For auto makers, the ability to accurately simulate turbulence helps to create quieter, more slippery and more fuel-efficient vehicles.
The airflow around a car is always turbulent, particularly in the critical boundary layer the few millimeters closest to the vehicle’s surface and in the vehicle’s wake. Not only that, but a turbulent flow is transient, as opposed to steady-state: it continuously changes with time. Smoke wands show this in a wind tunnel, and the phenomenon is reflected in the measurements that aerodynamicists record during tunnel testing.
Logically, any digital simulation of airflow ought to take account of its transient nature if we want to accurately replicate real-world behavior. If you ignore the transient nature of the airflow, it is impossible to predict what the aerodynamic force on the car will be.
At Exa, we believe that the turbulence model at the heart of our PowerFLOW software simulates turbulence far better than rival codes. We can calculate how the turbulent vortices interact with the car and evolve around it, then use that information to very accurately predict the air pressure distribution around the car.
Accurately predicting the aerodynamic forces is crucial to delivering the low drag coefficients (CD figures) that are helping auto makers to reduce their vehicles’ fuel consumption. By modeling how turbulence changes with time, PowerFLOW can provide unmatched simulation accuracy of ±1 count (equivalent to a CD of 0.001), as opposed to an estimated ±30 counts for the steady-state codes, which equates to about a 5% error in the predicted fuel economy.
Collectively known as the Lattice Boltzmann method, this is the most efficient numerical scheme for simulating transient flows, making PowerFLOW faster and more robust at simulating transient flows than rival codes, which are all based on Reynolds-Averaged Navier-Stokes (RANS) equations. RANS cannot deliver the level of accuracy the ±1 count that automotive customers are now demanding.
November 13, 2015