A physics-informed generative framework produces plausible four- and five-bladed propeller geometries conditioned on thrust, power, and diameter targets, then refines them with fast neural surrogates and evolutionary optimization.
An inverse design method for supercritical airfoil based on conditional generative models
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AI-Driven Performance-to-Design Generation and Optimization of Marine Propellers
A physics-informed generative framework produces plausible four- and five-bladed propeller geometries conditioned on thrust, power, and diameter targets, then refines them with fast neural surrogates and evolutionary optimization.