Numerical investigation on fracture evolution of asphalt mixture compared with acoustic emission

ABSTRACT

To reveal the fracture damage of asphalt mixture, an image-based numerical approach is proposed in this study considering the distribution of aggregate and asphalt mortar. Both digital image processing technique and discrete element method are applied to simulate the inhomogeneity of specimen and its fracture evolution at low temperature. At the same time, the acoustic emission (AE) activities are measured in laboratory to be compared with the micromechanical responses of numerical models. Results indicate that the developed method is suitable for modelling the numerical specimen of asphalt mixture, taking into account the size gradation and morphology of aggregates in the two-dimensional image. The numerical results of asphalt mixture have a good agreement with that of laboratory tests in cracking distribution and statistical probability. Cracks first appear on the aggregate–mortar interface, located in the upper and middle parts of the specimen, and then the brittle shear failure gradually propagates along the surface. Cumulative probabilities of both AE ringing counts and microfracture number follow the Weibull distribution. The numerical model has a significant advantage in the fracture evolution of asphalt mixture because the eccentric loading is unavoidable in laboratory tests due to personal and mechanical errors.

KEYWORDS:

• Asphalt mixture
• fracture evolution
• discrete element method
• digital image processing technique
• acoustic emission activity

Acknowledgements

We wish to thank the anonymous reviewers who have helped us to improve the work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was supported by the National Natural Science Foundation of China [grant numbers 51708048, 51974362], The Natural Science Foundation of Hunan [grant number 2020JJ5586], The Key Research and Development Program of Hunan Province [grant number 2019SK2171], 2019 Changsha University of Science and Technology Graduate Research and Innovation Project [grant number CX2019SS05], The Scientific Research Project of Hunan Provincial Department of Education for Excellent Young Scholars [grant number 20B039].