries 132 6.3 Grating Fabrication and Supply Chain 138 6.4 ZBD LCD Manufacturing Processes 141 6.5 Electrical Addressing 144 6.6 Optical Configurations 145 6.7 Novel Arrangements 149 6.8 Conclusions 150 7 Reflective LCD with Memory in Pixel Structure 153Yoko Fukunaga 7.1 Introduction 153 7.2 Memory in Pixel Technology and Its Super Low Power Operation 154 7.3 Sub-Pixel Pattern to Show Gray Scale 157 7.4 Reflective LCD Optical Design 158 7.5 How to Show a Natural Image 163 7.6 Design Characteristics of Current Market-Available Products and Their Super Low Power Operations 164 7.7 Summary of Power Consumption 167 7.8 Applications 168 7.9 Future Expectations 168 8 Optically Rewritable Liquid Crystal Display 171Wanlong Zhang, Abhishek Srivastava, Vladimir Chigrinov, and Hoi-Sing Kwok 8.1 Introduction 171 8.2 Photoalignment Technology 172 8.3 Flexible Optically Rewritable LCD 186 8.4 Dye-Doped Optically Rewritable LCD 188 8.5 Conclusion 190 9 Electrowetting Displays 197Doeke J. Oostra 9.1 Overviews 197 9.2 Introduction 197 9.3 The Promise of Electrowetting Displays 200 9.4 History of Electrowetting Display Development 204 9.5 Electrowetting Cells 205 9.6 Capabilities for Black and White 206 9.7 Capabilities for Video and Color 209 9.8 Driving 215 9.9 Architectures 216 9.10 Manufacturing 217 9.11 Reliability 220 9.12 Failure Mechanisms 220 9.13 In Conclusion: Electrowetting Displays Have Reached Maturity 221 10 Electrochromic Display 225Norihisa Kobayashi 10.1 Introduction 225 10.2 Structure of Electrochromic Display 226 10.3 EC Materials 228 10.4 Summary 239 11 Phase Change Material Displays 243Ben Broughton and Peiman Hosseini 11.1 Introduction 243 11.2 Phase Change Materials and Devices 243 11.3 Strong Interference in Ultra-Thin Absorbing Films 244 11.4 Potential for High Brightness, Low Power Color Reflective Displays 245 11.5 Solid-State Reflective Displays (SRD®) 248 11.6 SRD Prototype -- Progress and Performance 259 11.7 Other Approaches 263 11.8 Conclusions 265 12 Optical Measurements for E-Paper Displays 271Karlheinz Blankenbach 12.1 Introduction 271 12.2 Fundamentals of Reflection 272 12.3 Reflection Measurements Set-Ups 273 12.4 Display Image Quality Parameters 276 12.5 Temporal Parameters 281 12.6 Further Topics 283 12.7 Summary 283 Glossary incl. Abbreviations 284 References 284 Index 287

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Book SynopsisTable of ContentsForeword xv Preface xvii About the Companion Website xxi 1 Introduction 1 2 An Example: The Scalable Observation and Rescue System 5 3 Better Products – The Value of Systems Architecting 9 3.1 The Share of Systems Architecting in Making Better Products 9 3.2 Benefits that can be Achieved 10 3.2.1 Benefit for the Customer 10 3.2.2 Benefit for the Organization 12 3.3 Benefits that can be Communicated Inside the Organization 14 3.4 Beneficial Elements of Systems Architecting 15 3.5 Benefits of Model-Based Systems Architecting 16 4 Systems, Systems of Systems, and Cyber-Physical Systems 17 4.1 Definition of “System” 17 4.1.1 System Elements 19 4.1.2 System Context 20 4.1.3 System Characteristics 21 4.1.4 Purpose 22 4.1.5 System Evolution 23 4.2 Definition of “System of Systems” 23 4.3 Definition of “Cyber-Physical System” 26 4.4 Composition of a “Cyber-Physical System of Systems” 27 5 Definition of System Architecture 31 5.1 What Is Architecture? – Discussion of Some Existing Definitions 31 5.2 Relations