Sensitivity analysis for best-estimate thermal models of vertical dry cask storage systems
Abstract
Loading requirements for dry cask storage of spent nuclear fuel are driven primarily by decay heat capacity limitations, which themselves are determined through recommended limits on peak cladding temperature within the cask. This study examines the relative sensitivity of peak material temperatures within the cask to parameters that influence both the stored fuel residual decay heat as well as heat removal mechanisms. Here, these parameters include the detailed reactor operating history parameters (e.g., soluble boron concentrations and the presence of burnable poisons) as well as factors that influence heat removal, including non-dominant processes (such as conduction from the fuel basket to the canister and radiation within the canister) and ambient environmental conditions. By examining the factors that drive heat removal from the cask alongside well-understood factors that drive decay heat, it is therefore possible to make a contextual analysis of the most important parameters to evaluation of peak material temperatures within the cask.
- Authors:
-
- Univ. of Tennessee, Knoxville, TN (United States)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Publication Date:
- Research Org.:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Nuclear Energy (NE)
- OSTI Identifier:
- 1376326
- Alternate Identifier(s):
- OSTI ID: 1550433
- Grant/Contract Number:
- AC05-00OR22725
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Nuclear Engineering and Design
- Additional Journal Information:
- Journal Volume: 320; Journal Issue: C; Journal ID: ISSN 0029-5493
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS; 22 GENERAL STUDIES OF NUCLEAR REACTORS; COBRA-SFS; Dry cask storage; Used nuclear fuel; Peak clad temperature; Sensitivity analysis
Citation Formats
DeVoe, Remy R., Robb, Kevin R., and Skutnik, Steven E. Sensitivity analysis for best-estimate thermal models of vertical dry cask storage systems. United States: N. p., 2017.
Web. doi:10.1016/j.nucengdes.2017.06.005.
DeVoe, Remy R., Robb, Kevin R., & Skutnik, Steven E. Sensitivity analysis for best-estimate thermal models of vertical dry cask storage systems. United States. https://doi.org/10.1016/j.nucengdes.2017.06.005
DeVoe, Remy R., Robb, Kevin R., and Skutnik, Steven E. Sat .
"Sensitivity analysis for best-estimate thermal models of vertical dry cask storage systems". United States. https://doi.org/10.1016/j.nucengdes.2017.06.005. https://www.osti.gov/servlets/purl/1376326.
@article{osti_1376326,
title = {Sensitivity analysis for best-estimate thermal models of vertical dry cask storage systems},
author = {DeVoe, Remy R. and Robb, Kevin R. and Skutnik, Steven E.},
abstractNote = {Loading requirements for dry cask storage of spent nuclear fuel are driven primarily by decay heat capacity limitations, which themselves are determined through recommended limits on peak cladding temperature within the cask. This study examines the relative sensitivity of peak material temperatures within the cask to parameters that influence both the stored fuel residual decay heat as well as heat removal mechanisms. Here, these parameters include the detailed reactor operating history parameters (e.g., soluble boron concentrations and the presence of burnable poisons) as well as factors that influence heat removal, including non-dominant processes (such as conduction from the fuel basket to the canister and radiation within the canister) and ambient environmental conditions. By examining the factors that drive heat removal from the cask alongside well-understood factors that drive decay heat, it is therefore possible to make a contextual analysis of the most important parameters to evaluation of peak material temperatures within the cask.},
doi = {10.1016/j.nucengdes.2017.06.005},
journal = {Nuclear Engineering and Design},
number = C,
volume = 320,
place = {United States},
year = {Sat Jul 08 00:00:00 EDT 2017},
month = {Sat Jul 08 00:00:00 EDT 2017}
}
Web of Science