Statistical Fatigue Investigation and Failure Prediction of a Healable Composite System

被引:4
|
作者
Hostettler, Nathan [1 ]
Cohades, Amael [1 ]
Michaud, Veronique [1 ]
机构
[1] Ecole Polytech Fed Lausanne EPFL, Lab Proc Adv Composites LPAC, Lausanne, Switzerland
关键词
self-healing; composites; fatigue; failure prediction; Weibull statistics; VELOCITY IMPACT DAMAGE; EPOXY COMPOSITE; REPAIR; CRACKS; POLYMERS;
D O I
10.3389/fmats.2020.561852
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Fiber reinforced polymers are massively used as an alternative to metals in structural applications. The brittle nature of their matrix, however, makes them more susceptible to crack formation and propagation resulting in costly repair operations and increased environmental impact. Intrinsic healable composites provide a good alternative to these conventional composite materials, whereas their mechanical properties in static solicitation or impact testing are well documented, only few studies address fatigue testing. This research focuses on 3-point bending fatigue tests of polymer-blend based healable E-glass composite materials. The S-N curve was first built to compare the fatigue behavior of the healable system to a conventional epoxy composite. A statistical approach based on Weibull statistics was developed to predict the failure probability as a function of the applied stress amplitude, to compare both systems at equivalent probability of failure. The healable system showed a higher fatigue resistance at high cycle fatigue. Furthermore, a full stiffness recovery was obtained and a life extension of at least five times compared to the reference system when healed after reaching a 90% chance of survival. The healable system thus opens new perspectives for more sustainable load-bearing composites.
引用
收藏
页数:9
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