Data-driven physical fields reconstruction of supercritical-pressure flow in regenerative cooling channel using POD-AE reduced-order model

•A novel data-driven reduced-order model framework combining proper orthogonal decomposition-based reduced-order modeling method and autoencoder neural network is proposed.•A data-driven POD-AE reduced-order model of 3D regenerative cooling channel is established for the first time.•This framework a...

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Bibliographic Details

Published in:	International journal of heat and mass transfer Vol. 217; p. 124699
Main Authors:	Jiang, Wenwei, Pan, Tao, Jiang, Genghui, Sun, Zhaoyou, Liu, Huayu, Zhou, Zhiyuan, Ruan, Bo, Yang, Kai, Gao, Xiaowei
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 15.12.2023
Subjects:	Autoencoder neural network Kriging model Physical fields estimation Reduced-order model Supercritical pressure Physical fields estimation Kriging model Autoencoder neural network Reduced-order model Supercritical pressure
ISSN:	0017-9310, 1879-2189
Online Access:	Get full text
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