Between Concepts of “System,” “Architecture,” and “Architecture Description” 33 5.3 Definition of “Architecture” 35 5.3.1 Interactions 36 5.3.2 Principles 37 5.3.3 Architecture Decisions 37 5.4 Functional and Physical Architecture 37 5.5 Taxonomy of Physical Architectures 39 5.5.1 Logical Architecture 40 5.5.2 Product Architecture 41 5.5.3 Base Architecture 41 5.6 Architecture Landscape for Systems 41 5.6.1 System Architecture 42 5.6.2 System Design 43 5.6.3 Discipline-Specific Architecture and Design 44 6 Model-Based Systems Architecting 45 7 Model Governance 51 7.1 Overview 51 7.2 Model Governance in Practice 52 8 Architecture Description 57 8.1 Architecture Descriptions for Stakeholders 58 8.2 Definition of “Architecture Description” 60 8.2.1 Architecture Viewpoints 62 8.2.2 Architecture Views 65 8.2.3 Architecture Decisions 67 8.2.4 Architecture Rationales 69 8.3 How to Get Architecture Descriptions? 69 8.3.1 Model-Based Vision 69 8.3.2 Forms and Templates 71 9 Architecture Patterns and Principles 75 9.1 The SYSMOD Zigzag Pattern 76 9.2 The Base Architecture 82 9.3 Cohesion and Coupling 85 9.4 Separation of Definition, Usage, and Run-Time 87 9.5 Separate Stable from Unstable Parts 89 9.6 The Ideal System 89 9.7 View and Model 90 9.8 Diagram Layout 92 9.9 System Model Structure 93 9.10 System Architecture Principles 95 9.11 Heuristics 95 9.11.1 Heuristics as a Tool for the System Architect 95 9.11.2 Simplify, Simplify, Simplify: Strength and Pitfall 97 10 Model-Based Requirements Engineering and Use Case Analysis 99 10.1 Requirement and Use Case Definitions 99 10.2 Model-Based Requirements and Use Case Analysis from the MBSA Viewpoint 102 10.2.1 Identify and Define Requirements 103 10.2.2 Specify the System Context 104 10.2.3 Identify Use Cases 105 10.2.4 Describe Use Case Flows 109 10.2.5 Model the Domain Knowledge 110 10.3 The SAMS Method 112 10.3.1 SAMS Method Definitions 113 10.3.2 SAMS Method 114 10.4 Use Cases 2.0 117 11 Perspectives, Viewpoints and Views in System Architecture 119 11.1 Introduction 119 11.2 The Functional Perspective 121 11.2.1 SysML Modeling of Functional Blocks 123 11.2.2 Architecture Views for the System Architect 124 11.2.3 Different Architecture Views for the Stakeholders of Different Functions 124 11.3 The Physical Perspective 125 11.3.1 Logical Architecture Example 126 11.3.2 Product Architecture Example 127 11.4 The Behavioral Perspective 130 11.5 The Layered Perspective 130 11.5.1 The Layered Approach 130 11.5.2 The Layered Perspective in Systems Architecting 132 11.5.3 Relation to the Domain Knowledge Model 134 11.5.4 Architecting the Layers 136 11.5.5 SysML Modeling of Layers 136 11.6 System Deployment Perspective 142 11.7 Other Perspectives 144 11.8 Relation to the System Context 146 11.8.1 Validity of the System Boundary 146 11.8.2 Using the System Context as a Part of the Stakeholder-Specific Views 146 11.8.3 Special System Context View for Verification 147 11.9 Mapping Different System Elements Across Different Levels 148 11.9.1 Functional-to-Physical Perspective Mapping 149 11.9.2 Mapping More Perspectives 153 11.9.3 Mapping Different Levels 153 11.10 Traceability 155 11.11 Perspectives and Architecture Views in Model-based Systems Architecting 155 11.11.1 Creating Different Architecture Views in a Model-Based Approach 155 11.11.2 Using SysML for Working with Different Perspectives and Architecture Views 157 11.11.3 The Importance