WAKESET: A Large-Scale, High-Reynolds Number Flow Dataset for Machine Learning of Turbulent Wake Dynamics
Paper
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2602.01379
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Published
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numpy>=1.21.0
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pandas>=1.3.0
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scipy>=1.7.0
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matplotlib>=3.4.0
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xarray>=0.20.0
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WAKESET is a large-scale CFD dataset of turbulent wake flow fields around a generalized XLUUV geometry, spanning forward speed and turning angle parameterizations.
CUBE_128 (regular 128×128×128 Cartesian grid; ML-friendly volumetric tensors)VERTPLN and HORZPLN (planar exports / slices on the CFD mesh or interpolated grids, depending on file type)Examples/Python/ (loader scripts and minimal usage examples)Forward_[VVVV]_ms_Angle_[AA]_[TYPE]_[SUFFIX]
VVVV: forward speed in mm/s (e.g., 5000 = 5.00 m/s)AA: yaw angle in degrees (e.g., 20)TYPE: CUBE_128, VERTPLN, HORZPLN (and/or your specific suffix variants)u, v, w [m/s]v_mag [m/s]p_total, p_abs, p_dyn [Pa]omega_mag [1/s]I [%]license: cc-by-4.0).LICENSE for full terms.If you use WAKESET, please:
@dataset{wakeset,
title = {WAKESET: A Large-Scale, High-Reynolds Number Flow Dataset for Machine Learning of Turbulent Wake Dynamics},
author = {Cooper-Baldock, Zachary and Santos, Paulo E. and Brinkworth, Russell S. A. and Sammut, Karl},
year = {2026},
publisher = {Hugging Face},
note = {CC BY 4.0},
url = {https://huggingface.co/datasets/ZacharyCB99/WAKESET}
doi = {10.57967/hf/7698}
}
@article{wakeset_paper,
title = {WAKESET: A Large-Scale, High-Reynolds Number Flow Dataset for Machine Learning of Turbulent Wake Dynamics},
author = {Cooper-Baldock, Zachary and Santos, Paulo E. and Brinkworth, Russell S. A. and Sammut, Karl},
year = {2026},
eprint = {arXiv:2602.01379},
archivePrefix = {arXiv},
primaryClass = {physics.flu-dyn}
doi = {10.48550/arXiv.2602.01379}
}