Research on Fatigue Characteristics and Prediction of Large-Particle Asphalt Mixtures Based on Four-Point Bending Tests

Li Wei, Jinlong Lv, Hongliu Rong () and Xiaolong Yang
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Li Wei: College of Architecture and Civil Engineering, Nanning University, Nanning 541699, China
Jinlong Lv: School of Civil Engineering and Architecture, Guangxi University, Nanning 530004, China
Hongliu Rong: School of Civil Engineering and Architecture, Guangxi University, Nanning 530004, China
Xiaolong Yang: School of Civil Engineering and Architecture, Guangxi University, Nanning 530004, China

Sustainability, 2024, vol. 16, issue 11, 1-21

Abstract: Large aggregate asphalt mixtures can absorb noise, reduce water damage, effectively improve the service life of roads, and reduce environmental pressure. In this study, the fatigue characteristics of a large-sized asphalt mixture, LSAM-30, were investigated using four-point bending tests. The fatigue performance of LSAM-30 was compared to that of AC-13 and AC-20 asphalt mixtures across a range of temperatures, frequencies, and strains. The results indicated that the temperature, frequency, and strain significantly affect the fatigue performance of LSAM-30. As the temperature or frequency increased, the disparity in the fatigue performances of LSAM-30, AC-13, and AC-20 became more pronounced. Furthermore, the variations in the strain did not exhibit a clear pattern in the fatigue performance ratio among the three asphalt mixtures, with the ratio changes being minor (<5%). Additionally, an exponential-function-based predictive equation was proposed, showing how the fatigue characteristics of LSAM-30 vary with changes in frequency and temperature.

Keywords: large-sized asphalt mixture; four-point bending test; exponential function model; comparison of fatigue performance (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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