Download or read book Guide for Verification and Validation in Computational Solid Mechanics written by American Society of Mechanical Engineers and published by . This book was released on 2006 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Illustration of the Concepts of Verification and Validation in Computational Solid Mechanics written by American Society of Mechanical Engineers and published by . This book was released on 2012-06-30 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Verification and Validation in Scientific Computing written by William L. Oberkampf and published by Cambridge University Press. This book was released on 2010-10-14 with total page 782 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Standard for Verification and Validation in Computational Solid Mechanics written by and published by . This book was released on 2020 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computational Mechanics written by Zhenhan Yao and published by Springer Science & Business Media. This book was released on 2009-03-24 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Mechanics is the proceedings of the International Symposium on Computational Mechanics, ISCM 2007. This conference is the first of a series created by a group of prominent scholars from the Mainland of China, Hong Kong, Taiwan, and overseas Chinese, who are very active in the field. The book includes 22 full papers of plenary and semi-plenary lectures and approximately 150 one-page summaries.
Download or read book Verification and Validation for Modeling and Simulation written by Jeffrey Strickland and published by Lulu.com. This book was released on 2014-12-08 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work began when I was appointed as a Technical Director for Modeling and Simulation (M&S) Verification and Validation (V&V) for a major defense system in 2008. It is intended to provide the nuts and bolts of performing M&S V&V in one volume. It is not intended to provide a holistic approach to M&S V&V, as that can be derived from other sources. As such, this book assumes a basic understanding of V&V, including its place in the lifecycle, its purpose and its scope for ensuring the quality of models and simulations. During the process of developing this text, the Simulation Interoperability Standards Organization (SISO) completed SISO-GUIDE-001.2-2013, Guide for Generic Methodology for Verification and Validation (GM-VV) to Support Acceptance of Models, Simulations, and Data, 2 Volumes, June 2013. The guide does serve the purpose not covered by this book. This text provides procedural details for performing V&V. The procedures are static, dynamic and informal.
Download or read book Mechanical Testing of Materials written by Emmanuel Gdoutos and published by Springer Nature. This book was released on 2024-01-19 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensive and in-depth exploration of the most widely used test methods for characterizing the deformation and failure behavior of materials. It presents a thorough treatise on mechanical testing, providing a valuable resource for researchers, engineers, and students seeking to understand the mechanical properties and performance of materials across various applications. The book is organized into ten chapters dedicated to specific test methods including tensile, compression, bending, torsion, multiaxial, indentation, fracture, fatigue, creep, high strain rates, nondestructive evaluation, ensuring a thorough examination of each technique's principles, procedures, and applications. It features two special chapters focusing specifically on the mechanical characterization of concrete and fiber composite materials. These chapters delve into the unique aspects and challenges associated with testing and analyzing these specific materials.
Download or read book Verification Validation and Predictive Capability in Computational Engineering and Physics written by and published by . This book was released on 2003 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developers of computer codes, analysts who use the codes, and decision makers who rely on the results of the analyses face a critical question: How should confidence in modeling and simulation be critically assessed? Verification and validation (V & V) of computational simulations are the primary methods for building and quantifying this confidence. Briefly, verification is the assessment of the accuracy of the solution to a computational model. Validation is the assessment of the accuracy of a computational simulation by comparison with experimental data. In verification, the relationship of the simulation to the real world is not an issue. In validation, the relationship between computation and the real world, i.e., experimental data, is the issue. This paper presents our viewpoint of the state of the art in V & V in computational physics. (In this paper we refer to all fields of computational engineering and physics, e.g., computational fluid dynamics, computational solid mechanics, structural dynamics, shock wave physics, computational chemistry, etc., as computational physics.) We do not provide a comprehensive review of the multitudinous contributions to V & V, although we do reference a large number of previous works from many fields. We have attempted to bring together many different perspectives on V & V, highlight those perspectives that are effective from a practical engineering viewpoint, suggest future research topics, and discuss key implementation issues that are necessary to improve the effectiveness of V & V. We describe our view of the framework in which predictive capability relies on V & V, as well as other factors that affect predictive capability. Our opinions about the research needs and management issues in V & V are very practical: What methods and techniques need to be developed and what changes in the views of management need to occur to increase the usefulness, reliability, and impact of computational physics for decision making about engineering systems? We review the state of the art in V & V over a wide range of topics, for example, prioritization of V & V activities using the Phenomena Identification and Ranking Table (PIRT), code verification, software quality assurance (SQA), numerical error estimation, hierarchical experiments for validation, characteristics of validation experiments, the need to perform nondeterministic computational simulations in comparisons with experimental data, and validation metrics. We then provide an extensive discussion of V & V research and implementation issues that we believe must be addressed for V & V to be more effective in improving confidence in computational predictive capability. Some of the research topics addressed are development of improved procedures for the use of the PIRT for prioritizing V & V activities, the method of manufactured solutions for code verification, development and use of hierarchical validation diagrams, and the construction and use of validation metrics incorporating statistical measures. Some of the implementation topics addressed are the needed management initiatives to better align and team computationalists and experimentalists in conducting validation activities, the perspective of commercial software companies, the key role of analysts and decision makers as code customers, obstacles to the improved effectiveness of V & V, effects of cost and schedule constraints on practical applications in industrial settings, and the role of engineering standards committees in documenting best practices for V & V.
