Workshop On Uncertainty Quantification And Multiscale Materials Modeling
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Workshop On Uncertainty Quantification And Multiscale Materials Modeling
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Author :
language : en
Publisher:
Release Date : 2011
Workshop On Uncertainty Quantification And Multiscale Materials Modeling written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Uncertainty Quantification In Multiscale Materials Modeling
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Author : Yan Wang
language : en
Publisher: Woodhead Publishing
Release Date : 2020-03-12
Uncertainty Quantification In Multiscale Materials Modeling written by Yan Wang and has been published by Woodhead Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-12 with Technology & Engineering categories.
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.
Fundamentals Of Uncertainty Quantification For Engineers
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Author : Yan Wang
language : en
Publisher: Elsevier
Release Date : 2025-05-30
Fundamentals Of Uncertainty Quantification For Engineers written by Yan Wang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-30 with Technology & Engineering categories.
Fundamentals of Uncertainty Quantification for Engineers: Methods and Models provides a comprehensive introduction to uncertainty quantification (UQ) accompanied by a wide variety of applied examples and implementation details to reinforce the concepts outlined in the book. Sections start with an introduction to the history of probability theory and an overview of recent developments of UQ methods in the domains of applied mathematics and data science. Major concepts of copula, Monte Carlo sampling, Markov chain Monte Carlo, polynomial regression, Gaussian process regression, polynomial chaos expansion, stochastic collocation, Bayesian inference, modelform uncertainty, multi-fidelity modeling, model validation, local and global sensitivity analyses, linear and nonlinear dimensionality reduction are included. Advanced UQ methods are also introduced, including stochastic processes, stochastic differential equations, random fields, fractional stochastic differential equations, hidden Markov model, linear Gaussian state space model, as well as non-probabilistic methods such as robust Bayesian analysis, Dempster-Shafer theory, imprecise probability, and interval probability. The book also includes example applications in multiscale modeling, reliability, fatigue, materials design, machine learning, and decision making. • Introduces all major topics of uncertainty quantification with engineering examples and implementation details• Features examples from a wide variety of science and engineering disciplines (e.g., fluids, structural dynamics, materials, manufacturing, multiscale simulation)• Discusses sampling methods, surrogate modeling, stochastic expansion, sensitivity analysis, dimensionality reduction and more
Data Driven Modeling For Additive Manufacturing Of Metals
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Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2019-11-09
Data Driven Modeling For Additive Manufacturing Of Metals written by National Academies of Sciences, Engineering, and Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-09 with Technology & Engineering categories.
Additive manufacturing (AM) is the process in which a three-dimensional object is built by adding subsequent layers of materials. AM enables novel material compositions and shapes, often without the need for specialized tooling. This technology has the potential to revolutionize how mechanical parts are created, tested, and certified. However, successful real-time AM design requires the integration of complex systems and often necessitates expertise across domains. Simulation-based design approaches, such as those applied in engineering product design and material design, have the potential to improve AM predictive modeling capabilities, particularly when combined with existing knowledge of the underlying mechanics. These predictive models have the potential to reduce the cost of and time for concept-to-final-product development and can be used to supplement experimental tests. The National Academies convened a workshop on October 24-26, 2018 to discuss the frontiers of mechanistic data-driven modeling for AM of metals. Topics of discussion included measuring and modeling process monitoring and control, developing models to represent microstructure evolution, alloy design, and part suitability, modeling phases of process and machine design, and accelerating product and process qualification and certification. These topics then led to the assessment of short-, immediate-, and long-term challenges in AM. This publication summarizes the presentations and discussions from the workshop.
Uncertainty Quantification In Multiscale Materials Modeling
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Author : Yan Wang
language : en
Publisher: Woodhead Publishing
Release Date : 2020-03-10
Uncertainty Quantification In Multiscale Materials Modeling written by Yan Wang and has been published by Woodhead Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-10 with Technology & Engineering categories.
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
International Assessment Of Research And Development In Simulation Based Engineering And Science
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Author : Sharon C Glotzer
language : en
Publisher: World Scientific
Release Date : 2011-06-10
International Assessment Of Research And Development In Simulation Based Engineering And Science written by Sharon C Glotzer and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-10 with Mathematics categories.
