README.md

---
title: AirfRANS remeshed visualization
emoji: 🏆
colorFrom: purple
colorTo: pink
sdk: gradio
sdk_version: 5.16.0
app_file: app.py
pinned: false
license: mit
---

This space provides a visualization of the dataset created in [the paper](https://arxiv.org/abs/2212.07564):

```
@misc{bonnet2023airfranshighfidelitycomputational,
      title={AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier-Stokes Solutions}, 
      author={Florent Bonnet and Ahmed Jocelyn Mazari and Paola Cinnella and Patrick Gallinari},
      year={2023},
      eprint={2212.07564},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2212.07564}, 
}
```

This dataset is used in [the paper](https://arxiv.org/abs/2305.12871), and available at at [huggingface](https://huggingface.co/datasets/PLAID-datasets/AirfRANS_remeshed) and [Zenodo](https://zenodo.org/records/14840388).

```
@misc{casenave2023mmgpmeshmorphinggaussian,
      title={MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under non-parameterized geometrical variability}, 
      author={Fabien Casenave and Brian Staber and Xavier Roynard},
      year={2023},
      eprint={2305.12871},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2305.12871}, 
}
```