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Recalibration of the Flexible Pavement Rutting Model in Utah

机译:犹他州柔性路面车辙模型的重新校准

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The Utah Department of Transportation (UDOT) completed a study in 2009 to implement and adopt the American Association of State Highway and Transportation Officials (AASHTO) Mechanistic-Empirical Pavement Design Guide (MEPDG). Prior to 2009, UDOT used a van mounted 3-point laser profiler to obtain the transverse profile of the pavement at regular intervals (typically a tenth of a mile). Maximum rut depth was then computed using the three points obtained. These measurements were found to be different than the LTPP definition through a direct correlation of rut depth measurements and an adjustment was made to the rutting of the UDOT sections so that they would match the LTPP rutting measurements. UDOT pavement sections rut depth measurement changed in 2009 to include closely spaced laser measured full transverse profile and calculation of maximum rut depth in each wheel path. This definition is thus very similar to that in LTPP. The change in rut depth measurements prompted UDOT to recalibrate MEPDG rutting model. The recalibration of the MEPDG rutting model was conducted using a nonlinear model optimization tool, SAS. A revised calibration coefficients were developed for rutting prediction model using Utah-specific design inputs and performance data. Overall, the recalibration process helped remove the bias (consistent over- or under-prediction), reduce the prediction error, and improve the accuracy of rutting model. The improvement in these models was notable; thus, indicating that the Utah-calibrated rutting model would provide much more accurate, reliable, and cost-effective designs than previous UDOT rutting prediction model.
机译:犹他州交通部(UDOT)于2009年完成了一项研究,以实施和采用美国国家公路和运输官员(AASHTO)机制 - 实证路面设计指南(MEPDG)的协会。在2009年之前,UDOT使用了一个面包车安装的3点激光分析仪,以定期的间隔(通常是十分之一)获得路面的横向曲线。然后使用所获得的三个点计算最大RUT深度。发现这些测量与RUT深度测量的直接相关性不同,并且对UDOT部分的栅格进行调整,使得它们与LTPP车辙测量相匹配。 UDOT路面部分在2009年改变了深度测量,以包括紧密间隔的激光测量的全横向剖面和每个车轮路径中最大车辙深度的计算。因此,该定义与LTPP中非常相似。 RUT深度测量的变化提示UDOT重新校准MEPDG RUTTING模型。使用非线性模型优化工具,SAS进行MEPDG RUTTING模型的重新校准。使用犹他州特定的设计输入和性能数据来开发修订的校准系数。总的来说,重新校准过程有助于去除偏差(一致或欠预测),降低预测误差,提高车辙模型的准确性。这些模型的改善是值得注意的;因此,表明犹他州校准的车辙模型将提供比以前的UDOT车辙预测模型更准确,可靠,并且具有成本效益的设计。

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