1. Effect of fiber orientation distribution on constant fatigue life diagram of chopped carbon fiber chip-reinforced Sheet Molding Compound (SMC) composite
- Author
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Zhangxing Chen, Haiding Guo, Yang Li, Hong Tae Kang, Li Huang, Xuming Su, Xuze Sun, Haibin Tang, Guowei Zhou, Carlos Engler-Pinto, and Danielle Zeng
- Subjects
Cyclic stress ,Materials science ,Mechanical Engineering ,Composite number ,Diagram ,Modulus ,02 engineering and technology ,021001 nanoscience & nanotechnology ,Industrial and Manufacturing Engineering ,020303 mechanical engineering & transports ,Compressive strength ,0203 mechanical engineering ,Mechanics of Materials ,Modeling and Simulation ,Ultimate tensile strength ,Sheet moulding compound ,General Materials Science ,Composite material ,0210 nano-technology ,Constant (mathematics) - Abstract
The material behavior of chopped carbon fiber chip-reinforced Sheet Molding Compound (SMC) composite is investigated under both quasi-static and cyclic fatigue loading conditions in the present study. Quasi-static tensile and compressive strength data is collected, followed by a series of fatigue tests under three different cyclic loading conditions, i.e., Tension-Tension (T-T), Compression-Compression (C-C), and Tension-Compression (T-C). The experimental results show a considerable amount of variation for each loading condition, which is found to be induced by the spatial distribution of fiber orientation within the tested specimens. An analytical approach is developed to correlate the fatigue performance of the SMC material with the local modulus, which is determined by the fiber orientation distribution. Additionally, the similar failure modes are observed under different loading conditions. Based on these findings, a new form of Constant Fatigue Life (CFL) diagram is established in which the impact of fiber orientation tensor to the fatigue behavior of SMC is considered. This developed CFL diagram is examined by comparing the measured fatigue performance with prediction where local fiber orientation distribution is quantified from microscopic images.
- Published
- 2019