Steve Brunton: Machine Learning for Fluid Dynamics

Channel:
Canada LLMs Explained - Aggregate Intellect - AI.SCIENCE
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Published on ● Video Link: https://www.youtube.com/watch?v=20vB4MzAbCw


Duration: 1:20:15
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For slides and more information on the paper, visit https://ai.science/e/machine-learning-for-fluid-dynamics--U8rVB9u6KpUAErZf09Fd

Speaker: Steve Brunton; Host: Sajeda Mokbel

Check out Doctor Brunton's YouTube channel: https://www.youtube.com/channel/UCm5mt-A4w61lknZ9lCsZtBw

Motivation:
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 (ML) offers a wealth of techniques to extract information from data that can be translated into knowledge about the underlying fluid mechanics. Moreover, ML algorithms can augment domain knowledge and automate tasks related to flow control and optimization. This article presents an overview of past history, current developments, and emerging opportunities of ML for fluid mechanics.


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