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Notched spoilers may be used to suppress flow-induced cavity resonance in vehicles with open sunroofs or side windows. The notches are believed to generate streamwise vortices that break down the structure of the leading edge cross-stream vortices predominantly responsible for the cavity excitation. The objectives of the present study were to gain a better understanding of the buffeting suppression mechanisms associated with notched spoilers, and to gather data for computational model verification. To this end, experiments were performed to characterize the surface pressure field downstream of straight and notched spoilers mounted on a rigid wall to observe the effects of the notches on the static and dynamic wall pressure. Detailed flow velocity measurements were made using hot-wire anemometry. The results indicated that the presence of notches on the spoiler reduces drag, and thus tends to move the flow reattachment location closer to the spoiler.

The damping effect that is observed when a fibrous acoustical treatment is applied to a thin metal panel typical of automotive structures has been modeled by using three independent techniques. In the first two methods the fibrous treatment was modeled by using the limp frame formulation proposed by Bolton et al., while the third method makes use of a general poro-elastic model based on the Biot theory. All three methods have been found to provide consistent predictions that are in excellent agreement with one another. An examination of the numerical results shows that the structural damping effect results primarily from the suppression of the nearfield acoustical motion within the fibrous treatment, that motion being closely coupled with the vibration of the base panel. The observed damping effect is similar in magnitude to that provided by constrained layer dampers having the same mass per unit area as the fibrous layer.

In the past decades, automotive structure design has sought to minimize its mass while maintaining or improving structural performance. As such, topology optimization (TO) has become an increasingly popular tool during the conceptual design stage. While the designs produced by TO methods provide significant performance-to-mass ratio improvements, they require considerable computational resources when solving large-scale problems. An alternative for large-scale problems is to decompose the design domain into multiple scales that are coupled with homogenization. The problem can then be solved with hierarchical multiscale topology optimization (MSTO). The resulting optimal, homogenized macroscales are de-homogenized to obtain a high-fidelity, physically-realizable design. Even so MSTO methods are still computationally expensive due to the combined costs of solving nested optimization problems and performing de-homogenization.