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A Bayesian calibration approach to the thermal problem

Higdon, Dave, Nakhleh, Charles, Gattiker, James and Williams, Brian (2008) A Bayesian calibration approach to the thermal problem Computer Methods in Applied Mechanics and Engineering, 197, (29-32), pp. 2431-2441. (doi:10.1016/j.cma.2007.05.031).

Record type: Article


Many of the problems we work with at Los Alamos National Laboratory are similar to the thermal problem described in the tasking document. In this paper, we describe the tools and methods we have developed that utilize experimental data and detailed physics simulations for uncertainty quantification, and apply them to the thermal challenge problem. We then go on to address the regulatory question posed in the problem description. This statistical framework used here is largely based on the approach of Kennedy and O’Hagan [Kennedy, M., O’Hagan, A., Bayesian calibration of computer models (with discussion), J. Royal Stat. Soc. B 68 (2001) 425–464], but has been extended to deal with functional output of the simulation model.

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Published date: 1 May 2008
Keywords: Computer experiments, Predictability, Certification, Uncertainty quantification, Gaussian process, Predictive science, Functional data analysis, Verification and validation


Local EPrints ID: 64047
ISSN: 0045-7825
PURE UUID: 4da0c37d-ee2c-45be-bd64-17f81c004f9c

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Date deposited: 26 Nov 2008
Last modified: 17 Jul 2017 14:14

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Author: Dave Higdon
Author: Charles Nakhleh
Author: James Gattiker
Author: Brian Williams

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