Coarse-grained models for prediction, uncertainty quantification, and extreme event statistics of turbulent flows in engineering and geophysical settings using physics-consistent data-driven closures
Modeling and analysis of turbulent fluid flows remains one of the challenging areas of fluid mechanics where integration of the full equations is associated with extreme computational cost, while their simplification inevitably introduces important model errors. In this work we are aiming to answer...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2023
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| Online Access: | https://hdl.handle.net/1721.1/151911 |