Multi-scale insight into key factors affecting stress perception of smart aggregates

Smart aggregate (SA) is a multi-module integrated embedded monitoring sensor that has been employed in the construction, operation and maintenance of civil infrastructure. However, the differences in the shape and Yong's modulus of the SA and the host matrix lead to the matching errors between the SA sensor readings and the actual in-situ stress values. A systematic analysis of how the modulus ratio of the SA to the host matrix (E-p/E-m), the length-to-height ratio of the sensor (L/H), and the non-homogeneity of the particle media interfere with the sensor monitoring data has been conducted in this paper using the finite element method and the discrete element method. In addition, the differences of the stress response from SA sensor under different load contact areas have been further investigated. Simultaneously, the numerical analysis has been validated by means of both theoretical derivations and laboratory tests. The analysis results show that E-p/E-m and L/H are the two key factors affecting the matching error. In particular, when E-p/E-m > 1, the matching error is positive and vice versa, while the L/H of the sensor is negatively correlated with the matching error. It is also noteworthy that the errors in the SA sensor monitoring data due to media inhomogeneity can only be negligible when the sensor diameter is larger than 20 times of the largest particle size in the host matrix. This study provides a theoretical guidance for optimizing the design of SA sensors and improving the accuracy of their measurement results.

Automated summary

This paper conducted a systematic analysis on how modulus ratio, sensor size ratio and media inhomogeneity in smart aggregate (SA) affect monitoring data. The results show that the modulus ratio and sensor size ratio are two key factors affecting the matching error.