Spectrally Decomposed Diffusion Models for Generative Turbulence Recovery

We investigate the statistical recovery of missing physics and turbulent phenomena in fluid flows using generative machine learning. Here we develop a two-stage super-resolution method using spectral filtering to restore the high-wavenumber components of a Kolmogorov flow. We include a rigorous exam...

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Bibliographische Detailangaben

Hauptverfasser:	Sardar, Mohammed, Skillen, Alex, Zimoń, Małgorzata J, Draycott, Samuel, Revell, Alistair
Format:	Artikel
Sprache:	eng
Schlagworte:	Physics - Computational Physics Physics - Fluid Dynamics
Online-Zugang:	Volltext bestellen
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