Machine Learning for Fluid Mechanics

@article{Brunton2019MachineLF,
  title={Machine Learning for Fluid Mechanics},
  author={S. Brunton and B. R. Noack and P. Koumoutsakos},
  journal={ArXiv},
  year={2019},
  volume={abs/1905.11075}
}
The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from field measurements, experiments and large-scale simulations at multiple spatiotemporal scales. Machine learning offers a wealth of techniques to extract information from data that could be translated into knowledge about the underlying fluid mechanics. Moreover, machine learning algorithms can augment domain knowledge and automate tasks related to flow control and optimization. This article presents… Expand
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