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.

摘要

增材制造带来了一种新型纤维增强材料的出现；即可变角度牵引（VAT）复合材料。自动纤维铺放机允许纤维沿着椎板内的曲线路径松弛。理论上，设计师可以设想具有未开发能力的 VAT 结构，并定制具有优化刚度重量比的材料。在实践中，通常由玻璃或碳制成的转向脆性纤维并非微不足道，并且受打印机签名的影响很大。本文想探讨纤维错位对层压 VAT 复合材料屈曲响应的影响。为此，我们使用了 Carrera 统一公式 (CUF)，它允许以直接和系统的方式以前所未有的精度开发分层模型。通过蒙特卡洛分析，通过随机场在层级生成变化模式。随机变化（缺陷）通过尺度传播，并与增值税面板的全局屈曲响应相关。结果表明，分层模型优于等效的单层理论，因为前者能够预见屈曲模式之间的最终切换，从而使其成为不确定性分析的基础。