of Architecture Viewpoints in Model-Based Systems Architecting 159 12 Typical Architecture Stakeholders 161 12.1 Overview 161 12.2 Requirements Engineering 162 12.3 Verification 163 12.4 Configuration Management 166 12.5 Engineering and Information Technology Disciplines 167 12.6 Project and Product Management 171 12.7 Risk Managers 174 12.8 Development Roadmap Planners 174 12.9 Production and Distribution 177 12.10 Suppliers 178 12.11 Marketing and Brand Management 178 12.12 Management 180 13 Roles 185 13.1 Roles 185 13.2 The System Architect Role 186 13.2.1 Objective 186 13.2.2 Responsibilities 186 13.2.3 Tasks 187 13.2.4 Competences 188 13.2.5 Required Skills of a System Architect 188 13.2.6 Required Skills for Model-Based Systems Architecting 190 13.3 System Architecture Teams 190 13.4 System Architecture Stakeholders 192 13.5 Recruiting System Architecture People 192 13.6 Talent Development for System Architects 194 14 Processes 199 14.1 Systems Architecting Processes 199 14.1.1 Overview 199 14.1.2 Example of Generic Process Steps 201 14.1.3 Example of Concrete Process Steps 202 14.1.4 Validation, Review, and Approval in a Model-Based Environment 203 14.2 Design Definition Process 207 14.3 Change and Configuration Management Processes 207 14.4 Other Processes Involving the System Architect 207 15 Tools for the Architect 209 16 Agile Approaches 213 16.1 The History of Iterative–Incremental Approaches 214 16.1.1 Project Mercury (NASA, 1958) 214 16.1.2 The New New Product Development Game (1986) 215 16.1.3 Boehm’s Spiral Model (1988) 216 16.1.4 Lean (1945 Onwards) 217 16.1.5 Dynamic Systems Development Method (DSDM, 1994) 219 16.1.6 Scrum (1995) 220 16.2 The Manifesto for Agile Software Development (2001) 221 16.3 Agile Principles in Systems Engineering 223 16.3.1 Facilitate Face-to-Face Communication 223 16.3.2 Create a State of Confidence 224 16.3.3 Build Transdisciplinary and Self-Organized Teams 225 16.3.4 Create a Learning Organization 225 16.3.5 Design, but No Big Design (Up-Front) 226 16.3.6 Reduce Dependencies 227 16.3.7 Foster a Positive Error Culture 228 16.4 Scaling Agile 228 16.5 System Architects in an Agile Environment 230 17 The FAS Method 233 17.1 Motivation 234 17.2 Functional Architectures for Systems 236 17.3 How the FAS Method Works 239 17.4 FAS Heuristics 242 17.5 FAS with SysML 244 17.5.1 Identifying Functional Groups 244 17.5.2 Modeling the Function Structure 246 17.5.3 Modeling the Functional Architecture 249 17.6 SysML Modeling Tool Support 250 17.6.1 Create Initial Functional Groups 251 17.6.2 Changing and Adding Functional Groups 254 17.6.3 Creating Functional Blocks and their Interfaces 254 17.7 Mapping of a Functional Architecture to a Physical Architecture 254 17.8 Experiences with the FAS Method 256 17.9 FAS Workshops 258 17.10 Quality Requirements and the Functional Architecture 259 17.11 Functional Architectures and the Zigzag Pattern 262 17.12 CPS-FAS for Cyber-physical Systems 263 18 Product Lines and Variants 269 18.1 Definitions Variant Modeling 270 18.2 Variant Modeling with SysML 271 18.3 Other Variant Modeling Techniques 276 19 Architecture Frameworks 279 19.1 Enterprise Architectures 280 19.2 Characteristics of System of Systems (SoS) 282 19.2.1 Emergence 283 19.3 An Overview of Architecture Frameworks 285 19.3.1 Zachman FrameworkTM 285 19.3.2 The TOGAF® Standard 286 19.3.3 Federal Enterprise Architecture Framework (FEAF) 288 