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Virtual Design and Validation

E-BookPDF1 - PDF WatermarkE-Book
347 Seiten
Englisch
Springer International Publishingerschienen am03.03.20201st ed. 2020
This book provides an overview of the experimental characterization of materials and their numerical modeling, as well as the development of new computational methods for virtual design. Its 17 contributions are divided into four main sections: experiments and virtual design, composites, fractures and fatigue, and uncertainty quantification. The first section explores new experimental methods that can be used to more accurately characterize material behavior. Furthermore, it presents a combined experimental and numerical approach to optimizing the properties of a structure, as well as new developments in the field of computational methods for virtual design. In turn, the second section is dedicated to experimental and numerical investigations of composites, with a special focus on the modeling of failure modes and the optimization of these materials. Since fatigue also includes wear due to frictional contact and aging of elastomers, new numerical schemes in the field of crack modeling and fatigue prediction are also discussed. The input parameters of a classical numerical simulation represent mean values of actual observations, though certain deviations arise: to illustrate the uncertainties of parameters used in calculations, the book's final section presents new and efficient approaches to uncertainty quantification.mehr
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KlappentextThis book provides an overview of the experimental characterization of materials and their numerical modeling, as well as the development of new computational methods for virtual design. Its 17 contributions are divided into four main sections: experiments and virtual design, composites, fractures and fatigue, and uncertainty quantification. The first section explores new experimental methods that can be used to more accurately characterize material behavior. Furthermore, it presents a combined experimental and numerical approach to optimizing the properties of a structure, as well as new developments in the field of computational methods for virtual design. In turn, the second section is dedicated to experimental and numerical investigations of composites, with a special focus on the modeling of failure modes and the optimization of these materials. Since fatigue also includes wear due to frictional contact and aging of elastomers, new numerical schemes in the field of crack modeling and fatigue prediction are also discussed. The input parameters of a classical numerical simulation represent mean values of actual observations, though certain deviations arise: to illustrate the uncertainties of parameters used in calculations, the book's final section presents new and efficient approaches to uncertainty quantification.
Details
Weitere ISBN/GTIN9783030381561
ProduktartE-Book
EinbandartE-Book
FormatPDF
Format Hinweis1 - PDF Watermark
FormatE107
Erscheinungsjahr2020
Erscheinungsdatum03.03.2020
Auflage1st ed. 2020
ReiheLecture Notes in Applied and Computational Mechanics
Reihen-Nr.93
Seiten347 Seiten
SpracheEnglisch
IllustrationenVIII, 347 p. 201 illus., 162 illus. in color.
Artikel-Nr.5112713
Rubriken
Genre9200

Inhalt/Kritik

Inhaltsverzeichnis
1;Preface;6
2;Contents;8
3; Experiments and Virtual Design;10
