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Risk Assessment of Gas Leakage from School Laboratories Based on the Bayesian Network

Author

Listed:
  • Xiao Zhang

    (School of Information Technology and Network Security, People’s Public Security University of China, Beijing 102628, China)

  • Xiaofeng Hu

    (School of Information Technology and Network Security, People’s Public Security University of China, Beijing 102628, China)

  • Yiping Bai

    (School of Emergency Management and Safety Engineering, China University of Mining & Technology, Beijing 100083, China)

  • Jiansong Wu

    (School of Emergency Management and Safety Engineering, China University of Mining & Technology, Beijing 100083, China)

Abstract

In recent years, concerns about the safety of laboratories have been caused by several serious accidents in school laboratories. Gas leaks in the laboratory are often difficult to detect and cause serious consequences. In this study, a comprehensive model based on the Bayesian network is established for the assessment of the gas leaks evolution process and consequences in school laboratories. The model can quantitatively evaluate the factors affecting the probability and consequences of gas leakage. The results show that a model is an effective tool for assessing the risk of gas leakage. Among the various factors, the unsafe behavior of personnel has the greatest impact on the probability of gas leakage, and the concentration of toxic and harmful gases is the main factor affecting the consequences of accidents. Since the probability distribution of each node is obtained based on the experience of experts, there is a deviation in the quantitative calculation of the probability of gas leakage and consequences, but does not affect the risk analysis. This study could quantitatively assess the probability and consequences of gas leakage in the laboratory, and identify vulnerabilities, which helps improve the safety management level of gas in the school laboratory and reducing the possibility of gas leakage posing a threat to personal safety.

Suggested Citation

  • Xiao Zhang & Xiaofeng Hu & Yiping Bai & Jiansong Wu, 2020. "Risk Assessment of Gas Leakage from School Laboratories Based on the Bayesian Network," IJERPH, MDPI, vol. 17(2), pages 1-18, January.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:2:p:426-:d:306505
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    References listed on IDEAS

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    Cited by:

    1. Laihao Ma & Xiaoxue Ma & Jingwen Zhang & Qing Yang & Kai Wei, 2021. "A Methodology for Dynamic Assessment of Laboratory Safety by SEM-SD," IJERPH, MDPI, vol. 18(12), pages 1-18, June.
    2. Rongchen Zhu & Xiaofeng Hu & Xin Li & Han Ye & Nan Jia, 2020. "Modeling and Risk Analysis of Chemical Terrorist Attacks: A Bayesian Network Method," IJERPH, MDPI, vol. 17(6), pages 1-23, March.
    3. Syed Imran Ali & Shaine Mohammadali Lalji & Javed Haneef & Mohsin Yousufi & Kanza Bashir & Saman Sohail & Laiba Sajid Cheema, 2023. "HSE hazard ranking of chemicals related to Petroleum Drilling Laboratory of University using Fuzzy TOPSIS," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1386-1406, September.

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