Application of digital image correlation in behavior modelling of AM CFRTP composites

Additive technology has recently grown from experimental rapid prototyping to the production of functional engineering components for various applications, but the inherent quality of additive manufacturing and significantly weaker mechanical properties in comparison with traditional manufacturing still limit their application. Hence, a modified fused deposition modeling (FDM) method which allows the structure to be selectively reinforced with continuous fiber reinforcement results in composite structures with improved mechanical properties. It has indications of notable deviation from the classical laminate theory (CLT) theory and the rule of mixture, as well as a significant influence of manufacturing defects on the overall mechanical properties. Although the results in the mechanical behavior analysis of these materials are scarce today, authors up to date have documented some mechanical properties under tensile loading without interruption. Those experimental data lack the stress-strain relationship response in the unloading stages, thus missing the possibility of plastic strain determination. Therefore, eight sets of continuous carbon fiber reinforced thermoplastic composite (CFRTP) test specimens were designed and additively manufactured according to ASTM-D3039 for different fiber volume fractions and layer stacking sequences of 0/90,-30/30,-45/45,-60/60. Moreover, specimens were prepared by milling the unnecessary edges, and the layup surface was treated to achieve a stochastically paint pattern for digital image correlation (DIC) tracking. Finally, the prepared specimens were statically tested over three consecutive phases of progressive tensile loading and unloading, while the displacements were monitored and measured using the GOM-Aramis DIC system.