SPH hydrodynamic modeling and data-driven power performance optimization of a swing-wing wave energy converter
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In this work, we developed a numerical and optimization framework for enhancing the power performance of SW-WEC by integrating smoothed particle hydrodynamics (SPH), radial basis function neural network (RBFNN), and genetic algorithm (GA).
创建时间：
2026-03-04
