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

Title: Reduced-order modeling: using machine learning to enable large-scale simulation for many query problems.

Abstract

Abstract not provided.

Authors:
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1505388
Report Number(s):
SAND2018-3249PE
661891
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Conference
Resource Relation:
Conference: Proposed for presentation at the Advanced Modeling & Simulation Seminar Series held March 29, 2018 in Mountain View, CA.
Country of Publication:
United States
Language:
English

Citation Formats

Carlberg, Kevin Thomas. Reduced-order modeling: using machine learning to enable large-scale simulation for many query problems.. United States: N. p., 2018. Web.
Carlberg, Kevin Thomas. Reduced-order modeling: using machine learning to enable large-scale simulation for many query problems.. United States.
Carlberg, Kevin Thomas. Thu . "Reduced-order modeling: using machine learning to enable large-scale simulation for many query problems.". United States. https://www.osti.gov/servlets/purl/1505388.
@article{osti_1505388,
title = {Reduced-order modeling: using machine learning to enable large-scale simulation for many query problems.},
author = {Carlberg, Kevin Thomas},
abstractNote = {Abstract not provided.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {3}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share: