Machine learning in viscoelastic fluids via energy-based kernel embedding
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Publication:6615024
DOI10.1016/j.jcp.2024.113371MaRDI QIDQ6615024
Fabio V. G. Amaral, J. Nathan Kutz, Samuel E. Otto, Steven L. Brunton, Cassio M. Oishi
Publication date: 8 October 2024
Published in: Journal of Computational Physics (Search for Journal in Brave)
principal component analysiskernel methodmachine learningreproducing kernel Hilbert spaceviscoelastic flowenergy-based inner product
Basic methods in fluid mechanics (76Mxx) Artificial intelligence (68Txx) Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems (65Mxx)
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