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GPR-based evaluation of strength properties of unbound pavement material from electrical characteristics

机译:基于GpR的电气特性评估未结合路面材料的强度特性

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摘要

It is well known that inter-particle friction and cohesion of soil particles and aggregates deeply affect the strength and deformation properties of soils, exerting critical effects on the bearing capacity of unbound pavement materials.udIn that respect, considering that strength characteristics of soil are highly dependent on particle interactions, and assuming a relationship between electric properties (e.g. electric permittivity) and bulk density of materials, a good correlation between mechanical and electric characteristics of soil is expected.udIn this work, Ground Penetrating Radar (GPR) techniques are used to investigate this topic. Two GPR equipmentudwith same electronic characteristics and different survey configurations are used. Each radar operates with twoudground-coupled antennae at 600 MHz and 1600 MHz central frequencies. Measurements are developed using 4udchannels, 2 mono-static and 2 bi-static. The received signal is sampled in the time domain at dt = 7.8125 × 10−2 ns, and in the space domain every 2.4 × 10−2 m.udA semi-empirical model is proposed for predicting the resilient modulus of sub-asphalt layers from GPR-deriveduddata. Basically, the method requires to follow two steps. Firstly, laboratory tests are carried out for calibration, with the main focus to provide consistent empirical relationships between physical (e.g. bulk density) and electric properties. The second step is focused on the in-situ validation of results through soil strength measurements retrieved by CBR tests and Light Falling Weight Deflectometer (LFWD). On the basis of traditional empirical equations used for flexible pavement design, the following expression is proposed, where Ei [MPa] is the ith expected resilient modulus of the surveyed soil under the line of scan, hj,i [m] is the i th thickness referred to the j th layer, and αj is a dielectric parameter calibrated as a function of the relative electric permittivity.udThe experimental setting requires the use of road material, typically employed for subgrade and subbase courses.udDifferent types of soil ranging from group A1 to A4 by AASHTO soil classification system, are analyzed. Asudregards the laboratory experiments, material is gradually compacted in electrically and hydraulically isolated testudboxes. A large metal sheet supports the experimental boxes, so that the transmitted GPR signal is totally reflected.udGPR inspections are carried out for any compaction step up to the maximum density value available. Moreover,udin-situ tests are carried out on targeted types of soil, with grain size distribution and texture comparable to those analyzed in laboratory environment.udThe results of this study confirm a promising correlation between the electric permittivities and the strength anduddeformation properties of the surveyed soils. Laboratory analyses show that the relationship between the relativeudpermittivity and the bulk density is positive: the higher the density of the compacted soil sample, the higher theudelectric permittivity of the medium. Analogously, in-situ validation presents a good comparison between measuredudand predicted data. Percentage errors less than 20% demonstrate that a reliable prediction of Young Modulus using this GPR-based approach can be achieved.
机译:众所周知,土壤颗粒和聚集体之间的颗粒间摩擦和内聚力会深深影响土壤的强度和变形特性,对未结合的路面材料的承载力产生关键影响。 ud在这方面,考虑到土壤的强度特性是高度依赖于粒子之间的相互作用,并假设电特性(例如,介电常数)与材料的堆积密度之间存在关系,因此,土壤的机械特性和电特性之间具有良好的相关性。 ud在这项工作中,探地雷达(GPR)技术是用于调查此主题。使用了两个具有相同电子特性和不同测量配置的GPR设备。每个雷达均使用两个地耦合天线,中心频率为600 MHz和1600 MHz。使用4个 udchannel,2个单静态和2个双静态来开发测量。在时域以dt = 7.8125×10−2 ns采样接收信号,在空间域以每2.4×10−2 m采样采样信号。 ud提出了半经验模型来预测次沥青层的弹性模量来自GPR衍生的 uddata。基本上,该方法需要遵循两个步骤。首先,进行实验室测试以进行校准,其主要重点是提供物理(例如堆积密度)和电性能之间的一致的经验关系。第二步着重于通过CBR测试和轻型落锤挠度计(LFWD)获得的土壤强度测量结果的现场验证。在用于柔性路面设计的传统经验公式的基础上,提出以下表达式,其中Ei [MPa]是被测土壤在扫描线下的第i个预期弹性模量,hj,i [m]是第i个厚度是指第j层的厚度,αj是作为相对介电常数的函数校准的介电参数。 ud实验设置需要使用通常用于路基和路基层的道路材料。 ud不同类型的土壤,范围从通过AASHTO土壤分类系统对A1至A4组进行了分析。根据实验室实验,材料在电气和液压隔离的测试箱中逐渐压实。一块大的金属板支撑着实验箱,从而使传输的GPR信号被完全反射。 udGPR将对压实步骤进行检查,直至达到可用的最大密度值。此外, udin原位测试是针对目标类型的土壤进行的,其粒度分布和质地与实验室环境中的分析结果相当。 ud本研究的结果证实了介电常数与强度和 u形变之间有希望的相关性被调查土壤的性质。实验室分析表明,相对介电常数与堆积密度之间的关系为正:压实土壤样品的密度越高,介质的介电常数越高。类似地,原位验证在测得的数据和预测的数据之间呈现出良好的比较。小于20%的百分比误差表明,使用基于GPR的方法可以可靠地预测杨氏模量。

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