Research on the risk of submarine cable damage from anchored ships based on probability analysis

Mengxia Li, Xinya Zhao, Yufei Jiao, Chenguang Liu, Xiumin Chu and Junmin Mou

Reliability Engineering and System Safety, 2025, vol. 261, issue C

Abstract: With the development of marine resource development and maritime transportation, the conflict between submarine cables and anchorages has become a critical concern. Risk between anchorages and submarine cables is essential to prevent damage to the cable and optimize port resources. This paper proposes a probability-based modeling method for the risk of submarine cable damage caused by anchored ships. Firstly, the probability of submarine cable damage caused by the dragging anchor is determined by the dragging ship drifting distance and the anchor embedding depth. Then, the probability of submarine cable damage caused by the emergency dropping anchor is developed by combining the depth and timing of dropping an emergency anchor. Finally, the risk of submarine cable damage is calculated by comprehensively considering the probability of submarine cable damage caused by dragging anchor and emergency anchor. A case study in the Wenzhou waters of China indicates that the proposed model can identify the damage risk of submarine cables. This approach provides valuable insights into identifying the primary factors influencing the risk of submarine cable damage, as well as the risk associated with interactions between anchorages and submarine cables in real-world maritime scenarios. It not only offers robust evidence for the rational and scientific allocation of resources, but also enhances the safety and security of submarine cables in practical maritime management. Furthermore, it contributes to ensuring the protection of subsea cables while promoting the efficient and scientific utilization of resources.

Keywords: Probability of submarine cable damage; Monte Carlo algorithm; Dragging ship; Emergency drop anchor (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:261:y:2025:i:c:s0951832025003151

DOI: 10.1016/j.ress.2025.111114

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