China Safety Science Journal ›› 2024, Vol. 34 ›› Issue (3): 162-170.doi: 10.16265/j.cnki.issn1003-3033.2024.03.1155

• Safety engineering technology • Previous Articles     Next Articles

Multi-level disaster chain deduction analysis and case application of hazardous chemical accidents

HE Qinglun1,2(), JIANG Wenyu1,2, WANG Fei1,2,**(), LI Xin3, WANG Zhi3   

  1. 1 Department of Engineering Physics, Tsinghua University, Beijing 100084, China
    2 Institute of Safety Science and Technology, Tsinghua Shenzhen International Graduate School, Shenzhen Guangdong 518000, China
    3 Foshan Urban Safety Research Center, Foshan Guangdong 528000, China
  • Received:2023-09-14 Revised:2023-12-18 Online:2024-03-28 Published:2024-09-28
  • Contact: WANG Fei


To enhance the risk prevention and control capabilities of hazardous chemical factories and support emergency decision-making in case of accidents, a multi-level deduction model for the disaster chain was proposed. Furthermore, three categories of key factors (such as thermal radiation, toxic gases, and overpressure) affecting hazardous chemical accidents were considered in the model. Based on the fluid diffusion model and Probit model, the fire probability and sequence simulation algorithm of hazardous chemicals container and the ignition time estimation algorithm of hazardous chemicals explosion were proposed, respectively. Then, the quantitative analysis of the combustion and explosion evolution process in hazardous chemical accidents was performed. For the case of a resin chemical production company in Guangdong province, a disaster chain caused by hazardous chemical leakage accidents was developed to analyze the evolution time and probability of each node. The results indicated that the proposed deduction model can effectively analyze the evolution process of the actual hazardous chemical disaster chain, predict the probability and time of accident nodes, and provide fundamental knowledge for the safety layout of hazardous chemical plants.

Key words: hazardous chemical accidents, disaster chain, chain deduction, Monte Carlo, Probit model

CLC Number: