Abstract In view of the large difference between the traditional unit-cell model (UCM) and the actual microstructure of 2.5D woven composites, which will affect the mechanical properties and failure behavior, a representative volume element (RVE) modeling strategy considering the randomness of weft cross-section (WFCS) is developed, and the established model is called statistical volume element (SVE) in this work. Based on the microscopy observation of warp cross-section (WPCS) and WFCS, some geometric parameters are counted, and thereby the SVE can be established. Then, the mechanical properties of 2.5D woven composites, including the stiffness and strengths in the warp and weft directions, are predicted by the SVE and UCM, respectively. Compared with the experimental results, the maximum errors predicted by the SVE and UCM are 3.84% and 15.23%, respectively. Therefore, the mechanical properties predicted by the SVE are more accurate than those predicted by the UCM. Furthermore, considering the prediction accuracy and calculation cost comprehensively, the authors suggest that the SVE and UCM should be adopted for the warp-loaded and weft-loaded progressive damage process, respectively. This work provides a method for the RVE modeling of 2.5D woven composites considering randomness, which can be extended to the modeling of other textile composites.

中文翻译：

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考虑纬向横截面随机性的2.5D编织复合材料的代表性单元建模策略用于机械性能预测

摘要 鉴于传统的单元模型 (UCM) 与 2.5D 编织复合材料的实际微观结构之间存在较大差异，会影响其力学性能和失效行为，提出了一种考虑随机性的代表性体积元 (RVE) 建模策略。开发了纬纱横截面（WFCS），建立的模型在这项工作中称为统计体积元（SVE）。基于经纱横截面（WPCS）和WFCS的显微镜观察，计算一些几何参数，从而可以建立SVE。然后，2.5D 编织复合材料的机械性能，包括经向和纬向的刚度和强度，分别由 SVE 和 UCM 预测。与实验结果相比，SVE和UCM预测的最大误差分别为3.84%和15.23%，分别。因此，SVE 预测的力学性能比 UCM 预测的更准确。此外，综合考虑预测精度和计算成本，作者建议对经向载荷和纬向载荷的渐进损伤过程分别采用SVE和UCM。这项工作为考虑随机性的 2.5D 编织复合材料的 RVE 建模提供了一种方法，该方法可以扩展到其他纺织复合材料的建模。