A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing

An overview of a comprehensive framework is given for estimating the predictive uncertainty of scientific computing applications. The framework is comprehensive in the sense that it treats both types of uncertainty (aleatory and epistemic), incorporates uncertainty due to the mathematical form of th...

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Bibliographic Details
Published in:	Computer methods in applied mechanics and engineering Vol. 200; no. 25; pp. 2131 - 2144
Main Authors:	Roy, Christopher J., Oberkampf, William L.
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier B.V 15.06.2011 Elsevier
Subjects:	Applied sciences Compressible flows; shock and detonation phenomena Computation Computational methods in fluid dynamics Computational simulation Computer science; control theory; systems Computer simulation Discretization Errors Estimating Exact sciences and technology Fluid dynamics Fundamental areas of phenomenology (including applications) Mathematical models Modeling Physics Propagation Simulation Software Supersonic and hypersonic flows Uncertainty Uncertainty quantification Validation Verification Validation Uncertainty quantification Verification Modeling Computational simulation Uncertainty Error estimation Quantization Probability distribution Numerical approximation Interval analysis Uncertain system Model matching Discretization Incomplete information Random variable Experimental data Probabilistic approach Computational fluid dynamics Decision making Wind tunnel test Conversion Extrapolation Scientific computation Statistical model Approximation error Artificial intelligence
ISSN:	0045-7825, 1879-2138
Online Access:	Get full text
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