ArticleInternational journal of environmental research and public health2020
Bayesian Network-Based Risk Analysis of Chemical Plant Explosion Accidents.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 24 citations in OpenAlex.
- Dynamic Mechanical Properties and Energy Absorption Capabilities of Polyureas Through Experiments and Molecular Dynamic Simulation.Polymers · 2025Article
- Generation paths of major production safety accidents - A fuzzy-set qualitative comparative analysis based on Chinese data.Frontiers in public health · 2023Article
- Plant health index as an anomaly detection tool for oil refinery processes.Scientific reports · 2022Article
- Bayesian Network-Based Risk Analysis of Chemical Plant Explosion Accidents.International journal of environmental research and public health · 2020Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The chemical industry has made great contributions to the national economy, but frequent chemical plant explosion accidents (CPEAs) have also caused heavy property losses and casualties, as the CPEA is the result of interaction of many related risk factors, leading to uncertainty in the evolution of the accident. To systematically excavate and analyze the underlying causes of accidents, this paper first integrates emergency elements in the frame of orbit intersection theory and proposes 14 nodes to represent the evolution path of the accident. Then, combined with historical data and expert experience, a Bayesian network (BN) model of CPEAs was established. Through scenario analysis and sensitivity analysis, the interaction between factors and the impact of the factors on accident consequences was evaluated. It is found that the direct factors have the most obvious influence on the accident consequences, and the unsafe conditions contribute more than the unsafe behaviors. Furthermore, considering the factor chain, the management factors, especially safety education and training, are the key link of the accident that affects unsafe behaviors and unsafe conditions. Moreover, effective government emergency response has played a more prominent role in controlling environmental pollution. In addition, the complex network relationship between elements is presented in a sensitivity index matrix, and we extracted three important risk transmission paths from it. The research provides support for enterprises to formulate comprehensive safety production management strategies and control key factors in the risk transmission path to reduce CPEA risks.
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Registered trials
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