High-Fidelity Wind Correction for Motorsport Aero Maps
ClientSabe Fluid Dynamics
- CFD
- Machine Learning
- Aerodynamics
Result
CFD + deep neural network surrogate for real-time
site-specific wind correction
The problem
Top motorsport teams correct their aero maps using wind data from one or two fixed weather stations, applied as a single constant vector across the entire circuit. In practice, wind speed and direction vary sector to sector — grandstands, trees, and buildings all locally distort the flow — so a single-point correction is wrong everywhere except right at the sensor.
Approach
The fix combines CFD with a deep neural network. I extracted the significant terrain geometry around a circuit — grandstands, vegetation, structures — and ran CFD simulations of wind flow over it across a range of speeds, directions, and atmospheric boundary-layer profiles. That simulation data, paired with real weather-station readings, trained a DNN to act as a surrogate model: given live single-point weather data, it estimates high-fidelity wind speed and direction at every point on the circuit in real time.
Result
The surrogate model reproduces the CFD-level detail of the wind field without needing to re-run CFD live — it’s fast enough to correct aero maps during a session, not just after it.
Why it matters for your program
Any system where you have sparse real-world sensor data but need dense, physically accurate coverage — wind fields, thermal fields, pressure fields — is a candidate for this same CFD-trained-surrogate approach. It’s a way to get simulation-grade fidelity at sensor-reading speed.
Walkthrough
How it came together
- 01
Live wind data generated by the trained neural network from weather station input
- 02
CFD pressure field used to train the neural network
- 03
Turbulence and wind disturbance generated by grandstands and buildings around the circuit
Have a similar problem?
CFD + deep neural network surrogate for real-time, site-specific wind correction. Tell me what you're working on and I'll tell you directly whether and how I can help.
I reply to every enquiry within one business day.
+55 16 99785-1402