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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.

The aerodynamic properties of a full-scale car have been investigated in a wind-tunnel with upstream boundary layer suction, and in a water-basin where the car was rolling on the bottom. Measurements were carried out of the drag and lift forces, the static pressure distribution on the car body and the total head distribution between the car and the ground. By comparing data from the tunnel and the basin the ground simulation technique could be evaluated. The measured drag coefficients were found to be very similar in both facilities, while the absolute values of the lift coefficients were considerably higher in the tunnel. Lift differences due to configuration changes of the upperbody were essentially the same in the two facilities, while changes of the underbody caused smaller lift differences in the tunnel. In the project the water-basin technique was thoroughly investigated and proven.