skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Upper Subcritical Calculations Based on Correlated Data

Abstract

The American National Standards Institute and American Nuclear Society standard for Validation of Neutron Transport Methods for Nuclear Criticality Safety Calculations defines the upper subcritical limit (USL) as “a limit on the calculated k-effective value established to ensure that conditions calculated to be subcritical will actually be subcritical.” Often, USL calculations are based on statistical techniques that infer information about a nuclear system of interest from a set of known/well-characterized similar systems. The work in this paper is part of an active area of research to investigate the way traditional trending analysis is used in the nuclear industry, and in particular, the research is assessing the impact of the underlying assumption that the experimental data being analyzed for USL calculations are statistically independent. In contrast, the multiple experiments typically used for USL calculations can be correlated because they are often performed at the same facilities using the same materials and measurement techniques. This paper addresses this issue by providing a set of statistical inference methods to calculate the bias and bias uncertainty based on the underlying assumption that the experimental data are correlated. Methods to quantify these correlations are the subject of a companion paper and will not be discussedmore » here. The newly proposed USL methodology is based on the assumption that the integral experiments selected for use in the establishment of the USL are sufficiently applicable and that experimental correlations are known. Under the assumption of uncorrelated data, the new methods collapse directly to familiar USL equations currently used. We will demonstrate our proposed methods on real data and compare them to calculations of currently used methods such as USLSTATS and NUREG/CR-6698. Lastly, we will also demonstrate the effect experiment correlations can have on USL calculations.« less

Authors:
 [1];  [1];  [1];  [1];  [1];  [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
Work for Others (WFO)
OSTI Identifier:
1215586
DOE Contract Number:  
DE-AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: ICNC, Charlotte, NC, USA, 20150913, 20150913
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING

Citation Formats

Sobes, Vladimir, Rearden, Bradley T, Mueller, Don, Marshall, William BJ J, Scaglione, John M, and Dunn, Michael E. Upper Subcritical Calculations Based on Correlated Data. United States: N. p., 2015. Web.
Sobes, Vladimir, Rearden, Bradley T, Mueller, Don, Marshall, William BJ J, Scaglione, John M, & Dunn, Michael E. Upper Subcritical Calculations Based on Correlated Data. United States.
Sobes, Vladimir, Rearden, Bradley T, Mueller, Don, Marshall, William BJ J, Scaglione, John M, and Dunn, Michael E. Thu . "Upper Subcritical Calculations Based on Correlated Data". United States. doi:. https://www.osti.gov/servlets/purl/1215586.
@article{osti_1215586,
title = {Upper Subcritical Calculations Based on Correlated Data},
author = {Sobes, Vladimir and Rearden, Bradley T and Mueller, Don and Marshall, William BJ J and Scaglione, John M and Dunn, Michael E},
abstractNote = {The American National Standards Institute and American Nuclear Society standard for Validation of Neutron Transport Methods for Nuclear Criticality Safety Calculations defines the upper subcritical limit (USL) as “a limit on the calculated k-effective value established to ensure that conditions calculated to be subcritical will actually be subcritical.” Often, USL calculations are based on statistical techniques that infer information about a nuclear system of interest from a set of known/well-characterized similar systems. The work in this paper is part of an active area of research to investigate the way traditional trending analysis is used in the nuclear industry, and in particular, the research is assessing the impact of the underlying assumption that the experimental data being analyzed for USL calculations are statistically independent. In contrast, the multiple experiments typically used for USL calculations can be correlated because they are often performed at the same facilities using the same materials and measurement techniques. This paper addresses this issue by providing a set of statistical inference methods to calculate the bias and bias uncertainty based on the underlying assumption that the experimental data are correlated. Methods to quantify these correlations are the subject of a companion paper and will not be discussed here. The newly proposed USL methodology is based on the assumption that the integral experiments selected for use in the establishment of the USL are sufficiently applicable and that experimental correlations are known. Under the assumption of uncorrelated data, the new methods collapse directly to familiar USL equations currently used. We will demonstrate our proposed methods on real data and compare them to calculations of currently used methods such as USLSTATS and NUREG/CR-6698. Lastly, we will also demonstrate the effect experiment correlations can have on USL calculations.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Jan 01 00:00:00 EST 2015},
month = {Thu Jan 01 00:00:00 EST 2015}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share: