Abstract

An identification scheme is developed to investigate the nonlinear dynamic behaviors of the elastic-plastic system. The inverse problem of material characterization is formulated as parameter identification. A set of parameters corresponding to the material property can be found by minimizing objective function which accounts for experimental data and the calculated response of the mechanical model. Combining the global convergence characteristic of genetic algorithm with the fast neighbor searching of gradient optimization, the hybrid genetic algorithm is presented for the identification of the elastic-plastic material parameters. The performances of the proposed hybrid optimization algorithm were investigated with simulating data, and the effectiveness was consequently confirmed.

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