19.3.4 Department of Defense Architecture Framework (DoDAF) 289 19.3.5 Ministry of Defense Architecture Framework (MODAF) 290 19.3.6 NATO Architecture Framework (NAF) 291 19.3.7 TRAK 292 19.3.8 European Space Agency Architectural Framework (ESA-AF) 293 19.3.9 OMG Unified Architecture Framework® (UAF®) 295 19.4 System Architecture Framework (SAF) 296 Together with Michael Leute 296 19.4.1 SAF and Enterprise Frameworks 296 19.4.2 SAF Ontology 298 19.5 What to Do When We Come in Touch With Architecture Frameworks 298 20 Cross-cutting Concerns 301 20.1 The Game-Winning Nonfunctional Aspects 301 20.2 Human System Interaction and Human Factors Engineering 303 20.3 Risk Management 304 20.4 Trade Studies 305 20.5 Budgets 306 21 Architecture Assessment 307 22 Making It Work in the Organization 313 22.1 Overview 313 22.2 Organizational Structure for Systems Architecting 314 22.3 Recipes from the Authors’ Experience 318 22.3.1 Be Humble 319 22.3.2 Appraise the Stakeholders 319 22.3.3 Care About Organizational Interfaces 319 22.3.4 Show that it Was Always There 321 22.3.5 Lead by Good Example 321 22.3.6 Collect Success Stories and Share them When Appropriate 322 22.3.7 Acknowledge that Infections Beat Dictated Rollout 323 22.3.8 Assign the System Architect Role to Yourself 324 22.3.9 Be a Leader 324 23 Soft Skills 327 23.1 It’s All About Communication 328 23.1.1 Losses in Communication 329 23.1.2 The Anatomy of a Message 330 23.1.3 Factors Influencing Communication 333 23.1.3.1 The Language 333 23.1.3.2 The Media Used 333 23.1.3.3 Spatial Distance 333 23.1.3.4 Various Connotations of Words 335 23.1.4 The Usage of Communication Aids and Tools 335 23.2 Personality Types 338 23.2.1 Psychological Types by C. G. Jung 338 23.2.2 The 4MAT System by Bernice McCarthy 340 23.3 Team Dynamics 341 23.4 Diversity and Psychological Safety 342 23.4.1 Project Aristotle (Google) 342 23.4.2 Elements of Psychological Safety 343 23.5 Intercultural Collaboration Skills 344 24 Outlook: The World After Artificial Intelligence 347 Appendix A OMG Systems Modeling Language 349 A.1 Architecture of the Language 350 A.2 Diagram and Model 352 A.3 Structure Diagrams 353 A.3.1 Block Definition Diagram 354 A.3.2 Internal Block Diagram 357 A.3.3 Parametric Diagram 361 A.3.4 Package Diagram 362 A.4 Behavior Diagrams 363 A.4.1 Use Case Diagram 364 A.4.2 Activity Diagram 366 A.4.3 State Machine Diagram 369 A.4.4 Sequence Diagram 371 A.5 Requirements Diagram 372 A.6 Extension of SysML with Profiles 374 A.7 Next-Generation Modeling Language SysML v2 376 Appendix B The V-Model 381 B.1 A Brief History of the V-Model or the Systems Engineering Vee 381 B.2 A Handy Illustration but No Comprehensive Process Description 383 B.3 Critical Considerations 385 B.3.1 The V-Model as Process Description 386 B.3.2 The V-Model Does Not Impose a Waterfall Process 386 B.3.3 The V-Model Accommodates Iterations 387 B.3.4 The V-Model Permits Incremental Development 387 B.3.5 The V-Model and Concurrent Engineering 388 B.3.6 The V-Model Accommodates Change 388 B.3.7 The V-Model Permits Early Verification Planning 388 B.3.8 The V-Model Shows Where to Prevent Dissatisfaction 388 B.4 Reading Instruction for a Modern Systems Engineering Vee 389 B.4.1 The Vertical Dimension 389 B.4.2 The Horizontal Dimension 389 B.4.3 The Left Side 389 B.4.4 The Right Side 390 B.4.5 The Levels 390 B.4.6 Life Cycle Processes 390 B.4.7 The Third Dimension 390 Appendix C Glossary 391 C.1 Heritage of the Term “Glossary” 391 C.2 Terms with Specific Meaning 393 References 399 Index 417

