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Utilization of instrument response of SuperPave(TM) mixes at the Virginia Smart Road to calibrate laboratory developed fatigue equations.

机译:利用弗吉尼亚智能路的SuperPave(TM)混合物的仪器响应来校准实验室开发的疲劳方程。

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摘要

In the current mechanistic-empirical (M-E) design procedures for flexible pavements, the primary transfer functions are those that relate (a) maximum tensile strain in the hot-mix asphalt (HMA) surface layer to fatigue cracking and (b) compressive strain at the top of the subgrade layer to rutting at the surface. These functions, called fatigue and rutting equations, are usually derived from statistically based correlations of pavement condition with observed laboratory specimen performance, full-scale road test experiments or by both methods. Hot-mix asphalt fatigue behavior is an important component of a M-E design procedure; unfortunately, most of the existing models do not reflect field fatigue behavior. This is manifested in the fact that HMA fatigue failure is achieved much faster under a laboratory setting than in a field environment. This difference has been typically accounted for by the use of a single shift factor based mainly on engineering experience.;The flexible pavement portion of the Virginia Smart Road includes 12 different flexible pavement designs. Each section is approximately 100m long. The sections are instrumented with pressure cells, strain gages, time-domain reflectometry probes, thermocouples, and frost probes. The instruments were embedded as layers were built. Laboratory fatigue tests of field cores and field-mixed laboratory-compacted specimens along with measured response from the instrumented pavement sections at the Virginia Smart Road were used to quantify the differences between laboratory and field environments.;Four shift factors were identified to correlate field and lab fatigue behavior: stress-state, material difference, traffic wander, and healing. Field-measured critical strains and strain energy exerted during truck loading were both used to determine the stress state shift factor. Strain measurements of truck loading distribution (wander) were used to determine the wander shift factor. Finally, results from laboratory fatigue tests on cores and laboratory compacted specimens were used to evaluated a shift factor to account for the difference in compaction procedures. While the derived shift factors utilize the measured stresses and strains at the Virginia Smart Road, calculated strains and stresses, based on appropriate pavement and loading modeling, may also be used.
机译:在当前用于柔性路面的机械经验(ME)设计程序中,主要传递函数是与(a)热拌沥青(HMA)表层中的最大拉伸应变与疲劳龟裂和(b)处的压缩应变相关的传递函数。路基层的顶部使车辙在表面。这些功能称为疲劳和车辙方程,通常是根据路面状况与观察到的实验室标本性能,全面道路测试实验或这两种方法的统计相关性得出的。热拌沥青的疲劳性能是M-E设计程序的重要组成部分。不幸的是,大多数现有模型不能反映出场疲劳行为。这体现在以下事实:与实验室环境相比,在实验室环境下实现HMA疲劳失效要快得多。通常通过主要基于工程经验的单个换挡系数来解决这种差异。弗吉尼亚智能道路的柔性路面部分包括12种不同的柔性路面设计。每个路段长约100m。这些部分配有压力传感器,应变计,时域反射计探头,热电偶和霜冻探头。仪器是在构建图层时嵌入的。田间岩心和田间混合的实验室压实标本的实验室疲劳测试以及在弗吉尼亚智能路的仪器化路面部分的测量响应用于量化实验室和田间环境之间的差异;确定了四个移位因子以关联田间和田间环境。实验室疲劳行为:压力状态,物质差异,交通漂移和康复。在卡车装载期间施加的现场测量的临界应变和应变能均用于确定应力状态变化因子。卡车载荷分布(漂移)的应变测量用于确定漂移系数。最后,对芯和实验室压实样本进行实验室疲劳测试的结果用于评估偏移因子,以说明压实程序的差异。尽管导出的位移因子利用了弗吉尼亚智能路的测得应力和应变,但也可以使用基于适当的路面和荷载模型计算出的应变和应力。

著录项

  • 作者

    Nassar, Walid M.;

  • 作者单位

    Virginia Polytechnic Institute and State University.;

  • 授予单位 Virginia Polytechnic Institute and State University.;
  • 学科 Engineering Civil.
  • 学位 Ph.D.
  • 年度 2001
  • 页码 218 p.
  • 总页数 218
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 建筑科学;
  • 关键词

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