Optimization of NACA 0012 Airfoil Performance in Dynamics Stall Using Continuous Suction Jet

Abstract

Abstract Many different active flow control methods are used to manipulate the flow field about aerodynamic surfaces in order to obtain the most desirable aerodynamic performance. Among these techniques, boundary layer suction is one of the most effective techniques used to improve aerodynamic performance of the airfoil. In this study, the configuration of a pure suction jet actuator is optimized over an oscillating NACA0012 airfoil at the Reynolds number of 1.35 × 105 to control the dynamic stall behavior. The airfoil was pitched around the quarter-chord location with a sinusoidal motion and the angle of attack was varied between −5 and 25 degrees. Genetic algorithm was implemented as the optimization method. However, since large number of numerical simulations were required for this purpose, an artificial neural network was employed for training a function between the control parameters and the airfoil aerodynamic coefficients. Aerodynamic performance defined as lift-to-drag ratio was chosen as the objective function of the optimization. Location, velocity amplitude, opening length and jet incidence angle were the control parameters of this optimization. It was shown that when the velocity amplitude and opening length were maximum, the airfoil reached its highest performance. Moreover, the aerodynamic characteristics of the airfoil were remarkably improved when the jet incident angle approached to 90 degrees. Placing the suction jet actuator in the range between 3 to 6 percent of the airfoil chord, was found to have the greatest effect on improving the aerodynamic performance. For the optimum configuration, the airfoil separation. It was shown that when the velocity amplitude and opening length were maximum, the airfoil reached its highest performance. Moreover, the aerodynamic characteristics of the airfoil were peaked in the range between 90 to 120 degrees, with 107 having the best performance in our database.