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Book SynopsisExplore the theoretical foundations and real-world power system applications of convex programming In Mathematical Programming for Power System Operation with Applications in Python, Professor Alejandro Garces delivers a comprehensive overview of power system operations models with a focus on convex optimization models and their implementation in Python. Divided into two parts, the book begins with a theoretical analysis of convex optimization models before moving on to related applications in power systems operations. The author eschews concepts of topology and functional analysis found in more mathematically oriented books in favor of a more natural approach. Using this perspective, he presents recent applications of convex optimization in power system operations problems. Mathematical Programming for Power System Operation with Applications in Python uses Python and CVXPY as tools to solve power system optimization problems and includes mTable of ContentsAcknowledgment ix Introduction xi 1 Power systems operation 1 1.1 Mathematical programming for power systems operation 1 1.2 Continuous models 3 1.2.1 Economic and environmental dispatch 3 1.2.2 Hydrothermal dispatch 3 1.2.3 Effect of the grid constraints 5 1.2.4 Optimal power flow 5 1.2.5 Hosting capacity 7 1.2.6 Demand-side management 7 1.2.7 Energy storage management 9 1.2.8 State estimation and grid identification 9 1.3 Binary problems in power systems operation 11 1.3.1 Unit commitment 12 1.3.2 Optimal placement of distributed generation and capacitors 12 1.3.3 Primary feeder reconfiguration and topology identification 13 1.3.4 Phase balancing 13 1.4 Real-time implementation 14 1.5 Using Python 15 Part I Mathematical programming 17 2 A brief introduction to mathematical optimization 19 2.1 About sets and functions 19 2.2 Norms 22 2.3 Global and local optimum 24 2.4 Maximum and minimum values of continuous functions 25 2.5 The gradient method 26 2.6 Lagrange multipliers 32 2.7 The Newton’s method 33 2.8 Further readings 35 2.9 Exercises 35 3 Convex optimization 39 3.1 Convex sets 39 3.2 Convex functions 45 3.3 Convex optimization problems 47 3.4 Global optimum and uniqueness of the solution 50 3.5 Duality 52 3.6 Further readings 56 3.7 Exercises 58 4 Convex Programming in Python 61 4.1 Python for convex optimization 61 4.2 Linear programming 62 4.3 Quadratic forms 67 4.4 Semidefinite matrices 69 4.5 Solving quadratic programming problems 71 4.6 Complex variables 74 4.7 What is inside the box? 75 4.8 Mixed-integer programming problems 76 4.9 Transforming MINLP into MILP 79 4.10 Further readings 80 4.11 Exercises 81 5 Conic optimization 85 5.1 Convex cones 85 5.2 Second-order cone optimization 85 5.2.1 Duality in SOC problems 90 5.3 Semidefinite programming 92 5.3.1 Trace, determinant, and the Shur complement 92 5.3.2 Cone of semidefinite matrices 95 5.3.3 Duality in SDP 97 5.4 Semidefinite approximations 98 5.5 Polynomial optimization 102 5.6 Further readings 105 5.7 Exercises 106 6 Robust optimization 109 6.1 Stochastic vs robust optimization 109 6.1.1 Stochastic approach 110 6.1.2 Robust approach 110 6.2 Polyhedral uncertainty 111 6.3 Linear problems with norm uncertainty 113 6.4 Defining the uncertainty set 115 6.5 Further readings 121 6.6 