PhysicsX releases PX-Car-Aero-v1, a car-aerodynamics model pre-trained on 33,203 RANS simulations

PhysicsX makes PX-Car-Aero-v1 available on its platform: a model for external car aerodynamics pre-trained on PXNetCar, which now holds 33,203 RANS k-omega SST simulations from 444 baseline vehicles with a median of 88 morphed variants each. It predicts drag and lift coefficients, surface pressure and wall shear stress, and volume pressure and velocity. The post compares fine-tuning with training the same architecture from scratch. On a production SUV with a 21-parameter design space simulated with DES, fine-tuning needs roughly 84.4% fewer simulations to reach 85% directional accuracy on drag; on DrivAerML, with 5 training and 2 validation simulations, it reaches 90% against 70% from scratch. PhysicsX states that accuracy degrades on genuinely new designs on every metric. No weights, code or data are released.

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