Issue |
EPJ Web of Conf.
Volume 284, 2023
15th International Conference on Nuclear Data for Science and Technology (ND2022)
|
|
---|---|---|
Article Number | 14013 | |
Number of page(s) | 4 | |
Section | Nuclear Data Libraries, Processing, Adjustment, Consistency | |
DOI | https://doi.org/10.1051/epjconf/202328414013 | |
Published online | 26 May 2023 |
https://doi.org/10.1051/epjconf/202328414013
Statistical Uncertainty Quantification of Probability Tables for Unresolved Resonance Cross Sections
1 Japan Atomic Energy Agency, 2-4, Shirakata, Tokai-mura, Ibaraki, Japan
2 Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Japan
* Corresponding author: tada.kenichi@jaea.go.jp
Published online: 26 May 2023
The probability table method is an important method to treat the self-shielding effect in the unresolved resonance region. A probability table is generated by using many “ladders” that represent pseudo resonance structures. This study developed a quantification method of the statistical uncertainty of a probability table. The product of the probability table and average cross section in each probability bin was considered as the target of the statistical uncertainty of the probability table. The central limit theorem (CLT), bootstrap method, and jackknife method were adopted to calculate the statistical uncertainty. The statistical uncertainties calculated using these methods were compared with the reference results. The calculation results showed that the statistical uncertainties obtained by CLT were similar to those of the other methods. Because the CLT calculation time was faster than that of the other methods, CLT was deemed as the best method for calculating the statistical uncertainty of the probability table. The statistical uncertainty quantification of the probability table developed in this study was implemented in nuclear data processing code FRENDY version 2. FRENDY version 2 can generate a probability table using the tolerance of the statistical uncertainty of the probability table.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.