Structural Topology Optimization in Linear and Nonlinear Elasticity using Genetic Algorithms
Overview & Synopsis
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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Document Information
| Document Title | Structural Topology Optimization in Linear and Nonlinear Elasticity using Genetic Algorithms |
|---|---|
| Author / Organization | Couro Kane, François Jouve, Marc Schoenauer |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 1995 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-173789 |
| Original Source Link | Visit Source Page on hal.science » |