Hybrid Weight Window Techniques for Time-Dependent Monte Carlo Neutronics
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909721265438720 |
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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 |