Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.637847
Title: A self-organising approach to problems in computational science
Author: Langham, A. E.
Awarding Body: University of Wales Swansea
Current Institution: Swansea University
Date of Award: 2000
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Abstract:
In this thesis, problems from computational science are tackled using a swarm-based approach. The application areas considered are related to the use of the Finite Element Method which involves the simulation of complex fluid flow. The problem domain is first discretised into a set of geometrical elements and solution for quantities such as material strain or pressure is computed at the element nodes. This discretisation of the domain is known as mesh generation. The problem can then be divided for parallel execution. This is known as partitioning and must divide the task equally amongst processors such that the communication is minimised. Communication occurs when two connected nodes are assigned to different processors. Standard approaches to these problems use recursive methods in which the final solution is dependent on solutions found at higher levels. For example partitioning into k sets is done using recursive bisection and meshing is often performed by creating an initial coarse-grained mesh and inserting extra nodes into the existing elements to achieve the required density. The inherently parallel, distributed nature of the swarm-based approach allows us to simultaneously partition into k sets or create different parts of the mesh at the same time. Furthermore, because this approach is dependent only on the state of the local environment it is ideal for problems of an adaptive nature which are difficult for standard approaches to tackle. Results show that this approach is superior in quality when compared to standard methods. However, it is not as efficient and hence we outline various improvements to both speed up and improve the quality of the methods presented. A discussion of potential applications is also provided to indicate the general applicability of this approach to problems in computational science.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.637847  DOI: Not available
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