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Title: Excluding Benchmark Statistical Outliers in Nuclear Criticality Safety Validation: A Comparison Study of Upper Subcritical Limits for Plutonium Systems using Whisper-1.1

Abstract

Neutron transport methods used to establish subcriticality require validation by comparison to critical experiments considered to be benchmarks. Whisper is a sensitivity/uncertainty analysis tool developed to assist with the task of validation in nuclear criticality safety. Details on the Whisper methodology can be found in References 1-3 on the MCNP® reference collection website at https://mcnp.lanl.gov. During the process of validation there can be cases where a benchmark experiment may be found to be a statistical outlier, in which the calculated k-effective value and the experiment k-effective value differ by an amount atypical for similar experiments. A methodology optionally employed by Whisper is the exclusion of statistical outliers based upon the iterative diagonal chi-squared statistical rejection technique. Alternatively, there is an option to include all benchmarks in the Whisper library collection, even those benchmarks found to be statistical outliers, when computing the bias, bias uncertainty and margin of subcriticality (MOS) leading to establishment of the baseline upper subcritical limit (USL). A comparison study has been done to compute USLs with and without statistical outliers in the Whisper benchmark collection to determine what effect rejection of statistical outliers has on the recommended USL. The results show little overall difference in the recommendedmore » baseline USLs developed by Whisper when excluding statistical outliers. Additionally, there does not appear to be a clear trend in predicting whether the baseline USL will be higher or lower when rejecting statistical outliers from the benchmark critical experiment collection used for validation.« less

Authors:
 [1];  [1];  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1467235
Report Number(s):
LA-UR-18-27731
DOE Contract Number:  
AC52-06NA25396
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL PROTECTION

Citation Formats

Alwin, Jennifer Louise, Brown, Forest B., and Rising, Michael Evan. Excluding Benchmark Statistical Outliers in Nuclear Criticality Safety Validation: A Comparison Study of Upper Subcritical Limits for Plutonium Systems using Whisper-1.1. United States: N. p., 2018. Web. doi:10.2172/1467235.
Alwin, Jennifer Louise, Brown, Forest B., & Rising, Michael Evan. Excluding Benchmark Statistical Outliers in Nuclear Criticality Safety Validation: A Comparison Study of Upper Subcritical Limits for Plutonium Systems using Whisper-1.1. United States. doi:10.2172/1467235.
Alwin, Jennifer Louise, Brown, Forest B., and Rising, Michael Evan. Mon . "Excluding Benchmark Statistical Outliers in Nuclear Criticality Safety Validation: A Comparison Study of Upper Subcritical Limits for Plutonium Systems using Whisper-1.1". United States. doi:10.2172/1467235. https://www.osti.gov/servlets/purl/1467235.
@article{osti_1467235,
title = {Excluding Benchmark Statistical Outliers in Nuclear Criticality Safety Validation: A Comparison Study of Upper Subcritical Limits for Plutonium Systems using Whisper-1.1},
author = {Alwin, Jennifer Louise and Brown, Forest B. and Rising, Michael Evan},
abstractNote = {Neutron transport methods used to establish subcriticality require validation by comparison to critical experiments considered to be benchmarks. Whisper is a sensitivity/uncertainty analysis tool developed to assist with the task of validation in nuclear criticality safety. Details on the Whisper methodology can be found in References 1-3 on the MCNP® reference collection website at https://mcnp.lanl.gov. During the process of validation there can be cases where a benchmark experiment may be found to be a statistical outlier, in which the calculated k-effective value and the experiment k-effective value differ by an amount atypical for similar experiments. A methodology optionally employed by Whisper is the exclusion of statistical outliers based upon the iterative diagonal chi-squared statistical rejection technique. Alternatively, there is an option to include all benchmarks in the Whisper library collection, even those benchmarks found to be statistical outliers, when computing the bias, bias uncertainty and margin of subcriticality (MOS) leading to establishment of the baseline upper subcritical limit (USL). A comparison study has been done to compute USLs with and without statistical outliers in the Whisper benchmark collection to determine what effect rejection of statistical outliers has on the recommended USL. The results show little overall difference in the recommended baseline USLs developed by Whisper when excluding statistical outliers. Additionally, there does not appear to be a clear trend in predicting whether the baseline USL will be higher or lower when rejecting statistical outliers from the benchmark critical experiment collection used for validation.},
doi = {10.2172/1467235},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {8}
}

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