Skip to main content
U.S. Department of Energy
Office of Scientific and Technical Information

Machine Learning Uncertainty Quantification for Reduced Order Models of Hypersonic Flows.

Conference ·
OSTI ID:1766909

Abstract not provided.

Research Organization:
Sandia National Laboratories (SNL-CA), Livermore, CA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
DOE Contract Number:
AC04-94AL85000
OSTI ID:
1766909
Report Number(s):
SAND2020-2014C; 683981
Country of Publication:
United States
Language:
English

Similar Records

Uncertainty Quantification for Machine Learning and Statistical Models.
Conference · Tue Feb 28 23:00:00 EST 2017 · OSTI ID:1456317

Machine Learning for Uncertainty Quantification in Turbulent Flow Simulations.
Conference · Thu Dec 31 23:00:00 EST 2015 · OSTI ID:1338869

Machine-learned reduced-order modeling.
Conference · Thu Aug 01 00:00:00 EDT 2019 · OSTI ID:1645802

Related Subjects