Design Exploration of Airfoils for Advanced Air Mobility Using Multifidelity Optimization
This study presents a multifidelity, multi-objective optimization framework for the aerodynamic design of airfoils operating at [Formula: see text] Reynolds numbers in incompressible flow. The framework couples the efficiency of the panel solver XFOIL with the accuracy of the unsteady Reynolds-averaged Navier–Stokes solver transonic unsteady rotor Navier–Stokes (2D) (TURNS2D), which incorporates transition modeling via the [Formula: see text] model. The nondominated sorting genetic algorithm II minimizes drag at two design lift coefficients (0.3 and 0.7) while satisfying constraints on pitching moment, thickness, and maximum lift coefficient. XFOIL-based optimizations reproduce conventional laminar-flow design strategies, whereas subsequent high-fidelity refinement with TURNS2D captures transitional effects. Laminar separation bubble dynamics govern drag reduction and off-design robustness. For fixed-wing configurations, the Pareto knee airfoil achieves a 50% improvement in lift-to-drag ratio relative to the E387 baseline, with drag reduced from [Formula: see text] to [Formula: see text] at [Formula: see text]. For rotary-wing configurations, enforcing a tighter pitching-moment constraint ([Formula: see text]) reduces the pitching moment by an order of magnitude relative to the E387, with a drag penalty of 20–30 counts and a peak lift-to-drag ratio of approximately 100. Imposing an additional lift-to-drag constraint broadens the operational envelope, producing airfoils with flatter lift-to-drag ratio peaks and smoother transition behavior.