A 2D Aerodynamic Optimization Method Based On Genetic Algorithms

An efficient two dimensional aerodynamic optimization method is developed, using an optimization algorithm based on Genetic Algorithms (GAs). Several aerofoil optimization calculations are implemented using the developed method.A binary coded GAs with elitist strategy is used as a fundamental optimization method. Fitness calculations of the population are parallelized using OpenMP. A finite volume solver, based on Jameson method, is integrated with implicit residual smooth and agglomerate multigrid method to enhance the speed of convergence to the largest extent. To improve the accuracy of flow calculation, a vortex correction skill is utilized. Domain mesh is generated with a spring analogy method to maximize the optimization efficiency. Aerofoil geometry is parameterized using a newly developed CST (Class-Shape function Transformation) method.A NACA0012 surface pressure reconstruction problem is solved to validate the feasibility of the developed method used in aerofoil optimization. Then a shock control bump optimization on RAE2822 aerofoil under transonic flow conditions is implemented with the developed method. After that an aerofoil lift optimization with constraints under transonic flow conditions is implemented. Results show that the developed method is robust and efficient when used in aerofoil aerodynamic optimization.