A dynamic individual risk management method considering spatial and temporal synergistic effect of toxic substance leakage and fire accidents

Shou, Yuming; Chen, Jinyue; Guo, Xiaoxue; Jun, Zhu; Ding, Long; Ji, Jie; Cheng, Yuehua

doi:10.1016/j.psep.2022.11.012

Cited by 3 publications

(1 citation statement)

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“…Sarvestani et al also predicted the dynamic risk of propane tank by combining Bayesian network and fault tree analysis [ 35 ]. Based on the calculation of the total death probability of the probability model, Shou et al proposed a dynamic individual risk assessment method for the simultaneous occurrence of toxic substance leakage and fire accidents [ 36 ].…”

Section: Introductionmentioning

confidence: 99%

Study on Dynamic Probability and Quantitative Risk Calculation Method of Domino Accident in Pool Fire in Chemical Storage Tank Area

Meng

Wei

Zhou

et al. 2022

IJERPH

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The domino event caused by fire is one of the common accidents in hydrocarbon storage tank farms, which further expands the severity and scope of the accident. Due to the different failure sequence of the storage tanks in a domino accident, the radiant heat generated by the failed storage tank to the target tank is different. Based on the influence of this synergistic effect, this study combined the Monte Carlo algorithm and FSEM, and proposed a fast real-time probability calculation method for a fire domino accident in a storage tank area, for the first time. This method uses the Monte Carlo algorithm to simulate all accident scenarios, and obtains the evolution of multiple escalation fire domino accidents under the synergistic effect according to FSEM, and then calculates the real-time failure probability and risk. Based on a comprehensive analysis of the accident propagation path, this method avoids the problem of a large amount of calculation, and is conducive to the rapid and effective analysis of the fire risk in a storage tank area and the formulation of corresponding risk reduction measures. The effectiveness and superiority of the proposed method were proved by a case study.

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Section: Introductionmentioning

confidence: 99%