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A detailed Design of Experiments (DOE) study is presented to understand the aerodynamic effects of exterior design features and shape parameters of a pick-up truck using Computational Fluid Dynamics (CFD). The goal of the study is to characterize several key design parameters and the interactions between them as related to overall drag of the vehicle. Using this data, the exterior shape is optimized to minimize drag within specified design constraints. An adaptive sampling methodology is also presented that progressively reduces errors in the design response surfaces generated. This combined with a Latin Hypercube based initial design space characterization yields computational efficiency. A trend-predictive meta-model is presented that can be used for early design development. Results from the meta-model are also correlated with experimental data from the wind tunnel.

Pickup trucks are designed with a taller ride height and a larger tire envelope compared to other vehicle types given the duty cycle and environment they operate in. These differences play an important role in the flow field around spinning wheels and tires and their interactions with the vehicle body. From an aerodynamics perspective, understanding and managing this flow field are critical for drag reduction, wheel design, and brake cooling. Furthermore, the validation of numerical simulation methodology is essential for a systematic approach to aerodynamically efficient wheel design as a standard practice of vehicle design. This paper presents a correlation the near-wheel flow field for both front and rear spinning wheels with two different wheel designs for a Ram Quad Cab pick-up truck with moving ground. Twelve-hole probe experimental data obtained in a wind tunnel with a full width belt system are compared to the predictions of numerical simulations.