Advanced electromagnetic models for materials characterization and nondestructive evaluation / / Harold A. Sabbagh [and three others]

• Record Nr.: UNISA996466747703316
• Autore: Sabbagh Harold A.
• Pubbl/distr/stampa: Cham, Switzerland : , : Springer, , [2021]; ©2021
• ISBN: 3-030-67956-X
• Descrizione fisica: 1 online resource (353 pages) : illustrations
• Collana: Scientific Computation
• Disciplina: 620.1127
• Soggetti: Nondestructive testing; Electromagnetic testing
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Intro -- 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.