Collection of IDHEAS-based human error probability data for nuclear power plant commissioning through expert elicitation

Yin, Zijian; Li, Zhizhong; Liu, Zhaopeng; Yang, Dongfang; Zhang, Jinghong; Лонг, Линг; Zhang, Yijing; Gong, Boyang

doi:10.1016/j.anucene.2022.109544

Cited by 4 publications

(1 citation statement)

References 61 publications

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“…However, the ATHEANA method is for nuclear industries, time-consuming, and weak in quantification, so this study does not consider that method. With in-depth research on safety psychology, cognitive science, and system safety science, the newest generation of human reliability methods includes Phoenix and the Integrated Human Event Analysis System (IDHEAS) [22,23], which have been published and applied in areas such as the oil and gas industries and nuclear power plants [24,25]. The above-mentioned HRA methods are mostly designed for specific domains such as the oil and gas industry, the petrochemical industry, and the nuclear industry.…”

Section: Introductionmentioning

confidence: 99%

A Risk-Data-Based Human Reliability Analysis for Chemical Experiments with Hazardous Processes

Zhang

et al. 2023

Processes

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In recent years, chemical experiment accidents have frequently occurred, resulting in injuries and fatalities among researchers. It is crucial to address this issue to improve laboratory safety. Based on many publications, it is clear that human error makes a major contribution to many laboratory accidents which contain hazardous processes. However, there is limited research focusing on human error in laboratory safety, and there is also a lack of effective measures to assess Human Error Probability (HEP) for experimental process safety. Therefore, we propose an improved Cognitive Reliability and Error Analysis Method (CREAM) which is based on risk data to assess the HEP during hazardous processes in chemical experiments. The proposed method adjusts nine Common Performance Conditions (CPCs) in conventional CREAM to make them suitable to describe chemical experiments. Then, in contrast to the traditional approach, this study uses the definition of risk as the support to collect CPC data from the perspectives of possibility and severity, so as to improve the rationality of the data and decrease the subjectivity of expert judgment. Afterwards, the weight value of each CPC is calculated through Gray Relation Analysis (GRA) based on the collected risk data of each CPC. Meanwhile, the collected risk data are used to determine the fuzzy degrees of each CPC, the activated fuzzy If-Then rules, and the corresponding rule weights. Finally, the CPCs’ membership degrees, the CPCs’ weights, and If-Then rule weights are integrated together to acquire the HEP by defuzzification. In short, the proposed method changes the CPCs to ensure they are suitable, and then it innovatively uses risk data as the source to directly and indirectly determine the CPC’s fuzzy degree, the CPC’s importance weight, and the If-Then rule weight by fuzzy theory and GRA for collecting final HEP results. This method was tested on a selected chemical experiment, “preparation of active ferrous sulfide”, which contains hazardous processes. Through the proposed method, the HEP of each procedure in the selected risky chemical experiment could be determined, and among the procedures, the highest HEP was 1.51 × 10−3. In addition, with the HEP results, several subtasks with a high risk of human error could be identified. The results matched the real situations.

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