Control of flow separation from a curved ramp using multiple unsteady jets
Turbulent boundary layers subjected to an adverse pressure gradient are prone to separation, resulting in increased drag and noise, along with deteriorated aerodynamic efficiency. Active flow control strategies have been shown to effectively suppress flow separation, but often at the cost of significant energy consumption. In this study, an experimental investigation is conducted to evaluate the performance of genetic algorithm-optimized unsteady jets for the control of flow separation from a curved ramp at Reθ = 5700, where Reθ is the momentum thickness-based Reynolds number. Three spanwise slit jets are deployed; a total of nine independent control parameters are optimized, including their driving pressures, duty cycles, excitation frequency, and phase differences. The cost function is designed so that separation suppression and actuation energy are compromised. Particle image velocimetry and a pressure scanner are used to characterize the controlled flows. The optimized control eliminates the recirculation region while reducing energy consumption by 76.9% relative to its steady counterpart. Furthermore, the optimization identifies the key mechanism for enhancing control effectiveness. These results demonstrate that the distributed unsteady jets offer a promising pathway toward highly efficient turbulent flow separation control.