ABSTRACT
The influence of harsh Arctic environmental factors has caused ship-ice collision accidents to become the main threat faced by navigating ships. It is necessary to quantify the causation of ship accidents and perform effective risk management and control measures to ensure ship navigation safety. This study proposes a Bayesian network (BN) model-based risk analysis method for ship-ice collision accidents, which is used to quantitatively analyze the key risk factors and primary risk causation paths of ship accidents. First, the fault tree analysis (FTA) method is proposed to constructing the BN structure model, and the BN parameter solution method is further established. Consequently, a triangular fuzzy and defuzzification method is developed to quantify uncertain expert knowledge. Then, the BN inference method is used to analyze the collision risk causation where the North Atlantic and Arctic waters meet. The results indicate that the main risk factors in Arctic waters come from the environment. There are four primary risk causation paths; the proposed management and control measures of the risk causation paths (A), (B), (C), and (D) can effectively reduce the navigation risk by 29.95%, 9.98%, 25.05%, and 3.99%, respectively; the combination of these four measures can reduce the navigation risk by 54.63%.The proposed method has positive guiding significance for ensuring the safety of ship navigation in Arctic waters.