Fatigue property evaluation for fiber reinforced plastics based on mode conversion effect of guided wave

被引:0
|
作者
Zhang, Chao [1 ]
Huang, Yuxiang [1 ]
Tao, Chongcong [1 ]
Qiu, Jinhao [1 ]
Ji, Hongli [1 ]
机构
[1] State Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing,210016, China
基金
中国国家自然科学基金;
关键词
Fiber reinforced plastics - Fatigue testing - Stiffness matrix - Failure (mechanical) - Fracture mechanics - Elastomers - Cracks - Guided electromagnetic wave propagation;
D O I
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中图分类号
学科分类号
摘要
Fiber reinforced plastics (FRPs) are widely used in aerospace engineering industry. When the composite structure is subjected to the cyclic load, the initiation, propagation and accumulation of the fatigue damage in FRPs lead to structural failure. This paper presents a guided wave based fatigue property evaluation method to characterize matrix crack accumulation in FRPs, which provides a potential way to predict the remaining useful life of the structures. In this paper, a finite element model for FRPs is firstly developed to simulate the fatigue induced matrix cracks, which are randomly distributed in the structures. Both the initiation and propagation behaviors of the matrix cracks are modeled by the regulation of the random parameters, such as the number of fatigue elements and the degree of the stiffness reduction. Based on a series of models representing the fatigue evolution process of FRPs, the mode conversion effect of the guided wave is then investigated. A guided wave characteristic MCI (Mode Conversion Index) quantifying the mode conversion effect is used to evaluate the fatigue property of FRPs. Compared with the macroscopic stiffness, MCI shows higher sensitivity to the degree of matrix crack accumulation. Finally, controlled fatigue tests under different stress levels are carried out by using a fatigue testing machine, in which a laser ultrasonic system is employed to obtain the guided wave propagation in FRPs with different numbers of load cycles. The relationship between MCI and macroscopic stiffness is also obtained, providing a basis for using mode conversion feature to predict fatigue life. © 2022 Elsevier Ltd
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