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Title: A New Approach for Nuclear Data Covariance and Sensitivity Generation

Abstract

Covariance data are required to correctly assess uncertainties in design parameters in 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 U.S. Evaluated Nuclear Data File, 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. The computer code SAMMY is used in the analysis of the experimental data in the resolved and unresolved resonance energy regions. The data fitting of cross sections is based on generalized least-squares formalism (Bayes' 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, in addition, it also provides the resonance-parameter covariances. For existing resonance-parameter evaluations where no resonance-parameter covariance data are available, the alternative is to use an approach called the 'retroactive' resonance-parameter covariance generation. In the high-energy region the methodology for generating covariance data consists of least-squares fitting and model parameter adjustment. The least-squares fitting method calculates covariances directly from experimental data. Themore » parameter adjustment method employs a nuclear model calculation such as the optical model and the Hauser-Feshbach model, and estimates a covariance for the nuclear model parameters. In this paper we describe the application of the retroactive method and the parameter adjustment method to generate covariance data for the gadolinium isotopes.« less

Authors:
; ;  [1]; ;  [2]
  1. Oak Ridge National Laboratory (United States)
  2. Los Alamos National Laboratory (United States)
Publication Date:
OSTI Identifier:
20722562
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 769; Journal Issue: 1; Conference: International conference on nuclear data for science and technology, Santa Fe, NM (United States), 26 Sep - 1 Oct 2004; Other Information: DOI: 10.1063/1.1945017; (c) 2005 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
73 NUCLEAR PHYSICS AND RADIATION PHYSICS; DATA COVARIANCES; ERRORS; EVALUATION; GADOLINIUM ISOTOPES; LEAST SQUARE FIT; NUCLEAR DATA COLLECTIONS; NUCLEAR MODELS; OPTICAL MODELS; R MATRIX; RESONANCE; S CODES; SENSITIVITY; STATISTICAL MODELS

Citation Formats

Leal, L.C., Larson, N.M., Derrien, H., Kawano, T., and Chadwick, M.B. A New Approach for Nuclear Data Covariance and Sensitivity Generation. United States: N. p., 2005. Web. doi:10.1063/1.1945017.
Leal, L.C., Larson, N.M., Derrien, H., Kawano, T., & Chadwick, M.B. A New Approach for Nuclear Data Covariance and Sensitivity Generation. United States. doi:10.1063/1.1945017.
Leal, L.C., Larson, N.M., Derrien, H., Kawano, T., and Chadwick, M.B. Tue . "A New Approach for Nuclear Data Covariance and Sensitivity Generation". United States. doi:10.1063/1.1945017.
@article{osti_20722562,
title = {A New Approach for Nuclear Data Covariance and Sensitivity Generation},
author = {Leal, L.C. and Larson, N.M. and Derrien, H. and Kawano, T. and Chadwick, M.B.},
abstractNote = {Covariance data are required to correctly assess uncertainties in design parameters in 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 U.S. Evaluated Nuclear Data File, 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. The computer code SAMMY is used in the analysis of the experimental data in the resolved and unresolved resonance energy regions. The data fitting of cross sections is based on generalized least-squares formalism (Bayes' 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, in addition, it also provides the resonance-parameter covariances. For existing resonance-parameter evaluations where no resonance-parameter covariance data are available, the alternative is to use an approach called the 'retroactive' resonance-parameter covariance generation. In the high-energy region the methodology for generating covariance data consists of least-squares fitting and model parameter adjustment. The least-squares fitting method calculates covariances directly from experimental data. The parameter adjustment method employs a nuclear model calculation such as the optical model and the Hauser-Feshbach model, and estimates a covariance for the nuclear model parameters. In this paper we describe the application of the retroactive method and the parameter adjustment method to generate covariance data for the gadolinium isotopes.},
doi = {10.1063/1.1945017},
journal = {AIP Conference Proceedings},
number = 1,
volume = 769,
place = {United States},
year = {Tue May 24 00:00:00 EDT 2005},
month = {Tue May 24 00:00:00 EDT 2005}
}