A hybrid physical-informational platform for aerohydrodynamic design of blade systems with multicriterial optimization based on quantum and neural network methods
A hybrid physics-informed computing platform for aero-hydrodynamic analysis and multi-criteria optimization of blade system profiles is presented, combining the Neural Foil neural network surrogate with panel methods and gradient-based optimization. A generalized Magnus effect model for rotating profiles is developed a...