Comparative Study on Continuous and Discrete Design Optimization for the Fairlead Chain Stopper of Large-Scale Floating Offshore Wind Turbines

This study presents a comparative investigation of continuous and discrete design optimization for the fairlead chain stopper of large-scale 10 MW floating offshore wind turbines. The fairlead chain stopper plays a key role in ensuring mooring integrity, rapid port evacuation, and efficient maintenance under extreme weather conditions driven by global warming. The objective is to minimize structural weight while maintaining safety in accordance with the international classification rules of Det Norske Veritas. Three representative design load scenarios covering mooring and towing conditions are defined, and finite element analysis confirmed that the baseline design satisfies allowable stress limits. In the optimization stage, the thicknesses of nine principal components are selected as design variables. Continuous and discrete formulations are solved using particle swarm optimization, a non-dominated sorting genetic algorithm, and an evolutionary algorithm, and their convergence behavior and computational efficiency are compared. The results show that discrete optimization, which reflects actual manufacturing plate thicknesses, achieves nearly the same weight reduction as the continuous approach while offering superior practical applicability. Among the three techniques, the evolutionary algorithm provided the best convergence characteristics and attained up to 3.73 percent weight reduction. The proposed comparative methodology offers a useful guideline for rational weight-efficient design of core mooring equipment on large floating offshore wind power platforms.