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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.

A common fan model to use in automotive under hood simulations is the Multiple Reference Frame (MRF) model and within the industry, for this specific application, this model is well known to under predict performance. In a former paper, referenced 2009-01-0178, a simple “speed correction” of the MRF model was proposed by the authors'. The correction was shown to apply across different operating speeds for a specific fan. In this paper the generality and limitation of this correction across fans of different type, design and dimensions are investigated. Investigated in this paper is as well the sensitivity of the MRF model to specific methodology of use. In this paper it is shown that the speed correction of 14% proposed in the former paper applies widely, hence, although the MRF model is erroneous the error is consistent.

The objective of this paper is to investigate whether different appearance modes of the digital human models (DHM or manikins) affect the observers when judging a working posture. A case where the manikin is manually assembling a battery in the boot with help of a lifting device is used in the experiment. 16 different pictures were created and presented for the subjects. All pictures have the same background, but include a unique posture and manikin appearance combination. Four postures and four manikin appearances were used. The subjects were asked to rank the pictures after ergonomic assessment based on posture of the manikin. Subjects taking part in the study were either manufacturing engineering managers, simulation engineers or ergonomists. Results show that the different appearance modes affect the ergonomic judgment. A more realistic looking manikin is rated higher than the very same posture visualized with a less natural appearance.