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Quantitative risk assessment for ammonia ship-to-ship bunkering based on Bayesian network
Citation
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
Abstract
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 |
Downloads: | 0 |
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