Upgrading Limiting PeakPower Analysis Techniques with Modern Validation and Uncertainty Quantification for the Advanced Test Reactor
Abstract
Here, this work demonstrates the acceptability of the 2D deterministic transport code, HELIOS, to replace the legacy diffusion code, PDQ, for computing the peakpower performance parameters of the Advanced Test Reactor (ATR). The 95% Confidence Rule, commonly used in the commercial reactor sector, is explored to develop the socalled “reliability factors” which provide statistical confidence that the peakpower limits within the hottest location along a fuel plate, referred to as the hotstripe, will not be exceeded. Additionally, an alternative “legacy” methodology was explored that attempts to mimic the exact PDQ analysis process used for defining the peakpower limits. The legacy methodology, involves interpolating power between regions at azimuthal boundaries subtending the regions of interest. In order to apply the 95% Confidence Rule, a statistically significant calculationtomeasurement bias must first be established. Unlike the commercial world where thousands of power observations can be collected every cycle using online flux mapping instrumentation, the ATR power distribution must be measured during “depressurized” zeropower measurements using fission wires in polyethylene wands. In 2012, fission wire activation data was collected during a flux run in the Advanced Test Reactor – Critical facility. Also to improve statistical validity, archival data from ATR zero power flux runsmore »
 Authors:

 Idaho National Lab. (INL), Idaho Falls, ID (United States)
 Publication Date:
 Research Org.:
 Idaho National Lab. (INL), Idaho Falls, ID (United States)
 Sponsoring Org.:
 USDOE Office of Nuclear Energy (NE)
 OSTI Identifier:
 1473711
 Report Number(s):
 INL/JOU1741057Rev000
Journal ID: ISSN 00295450
 Grant/Contract Number:
 AC0705ID14517
 Resource Type:
 Accepted Manuscript
 Journal Name:
 Nuclear Technology
 Additional Journal Information:
 Journal Volume: 201; Journal Issue: 3; Journal ID: ISSN 00295450
 Publisher:
 Taylor & Francis  formerly American Nuclear Society (ANS)
 Country of Publication:
 United States
 Language:
 English
 Subject:
 21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS; Advanced Test Reactor; Verification and Validation; Uncertainty Quantification; 95% Confidence Rule; Reliability Factor
Citation Formats
Bays, Samuel E., Davis, Cliff B., and Archibald, Periann A.. Upgrading Limiting PeakPower Analysis Techniques with Modern Validation and Uncertainty Quantification for the Advanced Test Reactor. United States: N. p., 2018.
Web. doi:10.1080/00295450.2017.1415091.
Bays, Samuel E., Davis, Cliff B., & Archibald, Periann A.. Upgrading Limiting PeakPower Analysis Techniques with Modern Validation and Uncertainty Quantification for the Advanced Test Reactor. United States. https://doi.org/10.1080/00295450.2017.1415091
Bays, Samuel E., Davis, Cliff B., and Archibald, Periann A.. Fri .
"Upgrading Limiting PeakPower Analysis Techniques with Modern Validation and Uncertainty Quantification for the Advanced Test Reactor". United States. https://doi.org/10.1080/00295450.2017.1415091. https://www.osti.gov/servlets/purl/1473711.
@article{osti_1473711,
title = {Upgrading Limiting PeakPower Analysis Techniques with Modern Validation and Uncertainty Quantification for the Advanced Test Reactor},
author = {Bays, Samuel E. and Davis, Cliff B. and Archibald, Periann A.},
abstractNote = {Here, this work demonstrates the acceptability of the 2D deterministic transport code, HELIOS, to replace the legacy diffusion code, PDQ, for computing the peakpower performance parameters of the Advanced Test Reactor (ATR). The 95% Confidence Rule, commonly used in the commercial reactor sector, is explored to develop the socalled “reliability factors” which provide statistical confidence that the peakpower limits within the hottest location along a fuel plate, referred to as the hotstripe, will not be exceeded. Additionally, an alternative “legacy” methodology was explored that attempts to mimic the exact PDQ analysis process used for defining the peakpower limits. The legacy methodology, involves interpolating power between regions at azimuthal boundaries subtending the regions of interest. In order to apply the 95% Confidence Rule, a statistically significant calculationtomeasurement bias must first be established. Unlike the commercial world where thousands of power observations can be collected every cycle using online flux mapping instrumentation, the ATR power distribution must be measured during “depressurized” zeropower measurements using fission wires in polyethylene wands. In 2012, fission wire activation data was collected during a flux run in the Advanced Test Reactor – Critical facility. Also to improve statistical validity, archival data from ATR zero power flux runs from 1977, 1986, and 1994 were digitized from scanned reports and used to create new benchmark models. Borrowing from leastsquares adjustment methods commonly used for neutron activation spectroscopy, adjusted fission wire powers were calculated for all four datasets. The mean and standard deviation of the bias between a priori calculated and adjusted wirepowers was then taken as the bias and uncertainty used in the 95% Confidence Rule.},
doi = {10.1080/00295450.2017.1415091},
journal = {Nuclear Technology},
number = 3,
volume = 201,
place = {United States},
year = {2018},
month = {2}
}
Web of Science
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Works referenced in this record:
On measuring skewness and kurtosis
journal, September 2007
 Đorić, Dragan; NikolićĐorić, Emilija; Jevremović, Vesna
 Quality and Quantity, Vol. 43, Issue 3
A fission matrix based validation protocol for computed power distributions in the advanced test reactor
journal, December 2015
 Nielsen, Joseph W.; Nigg, David W.; LaPorta, Anthony W.
 Nuclear Engineering and Design, Vol. 295
An Extension of Shapiro and Wilk's W Test for Normality to Large Samples
journal, January 1982
 Royston, J. P.
 Applied Statistics, Vol. 31, Issue 2
An analysis of variance test for normality (complete samples)
journal, December 1965
 Shapiro, S. S.; Wilk, M. B.
 Biometrika, Vol. 52, Issue 34
Experimental Statistics
journal, January 1952
 Hader, R. J.; Youden, W. J.
 Analytical Chemistry, Vol. 24, Issue 1
An Analysis of Variance Test for Normality (Complete Samples)
journal, December 1965
 Shapiro, S. S.; Wilk, M. B.
 Biometrika, Vol. 52, Issue 3/4
Experimental Statistics.
journal, June 1964
 H., C.; Natrella, Mary Gibbons
 Journal of the American Statistical Association, Vol. 59, Issue 306
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