Estimating the effect of coarse aggregate meso-structure on the thermal contraction of asphalt mixture by a hierarchical prediction approach. (1st August 2022)

• Record Type: Journal Article
• Authors: Sun, Zhiqi; Qi, Haonan; Li, Shaohua; Tan, Yiqiu; Yue, Zurun; Lv, Huijie
• Is Part Of: Construction & building materials. Volume 342:Part A(2022)
• Publication Date: 2022-08-01
• Subjects: Asphalt mixtures -- Thermal contraction characteristics -- Meso-structure -- Mesoscopic mechanics model -- Low-temperature performance; Building materials -- Periodicals; 624.18
• DOI: 10.1016/j.conbuildmat.2022.128048
• Languages: English
• ISSNs: 0950-0618

Abstract

Highlights: Capture optimal models of hierarchical materials of different asphalt mixtures. Analyze the effect of coarse aggregate meso-structure on the thermal contraction of asphalt mixtures. Improve the prediction accuracy of thermal contraction of asphalt mixture. Abstract: The thermal contraction characteristics of asphalt mixture are closely associated with the low-temperature cracking of pavement. As for the research on the thermal contraction characteristics of asphalt mixture, it focuses mainly on the method of meso-theoretical prediction, which did not further analyze the impact of meso-structure characteristics of asphalt mixture. In this paper, a hierarchical prediction was made to analyze the effect of coarse aggregate meso-structure on the asphalt mixture. Experiments were conducted to obtain the thermal contraction strain of asphalt and asphalt mixture in steady heat transfer and to determine the meso-structure characteristics of asphalt mixture through industrial X-ray computed tomography (CT) and image processing. Given the matching degree of four meso-prediction models and asphalt-based materials and different meso-structure characteristics, the interaction term between inclusions in the meso-prediction model formula was clarified, and the impact of meso-structure on the thermal contraction of asphalt mixture was quantified. By analyzing the relationship between meso-structures and meso-prediction models, the Mori-Tanaka model was confirmed as optimal, and the model parameter of the interaction terms was adjusted using the test values of asphalt mixtures with different meso-structures, which further improves prediction accuracy for the thermal contraction of asphalt mixture. This paper provides a theoretical reference for the design of asphalt mixture materials.