4; Digital Volume Correlation of Laminographic and Tomographic Images: Results and Challenges;11
4.1;1 Introduction;11
4.2;2 Challenges;12
4.2.1;2.1 Material Microstructure;12
4.2.2;2.2 CT Imaging and Artifacts;13
4.2.3;2.3 Volume of Data/Duration of Acquisition;13
4.2.4;2.4 Detecting Features Invisible to the Eye;14
4.3;3 Recent Solutions;15
4.3.1;3.1 Filtering 3D Images;15
4.3.2;3.2 Global DVC;16
4.3.3;3.3 Reduced Bases and Integrated DVC;18
4.3.4;3.4 Regularized DVC;21
4.3.5;3.5 Projection-Based DVC;23
4.4;4 Conclusion;24
4.5;References;24
5; Manufacturing and Virtual Design to Tailor the Properties of Boron-Alloyed Steel Tubes;29
5.1;1 Introduction;30
5.2;2 Material;31
5.3;3 Technological Process;32
5.4;4 Phase Transformations During Heat-Treatment;33
5.4.1;4.1 Austenite Formation During Inductive Heating;33
5.4.2;4.2 Austenite Decomposition During Spray Cooling;39
5.5;5 Non-destructive Microstructure Characterization;43
5.6;6 Virtual Design of Tube Heat-Treatment;47
5.7;7 Conclusions;49
5.8;References;50
6; Mathematical Modelling and Analysis of Temperature Effects in MEMS;53
6.1;1 Introduction;53
6.2;2 The Full Model;55
6.2.1;2.1 The Evolution of the Membrane;56
6.2.2;2.2 The Electrostatic Potential;57
6.2.3;2.3 The Temperature;58
6.2.4;2.4 Transformation of the System;60
6.2.5;2.5 Examples for the Temperature Dependence;61
6.3;3 The Small Aspect Ratio Limit;62
6.3.1;3.1 The System;63
6.3.2;3.2 Solution to the Thermal and Electrostatic Problems;63
6.3.3;3.3 Well-Posedness of the Deflection Problem;64
6.4;References;66
7; Multi-fidelity Metamodels Nourished by Reduced Order Models;68
7.1;1 Introduction;69
7.2;2 Multi-fidelity Kriging in a Nutshell;70
7.3;3 Presentation of the Mechanical Problem and the LATIN Solver;72
7.3.1;3.1 Mechanical Problem;72
7.3.2;3.2 Chaboche's Elasto-Viscoplastic Behavior Law;72
7.3.3;3.3 LATIN-PGD Solver;74
7.4;4 Presentation of the Test-Cases;75
7.4.1;4.1 Test-Case 1: Plate with Inclusion;76
7.4.2;4.2 Test-Case 2 : Damping Part;77
7.5;5 Implementation of the Coupling Strategy;78
7.5.1;5.1 Correlation Between Error on the Quantity of Interest and LATIN Error Indicator;78
7.5.2;5.2 Method Used for Test Campaigns;79
7.6;6 Results of the Test Campaign;80
7.6.1;6.1 Full Generation of the Metamodel-Test-Case 1;80
7.6.2;6.2 Full Generation of the Metamodel-Test-Case 2;82
7.6.3;6.3 EGO Method for Finding the Global Optimum-Test-Case 1;82
7.6.4;6.4 EGO Method for Finding the Global Optimum - Test-Case 2;84
7.7;7 Conclusion;85
7.8;References;85
8; Application of Enhanced Peridynamic Correspondence Formulationpg for Three-Dimensional Simulationspg at Large Strains;87
8.1;1 Introduction;87
8.2;2 General Framework;88
8.3;3 Correspondence Formulation;91
8.3.1;3.1 Meshfree Discretisation;91
8.3.2;3.2 Time Integration;92
8.3.3;3.3 Stability Problems;93
8.3.4;3.4 Enhanced Formulation;94
8.4;4 Numerical Examples;96
8.4.1;4.1 Tension of a Rod;97
8.4.2;4.2 Punch Test;100
8.4.3;4.3 Torsion of Rod;105
8.5;5 Conclusion;108
8.6;References;109
9; Isogeometric Multiscale Modeling with Galerkin and Collocation Methods;111
9.1;1 Introduction;111
9.2;2 Basis Functions;113
9.2.1;2.1 B-Splines;114
9.2.2;2.2 Non-uniform Rational B-Splines;114
9.3;3 Computational Homogenization;115
9.3.1;3.1 Macroscopic Equilibrium Problem;115
9.3.2;3.2 Microscopic Equilibrium Problem;115
9.4;4 Isogeometric Formulation;116
9.4.1;4.1 Isogeometric Galerkin Formulation;116
9.4.2;4.2 Isogeometric Collocation Formulation;118
