Prediction of fatigue crack behaviour of carbon fibre reinforced asphalt using fracture testing and modelling of the adhesive zone CZM

ABSTRACT

Mechanical behaviour and fatigue failure characteristic of asphalt mixtures is complex under cyclic loading conditions and require better recognition due to the importance of these infrastructures. Fatigue tests are usually time-consuming, expensive, and require experience. These challenges increase when the mixtures contain a variety of additives that complicate the recognition of material behaviour. In this study, carbon fibres were investigated as additives with high tensile strength. After failure tests on SCB samples(5 different percentages of fibres and 5 different lengths), 1.5% fibres and 15 mm length were used as optimum values for other experiments for 3 fracture models (I,II, and mixed I&II modes). Monotonic and cyclic failure tests of mixtures containing carbon fibres are presented by Abaqus modelling to predict fatigue behaviour of these materials. For this purpose, the Cohesion Zone Model (CZM) was selected for modelling and the failure parameters obtained from the experiments were validated by the results of the modelling. Comparison of experimental and modelling results in the study of mulmouthle outputs indicates that the predicted and measured fatigue behaviour have good conformity. Achieving such models reduces the need for expensive and time-consuming experiments and provides a useful tool for examining other effective parameters.

KEYWORDS:

• Cohesion zone model
• cyclic failure tests
• SCB test
• carbon fibres
• fracture mechanics

Disclosure statement

The author of this publication receives research support with an equipment loan from Babol Nushirvany university. The author also has equity interest in, serves as a consultant to, serves on an advisory board or board of directors for This university. The terms of this arrangement have been reviewed and approved by the Babol Nushirvany university in accordance with its policy on objectivity in research.

Additional information

Funding

This work was supported by Babol Noshirvani University of Technology.