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Computational fluid dynamics (CFD), is used in the GM Racing NASCAR program to support race team operations and aerodynamic research projects. To function as a practical tool, the setup process for industrial CFD tools must use real engineering models of race vehicles and must realistically simulate on-track aerodynamic conditions. Then, these tools must provide realistic simulation for high-Reynolds number flow over the complex geometry of a real race car. The biggest challenge to CFD tools is accurate prediction in regions of separated turbulent flow, such as flow in the wake and underbody regions. These regions have a significant effect on race vehicle performance. Because of the critical nature of separated turbulent regions both for better understanding of vehicle aerodynamics and for evaluating accuracy of the CFD results, these regions warrant detailed study.

A new process is developed for the aerodynamic shape optimization of racing cars using Computational Fluid Dynamics (CFD). The process is based on using the mesh morphing techniques to create new designs for analysis by morphing the CFD mesh of the original design. The resulting improvements in the analysis turnaround time allow a quick exploration of the design parameters for determining the optimum aerodynamic design. The approach is used to perform a parametric study to optimize a racing car shape for maximum downforce. The analysis procedure used for the CFD analysis is tuned to ensure grid independence and accuracy of the predictions. The parametric study shows that the morpher-based process can quickly and precisely create designs for the CFD analysis. This process can become the foundation for the automated aerodynamic design optimization of the racing cars.