This study aims to assess the delamination effect and predict the evolution of damage in 3D printed specimens to investigate the mechanical behavior occurring due to the delamination of the layers of 3D printed thermoplastic polymers. Thus, additively manufactured ABS samples are subjected to tensile tests Made for different thicknesses of specimens by subtracting layer by layer. The mechanical behavior of the layers and the adherence between the layers are studied in this paper. The deposition of the layers is modeled as a laminated material. The delamination effect on the resistance of printed material is evaluated experimentally by comparing the mechanical characteristics of homogenously printed specimens, and laminated layers gathered together. Thus, the global resistance is reduced significantly due to the lack of adherence. Besides, crack growth, and critical intensity factor investigation are based on damage and rupture mechanics theories. Furthermore, the results allowed us to evaluate the energy behavior of the 3D printed material subjected to static loads and subsequently predict the evolution of the damage and find out the impact of layers' delamination. Indeed, we determined three stages of damage along with the critical life fraction leading to the failure of the specimen.
The study presents and compares an application of two procedures to identify the crack tip location in PVC Sent samples under a uniaxial tensile test based on the image processing method. An IDS camera captures several photos of the PVC surface as part of the image analysis procedure. All relevant data on crack initiation and propagation is collected and assessed using ImageJ software using image processing methods for detecting cracks. However, the second procedure involves a developed algorithm detecting the discontinuity using digital image correlation (DIC) measurement. Although, because of the experimental conditions, the acquisition of images by the digital camera is never perfect. This noise comes from several sources, including the digital camera, image distortion due to lens magnification or lens angle, the shape and size of the pattern, and electronic noise; ... This article discusses image enhancement methods to overcome these objectionable characteristics using and comparing several filters: Gaussian, median, and Unsharp Mask filters. The performance of the Gaussian filter is better than the Median and Unsharp mask filters. This research demonstrates that DIC is an effective technique for monitoring deformation and understanding the failure mechanism with the best-suited filter.
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