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author:

Li, Xin (Li, Xin.) [1] | Ge, Fanliang (Ge, Fanliang.) [2] (Scholars:葛樊亮) | Lin, Weidong (Lin, Weidong.) [3] | Yang, Fuqiang (Yang, Fuqiang.) [4] (Scholars:阳富强)

Indexed by:

EI Scopus SCIE

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.

Keyword:

Domino fire accident Dynamic Bayesian network Human error probability Human intervention Human reliability

Community:

  • [ 1 ] [Li, Xin]Fuzhou Univ, Coll Environm & Safety Engn, Fuzhou 350116, Peoples R China
  • [ 2 ] [Ge, Fanliang]Fuzhou Univ, Coll Environm & Safety Engn, Fuzhou 350116, Peoples R China
  • [ 3 ] [Yang, Fuqiang]Fuzhou Univ, Coll Environm & Safety Engn, Fuzhou 350116, Peoples R China
  • [ 4 ] [Lin, Weidong]Fujian Prov Inst Architectural Design & Res CO LTD, Fuzhou 350001, Peoples R China
  • [ 5 ] [Yang, Fuqiang]Fuzhou Univ, Fujian Prov Key Lab Remote Sensing Soil Eros & Dis, Fuzhou 350116, Peoples R China

Reprint 's Address:

  • 阳富强

    [Yang, Fuqiang]2 Xueyuan Rd, Fuzhou, Fujian Province, Peoples R China

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Source :

SAFETY SCIENCE

ISSN: 0925-7535

Year: 2025

Volume: 185

4 . 7 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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