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---
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},
}
``` |