Emerging trends in machine learning for computational fluid dynamics

November 28, 2022 ยท Declared Dead ยท ๐Ÿ› 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 1 month 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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