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Mechanical behaviors of materials are highly influenced by their architectures and/or microstructures. Hence, progress in material science involves understanding and modeling the link between the microstructure and the material behavior at different scales. This book gathers contributions from eminent researchers in the field of computational and experimental material modeling. It presents advanced experimental techniques to acquire the microstructure features together with dedicated numerical and analytical tools to take into account the randomness of the micro-structure.
Mechanical behaviors of materials are highly influenced by their architectures and/or microstructures. Hence, progress in material science involves understanding and modeling the link between the microstructure and the material behavior at different scales. This book gathers contributions from eminent researchers in the field of computational and experimental material modeling. It presents advanced experimental techniques to acquire the microstructure features together with dedicated numerical and analytical tools to take into account the randomness of the micro-structure.
Salima Bouvier, University of Technology of Compiègne, France
Inhaltsangabe
1. Synchrotron Imaging andDiffraction for In Situ 3D Characterization of Polycrystalline Materials. 2. Determining the Probability of Occurrence of Rarely Occurring Microstructural Configurations for Titanium Dwell Fatigue. 3. Wave Propagation Analysis in2D Nonlinear Periodic Structures Prone to Mechanical Instabilities. 4. Multiscale Model of Concrete Failure. 5. Discrete Numerical Simulationsof the Strength and Microstructure Evolution During Compaction of Layered Granular Solids. 6. Microstructural Views of Stresses in Three-Phase Granular Materials. 7. Effect of the Third Invariant of theStress Deviator on the Response of Porous Solids with Pressure-Insensitive Matrix. 8. High Performance Data-DrivenMultiscale Inverse Constitutive Characterizationof Composites. 9. New Trends in Computational Mechanics: Model Order Reduction, Manifold Learning and Data-Driven.
1. Synchrotron Imaging andDiffraction for In Situ 3D Characterization of Polycrystalline Materials. 2. Determining the Probability of Occurrence of Rarely Occurring Microstructural Configurations for Titanium Dwell Fatigue. 3. Wave Propagation Analysis in2D Nonlinear Periodic Structures Prone to Mechanical Instabilities. 4. Multiscale Model of Concrete Failure. 5. Discrete Numerical Simulationsof the Strength and Microstructure Evolution During Compaction of Layered Granular Solids. 6. Microstructural Views of Stresses in Three-Phase Granular Materials. 7. Effect of the Third Invariant of theStress Deviator on the Response of Porous Solids with Pressure-Insensitive Matrix. 8. High Performance Data-DrivenMultiscale Inverse Constitutive Characterizationof Composites. 9. New Trends in Computational Mechanics: Model Order Reduction, Manifold Learning and Data-Driven.
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