Emergency response research of gas accidents based on Bayesian network scenario deduction

Gas accidents are characterized by suddenness, uncertainty, and irregularity in their evolution. Due to their immense destructive power and wide-ranging impact, it is challenging to develop scientific and effective emergency response plans. Therefore, it is crucial to conduct a thorough study of the causes and influencing factors of gas accidents and formulate corresponding preventive measures. Using scenario response models and Bayesian network models, this paper analyzes the “ $10 \cdot 21$ “ large pipeline gas leakage and explosion accident that occurred at No. 222 South Taiyuan Street, Shenyang City. The research examines the transformation of accident scenarios while also quantitatively analyzing the emergency rescue process for gas accidents. The hidden danger investigation and treatment in the construction process can reduce the risk by $\mathbf{1 0 \%}$; Timely and effective emergency rescue measures can reduce the probability of other accidents by $\mathbf{1 0 \%}$; If the accident can be timely intervention in the early stage, the hidden dangers can be rectified in time, and the site safety can be increased by 15%. These results provide valuable insights for developing effective emergency response plans.

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Published
2024-09-20
DOI
https://doi.org/10.1109/epee63731.2024.10875373
Primary Topic
Safety and Risk Management
Type
article
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article

Emergency response research of gas accidents based on Bayesian network scenario deduction

Lina Chen, Jie Gao, Zipeng Sun
Safety and Risk Management
article

Emergency response research of gas accidents based on Bayesian network scenario deduction

Lina Chen, Jie Gao, Zipeng Sun
article en

Abstract

Gas accidents are characterized by suddenness, uncertainty, and irregularity in their evolution. Due to their immense destructive power and wide-ranging impact, it is challenging to develop scientific and effective emergency response plans. Therefore, it is crucial to conduct a thorough study of the causes and influencing factors of gas accidents and formulate corresponding preventive measures. Using scenario response models and Bayesian network models, this paper analyzes the “ $10 \cdot 21$ “ large pipeline gas leakage and explosion accident that occurred at No. 222 South Taiyuan Street, Shenyang City. The research examines the transformation of accident scenarios while also quantitatively analyzing the emergency rescue process for gas accidents. The hidden danger investigation and treatment in the construction process can reduce the risk by $\mathbf{1 0 \%}$; Timely and effective emergency rescue measures can reduce the probability of other accidents by $\mathbf{1 0 \%}$; If the accident can be timely intervention in the early stage, the hidden dangers can be rectified in time, and the site safety can be increased by 15%. These results provide valuable insights for developing effective emergency response plans.

Shanghai Institute of Technology (CN)
Climate action
Openalex Percentile: Top 63%
Safety and Risk Management
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Emergency response research of gas accidents based on Bayesian network scenario deduction — Lina Chen, Jie Gao, et al. · (2024) | TGRS Research Map | TGRS