Cross-scale study of the evolution of interparticle contact behavior using smart aggregate

Structural internal health monitoring is a critical step in the construction and maintenance of pavement, the current pavement health monitoring methods need to be improved in terms of accuracy, timeliness, and the understanding of the interaction mechanism between the sensors and surrounding media. In this paper, compaction and splitting tests of cement stabilized macadams (CSM) are conducted using the wireless embedded sensors-Smart aggregate (SA) and a new evolution indicator Sv is proposed to describe the generation and propagation of damage within the material. In addition, spherical and mixed particle assemblies are modeled using the discrete element method to investigate the variation of microscopic contact parameters between the SA and the surrounding granular medium under loading. The results show that SA sensor is an effective tool to monitor the inter-particle force and rotation changes within the mixture at meso-scale, and the fluctuation coefficient Sv can be used to more accurately characterize the evolution of inter-particle contact parameters. Moreover, there is a strong correlation between the SA readings and the microscopic contact parameters (e.g., coordination number, normal contact force), while the size and shape of particles in the medium can likewise significantly affect the monitoring results of SA sensors.

Automated summary

This study utilized wireless embedded sensors-Smart aggregate (SA) to investigate the performance of cement stabilized macadams (CSM) through compaction and splitting tests. A new evolution indicator Sv was proposed to describe the generation and propagation of damage within the material. In addition, the discrete element method was used to model spherical and mixed particle assemblies and study the variation of microscopic contact parameters between the SA and surrounding granular medium. The results showed that SA sensor is effective in monitoring inter-particle force and rotation changes within the mixture, and Sv can accurately characterize the evolution of inter-particle contact parameters.