Verification, Validation, and Uncertainty Quantification in Scientific Computing
| AUTHOR | Roy, Christopher J.; Oberkampf, William L. |
| PUBLISHER | Cambridge University Press (04/03/2025) |
| PRODUCT TYPE | Hardcover (Hardcover) |
Description
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.
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Product Format
Product Details
ISBN-13:
9781316516133
ISBN-10:
131651613X
Binding:
Hardback or Cased Book (Sewn)
Content Language:
English
Edition Number:
0002
More Product Details
Page Count:
729
Carton Quantity:
5
Product Dimensions:
7.00 x 1.56 x 10.00 inches
Weight:
3.24 pound(s)
Feature Codes:
Bibliography,
Index
Country of Origin:
US
Subject Information
BISAC Categories
Computers | General
Computers | Microscopes & Microscopy
Dewey Decimal:
502.85
Library of Congress Control Number:
2024023119
Descriptions, Reviews, Etc.
publisher marketing
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.
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List Price $140.00
Your Price
$138.60
