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    Finite element mesh optimization using genetic algorithms

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    Author
    Tonoyan, Arsen V.
    Issue Date
    2004
    Keywords
    Applied Mechanics.
    Engineering, Mechanical.
    Computer Science.
    Advisor
    Arabyan, Ara
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    In finite element analysis, structures are modeled as meshes of elements and nodes appropriate for the geometry, boundaries and loading of each structure. Typically, it is desirable to have a mesh which is finer in parts of the structure where stress gradients are high and coarser where such gradients are low. This is usually done by experienced engineers using intuition and previous experience. Otherwise, a fine mesh throughout the structure can be used which results in high computational costs. In this work, the possibility of using genetic algorithms for optimizing finite-element meshes is studied. The method is implemented on a number of simple loaded structures. The meshes used are generated using a number of parameters that can be varied randomly. Then the parameters are varied using operators appropriate to genetic algorithms such that the value of an objective function is minimized within a defined precision and iteration limit. The objective function used in this study is an energy-based error norm. The results obtained with this method are compared to those obtained from a commercial finite element package that incorporates its own mesh optimization algorithms.
    Type
    text
    Dissertation-Reproduction (electronic)
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Aerospace and Mechanical Engineering
    Degree Grantor
    University of Arizona
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