SHIFT-SUV Sample: High-Fidelity Computational Fluid Dynamics Dataset for SUV External Aerodynamics

We're excited to introduce the SHIFT-SUV Sample dataset—a sample release of high-fidelity aerodynamic simulations developed as part of the Luminary SHIFT Models initiative. This dataset enables the training and benchmarking of real-time physics foundation models for automotive aerodynamics.

Website: shift.luminarycloud.com Contact: [email protected]

Summary

Physics AI foundation models can transform early stage automotive design by giving users real-time feedback on the physics-based performance implications of design decisions. However, the lack of high-quality training data has been a barrier to their development. Luminary SHIFT Models provide access to both high-quality datasets and pretrained foundation models for a variety of applications and industries.

SHIFT-SUV is a massive step forward in this direction: purpose-built for high-fidelity aerodynamic inference, without requiring CFD expertise or meshing. Developed in collaboration with Honda and NVIDIA, SHIFT-SUV is based on thousands of parametrically morphed variants of the AeroSUV vehicle platform, developed by FKFS(Forschungsinstitut für Kraftfahrwesen und Fahrzeugmotoren Stuttgart).

This repository provides access to the first 100 simulations performed within the larger SHIFT-SUV dataset, hence the qualifier "Sample". To access the full dataset, please visit the SHIFT website. This dataset supports training surface-based aerodynamic surrogate models, real-time inference systems, and exploring shape-performance correlations for automotive design.

Applications

Rapid aerodynamic prototyping and shape optimization
Research in aero-inference, point cloud learning, or physics-aware generative models
Training and fine-tuning Physics AI foundation models

Attribution

Please attribute FKFS for the original AeroSUV model, and Luminary Cloud for the SHIFT-SUV model and dataset.

An article is being prepared so users can cite this dateset - we will update this accordingly when available. Until then you can use this citation:

@misc{shift_suv_2025,
  author = {Luminary Cloud},
  title = {SHIFT-SUV Sample: High-Fidelity Computational Fluid Dynamics Dataset for SUV External Aerodynamics},
  year = {2025},
  url = {https://huggingface.co/datasets/LuminaryCloud/shift-suv-samples}
}

This dataset contains a subset of the full SHIFT-SUV dataset: the first 100 simulation results and omitting the volume solution files (to reduce the repo size). How the data was generated and the data organization in this repository are described below.

Geometry Variation

A deformation cage approach was used to morph the discrete baseline AeroSUV model. The movement of the cage vertices were organized to mimic multiple different vehicle design parameters, informed by Honda Motors, common in early stage design. These parametric modifications were applied to multiple configurations of the baseline AeroSUV (e.g., estate-back and fastback configurations). Latin hypercube sample was used to determine the specific values for the samples.

CFD Solver

All cases were run using the Luminary Cloud platform. The cases were simulated using simulation practices honed during our participation in AutoCFD4 and leveraged transient scale-resolving detached eddy simulation (DES).

Files

There are 99 "RUN_XX" directories from 01-99. In each directory you will find

merged_surfaces.stl: STL file with the vehicle's geometry
merged_surfaces.vtp: surface field solution file
[DRAG, DRAG_COEFFICIENT, LIFT, LIFT_COEFFICIENT].csv: time histories of lift and drag during the transient simulation
residuals.csv: time history of the compressible solver residuals
residuals_and_forces.png: chart image displaying time-histories from above csv files
viz: directory of images showing the geometry and flow fields

Downloading

You can use HuggingFace to gain access to the entire repository (49.5GB). Note you will need to have git lfs installed first, then run

git clone [email protected]:datasets/LuminaryCloud/shift-suv-samples

Credits

Timo Kuthada & FKFS

The AeroSUV model was developed by FKFS and provides the basis of SHIFT-SUV. The AeroSUV itself remains for non-commerical purposes only, the SHIFT-SUV dataset does not change this restriction.

Please attribute FKFS for the original AeroSUV model, and Luminary Cloud for the SHIFT-SUV model and dataset.

Fong Loon Pan & Honda

Guidance on geometry variants and industry relevant parameterization of the geometry was provided by Honda Motors.

NVIDIA

NVIDIA provided tools and infrastructure for model training via PhysicsNeMo and DoMINO. This is relevant if accessing the full dataset and pretrained models, but not this sample dataset.

License

This dataset is distributed under the CC-BY-NC-4.0 license, which is also included in the dataset itself. By downloading the dataset you acknowledge the terms of this license.

Datasets:

LuminaryCloud
/

shift-suv-samples