Exercises 121 Part II Power systems operation 125 7 Economic dispatch of thermal units 127 7.1 Economic dispatch 127 7.2 Environmental dispatch 133 7.3 Effect of the grid 136 7.4 Loss equation 140 7.5 Further readings 143 7.6 Exercises 143 8 Unit commitment 145 8.1 Problem definition 145 8.2 Basic unit commitment model 146 8.3 Additional constraints 150 8.4 Effect of the grid 151 8.5 Further readings 153 8.6 Exercises 153 9 Hydrothermal scheduling 155 9.1 Short-term hydrothermal coordination 155 9.2 Basic hydrothermal coordination 156 9.3 Non-linear models 159 9.4 Hydraulic chains 162 9.5 Pumped hydroelectric storage 165 9.6 Further readings 168 9.7 Exercises 169 10 Optimal power flow 171 10.1 OPF in power distribution grids 171 10.1.1 A brief review of power flow analysis 173 10.2 Complex linearization 177 10.2.1 Sequential linearization 181 10.2.2 Exponential models of the load 182 10.3 Second-order cone approximation 184 10.4 Semidefinite approximation 188 10.5 Further readings 190 10.6 Exercises 190 11 Active distribution networks 195 11.1 Modern distribution networks 195 11.2 Primary feeder reconfiguration 196 11.3 Optimal placement of capacitors 200 11.4 Optimal placement of distributed generation 203 11.5 Hosting capacity of solar energy 205 11.6 Harmonics and reactive power compensation 208 11.7 Further readings 212 11.8 Exercises 212 12 State estimation and grid identification 215 12.1 Measurement units 215 12.2 State estimation 216 12.3 Topology identification 221 12.4 Ybus estimation 224 12.5 Load model estimation 228 12.6 Further readings 231 12.7 Exercises 232 13 Demand-side management 235 13.1 Shifting loads 235 13.2 Phase balancing 240 13.3 Energy storage management 246 13.4 Further readings 249 13.5 Exercises 249 A The nodal admittance matrix 253 B Complex linearization 257 C Some Python examples 263 C.1 Basic Python 263 C.2 NumPy 266 C.3 MatplotLib 268 C.4 Pandas 268 Bibliography 271 Index 281

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Book SynopsisPOWER QUALITY MEASUREMENT AND ANALYSIS USING HIGHER-ORDER STATISTICS Help protect your network with this important reference work on cyber security Power quality (PQ) in electrotechnical systems refers to a set of characteristics related to the movement of energy and the delivery of voltage to consumers in the highest standard. As electricity networks change and adapt to new technologies and concepts of energy within a future Smart Grid, it has become clear that standardized methods by which stability and accuracy of electrical service along a network are currently measured are no longer enough to solve inherent issues in service and ensure established requirements are met. Power Quality Measurement and Analysis using Higher-Order Statistics reflects the latest information related to PQ (Power Quality) analysis solutions, particularly that related to the implementation of new quality indices in the domain of higher-order statistics (HOS). Table of ContentsPOWER QUALITY MEASUREMENT AND ANALYSIS USING HIGHER-ORDER STATISTICS 1 Understanding HOS contribution on the Smart(er) Grid 1 POWER QUALITY MEASUREMENT AND ANALYSIS USING HIGHER-ORDER STATISTICS 3 Understanding HOS contribution on the Smart(er) Grid 3 LOGO 3 Contents 11 Contributors 14 Foreword 17 Acronyms 21 Acknowledgments 24 Chapter 1. Power quality monitoring and higher-order statistics. State of the Art 26 1.1 Introduction 27 1.2 Background on