Intelligent optimization design considering aerodynamic characteristics of airfoils

Aerodynamic optimization was performed for the DU21 airfoil of the NREL 5MW wind turbine = to enhance its lift-to-drag characteristics. An optimization framework based on a dynamic adaptive genetic algorithm was developed, utilizing seventh-order Bézier curves for geometric parameterization of the airfoil. Aerodynamic performance was evaluated by using the XFOIL solver. The objective function was defined to maximize the lift-to-drag ratio. Validation is performed using Computational Fluid Dynamics (CFD) based on the SST k-ω model incorporating the γ-Reθ transition correction. The results indicate that the optimized airfoil achieved an 8.93% increase in lift-to-drag ratio at 7° angle of attack, characterized by an enhanced leading-edge suction peak and improved pressure distribution. CFD results confirmed that the optimized design significantly delayed flow separation within an angle of attach range of 5 to 12°, with discrepancies between computational and experimental lift coefficients remaining below 8% at lower attack angles. These findings demonstrate that the proposed optimization strategy significantly enhances airfoil aerodynamic performance, offering an effective methodology for wind turbine blade design.