Machine learning to construct reduced-order models and scaling laws for reactive-transport applications
- Authors:
-
- Los Alamos National Laboratory
- Publication Date:
- Research Org.:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE Office of Environmental Management (EM)
- OSTI Identifier:
- 1412919
- Report Number(s):
- LA-UR-17-31172
- DOE Contract Number:
- AC52-06NA25396
- Resource Type:
- Conference
- Resource Relation:
- Conference: AGU ; 2017-12-11 - 2017-12-15 ; New Orleans, Louisiana, United States
- Country of Publication:
- United States
- Language:
- English
- Subject:
- Earth Sciences; Energy Sciences; Machine learning, reactive-transport, reduced-order models
Citation Formats
Mudunuru, Maruti Kumar, Karra, Satish, and Vesselinov, Velimir Valentinov. Machine learning to construct reduced-order models and scaling laws for reactive-transport applications. United States: N. p., 2017.
Web.
Mudunuru, Maruti Kumar, Karra, Satish, & Vesselinov, Velimir Valentinov. Machine learning to construct reduced-order models and scaling laws for reactive-transport applications. United States.
Mudunuru, Maruti Kumar, Karra, Satish, and Vesselinov, Velimir Valentinov. 2017.
"Machine learning to construct reduced-order models and scaling laws for reactive-transport applications". United States. https://www.osti.gov/servlets/purl/1412919.
@article{osti_1412919,
title = {Machine learning to construct reduced-order models and scaling laws for reactive-transport applications},
author = {Mudunuru, Maruti Kumar and Karra, Satish and Vesselinov, Velimir Valentinov},
abstractNote = {},
doi = {},
url = {https://www.osti.gov/biblio/1412919},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Dec 12 00:00:00 EST 2017},
month = {Tue Dec 12 00:00:00 EST 2017}
}
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