Dynamic feature capturing in a fluid flow reduced-order model using attention-augmented autoencoders

This study looks into how adding adaptive attention to convolutional autoencoders can help reconstruct flow fields in fluid dynamics applications. The study compares the effectiveness of the proposed adaptive attention mechanism with the convolutional block attention module approach using two differ...

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Bibliographic Details

Published in:	Engineering applications of artificial intelligence Vol. 149; p. 110463
Main Authors:	Beiki, Alireza, Kamali, Reza
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.06.2025
Subjects:	Adaptive attention mechanisms Convolutional autoencoders Flow field reconstruction Reduced-order modeling Time series forecasting in fluid dynamics Convolutional autoencoders Reduced-order modeling Flow field reconstruction Time series forecasting in fluid dynamics Adaptive attention mechanisms
ISSN:	0952-1976
Online Access:	Get full text
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