Individual Adjustment of Independent Cross-Section Set Based on Bayesian Theory

Abstract

We developed a cross-section adjustment method based on Bayesian theory for adjusting the independent cross-section set that is given by dividing the cross-section set. While all cross sections have to be adjusted in the conventional cross-section adjustment method, the independent cross-section set can be individually adjusted in the developed method. In addition, the covariance of cross sections that are assumed to be independent of each other is not adjusted in the developed method. The adjusted cross sections and the covariance are the same in both methods. The cross-section adjustment was performed using the criticality of the light water–moderated uranium benchmark. The result shows that the uncertainty of the multiplication factor is reduced from 0.005 to 0.007 Δk/k to 0.003 to 0.005 Δk/k by the developed method. The reduction is smaller than that by the conventional method since the developed method does not adjust the covariance of cross sections that are assumed to be independent of each other.

Keywords:

• Cross-section adjustment
• data assimilation
• Bayesian theory

Acknowledgments

The authors are deeply grateful to K. Yokoyama of the Japan Atomic Energy Agency for providing constructive comments.