Uncertainties in Predictions of Material Performance Using Experimental Data That Is Only Distantly Related to the System of Interest
Abstract
There is a need for predictive material “aging” models in the nuclear energy industry, where applications include life extension of existing reactors, the development of high burnup fuels, and dry cask storage of used nuclear fuel. These problems require extrapolating from the validation domain, where there is available experimental data, to the application domain, where there is little or no experimental data. The need for predictive material aging models will drive the need for associated assessments of the uncertainties in the predictions. Methods to quantify uncertainties in model predictions, using experimental data that is only distantly related to the application domain, are discussed.
- Authors:
-
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Consulting Engineer, Georgetown, TX (United States)
- Publication Date:
- Research Org.:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1502011
- Report Number(s):
- LLNL-JRNL-513477
Journal ID: ISSN 1868-4238; 538149
- Grant/Contract Number:
- AC52-07NA27344
- Resource Type:
- Accepted Manuscript
- Journal Name:
- IFIP Advances in Information and Computer Technology
- Additional Journal Information:
- Journal Volume: 377; Journal Issue: none; Journal ID: ISSN 1868-4238
- Publisher:
- Springer
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS; 97 MATHEMATICS AND COMPUTING; uncertainty quantification; model form uncertainty; model uncertainty; nuclear energy; neutron damage; ion damage; irradiation effects scaling; extrapolation
Citation Formats
King, Wayne E., Arsenlis, Athanasios, Tong, Charles, and Oberkampf, William L. Uncertainties in Predictions of Material Performance Using Experimental Data That Is Only Distantly Related to the System of Interest. United States: N. p., 2012.
Web. doi:10.1007/978-3-642-32677-6_19.
King, Wayne E., Arsenlis, Athanasios, Tong, Charles, & Oberkampf, William L. Uncertainties in Predictions of Material Performance Using Experimental Data That Is Only Distantly Related to the System of Interest. United States. https://doi.org/10.1007/978-3-642-32677-6_19
King, Wayne E., Arsenlis, Athanasios, Tong, Charles, and Oberkampf, William L. Sun .
"Uncertainties in Predictions of Material Performance Using Experimental Data That Is Only Distantly Related to the System of Interest". United States. https://doi.org/10.1007/978-3-642-32677-6_19. https://www.osti.gov/servlets/purl/1502011.
@article{osti_1502011,
title = {Uncertainties in Predictions of Material Performance Using Experimental Data That Is Only Distantly Related to the System of Interest},
author = {King, Wayne E. and Arsenlis, Athanasios and Tong, Charles and Oberkampf, William L.},
abstractNote = {There is a need for predictive material “aging” models in the nuclear energy industry, where applications include life extension of existing reactors, the development of high burnup fuels, and dry cask storage of used nuclear fuel. These problems require extrapolating from the validation domain, where there is available experimental data, to the application domain, where there is little or no experimental data. The need for predictive material aging models will drive the need for associated assessments of the uncertainties in the predictions. Methods to quantify uncertainties in model predictions, using experimental data that is only distantly related to the application domain, are discussed.},
doi = {10.1007/978-3-642-32677-6_19},
journal = {IFIP Advances in Information and Computer Technology},
number = none,
volume = 377,
place = {United States},
year = {Sun Jan 01 00:00:00 EST 2012},
month = {Sun Jan 01 00:00:00 EST 2012}
}
Free Publicly Available Full Text
Publisher's Version of Record
Other availability
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.