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The effect of an active flow control method is investigated on a 1:4 scale realistic vehicle model called “DrivAer” with notchback geometry. The wind tunnel experiments are conducted at a Reynolds number of Re=3.0·106. Fluidic oscillators are applied at the c-pillars and at the upper rear edge of the window. The actuators are installed inside the hollow designed model emitting a high frequency sweeping jet. The spacing of the actuators, the mass flow rate, and the position of actuation are varied. The effect of the active flow control on the car is investigated with force and surface pressure measurements. The surface trace pattern is visualized with tufts for the active flow control cases and the baseline case. A tuft algorithm analyzes provides statistical data of the flow angles. Moreover, particle image velocimetry measurements are performed in the plane of symmetry for β=0° to capture the flow field at the rear end and the wake.

Flow visualization techniques are widely used in aerodynamics to investigate the surface trace pattern. In this experimental investigation, the surface flow pattern over the rear end of a full-scale passenger car is studied using tufts. The movement of the tufts is recorded with a DSLR still camera, which continuously takes pictures. A novel and efficient tuft image processing algorithm has been developed to extract the tuft orientations in each image. This allows the extraction of the mean tuft angle and other such statistics. From the extracted tuft angles, streamline plots are created to identify points of interest, such as saddle points as well as separation and reattachment lines. Furthermore, the information about the tuft orientation in each time step allows studying steady and unsteady flow phenomena. Hence, the tuft image processing algorithm provides more detailed information about the surface flow than the traditional tuft method.