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A multiplicative damage model for strength of fibrous composite materials

机译:纤维复合材料强度的倍增损伤模型

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Knowledge of the tensile strength properties of a fibrous composite material is essential in the design of reliable structures from that material. Determination of statistical models for the tensile strength of a composite material which provide good fits to experimental data from tensile tests on material specimens is therefore important for engineering design. Perhaps the most commonly used statistical model is the Weibull distribution, based on 'weakest link of a chain' arguments. However, in many cases the usual Weibull distribution does not adequately fit experimental data on tensile strength for composite materials made from brittle fibers such as carbon. Here, an alternative model is developed for tensile strength of carbon composites, which is based on a multiplicative cumulative-damage approach. This approach results in a 3-parameter extension of the Birnbaum-Saunders fatigue model and incorporates the material specimen size (size effect) as a known variable. This new distribution can also be written as an inverse Gaussian-type distribution, which can be interpreted as the first passage of the accumulated damage past a damage threshold, resulting in material failure. The new model fits experimental tensile-strength data, for carbon micro-composites better than existing models, providing more accurate estimates of material strength.
机译:纤维复合材料的拉伸强度特性的知识对于由该材料设计可靠的结构至关重要。因此,确定复合材料拉伸强度的统计模型,使其与材料样品的拉伸试验的实验数据非常吻合,对于工程设计很重要。也许最常用的统计模型是基于“链的最弱链接”参数的威布尔分布。然而,在许多情况下,通常的威布尔分布不能充分拟合由碳等脆性纤维制成的复合材料的拉伸强度实验数据。在此,针对碳复合材料的抗张强度开发了一种替代模型,该模型基于乘积累积损伤方法。这种方法导致Birnbaum-Saunders疲劳模型的3参数扩展,并将材料样本的尺寸(尺寸效应)作为已知变量。这种新的分布也可以写成逆高斯型分布,可以解释为累积损伤的第一次通过超过损伤阈值,从而导致材料故障。新模型适合实验拉伸强度数据,与现有模型相比,碳微复合材料更好,可提供对材料强度的更准确估算。

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