A Dynamic Approach to Fault Tree Analysis based on Bayesian Beliefs Networks

A Dynamic Approach to Fault Tree Analysis based on Bayesian Beliefs Networks

According to the Seveso Directives, the risk assessment is crucial for an effective control of major accident hazard. Nevertheless, the complexity of many Seveso sites, due to human, technical and organizational factors makes recognized common practices limited because of their intrinsic static natu...

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Main Authors: Tomaso Vairo, Maria Milazzo, Paolo Bragatto, Bruno Fabiano
Format: Article
Language:English
Published: AIDIC Servizi S.r.l. 2019-09-01
Series:Chemical Engineering Transactions
Online Access:https://www.cetjournal.it/index.php/cet/article/view/10167
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spelling doaj-7c8eb90f6d1547aea34492c3c22cbded2021-02-16T20:59:51ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162019-09-017710.3303/CET1977139A Dynamic Approach to Fault Tree Analysis based on Bayesian Beliefs NetworksTomaso VairoMaria MilazzoPaolo BragattoBruno FabianoAccording to the Seveso Directives, the risk assessment is crucial for an effective control of major accident hazard. Nevertheless, the complexity of many Seveso sites, due to human, technical and organizational factors makes recognized common practices limited because of their intrinsic static nature. In this paper, a dynamic approach for risk assessment is proposed, which allows evaluating moment by moment the state of the system under analysis by Bayesian belief networks. A petrochemical coastal storage was selected as applicative case-study to verify the capability of the dynamic approach. Network training is performed by entering historical reliability data, near-miss and accidents data series collected on-site by periodical inspection plans on critical elements, as well as from the evidences of SMS reports. Upon proper refinement and further validation with reliable field data, the predictive approach may be used as a management decision-making tool.https://www.cetjournal.it/index.php/cet/article/view/10167
collection DOAJ
language English
format Article
sources DOAJ
author Tomaso Vairo
Maria Milazzo
Paolo Bragatto
Bruno Fabiano
spellingShingle Tomaso Vairo
Maria Milazzo
Paolo Bragatto
Bruno Fabiano
A Dynamic Approach to Fault Tree Analysis based on Bayesian Beliefs Networks
Chemical Engineering Transactions
author_facet Tomaso Vairo
Maria Milazzo
Paolo Bragatto
Bruno Fabiano
author_sort Tomaso Vairo
title A Dynamic Approach to Fault Tree Analysis based on Bayesian Beliefs Networks
title_short A Dynamic Approach to Fault Tree Analysis based on Bayesian Beliefs Networks
title_full A Dynamic Approach to Fault Tree Analysis based on Bayesian Beliefs Networks
title_fullStr A Dynamic Approach to Fault Tree Analysis based on Bayesian Beliefs Networks
title_full_unstemmed A Dynamic Approach to Fault Tree Analysis based on Bayesian Beliefs Networks
title_sort dynamic approach to fault tree analysis based on bayesian beliefs networks
publisher AIDIC Servizi S.r.l.
series Chemical Engineering Transactions
issn 2283-9216
publishDate 2019-09-01
description According to the Seveso Directives, the risk assessment is crucial for an effective control of major accident hazard. Nevertheless, the complexity of many Seveso sites, due to human, technical and organizational factors makes recognized common practices limited because of their intrinsic static nature. In this paper, a dynamic approach for risk assessment is proposed, which allows evaluating moment by moment the state of the system under analysis by Bayesian belief networks. A petrochemical coastal storage was selected as applicative case-study to verify the capability of the dynamic approach. Network training is performed by entering historical reliability data, near-miss and accidents data series collected on-site by periodical inspection plans on critical elements, as well as from the evidences of SMS reports. Upon proper refinement and further validation with reliable field data, the predictive approach may be used as a management decision-making tool.
url https://www.cetjournal.it/index.php/cet/article/view/10167
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