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dc.contributor.authorTramm, John R.
dc.contributor.authorSmith, Kord S.
dc.contributor.authorForget, Benoit
dc.contributor.authorSiegel, Andrew R.
dc.date.accessioned2022-06-13T19:18:48Z
dc.date.available2021-10-27T20:29:15Z
dc.date.available2022-06-13T19:18:48Z
dc.date.issued2018-02
dc.date.submitted2017-10
dc.identifier.issn0306-4549
dc.identifier.urihttps://hdl.handle.net/1721.1/135776.2
dc.description.abstract© 2017 Elsevier Ltd A massively parallel implementation of a recently developed technique for numerically integrating the transport equation, The Random Ray Method (TRRM) (Tramm et al., 2017), is applied to several large reactor benchmark problems. The implementation, which is part of a new development called The Advanced Random Ray Code (ARRC), is one of the first parallel implementations of TRRM. Our goal is to better understand the accuracy and performance characteristics of TRRM on massive scale problems, and to provide community software that facilitates further algorithmic development and potentially its application to a broader class of problems. Key features of ARRC include extreme memory efficiency, domain decomposition, a task based parallel structure, and the ability to efficiently utilize Single Instruction Multiple Data (SIMD) vector units. These attributes lead to efficient performance on modern high performance computer (HPC) architectures, enabling the detailed simulation of reactor cores in three dimensions.en_US
dc.language.isoen
dc.publisherElsevier BVen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.anucene.2017.10.015en_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourceProf. Forget via Chris Sherratten_US
dc.titleARRC: A random ray neutron transport code for nuclear reactor simulationen_US
dc.typeArticleen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Nuclear Science and Engineering
dc.relation.journalAnnals of Nuclear Energyen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2019-09-24T16:11:07Z
dspace.orderedauthorsTramm, JR; Smith, KS; Forget, B; Siegel, ARen_US
dspace.date.submission2019-09-24T16:11:09Z
mit.journal.volume112en_US
mit.metadata.statusAuthority Work Neededen_US


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