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Quantitative risk assessment for ammonia ship-to-ship bunkering based on Bayesian network
Process Safety Progress ( IF 1.0 ) Pub Date : 2021-11-30 , DOI: 10.1002/prs.12326
Hongjun Fan 1 , Hossein Enshaei 1 , Shantha Gamini Jayasinghe 1 , Sock Hua Tan 2 , Chunchang Zhang 3
Affiliation  

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.

中文翻译:

基于贝叶斯网络的氨船对船加注定量风险评估

海运业正在准备使用氨作为燃料来实现脱碳目标。然而,氨具有毒性、腐蚀性和易燃性,与传统燃料相比,在加油过程中提出了特定的安全挑战。通过选择合适的材料可以防止腐蚀。但是,有毒气体扩散和火灾的影响具有很大的不确定性,因此需要进行风险评估。目前,没有足够的氨加注风险评估指南。因此,本文提出了一种基于贝叶斯网络(BN)的定量风险评估框架,以研究氨在船对船加油中的潜在风险,并考虑其毒性和可燃性。该研究验证了所提出框架的实用性,并证明了 BN 作为执行概率计算和进行因果诊断的灵活模型的有效模型。结果表明,与可燃性相比,毒性对氨加注风险的影响最大。这项工作的主要创新是利用BN实现了氨船对船加注风险的有效量化。
更新日期:2021-11-30
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