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Machine Learning for Fluid Mechanics
[article]
2019
arXiv
pre-print
The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from experiments, field measurements, and large-scale simulations at multiple spatiotemporal scales. Machine learning presents us with a wealth of techniques to extract information from data that can 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
arXiv:1905.11075v2
fatcat:brszpilzezc3xmbttdcla7zome