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Progressive failure modeling of woven fabric composite materials using multicontinuum theory

机译:基于多连续性理论的机织物复合材料渐进破坏建模

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摘要

Failure of composite materials often results from damage accumulation in the individual constituents (fiber and matrix) of the composite. At times, damage may even be limited to a single constituent. The ability to accurately predict not only ultimate strength values but also intermediate constituent level failures is crucial to the success of introducing composite materials into demanding structural applications. In this paper, we develop two progressive failure models for the analysis of a plain weave composite material. The fo.rmulations are based on treating the weave as consisting of separate but linked continua representing the warp fiber bundles, fill fiber bundles, and pure matrix pockets. Retaining constituent identities allows one to access constituent (phase averaged) stress fields that are used in conjunction with both a stress based and damage based failure criterion to construct a nonlinear progressive failure algorithm for the woven fabric composite material. The MCT decomposition and the nonlinear progressive failure algorithm are incorporated within the framework of a traditional finite element analysis. The constituent based progressive failure algorithm combined with both the stress based and damage based failure criteria are compared against experimental data for a plain weave, woven fabric composite under various loading conditions. The analytical results from the damage based approach show a marked improvement over the stress based predictions and are in excellent agreement with the experimental data.
机译:复合材料的失效通常是由于复合材料各个成分(纤维和基质)中的损伤积累所致。有时,损坏甚至可能仅限于单个成分。准确预测不仅最终强度值,而且还能够准确预测中间成分水平失效的能力,对于将复合材料成功引入苛刻的结构应用中至关重要。在本文中,我们开发了两个渐进式破坏模型来分析平纹复合材料。配方基于将编织视为由代表经纱纤维束,填充纤维束和纯基质袋的独立但相连的连续体组成。保留组成成分身份,可以访问与基于应力和基于破坏的破坏准则结合使用的组成(相平均)应力场,从而为机织织物复合材料构建非线性渐进破坏算法。 MCT分解和非线性渐进破坏算法被纳入传统的有限元分析框架内。将基于成分的渐进式破坏算法与基于应力和基于破坏的破坏准则相结合,将其与各种负载条件下的平纹机织织物复合材料的实验数据进行了比较。基于损伤的方法的分析结果显示,与基于应力的预测相比,性能得到了显着改善,并且与实验数据非常吻合。

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