Nuclear data uncertainty propagation in continuous-energy Monte Carlo calculations

被引:0
|
作者
Aures, Alexander [1 ]
Eisenstecken, Thomas [1 ]
Elts, Ekaterina [1 ]
Kilger, Robert [1 ]
机构
[1] Forschungszentrum Julich, Gesell Anlagen & Reaktorsicherheit GRS gGmbH, Boltzmannstr 14, D-85748 Garching, Germany
关键词
Nuclear data uncertainties; Uncertainty and sensitivity analysis; Random sampling; ENDF/B-VII.1;
D O I
10.1016/j.anucene.2024.110955
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
The XSUSA method is a well-established stochastic sampling method for propagating nuclear data uncertainties through multigroup neutron transport calculations. To benefit from the advantages of Monte Carlo transport codes, namely modeling complex geometries and using continuous-energy nuclear data, an extension to XSUSA is proposed which allows perturbing continuous-energy nuclear data using multigroup nuclear data covariances. To verify the extension, sensitivity profiles of nuclear reactions are calculated via direct perturbation for the benchmark problems Jezebel, Godiva, LEU-SOL-THERM-002. The sensitivity profiles agree well with those obtained from TSUNAMI and Serpent. Secondly, the extension to XSUSA is applied to produce randomly sampled continuous-energy data libraries using the covariance libraries of SCALE 6.2. With these data libraries, samples of Serpent calculations are performed for Jezebel, Godiva, LEU-SOL-THERM-002, and the TMI-1 pin cell of the OECD/NEA LWR-UAM benchmark. For each problem, the multiplication factor uncertainty agrees well with the one from TSUNAMI.
引用
收藏
页数:9
相关论文
共 50 条
  • [21] Development of a Coupled Depletion Perturbation Theory Methodology in Continuous-Energy Monte Carlo Depletion Simulations
    Murphy, Benjamin R.
    Perfetti, Christopher M.
    NUCLEAR SCIENCE AND ENGINEERING, 2024,
  • [23] Monte Carlo uncertainty propagation approaches in ADS burn-up calculations
    Diez, C. J.
    Cabellos, O.
    Rochman, D.
    Koning, A. J.
    Martinez, J. S.
    ANNALS OF NUCLEAR ENERGY, 2013, 54 : 27 - 35
  • [24] Assessment and propagation of the 237Np nuclear data uncertainties in integral calculations by Monte Carlo techniques
    Noguere, Gilles
    Bernard, David
    Saint Jean, Cyrille De
    Iooss, Bertrand
    Gunsing, Frank
    Kobayashi, Katsuhei
    Mughabghab, Said F.
    Siegler, Peter
    NUCLEAR SCIENCE AND ENGINEERING, 2008, 160 (01) : 108 - 122
  • [25] Two practical methods for unionized energy grid construction in continuous-energy Monte Carlo neutron transport calculation
    Leppanen, Jaakko
    ANNALS OF NUCLEAR ENERGY, 2009, 36 (07) : 878 - 885
  • [26] Monte Carlo Uncertainty Propagation with the NIST Uncertainty Machine
    Albert, Daniel R.
    JOURNAL OF CHEMICAL EDUCATION, 2020, 97 (05) : 1491 - 1494
  • [27] Nuclear Reactor Transient Analysis by Continuous-Energy Monte Carlo Calculation Based on Predictor-Corrector Quasi-Static Method
    Jo, YuGwon
    Cho, Bumhee
    Cho, Nam Zin
    NUCLEAR SCIENCE AND ENGINEERING, 2016, 183 (02) : 229 - 246
  • [28] Evaluating Embedded Monte Carlo vs. Total Monte Carlo for Nuclear Data Uncertainty Quantification
    Biot, Gregoire
    Rochman, Dimitri
    Ducru, Pablo
    Forget, Benoit
    JOINT INTERNATIONAL CONFERENCE ON SUPERCOMPUTING IN NUCLEAR APPLICATIONS + MONTE CARLO, SNA + MC 2024, 2024, 302
  • [29] SCALE Continuous-Energy Eigenvalue Sensitivity Coefficient Calculations
    Perfetti, Christopher M.
    Rearden, Bradley T.
    Martin, William R.
    NUCLEAR SCIENCE AND ENGINEERING, 2016, 182 (03) : 332 - 353
  • [30] Comparison of Resonance Elastic Scattering Models Newly Implemented in MVP Continuous-Energy Monte Carlo Code
    Mori, Takamasa
    Nagaya, Yasunobu
    JOURNAL OF NUCLEAR SCIENCE AND TECHNOLOGY, 2009, 46 (08) : 793 - 798