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Dynamic quantitative risk assessment of LNG bunkering SIMOPs based on Bayesian network


Fan, H and Enshaei, H and Jayasinghe, SG, Dynamic quantitative risk assessment of LNG bunkering SIMOPs based on Bayesian network, Journal of Ocean Engineering and Science pp. 1-19. ISSN 2468-0133 (In Press) [Refereed Article]

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DOI: doi:10.1016/j.joes.2022.03.004


Liquified natural gas (LNG) bunkering simultaneous operations (SIMOPs) refers to the operations (such as cargo operations, port activities and ship maintenance) occurring around LNG bunkering. SIMOPs pose new risks to LNG bunkering, because the operations are dynamically interlocked in which the occurrence probabilities of potential consequences change at different times due to commencement or completion of specific SIMOP events. However, traditional static risk assessment approaches are not able to take the dynamic nature of these new risks into account. This article proposes a dynamic quantitative risk assessment (DQRA) methodology based on the Bayesian network (BN) to develop better understanding of dynamic risks of LNG bunkering SIMOPs. The methodology is demonstrated and evaluated through a truck-to-ship LNG bunkering case study. The results and discussion of the case study validate the utility of the proposed methodology and demonstrate that BNs are efficient in performing the probability calculations and are flexible in conducting causal diagnosis. The main innovation of this work is realizing the quantification of risks at different times, which reflects the most essential time-changing characteristics of risks associated with LNG bunkering SIMOPs.

Item Details

Item Type:Refereed Article
Keywords:maritime, alternative fuel, safety, LNG bunkering, SIMOPs, dynamic risk
Research Division:Engineering
Research Group:Maritime engineering
Research Field:Marine engineering
Objective Division:Transport
Objective Group:Water transport
Objective Field:International sea transport of liquefied gas
UTAS Author:Fan, H ( Hongjun Fan)
UTAS Author:Enshaei, H (Dr Hossein Enshaei)
UTAS Author:Jayasinghe, SG (Dr Shantha Jayasinghe Arachchillage)
ID Code:150547
Year Published:In Press
Deposited By:Seafaring and Maritime Operations
Deposited On:2022-06-20
Last Modified:2022-06-20

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