Open AccessStudy on Influencing Factors of Major Incidents in Petrochemical Parks Based on Bayesian Networks
Author(s) -
Haoran Hu,
Bowen Shao,
Jian Guo,
Bingyuan Hong
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1873/1/012076
Subject(s) - petrochemical , bayesian network , identification (biology) , fault tree analysis , incident report , scale (ratio) , risk analysis (engineering) , engineering , forensic engineering , computer security , computer science , business , reliability engineering , waste management , geography , artificial intelligence , cartography , botany , biology
With the rapid development of the petrochemical industry, the scale of the petrochemical park is gradually expanding. Safety incidents that occur from time to time and their serious consequences cannot be ignored. Based on the systematic summary of chemical incidents in the last 15 years, the main types of incidents are explosion, poisoning and suffocation, and fire. Thus, it is necessary to prevent major incidents from critical events. The incident tree model of major and extraordinarily large explosion incident in petrochemical park is constructed, and it is mapped to a Bayesian network for incident cause analysis and influence analysis. Consequently, it is concluded that illegal command and illegal operations are the main factors leading to the incident. The method of adding a protective layer is proposed to improve its overall safety. It can provide theoretical and technical support for accident risk identification, evaluation, and control in petrochemical park in the future.