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Realizability-Informed Machine Learning for Turbulence Anisotropy Mappings

Fuente: arXiv

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Dettagli Bibliografici
Autori principali:	McConkey, Ryley, Kalia, Nikhila, Yee, Eugene, Lien, Fue-Sang
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Fluid Dynamics Computational Physics
Accesso online:	Acceder al recurso
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