Abstract

The influence of fibre volume fraction and temperature on fatigue life of continuous glass fibre reinforced plastics is investigated in detail. The physical causes of the two effects on the slope of the S-N-curve in fibre direction at R = 0.1 are researched and can be explained with help of micrographs. A new phenomenological approach is presented to model both effects in fibre dominated laminates with different stacking sequences using only the static ultimate strength as an input. Static and fatigue tests of different layups and fibre volume fractions are performed at different temperatures to validate the fatigue life predictions. Additionally it is derived that there is an optimal fibre volume fraction regarding a minimum damage sum. This fibre volume fraction is dependent on a given loading spectra and can be calculated using the phenomenological model.

Highlights

  • The low specific weight of continuous fibre reinforced plastics (FRP) offers light weight design opportunities

  • As the analysis showed both the interface stress and the fatigue factor b increase with an increasing fibre volume fraction (FVF)

  • It is found that the fatigue factor increases with the FVF and decreases with the temperature

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Summary

Introduction

The low specific weight of continuous fibre reinforced plastics (FRP) offers light weight design opportunities. As shown by [5,6] the damage evolution in composite laminates can be separated into three different stages that are determined by five main damage mechanisms according to Talreja [6]: In the first stage multiple matrix cracking dominates in the layers with fibres aligned transverse to the loading direction. These are initiated by defects and voids. According to [17] these models can be separated in to three categories: 1) Fatigue life models that use S-N-curves and a fatigue failure criteria

AIMS Materials Science
Influence of Temperature and FVF on Fatigue Life
Materials and Method
Experimental Setup
Experimental Results
Theoretical Background
Phenomenological model
Results and Discussion
Fatigue life prediction
Optimal FVF
Conclusion

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