skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: A multiscale multi-permeability poroplasticity model linked by recursive homogenizations and deep learning

Authors:
; ORCiD logo
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1548754
Grant/Contract Number:  
NE0008534
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
Computer Methods in Applied Mechanics and Engineering
Additional Journal Information:
Journal Name: Computer Methods in Applied Mechanics and Engineering Journal Volume: 334 Journal Issue: C; Journal ID: ISSN 0045-7825
Publisher:
Elsevier
Country of Publication:
Netherlands
Language:
English

Citation Formats

Wang, Kun, and Sun, WaiChing. A multiscale multi-permeability poroplasticity model linked by recursive homogenizations and deep learning. Netherlands: N. p., 2018. Web. https://doi.org/10.1016/j.cma.2018.01.036.
Wang, Kun, & Sun, WaiChing. A multiscale multi-permeability poroplasticity model linked by recursive homogenizations and deep learning. Netherlands. https://doi.org/10.1016/j.cma.2018.01.036
Wang, Kun, and Sun, WaiChing. Fri . "A multiscale multi-permeability poroplasticity model linked by recursive homogenizations and deep learning". Netherlands. https://doi.org/10.1016/j.cma.2018.01.036.
@article{osti_1548754,
title = {A multiscale multi-permeability poroplasticity model linked by recursive homogenizations and deep learning},
author = {Wang, Kun and Sun, WaiChing},
abstractNote = {},
doi = {10.1016/j.cma.2018.01.036},
journal = {Computer Methods in Applied Mechanics and Engineering},
number = C,
volume = 334,
place = {Netherlands},
year = {2018},
month = {6}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1016/j.cma.2018.01.036

Citation Metrics:
Cited by: 45 works
Citation information provided by
Web of Science

Save / Share: