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Verification and validation in scientific computing

Author: William L Oberkampf; Christopher J Roy
Publisher: New York : Cambridge University Press, 2010.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
"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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Oberkampf, William L., 1944-
Verification and validation in scientific computing.
New York : Cambridge University Press, 2010
(DLC) 2010021488
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: William L Oberkampf; Christopher J Roy
ISBN: 9780511903977 0511903979 9780511906725 0511906722 9780511760396 0511760396
OCLC Number: 704518586
Description: 1 online resource (xiv, 767 pages) : illustrations
Contents: Machine generated contents note: Preface; 1. Introduction; Part I. Fundamental Concepts: 2. Fundamental concepts and terminology; 3. Modeling and computational simulation; Part II. Code Verification: 4. Software engineering; 5. Code verification; 6. Exact solutions; Part III. Solution Verification: 7. Solution verification; 8. Discretization error; 9. Solution adaptation; Part IV. Model Validation and Prediction: 10. Model validation fundamentals; 11. Design and execution of validation experiments; 12. Model accuracy assessment; 13. Predictive capability; Part V. Planning, Management, and Implementation Issues: 14. Planning and prioritization in modeling and simulation; 15. Maturity assessment of modeling and simulation; 16. Development and responsibilities for verification, validation and uncertainty quantification; Appendix. Programming practices; Index.
Responsibility: William L. Oberkampf, Christopher J. Roy.

Abstract:

Can you trust results from modelling and simulation? Verification, validation, and uncertainty quantification can help.  Read more...

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'This ambitious and well-written book is an excellent comprehensive review of what you need to know to evaluate or build a complex model or simulation of a physical process ... would be a good Read more...

 
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