Cross-section adjustment method based on Bayesian theory for specific cross-section set

A cross-section adjustment method based on Bayesian theory was derived for adjusting the specific cross-section set. The present method gives the 'a posteriori' distribution of the specific cross-section and does not require the adjustment of the other cross-sections. In the derivation, the experimental error, calculation error, and cross-section error are assumed to distribute normally and to be independent of each other. The adjusted specific cross-sections and the covariance between them are the same as those obtained by the conventional cross-section adjustment method. In addition, the adjustment of covariance between the adjusted cross-section and the other cross-section is not necessarily required in the derivation. For introducing these features of the present method, the specific cross-sections were adjusted by using the criticality of the light-water moderated uranium benchmark. The result shows that the uncertainty of the multiplication factor is reduced by the present method, and the reduction is drastically smaller than that by the conventional method.

Automated summary

A cross-section adjustment method based on Bayesian theory is derived for adjusting specific cross-sections, which reduces the uncertainty of the multiplication factor significantly compared to conventional methods.