Dynamic risk analysis of hazardous materials highway tunnel transportation based on fuzzy Bayesian network

Abstract

To effectively deal with the dynamic and uncertain problems in the occurrence and evolution of hazardous materials highway tunnel transportation, a dynamic risk assessment model for hazardous materials highway tunnel transportation accidents in tunnels is established to find the weak links prone to accidents and explore the impact scope of accidents. Firstly, the Bow-Tie model is used to identify the hazard sources of hazardous materials in highway tunnel transportation in the tunnel, and the dynamic Bayesian network model is constructed according to the mapping relationship between the Bow-Tie model and the Bayesian network. Then, the fuzzy set theory is used to improve the dynamic Bayesian model to make up for the error caused by the lack of data, monitor the data of transportation nodes, update the accident probability in real-time, and analyze the influence intensity of each risk factor. Secondly, the ALOHA software is used to simulate and analyze the consequences of hazardous materials highway tunnel transportation accidents, and the influence range of the accident is obtained. Finally, the real-time risk value of hazardous materials highway tunnel transportation is determined according to the obtained accident probability and the impact range of accident consequences, and the validity and feasibility of the model are verified by practical cases. The results show that this method can analyze the variation of risk value with internal and external conditions at different moments and provide a panoramic leverage for risk management decision-making of hazardous materials highway tunnel transportation.