Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
권호 표지
DOI QR코드

DOI QR Code

An assessment of the applicability of multigroup cross sections generated with Monte Carlo method for fast reactor analysis

  • Received : 2019.12.24
  • Accepted : 2020.05.27
  • Published : 2020.12.25
Download PDF
⟨ Previous Next ⟩

Abstract

This paper presents an assessment of applicability of the multigroup cross sections generated with Monte Carlo tools to the fast reactor analysis based on transport calculations. 33-group cross section sets were generated for simple one- (1-D) and two-dimensional (2-D) sodium-cooled fast reactor problems using the SERPENT code and applied to deterministic steady-state and depletion calculations. Relative to the reference continuous-energy SERPENT results, with the transport corrected P0 scattering cross section, the k-eff value was overestimated by 506 and 588 pcm for 1-D and 2-D problems, respectively, since anisotropic scattering is important in fast reactors. When the scattering order was increased to P5, the 1-D and 2-D problem errors were increased to 577 and 643 pcm, respectively. A sensitivity and uncertainty analysis with the PERSENT code indicated that these large k-eff errors cannot be attributed to the statistical uncertainties of cross sections and they are likely due to the approximate anisotropic scattering matrices determined by scalar flux weighting. The anisotropic scattering cross sections were alternatively generated using the MC2-3 code and merged with the SERPENT cross sections. The mixed cross section set consistently reduced the errors in k-eff, assembly powers, and nuclide densities. For example, in the 2-D calculation with P3 scattering order, the k-eff error was reduced from 634 pcm to -223 pcm. The maximum error in assembly power was reduced from 2.8% to 0.8% and the RMS error was reduced from 1.4% to 0.4%. The maximum error in the nuclide densities at the end of 12-month depletion that occurred in 237Np was reduced from 3.4% to 1.5%. The errors of the other nuclides are also reduced consistently, for example, from 1.1% to 0.1% for 235U, from 2.2% to 0.7% for 238Pu, and from 1.6% to 0.2% for 241Pu. These results indicate that the scalar flux weighted anisotropic scattering cross sections of SERPENT may not be adequate for application to fast reactors where anisotropic scattering is important.

Keywords

Acknowledgement

This research was performed using funding received from the DOE Office of Nuclear Energy's Nuclear Energy University Program.

References

  1. E. Fridman, J. Leppanen, On the use of the serpent Monte Carlo code for few-group cross section generation, Ann. Nucl. Energy 38 (2011) 1399-1405.
  2. H.J. Park, H.J. Shim, H.G. Joo, C.H. Kim, Generation of few-group diffusion constants by Monte Carlo code McCARD, Nucl. Sci. Eng. 172 (2012) 66-77.
  3. J. Navarro, M.D. DeHart, MCNP and SCALE 6.1 cross section evaluation for ATR-C verification and validation applications, Trans. Am. Nucl. Soc. 107 (2012) 1002-1006.
  4. A. Scopatz, E. Schneider, Interpolations of nuclide-specific scattering kernels generated with SERPENT, Proc. of PHYSOR (2012). ANS International Topical Meeting on Advances in Reactor Physics, Knoxville, Tennessee, April 15-20, 2012.
  5. A.G. Nelson, W.R. Martin, Improved Monte Carlo tallying of multi-group scattering moments using the NDPP code, Trans. Am. Nucl. Soc. 113 (2015) 645-648.
  6. S.Y. Yoo, H.J. Shim, C.H. Kim, Monte-carlo few-group constant generation for CANDU-6 core analysis, Sci. Technol. Nucl. Installations 2015 (2015).
  7. J. Ortensi, et al., Analysis of the HTR-10 initial critical core with the MAMMOTH reactor physics application, Trans. Am. Nucl. Soc. 119 (2018) 1103-1107.
  8. C.H. Lee, Y.S. Jung, Generation of the Cross Section Library for PROTEUS, Argonne National Laboratory, 2018. ANL/NE-18/2.
  9. J. Leppanen, M. Pusa, E. Fridman, Overview of methodology for spatial homogenization in the serpent 2 Monte Carlo code, Ann. Nucl. Energy 96 (2016) 126-136.
  10. F. Fejt, J. Frybort, Analysis of a small-scale reactor core with PARCS/serpent, Ann. Nucl. Energy 117 (2018) 25-31.
  11. W.S. Yang, Fast reactor physics and computational methods, Nuclear Engineering and Technology 44 (2012) 177-198.
  12. C.H. Lee, W.S. Yang, MC2-3: Multigroup Cross Section Generation Code for Fast System Analysis, Argonne National Laboratory, 2011. ANL/NE-11-41.
  13. C. Lim, H.G. Joo, W.S. Yang, Development of a fast reactor multigroup cross section generation code EXUS-F capable of direct processing of evaluated nuclear data files, Nuclear Engineering and Technology 50 (2018) 340-355.
  14. J. Leppanen, et al., The serpent Monte Carlo code: status, development, and applications in 2013, Ann. Nucl. Energy 82 (2015) 142-150.
  15. K.L. Derstine, DIF3D: A Code to Solve One-, Two-, and Three-Dimensional Finite Difference Diffusion Theory Problem, Argonne National Laboratory, 1984. ANL-82-64.
  16. R.D. Lawrence, The DIF3D Nodal Neutronics Option for Two- and Three-Dimensional Diffusion Theory Calculations in Hexagonal Geometry, Argonne National Laboratory, 1983. ANL-83-1.
  17. G. Palmiotti, E.E. Lewis, C.B. Carrico, VARIANT: Variational Anisotropic Nodal Transport for Multi-Dimensional Cartesian and Hexagonal Geometry Calculation, Argonne National Laboratory, 1995. ANL-95/40.
  18. M.A. Smith, C. Adams, W.S. Yang, E.E. Lewis, VARI3D & PERSENT: Perturbation and Sensitivity Analysis, Argonne National Laboratory, 2013. ANL/NE-13/8.
  19. B.J. Toppel, A User's Guide to the REBUS-3 Fuel Cycle Analysis Capability, Argonne National Laboratory, 1995. ANL-83-2.
  20. C.S. Lin, T.K. Park, W.S. Yang, Core design studies of a fast reactor and accelerator-driven system for two-stage fast spectrum fuel cycle option, Nucl. Technol. 1 (2017) 29-46.
  21. C.S. Lin, Design and Analysis of Sodium-Cooled Fast Reactor Systems for Nuclear Waste Minimization, Purdue University, 2018 (Ph.D Thesis).