---
license: odbl
#User-Defined Tags
tags:
  - AirfRANS
  - computational fluid dynamics
  - flow field prediction
language:
  - en
  - zh
---

<p align="center">
  <strong>
    <span style="font-size: 30px;">AirfRANS</span>
  </strong>
</p>

## 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°.

Paper: [AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier–Stokes Solutions](https://proceedings.neurips.cc/paper_files/paper/2022/hash/94ab7b23a345f93333eac8748a66c763-Abstract-Datasets_and_Benchmarks.html)

## 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:

```text
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:

```bash
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](https://proceedings.neurips.cc/paper_files/paper/2022/hash/94ab7b23a345f93333eac8748a66c763-Abstract-Datasets_and_Benchmarks.html)
- This dataset is organized from the original AirfRANS data and is licensed under the same ODbL-1.0 license.