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DimensionLab

Datasets

DrivAerML

High-fidelity CFD data for variations of the DrivAer vehicle.

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About DrivAerML

DrivAerML contains parametrically morphed DrivAer notchback geometries and hybrid RANS-LES simulations. Surface and volume fields are accompanied by geometry parameters and force coefficients for research into automotive aerodynamics models.

  • Study geometry-conditioned prediction on realistic vehicle shapes.
  • Access surface and volume fields, STL and STEP geometry.
  • Relate field predictions to aerodynamic quantities such as drag.

Before you use it

Third-party dataset indexed by Frontier Hub. A listing does not imply that every Frontier benchmark has been validated on this dataset. Read the original license and data card.

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