Fibre bridging effect on the Paris relation of mode I fatigue delamination in composite laminates with different thicknesses

Journal Article (2017)
Author(s)

L Yao (Northwestern Polytechnical University, Harbin Institute of Technology, TU Delft - Aerospace Structures & Materials)

Yi Sun (Harbin Institute of Technology)

Licheng Guo (Harbin Institute of Technology)

R.C. Alderiesten (TU Delft - Structural Integrity & Composites)

R Benedictus (TU Delft - Aerospace Structures & Materials)

Meiying Zhao (Northwestern Polytechnical University)

Liyong Jia (AVIC the First Aircraft Institute)

Research Group
Structural Integrity & Composites
DOI related publication
https://doi.org/10.1016/j.ijfatigue.2017.06.004
More Info
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Publication Year
2017
Language
English
Research Group
Structural Integrity & Composites
Volume number
103
Pages (from-to)
196-206

Abstract

Fatigue delamination with fibre bridging in composite laminates with different thicknesses was investigated. The experimental results clearly demonstrated fibre bridging had significant retardation effects on fatigue delamination behavior, making it insufficient to use a single Paris resistance curve to determine fatigue crack growth. To address this problem, the coefficients of the Paris relation were correlated to the normalized crack extension (a − a0)/Lpz. It was found that the exponent n was independent on the normalized crack extension and specimen thickness, whereas the parameter log(c) bi-linearly decreased with the normalized crack extension and kept constant once fibre bridging became saturation. And the magnitude of log(c) was independent on specimen thickness. Thus, it was concluded that fatigue delamination behavior and fibre bridging significance were independent on specimen thickness at a given normalized crack extension (a − a0)/Lpz. With substitutions of these correlations into the Paris relation, an empirical power law relation was developed to characterize fatigue delamination behavior. And its validation was verified by a comparison between predictions and experiments.

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