Aerodynamic Performance Optimization of Multiple Slat Airfoil based on Multi-Objective Genetic Algorithm

In this work, the optimization for the optimum position of the secondary slat was investigated with an emphasis on enhancing the aerodynamic performance. The method adopted here merges the computational fluid dynamic (CFD) technique with the response surface method. The multi-objective genetic algorithm was used for the optimization of the positioning of the secondary slat, and the Pareto ranking was done using a non-dominated sorting method. In CFD analysis, the Reynolds average Nervier–Stokes equation is solved using the k-ω shear stress transport model which is very popular due to its accuracy. The obtained numerical result for the primary airfoil NACA 2415 and the airfoil with a single slat is validated with the experimental data. The NACA 22 airfoil profile is selected to serve as a slat to impediment the separation of boundary layer and enhance airfoil characteristics. The addition of slat at the leading edge of the primary slat increases the overall aerodynamic performance of the configuration and enhances the stall angle from 12º to 22º. Further, the addition of slat significantly reduces the boundary layer thickness as a result delays the separation to a higher angle of attack. The method used in this work can be employed as a valuable tool for positioning optimization of the secondary slat at the leading edge of the primary slat of the airfoil.