Control of modeling error in calibration and validation processes for predictive stochastic models
KAUST Grant NumberUS00003
Permanent link to this recordhttp://hdl.handle.net/10754/597856
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AbstractThe idea of adaptive control of modeling error is expanded to include ideas of statistical calibration, validation, and uncertainty quantification. © 2010 John Wiley & Sons, Ltd.
CitationOden JT, Prudhomme S (2010) Control of modeling error in calibration and validation processes for predictive stochastic models. Int J Numer Meth Engng 87: 262–272. Available: http://dx.doi.org/10.1002/nme.3038.
SponsorsWe have benefitted from numerous discussions with colleagues over recent years on the subjects of verification, validation, statistical inverse analysis, and uncertainty quantification. In particular, we thank Ivo Babuska, Omar Ghattas, Raul Tempone, Ernesto Prudencio, and Robert Moser for helping us develop our current but still developing understanding of those subjects. We also gratefully acknowledge support of our work under the DOE Multiscale Mathematics Contract DE-FG02-05ER25701, the DOE PSAAP Contract DE-FC52-08NA28615, and the KAUST Contract US00003, all with ICES.