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Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) Applied to a Subcritical Experimental Reactor Physics Benchmark. VI: Overall Impact of 1st- and 2nd-Order Sensitivities on Response Uncertainties

Author

Listed:
  • Dan G. Cacuci

    (Center for Nuclear Science and Energy, Department of Mechanical Engineering, University of South Carolina, Columbia, SC 29208, USA)

  • Ruixian Fang

    (Center for Nuclear Science and Energy, Department of Mechanical Engineering, University of South Carolina, Columbia, SC 29208, USA)

  • Jeffrey A. Favorite

    (Los Alamos National Laboratory, Applied Physics (X) Division, MS F663, Los Alamos, NM 87545, USA)

Abstract

This work applies the Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) to compute the 1st-order and unmixed 2nd-order sensitivities of a polyethylene-reflected plutonium (PERP) benchmark’s leakage response with respect to the benchmark’s imprecisely known isotopic number densities. The numerical results obtained for these sensitivities indicate that the 1st-order relative sensitivity to the isotopic number densities for the two fissionable isotopes have large values, which are comparable to, or larger than, the corresponding sensitivities for the total cross sections. Furthermore, several 2nd-order unmixed sensitivities for the isotopic number densities are significantly larger than the corresponding 1st-order ones. This work also presents results for the first-order sensitivities of the PERP benchmark’s leakage response with respect to the fission spectrum parameters of the two fissionable isotopes, which have very small values. Finally, this work presents the overall summary and conclusions stemming from the research findings for the total of 21,976 first-order sensitivities and 482,944,576 second-order sensitivities with respect to all model parameters of the PERP benchmark, as presented in the sequence of publications in the Special Issue of Energies dedicated to “Sensitivity Analysis, Uncertainty Quantification and Predictive Modeling of Nuclear Energy Systems”.

Suggested Citation

  • Dan G. Cacuci & Ruixian Fang & Jeffrey A. Favorite, 2020. "Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) Applied to a Subcritical Experimental Reactor Physics Benchmark. VI: Overall Impact of 1st- and 2nd-Order Sensitivities o," Energies, MDPI, vol. 13(7), pages 1-37, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:7:p:1674-:d:340794
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    References listed on IDEAS

    as
    1. Ruixian Fang & Dan Gabriel Cacuci, 2020. "Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) Applied to a Subcritical Experimental Reactor Physics Benchmark: IV. Effects of Imprecisely Known Source Parameters," Energies, MDPI, vol. 13(6), pages 1-49, March.
    2. Ruixian Fang & Dan G. Cacuci, 2020. "Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) Applied to a Subcritical Experimental Reactor Physics Benchmark: V. Computation of Mixed 2nd-Order Sensitivities Involvin," Energies, MDPI, vol. 13(10), pages 1-50, May.
    3. D. G. Cacuci & R. Fang & J. A. Favorite & M. C. Badea & F. Di Rocco, 2019. "Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) Applied to a Subcritical Experimental Reactor Physics Benchmark: III. Effects of Imprecisely Known Microscopic Fission Cr," Energies, MDPI, vol. 12(21), pages 1-67, October.
    4. Dan G. Cacuci & Ruixian Fang & Jeffrey A. Favorite, 2019. "Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) Applied to a Subcritical Experimental Reactor Physics Benchmark: I. Effects of Imprecisely Known Microscopic Total and Ca," Energies, MDPI, vol. 12(21), pages 1-43, November.
    5. Ruixian Fang & Dan Gabriel Cacuci, 2019. "Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) Applied to a Subcritical Experimental Reactor Physics Benchmark: II. Effects of Imprecisely Known Microscopic Scattering ," Energies, MDPI, vol. 12(21), pages 1-33, October.
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    Citations

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    Cited by:

    1. Dan Gabriel Cacuci, 2021. "On the Need to Determine Accurately the Impact of Higher-Order Sensitivities on Model Sensitivity Analysis, Uncertainty Quantification and Best-Estimate Predictions," Energies, MDPI, vol. 14(19), pages 1-38, October.
    2. Dan Gabriel Cacuci, 2021. "Fourth-Order Comprehensive Adjoint Sensitivity Analysis (4th-CASAM) of Response-Coupled Linear Forward/Adjoint Systems: I. Theoretical Framework," Energies, MDPI, vol. 14(11), pages 1-45, June.
    3. Dan Gabriel Cacuci, 2021. "High-Order Deterministic Sensitivity Analysis and Uncertainty Quantification: Review and New Developments," Energies, MDPI, vol. 14(20), pages 1-53, October.
    4. Dan Gabriel Cacuci, 2021. "The n th -Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (n th -CASAM-L): I. Mathematical Framework," Energies, MDPI, vol. 14(24), pages 1-42, December.
    5. Dan Gabriel Cacuci, 2022. "Overview of Arbitrarily High-Order Adjoint Sensitivity and Uncertainty Quantification Methodology for Large-Scale Systems," Energies, MDPI, vol. 15(18), pages 1-44, September.
    6. Andrew G. Buchan & Dan G. Cacuci & Steven Dargaville & Christopher C. Pain, 2022. "Optimised Adjoint Sensitivity Analysis Using Adjoint Guided Mesh Adaptivity Applied to Neutron Detector Response Calculations," Energies, MDPI, vol. 15(14), pages 1-11, July.
    7. Ruixian Fang & Dan G. Cacuci, 2020. "Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) Applied to a Subcritical Experimental Reactor Physics Benchmark: V. Computation of Mixed 2nd-Order Sensitivities Involvin," Energies, MDPI, vol. 13(10), pages 1-50, May.
    8. Dan Gabriel Cacuci, 2022. "Sensitivity Analysis, Uncertainty Quantification and Predictive Modeling of Nuclear Energy Systems," Energies, MDPI, vol. 15(17), pages 1-7, September.
    9. Dan Gabriel Cacuci, 2022. "Advances in High-Order Sensitivity Analysis for Uncertainty Quantification and Reduction in Nuclear Energy Systems," Energies, MDPI, vol. 15(17), pages 1-6, September.

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