The Random Ray Method for neutral particle transport

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 a...

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Bibliographic Details
Published in:Journal of computational physics 2017-08, Vol.342
Main Authors: Tramm, John R., Argonne National Laboratory, Mathematics and Computer Science Department 9700 S Cass Ave, Argonne, IL 60439, Smith, Kord S., Forget, Benoit, Siegel, Andrew R.
Format: Article
Language:English
Subjects:
ACCURACY
ASTROPHYSICS
BENCHMARKS
CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS
COMPARATIVE EVALUATIONS
COMPUTERIZED SIMULATION
EFFICIENCY
GAMMA RADIATION
MATHEMATICAL METHODS AND COMPUTING
NEUTRAL PARTICLES
NEUTRON TRANSPORT
PARTIAL DIFFERENTIAL EQUATIONS
PARTICLE TRACKS
PHASE SPACE
RADIANT HEAT TRANSFER
RANDOMNESS
REACTOR PHYSICS
STOCHASTIC PROCESSES
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Summary: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.
ISSN:0021-9991
1090-2716
DOI:10.1016/J.JCP.2017.04.038