Covariance evaluation of neutron cross sections in CENDL

¹ China Nuclear Data Centre, China Institute of Atomic Energy, 102413 P.O.Box, Beijing, China
² China Institute of Atomic Energy, 102413 P.O.Box, Beijing, China
³ Graduate School of China National Nuclear Corporation, China Industry College, 102413 P.O.Box, Beijing, China

^* Corresponding author: xuruirui@ciae.ac.cn

Published online: 29 March 2023

Abstract

The covariance evaluation for neutron cross sections in CENDL is briefly introduced in this work. The methodology for evaluation contains the nuclear reaction theoretical model-dependent approach and the non-model dependent one according to the amount of experimental data. Both approaches are based on the Generalized Least-Squares (GLSQ) method. To obtain more reliable uncertainties from experimental measurement, the analysis of the sources of experimental uncertainties (ASEU) is used rigorously in the evaluation. Moreover, machine learning (ML) methods which can deal with the data mining with a more automatic way are employed to evaluate the cross sections in a large-scale nuclear mass region to compensate the uncertainties on some nuclides and reactions, lack of experimental data for, e.g., unstable nuclei and fission products. The covariance files for 70 fission product nuclei are obtained through the model-dependent method in CENDL-3.2, and the covariances for U and Pu isotopes have also been finished with high fidelity, which will be released as part of the next CENDL.