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Title: Adjoint-Based Sensitivity and Uncertainty Analysis for Density and Composition: A User’s Guide

Abstract

The ability to perform sensitivity analyses using adjoint-based first-order sensitivity theory has existed for decades. This paper provides guidance on how adjoint sensitivity methods can be used to predict the effect of material density and composition uncertainties in critical experiments, including when these uncertain parameters are correlated or constrained. Two widely used Monte Carlo codes, MCNP6 (Ref. 2) and SCALE 6.2 (Ref. 3), are both capable of computing isotopic density sensitivities in continuous energy and angle. Additionally, Perkó et al. have shown how individual isotope density sensitivities, easily computed using adjoint methods, can be combined to compute constrained first-order sensitivities that may be used in the uncertainty analysis. This paper provides details on how the codes are used to compute first-order sensitivities and how the sensitivities are used in an uncertainty analysis. Constrained first-order sensitivities are computed in a simple example problem.

Authors:
 [1];  [2];  [3];  [4]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Brigham and Women's Hospital (Harvard Medical School), Boston, MA (United States)
  3. Univ. of Michigan, Ann Arbor, MI (United States)
  4. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA), Office of Defense Programs (DP) (NA-10)
OSTI Identifier:
1374343
Alternate Identifier(s):
OSTI ID: 1348326
Report Number(s):
LA-UR-16-26659
Journal ID: ISSN 0029-5639
Grant/Contract Number:
AC05-00OR22725; AC52-06NA25396
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Nuclear Science and Engineering
Additional Journal Information:
Journal Volume: 185; Journal Issue: 3; Journal ID: ISSN 0029-5639
Publisher:
American Nuclear Society - Taylor & Francis
Country of Publication:
United States
Language:
English
Subject:
73 NUCLEAR PHYSICS AND RADIATION PHYSICS; 97 MATHEMATICS AND COMPUTING; Sensitivity analysis; Uncertainty quantification; Adjoint; 11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS; sensitivity analysis; uncertainty quantification; adjoint

Citation Formats

Favorite, Jeffrey A., Perko, Zoltan, Kiedrowski, Brian C., and Perfetti, Christopher M.. Adjoint-Based Sensitivity and Uncertainty Analysis for Density and Composition: A User’s Guide. United States: N. p., 2017. Web. doi:10.1080/00295639.2016.1272990.
Favorite, Jeffrey A., Perko, Zoltan, Kiedrowski, Brian C., & Perfetti, Christopher M.. Adjoint-Based Sensitivity and Uncertainty Analysis for Density and Composition: A User’s Guide. United States. doi:10.1080/00295639.2016.1272990.
Favorite, Jeffrey A., Perko, Zoltan, Kiedrowski, Brian C., and Perfetti, Christopher M.. Wed . "Adjoint-Based Sensitivity and Uncertainty Analysis for Density and Composition: A User’s Guide". United States. doi:10.1080/00295639.2016.1272990. https://www.osti.gov/servlets/purl/1374343.
@article{osti_1374343,
title = {Adjoint-Based Sensitivity and Uncertainty Analysis for Density and Composition: A User’s Guide},
author = {Favorite, Jeffrey A. and Perko, Zoltan and Kiedrowski, Brian C. and Perfetti, Christopher M.},
abstractNote = {The ability to perform sensitivity analyses using adjoint-based first-order sensitivity theory has existed for decades. This paper provides guidance on how adjoint sensitivity methods can be used to predict the effect of material density and composition uncertainties in critical experiments, including when these uncertain parameters are correlated or constrained. Two widely used Monte Carlo codes, MCNP6 (Ref. 2) and SCALE 6.2 (Ref. 3), are both capable of computing isotopic density sensitivities in continuous energy and angle. Additionally, Perkó et al. have shown how individual isotope density sensitivities, easily computed using adjoint methods, can be combined to compute constrained first-order sensitivities that may be used in the uncertainty analysis. This paper provides details on how the codes are used to compute first-order sensitivities and how the sensitivities are used in an uncertainty analysis. Constrained first-order sensitivities are computed in a simple example problem.},
doi = {10.1080/00295639.2016.1272990},
journal = {Nuclear Science and Engineering},
number = 3,
volume = 185,
place = {United States},
year = {Wed Mar 01 00:00:00 EST 2017},
month = {Wed Mar 01 00:00:00 EST 2017}
}

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  • The ability to perform sensitivity analyses using adjoint-based first-order sensitivity theory has existed for decades. This paper provides guidance on how adjoint sensitivity methods can be used to predict the effect of material density and composition uncertainties in critical experiments, including when these uncertain parameters are correlated or constrained. Two widely used Monte Carlo codes, MCNP6 (Ref. 2) and SCALE 6.2 (Ref. 3), are both capable of computing isotopic density sensitivities in continuous energy and angle. Additionally, Perkó et al. have shown how individual isotope density sensitivities, easily computed using adjoint methods, can be combined to compute constrained first-order sensitivitiesmore » that may be used in the uncertainty analysis. This paper provides details on how the codes are used to compute first-order sensitivities and how the sensitivities are used in an uncertainty analysis. Constrained first-order sensitivities are computed in a simple example problem.« less
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