A Multi-Objective Optimization of the Anchor-Last Deployment of the Marine Submersible Buoy System Based on the Particle Swarm Optimization Algorithm

Abstract

Marine submersible buoy systems hold significant value as critical equipment in marine science research. This study examines a marine submersible buoy system that includes an anchor block, mooring line, battery compartment, power supply cable, and submersible buoy. The anchor-last deployment method is a conventional strategy for deploying marine submersible systems. Initially, the other components are positioned on the sea surface, followed by the deployment of the anchor block from the ship’s deck. The anchor block will pull the battery compartment and submersible buoy into the water and eventually sink to the seabed. In this deployment process, ocean currents have a relatively large impact on the anchor block’s landing position. Increasing the weight of the anchor block will make the anchor block land on the seabed sooner, which can minimize the impact of ocean currents. However, an overabundance of weight can generate a significant strain on both the cables, potentially resulting in cable breakage. In order to find the parameters that can make the anchor block reach the seabed as soon as possible and ensure that the tension force of the cables does not exceed the maximum, a dynamic model of the deployment process is established based on computational fluid dynamics (CFD) and solved using the Runge–Kutta method of the fourth order. Particle swarm optimization is employed to optimize the key parameters. The penalty function is used to constrain the particle space. The findings indicate that the utilization of particle swarm optimization is efficacious for optimizing the parameters of submersible buoy systems for marine applications. Optimized parameters allow the anchor block to reach the seafloor quickly and the tension on the cables to not exceed the given value.