Download or read book Verification Validation and Predictive Capability in Computational Engineering and Physics written by William L. Oberkampf and published by . This book was released on 2003 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developers of computer codes, analysts who use the codes, and decision makers who rely on the results of the analyses face a critical question: How should confidence in modeling and simulation be critically assessed? Verification and validation (V & V) of computational simulations are the primary methods for building and quantifying this confidence. Briefly, verification is the assessment of the accuracy of the solution to a computational model. Validation is the assessment of the accuracy of a computational simulation by comparison with experimental data. In verification, the relationship of the simulation to the real world is not an issue. In validation, the relationship between computation and the real world, i.e., experimental data, is the issue. This paper presents our viewpoint of the state of the art in V & V in computational physics. (In this paper we refer to all fields of computational engineering and physics, e.g., computational fluid dynamics, computational solid mechanics, structural dynamics, shock wave physics, computational chemistry, etc., as computational physics.) We do not provide a comprehensive review of the multitudinous contributions to V & V, although we do reference a large number of previous works from many fields. We have attempted to bring together many different perspectives on V & V, highlight those perspectives that are effective from a practical engineering viewpoint, suggest future research topics, and discuss key implementation issues that are necessary to improve the effectiveness of V & V. We describe our view of the framework in which predictive capability relies on V & V, as well as other factors that affect predictive capability. Our opinions about the research needs and management issues in V & V are very practical: What methods and techniques need to be developed and what changes in the views of management need to occur to increase the usefulness, reliability, and impact of computational physics for decision making about engineering systems? We review the state of the art in V & V over a wide range of topics, for example, prioritization of V & V activities using the Phenomena Identification and Ranking Table (PIRT), code verification, software quality assurance (SQA), numerical error estimation, hierarchical experiments for validation, characteristics of validation experiments, the need to perform nondeterministic computational simulations in comparisons with experimental data, and validation metrics. We then provide an extensive discussion of V & V research and implementation issues that we believe must be addressed for V & V to be more effective in improving confidence in computational predictive capability. Some of the research topics addressed are development of improved procedures for the use of the PIRT for prioritizing V & V activities, the method of manufactured solutions for code verification, development and use of hierarchical validation diagrams, and the construction and use of validation metrics incorporating statistical measures. Some of the implementation topics addressed are the needed management initiatives to better align and team computationalists and experimentalists in conducting validation activities, the perspective of commercial software companies, the key role of analysts and decision makers as code customers, obstacles to the improved effectiveness of V & V, effects of cost and schedule constraints on practical applications in industrial settings, and the role of engineering standards committees in documenting best practices for V & V.
