Verification And Validation In Computational Fluid Dynamics
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Verification And Validation In Computational Fluid Dynamics
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Author : William L. Oberkampf
language : en
Publisher:
Release Date : 2002
Verification And Validation In Computational Fluid Dynamics written by William L. Oberkampf and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computational fluid dynamics categories.
Verification And Validation In Scientific Computing
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Author : William L. Oberkampf
language : en
Publisher: Cambridge University Press
Release Date : 2010-10-14
Verification And Validation In Scientific Computing written by William L. Oberkampf and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-14 with Computers categories.
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.
Verification And Validation In Computational Fluid Dynamics
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Author :
language : en
Publisher:
Release Date : 2002
Verification And Validation In Computational Fluid Dynamics written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with categories.
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.
Standard For Verification And Validation In Computational Fluid Dynamics And Heat Transfer
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Author :
language : en
Publisher:
Release Date : 2009
Standard For Verification And Validation In Computational Fluid Dynamics And Heat Transfer written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Computational fluid dynamics categories.
Verification And Validation In Computational Science And Engineering
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Author : Patrick J. Roache
language : en
Publisher:
Release Date : 1998
Verification And Validation In Computational Science And Engineering written by Patrick J. Roache and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Algorithms categories.
Verification And Validation Of Computational Fluid Dynamics
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Author :
language : en
Publisher:
Release Date : 2000
Verification And Validation Of Computational Fluid Dynamics written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with categories.
Standard For Verification And Validation In Computational Fluid Dynamics And Heat Transfer
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Author :
language : en
Publisher:
Release Date : 2009
Standard For Verification And Validation In Computational Fluid Dynamics And Heat Transfer written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Computational fluid dynamics categories.
Verification Validation And Predictive Capability In Computational Engineering And Physics
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Author : William L. Oberkampf
language : en
Publisher:
Release Date : 2003
Verification Validation And Predictive Capability In Computational Engineering And Physics written by William L. Oberkampf and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computer simulation categories.
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.
Bibliography For Verification And Validation In Computational Simulations
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Author : William L. Oberkampf
language : en
Publisher:
Release Date : 1998
Bibliography For Verification And Validation In Computational Simulations written by William L. Oberkampf and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Computer programs categories.
A bibliography has been compiled dealing with the verification and validation of computational simulations. The references listed in this bibliography are concentrated in the field of computational fluid dynamics (CFD). However, references from the following fields are also included: operations research, heat transfer, solid dynamics, software quality assurance, software accreditation, military systems, and nuclear reactor safety. This bibliography, containing 221 references, is not meant to be comprehensive. It was compiled during the last ten years in response to the author's interest and research in the methodology for verification and validation. The emphasis in the bibliography is in the following areas: philosophy of science underpinnings, development of terminology and methodology, high accuracy solutions for CFD verification, experimental datasets for CFD validation, and the statistical quantification of model validation. This bibliography should provide a starting point for individual researchers in many fields of computational simulation in science and engineering.
Issues In Computational Fluid Dynamics Code Verification And Validation
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Author : William L. Oberkampf
language : en
Publisher:
Release Date : 1997
Issues In Computational Fluid Dynamics Code Verification And Validation written by William L. Oberkampf and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Computational fluid dynamics categories.
A broad range of mathematical modeling errors of fluid flow physics and numerical approximation errors are addressed in computational fluid dynamics (CFD). It is strongly believed that if CFD is to have a major impact on the design of engineering hardware and flight systems, the level of confidence in complex simulations must substantially improve. To better understand the present limitations of CFD simulations, a wide variety of physical modeling, discretization, and solution errors are identified and discussed. Here, discretization and solution errors refer to all errors caused by conversion of the original partial differential, or integral, conservation equations representing the physical process, to algebraic equations and their solution on a computer. The impact of boundary conditions on the solution of the partial differential equations and their discrete representation will also be discussed. Throughout the article, clear distinctions are made between the analytical mathematical models of fluid dynamics and the numerical models. Lax's Equivalence Theorem and its frailties in practical CFD solutions are pointed out. Distinctions are also made between the existence and uniqueness of solutions to the partial differential equations as opposed to the discrete equations. Two techniques are briefly discussed for the detection and quantification of certain types of discretization and grid resolution errors.