Abstract This paper presents a novel approach to the evaluation of nuclear data (ND), combining experimental data for thermal cross sections with resonance parameters and nuclear reaction modeling. The method involves sampling of various uncertain parameters, in particular uncertain components in experimental setups, and provides extensive covariance information, including consistent cross-channel correlations over the whole energy spectrum. The method is developed for, and applied to, 59Ni, but may be used as a whole, or in part, for other nuclides. 59Ni is particularly interesting since a substantial amount of 59Ni is produced in thermal nuclear reactors by neutron capture in 58Ni and since it has a non-threshold (n,α) cross section. Therefore, 59Ni gives a very important contribution to the helium production in stainless steel in a thermal reactor. However, current evaluated ND libraries contain old information for 59Ni, without any uncertainty information. The work includes a study of thermal cross section experiments and a novel combination of this experimental information, giving the full multivariate distribution of the thermal cross sections. In particular, the thermal (n,α) cross section is found to be 12.7 ± . 7 b . This is consistent with, but yet different from, current established values. Further, the distribution of thermal cross sections is combined with reported resonance parameters, and with TENDL-2015 data, to provide full random ENDF files; all of this is done in a novel way, keeping uncertainties and correlations in mind. The random files are also condensed into one single ENDF file with covariance information, which is now part of a beta version of JEFF 3.3. Finally, the random ENDF files have been processed and used in an MCNP model to study the helium production in stainless steel. The increase in the (n,α) rate due to 59Ni compared to fresh stainless steel is found to be a factor of 5.2 at a certain time in the reactor vessel, with a relative uncertainty due to the 59Ni data of 5.4%.

中文翻译：

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不确定性驱动的核数据评估，包括应用于 59 Ni 的热 (n, α )

摘要 本文提出了一种评估核数据 (ND) 的新方法，将热截面的实验数据与共振参数和核反应建模相结合。该方法涉及对各种不确定参数（尤其是实验装置中的不确定成分）进行采样，并提供广泛的协方差信息，包括整个能谱上的一致跨通道相关性。该方法是为 59Ni 开发和应用的，但也可作为整体或部分用于其他核素。59Ni 特别有趣，因为在热核反应堆中通过 58Ni 中的中子俘获产生了大量 59Ni，并且它具有非阈值 (n,α) 截面。所以，59Ni 对热反应器中不锈钢中的氦气生产做出了非常重要的贡献。然而，当前评估的 ND 库包含 59Ni 的旧信息，没有任何不确定性信息。这项工作包括对热截面实验的研究和这种实验信息的新组合，给出了热截面的完整多元分布。特别是，发现热 (n,α) 截面为 12.7 ± 。7 乙。这与当前的既定价值观一致，但又有所不同。此外，热截面的分布与报告的共振参数和 TENDL-2015 数据相结合，以提供完全随机的 ENDF 文件；所有这一切都是以一种新颖的方式完成的，牢记不确定性和相关性。随机文件也被压缩成一个带有协方差信息的 ENDF 文件，它现在是 JEFF 3.3 测试版的一部分。最后，随机 ENDF 文件已被处理并用于 MCNP 模型，以研究不锈钢中的氦气生成。与新鲜不锈钢相比，59Ni 导致的 (n,α) 速率增加在反应器容器中的某个时间是 5.2 倍，由于 59Ni 数据的相对不确定性为 5.4%。