A Monte Carlo importance-splitting analytic benchmark - 25539

Conference · Wed Aug 15 04:00:00 EDT 2018

OSTI ID:23055109

Kulesza, Joel A. ^[1]; Solomon, Jr., Clell J. ^[2]; Kiedrowski, Brian C. ^[1]

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1. Department of Nuclear Engineeringand Radiological Sciences, University of Michigan, 2355 Bonisteel Blvd., Ann Arbor, MI, 48109 (United States)
2. Monte Carlo Methods, Codes, and Applications Group, Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM, 87545 (United States)

This paper describes a procedure to create analytic benchmarks for Monte Carlo variance reduction techniques that can be used to predict and/or verify the technique's mean and variance. The process uses the solutions of the first and second history-score moment equations (HSMEs) to obtain the analytic solution for the Monte Carlo mean and variance. For this work, a simple demonstration of the procedure examines the behavior of uncollided particles subject to importance splitting. In addition, a forward approach is given for calculating the same parameters. Finally, the analytic solutions are compared to both Monte Carlo calculations that directly compute the mean and variance and deterministic calculations that solve the HSMEs. All analytic and numeric results agree within the associated Monte Carlo uncertainties. (authors)

• Research Organization: American Nuclear Society - ANS, 555 North Kensington Avenue, La Grange Park, IL 60526 (United States)
• OSTI ID: 23055109
• Country of Publication: United States
• Language: English

Related Subjects

61 RADIATION PROTECTION AND DOSIMETRY
73 NUCLEAR PHYSICS AND RADIATION PHYSICS
97 MATHEMATICS AND COMPUTING
ANALYTICAL SOLUTION
BENCHMARKS
COMPUTERIZED SIMULATION
MONTE CARLO METHOD
NUCLEAR PHYSICS