#TITLE_ALTERNATIVE# - ARIF HAFIZUDDIN (NIM : 13607046); Pembimbing : Dr. Lavi R Zuhal, MUHAMMAD
Optimization of low Reynolds Number airfoils using Particle Swarm Optimization (PSO) method which is based on swarm intelligence approach is presented on current study. The needed of new airfoil is important to support the quick development of UAV. PSO is a machine-learning technique inspired by birds flocking in search of food which is now gaining popularity to be implemented field of optimization. The objective of optimization scheme in present work is to maximize lift to drag ratio of the airfoil in specified Reynolds Numbers. The airfoil in present study is generated by B-spline curves with 16 control points formulate the geometry of the airfoils where XFOIL solver is used to calculate the aerodynamic performance of generated airfoil. By using initial profiles of airfoil that is reproduced by tuning the control points of B-spline formula, initial geometry is systematically altered and optimized by Particle Swarm Optimization (PSO) method until convergence criteria is reached. High-lift airfoil S1223 is used as a benchmark to test the performance of developed optimization algorithm. The optimized S1223 airfoil has significant improvements in aerodynamic characteristic compared to the initial design where PSO is able to find satisfactory optimized airfoil even by only few numbers of function evaluation and short CPU time. The result demonstrates that PSO has a great potential to be used and improved as a design and optimization tool for airfoil.