New Parallel Group Accelerated Overrelaxation Algorithms For The Solution Of 2-D Poisson And Diffusion Equations

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dc.contributor.authorFoo, Kai Pin
dc.date.accessioned2018-12-11T06:37:28Z
dc.date.available2018-12-11T06:37:28Z
dc.date.issued2011-12
dc.description.abstractFinite difference method is commonly used to solve partial differential equations (PDEs) which arise from fluid mechanics and thermodynamics problem. However, the discretization of these PDEs oftenly lead to large sparse linear systems which require large amount of execution times to solve. The development in accelerated iterative techniques and parallel computing technologies can be utilized to surmount this problem. Point iterative schemes which are based on the standard five point discretization and the rotated five point discretization are commonly used to solve the Poisson equation. In addition, block or group iterative schemes where the mesh points are grouped into block have been shown to reduce the number of iterations and execution timings because the solution at the mesh points can be updated in groups or blocks instead of pointwise. Among these group iterative schemes, the Explicit Group (EG) method (Yousif and Evans, 1986) and Explicit Decoupled Group (EDG) method (Abdullah, 1990) have been extensively researched and have been shown to converge faster than their pointwise counterparts. In order to improve the rate of convergence of these methods, the common accelerated methods such as Successive OverRelaxation (SOR) method and Accelerated OverRelaxation (AOR) method may be applied to these methods and have been shown to reduce the number of iterations.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/7258
dc.language.isoenen_US
dc.publisherUniversiti Sains Malaysiaen_US
dc.subjectParallel group accelerated overrelaxation algorithmsen_US
dc.subjectsolution of 2-D poisson and diffusion equationsen_US
dc.titleNew Parallel Group Accelerated Overrelaxation Algorithms For The Solution Of 2-D Poisson And Diffusion Equationsen_US
dc.typeThesisen_US
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