@article{ref1,
title="An application of Bayesian network to quantify human reliability in nuclear power plants based on SPAR-H method",
journal="International journal of occupational safety and ergonomics",
year="2022",
author="Yan, Shengyuan and Yao, Kai and Li, Fengjiao and Wei, Yingying and Tran, Cong Chi",
volume="ePub",
number="ePub",
pages="ePub-ePub",
abstract="Human error is an important factor leading to nuclear power plants (NPPs) accidents. The human reliability analysis (HRA) is considered to be an effective method to reduce human error. Therefore, this paper proposes a method to quantify human reliability based on Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method. Firstly, this paper used the performance shaping factors of SPAR-H to build human reliability model. Secondly, the triangular fuzzy number was used to quantify the qualitative information of root nodes, and the fuzzy IF-THEN rule was used to determine the prior probability distribution of intermediate nodes. Finally, Bayesian reasoning was used to quantify human reliability based on the human reliability model. The result of the developed method is consistent with the result of Cognitive Reliability and Error Analysis Methods (CREAM). The developed method can be used as a tool to quantify the human reliability in the NPPs system.<p /> <p>Language: en</p>",
language="en",
issn="1080-3548",
doi="10.1080/10803548.2022.2026074",
url="http://dx.doi.org/10.1080/10803548.2022.2026074"
}