Uncertainty Quantification in Multiscale Materials Modeling

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  • Author : Yan Wang
  • Publisher : Woodhead Publishing
  • Pages : 604 pages
  • ISBN : 008102942X
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Uncertainty Quantification in Multiscale Materials Modeling

Download or Read online Uncertainty Quantification in Multiscale Materials Modeling full in PDF, ePub and kindle. this book written by Yan Wang and published by Woodhead Publishing which was released on 10 March 2020 with total page 604 pages. We cannot guarantee that Uncertainty Quantification in Multiscale Materials Modeling book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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. 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

Uncertainty Quantification in Multiscale Materials Modeling

Uncertainty Quantification in Multiscale Materials Modeling
  • Author : Yan Wang,David L. McDowell
  • Publisher : Woodhead Publishing
  • Release : 10 March 2020
GET THIS BOOK Uncertainty Quantification in Multiscale Materials Modeling

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

Model Validation and Uncertainty Quantification Volume 3

Model Validation and Uncertainty Quantification  Volume 3
  • Author : H. Sezer Atamturktur,Babak Moaveni,Costas Papadimitriou,Tyler Schoenherr
  • Publisher : Springer Science & Business Media
  • Release : 11 April 2014
GET THIS BOOK Model Validation and Uncertainty Quantification Volume 3

This third volume of eight from the IMAC - XXXII Conference, brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Linear Systems Substructure Modelling Adaptive Structures Experimental Techniques Analytical Methods Damage Detection Damping of Materials & Members Modal Parameter Identification Modal Testing Methods System Identification Active Control Modal Parameter Estimation Processing Modal Data

Improved Best Estimate Plus Uncertainty Methodology Including Advanced Validation Concepts to License Evolving Nuclear Reactors

Improved Best Estimate Plus Uncertainty Methodology Including Advanced Validation Concepts to License Evolving Nuclear Reactors
  • Author : Anonim
  • Publisher : Unknown
  • Release : 06 May 2021
GET THIS BOOK Improved Best Estimate Plus Uncertainty Methodology Including Advanced Validation Concepts to License Evolving Nuclear Reactors

Many evolving nuclear energy programs plan to use advanced predictive multi-scale multi-physics simulation and modeling capabilities to reduce cost and time from design through licensing. Historically, the role of experiments was primary tool for design and understanding of nuclear system behavior while modeling and simulation played the subordinate role of supporting experiments. In the new era of multi-scale multi-physics computational based technology development, the experiments will still be needed but they will be performed at different scales to calibrate and

High Performance Computing Applications in Numerical Simulation and Edge Computing

High Performance Computing Applications in Numerical Simulation and Edge Computing
  • Author : Changjun Hu,Wen Yang,Congfeng Jiang,Dong Dai
  • Publisher : Springer Nature
  • Release : 28 August 2019
GET THIS BOOK High Performance Computing Applications in Numerical Simulation and Edge Computing

This book constitutes the referred proceedings of two workshops held at the 32nd ACM International Conference on Supercomputing, ACM ICS 2018, in Beijing, China, in June 2018. This volume presents the papers that have been accepted for the following workshops: Second International Workshop on High Performance Computing for Advanced Modeling and Simulation in Nuclear Energy and Environmental Science, HPCMS 2018, and First International Workshop on HPC Supported Data Analytics for Edge Computing, HiDEC 2018. The 20 full papers presented during HPCMS 2018 and HiDEC 2018 were carefully