Optimised experimental characterisation of polymeric foam material using DIC and the Virtual Fields Method

This article presents a methodology to optimize the design of a realistic mechanical test to characterize the material elastic stiffness parameters of an orthotropic PVC foam material in one single test. Two main experimental techniques were used in this study: Digital Image Correlation (DIC) and the Virtual Fields Method (VFM). The actual image recording process was mimicked by numerically generating a series of deformed synthetic images. Subsequent to this, the entire measurement and data processing procedure was simulated by processing the synthetic images using DIC and VFM algorithms. This procedure was used to estimate the uncertainty of the measurements (systematic and random errors) by including the most significant parameters of actual experiments, e.g. the geometric test configuration, the parameters of the DIC process and the noise. By using these parameters as design variables and by defining different error functions as object functions, an optimization study was performed to minimize the uncertainty of the material parameter identification and to select the optimal test parameters. The confidence intervals of the identified parameters were predicted based on systematic and random errors obtained from the simulations. The simulated experimental results have shown that averaging multiple images can lead to a significant reduction of the random error. An experimental determination of the elastic coefficient of a PVC foam material was conducted using the optimized test parameters obtained from the numerical study. The identified stiffness values matched well with data from previous tests but even more interesting was the fact that the experimental uncertainty intervals matched reasonably well with the predictions of the simulations, which is a highly original result and probably the main outcome of the present paper