Research examines how load and temperature affect asphalt rutting in mixtures, suggesting improved prediction methods.
This study addresses the root causes of rutting defects by examining the influence of environmental temperature, load, water-heat coupling, and the maximum nominal particle size of aggregates on the permanent deformation of asphalt mixtures. Through testing rutting specimens under varying experimental conditions, the patterns of permanent deformation were analyzed. The results indicate that temperature, water-heat coupling, load, and aggregate nominal particle size are significant factors affecting rutting depth and dynamic stability, with load exerting the greatest impact, followed by water-heat coupling. Using machine learning algorithms, a predictive model was developed to estimate rutting depth and dynamic stability, enabling accurate evaluation of the high-temperature deformation capacity of asphalt mixtures.
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Hu et al. (2026) studied this question.
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