Generation of fission yield covariance matrices and its application in uncertainty analysis of decay heat
Wendi Chen, Tao Ye, Hairui Guo, Jiahao Chen, Bo Yang, Yangjun Ying

TL;DR
This paper develops covariance matrices for fission yields using a GLS approach, improving decay heat uncertainty analysis by reducing propagated uncertainties from nuclear data libraries.
Contribution
It introduces a novel GLS-based method to evaluate fission yield covariances constrained by physical laws and data, enhancing decay heat uncertainty quantification.
Findings
Uncorrelated yield data contribute about 4% uncertainty at all times.
Generated covariance matrices significantly reduce decay heat uncertainty.
Uncertainty at 0.1s cooling time is about 10% for ENDF/B-VIII.0 and JEFF-3.3, and 5% for JENDL-5.
Abstract
The uncertainties and covariance matrices of fission yield are important in the uncertainty analysis of decay heat. At present, there are no covariance matrixes of fission yield given in the evaluated nuclear data library, although they have provided the uncertainties with good estimates. In this work, the generalized least squares (GLS) updating approach was adopted to evaluate the fission yield covariances with the constraints from basic physical conservation equation and chain yield data, using the nuclear data files from ENDF/B-VIII.0, JENDL-5 and JEFF-3.3. Based on these original and updated data, summation calculation was performed for fission pulse decay heat of thermal neutron-induced fission of U. The uncertainties of decay heat were obtained through generalized perturbation theory, including the uncertainties propagated from fission yield, decay energy, decay constant…
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