Machine learning-based reduced-order reconstruction method for flow fields

•Design of the ROR model framework based on partial differential operators.•Extraction of low-dimensional flow field features using an autoencoder.•Combination of flow field and spatial features in low-dimensional space using a cross-fitting algorithm.•Elimination of high-dimensional redundancies an...

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Bibliographic Details

Published in:	Energy and buildings Vol. 320; p. 114575
Main Authors:	Gao, Hu, Qian, Weixin, Dong, Jiankai, Liu, Jing
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.10.2024
Subjects:	Convolutional autoencoder (CAE) Fast prediction Flow field Machine learning Reduced-order machine (ROM) Reduced-order machine (ROM) Fast prediction Flow field Convolutional autoencoder (CAE) Machine learning
ISSN:	0378-7788
Online Access:	Get full text
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