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Evaluation of HWD Backcalculation Tools and Methodologies Using FAA National Airport Pavement Test Facility's Data

机译:使用FAA国家机场路面测试设施的数据评估HWD反算工具和方法

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Accurate estimation of the elastic modulus of pavement layers is essential when examining the condition and load bearing capacity of an airfield pavement. Pavement surface deflections obtained from heavy weight deflectometer (HWD) has been widely used as a non-destructive testing method to obtain the elastic modulus of the pavement layers. The method involves a backcalculation procedure. The accuracy of the backcalculated modulus depends upon the accuracy of the forward calculation method as well as the iteration technique. This paper presents findings from implementing a number of tools and methodologies developed for HWD test analysis using data from the National Airport Pavement Test Facility's HWD Round-up study. Selected tools for backcalculation of the test data represent a variety of methodologies from the typical multilayer elastic theory to the method of equivalent thickness and the artificial neural network. The findings presented in this study formed the basis of the recommendation for improving and upgrading BAKFAA to be used more effectively as a comprehensive and state-of-the-practice airfield pavement backcalculation.
机译:在检查飞机场路面的状况和承载能力时,准确估算路面层的弹性模量至关重要。从重量偏折仪(HWD)获得的路面表面挠度已被广泛用作获得路面层的弹性模量的非破坏性测试方法。该方法涉及反算程序。反算模量的精度取决于正向计算方法以及迭代技术的精度。本文介绍了使用国家机场路面测试设施的HWD汇总研究数据,实施为HWD测试分析开发的许多工具和方法的发现。用来对测试数据进行反算的选定工具代表了从典型的多层弹性理论到等效厚度方法和人工神经网络的各种方法。这项研究中提出的发现构成了改进和升级BAKFAA的建议的基础,以便更有效地将其用作综合性和实践性的飞机场路面反算。

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