In this article, a coupled experimental and numerical method is utilized for characterizing the elastic–plastic constitutive properties of ductile materials. Three-dimensional digital image correlation (DIC) is used to measure the full field deformation on two mutually orthogonal surfaces of a uniaxial tensile test specimen. The material’s constitutive model, whose parameters are unknown a priori, is determined through an optimization process that compares these experimental measurements with finite element simulations in which the constitutive model is implemented. The optimization procedure utilizes the robust dataset of locally observed deformation measurements from DIC in addition to the standard measurements of boundary load and displacement data. When the difference between the experiment and simulations is reduced sufficiently, a set of parameters is found for the material model that is suitable to large strain levels. This method of material characterization is applied to a tensile specimen fabricated from a sheet of 15-5 PH stainless steel. This method proves to be a powerful tool for calibration of material models. The final parameters produce a simulation that tracks the local experimental displacement field to within a couple percent of error. Simultaneously, the percent error in the simulation for the load carried by the specimen throughout the test is less than 1%. Additionally, half of the parameters for Hill’s yield criterion, describing anisotropy of the normal stresses, are found from a single tensile test. This method will find even greater utility in calibrating more complex material models by greatly reducing the experimental effort required to identify the appropriate model parameters.

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