Nuclear Engineering and Technology

  • 제53권3호
  • /
  • Pages.715-731
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  • 2021
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  • 1738-5733(pISSN)
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  • 2234-358X(eISSN)
한국원자력학회 (Korean Nuclear Society)
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Uncertainty quantification of PWR spent fuel due to nuclear data and modeling parameters

  • Ebiwonjumi, Bamidele (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology) ;
  • Kong, Chidong (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology) ;
  • Zhang, Peng (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology) ;
  • Cherezov, Alexey (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology) ;
  • Lee, Deokjung (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology)
  • 투고 : 2020.04.06
  • 심사 : 2020.07.11
  • 발행 : 2021.03.25
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초록

Uncertainties are calculated for pressurized water reactor (PWR) spent nuclear fuel (SNF) characteristics. The deterministic code STREAM is currently being used as an SNF analysis tool to obtain isotopic inventory, radioactivity, decay heat, neutron and gamma source strengths. The SNF analysis capability of STREAM was recently validated. However, the uncertainty analysis is yet to be conducted. To estimate the uncertainty due to nuclear data, STREAM is used to perturb nuclear cross section (XS) and resonance integral (RI) libraries produced by NJOY99. The perturbation of XS and RI involves the stochastic sampling of ENDF/B-VII.1 covariance data. To estimate the uncertainty due to modeling parameters (fuel design and irradiation history), surrogate models are built based on polynomial chaos expansion (PCE) and variance-based sensitivity indices (i.e., Sobol' indices) are employed to perform global sensitivity analysis (GSA). The calculation results indicate that uncertainty of SNF due to modeling parameters are also very important and as a result can contribute significantly to the difference of uncertainties due to nuclear data and modeling parameters. In addition, the surrogate model offers a computationally efficient approach with significantly reduced computation time, to accurately evaluate uncertainties of SNF integral characteristics.

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과제정보

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT). (No. NRF-2019M2D2A1A03058371).

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피인용 문헌

  1. Analysis for the ARIANE GU3 sample: nuclide inventory and decay heat vol.7, 2021, https://doi.org/10.1051/epjn/2021013
  2. Bayesian method and polynomial chaos expansion based inverse uncertainty quantification of spent fuel using decay heat measurements vol.378, 2021, https://doi.org/10.1016/j.nucengdes.2021.111158
  3. On the use of criticality and depletion benchmarks for verification of nuclear data vol.161, 2021, https://doi.org/10.1016/j.anucene.2021.108415
  4. Comparison of nuclear data uncertainties with other nuclear fuel cycle uncertainty sources vol.45, pp.12, 2021, https://doi.org/10.1002/er.6992