Physics-Informed Super-Resolution of Turbulent Channel Flows via Three-Dimensional Generative Adversarial Networks

For a few decades, machine learning has been extensively utilized for turbulence research. The goal of this work is to investigate the reconstruction of turbulence from minimal or lower-resolution datasets as inputs using reduced-order models. This work seeks to effectively reconstruct high-resoluti...

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מידע ביבליוגרפי
מחבר ראשי: Nicholas J. Ward
פורמט: Article
שפה:English
יצא לאור: MDPI AG 2023-06-01
סדרה:Fluids
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גישה מקוונת:https://www.mdpi.com/2311-5521/8/7/195