Multiscale modeling and simulation of composite materials and structures pdf
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- Multiscale Modeling and Simulation of Composite Materials and Structures
- Uncertainty Quantification in Multiscale Materials Modeling
- Nanomaterials and Multiscale Modeling
Multi-scale and multi-physics materials modeling combines existing and emerging methods from diverse scientific disciplines to bridge the wide range of time and length scales that are inherent in a number of essential phenomena and processes in materials science and engineering. Currently we can observe how novel developments have changed the field in recent years from a descriptive to a predictive approach and have led to the modeling of properties and functions of complex materials under realistic constraints. A proper linkage of electronic-structure theory and statistical methods is necessary to describe the physics and chemistry that govern the properties and processes of materials under realistic temperature and pressure conditions. Multi-Scale and multiphysics models can be used along very different research and engineering directions. The most prominent field of multiscale materials modeling lies in predicting relations between structure, processing amd properties of complex materials beyond the regimes that have been probed experimentally.
Multiscale Modeling and Simulation of Composite Materials and Structures
Uncertainty Quantification in Multiscale Materials Modeling provides a complete overview of uncertainty quantification UQ in computational materials science. It provides practical tools and methods along with examples of their application to problems in materials modeling. UQ methods are applied to various multiscale models ranging from the nanoscale to macroscale. This book presents a thorough synthesis of the state-of-the-art in UQ methods for materials modeling, including Bayesian inference, surrogate modeling, random fields, interval analysis, and sensitivity analysis, providing insight into the unique characteristics of models framed at each scale, as well as common issues in modeling across scales.
His research areas include computer-aided design, computer-aided manufacturing, modeling and simulation, as well as uncertainty quantification. The overarching goal of his research group is to tackle the curse-of-dimensionality design challenge by developing new physics-based data-driven methods to enable engineers to establish comprehensive and robust process-structure-property relationships for the design of materials, products, and processes.
He has published over 90 archived journal papers and 80 peer-reviewed conference papers. He has been regularly invited to give lectures at universities in U. Associate Professor and George W. He has served as Executive Director of IMat since His research focuses on the development of physically-based, microstructure-sensitive constitutive models for nonlinear and time-dependent behavior of materials, with emphasis on wrought and cast metals.
Topics of interest include finite strain inelasticity and defect field mechanics, microstructure-sensitive computational approaches to deformation and damage of heterogeneous materials, with emphasis on metal fatigue, atomistic and coarse-grained atomistic simulations of dislocations, dynamic deformation and failure of materials, irradiation effects on materials, and multiscale modeling with methods for uncertainty quantification.
He has contributed to schemes for computational materials science and mechanics to inform systems design of materials. Applications of current interest span lightweight structural materials, materials for hot sections of aircraft gas turbine engines, titanium alloys, ferritic and austenitic alloys, and nanocrystalline materials, among others.
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Institutional Subscription. Free Shipping Free global shipping No minimum order. Synthesizes available UQ methods for materials modeling Provides practical tools and examples for problem solving in modeling material behavior across various length scales Demonstrates UQ in density functional theory, molecular dynamics, kinetic Monte Carlo, phase field, finite element method, multiscale modeling, and to support decision making in materials design Covers quantum, atomistic, mesoscale, and engineering structure-level modeling and simulation.
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Uncertainty Quantification in Multiscale Materials Modeling
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Nanomaterials and Multiscale Modeling
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Uncertainty Quantification in Multiscale Materials Modeling provides a complete overview of uncertainty quantification UQ in computational materials science. It provides practical tools and methods along with examples of their application to problems in materials modeling. UQ methods are applied to various multiscale models ranging from the nanoscale to macroscale.
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