Sensitivity Analysis and Cross Sections Data Adjustment for Multigroup Transport and Diffusion

Abstract

Uncertainties in basic nuclear data and other quantities involved in the characterization of an experiment affect the accuracy of the results when the respective experiment is modelled. The impact of these uncertainties on computed responses can be assessed by combining the sensitivities of these responses to the input parameters with data uncertainties and covariances. Furthermore, best estimates of both the input parameters and recomputed responses, with reduced uncertainties, can be obtained by using data assimilation and adjustment procedures. This paper reports the results of using the data adjustment methodology in conjunction with the well-known Godiva experiment and a partial set of uncertainties from the ZZ-COV-15 library for U-235 and U-238, together with sensitivities computed with APOLLO transport code by the Adjoint Sensitivity Analysis Procedure, to obtain best-estimate values for the k eigenvalue of the system, with reduced uncertainties. In parallel, sensitivities were also computed using COBAYA diffusion code, compared with those produced by APOLLO, and then employed in the adjustment formalism to obtain the adjusted k eigenvalue and its corresponding reduced uncertainty