Free PDF Verification and Validation in Scientific Computing
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Verification and Validation in Scientific Computing
Free PDF Verification and Validation in Scientific Computing
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Review
"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." Joan Horvath, Computing Reviews
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Book Description
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 framework for assessing its reliability and addresses inherent uncertainties, numerical approximation errors, and modeling errors.
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Product details
Hardcover: 790 pages
Publisher: Cambridge University Press; 1 edition (November 22, 2010)
Language: English
ISBN-10: 0521463408
ISBN-13: 978-0521113601
ASIN: 0521113601
Product Dimensions:
6.9 x 1.8 x 9.7 inches
Shipping Weight: 3.7 pounds (View shipping rates and policies)
Average Customer Review:
4.4 out of 5 stars
2 customer reviews
Amazon Best Sellers Rank:
#980,548 in Books (See Top 100 in Books)
Nice book for this subject from the experts in the field.
This book is an excellent resource for anyone dealing with concepts of verification and validation. This was an important part of my thesis work, and this reference was invaluable in providing a much-needed comprehensive overview of the verification and validation literature. Both Oberkampf and Roy have done much pioneering in the field of V&V, so the reader is in good/capable hands. The book covers some fundamental V&V concepts, then moves into code verification and software quality assurance (Part II) and solution verification (Part III). It then covers model validation (Part IV), and covers issues in implementation, planning, and management and use of V&V in these activities (Part V). Part V is perhaps the most unique part of the book, but the coverage in all parts of the book is thorough.This, along with Roache's "Verification and Validation in Computational Science and Engineering" (1998), proved to be an excellent survey of the field. (Much less helpful was the Salari and Knupp's "Verification of Computer Codes" (2002)). Coleman's "Experimentation, Validation, and Uncertainty Analysis for Engineers" (2009) has a more heavily experimental flavor, but is another great resource in this field.
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