TITLE

Best Practices for Finite Element Analysis of Spent Nuclear Fuel Transfer, Storage, and Transportation Systems

AUTHOR(S)
Bajwa, Christopher S.; Piotter, Jason; Cuta, Judith; Adkins, Harold; Klymyshyn, Nicholas; Fort, James; Suffield, Sarah
PUB. DATE
January 2010
SOURCE
Proceedings of the Institute of Nuclear Materials Management Ann;2010, p1
SOURCE TYPE
Conference Proceeding
DOC. TYPE
Article
ABSTRACT
Storage casks and transportation packages for spent nuclear fuel (SNF) are designed to confine SNF in sealed canisters or casks, provide structural integrity during accidents, and remove decay through a storage or transportation overpack. The transfer, storage, and transportation of SNF in dry storage casks and transport packages is regulated under 10 CFR Part 72 and 10 CFR Part 71, respectively. Finite Element Analysis (FEA) is used with increasing frequency in Safety Analysis Reports and other regulatory technical evaluations related to SNF casks and packages and their associated systems. Advances in computing power have made increasingly sophisticated FEA models more feasible, and as a result, the need for careful review of such models has also increased. This paper identifies best practice recommendations that stem from recent NRC review experience. The scope covers issues common to all commercially available FEA software, and the recommendations are applicable to any FEA software package. Three specific topics are addressed: general FEA practices, issues specific to thermal analyses, and issues specific to structural analyses. General FEA practices covers appropriate documentation of the model and results, which is important for an efficient review process. The thermal analysis best practices are related to cask analysis for steady state conditions and transient scenarios. The structural analysis best practices are related to the analysis of casks and associated payload during standard handling and drop scenarios. The best practices described in this paper are intended to identify FEA modeling issues and provide insights that can help minimize associated uncertainties and errors, in order to facilitate the NRC licensing review process.
ACCESSION #
58108569

 

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