Development of a Reduced-Order Method for the CFD-Based Aerodynamic Performance Analysis of a Formula One Car.
Figure 1: CFD-based aerodynamic performance prediction of the Formula 1 car.
This project involves the development of a reduced-order model (ROM) technique to be used to speed up the CFD-based aerodynamic design of the Toyota Formula 1 car. Preliminary numerical results show a reduction of 5 in the computational cost.

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Charbel Bou-Mosleh

Because of the constant introduction of various rules limiting engine power, Formula 1 --- the pinnacle of motor racing technology --- has become all about aerodynamics. While wind tunnels remain the most important aerodynamic design tool, Computational Fluid Dynamics (CFD) has emerged as a serious capability for gaining insight into the behavior of configurations that are impractical in a wind tunnel. CFD has also become the preferred if not exclusive tool for the detailed design of components such as mirrors and front wing endplates. It is now also accepted as a complementary design capability for minimum drag or maximum downforce.

To obtain fairly accurate results, high-fidelity CFD models have to be built (more than 26 millions nodes). This currently requires a few weeks to complete. This means that during the off-season (3 to 4 months), the design engineers are capable of building and testing a few car concepts which usually leads to misjudging the best concept to use during the season (see fig. 1).

To this end, this project is focused on developing a set of numerical tools for the preliminary aerodynamic design of the Formula 1 car based on advanced reduced-order modeling (ROM) technologies. The objective is to obtain a reduction in computational cost of at least one order of magnitude. This will allow the engineers to build and test more concepts and eventually decide on the best one.