Issue 77

T. Hachimi et alii, Fracture and Structural Integrity, 77 (2026) 173-206; DOI: 10.3221/IGF-ESIS.77.11

M ETHODOLOGY OF APPLYING D IGITAL I MAGE CORRELATION IN POLYMER AM

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he experimental workflow of DIC in polymer AM encompasses three intertwined component stages: namely, specimen preparation, the data acquisition through optical processes, and its subsequent computational correlation (Figure 4). Each of these stages requires careful parameter optimisation to the specificised `mesostructural` and surface properties of the 3D printed polymer in order to ensure metrological fidelity.

Figure 4: Standardized experimental workflow for DIC application in AM polymer characterization, encompassing specimen preparation, optical acquisition, and computational correlation. Specimen preparation and surface conditioning Effective DIC applications necessitate proper application of a high-contrast, randomly scattered speckle pattern that nonetheless remains suitably adherent in all orientations. Lupone et al. [64] and Pellegrini et al. [84] note that application of the speckle pattern is hindered by inherent surface roughness, translucency, or reflectivity that is often found in AM polymers. It is common to spray paint a white base on it, followed by speckling it in a random (black) manner. Lupone et al. [64] believe that airbrushing or inkjet printing would give more ideal results for `continuous fibre composites` and high texture geometry. To avoid pattern distortion during large deformations, speckle sizes should be tuned to 3-5 pixels to mitigate aliasing-induced measurement errors. Altering the pattern density and subset patch size is critical in capturing localized strain gradients at interlayer interfaces without adding excessive optical noise or concealing micro-defects. Experimental setup and imaging parameters Optical acquisition necessitates synchronized high-resolution cameras calibrated relative to the mechanical loading frame. Zouaoui et al. [120] and Tang et al. [101] state that diffused lighting must be implemented to avoid glare and shadow artefacts on polymeric surfaces. tensile/bending tests, low frame rates are sufficient, Zouaoui et al. [120] show that stereo-DIC configurations are essential for taking measurements of warping out-of-plane that naturally occurs in asymmetric AM architectures. High-speed imaging and proper scaling of the images to be captured are necessary to capture dynamic and impact loading, with camera calibration routines requiring extensive validation in order to accurately perform the reconstruction of the 3D strain fields, especially with regard to locating subpixel displacements across complex lattice topologies and non-planar “as-built” surfaces. Data processing and algorithmic workflows The acquired image sequences are subjected to subset-based correlation to determine pixel intensity variations from frame to frame. The subset and step parameters must be optimised as they represent a trade-off between spatial fidelity and noise

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