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dc.contributor.advisorElster, Anne Cathrinenb_NO
dc.contributor.authorRovde, Jan Magnenb_NO
dc.date.accessioned2014-12-19T13:38:31Z
dc.date.available2014-12-19T13:38:31Z
dc.date.created2012-11-08nb_NO
dc.date.issued2012nb_NO
dc.identifier565804nb_NO
dc.identifierntnudaim:7970nb_NO
dc.identifier.urihttp://hdl.handle.net/11250/252864
dc.description.abstractThis project focuses on enhancing the HPC-Lab snow simulator, with the aim to be able to simulate more realistic features such avalanches as snow accumulates though looking at granular flows.A Predictive-Corrective Incompressible SPH method was implemented, but however due to uncertainty around the pressure correction dependence on density being computed correctly the granular and cohesive method was not implemented.Compared to weakly compressible SPH solution a speedup of 6.9 gained by the PCISPH solution.nb_NO
dc.languageengnb_NO
dc.publisherInstitutt for datateknikk og informasjonsvitenskapnb_NO
dc.subjectntnudaim:7970no_NO
dc.subjectMTDT datateknikkno_NO
dc.subjectKomplekse datasystemerno_NO
dc.titleReal-Time Granular Flow Simulation Using the PCISPH Method on GPGPU Devices Using CUDAnb_NO
dc.typeMaster thesisnb_NO
dc.source.pagenumber73nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskapnb_NO


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