Datasets › DrivAerNet

DrivAerNet (A Parametric Car Dataset for Data-driven Aerodynamic Design and Graph-Based Drag Prediction)

Introduced by Mohamed Elrefaie et al. in DrivAerNet: A Parametric Car Dataset for Data-Driven Aerodynamic Design and Prediction12 Mar 2024 archive 2025-07-28

DrivAerNet is a large-scale, high-fidelity CFD dataset of 3D industry-standard car shapes designed for data-driven aerodynamic design. It comprises 4000 high-quality 3D car meshes and their corresponding aerodynamic performance coefficients, alongside full 3D flow field information.

It includes:

  • CFD Simulation Data: The raw dataset, including full 3D pressure, velocity fields, and wall-shear stresses, computed using 8-16 million mesh elements has a total size of ∼ 16TB.
  • Curated CFD Simulations: For ease of access and use, a streamlined version of the CFD simulation data is provided, refined to include key insights and data, reducing the size to ∼ 1TB.
  • 3D Car Meshes: A total of 4000 designs, showcasing a variety of conventional car shapes and emphasizing the impact of minor geometric modifications on aerodynamic efficiency. The 3D meshes and aerodynamic coefficients ∼ 84GB.
  • 2D slices include the car's wake in the x-direction and the symmetry plane in the y-direction ∼ 12GB.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 4 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • DrivAerNet

1 variant name, as the archive lists them.

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