Both blowing and suction crossing the boundary layer have been widely implemented on the airfoils top surface to control the flow field. These techniques have significant effects on the aerodynamic characteristics of the airfoil. Both methods were applied to Selig–Donovan 7003 (SD7003) airfoil at Reynolds number of 60,000. An optimization technique was used to find the optimum parameters of blowing/suction using genetic algorithm (GA). Considering that computational fluid dynamics CFD is time-consuming for determination of the objective function, an artificial neural network was coupled with GA in order to achieve this aim. We used aerodynamic performance, defined as lift to drag ratio (L/D), as the objective function to find the optimal configuration. Results showed that application of active flow control methods caused a reduction in flow separation zone which resulted in improvement of aerodynamic coefficients. Moreover, it was found that suction was more effective than blowing as a control mechanism.
