دانلود کتاب Advanced Electromagnetic Models for Materials Characterization and Nondestructive Evaluation (Scientific Computation)

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Preface
Acknowledgments
Contents
Part I Voxel-Based Inversion Algorithms
1 A Bilinear Conjugate-Gradient Inversion Algorithm
1.1 Optimization via Nonlinear Least-Squares
1.2 A Bilinear Conjugate-Gradient Inversion Algorithm Using Volume-Integrals
1.3 The Algorithm
1.4 Example: Raster Scan at Three Frequencies
2 Voxel-Based Inversion Via Set-Theoretic Estimation
2.1 The Electromagnetic Model Equations
2.2 Set-Theoretic Estimation
2.3 Statistical Analysis of the Feasible Set
2.4 A Layer-Stripping Algorithm
2.5 Some Examples of the Inversion Algorithm
2.6 Application to Aircraft Structures
Part II Materials Characterization
3 Modeling Composite Structures
3.1 Background
3.2 Constitutive Relations for Advanced Composites
3.3 Example Calculations Using VIC-3D®
3.4 A Coupled-Circuit Model of Maxwell\'s Equations
3.5 Eddy-Current Detection of Prepreg FAWT
3.6 An Anisotropic Inverse Problem for Measuring FAWT
3.6.1 Return to an Analysis of Fig.3.10
3.7 Further Results for Permittivity
3.8 Comments and Conclusions
3.9 Eigenmodes of Anisotropic Media
3.10 Computing a Green\'s Function for a Layered Workpiece
3.11 An Example of the Multilayer Model
3.12 A Bulk Model
4 Application of the Set-Theoretic Algorithm to CFRP\'s
4.1 Background
4.2 Statistical Analysis of the Feasible Set
4.3 An Anisotropic Inverse Problem for Measuring FAWT
4.3.1 First Set-Theoretic Result
4.3.2 Second Set-Theoretic Result
4.3.3 Comment
4.4 Modeling Microstructure Quantification Problems
4.4.1 Delaminations
4.4.2 Transverse Ply with Microcrack
4.5 Layer-Stripping for Anisotropic Flaws
4.6 Advanced Features for Set-Theoretic Microstructure Quantification
4.6.1 A Heuristic Iterative Scheme to Determine a Zero-Cutoff Threshold
4.7 Progress in Modeling Microstructure Quantification
4.8 Handling Rotations of Anisotropic Media
5 An Electromagnetic Model for Anisotropic Media: Green\'s Dyad for Plane-Layered Media
5.1 Theory
5.2 Applications
5.3 Some Inverse Problems with Random Anisotropies
5.4 Detectability of Flaws in Anisotropic Media: Application to Ti64
6 Stochastic Inverse Problems: Models and Metrics
6.1 Introducing the Problem
6.2 NLSE: Nonlinear Least-Squares Parameter Estimation
6.3 Confidence Levels: Stochastic Global Optimization
6.4 Summary
7 Integration of Functionals, PCM and Stochastic IntegralEquations
7.1 Theoretical Background
7.2 Probability Densities and Numerical Procedures
7.3 Second-Order Random Functions
7.4 A One-Dimensional Random Surface
7.5 gPC and PCM
7.6 HDMR and ANOVA
7.7 Determining the ANOVA Anchor Point
7.8 Interpolation Theory Using Splines Based Upon Higher-Order Convolutions of the Unit Pulse
7.9 Two-Dimensional Functions
7.10 Probability of Detection and the Chebychev Inequality
7.11 Consistency of Calculations
Appendix 1: The Numerical Model
Appendix 2: The Fortran RANDOM_NUMBER Subroutine
8 A Model for Microstructure Characterization
8.1 Introduction
8.2 Stochastic Euler Space
8.3 The Karhunen-Loève Model
8.4 Anisotropic Covariances
8.5 The Geometric Autocorrelation Function
8.6 Results for the Anisotropic Double-Exponential Model
9 High-Dimension Model Representation via Sparse GridTechniques
9.1 Introduction
9.2 Mathematical Structure of the Problem
9.3 Clenshaw-Curtis Grids
9.4 The TASMANIAN Sparse Grids Module
9.5 First TASMANIAN Results
9.6 Results for 4D-Level 8
9.7 The Geometry of the 4D-Level 8 Chebyshev Sparse Grid
9.8 Searching the Sparse Grid for a Starting Point for Inversion
9.9 A Five-Dimensional Inverse Problem
9.10 Noisy Data and Uncertainty Propagation
10 Characterization of Atherosclerotic Lesions by Inversion of Eddy-Current Impedance Data
10.1 The Model
10.2 Sample Impedance Calculations
10.3 The Eight-Layer Inversion Algorithm
10.4 Lesion 2
10.5 Noninvasive Detection and Characterization of Atherosclerotic Lesions
10.6 Electromagnetic Modeling of Biological Tissue
10.6.1 The Lesions Revisited
10.7 Determining Coil Parameters
10.7.1 Application to the 21.6mm Single-Turn Loop
10.8 Measuring the Frequency Response of Saline
10.9 Determining the Constitutive Parameters of Saline
10.10 Comments and Discussion
10.10.1 Summary
Appendix: The Levenberg–Marquardt Parameter in Least-Squares Problems
Part III Quantum Effects
11 Spintronics
11.1 Introduction
11.2 Paramagnetic Spin Dynamics and the Spin Hamiltonian
11.2.1 Application to Fe3+:TiO2
11.2.2 Ho++:CaF2
11.3 Superparamagnetic Iron Oxide
11.4 Fe3+ and Hund\'s Rules
11.5 Crystalline Anisotropy and TiO2
11.5.1 Application to a `Magnetic Lesion\'
11.6 Static Interaction Energy of Two Magnetic Moments
12 Carbon-Nanotube Reinforced Polymers
12.1 Introduction
12.2 Modeling Piezoresistive Effects in Carbon Nanotubes
12.2.1 The Structure of CNTs
12.3 Electromagnetic Features of CNTs
12.4 Quantum-Mechanical Model for Conductivity
12.5 What Are We Looking At?
12.6 An Example of a Bianisotropic System
12.7 Modeling Paramagnetic Effects in Carbon Nanotubes
12.7.1 Paramagnetic Spin Dynamics and the Spin Hamiltonian
12.7.2 Application to Fe3+:TiO2
12.7.3 Superparamagnetic Iron Oxide
Two Spins
Three Spins
12.8 Inverse Problems
12.8.1 Inverse Problem No. 1
12.8.2 A Thermally-Activated Transport Model
12.8.3 A Simple Inverse Problem
12.8.4 Voxel-Based Inversion: A Surface-Breaking Checkerboard at 50MHz
12.8.5 Voxel-Based Inversion: A Buried Checkerboard
12.8.6 Spatial Imaging Using Embedded CNT Sensors
12.8.7 Inverse Problem No. 2: Characterizing the CNT via ESR
12.8.8 What Does VIC-3D® Need?
References
Index