In this research, prediction of mechanical properties of short fiber-reinforced composites manufactured with the help of fused filament fabrication (FFF) process is investigated. Three-scale formulation of asymptotic homogenization is employed to upscale the properties from microscale to mesoscale and from mesoscale to macroscale. Since generating microscale representative volume element (RVE) infused with short fibers requires sophisticated modeling tools, the algorithm for the microscale RVE generation is presented and discussed. Homogenization was performed for microscale RVEs with random and aligned (fibers aligned with the beads on mesoscale) fiber orientations, and for mesoscale RVEs with unidirectional and 0/90 layup formation. Tensile tests were performed for different short carbon fiber concentrations 5, 7.5 and 10% (by volume) to validate predicted homogenized properties. Moreover, to analyze the morphology of 3D printed specimens, microstructural analysis using SEM was performed on all the printed specimens. Surface morphology helped to gain more insight into the bead structure and fiber distribution. It was concluded that Young's modulus prediction using random fiber orientation has low relative errors tested in bead direction. Overall, this study has unique contribution to mechanical property prediction for FFF-made short fiber-reinforced composite parts.

在这项研究中，研究了借助熔融长丝制造（FFF）工艺制造的短纤维增强复合材料的机械性能的预测。渐近均质化的三尺度公式被用来从微观尺度到中等尺度以及从中等尺度到宏观尺度将特性提升。由于生成掺有短纤维的微米级代表性体积元素（RVE）需要复杂的建模工具，因此将介绍和讨论用于生成微米级RVE的算法。均质化是针对具有随机且对齐的纤维取向的微尺度RVE，以及具有单向和0/90叠层形成的中等尺度RVE。针对不同的短碳纤维浓度5、7进行了拉伸测试。5％和10％（按体积计）以验证预测的均质性能。此外，为了分析3D打印样本的形态，对所有打印样本进行了使用SEM的显微结构分析。表面形态有助于深入了解珠子结构和纤维分布。结论是，使用随机纤维取向的杨氏模量预测在珠子方向上测试的相对误差较低。总体而言，这项研究对FFF制短纤维增强复合材料零件的机械性能预测具有独特的贡献。结论是，使用随机纤维取向的杨氏模量预测在珠子方向上测试的相对误差较低。总的来说，这项研究对FFF制短纤维增强复合材料零件的机械性能预测具有独特的贡献。结论是，使用随机纤维取向的杨氏模量预测在珠子方向上测试的相对误差较低。总的来说，这项研究对FFF制短纤维增强复合材料零件的机械性能预测具有独特的贡献。