A turbulence reduced order model based on non-interpolated convolutional autoencoder

Reduced-order modeling stands as a pivotal method in curbing the computational expenses linked with expansive fluid dynamics quandaries by employing proxy numerical simulations. Within this realm, downscaling and reconstruction methods serve as fundamental constituents of reduced-order modeling. The...

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Vydané v:	Xibei Gongye Daxue Xuebao Ročník 43; číslo 1; s. 149 - 153
Hlavní autori:	WU, Pin, ZHANG, Bo, SONG, Chao, ZHOU, Zhu
Médium:	Journal Article
Jazyk:	Chinese English
Vydavateľské údaje:	EDP Sciences 01.02.2025
Predmet:	non-interpolated convolutional autoencoder reduced-dimensional reconstruction reduced-order model
ISSN:	1000-2758, 2609-7125
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