A Bayesian Network Approach to Predicting Severity Status in Nuclear Reactor Accidents with Resilience to Missing Data

A Bayesian Network Approach to Predicting Severity Status in Nuclear Reactor Accidents with Resilience to Missing Data

Nuclear energy is a cornerstone of the global energy mix, delivering reliable, low-carbon power essential for sustainable energy systems. However, the safety of nuclear reactors is critical to maintaining operational reliability and public trust, particularly during accidents like a Loss of Coolant...

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Bibliographic Details
Main Authors: Kaiyu Li, Ling Chen, Xinxin Cai, Cai Xu, Yuncheng Lu, Shengfeng Luo, Wenlin Wang, Lizhi Jiang, Guohua Wu
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Energies
Subjects:
nuclear energy safety
accident prediction
Bayesian networks
energy system reliability
missing-data resilience
Online Access:https://www.mdpi.com/1996-1073/18/11/2684
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