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Deterministic and Stochastic Modeling in Computational Electromagnetics Help protect your network with this important reference work on cyber security Deterministic computational models are those for which all inputs are precisely known, whereas stochastic modeling reflects uncertainty or randomness in one or more of the data inputs. Many problems in computational engineering therefore require both deterministic and stochastic modeling to be used in parallel, allowing for different degrees of confidence and incorporating datasets of different kinds. In particular, non-intrusive stochastic…mehr
Deterministic and Stochastic Modeling in Computational Electromagnetics Help protect your network with this important reference work on cyber security Deterministic computational models are those for which all inputs are precisely known, whereas stochastic modeling reflects uncertainty or randomness in one or more of the data inputs. Many problems in computational engineering therefore require both deterministic and stochastic modeling to be used in parallel, allowing for different degrees of confidence and incorporating datasets of different kinds. In particular, non-intrusive stochastic methods can be easily combined with widely used deterministic approaches, enabling this more robust form of data analysis to be applied to a range of computational challenges. Deterministic and Stochastic Modeling in Computational Electromagnetics provides a rare treatment of parallel deterministic-stochastic computational modeling and its beneficial applications. Unlike other works of its kind, which generally treat deterministic and stochastic modeling in isolation from one another, it aims to demonstrate the usefulness of a combined approach and present particular use-cases in which such an approach is clearly required. It offers a non-intrusive stochastic approach which can be incorporated with minimal effort into virtually all existing computational models. Readers will also find: * A range of specific examples demonstrating the efficiency of deterministic-stochastic modeling * Computational examples of successful applications including ground penetrating radars (GPR), radiation from 5G systems, transcranial magnetic and electric stimulation (TMS and TES), and more * Introduction to fundamental principles in field theory to ground the discussion of computational modeling Deterministic and Stochastic Modeling in Computational Electromagnetics is a valuable reference for researchers, including graduate and undergraduate students, in computational electromagnetics, as well as to multidisciplinary researchers, engineers, physicists, and mathematicians.
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Autorenporträt
DRAGAN POLJAK, PH.D., is Professor in the Department of Electronics and Computing Technology, University of Split, Croatia. He is a Senior Member of the IEEE and author of three books and more than 150 articles on subjects related to computational electromagnetics.
ANNA sUsNJARA, PH.D., is a Postdoctoral Researcher in the Department of Electronics and Computing Technology, University of Split, Croatia. She is a member of the IEEE and has authored or co-authored more than 40 journal and conference papers on subjects related to computational electromagnetics.
Inhaltsangabe
About the Authors xv
Preface xvii
Part I Some Fundamental Principles in Field Theory 1
1 Least Action Principle in Electromagnetics 3
1.1 Hamilton Principle 4
1.2 Newton's Equation of Motion from Lagrangian 7
1.3 Noether's Theorem and Conservation Laws 8
1.4 Equation of Continuity from Lagrangian 12
1.5 Lorentz Force from Gauge Invariance 16
2 Fundamental Equations of Engineering Electromagnetics 21
2.1 Derivation of Two-Canonical Maxwell's Equation 21
2.2 Derivation of Two-Dynamical Maxwell's Equation 22
2.3 Integral Form of Maxwell's Equations, Continuity Equations, and Lorentz Force 25
2.4 Phasor Form of Maxwell's Equations 27
2.5 Continuity (Interface) Conditions 29
2.6 Poynting Theorem 30
2.7 Electromagnetic Wave Equations 32
2.8 Plane Wave Propagation 35
2.9 Hertz Dipole as a Simple Radiation Source 37
2.10 Wire Antennas of Finite Length 41
3 Variational Methods in Electromagnetics 47
3.1 Analytical Methods 47
3.2 Variational Basis for Numerical Methods 51
4 Outline of Numerical Methods 57
4.1 Variational Basis for Numerical Methods 60
4.2 The Finite Element Method 61
4.3 The Boundary Element Method 77
Part II Deterministic Modeling 87
5 Wire Configurations - Frequency Domain Analysis 89
5.1 Single Wire in the Presence of a Lossy Half-Space 89
5.2 Horizontal Dipole Above a Multi-layered Lossy Half-Space 100
5.3 Wire Array Above a Multilayer 125
5.4 Wires of Arbitrary Shape Radiating Over a Layered Medium 150
5.5 Complex Power of Arbitrarily Shaped Thin Wire Radiating Above a Lossy Half-Space 186
6 Wire Configurations - Time Domain Analysis 207
6.1 Single Wire Above a Lossy Ground 208
6.2 Numerical Solution of Hallen Equation via the Galerkin-Bubnov Indirect Boundary Element Method (GB-IBEM) 222
6.3 Application to Ground-Penetrating Radar 228
6.4 Simplified Calculation of Specific Absorption in Human Tissue 246
6.5 Time Domain Energy Measures 255
6.6 Time Domain Analysis of Multiple Straight Wires above a Half-Space by Means of Various Time Domain Measures 260
7 Bioelectromagnetics - Exposure of Humans in GHz Frequency Range 285
7.1 Assessment of Sab in a Planar Single Layer Tissue 286
7.2 Assessment of Transmitted Power Density in a Single Layer Tissue 295
7.3 Assessment of Sab in a Multilayer Tissue Model 318
7.4 Assessment of Transmitted Power Density in the Planar Multilayer Tissue Model 325
8 Multiphysics Phenomena 339
8.1 Electromagnetic-Thermal Modeling of Human Exposure to HF Radiation 340
8.2 Magnetohydrodynamics (MHD) Models for Plasma Confinement 348
