an:05287987
Zbl 1388.80005
Higdon, Dave; Nakhleh, Charles; Gattiker, James; Williams, Brian
A Bayesian calibration approach to the thermal problem
EN
Comput. Methods Appl. Mech. Eng. 197, No. 29-32, 2431-2441 (2008).
00219748
2008
j
80M25 80-05 62P35
computer experiments; predictability; certification; uncertainty quantification; Gaussian process; predictive science; functional data analysis; verification and validation
Summary: 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 \textit{M. C. Kennedy} and \textit{A. O'Hagan} [J. R. Stat. Soc., Ser. B, Stat. Methodol. 63, No. 3, 425--464 (2001; Zbl 1007.62021)], but has been extended to deal with functional output of the simulation model.
Zbl 1007.62021