Aerodynamic Research by Computational Fluid Dynamics

In 1998, Dr Adrian Reynard founded Advantage CFD Ltd in order to explore aero solutions that were not easily researched in either wind tunnel development or full scale data acquisition on board the vehicle.

Dr Robert Lewis was recruited to lead this campaign and he immediately discovered that CFD was not only useful for these discreet gains, but also a vital tool in the aerodynamicists toolbox for validation and thought provocation.

One of the biggest appreciators was the Honda Racing F1 Team which is also co-owned by Dr Adrian Reynard. By 2002 the A-CFD team had grown to over 20 staff and as well as many commercial client applications throughout the transportation industry, Honda Racing had also grown quite dependent for its valuable contribution to the Honda Racing F1 car development. So Honda Racing bought A-CFD Ltd.

The A-CFD team still consults to the transportation industry whilst being exclusive to Honda in the F1 field. Dr Adrian Reynard firmly believes that this is a technology of the future. He addressed the 5th MIRA Vehicle Aerodynamic Conference in October 2004 and featured some of the award winning CFD movies that he had helped spawn and also more recent research released from Honda Racing F1 Team who had just powered themselves to second place (to Ferrari) in the FIA Formula 1 Constructors Championship.

“I am convinced that our understanding of Computational Fluid Dynamics has complemented our car and helped us catch-and-beat established teams such as Williams and McLaren. Aerodynamics is of “first order” importance in understanding how to extract better efficiencies from all aspects of the F1 car and I am convinced that these techniques will have a much wider application in any area of vehicle research.”

In the side bar are some samples of the movies. The colours can represent pressures or velocities. These are not just pretty videos since the true geometry of the car is created by CAD and mesh first so that any position can be interrogated for real data. Real-time results can be evaluated an a configuration change can be much faster than by other data-collection methods. The optimum design can therefore be solved for very rapidly.