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All issues Volume 11 (2025) EPJ Nuclear Sci. Technol., 11 (2025) 1 References
Issue
EPJ Nuclear Sci. Technol.
Volume 11, 2025
Status and advances of Monte Carlo codes for particle transport simulation
Article Number 1
Number of page(s) 7
DOI https://doi.org/10.1051/epjn/2024020
Published online 08 January 2025
  1. T. Mori, M. Nakagawa, JAERI-Data/Code 94-007 (1994) [Google Scholar]
  2. Y. Nagaya, K. Okumura, T. Mori, M. Nakagawa, JAERI 1348 (2005) [Google Scholar]
  3. Y. Nagaya, K. Okumura, T. Sakurai, T. Mori, JAEA-Data/Code 2016-018 (2017) [Google Scholar]
  4. Y. Nagaya, T. Ueki, K. Tonoike, Solomon: A Monte Carlo solver for criticality safety analysis, in Proceedings of the 11th International Conference on Nuclear Criticality Safety (ICNC 2019), 15-2 September 2019, Paris, France (2019) [Google Scholar]
  5. T. Mori, Y. Nagaya, K. Okumura, K. Kaneko, JAERI-Data/Code 2004-011 (2004) [Google Scholar]
  6. L.B. Levitt, Nucl. Sci. Eng. 49, 450 (1972) [CrossRef] [Google Scholar]
  7. T. Mori, M. Nakagawa, M. Sasaki, J. Nucl. Sci. Technol. 29, 325 (1992) [CrossRef] [Google Scholar]
  8. OECD/NEA, NEA/NSC/DOC (95)03, July 2019 Edition, OECD/NEA (2019) [Google Scholar]
  9. OECD/NEA, NEA/NSC/DOC (2006)1, March 2012 Edition, OECD/NEA (2012) [Google Scholar]
  10. K. Shibata, et al., J. Nucl. Sci. Technol. 48, 1 (2011) [CrossRef] [Google Scholar]
  11. K. Tada, et al., J. Nucl. Sci. Technol. 61, 222 (2023) [Google Scholar]
  12. O. Iwamoto, et al., J. Nucl. Sci. Technol. 60, 160 (2023) [Google Scholar]
  13. I. Murata, T. Mori, M. Nakagawa, Nucl. Sci. Eng. 123, 96 (1996) [CrossRef] [Google Scholar]
  14. K. Okumura, et al., J. Nucl. Sci. Technol. 37, 128 (2000) [CrossRef] [Google Scholar]
  15. R.J. Stamm'ler, M.J. Abbate, Methods of Steady-State Reactor Physics in Nuclear Design (Academic Press, London, 1983) [Google Scholar]
  16. Y. Nagaya, T. Mori, J. Nucl. Sci. Technol. 42, 428 (2005) [CrossRef] [Google Scholar]
  17. Y. Nagaya, T. Mori, Prog. Nucl. Sci. Technol. 2, 842 (2011) [CrossRef] [Google Scholar]
  18. Y. Nagaya, K. Okumura, T. Mori, Recent developments of JAEA's Monte Carlo Code MVP for reactor physics applications, in Proceedings of the Joint International Conference on Supercomputing in Nuclear Applications and Monte Carlo 2013 (SNA+MC 2013), 27-31 October 2013, Paris, France (2013) [Google Scholar]
  19. Y. Nagaya, T. Mori, Ann. Nucl. Energy 38, 254 (2011) [CrossRef] [Google Scholar]
  20. Y. Nagaya, Ann. Nucl. Energy 82, 226 (2015) [CrossRef] [Google Scholar]
  21. https://rpg.jaea.go.jp/main/en/download_mvp3 [Google Scholar]
  22. N.E. Horelik, B.R. Herman, B. Forget, K.S. Smith, Benchmark for Evaluation and Validation of Reactor Simulations (BEAVRS), in Proceedings of the International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2013), 59 May 2013, Sun Valley, Idaho, USA (2013) [Google Scholar]
  23. M. Suzuki, Y. Nauchi, Analysis of BEAVRS benchmark problem by using enhanced monte carlo code MVP with JENDL-4.0, in Proceedings of Joint International Conference on Mathematics and Computation (M&C), Supercomputing in Nuclear Applications (SNA) and the Monte Carlo (MC) Method (M&C+SNA+MC 2015), 19-23 April 2015, Nashville, Tennessee, USA (2015) [Google Scholar]
