Beyond actuator line arrays in active flow control studies: Lessons from a genetic algorithm approach

Active flow control with microjets in crossflow is a promising technology to improve the performance of many engineering flows. Predicting effective placement for the microjets at the surface of the aerodynamic model remains an unsolved challenge due to the complex interactions between the jets and the main flow. We propose and demonstrate a fully experimental, model-free approach using a solenoid array and a genetic algorithm to find a highly effective actuator pattern for drag reduction in the flow over a simplified fuselage afterbody, deploying thousands of actuator configurations in a single experiment and reaching a configuration that achieves a 10% reduction in drag.