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Structural Topology Optimization in Linear and Nonlinear Elasticity using Genetic Algorithms

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Abstract

In this paper, structural topology optimization is addressed through Genetic Algorithms. A set of designs is evolved following the Darwinian survival-of-fittest principle. The standard crossover and mutation operators are tailored for the needs of 2D topology optimization. The genetic algorithm based on these operators is experimented on plane stress problems of cantilever plates: the goal is to optimize the weight of the structure under displacement constraints. The main advantage of this approach is that it can both find out alternative optimal solutions, as experimentally demonstrated on a problem with multiple solutions, and handle different kinds of mechanical model: some results in elasticity with large displacements are presented. In that case, the nonlinear geometrical ffects of the model lead to non viable solutions , unless some constraints are imposed on the stress field.
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Dates and versions

hal-02985724 , version 1 (02-11-2020)

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  • HAL Id : hal-02985724 , version 1

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Couro Kane, François Jouve, Marc Schoenauer. Structural Topology Optimization in Linear and Nonlinear Elasticity using Genetic Algorithms. Proc. 21st ASME Design Automatic Conference, Sep 1995, Boston, United States. ⟨hal-02985724⟩
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