  24. M. Suzuki, Y. Nauchi, Analysis of BEAVRS revision 2.0 LWR whole core calculation using MVP with JENDL-4.0, in Proceedings of International Conference on Mathematics & Computational Methods Applied to Nuclear Science & Engineering (M&C 2017), 16-20 April 2017, Jeju, Korea (2017) [Google Scholar]
  25. N. Horelik, B. Herman, B. Forget, K. Smith, Benchmark for Evaluation and Validation of Reactor Simulations (BEAVRS), RELEASE v. 2.0.2, MIT Computational Reactor Physics Group, USA, April 11 (2018) [Google Scholar]
  26. S. Yamashita, T. Ina, Y. Idomura, H. Yoshida, Nucl. Eng. Des. 332, 301 (2017) [CrossRef] [Google Scholar]
  27. T. Kamiya, et al., Neutronics/thermal-hydraulics coupling simulation using JAMPAN in a single BWR fuel assembly, in Proceedings of the 31st International Conference on Nuclear Engineering (ICONE31), 4-8 August 2024, Prague, Czech Republic (2024) [Google Scholar]
  28. K. Tada, et al., Development of high-fidelity multi-physics platform JAMPAN, in Proceedings of the International Conference on Physics of Reactors (Physor 2024), 21-24 April 2024, San Francisco, California, USA (2024) [Google Scholar]
  29. T. Hino, et al., Core design of RBWR (Resource-renewable Boiling Water Reactor) and benchmark calculation of core analysis tools, in Proceedings of the International Congress on Advances in Nuclear Power Plants (ICAPP 2019), 12-15 May 2019, Juan-les-pins, France (2019) [Google Scholar]
  30. K. Yokoi, et al., Study of neutronics calculation applicability for heterogeneous core of RBWR (Resource-renewable Boiling Water Reactor), in Proceedings of the International Congress on Advances in Nuclear Power Plants (ICAPP2021), 16-20 October 2021, Abu Dhabi, UAE (2021) [Google Scholar]
  31. K. Okumura, Sophistication of Analysis Method, JAERI-Research 2000-035 (2000), pp. 98–161 [Google Scholar]
  32. X-5 Monte Carlo Team, LA-CP-03-0284 (2003) [Google Scholar]
  33. K. Tada, A. Yamamoto, S. Kunieda, et al., Development of nuclear data processing code FRENDY version 2, J. Nucl. Sci. Technol. 61, 830 (2024) [CrossRef] [Google Scholar]
  34. R.E. MacFarlane, et al., LA-UR-17-20093 (2017) [Google Scholar]
  35. X-5 Monte Carlo Team, LA-UR-03-1987 (2003) [Google Scholar]
  36. J. Spanier, E.M. Gelbard, Monte Carlo Principle and Neutron Transport Problems (Addison-Weslay, New York, 1969) [Google Scholar]
  37. T. Ueki, Monte Carlo criticality analysis under material distribution uncertainty, J. Nucl. Sci. Technol. 54, 267 (2017) [Google Scholar]
  38. OECD/NEA, Criticality Calculations in Random Media, NEA/WPNCS SG9 report (to be appeared) [Google Scholar]
  39. Y. Nagaya, Solution to random-media criticality benchmarks with a Monte Carlo solver Solomon, in Proceedings of the 12th International Conference on Nuclear Criticality Safety (ICNC 2023), 16 October 2023, Sendai, Japan (2023) [Google Scholar]
  40. T. Ueki, Monte carlo criticality calculation of random media formed by multimaterials mixture under extreme disorder, Nucl. Sci. Eng. 195, 214 (2021) [CrossRef] [Google Scholar]
  41. T. Ueki, Weierstrass function methodology for uncertainty analysis of random media criticality with spectrum range control, Prog. Nucl. Energy 144, 104099 (2022) [CrossRef] [Google Scholar]

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