An object-oriented Bayesian network model for the quantitative risk assessment of navigational accidents in ice-covered Arctic waters

Funding Information: This study is supported by the National Natural Science Foundation of China under Grant 52271363 , the Shanghai Science and Technology Innovation Action Plan under Grant 22dz1204503, the Shanghai Rising-Star Program under Grant 22QC1400600 , and the Natural Science Foundation of...

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Bibliographic Details
Published in:Reliability Engineering & System Safety
Main Authors: Fu, Shanshan, Zhang, Yue, Zhang, Mingyang, Han, Bing, Wu, Zhongdai
Other Authors: Department of Mechanical Engineering, Marine and Arctic Technology, Shanghai Maritime University, Minjiang University, Shanghai Ship and Shipping Research Institute, Aalto-yliopisto, Aalto University
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier Ltd 2023
Subjects:
Online Access:https://aaltodoc.aalto.fi/handle/123456789/123518
https://doi.org/10.1016/j.ress.2023.109459
Description
Summary:Funding Information: This study is supported by the National Natural Science Foundation of China under Grant 52271363 , the Shanghai Science and Technology Innovation Action Plan under Grant 22dz1204503, the Shanghai Rising-Star Program under Grant 22QC1400600 , and the Natural Science Foundation of Fujian Province of China under Grant 2022J011128 . Publisher Copyright: © 2023 The Author(s) Merchant ship operations in the ice-covered Arctic waters may encounter traditional navigational accident risks (i.e., grounding, collision, etc.) and risks from sea ice, such as ship besetting in ice. However, describing, modeling, and quantifying the multiple risks in ice navigation are challenges from maritime risk assessment perspective. This paper proposes an object-oriented Bayesian network (OOBN) model for the quantitative risk assessment of multiple navigational accidents in ice-covered Arctic waters. The OOBN model makes use of the accident database from Lloyd's intelligence and maritime accident investigation reports. The proposed model decomposes navigational accidents into five levels based on accident causation theory: environment, unsafe condition, unsafe act, probability of navigational accident, and consequence of the navigational accident. Consequently, collision, grounding, ship besetting in ice, and ship–ice collision accidents are selected as the cases to interpret the quantitative risk assessment for navigational risk factors identification, risk analysis, and evaluation. The results demonstrate that (1) the risk is the highest in grounding accidents, followed by besetting in ice, collision, and ship–ice collision in ice-covered Arctic waters; (2) unsafe speed and unsafe condition are the critical mutual factors of these four accident scenarios; (3) and the critical risk influencing factors for the specific navigational accidents are identified to propose corresponding risk control options. The proposed OOBN model can be used for quantitative risk assessment of navigational accidents in ice-covered ...