Development of the unified cross-section set ADJ2017R

Yokoyama, Kenji; Maruyama, Shuhei; Taninaka, Hiroshi; Oki, Shigeo

JAEA-Data/Code 2021-019, 115 Pages, 2022/03

JAEA-Data-Code-2021-019.pdf:6.21MB
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In JAEA, several versions of unified cross-section set for fast reactors have been developed so far; we have developed a new unified cross-section set ADJ2017R, which is an improved version of the unified cross-section setADJ2017 for fast reactors. The unified cross-section set is used for reflecting information of C/E values (analysis / experiment values) obtained by integral experiment analyses in reactor core design via the cross-section adjustment methodology; the values are stored in the standard database for FBR core design. In the methodology, the cross-section set is adjusted by integrating the information such as uncertainty (covariance) of nuclear data, uncertainty of integral experiment / analysis, sensitivity of integral experiment with respect to nuclear data. ADJ2017R basically has the same performance as ADJ2017, but we conducted an additional investigation on ADJ2017 and revised the following two points. The first is to unify the evaluation method of the correlation coefficient of uncertainty caused by experiments (hereinafter referred to as the experimental correlation coefficient). Because it was found that the common uncertainty used in the evaluation of the experimental correlation coefficient was evaluated by two different methods, the experimental correlation coefficients were revised for all experimental data, and the evaluation method was unified. The second is the review of the integral experiment data used for the cross-section adjustment calculation. It was found that one of the experimental values of composition ratio after irradiation of the Am-243 sample has a problem in uncertainty evaluation because its experimental uncertainty is extremely small compared to the others. The cross-section adjustment calculation was, therefore, redone by excluding the experimental value. In the creation of ADJ2017, a total of 719 data sets were analyzed and evaluated, and eventually adopted 620 integral experimental data sets. In contrast, a total of 61