Hybrid Weight Window Techniques for Time-Dependent Monte Carlo Neutronics

Fuente: arXiv
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Main Authors: Shaw, Caleb S., Anistratov, Dmitriy Y.
Format: Preprint
Published: 2025
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author Shaw, Caleb S.
Anistratov, Dmitriy Y.
author_facet Shaw, Caleb S.
Anistratov, Dmitriy Y.
contents Efficient variance reduction of Monte Carlo simulations is desirable to avoid wasting computational resources. This paper presents an automated weight window algorithm for solving time-dependent particle transport problems. The weight window centers are defined by a hybrid forward solution of the discretized low-order second moment (LOSM) problem. The second-moment (SM) functionals defining the closure for the LOSM equations are computed by Monte Carlo solution. A filtering algorithm is applied to reduce noise in the SM functionals. The LOSM equations are discretized with first- and second-order time integration methods. We present numerical results of the AZURV1 benchmark. The hybrid weight windows lead to a uniform distribution of Monte Carlo particles in space. This causes a more accurate resolution of wave fronts and regions with relatively low flux.
format Preprint
id arxiv_https___arxiv_org_abs_2501_06144
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Hybrid Weight Window Techniques for Time-Dependent Monte Carlo Neutronics
Shaw, Caleb S.
Anistratov, Dmitriy Y.
Numerical Analysis
Data Analysis, Statistics and Probability
Efficient variance reduction of Monte Carlo simulations is desirable to avoid wasting computational resources. This paper presents an automated weight window algorithm for solving time-dependent particle transport problems. The weight window centers are defined by a hybrid forward solution of the discretized low-order second moment (LOSM) problem. The second-moment (SM) functionals defining the closure for the LOSM equations are computed by Monte Carlo solution. A filtering algorithm is applied to reduce noise in the SM functionals. The LOSM equations are discretized with first- and second-order time integration methods. We present numerical results of the AZURV1 benchmark. The hybrid weight windows lead to a uniform distribution of Monte Carlo particles in space. This causes a more accurate resolution of wave fronts and regions with relatively low flux.
title Hybrid Weight Window Techniques for Time-Dependent Monte Carlo Neutronics
topic Numerical Analysis
Data Analysis, Statistics and Probability
url https://arxiv.org/abs/2501.06144