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首页> 外文会议>International Airfield and Highway Pavements Conference >Calibration of Fatigue Cracking and Rutting Prediction Models in Pennsylvania Using Laboratory Test Data for Asphalt Concrete Pavement in AASHTOWare Pavement ME Design
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Calibration of Fatigue Cracking and Rutting Prediction Models in Pennsylvania Using Laboratory Test Data for Asphalt Concrete Pavement in AASHTOWare Pavement ME Design

机译：柏油盆地路面路面上沥青混凝土路面实验室试验数据在宾夕法尼亚州疲劳裂缝和车辙预测模型的校准

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The Pennsylvania Department of Transportation (PennDOT) is transitioning from empirical design procedures to the American Association of State Highway and Transportation Officials (AASHTO) Mechanistic-Empirical Pavement Design Guide (MEPDG) procedure and accompanying software AASHTOWare Pavement ME Design (Pavement ME) into its routine pavement design practice. Some aspects of the PennDOT pavement design practices were modified to implement the Pavement ME as a PennDOT standard. In addition, the implementation of the Pavement ME in Pennsylvania required local calibration to develop unbiased distress and smoothness prediction models suited to Pennsylvania's local conditions. This paper discusses the local calibration efforts undertaken to accurately predict the performance of fatigue cracking and total pavement rutting of asphalt concrete pavements in Pennsylvania using laboratory data from intermediate temperature indirect tensile strength and repeated load permanent deformation tests. As part of this study, the fatigue cracking and total pavement rutting global models were calibrated to reflect Pennsylvania-specific traffic, materials and soils, and environmental conditions, and PennDOT's commonly adopted pavement construction practices. The local calibration of the Pavement ME global performance prediction models was conducted using nonlinear model optimization techniques. The new local calibration coefficients were developed for each performance prediction model using Pennsylvania-specific design inputs and performance data. Overall, the local calibration process helped remove the bias (consistent over- or under-prediction), reduce the prediction error, and improve the accuracy of performance models. The improvement in these models was notable, thus indicating that the Pennsylvania-calibrated models would provide much more accurate, reliable, and cost-effective designs than the global performance prediction models.
机译：宾夕法尼亚州交通部（Penndot）正在向美国国家公路和运输官员（AASHTO）机制 - 经验路面设计指南（MEPDG）程序和伴随软件AASHTOWARE LAPEMENT ME DESIGN（PAWEMENT ME）进入其时的经验设计程序常规路面设计实践。 Penndot路面设计实践的一些方面被修改为将人行道的路面作为Penndot标准。此外，在宾夕法尼亚州的路面上的实施需要局部校准，以开发适用于宾夕法尼亚州当地条件的无偏见遇险和平滑预测模型。本文讨论了本地校准努力，以准确地预测宾夕法尼亚州的中间温度间接拉伸强度和重复载荷永久性变形试验的实验室数据在宾夕法尼亚州伯克夸的混凝土路面的疲劳裂缝和总路面排列的性能。作为本研究的一部分，疲劳开裂和整个路面集装箱全球模型被校准，以反映宾夕法尼亚特有的交通，材料和土壤，以及环境条件，以及Penndot通常采用的路面建设实践。使用非线性模型优化技术进行了路面校准ME全局性能预测模型。使用宾夕法尼亚特异性设计输入和性能数据为每个性能预测模型开发了新的局部校准系数。总的来说，本地校准过程有助于去除偏差（一致或欠预测），降低预测误差，提高性能模型的准确性。这些模型的改进是值得注意的，因此表明宾夕法尼亚州校准的模型将提供比全局性能预测模型更准确，可靠，并且具有成本效益的设计。

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