Optimization of airfoil flow control using a genetic algorithm with diversity control

The aerospace community is on the verge of a new generation of practical active flow control devices, from synthetic jets to plasma actuators. However, even as the mechanical challenges of implementing these systems seem attainable, the proper placement, orientation, and energy inputs to achieve the maximum benefit in a variety of flow conditions are often poorly known. Successful application of computational fluid dynamics to this type of control problem critically depends on an efficient searching algorithm for design optimization. Based on our previous research of single-suction/blowing-jet control on a NACA 0012 airfoil, the design parameters of a test two-jet system are proposed. A genetic algorithm drives the computational fluid dynamics simulations, guiding the configuration of a suction jet and a blowing jet on the airfoil's upper surface. Reasonable optimum control values are determined within the control parameter range, and the sensitivity of the control values can be determined through a comparison of the fitness value from a large number of computational fluid dynamics simulations.