Khosravani, Mohammad Reza
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Publication Access status: Open Access , Brittle fracture of notched components fabricated by stereolithographySince additive manufacturing (AM, i.e., 3D printing) has been widely used for production of end-used products, the mechanical strength of parts fabricated by this technology have gained considerable significance. The current study presents fracture load assessment of 3D-printed components fabricated by the stereolithography (SLA) technique using UV sensitive resin material. In this context, dumbbell-shaped specimens were printed and tested to determine basic mechanical properties. Moreover, V-notched semi-circular bending test coupons with various notch opening angles (i.e., 15°, 30°, 45°, 60°, 75°, and 90°) were printed and examined. Parallel to the experimental tests, we developed a finite element model to simulate the load carrying performance of 3D-printed parts. Moreover, we used the digital image correlation technique to determine displacement and strain field on the surface of the examined specimens. Since the mechanical strength and fracture behavior of 3D-printed parts are investigated in the current study, the presented outcomes can be utilized for innovative designs of parts fabricated by SLA with a higher mechanical strength, and improved load-carrying capacity.Source Type:Article7 11 - Some of the metrics are blocked by yourconsent settings
Publication Access status: Open Access , Effects of steps on the load bearing capacity of 3D-printed single lap jointsDamage in adhesively bonded joints typically initiates in the overlap area due to high level of bonding (peel) stress. Different approaches are being considered to decrease the peel stress and improve the overall strength of the joint. One possible approach is to shape the over lap area into a stepped form configuration and enhance the performance of the joint. In the current study, we investigate effects of stepped-shape overlap area on the load bearing capacity of additively manufactured single-lap joints. To this aim, stepped-lap adhesively bonded joints with different designs and geometries in the overlap (bonding) area are considered with 3D-printed polylactic acid (PLA) adherends using the fused deposition modeling (FDM) process. Three configurations with different step sizes are considered to manufactured a set of adhesively bonded single-lap joints and to investigate the optimum length of the steps. The results are compared with our previous experimental findings on 3D-printed conventional single-lap joints. The obtained outcomes reveal that creating steps in the overlap area has a significant influence on the structural integrity and fracture load of 3D-printed adhesive-bonded joints and the bonded structures with identical step size in boding area reveal a better performance in load carrying capacity and shows a higher fracture load. Parallel to the experimental practices, a finite element model also developed to simulate the load carrying performance of the adhesively bonded singlelap joints with equal step size and 3D-printed PLA adherends. The FE model confirms the experimental outcomes and reveals the details of the cohesive failure and damage evolution mechanism in this bonded structures with PLA printed adherends. The proposed technique has a great potential to be a competitive alternative to conventional single-lap joints made by 3D printing. The presented results can be used for further fabrication of 3D-printed joints with a better structural performance.Source Type:Article2 17 - Some of the metrics are blocked by yourconsent settings
Publication Access status: Open Access , Machine learning in predicting mechanical behavior of additively manufactured partsAlthough applications of additive manufacturing (AM) have been significantly increased in recent years, its broad application in several industries is still under progress. AM also known as three-dimensional (3D) printing is layer by layer manufacturing process which can be used for fabrication of geometrically complex customized functional end-use products. Since AM processing parameters have significant effects on the performance of the printed parts, it is necessary to tune these parameters which is a difficult task. Today, different artificial intelligence techniques have been utilized to optimize AM parameters and predict mechanical behavior of 3D-printed components. In the present study, applications of machine learning (ML) in prediction of structural performance and fracture of additively manufactured components has been presented. This study first outlines an overview of ML and then summarizes its applications in AM. The main part of this review, focuses on applications of ML in prediction of mechanical behavior and fracture of 3Dprinted parts. To this aim, previous research works which investigated application of ML in characterization of polymeric and metallic 3D-printed parts have been reviewed and discussed. Moreover, the review and analysis indicate limitations, challenges, and perspectives for industrial applications of ML in the field of AM. Considering advantages of ML increase in applications of ML in optimization of 3D printing parameters, prediction of mechanical performance, and evaluation of 3D-printed products is expected.Source Type:Article2 13
