The work described in this thesis investigated the use of novel shape representations and algorithms for shape optimisation. The aim was to find techniques which could search through a large generality of shapes. This would allow a computer to be used in a more creative way to synthesise shapes for components given a specification of the desired function. Three examples of work done on shape optimisation using evolutionary algorithms and various shape representations and the problems encountered in linking them together effectively with the analysis module are described. These examples are aerofoil profile optimisation with a genetic algorithm, optimisation of a constructive solid geometry solid model with genetic programming and structural optimisation of a voxel shape representation with a genetic algorithm. Most shape optimisation techniques rely on three separate modules: an optimiser, a shape representation and an analysis method. Each of these modules uses a different internal data structure. This thesis argues that using a common data structure for each of these modules would allow a ' number of novel and effective algorithms for shape optimisation to be developed. The data structure proposed is based on Chain models using cell complexes and chains from algebraic topology. As an example of a new approach to shape optimisation enabled by the new data structure, a novel algorithm which adds a morphogenic stage to a genetic algorithm for structural optimisation is also described.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:661852 |
| Date | January 2003 |
| Creators | Sherlock, Andrew |
| Publisher | University of Edinburgh |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1842/14413 |
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