Search

Escort operation is an effective mean to ensure the safety of ship navigation in the Arctic ice area and expand the window period for ship navigation. At the same time, the operation mode between icebreaker and escorted ship may also causes collision accident. In order to scientifically reflect the complex coupling relationship in the escort operation system in Arctic waters and effectively manage the navigation risks. This study proposes to use the functional resonance analysis method (FRAM) to identify the risk factors of ship escort operation in Arctic waters, and uses the Bayesian network (BN) method to establish a risk assessment model for escort operation collision accident. The cloud model is used to process the uncertain data information. The proposed method is applied during the actual escort operation of a commercial ship on the Arctic Northeast Passage. According to the model simulation results, the risk performance of ship escort operation in Arctic waters is quantitatively analyzed, and the key risk causes are further analyzed. This study has positive significance for better understanding the risk evolution mechanism of ship escort operation in Arctic ice area and helping relevant management departments to take risk control measures. [ABSTRACT FROM AUTHOR]

Ship collision accidents have a greatly adverse impact on the development of the shipping industry. Due to the uncertainty relating to these accidents, maritime risk is often difficult to accurately quantify. This study innovatively proposes a comprehensive method combining qualitative and quantitative methods to predict the risk of ship collision accidents. First, in view of the uncertain impact of risk factors, the Bayesian network analysis method was used to characterize the correlations between risk factors, and a collision accident risk assessment network model was established. Secondly, in view of the uncertainty relating to the information about risk factors, a subjective data quantification method based on the cloud model was adopted, and the quantitative reasoning of collision accident risk was determined based on multi-source data fusion. The proposed method was applied to the spatiotemporal analysis of ship collision accident risk in China's coastal port waters. The results show that there is a higher risk of collision accidents in Guangzhou Port and Ningbo Port in China, the potential for ship collision accidents in southern China is greater, and the occurrence of ship collision accidents is most affected by the environment and operations of operators. Combining the Bayesian network and cloud model and integrating multi-source data information to conduct an accident risk assessment, this innovative analysis method has significance for improving the prevention of and response to risks of ship navigation operations in China's coastal ports. [ABSTRACT FROM AUTHOR]

The objective of this study is to propose a methodology for assessing waterway traffic capacity in the Shanghai estuary of the Yangtze River. To achieve this objective, we first put forward the estimation method which utilises the minimum collision distance taking the dynamic ship domain into consideration. Considering possible effects caused by unknown external factors, the waterway traffic capacity is then represented by a probability distribution. Finally, we quantify the equivalent units of ships with various ship sizes as well as the effects of large-sized ships on the waterway traffic capacity. Results show that a large-sized ship is equivalent to more small-sized ships during the daytime period than at night. In addition, the deployment of large-sized ships could increase the waterway traffic capacity and such an increment highly depends on the increased proportion of large-sized ships in the waterway traffic. [ABSTRACT FROM AUTHOR]