Digital Image Correlation for investigating the behavior of composite materials

Abstract: Composite structures are now widely used in the aerospace industry because of their outstanding specific performances. Nevertheless, these structures exhibit very complex behaviors that are still difficult to predict. Kinematic full-field measurements now allow us to take a new look at the mechanics of such structures, and to perform experiments in situations more representative of their use (structural tests, multiaxial tests, etc.). Due to its simplicity of use, its wide range of applications (shape and displacement measurements, large deformations, dynamics, etc.) and its unique ability to exploit different imaging modalities (tomography, microscopy, etc.), Digital Image Correlation (DIC) has become the reference method in laboratories today. The subset-based approach initiated in the 1980s, similar to classical PIV, is still in the hands of software publishers who equip most laboratories. However, this approach to DIC does not make interfacing measurements and models easy. In the course of the 2000s, new formulations of the DIC (so-called global) were proposed. They make it possible to integrate a more or less important mechanical a priori. For example, the FE-DIC [1] makes it possible to use a Finite Element description of the displacement field. It is therefore possible, in theory, to exploit the optimized FE mesh built for simulation purposes. This provides the opportunity to avoid reprojection issues when comparing simulations and experiments [6], to integrate the model into the measurement in order to regularize it [8], or even to identify constitutive parameters directly from images (Integrated DIC [3]). Some examples of developments (in 2D, in stereo and volume DIC) conducted around these aspects will be presented [2-8]. The interest of "multi-scale" instrumentation in the context of identification, but also in the case of structural tests performed on large notched laminate panels, will specifically be detailed [6,8].

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