基于参数变异性的车辙深度预估

The Rutting Predication of Asphalt Pavement Based on Variability Analysis

合理的车辙预估是改善车辙设计的基础,对车辙进行合理预估能够在设计阶段就采取措施,降低车辙病害发生的几率与程度。本文在基于全厚度车辙试验的车辙预估模型的基础上,考虑影响路面车辙发展的温度、轴载、车速不是一个常数的事实,而通常车辙预估模型对应的参数只是取一个统计意义上的均值,没有考虑具体分布变异的影响,对建立的车辙预估模型进行了参数统计变异性分析,进一步建立了考虑参数统计变异性的车辙预估模型。得到如下结论:温度、速度统计变异性对车辙预估结果影响较大,随着统计变异性的增大,车辙预估值增大;轴重统计变异性对车辙预估结果影响较小;对车辙预估模型进行统计变异性修正后,可以提高预估精度。

A reasonable rutting prediction is fundamental to rutting resistance design,which aims at establishing a model to predict rutting resistance of the pavement to judge whether the pavement structure design and material design meet the requirements of the specification or design goal or not,and finally causing less rutting failure. Considering parameters of rutting prediction model such as temperautre,wheel load and vehicle velocity were normally set as statistical constants rather than variables with specific distribution variation,the statistical variability of parameters is analyzed to investigate the influence to rutting predication,and modified the rutting predication model to improve its accuracy. These conclusions are obtained： the rutting predication is obviously influenced by the statistical variabilities of temperature and vehicle velocity,greater statistical variabilities causing deeper rut; the statistical variability of wheel load have little influence on the rutting prediaction; and after the modificaiton of the statistical variability,the accuracy of the rutting predication is enhanced.