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Title: Statistically based uncertainty analysis for ranking of component importance in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor

Abstract

The Analytic Hierarchy Process (AHP) has been used to help determine the importance of components and phenomena in thermal-hydraulic safety analyses of nuclear reactors. The AHP results are based, in part on expert opinion. Therefore, it is prudent to evaluate the uncertainty of the AHP ranks of importance. Prior applications have addressed uncertainty with experimental data comparisons and bounding sensitivity calculations. These methods work well when a sufficient experimental data base exists to justify the comparisons. However, in the case of limited or no experimental data the size of the uncertainty is normally made conservatively large. Accordingly, the author has taken another approach, that of performing a statistically based uncertainty analysis. The new work is based on prior evaluations of the importance of components and phenomena in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor (ANSR), a new facility now in the design phase. The uncertainty during large break loss of coolant, and decay heat removal scenarios is estimated by assigning a probability distribution function (pdf) to the potential error in the initial expert estimates of pair-wise importance between the components. Using a Monte Carlo sampling technique, the error pdfs are propagated through the AHP software solutions tomore » determine a pdf of uncertainty in the system wide importance of each component. To enhance the generality of the results, study of one other problem having different number of elements is reported, as are the effects of a larger assumed pdf error in the expert ranks. Validation of the Monte Carlo sample size and repeatability are also documented.« less

Authors:
Publication Date:
Research Org.:
EG and G Idaho, Inc., Idaho Falls, ID (United States)
Sponsoring Org.:
USDOE, Washington, DC (United States)
OSTI Identifier:
10139074
Report Number(s):
EGG-NE-10078
ON: DE92012311
DOE Contract Number:  
AC07-76ID01570
Resource Type:
Technical Report
Resource Relation:
Other Information: PBD: Jan 1992
Country of Publication:
United States
Language:
English
Subject:
22 GENERAL STUDIES OF NUCLEAR REACTORS; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; RESEARCH REACTORS; SAFETY ANALYSIS; HEAT TRANSFER; HYDRAULICS; DATA COVARIANCES; REACTOR COMPONENTS; REACTOR SAFETY; MONTE CARLO METHOD; DISTRIBUTION FUNCTIONS; AFTER-HEAT REMOVAL; LOSS OF COOLANT; PROBABILITY; STATISTICAL DATA; 220900; 220600; 990200; RESEARCH, TEST, TRAINING, PRODUCTION, IRRADIATION, MATERIALS TESTING REACTORS; MATHEMATICS AND COMPUTERS

Citation Formats

Wilson, G E. Statistically based uncertainty analysis for ranking of component importance in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor. United States: N. p., 1992. Web. doi:10.2172/10139074.
Wilson, G E. Statistically based uncertainty analysis for ranking of component importance in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor. United States. https://doi.org/10.2172/10139074
Wilson, G E. 1992. "Statistically based uncertainty analysis for ranking of component importance in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor". United States. https://doi.org/10.2172/10139074. https://www.osti.gov/servlets/purl/10139074.
@article{osti_10139074,
title = {Statistically based uncertainty analysis for ranking of component importance in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor},
author = {Wilson, G E},
abstractNote = {The Analytic Hierarchy Process (AHP) has been used to help determine the importance of components and phenomena in thermal-hydraulic safety analyses of nuclear reactors. The AHP results are based, in part on expert opinion. Therefore, it is prudent to evaluate the uncertainty of the AHP ranks of importance. Prior applications have addressed uncertainty with experimental data comparisons and bounding sensitivity calculations. These methods work well when a sufficient experimental data base exists to justify the comparisons. However, in the case of limited or no experimental data the size of the uncertainty is normally made conservatively large. Accordingly, the author has taken another approach, that of performing a statistically based uncertainty analysis. The new work is based on prior evaluations of the importance of components and phenomena in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor (ANSR), a new facility now in the design phase. The uncertainty during large break loss of coolant, and decay heat removal scenarios is estimated by assigning a probability distribution function (pdf) to the potential error in the initial expert estimates of pair-wise importance between the components. Using a Monte Carlo sampling technique, the error pdfs are propagated through the AHP software solutions to determine a pdf of uncertainty in the system wide importance of each component. To enhance the generality of the results, study of one other problem having different number of elements is reported, as are the effects of a larger assumed pdf error in the expert ranks. Validation of the Monte Carlo sample size and repeatability are also documented.},
doi = {10.2172/10139074},
url = {https://www.osti.gov/biblio/10139074}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Jan 01 00:00:00 EST 1992},
month = {Wed Jan 01 00:00:00 EST 1992}
}