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Conditional Point Sampling: A Monte Carlo Method for Radiation Transport in Stochastic Media.

Journal Article · · Journal of Quantitative Spectroscopy and Radiative Transfer
 [1];  [2]
  1. Univ. of Michigan, Ann Arbor, MI (United States). Dept. of Nuclear Engineering and Radiological Sciences; Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Current methods for stochastic media transport are either computationally expensive or, by nature, approximate. Moreover, none of the well-developed, benchmarked approximate methods can compute the variance caused by the stochastic mixing, a quantity especially important to safety calculations. Therefore, we derive and apply a new conditional probability function (CPF) for use in the recently developed stochastic media transport algorithm Conditional Point Sampling (CoPS), which 1) leverages the full intra-particle memory of CoPS to yield errorless computation of stochastic media outputs in 1D, binary, Markovian-mixed media, and 2) leverages the full inter-particle memory of CoPS and the recently developed Embedded Variance Deconvolution method to yield computation of the variance in transport outputs caused by stochastic material mixing. Numerical results demonstrate errorless stochastic media transport as compared to reference benchmark solutions with the new CPF for this class of stochastic mixing as well as the ability to compute the variance caused by the stochastic mixing via CoPS. Using previously derived, non-errorless CPFs, CoPS is further found to be more accurate than the atomic mix approximation, Chord Length Sampling (CLS), and most of memory-enhanced versions of CLS surveyed. In addition, we study the compounding behavior of CPF error as a function of cohort size (where a cohort is a group of histories that share intra-particle memory) and recommend that small cohorts be used when computing the variance in transport outputs caused by stochastic mixing.

Research Organization:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA); USDOE Office of Nuclear Energy (NE), Nuclear Energy University Program (NEUP)
Grant/Contract Number:
AC04-94AL85000; NA0003525
OSTI ID:
1810758
Alternate ID(s):
OSTI ID: 1815189
OSTI ID: 1822229
OSTI ID: 23194204
Report Number(s):
SAND--2020-9207J; 690321
Journal Information:
Journal of Quantitative Spectroscopy and Radiative Transfer, Journal Name: Journal of Quantitative Spectroscopy and Radiative Transfer Vol. 272; ISSN 0022-4073
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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