Surrogate Modeling of Spent Fuel Degradation for Repository Performance Assessment.
Abstract not provided.
- Research Organization:
- Sandia National Laboratories (SNL-CA), Livermore, CA (United States); Sandia National Laboratories, Albuquerque, NM
- Sponsoring Organization:
- USDOE Office of Nuclear Energy (NE), Fuel Cycle Technologies (NE-5)
- DOE Contract Number:
- NA0003525;
- OSTI ID:
- 1854307
- Report Number(s):
- SAND2021-2451C; 694434
- Resource Type:
- Conference presentation
- Conference Information:
- Proposed for presentation at the Society for Industrial and Applied Mathematics (SIAM) Conference on Computational Science and Engineering (CSE21) held March 1-5, 2021 in Virtual / Originally Fort Worth.
- Country of Publication:
- United States
- Language:
- English
Similar Records
Machine Learning Surrogate Process Models for Efficient Performance Assessment of a Nuclear Waste Repository.
Machine Learning Surrogate Process Models for Efficient Performance Assessment of a Nuclear Waste Repository.
Machine Learning Surrogate Process Models for Efficient Performance Assessment of a Nuclear Waste Repository.
Conference
·
2022
·
OSTI ID:2006027
Machine Learning Surrogate Process Models for Efficient Performance Assessment of a Nuclear Waste Repository.
Conference
·
2022
·
OSTI ID:2003752
Machine Learning Surrogate Process Models for Efficient Performance Assessment of a Nuclear Waste Repository.
Conference
·
2022
·
OSTI ID:2004293