CFD-validated deep active subspace learning for reliable offline transonic airfoil optimization and shock-control analysis
Offline aerodynamic optimization can fail when a search exploits surrogate error and predicted gains disappear under high-fidelity computational fluid dynamics (CFD) reevaluation. We develop a data-driven deep active subspace method (DASM) that jointly learns nonlinear active coordinates and a neural response for direc...