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Carbon Nanotube Networks as a Strain Indicator and Failure Predictor in Polymer Matrix Composites Subjecting to Static and Dynamic Loads

机译:碳纳米管网络作为聚合物基质复合材料的应变指示器和失效预测因子,其经受静态和动态载荷的聚合物基复合材料

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In this work, multiwall carbon nanotubes (MWCNTs) have been used to form a network of sensors to predict the failure region and to monitor the degradation of mechanical properties in laminated composites subjected to tensile and cyclic fatigue loadings. This is achieved by measuring the electrical resistivity change in the semi-conductive MWCNT-fiber glass-epoxy polymer matrix composites. By partitioning the tensile samples with electrically conductive probes, it has been shown that with increasing tensile load, different resistivity changes are detected in different regions and failure happens in the part in which higher resistivity change was detected. In cyclic loading, in which the maximum load is higher than the elastic limit of the laminate, a sharp increase in resistivity occurs within the first several cycles. There is also a change in resistivity during long term cyclic loading which gives this technique a good potential to monitor strength degradation during fatigue.
机译:在这项工作中,已经使用多壁碳纳米管(MWCNT)来形成传感器网络以预测失效区域并监测经受拉伸和循环疲劳载荷的层叠复合材料中的机械性能的劣化。这是通过测量半导体MWCNT-纤维玻璃 - 环氧聚合物基复合材料中的电阻率变化来实现的。通过用导电探针划分拉伸样品,已经示出了随着拉伸载荷的增加,在不同区域中检测不同的电阻率变化,并且在检测到较高电阻率变化的部分中发生故障发生故障。在循环加载中,其中最大负荷高于层压板的弹性极限,在前几个循环内发生电阻率的急剧增加。在长期循环负载期间还存在电阻率的变化,使该技术能够在疲劳期间监测强度降解的良好潜力。

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