858
Views
0
CrossRef citations to date
0
Altmetric
Technical Papers

Monte Carlo Source Convergence Acceleration by Hybrid Multigroup and Continuous Energy Neutron Transport

ORCID Icon, , &
Pages 364-380 | Received 18 Mar 2022, Accepted 19 Jul 2022, Published online: 12 Sep 2022

References

  • F. B. BROWN, “Fundamentals of Monte Carlo Particle Transport” (2005).
  • F. B. BROWN, “On the Use of Shannon Entropy of the Fission Distribution for Assessing Convergence of Monte Carlo Criticality Calculations,” Proc. PHYSOR 2006, Vancouver, British Columbia (2006).
  • B. R. HERMAN, “Monte Carlo and Thermal Hydraulic Coupling Using Low-Order Nonlinear Diffusion Acceleration,” PhD Thesis, Massachusetts Institute of Technology, Department of Nuclear Science and Engineering (2014).
  • E. DUMONTEIL et al., “Particle Clustering in Monte Carlo Criticality Simulations,” Ann. Nucl. Energy, 63, 612 (Jan. 2014); https://doi.org/10.1016/j.anucene.2013.09.008.
  • J. LEPPÄNEN, “Acceleration of Fission Source Convergence in the Serpent 2 Monte Carlo Code Using a Response Matrix Based Solution for the Initial Source Distribution,” Ann. Nucl. Energy, 128, 63 (2019); https://doi.org/10.1016/j.anucene.2018.12.044.
  • J. LEPPÄNEN et al., “The Serpent Monte Carlo Code: Status, Development and Applications in 2013,” Ann. Nucl. Energy, 82, 142 (2015); https://doi.org/10.1016/j.anucene.2014.08.024.
  • M. J. LEE et al., “Coarse Mesh Finite Difference Formulation for Accelerated Monte Carlo Eigenvalue Calculation,” Ann. Nucl. Energy, 65, 101 (2014); https://doi.org/10.1016/j.anucene.2013.10.025.
  • K. P. KEADY and E. W. LARSEN, “Stability of Monte Carlo k-eigenvalue Simulations with CMFD Feedback,” J. Comput. Phys., 321, 947 (2016); https://doi.org/10.1016/j.jcp.2016.06.002.
  • T. J. URBATSCH, “Iterative Acceleration Methods for Monte Carlo and Deterministic Criticality Calculations,” PhD Thesis, University of Michigan, Department of Nuclear Engineering and Radiological Sciences (1995).
  • A. L. LUND, P. K. ROMANO, and A. R. SIEGEL, “Accelerating Source Convergence in Monte Carlo Criticality Calculations Using a Particle Ramp-up Technique,” presented at the Int. Conf. on Mathematics & Computational Methods Applied to Nuclear Science & Engineering, Jeju, Korea (2017).
  • M. A. KOWALSKI, “Variable Fidelity Monte Carlo Neutron Transport,” PhD Thesis, University of Cambridge, Department of Engineering (2020).
  • V. RAFFUZZI et al., “Monte Carlo Source Convergence Acceleration by Multi-group Inactive Cycles,” presented at PHYSOR 2022 (2022).
  • J. R. TRAMM and A. R. SIEGEL, “Memory Bottlenecks and Memory Contention in Multi-core Monte Carlo Transport Codes,” Int. J. High Perform. Comput. Appl., 28, 1, 04208 (2014).
  • M. A. KOWALSKI et al., “SCONE: A Student-Oriented Modifiable Monte Carlo Particle Transport Framework,” presented at PHYSOR 2020, Cambridge, United Kingdom (2020).
  • J. LEPPÄNEN, “Development of a New Monte Carlo Reactor Physics Code,” PhD Thesis, Helsinki University of Technology, Department of Physics (2007).
  • W. BOYD et al., “Multigroup Cross-Section Generation with the OpenMC Monte Carlo Particle Transport Code,” Nucl. Technol., 205, 7, 928 (2019); https://doi.org/10.1080/00295450.2019.1571828.
  • M. NOWAK et al., “Monte Carlo Power Iteration: Entropy and Spatial Correlations,” Ann. Nucl. Energy, 94, 856 (2016); https://doi.org/10.1016/j.anucene.2016.05.002.
  • M. GARCÍA et al., “Validation of Serpent-SUBCHANFLOW-TRANSURANUS pin-by-pin Burnup Calculations Using Experimental Data from the Temelín II VVER-1000 Reactor,” Nucl. Eng. Technol., 53, 10, 3133 (2021); https://doi.org/10.1016/j.net.2021.04.023.
  • K. WANG et al., “Analysis of BEAVRS Two-Cycle Benchmark Using RMC Based on Full Core Detailed Model,” Prog. Nucl. Energy, 98, 301 (2017); https://doi.org/10.1016/j.pnucene.2017.04.009.
  • S. HARPER, “Tally Derivative Based Surrogate Models for Faster Monte Carlo Multiphysics,” PhD Thesis, Massachusetts Institute of Technology, Department of Nuclear Science and Engineering (2020).
  • “Benchmark on Deterministic Transport Calculations Without Spatial Homogenisation, A 2-D/3-D MOX Fuel Assembly Benchmark,” Technical Report, Organisation for Economic Co-operation and Development (2003).
  • D. J. KELLY, T. M. SUTTON, and S. C. WILSON, “MC21 Analysis of the Nuclear Energy Agency Monte Carlo Performance Benchmark Problem,” Proc. PHYSOR 2012, Pittsburgh, Pennsylvania (2012).