New paradigm for nuclear data evaluation

Abstract

A new paradigm for nuclear reaction data evaluations is proposed to produce adjusted libraries that take into account integral experiments on the same footing as the differential ones. These evaluations will provide comprehensive covariance matrices including cross-correlations among different materials/reactions that are critical for realistic propagation of data uncertainties to integral quantities. The new approach should also reduce error compensation issues and facilitate updating of the library to account for new or corrected experiments and advances in reaction modeling.

Artificial Intelligence for Multiphysics Nuclear Design Optimization with Additive Manufacturing

“…A summary of the current status of using AI/ML for existing nuclear power plants related to nuclear reactor heath, monitoring, and radiation detection is provided by Gomez-Fernandex et al [12]. AI techniques are also being applied to numerous nuclear data problems including nuclear data uncertainty [13], identification of problems in nuclear data [14,15], and aiding in performing nuclear data evaluations [16][17][18]. AI/ML techniques have also gain popularity for nuclear material security applications, the current status of which is summarized by Alamaniotis and Heifetz [19].…”