Uncertainty-triggered multi-fidelity GPs inside a hybrid GA redesign a 12-parameter CST airfoil for two flight conditions with only ~10–15% RANS calls and large reported gains over generation 1.
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Optimization-Embedded Active Multi-Fidelity Surrogate Learning for Multi-Condition Airfoil Shape Optimization
Uncertainty-triggered multi-fidelity GPs inside a hybrid GA redesign a 12-parameter CST airfoil for two flight conditions with only ~10–15% RANS calls and large reported gains over generation 1.