A combined genetic algorithm and nonlinear least squares method for material characterization using elastic waves

Abstract The inverse problem of material characterization is formulated as a parameter identification problem in which a set of parameters corresponding to the material property can be found by minimizing error functions formulated using the measured displacement response and the one computed by a forward solver based on projected candidates of parameters. A hybrid numerical method is employed as the forward solver to calculate the dynamic displacement response on the surface of the composite plate for given material property. A combined method is used as the inverse operator to determine the material property of composite plate. In this method, genetic algorithm is first used to select a set of better solutions close to the optima; then the nonlinear least squares method is applied using these better solutions as the initial guesses. Finally, the identification results can be determined from the solutions of nonlinear least squares method by comparing their corresponding error function values. Actual material characterizations of composites demonstrate the higher efficiency of the present method.

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