Physics-based dimension reduction in uncertainty quantification for radiative transfer

Conference · Mon Jul 01 04:00:00 EDT 2013

OSTI ID:22212864

Hetzler, A. C.; Adams, M. L.; Stripling, Iv, H. F.; Hawkins, W. D. ^[1]

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1. Department of Nuclear Engineering, Texas A and M University, 3133 TAMU, College Station, TX 77843-3133 (United States)

We present a physics-based methodology for quantifying the uncertainty in a given quantity of interest (QOI) that is contributed by uncertainties in opacities in radiation transport problems. Typically, opacities are tabulated as a function of density, temperature, and photon energy group. The size of this table makes a study of uncertainties at this level challenging because of the well-known 'curse of dimensionality.' We address this by studying uncertain parameters in the underlying physical model that generates the opacity tables. At this level, there are fewer uncertain parameters but still too many to analyze directly through computationally expensive radiation transport simulations. In order to explore this large uncertain parameter space, we develop two simplified radiation transport problems that are much less computationally demanding than the target problem of interest. An emulator is created for each QOI for each simplified problem using Bayesian Multivariate Adaptive Regression Splines (BMARS). This emulator is used to create a functional relationship between the QOIs and the uncertain parameters. Sensitivity analysis is performed using the emulator to determine which parameters contribute significantly to the uncertainty. This physics-based screening process reduces the dimension of the parameter space that is then studied via the computationally expensive radiation transport calculation to generate distributions of quantities of interest. Results of this research demonstrate that the QOIs for the target problem agree for varying screening criteria determined by the sensitivity analysis, and the QOIs agree well for varying Latin Hypercube Design (LHD) sample sizes for the uncertain space. (authors)

• Research Organization: American Nuclear Society, 555 North Kensington Avenue, La Grange Park, IL 60526 (United States)
• OSTI ID: 22212864
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
FUNCTIONS
MATHEMATICAL SPACE
MULTIVARIATE ANALYSIS
RADIANT HEAT TRANSFER
RADIATION TRANSPORT
SENSITIVITY ANALYSIS
SIMULATION