Impact of Experimental Uncertainties on the Identification of Mechanical Material Properties using DIC

This paper is concerned with an in-depth study of the interactions between full-field measurements errors and material identification. It is a further step in a research plan that aims to create a simulation procedure of actual experiments, with the final goal of using the simulator to optimise the test set-up in terms of specimen shape, measurement technique, applied load etc. In particular,here, Digital Image Correlation (DIC) is used as a full-field technique to obtain strain and displacement fields. These maps are used as input in an inverse methodology as, for instance, the virtual fields method (VFM) to obtain the material parameters introducing uncertainties in the characterization. The purpose of this contribution is to bridge the gap between experiments and simulations, in order to obtain predictions as close as possible to reality in terms of identification error. That will be used, as final goal of the general study, to optimize numerically a test set-up configuration, giving a priori the best parameters to use to experimentally identify a specimen. In the present contribute, the operating procedure is to perform real experiments and then to reproduce them numerically. Experimental uncertainties such as noise, lighting conditions, in-plane and out-of-plane motions are treated separately and introduced in the simulator. As such, their impact on the identified material properties can be unambiguously investigated. Here, focus is on the elastic properties of aluminium specimens, i.e. the Young’s modulus and the Poisson ratio and their specific variances due to the aforementioned errors. The simulator predicts reality to a large extent.