Emerging trends in machine learning for computational fluid dynamics
November 28, 2022 Β· Declared Dead Β· π Computing in science & engineering (Print)
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Authors
Ricardo Vinuesa, Steve Brunton
arXiv ID
2211.15145
Category
physics.flu-dyn
Cross-listed
cs.LG
Citations
24
Venue
Computing in science & engineering (Print)
Last Checked
3 months ago
Abstract
The renewed interest from the scientific community in machine learning (ML) is opening many new areas of research. Here we focus on how novel trends in ML are providing opportunities to improve the field of computational fluid dynamics (CFD). In particular, we discuss synergies between ML and CFD that have already shown benefits, and we also assess areas that are under development and may produce important benefits in the coming years. We believe that it is also important to emphasize a balanced perspective of cautious optimism for these emerging approaches
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