Application of Genetic Algorithms in Shape Optimization for Aerodynamic Bodies

The objective of this study is to minimize the drag coefficient of aerodynamics bodies for a specified design Reynolds number regime. With the aerodynamics model the gradient of the objective function (drag coefficient) cannot be determined analytically. Furthermore, it is expected that the objective function is multi-modal, i.e. it shows more than one minimum. Therefore, the optimization algorithm must be efficiently applicable to such multidimensional, multi-modal and nonlinear objective functions. A powerful optimization procedure called Genetic Algorithms (GA) has been combined with the aerodynamics calculation to find the optimal shape with minimum drag coefficient. The aerodynamics calculation of flow field around the body of revolution is determined to get accurate drag coefficient. An effective numerical calculation called the Finite Volume Method is considered. For the laminar to turbulent transition locations, the linear stability analysis is applied to predict the natural transition location. The results were compared with those obtained from integral method and also experimental results and indicate a good agreement. It is concluded that for the purpose of the shape optimization of streamline bodies, the Genetic Algorithms and the Finite Volume Method with natural transition criterion is an essential approaches to indicate the optimal shape for various ranges of Reynolds number.