Desirable Values for Pavement Evaluation and Study of Performance Prediction Model

众所周知，沥青混凝土的模量在很大程度上取决于它的温度。寒冷地区土木工程研究所和行政机关公共工程研究所于2004年在北海道Wakkanai的试验场进行了路面试验，目的是建立寒冷地区的路面设计规范。在2006年6月、8月和11月进行了FWD测试，并测量了路面温度。我们利用了这些数据。采用静、动态两种反算方法估计层模量。根据反演的层模量和温度，建立了沥青混凝土层的温度依赖模型。并通过探地雷达试验测量了沥青混凝土层厚，证实了探地雷达可以识别沥青混凝土层厚。由于沥青混凝土模量对其温度非常敏感，因此在不直接测量的情况下对路面温度进行预测具有重要意义。路面温度受气象变化和路面层热特性的影响。去年，我们开发了一种方法来估计热性能，如热容量和导热系数从测量温度数据。为了预测路面温度，我们发现大气辐射和太阳辐射一样重要。我们利用在东京电机大学试验场观测到的向下红外辐射发展了大气辐射模型。估计路面层模量的常用方法是利用FWD数据中的峰值荷载和峰值挠度。考虑到FWD对路面施加脉冲荷载，我们开发了高效的动态反算软件DBALM。DBALM不仅可以识别层模量，还可以识别相应的层阻尼系数。除了层模量和阻尼系数外，我们还开发了一种新的层密度识别算法。算法的可靠性验证正在进行中。

It has been known that a modulus of asphalt concrete depends highly on its temperature. Civil Engineering Research Institute for Cold Region, Incorporated Administrative Agency Public Works Research Institute conducted pavement at the test sites in Wakkanai, Hokkaido in 2004 for the purpose of establishing pavement design code in the cold region. In June, August, November 2006, FWD tests were conducted and pavement temperature was also measured. We made use of these data. Backcalcalculat5ion was performed by both static and dynamic methods to estimate layer moduli. From both backcalculated Layer moduli and there temperature, a temperature dependent model of asphalt concrete layer was established. We also measured layer thickness by GPR test, we confirmed that GPR could identify thickness of asphalt concrete layer.Since asphalt concrete modulus is sensitive to its temperature, it is important to predict pavement temperature without measuring it directly. Temperature in pavement is influenced by meteorological change and thermal properties of pavement layers. Last year we developed a method to estimate thermal properties such as heat capacity and thermal conductivity from measured temperature data. In order to predict pavement temperature, we found atmospheric radiation is as important as solar radiation. We developed the atmospheric radiation model using downward infrared radiation observed at our test site at Tokyo Denki University.A common approach to estimate pavement layer moduli utilizes peak load and peak deflections from FWD data. Considering that FWD applies impulsive load to pavement surface, we have developed efficient dynamic backcalculation software called DBALM. DBALM can identify not only layer moduli but also the corresponding layer damping coefficients. In addition to layer modulus and damping coefficients, we have developed new algorithm which can identify a layer density. Reliability confrimation of the algorithm is in progress.