Influence of Aggregate Motion Related to Rutting Depth of Asphalt Mixture Based on Intelligent Aggregate and DEM

• Published in: Journal of materials in civil engineering Vol. 36; no. 5
• Main Authors: Gong, Fangyuan, Deng, Rui, Wang, Qinghua, Bai, Jiawei, Cheng, Xuejiao
• Format: Journal Article
• Language: English
• Published: New York American Society of Civil Engineers 01-05-2024
• Subjects: Asphalt mixes; Axis movements; Correlation analysis; Correlation coefficients; Discrete element method; Displacement; Prediction models; Predictions; Rotation
• ISSN: 0899-1561; 1943-5533
• DOI: 10.1061/JMCEE7.MTENG-17165

With the use of intelligent aggregate (IA) and discrete element method (DEM), a method was proposed to predict the influence of aggregate motion on the rutting depth in asphalt mixtures. The IAs were embedded in the center and side position of the specimen in a wheel tracking test, and the characteristics of IA motion parameters were compared with those obtained from virtual tests. The suitable motion factors for prediction model of rutting depth were first selected based on the trend of curve changes from the comparing results. Evaluation of the correlation between motion factors (Z-axis displacement and X-axis rotation angle of different IAs) and rutting depth of asphalt mixture was used to build the correlation matrix. Based on the high correlation coefficients, the curves of Z-axis displacement for No. 1 and No. 2 IA and X-axis rotation angle for No. 1 IA were further selected as the predicted factors, the prediction models of rutting depth were established. The feasibility of prediction models was verified by returning the IA motion data in indoor test and virtual test separately to observe the fitting degree between the actual curve and the prediction curve. It showed that the deviation of the prediction curve with the displacement factors was less than 4%, which was suitable to use as the predicted factors. On the other hand, due to the large fluctuation range of the rotation angle, the prediction curve with the rotation angle factor was more appropriate as a confidence curve to validate the prediction curve.