| Author | : Yan Wang,David L. McDowell |
| Publisher | : Woodhead Publishing |
| Release Date | : 2020-03-10 |
| ISBN 10 | : 008102942X |
| Pages | : 604 pages |
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
| Author | : United States. Congress. House. Committee on Appropriations. Subcommittee on Energy and Water Development |
| Publisher | : N.A |
| Release Date | : 2000 |
| ISBN 10 | : |
| Pages | : 329 pages |
| Author | : H. Sezer Atamturktur,Babak Moaveni,Costas Papadimitriou,Tyler Schoenherr |
| Publisher | : Springer Science & Business Media |
| Release Date | : 2014-04-11 |
| ISBN 10 | : 3319045520 |
| Pages | : 427 pages |
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
| Author | : United States. Congress. House. Committee on Appropriations. Subcommittee on Energy and Water Development |
| Publisher | : N.A |
| Release Date | : 2013 |
| ISBN 10 | : |
| Pages | : 329 pages |
| Author | : United States. Congress. House. Committee on Appropriations. Subcommittee on Energy and Water Development |
| Publisher | : N.A |
| Release Date | : 2009 |
| ISBN 10 | : |
| Pages | : 329 pages |
| Author | : N.A |
| Publisher | : N.A |
| Release Date | : 2010 |
| ISBN 10 | : |
| Pages | : 329 pages |
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 validate models leading predictive simulations. Cost saving goals of programs will require us to minimize the required number of validation experiments. Utilization of more multi-scale multi-physics models introduces complexities in the validation of predictive tools. Traditional methodologies will have to be modified to address these arising issues. This paper lays out the basic aspects of a methodology that can be potentially used to address these new challenges in design and licensing of evolving nuclear technology programs. The main components of the proposed methodology are verification, validation, calibration, and uncertainty quantification. An enhanced calibration concept is introduced and is accomplished through data assimilation. The goal is to enable best-estimate prediction of system behaviors in both normal and safety related environments. To achieve this goal requires the additional steps of estimating the domain of validation and quantification of uncertainties that allow for extension of results to areas of the validation domain that are not directly tested with experiments, which might include extension of the modeling and simulation (M & S) capabilities for application to full-scale systems. The new methodology suggests a formalism to quantify an adequate level of validation (predictive maturity) with respect to required selective data so that required testing can be minimized for cost saving purposes by showing further testing wold not enhance the quality of the validation of predictive tools. The proposed methodology is at a conceptual level. When matured and if considered favorably by the stakeholders, it could serve as a new framework for the next generation of the best estimate plus uncertainty licensing methodology that USNRC developed previously. In order to come to that level of maturity it is necessary to communicate the methodology to scientific, design and regulatory stakeholders for discussion and debates. This paper is the first step to establish this communication.
| Author | : National Research Council,Division on Engineering and Physical Sciences,Board on Mathematical Sciences and Their Applications,Committee on Mathematical Foundations of Verification, Validation, and Uncertainty Quantification |
| Publisher | : National Academies Press |
| Release Date | : 2012-07-26 |
| ISBN 10 | : 0309256348 |
| Pages | : 144 pages |
Advances in computing hardware and algorithms have dramatically improved the ability to simulate complex processes computationally. Today's simulation capabilities offer the prospect of addressing questions that in the past could be addressed only by resource-intensive experimentation, if at all. Assessing the Reliability of Complex Models recognizes the ubiquity of uncertainty in computational estimates of reality and the necessity for its quantification. As computational science and engineering have matured, the process of quantifying or bounding uncertainties in a computational estimate of a physical quality of interest has evolved into a small set of interdependent tasks: verification, validation, and uncertainty of quantification (VVUQ). In recognition of the increasing importance of computational simulation and the increasing need to assess uncertainties in computational results, the National Research Council was asked to study the mathematical foundations of VVUQ and to recommend steps that will ultimately lead to improved processes. Assessing the Reliability of Complex Models discusses changes in education of professionals and dissemination of information that should enhance the ability of future VVUQ practitioners to improve and properly apply VVUQ methodologies to difficult problems, enhance the ability of VVUQ customers to understand VVUQ results and use them to make informed decisions, and enhance the ability of all VVUQ stakeholders to communicate with each other. This report is an essential resource for all decision and policy makers in the field, students, stakeholders, UQ experts, and VVUQ educators and practitioners.
