基于参数变异性的车辙深度预估  

The Rutting Predication of Asphalt Pavement Based on Variability Analysis

作　　者：张勇[1] 吴克宝 葛慧芝 罗辉[4] 

机构地区：[1]中交第二航务工程局有限公司第五工程分公司,湖北武汉430012 [2]武汉华中科大土木工程检测中心,湖北武汉430074 [3]河南省平顶山中亚路桥建设工程有限公司,河南平顶山467000 [4]华中科技大学土木工程与力学学院,湖北武汉430074

出　　处：《土木工程与管理学报》2016年第5期33-37,43,共6页Journal of Civil Engineering and Management

基　　金：国家自然科学基金(51578261);湖北省科技支撑计划项目(2015BAA112);中央高校基本科研业服务费专项资金(2015MS071)

摘　　要：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.

关 键 词：车辙预估 变异性 全厚度车辙试验 温度 轴重 车速 

分 类 号：U416.217[交通运输工程—道路与铁道工程]