journal article·2020-01

Meso-structural characteristics of asphalt mixture main skeleton based on meso-scale analysis

Liwan Shi, Duanyi Wang, Xin Xiao, Xiao Qin

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Abstract

Abstract To provide a reference for the gradation design of dense skeleton asphalt mixture (DSAM), a meso-scale main skeleton structural system with a contact chain as the medium scale, composed of coarse aggregates and contact points, contact chains, and a main skeleton, is proposed in this study. Based on the theoretical analysis of the main contact chain structure stability, the statistical characteristics of the main skeleton, contact chain of the asphalt mixtures, as well as their gradual behaviour under loading, were studied using the digital image processing (DIP) techniques. At last, the corresponding meso-evaluation indices and design criteria for the main skeleton were proposed. The results indicate that the factors affecting the stability of the main contact chain include the particle size of the coarse aggregate, the length, structure, and direction of the main contact chain, and the cohesion of asphalt binder. Coarser gradation and a shorter contact chain, as well as a linear main contact chain with the same load action direction, exhibit greater stiffness and superior resistance to deformation. A lower number of contact chains and longer contact chains in the asphalt mixture result in a more perfect main skeleton. When creating asphalt mixture specimens using the wheel rolling method, the design criteria of the main skeleton structure meso-index should reach Ks ≥ 80% and Nn ≤ 37. The design criteria can be used as a reference basis for the design of DSAM with a nominal maximum particle size of 13.2 mm, ensuring that the coarse aggregates are interlocked to form a stable main skeleton.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Asphalt Pavement Performance Evaluation · Infrastructure Maintenance and Monitoring · Geotechnical Engineering and Underground Structures

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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