license: odbl
tags:
- AirfRANS
- computational fluid dynamics
- flow field prediction
language:
- en
- zh
AirfRANS
Dataset Description
AirfRANS is a high-fidelity two-dimensional airfoil CFD dataset introduced in a paper from the NeurIPS 2022 Datasets and Benchmarks Track. The data is intended for surrogate modeling of the incompressible steady-state Reynolds-averaged Navier-Stokes (RANS) equations and contains 1,000 subsonic airfoil simulation cases.
The cases cover NACA four-digit and five-digit airfoils, with Reynolds numbers ranging from 2 million to 6 million and angles of attack ranging from -5° to 15°.
Supported Tasks
| Scenario | Description |
|---|---|
| CFD surrogate modeling | Predict flow fields from airfoil geometry, boundary conditions, and fluid parameters. |
| Full-data training | Learn airfoil flow behavior using the complete training set. |
| Data-scarce training | Perform surrogate modeling with a limited number of training cases. |
| Parameter extrapolation evaluation | Evaluate model generalization to unseen Reynolds numbers or angles of attack. |
Dataset Format and Structure
The data is organized by case:
data/Dataset/
manifest.json
<case>/
<case>_internal.vtu
<case>_freestream.vtp
<case>_aerofoil.vtp
Each case contains a volume mesh, far-field boundary data, and airfoil surface data:
| File | VTK Type | Main Fields | Description |
|---|---|---|---|
<case>_internal.vtu |
UnstructuredGrid |
U, p, nut, implicit_distance |
Volume-domain velocity, pressure, turbulent kinematic viscosity, and implicit distance. |
<case>_freestream.vtp |
PolyData |
U, p, nut |
Far-field boundary flow data. |
<case>_aerofoil.vtp |
PolyData |
Normals, U, p, nut |
Airfoil surface normals and flow data. |
manifest.json records the dataset splits for tasks such as full, scarce, reynolds, and aoa. The VTK files use XML format, and mesh sizes vary by case.
How to Use the Dataset
This dataset has been adapted for the OneScience-Group/Transolver-Airfoil-Design model. Download the dataset and model:
hf download --dataset OneScience-Group/airfrans --local-dir ./data
Official OneScience Information
| Platform | OneScience Main Repository | Skills Repository |
|---|---|---|
| Gitee | https://gitee.com/onescience-ai/onescience | https://gitee.com/onescience-ai/oneskills |
| GitHub | https://github.com/onescience-ai/OneScience | https://github.com/onescience-ai/oneskills |
Citation and License
- Original AirfRANS paper: AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier–Stokes Solutions
- This dataset is organized from the original AirfRANS data and is licensed under the same ODbL-1.0 license.