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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.

In the 1955 Le Mans race the worst crash in motor racing history occurred and this accident would change the face of motor racing for decades. After the crash numerous investigations on the disaster were performed, and fifty years after some interesting books were launched on the subject. However, a number of key questions remain unsolved; and one open area is the influence of aerodynamics on the scenario, since the Mercedes-Benz 300 SLR involved in the crash was equipped with an air-brake and its influence on the accident is basically unknown. This work may be considered as a first attempt to establish CFD as a tool to aid in resolving aerodynamic aspects in motor sport accidents and in the present paper, CFD has been used to investigate the aerodynamics and estimate the drag and lift coefficients of the Mercedes-Benz 300 SLR used in the Le Mans race of 1955.