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    Dynamic reliability assessment of flare systems by combining fault tree analysis and Bayesian networks

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    Kabir_Energy_Sources (521.3Kb)
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    Publication date
    2019
    Author
    Kabir, Sohag
    Taleb-Berrouane, M.
    Papadopoulos, Y.
    Keyword
    Reliability
    Fault tree analysis
    Ecological risk
    Bayesian network
    Flare system
    Rights
    © 2019 Taylor & Francis. This is an Author's Original Manuscript of an article published by Taylor & Francis in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects on 24 Sep 2019 available online at http://www.tandfonline.com/10.1080/15567036.2019.1670287
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    Flaring is a combustion process commonly used in the oil and gas industry to dispose flammable waste gases. Flare flameout occurs when these gases escape unburnt from the flare tip causing the discharge of flammable and/or toxic vapor clouds. The toxic gases released during this process have the potential to initiate safety hazards and cause serious harm to the ecosystem and human health. Flare flameout could be caused by environmental conditions, equipment failure, and human error. However, to better understand the causes of flare flameout, a rigorous analysis of the behavior of flare systems under failure conditions is required. In this article, we used fault tree analysis (FTA) and the dynamic Bayesian network (DBN) to assess the reliability of flare systems. In this study, we analyzed 40 different combinations of basic events that can cause flare flameout to determine the event with the highest impact on system failure. In the quantitative analysis, we use both constant and time-dependent failure rates of system components. The results show that combining these two approaches allows for robust probabilistic reasoning on flare system reliability, which can help improving the safety and asset integrity of process facilities. The proposed DBN model constitutes a significant step to improve the safety and reliability of flare systems in the oil and gas industry.
    URI
    http://hdl.handle.net/10454/17424
    Version
    Accepted manuscript
    Citation
    Kabir S, Taleb-Berrouane M and Papadopoulos Y (2019) Dynamic reliability assessment of flare systems by combining fault tree analysis and Bayesian networks. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. Accepted for Publication.
    Link to publisher’s version
    https://doi.org/10.1080/15567036.2019.1670287
    Type
    Article
    Collections
    Engineering and Informatics Publications

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