Flow field recovery in restricted domains using a generative adversarial network framework

This study aims to reconstruct the complete flow field from spatially restricted domain data by utilizing an enhanced super-resolution generative adversarial network (ESRGAN) model. The difficulty in flow field reconstruction lies in accurately capturing and reconstructing large amounts of data unde...

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Veröffentlicht in:	Physics of fluids (1994) 2024-12, Vol.36 (12)
Hauptverfasser:	Yousif, Mustafa Z., Mohammadikarachi, Arash
Format:	Artikel
Sprache:	eng
Schlagworte:	Channel flow Computational efficiency Computing costs Data recovery Density Direct numerical simulation Domain names Flow mapping Fluid dynamics Fluid flow Generative adversarial networks Image quality Image reconstruction Laminar flow Local flow Particle image velocimetry Reynolds number Statistical analysis Turbulence Turbulent flow Velocity distribution
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