Bayesian Data Fusion of Imperfect Fission Yields for Augmented Evaluations

We demonstrate that Bayesian machine learning can be used to treat the vast amount of experimental fission data which are noisy, incomplete, discrepant, and correlated. As an example, the two-dimensional cumulative fission yields (CFY) of neutron-induced fission of \(^{238}\)U are evaluated with ene...

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Bibliographic Details
Published in:arXiv.org 2021-11
Main Authors: Wang, Z A, Pei, J C, Chen, Y J, Qiao, C Y, Xu, F R, Ge, Z G, Shu, N C
Format: Article
Language:English
Subjects:
Bayesian analysis
Data integration
Machine learning
Military strategy
Online Access:Get full text
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Summary:We demonstrate that Bayesian machine learning can be used to treat the vast amount of experimental fission data which are noisy, incomplete, discrepant, and correlated. As an example, the two-dimensional cumulative fission yields (CFY) of neutron-induced fission of \(^{238}\)U are evaluated with energy dependencies and uncertainty qualifications. For independent fission yields (IFY) with very few experimental data, the heterogeneous data fusion of CFY and IFY is employed to interpolate the energy dependence. This work shows that Bayesian data fusion can facilitate the further utilization of imperfect raw nuclear data.
ISSN:2331-8422
DOI:10.48550/arxiv.2111.14102