Reduced-order deep learning for flow dynamics. The interplay between deep learning and model reduction
Type
Journal articleSubject
Science & TechnologyTechnology
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
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https://hdl.handle.net/10161/20371Published Version (Please cite this version)
10.1016/j.jcp.2019.108939Publication Info
(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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Show full item recordScholars@Duke
Min Wang
Phillip Griffiths Assistant Research Professor
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