Journal ArticleDOI
Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches
TLDR
The paper concludes that BN is a superior technique in safety analysis because of its flexible structure, allowing it to fit a wide variety of accident scenarios.About:
This article is published in Reliability Engineering & System Safety.The article was published on 2011-08-01. It has received 573 citations till now. The article focuses on the topics: Fault tree analysis & System safety.read more
Citations
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Technical, human, and organizational factors affecting failures of firefighting systems (FSs) of atmospheric storage tanks: Providing a risk assessment approach using Fuzzy Bayesian Network (FBN) and content validity indicators
Fereydoon Laal,Mostafa Pouyakian,Mohammad Jafari,Farshad Nourai,Ali Akbar Hosseini,Alireza Khanteymoori +5 more
TL;DR: Results of a case study in the Atmospheric Storage Tanks of the Methanol Floating Roof of a Petrochemical Industry showed that FBN simulation and FT validation could provide a practical way to determine FFSs probabilities, identify impactful events, and reduce the above uncertainties.
Journal ArticleDOI
Reliability analysis of mooring lines for floating structures using ANN-BN inference:
TL;DR: A methodology to assess the reliability of mooring lines under given extreme environmental conditions based on artificial neural network–Bayesian network inference and validates artificial neural networks for the response prediction of floating structures is proposed.
Journal ArticleDOI
Bayesian estimation and consequence modelling of deliberately induced domino effects in process facilities
TL;DR: A dedicated Bayesian network is developed to model the domino propagation sequence in the chemical storage area of the industry, and to estimate the Domino probabilities at different levels, which has the advantage of accurately quantifying domino occurrence probabilities and identifying possible higher levels of escalations.
Journal ArticleDOI
Bayesian network modelling of an offshore electrical generation system for applications within an asset integrity case for normally unattended offshore installations
Sean Loughney,Jin Wang +1 more
TL;DR: This article proposes the initial stages of the application of Bayesian networks in conducting quantitative risk assessment of the integrity of an offshore system and construction of a Bayesian network model that demonstrates the interactions of multiple offshore safety critical elements to analyse asset integrity.
Journal ArticleDOI
An assessment of causes and failure likelihood of cross-country pipelines under uncertainty using bayesian networks
TL;DR: In this paper , a Bayesian Network (BN) model has been developed to highlight the contributing failure factors to the identified pipeline hazards and their interrelationships, which enables the pipeline stakeholders and operators to determine those parameters or interventions that have the most impact on the reduction in pipeline loss of containment as part of risk management.
References
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Book
Bayesian networks and decision graphs
TL;DR: The book introduces probabilistic graphical models and decision graphs, including Bayesian networks and influence diagrams, and presents a thorough introduction to state-of-the-art solution and analysis algorithms.
Journal ArticleDOI
Improving the analysis of dependable systems by mapping fault trees into Bayesian networks
TL;DR: It is shown that any FT can be directly mapped into a BN and that basic inference techniques on the latter may be used to obtain classical parameters computed from the former, i.e. reliability of the Top Event or of any sub-system, criticality of components, etc.
Book
Introduction to reliability engineering
TL;DR: Reliability and Rates of Failure, Loads, Capacity, and Reliability, and System Safety Analysis; Quality and Its Measures; and Answers to Odd--Numbered Exercises.
Journal ArticleDOI
Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas
TL;DR: A bibliographical review over the last decade is presented on the application of Bayesian networks to dependability, risk analysis and maintenance and an increasing trend of the literature related to these domains is shown.
Book
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis
Uffe Kjærulff,Anders L. Madsen +1 more
TL;DR: Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks.