Abstract

Asphalt mixtures will inevitably be affected by rainwater and the effect of the wet temperature cycle during a pavement’s life span. Especially in coastal areas such as Guangdong and Hainan in China, asphalt pavement is particularly susceptible to the sizeable wet temperature cycle formed by the high temperature and sudden temperature drop of rainstorms in summer. For this study, we used a homemade sizeable wet temperature cycle environment simulation device to analyze the decay characteristics and the mechanical properties of asphalt pavements in this environment; modified bending and tensile strength and shear strength tests were used to study the decay patterns of shear strength, bending, and tensile strength, and the stiffness modulus of asphalt mixtures with different air voids and different pavement depths under the action of a sizeable wet temperature cycle. In addition, the Grey correlation method was used to analyze the significance of each influencing factor on the decay of mechanical properties, and mathematical fitting was used to establish the prediction equation of the mechanical properties of asphalt mixtures. The results show that with the increase in the number of sizeable wet temperature cycles, the asphalt mixture’s shear strength, flexural tensile strength, and flexural tensile modulus decrease, the degree of decay increases, and the rate of decay gradually slows down. In the case of the same number of sizeable wet temperature cycles, the degree of decay of the asphalt mixtures gradually decreases with increasing depth or decreasing void ratio. After 100 sizeable wet temperature cycles, the maximum values of the decay of shear strength, modulus of strength, and flexural tensile strength were 22.30%, 23.29%, and 32.01%. The importance of the influence of each factor on the decay of the mechanical properties is as follows: the number of sizeable wet temperature cycles > void rate > depth. The prediction equations of the established mechanical properties have a good prediction effect, and the correlation between predicted values and actual values can be up to 0.925. The prediction equations can effectively predict the mechanical properties of asphalt mixtures with different air voids and depths under the action of sizeable wet temperature cycles.

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