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Quantitative risk assessment for ammonia ship-to-ship bunkering based on Bayesian network


Fan, H and Enshaei, H and Jayasinghe Arachchillage, SDG and Tan, SH and Zhang, C, Quantitative risk assessment for ammonia ship-to-ship bunkering based on Bayesian network, Process Safety Progress, 41, (2) Article 395-410. ISSN 1547-5913 (2022) [Refereed Article]

Copyright Statement

2021 American Institute of Chemical Engineers

DOI: doi:10.1002/prs.12326


The maritime industry is getting prepared for using ammonia as a fuel to meet the decarbonization goal. However, ammonia is toxic, corrosive, and flammable, which poses specific safety challenges during bunkering compared with conventional fuels. The corrosion can be prevented by selecting suitable materials. However, the impact of toxic gas dispersion and fire has high uncertainties, thus risk assessment should be conducted. Currently, there are insufficient risk assessment guidelines for ammonia bunkering available. Therefore, this paper proposes a Bayesian network (BN) based quantitative risk assessment framework to investigate the potential risks of ammonia in ship-to-ship bunkering considering the toxicity and flammability. The study validates the utility of the proposed framework and demonstrates the BN as an efficient model in performing the probabilities calculations and flexible in conducting causal diagnosis. The results show that toxicity has the greatest impact on the risks of ammonia bunkering compared with flammability. The main innovation of this work is realizing the efficient quantification of risks for ammonia ship-to-ship bunkering by using the BN.

Item Details

Item Type:Refereed Article
Keywords:ammonia, Bayesian network, bunkering, extended event tree, marine fuel
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 (Dr Hongjun Fan)
UTAS Author:Enshaei, H (Dr Hossein Enshaei)
UTAS Author:Jayasinghe Arachchillage, SDG (Dr Shantha Jayasinghe Arachchillage)
ID Code:148225
Year Published:2022 (online first 2021)
Web of Science® Times Cited:1
Deposited By:Seafaring and Maritime Operations
Deposited On:2021-12-13
Last Modified:2022-09-30

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