Download or read book Verification and Validation in Computational Science and Engineering written by Patrick J. Roache and published by . This book was released on 1998 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Verification Validation and Uncertainty Quantification in Scientific Computing written by William L. Oberkampf and published by Cambridge University Press. This book was released on 2024-12-31 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can you trust results from modeling and simulation? This text provides a framework for assessing the reliability of and uncertainty included in the results used by decision makers and policy makers in industry and government. The emphasis is on models described by PDEs and their numerical solution. Procedures and results from all aspects of verification and validation are integrated with modern methods in uncertainty quantification and stochastic simulation. Methods for combining numerical approximation errors, uncertainty in model input parameters, and model form uncertainty are presented in order to estimate the uncertain response of a system in the presence of stochastic inputs and lack of knowledge uncertainty. This new edition has been extensively updated, including a fresh look at model accuracy assessment and the responsibilities of management for modeling and simulation activities. Extra homework problems and worked examples have been added to each chapter, suitable for course use or self-study.
Download or read book Proceedings of the 1st International Conference in Safety and Crisis Management in the Construction Tourism and SME Sectors written by and published by Universal-Publishers. This book was released on with total page 748 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Verification and Validation in Computational Fluid Dynamics written by and published by . This book was released on 2002 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Verification and validation (V and V) are the primary means to assess accuracy and reliability in computational simulations. This paper presents an extensive review of the literature in V and V in computational fluid dynamics (CFD), discusses methods and procedures for assessing V and V, and develops a number of extensions to existing ideas. The review of the development of V and V terminology and methodology points out the contributions from members of the operations research, statistics, and CFD communities. Fundamental issues in V and V are addressed, such as code verification versus solution verification, model validation versus solution validation, the distinction between error and uncertainty, conceptual sources of error and uncertainty, and the relationship between validation and prediction. The fundamental strategy of verification is the identification and quantification of errors in the computational model and its solution. In verification activities, the accuracy of a computational solution is primarily measured relative to two types of highly accurate solutions: analytical solutions and highly accurate numerical solutions. Methods for determining the accuracy of numerical solutions are presented and the importance of software testing during verification activities is emphasized.
Download or read book Experimentation Validation and Uncertainty Analysis for Engineers written by Hugh W. Coleman and published by John Wiley & Sons. This book was released on 2018-04-09 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Helps engineers and scientists assess and manage uncertainty at all stages of experimentation and validation of simulations Fully updated from its previous edition, Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition includes expanded coverage and new examples of applying the Monte Carlo Method (MCM) in performing uncertainty analyses. Presenting the current, internationally accepted methodology from ISO, ANSI, and ASME standards for propagating uncertainties using both the MCM and the Taylor Series Method (TSM), it provides a logical approach to experimentation and validation through the application of uncertainty analysis in the planning, design, construction, debugging, execution, data analysis, and reporting phases of experimental and validation programs. It also illustrates how to use a spreadsheet approach to apply the MCM and the TSM, based on the authors’ experience in applying uncertainty analysis in complex, large-scale testing of real engineering systems. Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition includes examples throughout, contains end of chapter problems, and is accompanied by the authors’ website www.uncertainty-analysis.com. Guides readers through all aspects of experimentation, validation, and uncertainty analysis Emphasizes the use of the Monte Carlo Method in performing uncertainty analysis Includes complete new examples throughout Features workable problems at the end of chapters Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition is an ideal text and guide for researchers, engineers, and graduate and senior undergraduate students in engineering and science disciplines. Knowledge of the material in this Fourth Edition is a must for those involved in executing or managing experimental programs or validating models and simulations.
Download or read book A Verification and Validation Procedure for Computational Fluid Dynamics Solutions written by Michael P Ebert and published by . This book was released on 2001 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report presents the mechanics of performing a verification and validation analysis for practical problems, focusing mainly on the estimation of uncertainty in the numerical prediction due to the use of finite grid sizes. A detailed example is presented along with discussions regarding many of the practical issues involved in performing a rigorous verification and validation analysis. The particular approach outlined in this report is mainly based on theoretical work performed at the Iowa Institute of Hydraulic Research. This approach requires numerical solutions on 3 related grids; however, an alternative approach requiring solutions on only 2 grids is also demonstrated.
