收稿日期: 2017-02-27
修回日期: 2017-06-23
网络出版日期: 2017-06-23
基金资助
国家自然科学基金(51335003)
Test and prediction model of statics property of fiber metal laminates
Received date: 2017-02-27
Revised date: 2017-06-23
Online published: 2017-06-23
Supported by
National Natural Science Foundation of China (51335003)
为研究纤维金属层板(FML)的非线性变形行为和损伤机制,对GLARE2-2/1、GLARE2-3/2、GLARE3-2/1、GLARE3-3/2、GLARE6-2/1和GLARE6-3/2层板进行了静力拉伸测试,同时采用数字图像相关(DIC)技术观测了GLARE2-3/2、GLARE3-3/2和GLARE6-3/2试样的全场应变,基于修正的经典层板理论建立了考虑金属层塑性和预浸料层损伤的理论本构模型,模拟预测了GLARE层板的轴向弹性模量、断裂强度和应力-应变曲线,与测试结果进行了对比分析。对经历载荷作用的试样,采用腐蚀去层的方法研究了内部预浸料层的损伤。结果显示:铺层增加后受损伤预浸料层的性能退化更多,采用DIC技术能够有效检测静力拉伸载荷下GLARE试样内预浸料层的损伤,理论模型方法能够很好地模拟GLARE试样的静力拉伸试验过程。
关键词: 纤维金属层板(FML); 修正的经典层板理论; 应力-应变曲线; 损伤机制; 数字图像相关(DIC)技术; 无损检测
佟安时 , 谢里阳 , 白恩军 , 白鑫 , 张诗健 , 王博文 . 纤维金属层板的静力学性能测试与预测模型[J]. 航空学报, 2017 , 38(11) : 221193 -221193 . DOI: 10.7527/S1000-6893.2017.221193
To investigate the nonlinear tensile response and fracture behavior of Fiber Metal Laminates (FMLs), tests of static tensile of GLARE2-2/1, GLARE2-3/2, GLARE3-2/1, GLARE3-3/2, GLARE6-2/1 and GLARE6-3/2 laminates were carried out. Digital Image Correlation (DIC) techniques were employed to observe the full-field strain of GLARE2-3/2, GLARE3-3/2, and GLARE6-3/2 laminates during loading. An analytical constitutive model based on a modified classical lamination theory, which considers both the elastic-plastic behavior of the aluminium alloy and the damage process of prepreg layers, are proposed to predict the elasticity modulus, tensile strength and stress-strain response of GLARE laminates. The prediction results are compared with the test results. To identify the damage characteristics of the glass/epoxy prepreg layer, the aluminium lays of the fracture specimens were removed by the chemical method. The results show that the performance of the injured prepreg layers will decrease with the increase of the number of the ply. The DIC technique can be used to detect effectively the damage of the prepreg layers in GLARE laminates under tensile loading. Good agreement can be obtained between model predictions and test results.
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