A Fuzzy Bayesian Network-Based Method for Evaluating the Leakage Risk of STS LNG Bunkering

被引:4
作者
Zhang, Wenfen [1 ]
Yu, Yang [1 ]
Wu, Bing [2 ]
Wan, Chengpeng [2 ]
Yu, Niu [1 ]
Song, Yateng [3 ]
机构
[1] Wuhan Text Univ, Management Sch, 1 Sunshine Ave, Wuhan 430200, Peoples R China
[2] Wuhan Univ Technol, Intelligent Transport Syst Res Ctr, 1178 Heping Ave, Wuhan 430063, Peoples R China
[3] Zhoushan Port Business Dev Ctr, 555 Wengshan Rd, Zhoushan, Peoples R China
关键词
Maritime safety; Fuzzy Bayesian network; Liquefied natural gas (LNG) bunkering; Leakage risk; VESSELS; ZONE;
D O I
10.1061/AJRUA6.RUENG-1204
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
As a promising clean fuel, the liquefied natural gas (LNG) has been considered as the alternative energy for ships and the LNG-fueled vessels has sharply increased in recent years. However, the leakage of LNG has become a serious challenge for the wide application of LNG-fueled vessels, especially during ship-to-ship (STS) bunkering. This study analyzes leakage accidents during STS LNG bunkering, considering its operation process, and develops a fuzzy Bayesian network model to evaluate the probability of LNG leakage during STS LNG bunkering. Sensitivity analysis is carried out to identify the critical risk factors. Moreover, the study simulates the consequence of LNG leakage using the Fire Dynamics Simulator (FDS) software and derives the F-N curve to determine the risk levels of LNG leakage considering the thermal radiation criteria. A case study of LNG-fueled vessel in Ningbo is conducted to verify the proposed method. The results show that the probability of LNG leakage and fire accidents during STS bunkering is 0.93% and 1.3829x10-4 respectively, which is located in the as low as reasonably practicable (ALARP) zone. Afterwards, it is found that uneven force on the ropes and fenders are the crucial factor influencing LNG bunkering. The simulation experiments demonstrate that the high-risk areas of STS LNG bunkering are 4 to 16 m away from the LNG-fueled ship. This study analyzes leakage accidents during ship-to-ship (STS) liquefied natural gas (LNG) bunkering, and develops a fuzzy Bayesian network model to evaluate the probability of LNG leakage during STS LNG bunkering. A case study of LNG-fueled vessel named XINAO in Ningbo is conducted to verify the proposed method. Moreover, the study simulates the consequence of LNG leakage using the Fire Dynamics Simulator (FDS) software and derives the frequency versus number of fatalities (F-N) curve to determine the risk levels of LNG leakage considering the thermal radiation criteria. The results show that the probability of LNG leakage and fire accidents during STS bunkering is 0.93% and 1.3829x10-4 respectively, which is located in the as low as reasonably practical (ALARP) zone. Then, it is found that uneven force on the ropes and fenders are the crucial factor during STS LNG bunkering. The simulation experiments demonstrate that the high-risk areas of STS LNG bunkering are 4-16 m away from the LNG-fueled ship. This paper delivers a remarkable research work providing rule-makers with an insight into the safety management during STS LNG bunkering.
引用
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页数:16
相关论文
共 39 条
[1]  
Aneziris O., 2022, Chemical Engineering Transactions, V91, P535, DOI [DOI 10.3303/CET2291090, 10.3303/CET2291090]
[2]   Safety guidelines and a training framework for LNG storage and bunkering at ports [J].
Aneziris, Olga ;
Gerbec, Marko ;
Koromila, Ioanna ;
Nivolianitou, Zoe ;
Pilo, Francesco ;
Salzano, Ernesto .
SAFETY SCIENCE, 2021, 138
[3]  
Duan Y., 2013, Ship Ocean Eng, V42, P191
[4]   Dynamic quantitative risk assessment of LNG bunkering SIMOPs based on Bayesian network [J].
Fan, Hongjun ;
Enshaei, Hossein ;
Jayasinghe, Shantha Gamini .
JOURNAL OF OCEAN ENGINEERING AND SCIENCE, 2023, 8 (05) :508-526
[5]   Safety philosophy and risk analysis methodology for LNG bunkering simultaneous operations (SIMOPs): A literature review [J].
Fan, Hongjun ;
Enshaei, Hossein ;
Jayasinghe, Shantha Gamini .
SAFETY SCIENCE, 2021, 136
[6]   Towards a probabilistic approach for risk analysis of nuclear-powered icebreakers using FMEA and FRAM [J].
Fu, Shanshan ;
Yu, Yuerong ;
Chen, Jihong ;
Han, Bing ;
Wu, Zhongdai .
OCEAN ENGINEERING, 2022, 260
[7]   A framework for quantitative analysis of the causation of grounding accidents in arctic shipping [J].
Fu, Shanshan ;
Yu, Yuerong ;
Chen, Jihong ;
Xi, Yongtao ;
Zhang, Mingyang .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2022, 226
[8]   Framework for the quantitative assessment of the risk of leakage from LNG-fueled vessels by an event tree-CFD [J].
Fu, Shanshan ;
Yan, Xinping ;
Zhang, Di ;
Li, Chaoyu ;
Zio, Enrico .
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES, 2016, 43 :42-52
[9]   Evaluating the potential for overpressures from the ignition of an LNG vapor cloud during offloading [J].
Gavelli, Filippo ;
Davis, Scott G. ;
Hansen, Olav R. .
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES, 2011, 24 (06) :908-915
[10]   Uncertainties in failure rates in the LNG bunkering risk assessment [J].
Gerbec, Marko ;
Aneziris, Olga .
SAFETY SCIENCE, 2022, 152