Nuclear Engineering and Technology

  • 제46권3호
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  • Pages.343-352
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  • 2014
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  • 1738-5733(pISSN)
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  • 2234-358X(eISSN)
한국원자력학회 (Korean Nuclear Society)
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NUCLEAR DATA UNCERTAINTY AND SENSITIVITY ANALYSIS WITH XSUSA FOR FUEL ASSEMBLY DEPLETION CALCULATIONS

  • Zwermann, W. (Gesellschaft fuer Anlagen- und Reaktorsicherheit (GRS) mbH Forschungszentrum) ;
  • Aures, A. (Gesellschaft fuer Anlagen- und Reaktorsicherheit (GRS) mbH Forschungszentrum) ;
  • Gallner, L. (Gesellschaft fuer Anlagen- und Reaktorsicherheit (GRS) mbH Forschungszentrum) ;
  • Hannstein, V. (Gesellschaft fuer Anlagen- und Reaktorsicherheit (GRS) mbH Forschungszentrum) ;
  • Krzykacz-Hausmann, B. (Gesellschaft fuer Anlagen- und Reaktorsicherheit (GRS) mbH Forschungszentrum) ;
  • Velkov, K. (Gesellschaft fuer Anlagen- und Reaktorsicherheit (GRS) mbH Forschungszentrum) ;
  • Martinez, J.S. (Department of Nuclear Engineering, Universidad Politecnica de Madrid)
  • 투고 : 2013.10.17
  • 발행 : 2014.06.25
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초록

Uncertainty and sensitivity analyses with respect to nuclear data are performed with depletion calculations for BWR and PWR fuel assemblies specified in the framework of the UAM-LWR Benchmark Phase II. For this, the GRS sampling based tool XSUSA is employed together with the TRITON depletion sequences from the SCALE 6.1 code system. Uncertainties for multiplication factors and nuclide inventories are determined, as well as the main contributors to these result uncertainties by calculating importance indicators. The corresponding neutron transport calculations are performed with the deterministic discrete-ordinates code NEWT. In addition, the Monte Carlo code KENO in multi-group mode is used to demonstrate a method with which the number of neutron histories per calculation run can be substantially reduced as compared to that in a calculation for the nominal case without uncertainties, while uncertainties and sensitivities are obtained with almost the same accuracy.

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피인용 문헌

  1. Experimental analysis and uncertainty quantification using random sampling technique for ADS experiments at KUCA pp.1881-1248, 2018, https://doi.org/10.1080/00223131.2017.1403387
  2. Exploring Stochastic Sampling in Nuclear Data Uncertainties Assessment for Reactor Physics Applications and Validation Studies vol.9, pp.12, 2016, https://doi.org/10.3390/en9121039