Use of a machine learning model for a constitutive chemistry model within a groundwater flow and transport application modeling nuclear fuel degradation in a waste repository.
Abstract not provided.
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE Office of Nuclear Energy (NE), Fuel Cycle Technologies (NE-5)
- DOE Contract Number:
- NA0003525
- OSTI ID:
- 2002228
- Report Number(s):
- SAND2022-4181C; 704782
- Country of Publication:
- United States
- Language:
- English
Similar Records
Machine learning constitutive models.
Machine Learning Surrogates for Fuel Degradation Processes in Nuclear Waste Repository Simulations
Machine Learning Surrogate Process Models for Efficient Performance Assessment of a Nuclear Waste Repository.
Conference
·
Sun Aug 01 00:00:00 EDT 2021
·
OSTI ID:1883538
Machine Learning Surrogates for Fuel Degradation Processes in Nuclear Waste Repository Simulations
Conference
·
Sat Jul 01 00:00:00 EDT 2023
·
OSTI ID:2430768
Machine Learning Surrogate Process Models for Efficient Performance Assessment of a Nuclear Waste Repository.
Conference
·
Tue Nov 01 00:00:00 EDT 2022
·
OSTI ID:2006027