power quality 27 1.3 PQ Practices at the Industrial Level 33 1.4 A new PQ monitoring Framework 33 1.4.1 The Smart Grid 35 1.4.2 The Smart Grid and the Power Quality 35 1.4.3 Performance Indicators 36 1.4.4 Existing measurement and instrumentation solutions 37 1.4.5 New approach in Measurement and Instrumentation solutions in the SG 38 1.4.6 Economic Issues for PQ 39 1.4.7 Power Quality and Big Data 39 1.4.8 Signal Processing for PQ 40 1.4.9 HOS for PQ analysis 43 Chapter 2. HOS Measurements in the time domain 47 HOS Measurements in the time domain 48 2.1 Introduction 48 2.2 Background on power quality 48 2.3 Traditional theories of electrical time domain 49 2.4 HOS contribution in the PQ field 51 2.4.1 HOS indices definitions 51 2.4.2 HOS performance in signal processing 52 2.4.3 HOS versus electrical time domain indices 53 2.5 Regulations 55 2.6 The Sliding Window Method for HOS feature extraction 56 2.6.1 Amplitude Changes 57 2.6.2 Phase Angle Jumps 58 2.6.3 Fundamental Frequency 60 2.6.4 Waveform shape deviation 62 2.7 PQ index based on HOS 64 2.8 Representations used by the time-domain 67 Chapter 3. Event Detection Strategies based on HOS feature extraction 72 3.1 Introduction 73 3.2 Detection methods based in HOS 73 3.3 Experiment description 73 3.3.1 Computational Strategy 73 3.3.2 HOS for Sag Detection under Symmetrical and Sinusoidal Conditions 74 3.3.2 HOS for Sag Detection including Phase-Angle Jump based on Non-Symmetrical & Non-Sinusoidal conditions 75 3.3.2.1 HOS range for Transient detection including Phase-Angle Jump based on Non-Symmetrical & Non- Sinusoidal conditions 87 3.3 Flow Diagram of HOS monitoring strategy focus on detecting short duration events: detecting amplitude, symmetry, and sinusoidal states 87 3.4 Continuous event’s characterization fundamental frequency 90 3.4.1 Frequency deviation regions in the HOS planes 92 3.4.2 Frequency deviation regions in the HOS planes 94 3.5 Detection of Harmonics with HOS in the time domain 95 3.6 Conclusions 97 Chapter 4. Measurements in the Frequency domain 100 4.1 Introduction 101 4.2 Frequency-domain 101 4.3 HOS in Frequency-domain 102 4.3.1 Spectral Kurtosis in Power Quality 103 4.4 Harmonic distortion 103 4.4.1 Types of Harmonic distortion 104 4.4.2 Sources of Harmonic distortion 105 4.4.3 Impact of harmonic distortion over power system 105 4.5 Traditional theories of electrical frequency-domain indicators 105 4.5.1 Harmonic measure 105 4.5.2 DFT derived measures 107 4.6 HOS contribution in PQ in the frequency-domain 107 4.6.1 Spectral Kurtosis 108 4.6.2 Spectral Kurtosis basic usage 115 4.6.3 Spectral Kurtosis and Power quality 118 Chapter 5 Measurement Campaigns and Virtual Instruments 124 5.1 Introduction 125 5.2 Virtual Instrument 126 5.2.1 Measurement Analysis Framework 126 5.2.2 Experimental Strategy for PQM through a Virtual Instrument 128 5.2.3 Configuration of the Virtual Instrument 128 5.2.4 Results 131 5.3 PQ continuous monitoring based on HOS for consumers characterization, public networks and household 132 5.3.1 Measurement and Analysis Framework 132 5.3.2 Evolution of the individual statistics histograms during several weeks 133 References 149 Annex A. Voltage Waveform 1 Theoretical power system waveform 1 Annex. B. Time-domain cumulants 1 Annex. C. HOS Range for Sag Detection, one cycle 3 Annex. D. HOS Range for Sag Detection, 10 cycles 7

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