首页> 外文期刊>Journal of Reinforced Plastics and Composites >Microstructural damage based micromechanics model to predict stiffness reduction in damaged unidirectional composites
【24h】

Microstructural damage based micromechanics model to predict stiffness reduction in damaged unidirectional composites

机译:基于微观结构损伤的微机械模型,以预测损坏单向复合材料僵硬

获取原文
获取原文并翻译 | 示例
           

摘要

Prediction of the residual stiffness of the carbon fiber reinforced polymer composite, subjected to fatigue loading, can be performed using some of the phenomenological models. However, it is still a challenge to find the stiffness based on the known microstructural damage state (that was developed irrespective of the load history). In this work, two micromechanics-based models were developed to predict reduction in the stiffness of the damaged composite. Fiber crack density and interface debonding was used to define the microstructural damage state of the composite. These models account for the fiber crack density in the form of change in either geometry (equivalent ellipsoid model) or material property of the fiber (reduced stiffness model). The microstructural damage state in the unidirectional carbon fiber reinforced polymer composite, obtained from the on-axis tension-tension fatigue loading, was used to validate the models. The results from reduced fiber stiffness model were compared against experiment and finite element analysis for the given microstructural damage. The stiffness obtained using reduced fiber stiffness model was in good agreement with that obtained from the experiment. However, reduced fiber stiffness model underestimated reduction in stiffness compared to finite element analysis.
机译:可以使用一些现象学模型进行疲劳负载的碳纤维增强聚合物复合材料的残留刚度的预测。然而,基于已知的微观结构损伤状态找到刚度仍然是一个挑战(这是不管负载历史如何发展的)。在这项工作中,开发了两个基于微机械的模型以预测受损复合材料的刚度降低。纤维裂纹密度和界面剥离用于定义复合材料的微观结构损伤状态。这些模型占纤维(等同椭球模型)或纤维的材料特性的变化形式的纤维裂纹密度(减少刚度模型)。从轴上张力张力疲劳负荷获得的单向碳纤维增强聚合物复合材料中的微观结构损伤状态用于验证模型。将降低纤维刚度模型的结果与给定的微观结构损伤的实验和有限元分析进行了比较。使用降低的纤维刚度模型获得的刚度与从实验中获得的良好一致。然而,与有限元分析相比,降低了纤维刚度模型低估了刚度的降低。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号