降级(电信)
沥青
紫外线
联轴节(管道)
辐射
材料科学
紫外线辐射
复合材料
环境科学
化学
工程类
光电子学
物理
光学
电气工程
放射化学
作者
Tangxin Xie,Zhongming He,Yuetan Ma,Huanan Yu,Zhichen Wang,Chao Huang,Feiyu Yang,Pengxu Wang
出处
期刊:Coatings
[Multidisciplinary Digital Publishing Institute]
日期:2025-07-19
卷期号:15 (7): 849-849
被引量:2
标识
DOI:10.3390/coatings15070849
摘要
In actual service, asphalt pavement is subjected to freeze–thaw cycles and ultraviolet radiation (UV) over the long term, which can easily lead to mixture aging, enhanced brittleness, and structural damage, thereby reducing pavement durability. This study focuses on the influence of freeze–thaw cycles and ultraviolet aging on the performance of recycled asphalt mixtures. Systematic indoor road performance tests were carried out, and a fatigue prediction model was established to explore the comprehensive effects of recycled asphalt pavement (RAP) content, environmental action (ultraviolet radiation + freeze–thaw cycle), and other factors on the performance of recycled asphalt mixtures. The results show that the high-temperature stability of recycled asphalt mixtures decreases with the increase in environmental action days, while higher RAP content contributes to better high-temperature stability. The higher the proportion of old materials, the more significant the environmental impact on the mixture; both the flexural tensile strain and flexural tensile strength decrease with the increase in environmental action time. When the RAP content increased from 30% to 50%, the bending strain continued to decline. With the extension of environmental action days, the decrease in the immersion Marshall residual stability and the freeze–thaw splitting strength became more pronounced. Although the increase in RAP content can improve the forming stability, the residual stability decreases, and the freeze–thaw splitting strength is lower than that before the freeze–thaw. Based on the fatigue test results, a fatigue life prediction model with RAP content and freeze–thaw cycles as independent variables was constructed using the multiple nonlinear regression method. Verification shows that the established prediction model is basically consistent with the change trend of the test data. The research results provide a theoretical basis and optimization strategy for the performance improvement and engineering application of recycled asphalt materials.
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