Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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Handling dependencies among performance shaping factors in SPARH through DEMATEL method

  • Zhihui Xu (State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment) ;
  • Shuwen Shang (School of Automation Engineering, Shanghai University of Electric Power) ;
  • Xiaoyan Su (School of Automation Engineering, Shanghai University of Electric Power) ;
  • Hong Qian (School of Automation Engineering, Shanghai University of Electric Power) ;
  • Xiaolei Pan (School of Automation Engineering, Shanghai University of Electric Power)
  • Received : 2022.10.11
  • Accepted : 2023.04.12
  • Published : 2023.08.25
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Abstract

The Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method is a widely used method in human reliability analysis (HRA). Performance shaping factors (PSFs) refer to the factors that may influence human performance and are used to adjust nominal human error probabilities (HEPs) in SPAR-H. However, the PSFs are assumed to be independent, which is unrealistic and can lead to unreasonable estimation of HEPs. In this paper, a new method is proposed to handle the dependencies among PSFs in SPAR-H to obtain more reasonable results. Firstly, the dependencies among PSFs are analyzed by using decision-making trial and evaluation laboratory (DEMATEL) method. Then, PSFs are assigned different weights according to their dependent relationships. Finally, multipliers of PSFs are modified based on the relative weights of PSFs. A case study is illustrated that the proposed method is effective in handling the dependent PSFs in SPAR-H, where the duplicate calculations of the dependent part can be reduced. The proposed method can deal with a more general situation that PSFs are dependent, and can provide more reasonable results.

Keywords

Acknowledgement

The authors greatly appreciate the anonymous reviewers' suggestions and the editor's encouragement. The work is partially supported by Shanghai Rising-Star Program (Grant No.21QA1403400), Shanghai Key Laboratory of Power Station Automation Technology (Grant No.13DZ2273800).

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