Uncertainties in Predictions of Material Performance Using Experimental Data That Is Only Distantly Related to the System of Interest

Abstract : There is a need for predictive material “aging” models in the nuclear energy industry, where applications include life extension of existing reactors, the development of high burnup fuels, and dry cask storage of used nuclear fuel. These problems require extrapolating from the validation domain, where there is available experimental data, to the application domain, where there is little or no experimental data. The need for predictive material aging models will drive the need for associated assessments of the uncertainties in the predictions. Methods to quantify uncertainties in model predictions, using experimental data that is only distantly related to the application domain, are discussed in this paper.
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Andrew M. Dienstfrey; Ronald F. Boisvert. 10th Working Conference on Uncertainty Quantification in Scientific Computing (WoCoUQ), Aug 2011, Boulder, CO, United States. Springer, IFIP Advances in Information and Communication Technology, AICT-377, pp.294-311, 2012, Uncertainty Quantification in Scientific Computing. 〈10.1007/978-3-642-32677-6_19〉
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Wayne King, Athanasios Arsenlis, Charles Tong, William Oberkampf. Uncertainties in Predictions of Material Performance Using Experimental Data That Is Only Distantly Related to the System of Interest. Andrew M. Dienstfrey; Ronald F. Boisvert. 10th Working Conference on Uncertainty Quantification in Scientific Computing (WoCoUQ), Aug 2011, Boulder, CO, United States. Springer, IFIP Advances in Information and Communication Technology, AICT-377, pp.294-311, 2012, Uncertainty Quantification in Scientific Computing. 〈10.1007/978-3-642-32677-6_19〉. 〈hal-01518673〉

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