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arXiv · 1707.00884

Identification of non-linear behavior models with restricted or redundant data

S. Carbillet·V. Guicheret-Retel·F. Trivaudey·F. Richard·M. L. Boubakar
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Abstract

This study presents a new strategy for the identification of material parameters in the case of restricted or redundant data, based on a hybrid approach combining a genetic algorithm and the Levenberg-Marquardt method. The proposed methodology consists essentially in a statistically based topological analysis of the search domain, after this one has been reduced by the analysis of the parameters ranges. This is used to identify the parameters of a model representing the behavior of damaged elastic, visco-elastic, plastic and visco-plastic composite laminates. Optimization of the experimental tests on tubular samples leads to the selective identification of these parameters.

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S. Carbillet, V. Guicheret-Retel, F. Trivaudey, F. Richard, M. L. Boubakar. 2017-07-04. Identification of non-linear behavior models with restricted or redundant data. https://arxiv.org/abs/1707.00884

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