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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Veröffentlicht in: | Journal of computational physics 2017-08, Vol.342 |
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container_title | Journal of computational physics |
container_volume | 342 |
creator | 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. |
description | 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. |
doi_str_mv | 10.1016/J.JCP.2017.04.038 |
format | Article |
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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. 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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.</abstract><cop>United States</cop><doi>10.1016/J.JCP.2017.04.038</doi></addata></record> |
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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 |
title | The Random Ray Method for neutral particle transport |
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