The Random Ray Method for neutral particle transport

Abstract A new approach to solving partial differential equations (PDEs) based on the method of characteristics (MOC) is presented. The Random Ray Method (TRRM) uses a stochastic rather than deterministic discretization of characteristic tracks to integrate the phase space of a problem. TRRM is potentially applicable in a number of transport simulation fields where long characteristic methods are used, such as neutron transport and gamma ray transport in reactor physics as well as radiative transfer in astrophysics. In this study, TRRM is developed and then tested on a series of exemplar reactor physics benchmark problems. The results show extreme improvements in memory efficiency compared to deterministic MOC methods, while also reducing algorithmic complexity, allowing for a sparser computational grid to be used while maintaining accuracy.

[1]  T. Peters,et al.  Radiation hydrodynamics using characteristics on adaptive decomposed domains for massively parallel star formation simulations , 2015, 1501.04501.

[2]  Andrew Siegel,et al.  Memory Bottlenecks and Memory Contention in Multi-Core Monte Carlo Transport Codes , 2014, ICS 2014.

[3]  Benoit Forget,et al.  The OpenMC Monte Carlo particle transport code , 2012 .

[4]  William Robert Dawson Boyd,et al.  Massively parallel algorithms for method of characteristics neutral particle transport on shared memory computer architectures , 2014 .

[5]  Edward W. Larsen,et al.  2D/1D approximations to the 3D neutron transport equation. I: Theory , 2013 .

[6]  R. Aggarwal,et al.  Error bars for distributions of numbers of events , 2011, 1112.2593.

[7]  Geoffrey Alexander Gunow,et al.  SimpleMOC - A performance abstraction for 3D MOC , 2015 .

[8]  Gamma ray transport simulations using SGaRD code , 2017 .

[9]  Benoit Forget,et al.  The OpenMOC method of characteristics neutral particle transport code , 2014 .

[10]  Cristian Rabiti,et al.  Recent research progress on UNIC at Argonne national laboratory , 2009 .

[11]  Cristian Rabiti,et al.  UNÌC: Ultimate Neutronic Investigation Code , 2007 .

[12]  T. Abel,et al.  enzo+moray: radiation hydrodynamics adaptive mesh refinement simulations with adaptive ray tracing , 2010, 1012.2865.

[13]  S. Santandrea,et al.  Optimized tracking strategies for step MOC calculations in extruded 3D axial geometries , 2016 .

[14]  A. Yamamoto,et al.  Derivation of Optimum Polar Angle Quadrature Set for the Method of Characteristics Based on Approximation Error for the Bickley Function , 2007 .

[15]  Jeffrey S. Oishi,et al.  Hybrid Adaptive Ray-Moment Method (HARM2): A highly parallel method for radiation hydrodynamics on adaptive grids , 2016, J. Comput. Phys..

[16]  K. Kim,et al.  Gamma transport and diffusion calculation capability coupled with neutron transport simulation in KARMA 1.2 , 2013 .

[17]  J. Mark Bull Single Node Performance Analysis of Applications on HPCx , 2007 .

[18]  Brendan Matthew Kochunas,et al.  A Hybrid Parallel Algorithm for the 3-D Method of Characteristics Solution of the Boltzmann Transport Equation on High Performance Compute Clusters. , 2013 .

[19]  Richard Sanchez,et al.  PROSPECTS IN DETERMINISTIC THREE-DIMENSIONAL WHOLE-CORE TRANSPORT CALCULATIONS , 2012 .

[20]  G. Marleau,et al.  Computation of 3D neutron fluxes in one pin hexagonal cell , 2013 .

[21]  A. Hébert,et al.  Tracking algorithms for multi-hexagonal assemblies (2D and 3D) , 2014 .

[22]  Kord Smith,et al.  Linear source approximation in CASMO5 , 2012 .

[23]  Bryan R. Herman,et al.  Monte Carlo and thermal hydraulic coupling using low-order nonlinear diffusion acceleration , 2014 .

[24]  G. Mellema,et al.  Hybrid Characteristics: 3D radiative transfer for parallel adaptive mesh refinement hydrodynamics , 2005, astro-ph/0505213.

[25]  E. D. Walker Modeling Integral Fuel Burnable Absorbers Using the Method of Characteristics , 2014 .

[26]  Andrew R. Siegel,et al.  A task-based parallelism and vectorized approach to 3D Method of Characteristics (MOC) reactor simulation for high performance computing architectures , 2016, Comput. Phys. Commun..

[27]  Fernando Porcelli,et al.  On the black hole’s thermodynamics and the entropic origin of gravity , 2010 .

[28]  Miltiadis Alamaniotis,et al.  Method of characteristics – A review with applications to science and nuclear engineering computation , 2015 .