Aerodynamic optimization and robust design of a flow deflector for wing stall control

This study develops and numerically assesses a robust aerodynamic optimization framework for a passive flow deflector on a three-dimensional cambered “Flugzeug nächster Generation” (FNG) wing. A surrogate-assisted Efficient Global Optimization (EGO) algorithm is employed to automate the design of the deflector configuration. The robustness of the optimized design is evaluated under different side-boundary conditions and turbulence models. At a high angle of attack of 19°, the optimized configuration improves the lift-to-drag ratio by 40.15% under periodic boundary conditions with the Spalart-Allmaras (S-A) model and by 63.86% with the Transition-SST model. Under wall-bounded conditions, which are introduced to better approximate future wind-tunnel configurations, the lift-to-drag ratio is further improved by 53.32%. Across all tested numerical settings, the optimized deflector consistently strengthens the leading-edge suction peak, smooths the upper-surface streamline pattern, suppresses large-scale vortex formation, and delays stall onset. The present work therefore provides a systematic numerical framework for robust aerodynamic design, while experimental validation of the optimized configuration remains a subject for future work.