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为了研究不同降雨条件下道路路面水膜深度的变化情况,通过3个全尺寸预制路面模型(6m×3m)在模拟降雨大厅中6种不同降雨强度及7个不同坡度下的水膜深度观测试验,实测了路面水膜深度,根据试验数据标定了水膜深度回归模型,验证并校核了国内外既有水膜深度预测模型的计算结果。研究结果表明:国内外已有的几种典型路面水膜深度预测模型中,回归模型的预测精度高于数学物理模型,其中以RRL模型和Gallaway模型与提出的回归模型差异最小;各回归模型参数存在差异,主要是由于标定回归模型的水膜深度观测值受试验条件的影响较大;当降雨引起路面产生水膜时,影响路面摩阻系数变化的水膜应以包含路面构造深度的平均水膜深度作为表征,而不是除去路面构造深度的路面水膜深度。
In order to study the changes of the water film depth of road pavement under different rainfall conditions, three full-size prefabricated pavement models (6m × 3m) were used to simulate the water depth of 6 different rainfall intensities and 7 different slopes , The depth of pavement water film was measured. Based on the experimental data, the water depth regression model was calibrated to verify and verify the calculated results of the existing water depth prediction model at home and abroad. The results show that the prediction accuracy of regression model is higher than that of mathematical physics model in several typical pavement water depth prediction models both at home and abroad. The difference between the RRL model and Gallaway model and the proposed regression model is the smallest. The regression model parameters The difference is mainly due to the fact that the observed water depth of the calibration regression model is greatly influenced by the experimental conditions. When the water film is produced by the rain on the pavement, the water film that affects the pavement friction coefficient change should be averaged with the average water depth The depth of the film is used as a representation, not the depth of pavement water depth, excluding the pavement depth.