Influence of fiber misalignments on buckling performance of variable stiffness composites using layerwise models and random fields

Abstract

Additive manufacturing brought to the emergence of a new class of fiber-reinforced materials; namely, the Variable Angle Tow (VAT) composites. Automated fiber placement machines allow the fibers to be relaxed along curvilinear paths within the lamina. In theory, the designer can conceive VAT structures with unexplored capabilities and tailor materials with optimized stiffness-to-weight ratios. In practise, steering brittle fibers, generally made of glass or carbon, is not trivial and highly affected from the printer signature. This paper wants to explore the effect of fiber misalignment on the buckling response of laminated VAT composites. For doing so, we use the Carrera Unified Formulation (CUF), which allows to develop layerwise models with unprecedented accuracy in a straightforward and systematic manner. Variation patterns are generated at the layer scale by means of random fields through a Monte Carlo analysis. The stochastic variation (defects) is propagated through the scales and correlated with the global buckling response of VAT panels. The results show that layerwise models outperform equivalent single layer theories, since the former are able to foresee eventual switching between buckling modes, and thus making them fundamental in uncertainty analysis.