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

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...

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Detalles Bibliográficos
Autores principales: Zhang, Xiao, Hu, Xiaofeng, Bai, Yiping, Wu, Jiansong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014332/
https://www.ncbi.nlm.nih.gov/pubmed/31936352
http://dx.doi.org/10.3390/ijerph17020426
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author Zhang, Xiao
Hu, Xiaofeng
Bai, Yiping
Wu, Jiansong
author_facet Zhang, Xiao
Hu, Xiaofeng
Bai, Yiping
Wu, Jiansong
author_sort Zhang, Xiao
collection PubMed
description 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.
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spelling pubmed-70143322020-03-09 Risk Assessment of Gas Leakage from School Laboratories Based on the Bayesian Network Zhang, Xiao Hu, Xiaofeng Bai, Yiping Wu, Jiansong Int J Environ Res Public Health Article 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. MDPI 2020-01-08 2020-01 /pmc/articles/PMC7014332/ /pubmed/31936352 http://dx.doi.org/10.3390/ijerph17020426 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Xiao
Hu, Xiaofeng
Bai, Yiping
Wu, Jiansong
Risk Assessment of Gas Leakage from School Laboratories Based on the Bayesian Network
title Risk Assessment of Gas Leakage from School Laboratories Based on the Bayesian Network
title_full Risk Assessment of Gas Leakage from School Laboratories Based on the Bayesian Network
title_fullStr Risk Assessment of Gas Leakage from School Laboratories Based on the Bayesian Network
title_full_unstemmed Risk Assessment of Gas Leakage from School Laboratories Based on the Bayesian Network
title_short Risk Assessment of Gas Leakage from School Laboratories Based on the Bayesian Network
title_sort risk assessment of gas leakage from school laboratories based on the bayesian network
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014332/
https://www.ncbi.nlm.nih.gov/pubmed/31936352
http://dx.doi.org/10.3390/ijerph17020426
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