Deterministically estimated fission source distributions for Monte Carlo k-eigenvalue problems

Abstract The standard Monte Carlo (MC) k-eigenvalue algorithm involves iteratively converging the fission source distribution using a series of potentially time-consuming inactive cycles before quantities of interest can be tallied. One strategy for reducing the computational time requirements of these inactive cycles is the Sourcerer method, in which a deterministic eigenvalue calculation is performed to obtain an improved initial guess for the fission source distribution. This method has been implemented in the Exnihilo software suite within SCALE using the SP N or S N solvers in Denovo and the Shift MC code. The efficacy of this method is assessed with different Denovo solution parameters for a series of typical k-eigenvalue problems including small criticality benchmarks, full-core reactors, and a fuel cask. It is found that, in most cases, when a large number of histories per cycle are required to obtain a detailed flux distribution, the Sourcerer method can be used to reduce the computational time requirements of the inactive cycles.

[1]  Forrest B. Brown,et al.  CONVERGENCE TESTING FOR MCNP5 MONTE CARLO EIGENVALUE CALCULATIONS , 2007 .

[2]  Cihangir Celik,et al.  Hybrid Technique in SCALE for Fission Source Convergence Applied to Used Nuclear Fuel Analysis , 2013 .

[3]  Alireza Haghighat,et al.  Study of methods of stationarity detection for monte carlo criticality analysis with KENO V.a , 2007 .

[4]  Tara M. Pandya,et al.  Hot zero power reactor calculations using the Insilico code , 2016, J. Comput. Phys..

[5]  Forrest B. Brown,et al.  A review of best practices for Monte Carlo criticality calculations , 2009 .

[6]  Gregory G. Davidson,et al.  Full Core Reactor Analysis: Running Denovo on Jaguar , 2013 .

[7]  G. I. Bell,et al.  Nuclear Reactor Theory , 1952 .

[8]  Tara M. Pandya,et al.  Implementation, capabilities, and benchmarking of Shift, a massively parallel Monte Carlo radiation transport code , 2016, J. Comput. Phys..

[9]  Thomas M. Evans,et al.  Efficient solution of the simplified PN equations , 2015, J. Comput. Phys..

[10]  W. Martin,et al.  Theory and applications of the fission matrix method for continuous-energy Monte Carlo , 2014 .

[11]  Forrest B. Brown,et al.  Stationarity Modeling and Informatics-Based Diagnostics in Monte Carlo Criticality Calculations , 2005 .

[12]  Tara M. Pandya,et al.  Shift Verification and Validation , 2016 .

[13]  Todd James Urbatsch.  Iterative acceleration methods for Monte Carlo and deterministic criticality calculations. , 1995 .

[14]  Benoit Forget,et al.  Monte Carlo power iteration: Entropy and spatial correlations , 2016 .

[15]  Kevin T. Clarno,et al.  Denovo: A New Three-Dimensional Parallel Discrete Ordinates Code in SCALE , 2010 .

[16]  Toshihiro Yamamoto,et al.  Reliable Method for Fission Source Convergence of Monte Carlo Criticality Calculation with Wielandt's Method , 2004 .