Download or read book Concepts of Model Verification and Validation written by M. C. Anderson and published by . This book was released on 2004 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model verification and validation (V & V) is an enabling methodology for the development of computational models that can be used to make engineering predictions with quantified confidence. Model V & V procedures are needed by government and industry to reduce the time, cost, and risk associated with full-scale testing of products, materials, and weapon systems. Quantifying the confidence and predictive accuracy of model calculations provides the decision-maker with the information necessary for making high-consequence decisions. The development of guidelines and procedures for conducting a model V & V program are currently being defined by a broad spectrum of researchers. This report reviews the concepts involved in such a program. Model V & V is a current topic of great interest to both government and industry. In response to a ban on the production of new strategic weapons and nuclear testing, the Department of Energy (DOE) initiated the Science-Based Stockpile Stewardship Program (SSP). An objective of the SSP is to maintain a high level of confidence in the safety, reliability, and performance of the existing nuclear weapons stockpile in the absence of nuclear testing. This objective has challenged the national laboratories to develop high-confidence tools and methods that can be used to provide credible models needed for stockpile certification via numerical simulation. There has been a significant increase in activity recently to define V & V methods and procedures. The U.S. Department of Defense (DoD) Modeling and Simulation Office (DMSO) is working to develop fundamental concepts and terminology for V & V applied to high-level systems such as ballistic missile defense and battle management simulations. The American Society of Mechanical Engineers (ASME) has recently formed a Standards Committee for the development of V & V procedures for computational solid mechanics models. The Defense Nuclear Facilities Safety Board (DNFSB) has been a proponent of model V & V for all safety-related nuclear facility design, analyses, and operations. In fact, DNFSB 2002-1 recommends to the DOE and National Nuclear Security Administration (NNSA) that a V & V process be performed for all safety related software and analysis. Model verification and validation are the primary processes for quantifying and building credibility in numerical models. Verification is the process of determining that a model implementation accurately represents the developer's conceptual description of the model and its solution. Validation is the process of determining the degree to which a model is an accurate representation of the real world from the perspective of the intended uses of the model. Both verification and validation are processes that accumulate evidence of a model's correctness or accuracy for a specific scenario; thus, V & V cannot prove that a model is correct and accurate for all possible scenarios, but, rather, it can provide evidence that the model is sufficiently accurate for its intended use. Model V & V is fundamentally different from software V & V. Code developers developing computer programs perform software V & V to ensure code correctness, reliability, and robustness. In model V & V, the end product is a predictive model based on fundamental physics of the problem being solved. In all applications of practical interest, the calculations involved in obtaining solutions with the model require a computer code, e.g., finite element or finite difference analysis. Therefore, engineers seeking to develop credible predictive models critically need model V & V guidelines and procedures. The expected outcome of the model V & V process is the quantified level of agreement between experimental data and model prediction, as well as the predictive accuracy of the model. This report attempts to describe the general philosophy, definitions, concepts, and processes for conducting a successful V & V program. This objective is motivated by the need for highly accurate numerical models for making predictions to support the SSP, and also by the lack of guidelines, standards and procedures for performing V & V for complex numerical models.
Download or read book Computer Simulation Validation written by Claus Beisbart and published by Springer. This book was released on 2019-04-09 with total page 1074 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique volume introduces and discusses the methods of validating computer simulations in scientific research. The core concepts, strategies, and techniques of validation are explained by an international team of pre-eminent authorities, drawing on expertise from various fields ranging from engineering and the physical sciences to the social sciences and history. The work also offers new and original philosophical perspectives on the validation of simulations. Topics and features: introduces the fundamental concepts and principles related to the validation of computer simulations, and examines philosophical frameworks for thinking about validation; provides an overview of the various strategies and techniques available for validating simulations, as well as the preparatory steps that have to be taken prior to validation; describes commonly used reference points and mathematical frameworks applicable to simulation validation; reviews the legal prescriptions, and the administrative and procedural activities related to simulation validation; presents examples of best practice that demonstrate how methods of validation are applied in various disciplines and with different types of simulation models; covers important practical challenges faced by simulation scientists when applying validation methods and techniques; offers a selection of general philosophical reflections that explore the significance of validation from a broader perspective. This truly interdisciplinary handbook will appeal to a broad audience, from professional scientists spanning all natural and social sciences, to young scholars new to research with computer simulations. Philosophers of science, and methodologists seeking to increase their understanding of simulation validation, will also find much to benefit from in the text.
