Acknowledgement
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT). (No.NRF-2019M2D1A1067205)
References
- Status of spent fuel storage for the first quarter of 2019 [Online]. (Available from: http://www.khnp.co.kr/board/BRD_000179/boardView.do?pageIndex=1&boardSeq=70138&mnCd=FN051304&schPageUnit=10&searchCondition=0&searchKeyword=, 2019-. Accessed on April 2019.
- G. Ilas, Liljenfeldt H, Decay heat uncertainty for BWR used fuel due to modeling and nuclear data uncertainties, Nucl. Eng. Des. 319 (2017) 176-184, https://doi.org/10.1016/j.nucengdes.2017.05.009.
- J. Jang, B. Ebiwonjumi, W. Kim, J. Park, J. Choe, D. Lee, Validation of spent nuclear fuel decay heat calculation by a two-step method, Nucl. Eng. Technol. (2021), https://doi.org/10.1016/j.net.2020.06.028.
- J. Jang, B. Ebiwonjumi, W. Kim, A. Cherezov, J. Park, D. Lee, Validation of Isotope Inventory Prediction for Back-End Cycle Management by Two-step Method, 2021, https://doi.org/10.1016/j.net.2021.01.009.
- O. Leray, D. Rochman, P. Grimm, H. Ferroukhi, A. Vasiliev, M. Hursin, G. Perret, A. Pautz, Nuclear data uncertainty propagation on spent fuel nuclide compositions, Ann. Nucl. Energy 94 (2016) 603-611, https://doi.org/10.1016/j.anucene.2016.03.023.
- N. Garcia-Herranz, O. Cabellos, J. Sanz, J. Juan, J.C. Kuijper, Propagation of statistical and nuclear data uncertainties in Monte Carlo burn-up calculations, Ann. Nucl. Energy 35 (2008) 714-730, https://doi.org/10.1016/j.anucene.2010.06.006.
- D. Rochman, A. Vasiliev, H. Ferroukhi, T. Zhu, S.C. van der Marck, A.J. Koning, Nuclear data uncertainty for criticality-safety: Monte Carlo vs. linear perturbation, Ann. Nucl. Energy 92 (2016) 150-160, https://doi.org/10.1016/j.anucene.2016.01.042.
- M.B. Chadwick, et al., ENDF/B-VII.1 nuclear data for science and technology: cross sections, covariances, fission product yields and decay data, Nucl. Data Sheets 112 (12) (2011) 2887-2996, https://doi.org/10.1016/j.nds.2011.11.002.
- Ornl, SCALE: A Modular Code System for Performing Standardized Computer Analyses for Licensing Evaluations, ORNL/TM-2005/39, Version 6, vol. 4, 2009.
- N. Garcia-Herranz, O. Cabellos, J. Sanz, Applicability of the MCNP-ACAB system to inventory prediction in high burn-up fuels: sensitivity/uncertainty estimates, in: Proc. Int. Conf. on Mathematics and Computation, M&C2005, Avignon, France, 2005.
- Validation of SCALE 5 Decay Heat Prediction for LWR Spent Nuclear Fuel. U.S.: U.S. National Regulatory Commission, NUREG/CR-6972, 2010.
- S. Choi, C. Lee, D. Lee, Resonance treatment using pin-based pointwise energy slowing-down method, J. Comput. Phys. 330 (2017) 134-155. https://doi.org/10.1016/j.jcp.2016.11.007
- J. Choe, S. Choi, P. Zhang, J. Park, W. Kim, H.C. Shin, H.S. Lee, J. Jung, D. Lee, Verification and validation of STREAM/RAST-K for PWR analysis, Nucl. Eng. Technol. 51 (2) (2019) 356-368. https://doi.org/10.1016/j.net.2018.10.004
- R.J.J. Stamm'ler, M.J. Abbate, Methods of Steady-State Reactor Physics in Nuclear Design, Academic Press, London, 1983.
- A. Yamamoto, K. Kinoshita, T. Watanabe, T. Endo, Uncertainty quantification of LWR core characteristics using random sampling method, Nucl. Sci. Eng. 181 (2015) 160-174, https://doi.org/10.13182/NSE14-152.
- R. Arcilla, et al., Processing neutron cross section covariances using NJOY-99 and PUFF-IV, Nucl. Data Sheets 109 (12) (2008) 2910-2914, https://doi.org/10.1016/j.nds.2008.11.033.
- D. Smith, Evaluated nuclear data covariances: the journey from ENDF/B-VII.0 to ENDF/BVII.1, Nucl. Data Sheets 112 (12) (2011) 3037-3053, https://doi.org/10.1016/j.nds.2011.11.004.
- P. Talou, P. Young, T. Kawano, et al., Quantification of uncertainties for evaluated neutron-induced reactions on actinides in the fast region, Nucl. Data Sheets 112 (12) (2011) 3054-3074, https://doi.org/10.1016/j.nds.2011.11.005.
- S. Hoblit, Y.-S. Cho, M. Herman, et al., Neutron cross section covariances for structural materials and fission products, Nucl. Data Sheets 112 (12) (2011) 3075-3097, https://doi.org/10.1016/j.nds.2011.11.006.
- B. Ebiwonjumi, S. Choi, M. Lemaire, D. Lee, H.C. Shin, H.S. Lee, Verification and validation of radiation source term capabilities in STREAM, Ann. Nucl. Energy 124 (2019) 80-87, https://doi.org/10.1016/j.anucene.2018.09.034.
- A. Quarteroni, R. Sacco, F. Saleri, Numerical Mathematics, 2007.
- S. Borresen, T. Bahadir, M. Kruners, Validation of CMS/SNF Calculations against Preliminary CLAB Decay Heat Measurements, Transactions of the American nuclear society, Omni Shoreham Hotel Washington, D.C, 2004. November 14-18.
- S. Borresen, Spent fuel analyses based on in-core fuel management calculations, in: Proc. of the PHYSOR 2004, The Physics of Fuel Cycles and Advanced Nuclear Systems: Global Developments, Chicago, Illinois, 2004. April 25-29.
- B. Ebiwonjumi, S. Choi, M. Lemaire, D. Lee, H.C. Shin, Lee Hs, Validation of lattice physics code STREAM for predicting pressurized water reactor spent nuclear fuel isotopic inventory, Ann. Nucl. Energy 120 (2018) 431-449, https://doi.org/10.1016/j.anucene.2018.06.002.
- B. Ebiwonjumi, C. Kong, P. Zhang, A. Cherezov, D. Lee, Uncertainty quantification of PWR spent fuel due to nuclear data and modelling parameters, Nucl. Eng. Technol. (2021), https://doi.org/10.1016/j.net.2020.07.012.
- R. Ihaka, R. Gentleman, R: a language for data analysis and graphics, J. Comput. Graph Stat. 5 (3) (1995) 299-314. https://doi.org/10.2307/1390807
- M. Matsumoto, T. Nishimura, Mersenne Twister: a 623-dimensionally equidistributed uniform pseudorandom number generator, ACM Trans. Model Comput. Simulat 8 (1) (1998). January pp.3-30. https://doi.org/10.1145/272991.272995
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