TY - JOUR
T1 - A Bayesian network risk model for predicting ship besetting in ice during convoy operations along the Northern Sea Route
AU - Xu, Sheng
AU - Kim, Ekaterina
AU - Haugen, Stein
AU - Zhang, Mingyang
N1 - Funding Information:
This work is a part of the NTNU Oceans Pilot Project?Risk, Reliability, and Ice Data in Arctic Marine Environment. The authors would like to thank Captain Alexandros Serpanos for his comments and discussion on the BN model and all experts participating in the estimation of the CPT, and COSCO SHIPPING Specialized Carriers Co. Ltd. for providing the voyage data of TIAN YOU for this study. The first author thanks Nabil Panchi for help with processing and visualizing ice concertation data in Fig. 8.
Publisher Copyright:
© 2022 The Author(s)
PY - 2022/7
Y1 - 2022/7
N2 - 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.
AB - 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.
KW - Bayesian Network
KW - Convoy operations
KW - Maritime safety
KW - Northern Sea Route
KW - Ship besetting in ice
UR - http://www.scopus.com/inward/record.url?scp=85126890087&partnerID=8YFLogxK
U2 - 10.1016/j.ress.2022.108475
DO - 10.1016/j.ress.2022.108475
M3 - Article
AN - SCOPUS:85126890087
SN - 0951-8320
VL - 223
JO - Reliability Engineering and System Safety
JF - Reliability Engineering and System Safety
M1 - 108475
ER -