Deployment of Multifidelity Uncertainty Quantification for Thermal Battery Assessment Part I: Algorithms and Single Cell Results
- Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
This report documents the results of an FY22 ASC V&V level 2 milestone demonstrating new algorithms for multifidelity uncertainty quantification. Part I of the report describes the algorithms, studies their performance on a simple model problem, and then deploys the methods to a thermal battery example from the open literature. Part II (restricted distribution) applies the multifidelity UQ methods to specific thermal batteries of interest to the NNSA/ASC program.
- Research Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- DOE Contract Number:
- NA0003525
- OSTI ID:
- 1885882
- Report Number(s):
- SAND2022-11856; 709525
- Country of Publication:
- United States
- Language:
- English
Similar Records
Efficient algorithms for mixed aleatory-epistemic uncertainty quantification with application to radiation-hardened electronics. Part I, algorithms and benchmark results.
Multifidelity uncertainty quantification with models based on dissimilar parameters
Leveraging Intrinsic Principal Directions for Multifidelity Uncertainty Quantification
Technical Report
·
Tue Sep 01 00:00:00 EDT 2009
·
OSTI ID:1885882
Multifidelity uncertainty quantification with models based on dissimilar parameters
Journal Article
·
Sat Aug 05 00:00:00 EDT 2023
· Computer Methods in Applied Mechanics and Engineering
·
OSTI ID:1885882
+3 more
Leveraging Intrinsic Principal Directions for Multifidelity Uncertainty Quantification
Technical Report
·
Sat Sep 01 00:00:00 EDT 2018
·
OSTI ID:1885882