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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Journal ArticleDOI
Comprehensive risk evaluation of long-distance oil and gas transportation pipelines using a fuzzy Petri net model
TL;DR: It is verified that the risk evaluation method based on the FPN model applies for the long-distance oil and gas transportation pipelines and provides some decision support for the risk management of theOil and gas pipelines.
Journal ArticleDOI
Failure probability analysis of the urban buried gas pipelines using Bayesian networks
TL;DR: In this article, the authors presented an advanced two-step approach to analyze failure probabilities of the urban buried gas pipeline. And the results indicate that this approach is feasible and reasonable which can assist in identifying safety critical factors.
Journal ArticleDOI
Decision support analysis for safety control in complex project environments based on Bayesian Networks
TL;DR: The safety control process is extended to the entire life cycle of risk-prone events in model application, rather than restricted to pre-accident control, but during-construction continuous and post-accidents control are included.
Journal ArticleDOI
A thorough classification and discussion of approaches for modeling and managing domino effects in the process industries
TL;DR: An overview of what constitutes domino effects based on the definition and features is provided, characterizing domino effect studies according to different research issues and approaches, and future research directions are offered.
Journal ArticleDOI
Risk analysis of dust explosion scenarios using Bayesian networks.
TL;DR: In this study, a methodology has been proposed for risk analysis of dust explosion scenarios based on Bayesian network and benefits from a bow-tie diagram to better represent the logical relationships existing among contributing factors and consequences of dust explosions.
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.