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Vol. 46 (2005) No. 3 December n. 149

Computational Morphogenesis of Discrete Structures Based on Fuzzy Theory

< Table of Contents for Vol. 46 (2005) No. 3 December n. 149
  • Journal Name: Journal of the International Association for Shell and Spatial Structures (J. IASS)
  • ISSN: (Electronic Version) 1996-9015
  • ISSN: (Print Version) 1028-365X
  • Issue: Vol. 46 (2005) No. 3 December n. 149
  • Pages: 167-172
  • Title: Computational Morphogenesis of Discrete Structures Based on Fuzzy Theory
  • Author(s): H. Kawamura and H. Ohmori
  • Keywords: Structural Optimization, Genetic algorithm, fuzzy theory
Present paper describes a structural optimization method for truss and frame structures having some uncertain factors in its constitutive materials, configurations or design loads by using fuzzy theory as well as genetic algorithm (GA) techniques. GA has been already recognized as a strong and a useful tool for optimization problems with discrete variables and has been applied for topology optimization problems of trusses and frames. On the other hand, uncertainties which exist in structural problems such as those is the design loads, of the structural configurations and of the constitutive materials should be dealt with from the view point of the practical structural design. The probability statistics theory has been considered as the only technique for reliability analysis that can treat the uncertainty in structures. Probability theory can be used, when there is sufficient random data to define the probability density function. However, in actual structure design, such cases can be said to be very rare. Furthermore, although various factors (human error, etc.) must also be taken into consideration in order to evaluate the safety of real structures, they cannot be defined within a framework of the probability theory. In this paper, such factors are included in use of the fuzzy theory and the topology optimization problem of frame structures having uncertainties in their materials or configurations is shown to be rationally solved.

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