9.5;5 Numerical Examples;119
9.5.1;5.1 Microscale Problem;119
9.6;6 Conclusion;124
9.7;References;125
10; Composites;127
11; Experimental and Numerical Investigations on the Combined Forming Behaviour of DX51 and Fibre Reinforced Thermoplastics Under Deep Drawing Conditions;128
11.1;1 Introduction;129
11.2;2 Methodology;132
11.2.1;2.1 Experimental Procedure;133
11.2.2;2.2 Forming Tests;136
11.2.3;2.3 Numerical Methods;136
11.3;3 Results and Discussion;138
11.3.1;3.1 Material Characterization and Modelling;138
11.3.2;3.2 Hemispherical Dome Tests;146
11.4;4 Summary and Outlook;149
11.5;References;149
12; The Representation of Fiber Misalignment Distributions in Numerical Modeling of Compressive Failure of Fiber Reinforced Polymers;152
12.1;1 Introduction;152
12.1.1;1.1 Previous Work;153
12.1.2;1.2 Current Work;155
12.2;2 Measurement Data Driven Model Generation;155
12.2.1;2.1 Fiber Misalignment Distribution Generation from Experimentally Characterized Spectral Density;156
12.2.2;2.2 Generated Distributions Examples;163
12.2.3;2.3 Mapping of Fiber Misalignment Distribution to Numerical Model;166
12.3;3 Numerical Example Results;168
12.4;4 Concluding Remarks;169
12.5;References;170
13; A Multiscale Projection Method for the Analysis of Fiber Microbuckling in Fiber Reinforced Composites;172
13.1;1 Introduction;172
13.2;2 Fine Scale Modeling;174
13.3;3 Transversely Isotropic Material Model for the Coarse Scale;175
13.4;4 Geometrically Nonlinear Cohesive Element;176
13.4.1;4.1 Weak Formulation and Kinematics;177
13.4.2;4.2 Finite Element Discretization;178
13.5;5 Multiscale Modeling;179
13.6;6 Numerical Examples;183
13.7;7 Conclusion;187
13.8;References;188
14; Topology Optimization of 1-3 Piezoelectric Composites;190
14.1;1 Introduction;190
14.2;2 Constitutive Relation of the 1-3 Piezocomposite;192
14.3;3 Materials Microstructure Topology Optimization by the Level Set Method;194
14.4;4 Optimization Algorithm;197
14.5;5 Results;198
14.6;6 Conclusion;200
14.7;References;201
15; Fracture and Fatigue;204
16; Treatment of Brittle Fracture in Solids with the Virtual Element Method;205
16.1;1 Introduction;205
16.2;2 Governing Equations of Brittle Fracture;207
16.2.1;2.1 Basic Equations of Elastic Body;207
16.2.2;2.2 Crack Propagation Based on Stress Intensity Factors;209
16.2.3;2.3 Phase-Field Approach for Brittle Crack Propagation;211
16.3;3 Formulation of the Virtual Element Method;213
16.3.1;3.1 Ansatz Functions for VEM;214
16.3.2;3.2 Residual and Stiffness Matrix of the Virtual Elements;216
16.4;4 Construction of the Crack Path;219
16.5;5 Numerical Examples;221
16.5.1;5.1 Crack Propagation Using Phase-Field Approach;221
16.5.2;5.2 Crack Propagation Using Stress Intensity Factors;226
16.6;6 Conclusion;228
16.7;References;229
17; A Semi-incremental Scheme for Cyclic Damage Computations;233
17.1;1 Introduction;233
17.1.1;1.1 Notation;235
17.2;2 An Overview of the LATIN-PGD Method;236
17.2.1;2.1 Local Stage;237
17.2.2;2.2 Global Stage;238
17.3;3 Variable Amplitude and Frequency Loading;240
17.3.1;3.1 Hybrid Search Direction Formulation;241
17.4;4 Optimality of the Generated ROB;242
17.4.1;4.1 Randomised Singular Value Decomposition (RSVD) Compression of PGD Bases;242
17.5;5 Numerical Results;243
17.5.1;5.1 Model Verification;244
17.5.2;5.2 Comparison Between Deterministic and Randomised SVD Schemes;245
17.5.3;5.3 Variable Amplitude and Frequency Loading;246
17.6;6 Conclusions;249
