期刊
SAFETY SCIENCE
卷 137, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.ssci.2021.105192
关键词
port LNG storage tanks; Terrorist attack; Risk analysis; Bayesian network
资金
- National Natural Science Foundation of China [71704183]
This article presents a new risk analysis method for terrorist attacks on port's LNG storage tanks, identifying risk factors from a multidimensional perspective, analyzing risks using Bayesian network and event tree, evaluating accident consequences, and using knowledge graph to store risk knowledge. Case studies verify the method's effectiveness in studying defense capabilities of police and various prevention strategies, showing significant differences in accident consequence between different defensive and emergency response forces. Nine scenario analyses were conducted to provide theoretical basis and method support for public security and urban risk management departments' security prevention decisions.
In recent years, with the increasing demand for liquefied natural gas (LNG) worldwide, a large amount of LNG is stored, processed, and transported in ports. The port's LNG storage tanks may become a hot target for terrorist attacks because the failure or destruction of these facilities will put markets, cities, and the environment at high risk. This article presents a new risk analysis method of terrorist attacks on the port's LNG Storage tanks. The steps are as follows: (1) Identify risk factors from a multidimensional perspective. (2) Analyze the risk using the Bayesian network and event tree. (3) Evaluate and quantify the accident consequence. (4) Use knowledge graph to store risk knowledge. We verify the effectiveness of the method through case studies. The defence capabilities of the police and different prevention strategies were studied. The results show significant differences in accident consequence between different defensive and emergency response forces. We also conducted nine scenario analysis, which could provide a theoretical basis and method support for public security and urban risk management departments' security prevention decisions.
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