Simulation-Based Engineering and Science (SBE&S) cuts across disciplines, showing tremendous promise in areas from storm prediction and climate modeling to understanding the brain and the behavior of numerous other complex systems.In this groundbreaking volume, nine distinguished leaders assess the latest research trends, as a result of 52 site visits in Europe and Asia and hundreds of hours of expert interviews, and discuss the implications of their findings for the US government.The authors conclude that while the US remains the quantitative leader in SBE&S research and development, it is very much in danger of losing that edge to Europe and Asia.Commissioned by the National Science Foundation, this multifaceted study will capture the attention of Fortune 500 companies and policymakers.Distinguished contributors: Sharon C Goltzer, University of Michigan, Ann Arbor, USA Sangtae Kim, Morgridge Institute for Research, USA Peter T Cummings, Vanderbilt University, USA and Oak Ridge National Laboratory, USA Abhijit Deshmukh, Texas A&M University, USA Martin Head-Gordon, University of California, Berkeley, USA George Em Karniadakis, Brown University, USA Linda Petzold, University of California, Santa Barbara, USA Celeste Sagui, North Carolina State University, USA Masanobu Shinozuka, University of California, Irvine, USA
Machine Learning In Modeling And Simulation
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Author : Timon Rabczuk
language : en
Publisher: Springer Nature
Release Date : 2023-10-03
Machine Learning In Modeling And Simulation written by Timon Rabczuk and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-03 with Technology & Engineering categories.
Machine learning (ML) approaches have been extensively and successfully employed in various areas, like in economics, medical predictions, face recognition, credit card fraud detection, and spam filtering. There is clearly also the potential that ML techniques developed in Engineering and the Sciences will drastically increase the possibilities of analysis and accelerate the design to analysis time. With the use of ML techniques, coupled to conventional methods like finite element and digital twin technologies, new avenues of modeling and simulation can be opened but the potential of these ML techniques needs to still be fully harvested, with the methods developed and enhanced. The objective of this book is to provide an overview of ML in Engineering and the Sciences presenting fundamental theoretical ingredients with a focus on the next generation of computer modeling in Engineering and the Sciences in which the exciting aspects of machine learning are incorporated. The book is of value to any researcher and practitioner interested in research or applications of ML in the areas of scientific modeling and computer aided engineering.
Computational Materials System Design
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Author : Dongwon Shin
language : en
Publisher: Springer
Release Date : 2017-11-10
Computational Materials System Design written by Dongwon Shin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-10 with Technology & Engineering categories.
This book provides state-of-the-art computational approaches for accelerating materials discovery, synthesis, and processing using thermodynamics and kinetics. The authors deliver an overview of current practical computational tools for materials design in the field. They describe ways to integrate thermodynamics and kinetics and how the two can supplement each other.
Predictive Theoretical And Computational Approaches For Additive Manufacturing
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Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2016-12-21
Predictive Theoretical And Computational Approaches For Additive Manufacturing written by National Academies of Sciences, Engineering, and Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-21 with Technology & Engineering categories.
Additive manufacturing (AM) methods have great potential for promoting transformative research in many fields across the vast spectrum of engineering and materials science. AM is one of the leading forms of advanced manufacturing which enables direct computer-aided design (CAD) to part production without part-specific tooling. In October 2015 the National Academies of Sciences, Engineering, and Medicine convened a workshop of experts from diverse communities to examine predictive theoretical and computational approaches for various AM technologies. While experimental workshops in AM have been held in the past, this workshop uniquely focused on theoretical and computational approaches and involved areas such as simulation-based engineering and science, integrated computational materials engineering, mechanics, materials science, manufacturing processes, and other specialized areas. This publication summarizes the presentations and discussions from the workshop.
Information And Communications
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2003-11-28
Information And Communications written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-11-28 with Computers categories.
Since publication of the National Research Council (NRC) reports on chemistry in 1985 and chemical engineering in 1988,1,2 dramatic advances in information technology (IT) have totally changed these communities. During this period, the chemical enterprise and information technology have enjoyed both a remarkably productive and mutually supportive set of advances. These synergies sparked unprecedented growth in the capability and productivity of both fields including the definition of entirely new areas of the chemical enterprise. The chemical enterprise provided information technology with device fabrication processes, new materials, data, models, methods, and (most importantly) people. In turn, information technology provided chemical science and technology with truly remarkable and revolutionary resources for computations, communications, and data management. Indeed, computation has become the strong third component of the chemical science research and development effort, joining experiment and theory. Sustained mutual growth and interdependence of the chemical and information communities should take account of several unique aspects of the chemical sciences. These include extensive and complex databases that characterize the chemical disciplines; the importance of multiscale simulations that range from molecules to technological processes; the global economic impact of the chemical industry; and the industry's major influence on the nation's health, environment, security, and economic well-being. In planning the future of the chemical sciences and technology, it is crucial to recognize the benefits already derived from advances in information technology as well as to point the way to future benefits that will be derived.