17.7;References;249
18; Robust Contact and Friction Model for the Fatigue Estimate of a Wire Rope in the Mooring Line of a Floating Offshore Wind Turbine;252
18.1;1 Introduction;253
18.2;2 Detailed Wire Rope Model;254
18.2.1;2.1 A New Contact and Friction Element for Wire Rope;254
18.2.2;2.2 Comparison to Analytical and Surface to Surface Solutions;257
18.2.3;2.3 Boundary Conditions;260
18.2.4;2.4 Wire Rope Properties;263
18.3;3 Application to a FOWT Model;263
18.3.1;3.1 Global Hydrodynamic FOWT Model;263
18.3.2;3.2 Global Model Results;266
18.3.3;3.3 Results of the Detailed Wire Rope Model;267
18.4;4 Conclusion;271
18.5;References;272
19; Micromechanically Motivated Model for Oxidation Ageing of Elastomers;274
19.1;1 Introduction;274
19.2;2 Current State of the Art;276
19.3;3 Network Degradation Dynamics;279
19.3.1;3.1 Compartment Model;280
19.3.2;3.2 Reduction Factor;282
19.4;4 Continuum Model;284
19.4.1;4.1 Primary Network Stress;285
19.4.2;4.2 Secondary Network Stress;286
19.4.3;4.3 Kirchhoff Stress and Material Tangent;287
19.5;5 Numerical Results;288
19.5.1;5.1 Stress Softening and Stiffening;288
19.5.2;5.2 Network Degradation and Permanent Set;289
19.5.3;5.3 Finite Element Example;291
19.6;6 Conclusion;292
19.7;References;292
20; Uncertainty Quantification;294
21; A Bayesian Approach for Uncertainty Quantification in Elliptic Cauchy Problem;295
21.1;1 Introduction;295
21.2;2 The Steklov-Poincaré Approach for the Cauchy Problem;296
21.2.1;2.1 Forward and Cauchy Problems in Linear Elasticity;296
21.2.2;2.2 The Steklov-Poincaré Method;298
21.2.3;2.3 Conjugate Gradient and Ritz Values Computation;299
21.3;3 Bayesian Inference for the Cauchy Problem;300
21.3.1;3.1 Bayes' Theory and Its Application in the Linear Gaussian Case;300
21.3.2;3.2 Application to the Cauchy Problem;301
21.4;4 Reduction by Ritz Modes;302
21.5;5 Numerical Example;305
21.6;6 Conclusion and Perspectives;308
21.7;References;309
22; On-the-Fly Bayesian Data Assimilation Using Transport Map Sampling and PGD Reduced Models;311
22.1;1 Introduction;311
22.2;2 Posterior Sampling in Bayesian Data Assimilation;313
22.2.1;2.1 Basics on Bayesian Inference;313
22.2.2;2.2 Transport Map Sampling;314
22.3;3 PGD Model Order Reduction in Bayesian Inference;318
22.3.1;3.1 Basics on PGD;318
22.3.2;3.2 Transport Map Sampling with PGD Models;318
22.4;4 Illustrative Example;319
22.4.1;4.1 Inference Problem;320
22.4.2;4.2 PGD Solution;321
22.4.3;4.3 Sequential Data Assimilation;321
22.4.4;4.4 Uncertainty Propagation on Outputs of Interest;325
22.5;5 Conclusions and Prospects;329
22.6;References;329
23; Stochastic Material Modeling for Fatigue Damage Analysis;331
23.1;1 Introduction;331
23.2;2 Deterministic Modelling of Fatigue Damage;333
23.2.1;2.1 Material Model;333
23.2.2;2.2 Numerical Approach;334
23.3;3 Stochastic Modelling of Fatigue Damage;335
23.3.1;3.1 From a Deterministic to a Stochastic Process;336
23.3.2;3.2 Numerical Properties of the Damage Process;336
23.3.3;3.3 Proposed Diffusion Random Process;337
23.3.4;3.4 Drift Term;337
23.3.5;3.5 Diffusion Term;338
23.3.6;3.6 Introduction of the Stochastic Damage Model in the Finite-Element Framework;339
23.4;4 Numerical Example;341
23.4.1;4.1 Influence of the Numerical Parameters on the Stochastic Results;342
23.4.2;4.2 Evolution of Stochastic Fatigue Damage;343
23.4.3;4.3 Virtual S-N Curves;345
23.5;5 Summary;348
23.6;References;348mehr

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