In our last article, we discussed how the aerodynamic performance of a race car is analysed based on the various sources of on-track data and the driver’s feedback. Today, we will discuss the correlation between track and predictive tools.

For the purpose of this article, we describe aerodynamic correlation as the level of agreement between the flow measured in the wind tunnel or calculated through simulations, to the real-life conditions in the track. For aerodynamicists, good correlation means they can be confident that the surfaces developed using a wind tunnel and CFD will translate into performance for the race car.

Determining the levels of correlation across the domains is a highly challenging task. The first and main obstacle is obtaining clear and conclusive performance data from the race car, as discussed in the previous article.

A second obstacle, not technically challenging but resource-consuming, is matching the operating conditions from the race car during the on-track measurements to the wind tunnel and CFD measurements. Examples of variables that typically need to be matched are the front/rear ride heights, yaw, steer, roll and flow curvature.

A third obstacle relates to the differences in the modelling across the predictive tools. The limitations of the wind tunnel often discussed are the scale, blockage, wall constraints, Reynolds number discrepancies, lack of flow curvature and others. However, from our experience, the dominant factor affecting the wind tunnel and track correlation relates to the geometry itself. Examples of relevant discrepancies are the tyre and contact patch shapes, aero surfaces deformation under load, internal flow blockage, and the presence of strut and belt roughness.

Within the CFD domain, the limitations related to the domain discretisation and simplifications applied to the turbulence modelling are well advertised and will not be discussed here. However, one of CFD’s significant advantages is that many of the geometrical modelling challenges from the wind tunnel can be easily addressed. This means that CFD can be turned into a much more accurate representation of the geometry and operating conditions on the track.

Each tool predicts the car’s performance better in some areas and operating conditions than others. Therefore, it is crucial for aerodynamicists to understand each tool’s limitations and how to best use the wind tunnel and CFD in a combined manner to achieve robust aerodynamic designs that translate into performance on the track where it matters most.