An optimization study was conducted to find the optimum operational characteristics of a synthetic jet actuator (SJA) to postpone the static stall separation over an SD7003 airfoil at Reynolds number of 60,000. A genetic algorithm (GA) coupled with an artificial neural network (ANN) was employed. Aerodynamic performance (L/D) was chosen as the objective function. Both tangent to the boundary layer (TBL) and the cross to the boundary layer (CBL) configurations of SJA were used and their effectiveness in separation control were compared. The following design variables of the SJA were allowed to change within a predetermined range: location, the opening length, the injection velocity amplitude, the injection angle, and the nondimensional frequency. It was found that for location, opening length, and velocity amplitude ratio, a narrow range near the peak optimum values achieved the best performance. However, for the nondimensional frequency and jet injection angle, the optimum values providing highest performance were in a wider range of values. Activation of SJ actuator improved the aerodynamic performance of the airfoil significantly. However, TBL configuration of SJA produced superior improvement in aerodynamic performance. The optimum aerodynamic performance achieved by TBL-SJA was 34.4, in comparison to 25.3 for CBL-SJA and 5 for the uncontrolled stalled airfoil at 13 deg angle of attack.
The effects of applying a coupled unsteady blowing and suction combination over SD7003 airfoil at Reynolds number of 60,000 at an angle of attack of 13°, where a large separation on the suction side of the airfoil existed, was considered to investigate active flow control (AFC) mechanism. URANS equations were employed to solve the flow field and k–ω SST was used as the turbulence model. The unsteady blowing and suction were implemented at an angle to the surface crossing the boundary layer (CBL). The influence of location and frequency of the blowing/suction jets were examined.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.