A methodology for uncertainty quantification and sensitivity analysis for responses subject to Monte Carlo uncertainty with application to fuel plate characteristics in the ATRC

Price, Dean; Maile, Andrew; Peterson-Droogh, Joshua; Blight, Derreck

doi:10.1016/j.net.2021.09.010

Title: A methodology for uncertainty quantification and sensitivity analysis for responses subject to Monte Carlo uncertainty with application to fuel plate characteristics in the ATRC

Journal Article · 01 March 2022 · Nuclear Engineering and Technology

DOI: https://doi.org/10.1016/j.net.2021.09.010 · OSTI ID:1819808

; Maile, Andrew; Peterson-Droogh, Joshua; Blight, Derreck

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Sponsoring Organization:: USDOE Office of Nuclear Energy (NE)

Grant/Contract Number:: AC07-05ID14517

OSTI ID:: 1819808

Journal Information:: Nuclear Engineering and Technology, Journal Name: Nuclear Engineering and Technology Journal Issue: 3 Vol. 54; ISSN 1738-5733

Publisher:: ElsevierCopyright Statement

Country of Publication:: Korea, Republic of

Language:: English

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Uncertainty estimation for multivariate regression coefficients Faber, Nicolaas (Klaas) M. Chemometrics and Intelligent Laboratory Systems, Vol. 64, Issue 2 https://doi.org/10.1016/S0169-7439(02)00102-8	journal	November 2002
ENDF/B-VII.1 Nuclear Data for Science and Technology: Cross Sections, Covariances, Fission Product Yields and Decay Data Chadwick, M. B.; Herman, M.; Obložinský, P. Nuclear Data Sheets, Vol. 112, Issue 12 https://doi.org/10.1016/j.nds.2011.11.002	journal	December 2011
Uncertainty Propagation with Fast Monte Carlo Techniques Rochman, D.; van der Marck, S. C.; Koning, A. J. Nuclear Data Sheets, Vol. 118 https://doi.org/10.1016/j.nds.2014.04.082	journal	April 2014
Decay heat uncertainty for BWR used fuel due to modeling and nuclear data uncertainties Ilas, Germina; Liljenfeldt, Henrik Nuclear Engineering and Design, Vol. 319 https://doi.org/10.1016/j.nucengdes.2017.05.009	journal	August 2017
Advanced BWR criticality safety part I: Model development, model benchmarking, and depletion with uncertainty analysis Radaideh, Majdi I.; Price, Dean; O'Grady, Daniel Progress in Nuclear Energy, Vol. 113 https://doi.org/10.1016/j.pnucene.2019.01.010	journal	May 2019
Advanced BWR criticality safety part II: Cask criticality, burnup credit, sensitivity, and uncertainty analyses Price, Dean; Radaideh, Majdi I.; O'Grady, Daniel Progress in Nuclear Energy, Vol. 115 https://doi.org/10.1016/j.pnucene.2019.03.039	journal	August 2019
Survey of sampling-based methods for uncertainty and sensitivity analysis Helton, J. C.; Johnson, J. D.; Sallaberry, C. J. Reliability Engineering & System Safety, Vol. 91, Issue 10-11 https://doi.org/10.1016/j.ress.2005.11.017	journal	October 2006
Monte-Carlo based uncertainty analysis: Sampling efficiency and sampling convergence Janssen, Hans Reliability Engineering & System Safety, Vol. 109 https://doi.org/10.1016/j.ress.2012.08.003	journal	January 2013
A Comparison of Sensitivity Analysis Techniques Hamby, D. M. Health Physics, Vol. 68, Issue 2 https://doi.org/10.1097/00004032-199502000-00005	journal	January 1995
The International Criticality Safety Benchmark Evaluation Project Briggs, J. Blair; Scott, Lori; Nouri, Ali Nuclear Science and Engineering, Vol. 145, Issue 1 https://doi.org/10.13182/NSE03-14	journal	September 2003
Sensitivity and Uncertainty Analysis Capabilities and Data in SCALE Rearden, B. T.; Williams, M. L.; Jessee, M. A. Nuclear Technology, Vol. 174, Issue 2 https://doi.org/10.13182/NT174-236	journal	May 2011
Atomic weights of the elements 2013 (IUPAC Technical Report) Meija, Juris; Coplen, Tyler B.; Berglund, Michael Pure and Applied Chemistry, Vol. 88, Issue 3 https://doi.org/10.1515/pac-2015-0305	journal	March 2016
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