This is an exciting opportunity to work on applying Machine Learning (ML) for extreme scale simulations of high Reynolds number turbulent flows on Aurora — the first exa-scale computing platform in the United States. The extreme levels of parallelism available on Aurora create unique optimization challenges for both the CFD solver as well as the ML layer that will be used to learn and develop sub-grid models for turbulence simulations using Hybrid RANS/LES techniques. This research had the potential to revolutionize the development of sub-grid models for high Reynolds number separated flows.
Required Skills Valued and Developed Over the Life of the Project (but not required at start)
Skills Valued and Developed Over the Life of the Project (but not required at start)
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