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Title: A Comparison of Monte Carlo Particle Transport Algorithms for an Interior Source Binary Stochastic Medium Benchmark Suite

Abstract

Particle transport through binary stochastic mixtures has received considerable research attention in the last two decades. Zimmerman and Adams proposed a Monte Carlo algorithm (Algorithm A) that solves the Levermore-Pomraning equations and another Monte Carlo algorithm (Algorithm B) that should be more accurate as a result of improved local material realization modeling. Zimmerman and Adams numerically confirmed these aspects of the Monte Carlo algorithms by comparing the reflection and transmission values computed using these algorithms to a standard suite of planar geometry binary stochastic mixture benchmark transport solutions. The benchmark transport problems are driven by an isotropic angular flux incident on one boundary of a binary Markovian statistical planar geometry medium. In a recent paper, we extended the benchmark comparisons of these Monte Carlo algorithms to include the scalar flux distributions produced. This comparison is important, because as demonstrated, an approximate model that gives accurate reflection and transmission probabilities can produce unphysical scalar flux distributions. Brantley and Palmer recently investigated the accuracy of the Levermore-Pomraning model using a new interior source binary stochastic medium benchmark problem suite. In this paper, we further investigate the accuracy of the Monte Carlo algorithms proposed by Zimmerman and Adams by comparing to the benchmarkmore » results from the interior source binary stochastic medium benchmark suite, including scalar flux distributions. Because the interior source scalar flux distributions are of an inherently different character than the distributions obtained for the incident angular flux benchmark problems, the present benchmark comparison extends the domain of problems for which the accuracy of these Monte Carlo algorithms has been investigated.« less

Authors:
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
970148
Report Number(s):
LLNL-CONF-414422
TRN: US201003%%389
DOE Contract Number:  
W-7405-ENG-48
Resource Type:
Conference
Resource Relation:
Conference: Presented at: American Nuclear Society: 2009 Winter Meeting, Washington, DC, United States, Nov 15 - Nov 19, 2009
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUMM MECHANICS, GENERAL PHYSICS; ACCURACY; ALGORITHMS; BENCHMARKS; GEOMETRY; MIXTURES; REFLECTION; SCALARS; SIMULATION; TRANSPORT

Citation Formats

Brantley, P S. A Comparison of Monte Carlo Particle Transport Algorithms for an Interior Source Binary Stochastic Medium Benchmark Suite. United States: N. p., 2009. Web.
Brantley, P S. A Comparison of Monte Carlo Particle Transport Algorithms for an Interior Source Binary Stochastic Medium Benchmark Suite. United States.
Brantley, P S. 2009. "A Comparison of Monte Carlo Particle Transport Algorithms for an Interior Source Binary Stochastic Medium Benchmark Suite". United States. https://www.osti.gov/servlets/purl/970148.
@article{osti_970148,
title = {A Comparison of Monte Carlo Particle Transport Algorithms for an Interior Source Binary Stochastic Medium Benchmark Suite},
author = {Brantley, P S},
abstractNote = {Particle transport through binary stochastic mixtures has received considerable research attention in the last two decades. Zimmerman and Adams proposed a Monte Carlo algorithm (Algorithm A) that solves the Levermore-Pomraning equations and another Monte Carlo algorithm (Algorithm B) that should be more accurate as a result of improved local material realization modeling. Zimmerman and Adams numerically confirmed these aspects of the Monte Carlo algorithms by comparing the reflection and transmission values computed using these algorithms to a standard suite of planar geometry binary stochastic mixture benchmark transport solutions. The benchmark transport problems are driven by an isotropic angular flux incident on one boundary of a binary Markovian statistical planar geometry medium. In a recent paper, we extended the benchmark comparisons of these Monte Carlo algorithms to include the scalar flux distributions produced. This comparison is important, because as demonstrated, an approximate model that gives accurate reflection and transmission probabilities can produce unphysical scalar flux distributions. Brantley and Palmer recently investigated the accuracy of the Levermore-Pomraning model using a new interior source binary stochastic medium benchmark problem suite. In this paper, we further investigate the accuracy of the Monte Carlo algorithms proposed by Zimmerman and Adams by comparing to the benchmark results from the interior source binary stochastic medium benchmark suite, including scalar flux distributions. Because the interior source scalar flux distributions are of an inherently different character than the distributions obtained for the incident angular flux benchmark problems, the present benchmark comparison extends the domain of problems for which the accuracy of these Monte Carlo algorithms has been investigated.},
doi = {},
url = {https://www.osti.gov/biblio/970148}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Jun 30 00:00:00 EDT 2009},
month = {Tue Jun 30 00:00:00 EDT 2009}
}

Conference:
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