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Adaptive Analysis Refinement and Shape Optimization—Some New Possibilities

  • Chapter
The Optimum Shape

Part of the book series: General Motors Research Laboratories Symposia Series ((RLSS))

Abstract

Engineers have turned to shape optimization of structures to assure the efficient use of finite element analysis in producing safe and economical designs. Constraints on stresses and displacements should however be imposed with an accuracy commensurate with the degree of precision attainable in the analysis. A progressive refinement strategy can be used to increase the accuracy as the optimal design is approached and constraints are most critical. For this reason a simple and efficient error estimation capacity and an adaptive refinement strategy must be incorporated into the design program. This chapter will describe a new and efficient error estimation method based on mixed formulation concepts which can be incorporated into any existing program framework. In addition, a relatively simple refinement strategy will be shown which for a given problem can be designed to yield a specified accuracy of stress computation. Finally, a review of the methods used in shape optimization indicates the need for efficient mesh generation capabilities. If these can be combined with the indicators of error, then the objectives outlined above can be achieved.

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Author information

Authors and Affiliations

  1. University College of Swansea, Swansea, UK

    O. C. Zienkiewicz, A. W. Craig & J. Z. Zhu

  2. Worcester Polytechnic Institute, Worcester, Massachusetts, USA

    R. H. Gallagher

Authors
  1. O. C. Zienkiewicz
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  2. A. W. Craig
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  3. J. Z. Zhu
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  4. R. H. Gallagher
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Editor information

Editors and Affiliations

  1. General Motors Research Laboratories, USA

    J. A. Bennett  & M. E. Botkin  & 

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© 1986 Plenum Press, New York

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Zienkiewicz, O.C., Craig, A.W., Zhu, J.Z., Gallagher, R.H. (1986). Adaptive Analysis Refinement and Shape Optimization—Some New Possibilities. In: Bennett, J.A., Botkin, M.E. (eds) The Optimum Shape. General Motors Research Laboratories Symposia Series. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-9483-3_1

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  • DOI: https://doi.org/10.1007/978-1-4615-9483-3_1

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4615-9485-7

  • Online ISBN: 978-1-4615-9483-3

  • eBook Packages: Springer Book Archive

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