Issue 35

E. Dall’Asta et alii, Frattura ed Integrità Strutturale, 35 (2016) 161-171; DOI: 10.3221/IGF-ESIS.35.19 162 Masad et al. [8] used both digital imaging and X-ray computed tomography techniques to evaluate the microstructure of hot mix asphalts in terms of aggregate orientation and air voids concentration, as well as strain distribution. Birgisson et al. [9] used DIC to validate the theory at the base of the visco-elastic fracture mechanics-based crack growth, which identifies a fundamental crack growth threshold as the key element in defining the cracking mechanism and fracture resistance of asphalt mixtures. Nowadays, DIC strain measurement is a continuously improving technique: for instance, Nashon et. al. [10] have analysed the ductile fracture of aluminum panels, using the obtained results also as calibration and validation data for the numerical modeling of ductile fracture in large structures. Strain and displacement analysis of specific and unusual materials were recently tested by using DIC: Makki et. al. [11] have presented the stress localization and concentration for isotropic and orthotropic materials with holes and, in Petrikova et. al. [12], the big deformations of a hyperelastic material are investigated. Recent advances and perspectives in DIC and related methods for accurate, full-field deformation mappings have finally been described [13]. In this paper, 2D full-field strain experimental measurements of plain and notched specimens under tensile loading, using DIC technique, are performed. Two materials with different areas of application, both characterized by a high deformability, are investigated: hot mix asphalt for road pavements and thermoplastic composites for 3D-printing. The final goal is to verify the applicability of DIC technique in the measurement of large displacements and high deformations in the presence of strain gradients. On one hand, non-homogeneous strain fields are explored in the case of hot mix asphalt mixture by studying mastic elements, composed by binder and filler. On the other hand, notched specimens of thermoplastic polymers with elliptical holes are considered in order to investigate mixed-mode fracture initiation of the material. Strain localization and damage distribution are measured using both an open source Matlab code Ncorr [14] and a proprietary DIC software developed at the University of Parma. Thanks to the in-house implementation of two different image-matching algorithms, the oldest, based on Least Squares Matching (LSM) and the newest, based on Semi-Global Matching (SGM) techniques, the reliability of the measured deformation, especially in highly deformable materials, can be assessed. The latter technique is based on a recent stereo matching method [15] that is rapidly spreading in Photogrammetry and Computer Vision communities. Until now it has been successfully applied for 1D displacement field estimation (for example for stereo vision applications) and never tested in DIC application where the full 2D displacement field of the specimen is commonly required. For this reason, a novel implementation of the SGM technique with an algorithmic extension to a 2D displacement search domain has been developed and tested. This paper summarizes the most significant experimental studies performed using DIC-based techniques on the two different high deformable materials, comparing strains registered by different DIC stereo matching algorithms with finite element simulations. T HEORETICAL PRINCIPLES OF DIC IC is a non-contact optical technique which allows measurement of displacements and strains in engineering materials. It works by tracking the same points between two consecutive images (before and under loading) of the material specimen at different stage of its deformation. The feature tracking is usually achieved using Area Based Matching (ABM), a technique for the extraction of image correspondences based on similarities between grey values. In ABM, each image point to be matched is the centre of a small pixels window (template) in a selected reference image (master image), which usually corresponds to the first image (before loading) in the sequence of frames. The grey values of the template are compared with those of an equally sized pixels (patch) in a deformed search image (slave image). In short, all the different image matching techniques aim at the same result: comparing images that present radiometric and geometric differences due to a relative (three-dimensional) motion between the camera (the observer) and the object (the scene framed by the camera), and tracking the (two-dimensional) movement of specific elements on the image. DIC performances depend on the algorithm capability to identify the same feature in different images: well-contrasted and recognizable pattern facilitate the tracking process, achieving good accuracies and high matching reliability. To draw a boundary line between the plethora of techniques that can be used for image matching applications, a first criterion is the kind of image elements that are tackled by the algorithm. Accordingly, we can distinguished between: (i) Local methods (e.g. Least Squares Matching) which track the position of one point at a time comparing the area (i.e. the image block) surrounding the point itself (neighbouring points and thus neighbouring measures are not influenced by each other); (ii) Global/semi-global methods which estimate the whole displacement field of the Region Of Interest, ROI (in many cases the ROI corresponds to the full image extent) in a single pass (every point affects the neighbouring ones and D