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The applicability of high-performance computing (HPC) to vehicle aerodynamics is presented using a Cartesian grid approach of computational fluid dynamics. Methodology that allows the user to avoid a large amount of manual work in preparing geometry is indispensable in HPC simulation whereas conventional methodologies require much manual work. The new frame work allowing a solver to treat ‘dirty’ computer-aided-design data directly was developed with a modified immersed boundary method. The efficiency of the calculation of the vehicle aerodynamics using HPC is discussed. The validation case of flow with a high Reynolds number around a sphere is presented. The preparation time for the calculation is approximately 10 minutes. The calculation time for flow computation is approximately one-tenth of that of conventional unstructured code.

The drag reduction effect was investigated with regard to the bed and rear flap variation for a pickup truck through design of experiments process. The design factors were the bed length, bed height, rear flap length, and flap inset with three levels, and the noise factor was the yaw angle. The signal-to-noise ratio calculation was introduced to evaluate the low-drag performance under a crosswind. Analysis of variance indicated the significant interaction effect between the bed length and bed height. Since the bed flow of the short with low bed was attached to the tailgate, which increased the drag coefficient and lowered the S/N ratio. The rear flap add-on at the rear edge of a roof was effective to reduce the drag coefficient. However, the sensitivity of the flap length variation on the drag reduction was not significant. The flap inset had a negative effect on the drag reduction as it lowered the inset area pressure of the cabin back surface.