A Bayesian network risk model for predicting ship besetting in ice during convoy operations along the Northern Sea Route

被引:50
作者
Xu, Sheng [1 ]
Kim, Ekaterina [1 ]
Haugen, Stein [1 ]
Zhang, Mingyang [2 ]
机构
[1] Norwegian Univ Sci & Technol, Fac Engn, Dept Marine Technol, NTNU, Trondheim, Norway
[2] Aalto Univ, Dept Mech Engn, Marine Technol Grp, Espoo, Finland
关键词
Ship besetting in ice; Convoy operations; Northern Sea Route; Bayesian Network; Maritime safety; MARITIME TRANSPORTATION SYSTEMS; WINTER NAVIGATION; PROBABILISTIC MODEL; ESCORT;
D O I
10.1016/j.ress.2022.108475
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
To facilitate shipping in ice and to meet the increasing requirements of icebreaker services, convoy operations are the most effective alternative. However, convoy operations are among the most dangerous operations as they can result in ship-ship collisions and/or ship besetting in ice. To safeguard the assisted ships and improve the efficiency of convoy operations, predicting the besetment event is a paramount proactive measure. In this study, a Bayesian Network model is developed to predict the probability of ship besetting in ice in a convoy operation along the Northern Sea Route (NSR). The model focuses on the first-assisted ship and is based on expert elicitation. Correspondingly, four scenarios that may result in the first assisted ship besetting in ice have been identified. Further, the applicability of the model is evaluated through 12 scenarios derived from the real NSR voyage of 'TIAN YOU' assisted by the icebreaker 'VAYGACH' in August 2018. The results of the model evaluation and validity studies indicate that the developed model is feasible and can adequately predict the besetment event of the first assisted ship in convoy operations. The most important factors contributing to besetting in ice were found to be ice concentration, distance between icebreaker and ship, and navigation experience.
引用
收藏
页数:14
相关论文
共 90 条
[1]   Dynamic reliability assessment of ship grounding using Bayesian Inference [J].
Abaei, Mohammad Mahdi ;
Arzaghi, Ehsan ;
Abbassi, Rouzbeh ;
Garaniya, Vikram ;
Javanmardi, Mohammadreza ;
Chai, Shuhong .
OCEAN ENGINEERING, 2018, 159 :47-55
[2]   Arctic shipping accident scenario analysis using Bayesian Network approach [J].
Afenyo, Mawuli ;
Khan, Faisal ;
Veitch, Brian ;
Yang, Ming .
OCEAN ENGINEERING, 2017, 133 :224-230
[3]  
[Anonymous], 2014, SCI ASSESSMENT OZONE, P1
[4]   Validation of risk analysis for ship collision in narrow waters by using fuzzy Bayesian networks approach [J].
Aydin, Muhammet ;
Akyuz, Emre ;
Turan, Osman ;
Arslan, Ozcan .
OCEAN ENGINEERING, 2021, 231
[5]   Marine transportation risk assessment using Bayesian Network: Application to Arctic waters [J].
Baksh, Al-Amin ;
Abbassi, Rouzbeh ;
Garaniya, Vikram ;
Khan, Faisal .
OCEAN ENGINEERING, 2018, 159 :422-436
[6]   Risk management model of winter navigation operations [J].
Banda, Osiris A. Valdez ;
Goerlandt, Floris ;
Kuzmin, Vladimir ;
Kujala, Pentti ;
Montewka, Jakub .
MARINE POLLUTION BULLETIN, 2016, 108 (1-2) :242-262
[7]   A risk analysis of winter navigation in Finnish sea areas [J].
Banda, Osiris A. Valdez ;
Goerlandt, Floris ;
Montewka, Jakub ;
Kujala, Pentti .
ACCIDENT ANALYSIS AND PREVENTION, 2015, 79 :100-116
[8]  
BBC, BBC
[9]  
Berg N, 2010, ICE NAVIGATION ICE C
[10]  
Bryant D.T., 1991, The Human Element in Shipping Casualties