Efficient global optimization of vortex generators on a supercritical infinite wing

Multi-objective optimization of vortex generators on a transonic infinite wing is performed using computational fluid dynamics and a multi-objective genetic algorithm coupled with surrogate models. Vortex generator arrangements are defined by five design variables: height, length, incidence angle, chord location, and spacing. The objective functions are to maximize the lift-to-drag ratio at low angle of attack, to maximize lift coefficient at high angle of attack, and to the shift chordwise separation location downstream at high angle of attack.To evaluate these objective functions of each individual in the multi-objective genetic algorithm, the ordinary kriging surrogate model and the radial-basis-function/kriging hybrid surrogate model are employed because numerical analysis of the wing with vortex generators requires a large amount of computational time. Nondominated solutions are classified into five clusters with different aerodynamic characteristics. Comparison of the five clusters revealed that the balance among three objective functions is controlled mainly by vortex generator height, spacing, and their ratio. The solutions in each cluster have specific values of these three parameters, which identify the aerodynamic characteristics. In addition, appropriate values of design variables for generating the vortex most effectively are investigated.