The transverse strength of fiber-reinforced composites is a matrix-dominated property whose accurate prediction is crucial to designing and optimizing efficient, lightweight structures. State-of-the-art analytical models for composite strength predictions do not account for fiber distribution, orientation, and curing-induced residual stress that greatly influence damage initiation and failure propagation at the microscale. This work presents a novel methodology to develop an analytical solution for transverse composite strength based on computational micromechanics that enables the modeling of stress concentration due to representative volume elements (RVE) morphology and residual stress. Finite element simulations are used to model statistical samples of composite microstructures, generate stress-strain curves, and correlate statistical descriptors of the microscale to stress concentration factors to predict transverse strength as a function of fiber volume fraction. Tensile tests of thin plies validated this approach for carbon- and glass-reinforced composites showing promise to obtain a generalized analytical model for transverse composite strength prediction.

中文翻译：

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基于计算微力学的复合材料横向强度分析模型

纤维增强复合材料的横向强度是一种以基体为主导的特性，其准确预测对于设计和优化高效、轻质结构至关重要。用于复合强度预测的最先进的分析模型没有考虑纤维分布、取向和固化引起的残余应力，这些在微观尺度上会极大地影响损伤的萌生和失效传播。这项工作提出了一种新的方法来开发基于计算微观力学的横向复合材料强度的解析解，该方法能够对由于代表性体积元素 (RVE) 形态和残余应力引起的应力集中进行建模。有限元模拟用于对复合微观结构的统计样本进行建模，生成应力-应变曲线，并将微尺度的统计描述符与应力集中因子相关联，以预测作为纤维体积分数函数的横向强度。薄层拉伸试验验证了这种用于碳纤维和玻璃纤维增​​强复合材料的方法，表明有望获得用于横向复合材料强度预测的通用分析模型。