On algorithms in FE-DIC

International audienceBeyond simplifying the dialogue between experimentation and simulation, Finite Element Digital Image Correlation (FE-DIC) mainly allows to develop new hybrid approaches combining numerical models and experimental image data (integrated approaches, mechanical regularization, data-driven simulation…). These new approaches allow experimental solid mechanicians access to properties that could not be measured with conventional tools.Since a decade, many efforts have been dedicated to improve the FE-DIC concept. Indeed, the method, initially developed in 2D and further extended in 3D (Digital Volume Correlation (DVC)), was also recently adapted to the context of Stereo-Digital Image Correlation (FE-SDIC). In all these applications though, the FE-DIC method is, until now, essentially based on a Gauss-Newton algorithm. Most of the time, it is even a quasi-Gauss-Newton, since the gradient of the graylevel image is often kept constant during the iterations, for the construction of the left and right hand side operators.In this presentation, we will review a series of other alternative algorithms to (quasi) Gauss-Newton to perform FE-DIC. For each considered algorithm, we will try to explain the theory, to illustrate on emblematic cases and to identify the advantages and drawbacks