Subspacebased Inverse Uncertainty Quantification for Nuclear Data Assessment
Abstract
Safety analysis and design optimization depend on the accurate prediction of various reactor attributes. Predictions can be enhanced by reducing the uncertainty associated with the attributes of interest. An inverse problem can be defined and solved to assess the sources of uncertainty, and experimental effort can be subsequently directed to further improve the uncertainty associated with these sources. In this work a subspacebased algorithm for inverse sensitivity/uncertainty quantification (IS/UQ) has been developed to enable analysts account for all sources of nuclear data uncertainties in support of target accuracy assessmenttype analysis. An approximate analytical solution of the optimization problem is used to guide the search for the dominant uncertainty subspace. By limiting the search to a subspace, the degrees of freedom available for the optimization search are significantly reduced. A quarter PWR fuel assembly is modeled and the accuracy of the multiplication factor and the fission reaction rate are used as reactor attributes whose uncertainties are to be reduced. Numerical experiments are used to demonstrate the computational efficiency of the proposed algorithm. Our ongoing work is focusing on extending the proposed algorithm to account for various forms of feedback, e.g., thermalhydraulics and depletion effects.
 Authors:
 Publication Date:
 OSTI Identifier:
 22436758
 Resource Type:
 Journal Article
 Resource Relation:
 Journal Name: Nuclear Data Sheets; Journal Volume: 123; Conference: International workshop on nuclear data covariances, Santa Fe, NM (United States), 28 Apr  1 May 2014; Other Information: Copyright (c) 2014 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA)
 Country of Publication:
 United States
 Language:
 English
 Subject:
 21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS; 73 NUCLEAR PHYSICS AND RADIATION PHYSICS; ALGORITHMS; ANALYTICAL SOLUTION; DATA; FUEL ASSEMBLIES; OPTIMIZATION; PWR TYPE REACTORS; REACTION KINETICS; SAFETY ANALYSIS; STATISTICAL MODELS; THERMAL HYDRAULICS
Citation Formats
Khuwaileh, B.A., Email: bakhuwai@ncsu.edu, and AbdelKhalik, H.S. Subspacebased Inverse Uncertainty Quantification for Nuclear Data Assessment. United States: N. p., 2015.
Web. doi:10.1016/J.NDS.2014.12.010.
Khuwaileh, B.A., Email: bakhuwai@ncsu.edu, & AbdelKhalik, H.S. Subspacebased Inverse Uncertainty Quantification for Nuclear Data Assessment. United States. doi:10.1016/J.NDS.2014.12.010.
Khuwaileh, B.A., Email: bakhuwai@ncsu.edu, and AbdelKhalik, H.S. 2015.
"Subspacebased Inverse Uncertainty Quantification for Nuclear Data Assessment". United States.
doi:10.1016/J.NDS.2014.12.010.
@article{osti_22436758,
title = {Subspacebased Inverse Uncertainty Quantification for Nuclear Data Assessment},
author = {Khuwaileh, B.A., Email: bakhuwai@ncsu.edu and AbdelKhalik, H.S.},
abstractNote = {Safety analysis and design optimization depend on the accurate prediction of various reactor attributes. Predictions can be enhanced by reducing the uncertainty associated with the attributes of interest. An inverse problem can be defined and solved to assess the sources of uncertainty, and experimental effort can be subsequently directed to further improve the uncertainty associated with these sources. In this work a subspacebased algorithm for inverse sensitivity/uncertainty quantification (IS/UQ) has been developed to enable analysts account for all sources of nuclear data uncertainties in support of target accuracy assessmenttype analysis. An approximate analytical solution of the optimization problem is used to guide the search for the dominant uncertainty subspace. By limiting the search to a subspace, the degrees of freedom available for the optimization search are significantly reduced. A quarter PWR fuel assembly is modeled and the accuracy of the multiplication factor and the fission reaction rate are used as reactor attributes whose uncertainties are to be reduced. Numerical experiments are used to demonstrate the computational efficiency of the proposed algorithm. Our ongoing work is focusing on extending the proposed algorithm to account for various forms of feedback, e.g., thermalhydraulics and depletion effects.},
doi = {10.1016/J.NDS.2014.12.010},
journal = {Nuclear Data Sheets},
number = ,
volume = 123,
place = {United States},
year = 2015,
month = 1
}

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