This thesis describes new geometric decomposition tools for parallel computing. A new complete process of model preparation for parallel analysis is proposed 'and investigated. The process focuses on applying geometrical entities rather than mesh elements to the decomposition problem. The study starts with an exploration of different geometrical representations in order to select the most suitable representation-f6i:- the purpose of this research. Next, the model is orthogollalised and cut into blocks to create a decomposed orthogonal model. The blocks composing the model are allocated to a giyen number of processors using weight factors determined by a grid mesh generated for the model. Finally, the dccomposed orthogonal model is mapped back into its original shape while preserving the relationship between the mesh elements and geometrical entities. A number of different methodologies are successfully applied to perform the whole process. Fuzzy Logic and Genetic Algorithms are used to orthogonalise the original model. The Gcnetic Algorithms are also llscd for a graph partitioning problem, where a weighted graph is designed to represent the decomposed model. Additionally, Extreme Vertices Model inspired the model's representation required for decomposition. Each part of the whole process presented in this thesis is followed by examples and discussion.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:486873 |
| Date | January 2007 |
| Creators | Obiala, Renata |
| Publisher | Heriot-Watt University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10399/2042 |
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