A self-optimizing, inverse analysis method for parameter identification of nonlinear material constitutive models utilizes the global force and displacement boundary loadings that are experimentally identified to globally search for initial constitutive parameters using a genetic algorithm. The initially identified constitutive parameters are then iteratively optimized by a simplex method in which two nonlinear finite element analyses are conducted in parallel using updated material constitutive parameters under the experimentally measured force and displacement boundary loadings. Stress and strain values for both the force and displacement finite element analyses are then input into an implicit objection function. Finally, the simplex optimization is performed for a number of predetermined number of iterations, whereupon the start of each new iteration utilizes the previously optimized set of constitutive parameters.
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