Cellular automata as an approximate method in structural analysis

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dc.contributor.advisor Groenwold, Albert A. en
dc.contributor.postgraduate Hindley, Michael Philip en
dc.date.accessioned 2013-09-07T14:59:49Z
dc.date.available 2005-11-01 en
dc.date.available 2013-09-07T14:59:49Z
dc.date.created 2002-09-01 en
dc.date.issued 2006-11-01 en
dc.date.submitted 2005-10-31 en
dc.description Dissertation (MEng (Mechanical Engineering))--University of Pretoria, 2006. en
dc.description.abstract This thesis deals with the mathematical idealization denoted cellular automata (CA) and the applicability of this method to structural mechanics. When using CA, all aspects such as space and time are discrete. This discrete nature of CA allows for ease of interaction with digital computers, while physical phenomena which are essentially discrete in nature can be simulated in a realistic way. The application of such a novel numerical method opens up new possibilities in structural analysis. In this study, the fundamentals of CA are studied to determine how the parameters of the method are to be evaluated and applied to the established field of structural analysis. Attention is given to the underlying mathematics of structural mechanics, as well as approximate methods currently used in structural analysis, e.g. the finite element method (FEM) and the boundary element method (BEM). For structural simulations performed with the CA implemented in this study, machine learning based on a genetic algorithm (GA) is used to determine optimum rules for the CA, using finite element, boundary element and analytical approximations as the basis for machine learning. Rather unconventionally, symmetric problems in structural analysis are analyzed using asymmetric rules in the machine learning process, where the symmetry of the solution found is used as a quantitative indication of the quality of the solution. It is demonstrated that the quality of the asymmetric rules is superior to the quality of symmetric rules, even for those problems that are symmetric in nature. Finally, exploiting the inherent parallelism of CA, it is shown that distributed computing can greatly improve the efficiency of the CA simulation, even though the speed-up factor is not necessarily proportional to the number of sub lattices used. The distributed computing device itself is constructed by combining 18 obsolete Pentium computers in a single cluster. In terms of CPU performance the constructed distributed computer is not state-of-art, but it is constructed with no hardware costs whatsoever. In addition, the software used in assembling the cluster is in the public domain, and is also available free of charge. Such a parallel configuration is also known as the poor man’s computer. However, faster and more modern machines can simply be added to the existing cluster as and when they become available. While CA are recent additions to the “tools” used in structural analysis, increased use of CA as distributed computing becomes more widely available is envisaged, even though the CA rules are at this stage not transferable between different problems or even between meshes of varying refinement for a given problem. en
dc.description.availability unrestricted en
dc.description.department Mechanical and Aeronautical Engineering en
dc.identifier.citation Hindley, MP 2002, Cellular automata as an approximate method in structural analysis, MEng dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://hdl.handle.net/2263/29150 > en
dc.identifier.other H147/ag en
dc.identifier.upetdurl http://upetd.up.ac.za/thesis/available/etd-10312005-101342/ en
dc.identifier.uri http://hdl.handle.net/2263/29150
dc.language.iso en
dc.publisher University of Pretoria en_ZA
dc.rights © 2002, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. en
dc.subject Cellular automata en
dc.subject Structural analysis en
dc.subject UCTD en_US
dc.title Cellular automata as an approximate method in structural analysis en
dc.type Dissertation en


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