The effect of dominance ratio on the statistical convergence of sensitivity in Monte Carlo codes
Sensitivity computation in Monte Carlo-based codes is widely used and has been enhanced significantly. Although sensitivity converges in most reactor configurations, it encounters difficulties in large core designs. We suspect that this issue might be linked to the dominance ratio. To test this hypo...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
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| Series: | EPJ Web of Conferences |
| Online Access: | https://www.epj-conferences.org/articles/epjconf/pdf/2024/12/epjconf_snamc2024_04006.pdf |
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| Summary: | Sensitivity computation in Monte Carlo-based codes is widely used and has been enhanced significantly. Although sensitivity converges in most reactor configurations, it encounters difficulties in large core designs. We suspect that this issue might be linked to the dominance ratio. To test this hypothesis, we develop a simple benchmark to validate whether statistical convergence of sensitivity depends on dominance ratio, and if it may be linked to other factors, such as neutron energy spectrum. The benchmark’s simplicity enables us to calculate the dominance ratio analytically and use eigenmodes decomposition to compute sensitivity to total fission neutron yields, substantially lowering computational costs. This method results in a good match when compared to the direct method which serves as a reference. We clearly see regular sensitivity convergence speed behavior linking it with the number of latent generations and the dominance ratio. Therefore, we establish a formula to recommend the number of latent generations required for sensitivity to converge, thus significantly saving computational resources. |
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| ISSN: | 2100-014X |