Covariance Evaluation for Nuclear Data of Interest to the Reactivity Loss Estimation of the Jules Horowitz Material Testing Reactor

Abstract

In modern nuclear technology, integral reactor parameter uncertainty evaluation plays a crucial role for both economic and safety purposes. Target accuracies for operating and future nuclear facilities can be obtained only if the available simulation tools, such that computational platforms and nuclear data, are precise enough to produce reduced biases and uncertainties on target reactor parameters. The quality of any engineering parameter uncertainty quantification analysis strongly depends on the reliability related to the covariance information contained in evaluated libraries. To propagate properly nuclear data uncertainty on nuclear reactor parameters, science-based variance-covariance matrices are then indispensable. The present work is devoted to nuclear data covariance matrices generation for reactivity loss uncertainty estimations regarding the Jules Horowitz Reactor (JHR), a material testing facility under construction at CEA-Cadarache (France). During depletion, in fact, various fission products appear and the related nuclear data are often barely known. In particular, the strenuous and worldwide recognized problem of generating fission product yields covariances has been mainly considered. Present nuclear data libraries such as JEFF or ENDF/B do not have complete uncertainty information on fission yields, which is limited to only variances. The main goal of this work is to generate science-based and physically consistent fission yields covariances to be associated to the existing European library JEFF-3.1.1. Variance-covariance matrices have been evaluated using CONRAD (COde for Nuclear Reaction Analysis and Data assimilation, developed at CEA-Cadarache) for the most significant fissioning systems.