NVIDIA's PhysicsNeMo-CFD adds a benchmark for car-aero surrogates and four pretrained checkpoints

NVIDIA's PhysicsNeMo-CFD module, released with PhysicsNeMo 26.05, scores pretrained models on DrivAerML or a user's own dataset with L2 errors on pressure, turbulent viscosity and velocity, and drag and lift coefficient errors. Pretrained checkpoints for GeoTransolver, DoMINO, MeshGraphNet and FigConvNet are published on Hugging Face. The post argues for shared datasets, metrics and leaderboards so that domain experts can test physical consistency and edge cases themselves.

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