Convergence Acceleration of Fluid-Flow Computation with Special Emphasis on Multigrid Technique

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dc.contributor.authorKalita, Subhra Sankar
dc.date.accessioned2024-06-07T10:59:50Z
dc.date.available2024-06-07T10:59:50Z
dc.date.issued2022
dc.descriptionSupervisor: Dass, Anoop K
dc.description.abstractThis thesis is concerned with the study and analysis of various convergence-acceleration strategies that can help CFD practitioners to obtain their simulation results quickly. Convergence-acceleration can be achieved either by choosing a fast algorithm or by parallelizing the solution strategy. The multigrid method lies in the former category and is considered as one of the most powerful convergence-acceleration strategies. CUDA, which is a relatively new method for parallelizing CFD codes falls under the second category and as a part of the convergence-acceleration efforts embodied in this thesis, CUDA is used to parallelize LBM-based computationsen_US
dc.identifier.otherROLL NO.126103006
dc.identifier.urihttps://gyan.iitg.ac.in/handle/123456789/2632
dc.language.isoenen_US
dc.relation.ispartofseriesTH-2900;
dc.subjectMultigrid
dc.subjectLattice Boltzmann Method
dc.subjectGPU,CUDA
dc.subjectStreamfunction-velocity
dc.subjectConvergence Acceleration
dc.titleConvergence Acceleration of Fluid-Flow Computation with Special Emphasis on Multigrid Technique
dc.typeThesis
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