| Verification, Validation, and Uncertainty Quantification in Scientific Computing, 2nd Ed (Cambridge University Press) |
| Friday, 16 May 2025 | |||
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This book asks the question "Can you trust results from modeling and simulation?" and 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. William L. Oberkampf and Christopher J. Roy consider procedures and results from all aspects of verification and validation, integrated with modern methods in uncertainty quantification and stochastic simulation. <ASIN:131651613X > 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. Author: William L. Oberkampf and Christopher J. Roy
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