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A Risk Treatment Strategy Model for Oil Pipeline Accidents Based on a Bayesian Decision Network Model

Risk treatment is an effective way to reduce the risk of oil pipeline accidents. Many risk analysis and treatment strategies and models have been established based on the event tree method, bow-tie method, Bayesian network method, and other methods. Considering the characteristics of the current mod...

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Autores principales: Zhang, Chao, Wang, Wan, Xu, Fengjiao, Chen, Yong, Qin, Tingxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9603165/
https://www.ncbi.nlm.nih.gov/pubmed/36293630
http://dx.doi.org/10.3390/ijerph192013053
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author Zhang, Chao
Wang, Wan
Xu, Fengjiao
Chen, Yong
Qin, Tingxin
author_facet Zhang, Chao
Wang, Wan
Xu, Fengjiao
Chen, Yong
Qin, Tingxin
author_sort Zhang, Chao
collection PubMed
description Risk treatment is an effective way to reduce the risk of oil pipeline accidents. Many risk analysis and treatment strategies and models have been established based on the event tree method, bow-tie method, Bayesian network method, and other methods. Considering the characteristics of the current models, a risk treatment strategy model for oil pipeline accidents based on Bayesian decision network (BDNs) is proposed in this paper. First, the quantitative analysis method used in the Event-Evolution-Bayesian model (EEB model) is used for risk analysis. Second, the consequence weights and initial event likelihoods are added to the risk analysis model, and the integrated risk is obtained. Third, the risk treatment strategy model is established to achieve acceptable risk with optimal resources. The risk treatment options are added to the Bayesian network (BN) risk analysis model as the decision nodes and utility nodes. In this approach, the BN risk analysis model can be transformed into a risk treatment model based on BDNs. Compared to other models, this model can not only identify the risk factors comprehensively and illustrate the incident evolution process clearly, but also can support diverse risk treatment strategies for specific cases, such as to reduce the integrated risk to meet acceptable criterion or to balance the benefit and cost of an initiative. Furthermore, the risk treatment strategy can be updated as the risk context changes.
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spelling pubmed-96031652022-10-27 A Risk Treatment Strategy Model for Oil Pipeline Accidents Based on a Bayesian Decision Network Model Zhang, Chao Wang, Wan Xu, Fengjiao Chen, Yong Qin, Tingxin Int J Environ Res Public Health Article Risk treatment is an effective way to reduce the risk of oil pipeline accidents. Many risk analysis and treatment strategies and models have been established based on the event tree method, bow-tie method, Bayesian network method, and other methods. Considering the characteristics of the current models, a risk treatment strategy model for oil pipeline accidents based on Bayesian decision network (BDNs) is proposed in this paper. First, the quantitative analysis method used in the Event-Evolution-Bayesian model (EEB model) is used for risk analysis. Second, the consequence weights and initial event likelihoods are added to the risk analysis model, and the integrated risk is obtained. Third, the risk treatment strategy model is established to achieve acceptable risk with optimal resources. The risk treatment options are added to the Bayesian network (BN) risk analysis model as the decision nodes and utility nodes. In this approach, the BN risk analysis model can be transformed into a risk treatment model based on BDNs. Compared to other models, this model can not only identify the risk factors comprehensively and illustrate the incident evolution process clearly, but also can support diverse risk treatment strategies for specific cases, such as to reduce the integrated risk to meet acceptable criterion or to balance the benefit and cost of an initiative. Furthermore, the risk treatment strategy can be updated as the risk context changes. MDPI 2022-10-11 /pmc/articles/PMC9603165/ /pubmed/36293630 http://dx.doi.org/10.3390/ijerph192013053 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Chao
Wang, Wan
Xu, Fengjiao
Chen, Yong
Qin, Tingxin
A Risk Treatment Strategy Model for Oil Pipeline Accidents Based on a Bayesian Decision Network Model
title A Risk Treatment Strategy Model for Oil Pipeline Accidents Based on a Bayesian Decision Network Model
title_full A Risk Treatment Strategy Model for Oil Pipeline Accidents Based on a Bayesian Decision Network Model
title_fullStr A Risk Treatment Strategy Model for Oil Pipeline Accidents Based on a Bayesian Decision Network Model
title_full_unstemmed A Risk Treatment Strategy Model for Oil Pipeline Accidents Based on a Bayesian Decision Network Model
title_short A Risk Treatment Strategy Model for Oil Pipeline Accidents Based on a Bayesian Decision Network Model
title_sort risk treatment strategy model for oil pipeline accidents based on a bayesian decision network model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9603165/
https://www.ncbi.nlm.nih.gov/pubmed/36293630
http://dx.doi.org/10.3390/ijerph192013053
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