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Reduced-order deep learning for flow dynamics. The interplay between deep learning and model reduction

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Date
2020-01
Authors
Wang, Min
Cheung, Siu Wun
Leung, Wing Tat
Chung, Eric T
Efendiev, Yalchin
Wheeler, Mary
Repository Usage Stats
29
views
75
downloads
Type
Journal article
Subject
Science & Technology
Technology
Physical Sciences
Computer Science, Interdisciplinary Applications
Physics, Mathematical
Computer Science
Physics
Multiscale
Upscaling
Porous media
Deep learning
Dynamics
FINITE-ELEMENT METHODS
MULTISCALE MODEL
UNCERTAINTY QUANTIFICATION
WAVE-PROPAGATION
HOMOGENIZATION
EFFICIENT
NETWORKS
Permalink
https://hdl.handle.net/10161/20371
Published Version (Please cite this version)
10.1016/j.jcp.2019.108939
Publication Info
Wang, Min; Cheung, Siu Wun; Leung, Wing Tat; Chung, Eric T; Efendiev, Yalchin; & Wheeler, Mary (2020). Reduced-order deep learning for flow dynamics. The interplay between deep learning and model reduction. Journal of Computational Physics, 401. pp. 108939-108939. 10.1016/j.jcp.2019.108939. Retrieved from https://hdl.handle.net/10161/20371.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
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Scholars@Duke

Wang

Min Wang

Phillip Griffiths Assistant Research Professor
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