A risk assessment method to quantify the effect of human reliability on storage tank safety combining optimized CREAM and dynamic Bayesian network

IF 4.7 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

Safety Science Pub Date : 2025-01-28 DOI:10.1016/j.ssci.2025.106796

Xin Li , Fanliang Ge , Weidong Lin , Fuqiang Yang

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引用次数: 0

Abstract

Human error, as a major accident causal factor, can trigger an storage tank fire accident and delay the activation of active protection. In this work, a domino-human intervention model was proposed to assess the effect of human reliability on domino fire accidents. The optimized cognitive reliability and error analysis method (CREAM) was constructed to calculate the human error probability (HEP). The dynamic Bayesian network (DBN) of the domino-human intervention model was constructed by the probability of fire escalation and HEP. Among them, the analyzed network includes an initial accident scenario and a safety barrier protection scenario. Lastly, the domino-human intervention model was applied in a case study. The application of the model is validated in the case study, which confirms that HEP can reduce storage tank safety, as well as have a delayed effect on active protection. The proposed model will serve as an assessment tool for the effect of human reliability on domino accidents.

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来源期刊

Safety Science 管理科学-工程：工业

CiteScore

13.00

自引率

9.80%

发文量

335

审稿时长

53 days

期刊介绍： Safety Science is multidisciplinary. Its contributors and its audience range from social scientists to engineers. The journal covers the physics and engineering of safety; its social, policy and organizational aspects; the assessment, management and communication of risks; the effectiveness of control and management techniques for safety; standardization, legislation, inspection, insurance, costing aspects, human behavior and safety and the like. Papers addressing the interfaces between technology, people and organizations are especially welcome.