A Human-Equipment-Society (HES) framework for classifying and analyzing operational events in Chinese nuclear power plants

An effective analysis of operational events is crucial to preventing major accidents and improving safety levels in nuclear power. However, global event reporting currently suffers from inconsistent standards, vague information descriptions, and superficial root cause analysis. These shortcomings hinder the closure of the feedback loop of the experience and constrain systematic improvements in nuclear power safety management. Based on accident causation theory, the Human-Equipment Society (HES) cause classification and analysis framework was proposed for nuclear power operational events. The framework aims to achieve systematic and standardized attribution of event causes. A total of 532 operational events published by the Chinese National Nuclear Safety Administration between 2006 and 2024 were compiled and analyzed using the HES framework. At the triggering factor level, the results show that human factors account for 50.38% and equipment factors account for 46.62% of the triggering events, while society factors account for 3.01%. At the root cause level, the results show that equipment failure (35.71%), organizational failures (26.32%), and individual failure (19.17%) are the main root causes. It can be found that root causes related to human error account for 57.52% (including coupling failure) and those related to equipment failure account for 54.51% (including coupling failure). The average number of events per unit of operation has shown a downward trend since 2016. Differences in the distribution of event triggers in different nuclear power plants highlight the need for targeted safety management. The standardized analysis framework developed in this study can provide data-driven decision support for nuclear regulatory agencies and operators, and facilitate a change in experience feedback from case-specific handling to systematic prevention. In addition, it promotes the intelligent and refined development of nuclear power safety management.

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Publication Details

Journal
Progress in Nuclear Energy
Published
2026-09-11
DOI
https://doi.org/10.1016/j.pnucene.2026.106598
Primary Topic
Risk and Safety Analysis
Type
article
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article

A Human-Equipment-Society (HES) framework for classifying and analyzing operational events in Chinese nuclear power plants

Jianqiang Shan, Tao Zhang, Shengzhi Liu
Progress in Nuclear Energy
Risk and Safety Analysis
article

A Human-Equipment-Society (HES) framework for classifying and analyzing operational events in Chinese nuclear power plants

Jianqiang Shan, Tao Zhang, Shengzhi Liu
article en

Abstract

An effective analysis of operational events is crucial to preventing major accidents and improving safety levels in nuclear power. However, global event reporting currently suffers from inconsistent standards, vague information descriptions, and superficial root cause analysis. These shortcomings hinder the closure of the feedback loop of the experience and constrain systematic improvements in nuclear power safety management. Based on accident causation theory, the Human-Equipment Society (HES) cause classification and analysis framework was proposed for nuclear power operational events. The framework aims to achieve systematic and standardized attribution of event causes. A total of 532 operational events published by the Chinese National Nuclear Safety Administration between 2006 and 2024 were compiled and analyzed using the HES framework. At the triggering factor level, the results show that human factors account for 50.38% and equipment factors account for 46.62% of the triggering events, while society factors account for 3.01%. At the root cause level, the results show that equipment failure (35.71%), organizational failures (26.32%), and individual failure (19.17%) are the main root causes. It can be found that root causes related to human error account for 57.52% (including coupling failure) and those related to equipment failure account for 54.51% (including coupling failure). The average number of events per unit of operation has shown a downward trend since 2016. Differences in the distribution of event triggers in different nuclear power plants highlight the need for targeted safety management. The standardized analysis framework developed in this study can provide data-driven decision support for nuclear regulatory agencies and operators, and facilitate a change in experience feedback from case-specific handling to systematic prevention. In addition, it promotes the intelligent and refined development of nuclear power safety management.

Progress in Nuclear EnergyVol. 202
China General Nuclear Power Corporation (China) (CN), Xi'an Jiaotong University (CN)
Openalex Percentile: Top 8%
Risk and Safety Analysis
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