Neural network based pore flow field prediction in porous media using super resolution

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dc.contributor.authorZhou, Xu-Hui X.en
dc.contributor.authorMcClure, Jamesen
dc.contributor.authorChen, Chengen
dc.contributor.authorXiao, Hengen
dc.date.accessioned2022-02-16T15:17:59Zen
dc.date.available2022-02-16T15:17:59Zen
dc.date.issued2021en
dc.date.updated2022-02-16T15:17:57Zen
dc.description.abstractPrevious works have demonstrated using the geometry of the microstructure of porous media to predict the ow velocity fields therein based on neural networks. However, such schemes are purely based on geometric information without accounting for the physical constraints on the velocity fields such as that due to mass conservation. In this work, we propose using a super-resolution technique to enhance the velocity field prediction by utilizing coarse-mesh velocity fields, which are often available inexpensively but carry important physical constraints. We apply our method to predict velocity fields in complex porous media. The results demonstrate that incorporating the coarse-mesh flow field significantly improves the prediction accuracy of the fine-mesh flow field as compared to predictions that rely on geometric information alone. This study highlights the merits of including coarse-mesh flow field with physical constraints embedded in it.en
dc.description.versionSubmitted versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.orcidXiao, Heng [0000-0002-3323-4028]en
dc.identifier.urihttp://hdl.handle.net/10919/108374en
dc.language.isoenen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subject0102 Applied Mathematicsen
dc.subject0203 Classical Physicsen
dc.subject0913 Mechanical Engineeringen
dc.titleNeural network based pore flow field prediction in porous media using super resolutionen
dc.title.serialPhysical Review Fluidsen
dc.typeArticleen
dc.type.dcmitypeTexten
dc.type.otherArticleen
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Engineeringen
pubs.organisational-group/Virginia Tech/Engineering/Aerospace and Ocean Engineeringen
pubs.organisational-group/Virginia Tech/University Research Institutesen
pubs.organisational-group/Virginia Tech/University Research Institutes/Fralin Life Sciencesen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Engineering/COE T&R Facultyen
pubs.organisational-group/Virginia Tech/University Research Institutes/Fralin Life Sciences/Durelle Scotten

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