Dynamic probabilistic risk assessment considering the domino effect in chemical parks based on Monte Carlo simulation

被引:0
|
作者
Hu, Hong [1 ]
Lan, Meng [2 ]
Qin, Rongshui [3 ]
Zhu, Jiping [1 ]
机构
[1] State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei,230026, China
[2] Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing,100084, China
[3] School of Civil Engineering, Anhui Jianzhu University, Hefei,230026, China
基金
中国国家自然科学基金;
关键词
Chemical hazards - Risk perception;
D O I
10.1016/j.psep.2024.11.055
中图分类号
学科分类号
摘要
In chemical industrial parks, accidents involving installations containing hazardous substances can trigger domino effects, thus exponentially spreading the incident both spatially and temporally. The inherent complexity of the effect renders dynamic risk assessment a challenge. This study aims to comprehensively evaluate dynamic risks induced by the domino effect and proposes a new algorithm based on Monte Carlo simulation and the temporal evolution of accidents. The algorithm adeptly considers both thermal accumulation and multiple accident scenarios following unit leakage, thus effectively overcoming the constraints that are prevalent in existing dynamic risk assessment approaches, which often suffer from incomplete modeling considerations or restricted application ranges. Furthermore, it redesigns accident progression while independently considering the impact of time to emergency rescue on the domino effect rather than incorporating it into the model for assessing the probability of equipment failure caused by thermal radiation. This design accurately captures the developmental characteristics of an accident. Compared to those in previous studies, the algorithm proposed in this paper more thoroughly and realistically models the domino effect and accurately depicts its evolution. The proposed algorithm enables a comprehensive assessment of dynamic risks over time with respect to units, including potential domino chains and damage probabilities, thus aiding in planning and the prevention of domino effects. The application of this algorithm is demonstrated through three case studies. The case studies demonstrate the effectiveness and superiority of the algorithm in assessing the dynamic risks associated with accidents that involve the domino effect. Furthermore, the results underscore the importance of considering thermal accumulation in domino accident modeling, along with the critical role of emergency rescue in mitigating the progression of the domino effect. © 2024 The Institution of Chemical Engineers
引用
收藏
页码:856 / 873
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