An Optimum Approach to Monte Carlo Burnup

Abstract Monte Carlo codes are powerful and accurate tools for reactor core calculations. For coupled core-evolution applications, however, they remain rather demanding on calculation time because of the sheer number of reaction rates required for the evolution calculation. To make Monte Carlo burnup codes more efficient, we must therefore optimize reaction rate calculation to reduce calculation time without loss of accuracy. In the optimal situation, the calculation time of the Monte Carlo burnup code should be as close as possible to that of the basic Monte Carlo simulation. Through a deep analysis of the Monte Carlo simulation process as implemented in MCNP or MCNPX, we have developed an optimum approach called hereafter the multigroup binning approach to reaction rate calculation. In this paper, we have analyzed the performance of the multigroup binning approach as compared to a generic Monte Carlo burnup code. We have implemented this multigroup binning approach into ALEPH, a C++ interface code coupling MCNP or MCNPX, and ORIGEN. A number of validation benchmarks and applications of ALEPH to particular problems such as the rim effect and the High Flux Isotope Reactor of Oak Ridge National Laboratory have also been presented.

[1]  R.E. MacFarlane,et al.  The NJOY Nu-clear Data Processing System Version 91 , 1994 .

[2]  C. A. Wemple,et al.  MOCUP: MCNP-ORIGEN2 coupled utility program , 1995 .

[3]  J. F. Briesmeister MCNP-A General Monte Carlo N-Particle Transport Code , 1993 .

[4]  Ned Xoubi,et al.  CHARACTERIZATION OF EXPOSURE-DEPENDENT EIGENVALUE DRIFT USING MONTE CARLO BASED NUCLEAR FUEL MANAGEMENT , 2005 .

[5]  A. G. Croff,et al.  User's manual for the ORIGEN2 computer code , 1980 .

[6]  Peng Hong Liem Phase IV-B: Results and Analysis of MOX Fuel Depletion Calculations , 2003 .

[7]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[8]  D. Papaioannou,et al.  On the thermal conductivity of UO2 nuclear fuel at a high burn-up of around 100 MWd/kgHM , 2006 .

[9]  M. V. Wilkes,et al.  The Art of Computer Programming, Volume 3, Sorting and Searching , 1974 .

[10]  Donald E. Knuth,et al.  The Art of Computer Programming: Volume 3: Sorting and Searching , 1998 .

[11]  Wim Haeck,et al.  Application of EPMA Data for the Development of the Code Systems TRANSURANUS and ALEPH , 2007, Microscopy and Microanalysis.

[12]  R. Manzel,et al.  EPMA and SEM of fuel samples from PWR rods with an average burn-up of around 100 MWd/kgHM , 2002 .

[13]  A. Santamarina,et al.  VALMOX: validation of nuclear data for high burn-up MOX fuels , 2005 .

[14]  H. Yoriyaz,et al.  Transmutation Feature Within MCNPX , 2004 .

[15]  K. Lassmann,et al.  The radial distribution of plutonium in high burnup UO2 fuels , 1994 .

[16]  I. Lux Monte Carlo Particle Transport Methods: Neutron and Photon Calculations , 1991 .