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Uncertainty quantification in the calculation of keff using sensitity and stochastic sampling method

Hu Ze-Hua Ye Tao Liu Xiong-Guo Wang Jia

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Uncertainty quantification in the calculation of keff using sensitity and stochastic sampling method

Hu Ze-Hua, Ye Tao, Liu Xiong-Guo, Wang Jia
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  • The sensitivity and uncertainty analysis(S/U) method based on the first order perturbation theory is commonly employed to calculate the uncertainties in-nuclear reactor's integral parameters, such as the neutron effective multiplication factor(keff), due to uncertainties in nuclear data. However, this method is only theoretically suitable for the linear model because of its first order approximation. Moreover, S/U method is difficult to incorporate into a neutronics code, because the adjoint angular flux is needed to obtain the sensitivity coefficient of an integral parameter to nuclear data. Meanwhile, the sampling approach based on parametric random sampling of input parameters, an easy implemented method, evaluates the uncertainties in the integral parameters by performing a set of neutronics simulations inputted with a set of stochastic nuclear data sampled from a multinomial normal distribution with nuclear cross section mean values and covariance data. The sampling approach is considered as a more exact method, as linear approximation is not needed. With the increase of computational power, the sampling methods with consuming more time are now possible. The sampling approach is incorporated into SURE, a sensitivity and uncertainty analysis code developed in IAPCM, as a functional module. A careful verification of the new function is necessary before it is used to analyze complicated problems, such as multi-physical coupling calculations of nuclear reactor. Two simple fast criticality benchmark experiments, namely Godiva(HEU-MET-FAST-001) and Jezebel(PU-MET-FAST-001), are selected to verify the sampling module of SURE. The uncertainties in nuclear data are given by multigroup covariance matrices processed from ENDF/B-VⅡ. 1 data. The uncertainties in the computed value of keff resulting from uncertainties in the nuclear data are calculated with both S/U and sampling methods. The uncertainties due to reaction cross sections for each nuclide in two benchmarks given by two methods with the multigroup covariance matrices are in good agreement. Since the S/U module of SURE code is verified extensively, the correctness of the sampling function of the code is confirmed as well. The distribution of the keff from the sampling approach obeys the normal distribution pretty well, which indicates that keff varies linearly with the nuclear data under its uncertainty range, since the nuclear data used in calculations are assumed to be normal distribution in the sampling method. The results from the sampling method also support the S/U method with linear approximation as a suitable uncertainty quantification method for keff calculation.
      Corresponding author: Hu Ze-Hua, hu_zehua@iapcm.ac.cn
    • Funds: Project supported by the Key Laboratory of Neutron Physics of China Academy of Engineering Physics(Grant No. 2013AA02), Sub-item of Special Project of the National Energy Bureau, China(Grant No. 2015ZX06002008), National Magnetic Confinement Fusion Energy Research Project, China(Grant No. 2015GB108002).
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  • [1]

    USDOE 2002 A Technology Roadmap for Generation-IV Nuclear Energy Systems USDOE/GIF-002-00(Washington:USDOE) p1

    [2]

    Salvatores M, Jacqmin R 2008 Uncertainty and Target Accuracy Assessment for Innovative Systems Using Recent Covariance Data Evaluations NEA/WPEC-26(Paris:OECD/NEA) p1

    [3]

    Marable J H, Weisbin C R 1979 Theory and Application of Sensitivity and Uncertainty Analysis(Oak Ridge:Oak Ridge National Laboratory) p16

    [4]

    Gilli L, Lathouwers D, Kloosterman J L, van der Hagen T H J J 2013 Nucl. Sci. Eng. 175 172

    [5]

    Kim D H, Gil C S, Lee Y O 2008 International Conference on Nuclear Data for Science and Technology Nice, France, April 22-27, 2007 p289

    [6]

    Kodeli I 2008 Sci. Technol. Nucl. Instll. 2008 659861

    [7]

    Pusa M 2012 Sci. Technol. Nucl. Instll. 2012 157029

    [8]

    Williams M L, Rearden B T 2008 Nucl. Data Sheets 109 5

    [9]

    Hu Z H, Wang J, Sun W L, Li M S 2013 Atom. Energy Sci. Technol. 47 25 (in Chinese)[胡泽华, 王佳, 孙伟力, 李茂生2013原子能科学技术47 25]

    [10]

    Dossantos-Uzarralde P J, Guittet A 2008 Nucl. Data Sheets 109 2894

    [11]

    Gilli L, Lathouwers D, Kloosterman J L, van der Hagen T H J J, Koning A J, Rochman D 2013 Ann. Nucl. Energy 56 71

    [12]

    Williams M M R 2007 Nucl. Sci. Eng. 155 109

    [13]

    Wieselquist W, Zhu T, Vasiliev A, Ferroukhi H 2013 Sci. Technol. Nucl. Instll. 2013 549793

    [14]

    Zhu T, Vasiliev A, Ferroukhi H, Pautz A 2014 Nucl. Data Sheets 118 453

    [15]

    Zhu T, Vasiliev A, Ferroukhi H, Pautz A 2015 Ann. Nucl. Energy 75 713

    [16]

    Zhu T, Vasiliev A, Ferroukhi H, Pautz A, Tarantola S 2015 J. Nucl. Sci. Technol. 52 8

    [17]

    Chadwick M B, Herman M, Oblozinsky P 2011 Nucl. Data Sheets 112 110

    [18]

    Engle W W J 1967 A User's Manual for ANISN:A One-Dimensional Discrete Ordinates Transport Code with Anisotropic Scattering(Oak Ridge:Oak Ridge Gaseous Diffusion Plant Computing Technology Center) p1

    [19]

    Macfarlane R E, Muir D W, Boicourt R M, Kahler A C 2012 The NJOY Nuclear Data Processing System (Los Alamos:Los Alamos National Laboratory) p1

    [20]

    Kiedrowski B C, Brown F B 2013 Nucl. Sci. Eng. 174 227

    [21]

    Briggs J B 2004 International Handbook of Evaluated Criticality Safety Benchmark Experiments(Paris:Nuclear Energy Agency) p1

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Publishing process
  • Received Date:  07 July 2016
  • Accepted Date:  30 September 2016
  • Published Online:  05 January 2017

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