Generative adversarial networks to infer velocity components in rotating turbulent flows

ABSTRACT: Inference problems for two-dimensional snapshots of rotating turbulent flows are studied. We perform a systematic quantitative benchmark of point-wise and statistical reconstruction capabilities of the linear Extended Proper Orthogonal Decomposition (EPOD) method, a nonlinear Convolutional...

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Detalles Bibliográficos
Autores principales: Li, Tianyi, Buzzicotti, Michele, Biferale, Luca, Bonaccorso, Fabio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Regular Article - Flowing Matter
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10160208/
https://www.ncbi.nlm.nih.gov/pubmed/37140827
http://dx.doi.org/10.1140/epje/s10189-023-00286-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10160208/
https://www.ncbi.nlm.nih.gov/pubmed/37140827
http://dx.doi.org/10.1140/epje/s10189-023-00286-7

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