Wind tunnel evaluation-based optimization for improvement of flow control by plasma actuator using kriging model-based genetic algorithm

Abstract

A Kriging-based genetic algorithm (GA) called efficient global optimization (EGO) was employed to optimize the parameters for the operating conditions of a plasma actuator (PA). The aerodynamic performance was evaluated by wind tunnel testing to overcome the disadvantages of time-consuming numerical simulations. The developed optimization system explores the optimum waveform of parameters for AC voltage by changing the waveform automatically. The proposed system was used on the drag minimization problem around a semicircular cylinder to design the power supply for a PA. Based on the results, the optimum design and global design information were obtained while drastically reducing the number of experiments required compared to a full factorial experiment.