Monte Carlo solution for uncertainty propagation in particle transport with a stochastic Galerkin method

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

OSTI ID:22212766

Franke, B. C. ^[1]; Prinja, A. K. ^[2]

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1. Sandia National Laboratories, Albuquerque, NM 87185 (United States)
2. Department of Chemical and Nuclear Engineering, University of New Mexico, Albuquerque, NM 87131 (United States)

The stochastic Galerkin method (SGM) is an intrusive technique for propagating data uncertainty in physical models. The method reduces the random model to a system of coupled deterministic equations for the moments of stochastic spectral expansions of result quantities. We investigate solving these equations using the Monte Carlo technique. We compare the efficiency with brute-force Monte Carlo evaluation of uncertainty, the non-intrusive stochastic collocation method (SCM), and an intrusive Monte Carlo implementation of the stochastic collocation method. We also describe the stability limitations of our SGM implementation. (authors)

• Research Organization: American Nuclear Society, 555 North Kensington Avenue, La Grange Park, IL 60526 (United States)
• OSTI ID: 22212766
• Resource Relation: Conference: M and C 2013: 2013 International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, Sun Valley, ID (United States), 5-9 May 2013; Other Information: Country of input: France; 9 refs.; Related Information: In: Proceedings of the 2013 International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering - M and C 2013| 3016 p.
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICAL METHODS AND COMPUTING
COMPARATIVE EVALUATIONS
EFFICIENCY
EQUATIONS
MATHEMATICAL SOLUTIONS
MONTE CARLO METHOD
PROBABILITY
RANDOMNESS
STABILITY
STOCHASTIC PROCESSES