Synthetic Jet Flow Control Optimization on SD7003 Airfoil at Low Reynolds Number

Abstract

Synthetic jet crossing the boundary layer has been widely implemented on the airfoil’s top surface to control the flow field. Introducing a genetic algorithm coupled with artificial neural network (ANN) was used in this study to find optimum values for design parameters. Optimization was done for SD7003 airfoil at Reynolds number of 60,000 and angles of attack of 13° and 16°. URANS equations were employed to solve the flow field and k–ω SST was used as the turbulence model. The synthetic jets were implemented tangential to boundary layer (TBL). It was found that at optimum values of design parameters a significant improvement in aerodynamic coefficients by increasing lift and reducing drag can be achieved. Drag force reduction was achieved by reducing pressure drag at post stall and a significant reduction of separation zone.