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Verification and Validation in Scientific Computing

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Cambridge University Press
  

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Scientific computing is finding more uses in engineering and research. This book is about model verification. The questions are how well a simulation matches an actual activity, or how to get experimental data for a mathematics of micro- and nano-scales, and whether reviewers will find the results credible. Verification activities are shown for software, solution, model and management. Predictive capability is summarized in several steps for identifying sources of uncertainty, characterizing them, estimating error and uncertainty in the system response quantities (SRQs), updating the model, and analyzing sensitivities. There are five parts for sixteen chapters, and an appendix. 

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