Covariance and sensitivity data generation at ORNL

Covariance data are required to assess uncertainties in design parameters in several nuclear applications. The error estimation of calculated quantities relies on the nuclear data uncertainty information available in the basic nuclear data libraries, such as the US Evaluated Nuclear Data Library, EN...

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Veröffentlicht in:Radiation protection dosimetry 2005-01, Vol.115 (1-4), p.133-135
Hauptverfasser: Leal, L. C., Derrien, H., Larson, N. M., Alpan, A.
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container_issue 1-4
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container_title Radiation protection dosimetry
container_volume 115
creator Leal, L. C.
Derrien, H.
Larson, N. M.
Alpan, A.
description Covariance data are required to assess uncertainties in design parameters in several nuclear applications. The error estimation of calculated quantities relies on the nuclear data uncertainty information available in the basic nuclear data libraries, such as the US Evaluated Nuclear Data Library, ENDF/B. The uncertainty files in the ENDF/B library are obtained from the analysis of experimental data and are stored as variance and covariance data. In this paper we address the generation of covariance data in the resonance region done with the computer code SAMMY. SAMMY is used in the evaluation of the experimental data in the resolved and unresolved resonance energy regions. The data fitting of cross sections is based on the generalised least-squares formalism (Bayesian theory) together with the resonance formalism described by R-matrix theory. Two approaches are used in SAMMY for the generation of resonance parameter covariance data. In the evaluation process SAMMY generates a set of resonance parameters that fit the data, and, it provides the resonance parameter covariances. For resonance parameter evaluations where there are no resonance parameter covariance data available, the alternative is to use an approach called the ‘retroactive’ resonance parameter covariance generation. In this paper, we describe the application of the retroactive covariance generation approach for the gadolinium isotopes.
doi_str_mv 10.1093/rpd/nci126
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subjects Computer-Aided Design
Data Interpretation, Statistical
Databases, Factual
Equipment Design - methods
Equipment Failure Analysis - methods
Nuclear Reactors
Radiation Protection - instrumentation
Radiation Protection - methods
Radioisotopes - analysis
Radiometry - methods
Reproducibility of Results
Sensitivity and Specificity
Software
Statistics as Topic
Tennessee
title Covariance and sensitivity data generation at ORNL
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