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CCF300/QY8911单向纤维增强复合材料纵向压缩性能预测
引用本文:张勇波,傅惠民,王治华.CCF300/QY8911单向纤维增强复合材料纵向压缩性能预测[J].航空动力学报,2013,28(6):1231-1235.
作者姓名:张勇波  傅惠民  王治华
作者单位:北京航空航天大学小样本技术研究中心,北京,100191
基金项目:中国博士后科学基金(2011M500221);国家重点基础研究发展计划(2012CB720000)
摘    要:提出了一种单向纤维增强复合材料压缩性能的预测方法.该方法基于纤维增强复合材料压缩的微屈曲失效机理与纤维膝切失效机理,对CCF300/QY8911碳纤维增强复合材料单向层合板的纵向压缩性能展开研究.将纤维微屈曲失效与纤维膝切失效机理统一起来,提出一种基于两种失效机理的预测模型,很好地实现了CCF300/QY8911单向纤维增强复合材料压缩性能的预测.通过与试验数据进行比较表明:基于两种失效机理分析的CCF300/QY8911单向纤维复合材料压缩性能预测模型与试验数据符合较好,误差在5%以内.

关 键 词:纤维微屈曲  纤维膝切  预测模型  压缩性能  复合材料
收稿时间:2012/4/25 0:00:00

Compressive strength prediction of CCF300/QY8911 unidirectional fiber reinforced composites
ZHANG Yong-bo,FU Hui-min and WANG Zhi-hua.Compressive strength prediction of CCF300/QY8911 unidirectional fiber reinforced composites[J].Journal of Aerospace Power,2013,28(6):1231-1235.
Authors:ZHANG Yong-bo  FU Hui-min and WANG Zhi-hua
Institution:Research Center of Small Sample Technology, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;Research Center of Small Sample Technology, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;Research Center of Small Sample Technology, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
Abstract:A method for the compressive strength prediction of unidirectional fiber reinforced composite was proposed. Based on the fiber microbuckling mechanism and fiber kinking mechanism, an investigation on the compressive strength prediction of CCF300/QY8911 unidirectional fiber reinforced composites was made. Combining the fiber microbuckling mechanism and fiber kinking mechanism together, which were both responsible for the failure, a combined model for compressive strength prediction of the unidirectional CCF300/QY8911 composite was proposed. According to the compression between the predicted results and measured date, it shows that to compare with the microbuckling model and the kinking model, the combined model makes a better agreement that keep the difference less than 5%.
Keywords:fiber microbuckling  fiber kinking  prediction model  compressive strength  composites
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