| Author | : Paul G. Constantine |
| Publisher | : SIAM |
| Release Date | : 2015-03-17 |
| ISBN 10 | : 1611973864 |
| Pages | : 100 pages |
Scientists and engineers use computer simulations to study relationships between a model's input parameters and its outputs. However, thorough parameter studies are challenging, if not impossible, when the simulation is expensive and the model has several inputs. To enable studies in these instances, the engineer may attempt to reduce the dimension of the model's input parameter space. Active subspaces are an emerging set of dimension reduction tools that identify important directions in the parameter space. This book describes techniques for discovering a model's active subspace and proposes methods for exploiting the reduced dimension to enable otherwise infeasible parameter studies. Readers will find new ideas for dimension reduction, easy-to-implement algorithms, and several examples of active subspaces in action.
| Author | : Jun Wang,Xin Li,Chris Allison,Judy Hohorst |
| Publisher | : Woodhead Publishing |
| Release Date | : 2020-11-10 |
| ISBN 10 | : 0128181915 |
| Pages | : 608 pages |
Nuclear Power Plant Design and Analysis Codes: Development, Validation, and Application presents the latest research on the most widely used nuclear codes and the wealth of successful accomplishments which have been achieved over the past decades by experts in the field. Editors Wang, Li,Allison, and Hohorst and their team of authors provide readers with a comprehensive understanding of nuclear code development and how to apply it to their work and research to make their energy production more flexible, economical, reliable and safe. Written in an accessible and practical way, each chapter considers strengths and limitations, data availability needs, verification and validation methodologies and quality assurance guidelines to develop thorough and robust models and simulation tools both inside and outside a nuclear setting. This book benefits those working in nuclear reactor physics and thermal-hydraulics, as well as those involved in nuclear reactor licensing. It also provides early career researchers with a solid understanding of fundamental knowledge of mainstream nuclear modelling codes, as well as the more experienced engineers seeking advanced information on the best solutions to suit their needs. Captures important research conducted over last few decades by experts and allows new researchers and professionals to learn from the work of their predecessors Presents the most recent updates and developments, including the capabilities, limitations, and future development needs of all codes Incudes applications for each code to ensure readers have complete knowledge to apply to their own setting.
| Author | : Franz Roters,Philip Eisenlohr,Thomas R. Bieler,Dierk Raabe |
| Publisher | : John Wiley & Sons |
| Release Date | : 2011-08-04 |
| ISBN 10 | : 3527642099 |
| Pages | : 208 pages |
Written by the leading experts in computational materials science, this handy reference concisely reviews the most important aspects of plasticity modeling: constitutive laws, phase transformations, texture methods, continuum approaches and damage mechanisms. As a result, it provides the knowledge needed to avoid failures in critical systems udner mechanical load. With its various application examples to micro- and macrostructure mechanics, this is an invaluable resource for mechanical engineers as well as for researchers wanting to improve on this method and extend its outreach.
| Author | : Robert Martin,Cesare Frepoli |
| Publisher | : World Scientific |
| Release Date | : 2019-02-13 |
| ISBN 10 | : 9813275677 |
| Pages | : 716 pages |
This book captures the principles of safety evaluation as practiced in the regulated light-water reactor nuclear industry, as established and stabilized over the last 30 years. It is expected to serve both the current industry and those planning for the future. The work's coverage of the subject matter is the broadest to date, including not only the common topics of modeling and simulation, but also methods supporting the basis for the underlying assumptions, the extension to radiological safety, what to expect in a licensing review, historical perspectives and the implication for new designs.This text is an essential resource for practitioners and students, on the current best-practices in nuclear power plant safety and their basis. Contributors of this work are subject matter experts in their specialties, much of which was nurtured and inspired by Prof. Larry Hochreiter, a prominent nuclear safety pioneer.Related Link(s)
| Author | : William L. Oberkampf,Christopher J. Roy |
| Publisher | : Cambridge University Press |
| Release Date | : 2010-10-14 |
| ISBN 10 | : 1139491768 |
| Pages | : 329 pages |
Advances in scientific computing have made modelling and simulation an important part of the decision-making process in engineering, science, and public policy. This book provides a comprehensive and systematic development of the basic concepts, principles, and procedures for verification and validation of models and simulations. The emphasis is placed on models that are described by partial differential and integral equations and the simulations that result from their numerical solution. The methods described can be applied to a wide range of technical fields, from the physical sciences, engineering and technology and industry, through to environmental regulations and safety, product and plant safety, financial investing, and governmental regulations. This book will be genuinely welcomed by researchers, practitioners, and decision makers in a broad range of fields, who seek to improve the credibility and reliability of simulation results. It will also be appropriate either for university courses or for independent study.