A Natural Evolution Based Numerical Optimisation Framework to Develop and Enhance Airfoil-Slat Arrangement

Abstract Leading Edge Slats are popularly being put into practice due to their capability to provide a significant increase in the lift generated by the wing airfoil and decrease in the stall. Consequently, their optimum design is critical for increased fuel efficiency and minimized environmental impact. This paper attempts to develop and optimize the Leading-Edge Slat geometry and its orientation with respect to airfoil using Genetic Algorithm. The class of Genetic Algorithm implemented was Invasive Weed Optimization as it showed significant potential in converging design to an optimal solution. For the study, Clark Y was taken as test airfoil. Slats being aerodynamic devices require smooth contoured surfaces without any sharp deformities and accordingly Bézier airfoil parameterization method was used. The design process was initiated by producing an initial population of various profiles (chromosomes). These chromosomes are composed of genes which define and control the shape and orientation of the slat. Control points, Airfoil-Slat offset and relative chord angle were taken as genes for the framework and different profiles were acquired by randomly modifying the genes within a decided design space. To compare individual chromosomes and to evaluate their feasibility, the fitness function was determined using Computational Fluid Dynamics simulations conducted on OpenFOAM. The lift force at a constant angle of attack (AOA) was taken as fitness value. It was assigned to each chromosome and the process was then repeated in a loop for different profiles and the fittest wing slat arrangement was obtained which had an increase in CL by 78% and the stall angle improved to 22°. The framework was found capable of optimizing multi-element airfoil arrangements.