Hybrid Weight Window Techniques for Time-Dependent Monte Carlo Neutronics
Abstract
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.
Cite
@article{arxiv.2501.06144,
title = {Hybrid Weight Window Techniques for Time-Dependent Monte Carlo Neutronics},
author = {Caleb S. Shaw and Dmitriy Y. Anistratov},
journal= {arXiv preprint arXiv:2501.06144},
year = {2025}
}