基于动态模量的沥青混合料车辙预估模型研究

发布时间：2018-01-12 14:14

本文关键词：基于动态模量的沥青混合料车辙预估模型研究　出处：《西安建筑科技大学》2014年硕士论文　论文类型：学位论文

【摘要】：在车辆荷载的长期反复作用下，沥青路面会出现不同程度的车辙病害，尤其在夏季高温条件下，这种病害发展更快，严重影响了路面的使用寿命和服务质量，还危及行车安全。长期以来，道路科研工作者或者从沥青混合料材料性能、沥青路面结构出发，或者从影响路面车辙的外部条件出发，分析沥青路面车辙产生的机理，采用不同方法对沥青面层的永久变形进行了预估。有研究者指出沥青混合料动态模量及动态模量指标与其高温性能密切相关，同时验证了动态模量及动态模量指标与沥青路面永久变形的相关性，试图运用这一动态指标对沥青路面车辙问题进行研究。基于此，本文首先借助于旋转压实仪及简单性能试验机(SPT)，进行了室内沥青混合料旋转压实试验和动态模量试验，分析了试验温度T，加载频率f，加载应力P，混合料的体积指标（如孔隙率VV，有效沥青用量Vbeff等）以及混合料级配等对混合料动态模量和相位角的影响规律，根据时间—温度置换原理,运用非线性最小二乘法回归拟合得到了不同温度间的移位因子，建立了动态模量主曲线，获得了主曲线方程。之后根据Witczak动态模量预估模型及Sigmoidal函数方程基本思想，通过考虑试验温度、加载频率、加载应力、混合料体积指标和级配特征，运用麦夸特法优化算法得到了沥青混合料动态模量预估模型，并对该预估模型进行了验证。验证表明该预估模型具有较好的通用性。动态模量与动态模量指标能够反映沥青混合料在车辆荷载作用下的动态特性，通过分析表明其与车辙变形量有较强的相关性。而后通过室内标准车辙试验及改进车辙仪的全厚式车辙试验得到了不同温度，厚度，级配，加载条件下单层，双层，全厚式车辙板试件的车辙变形规律。通过分析沥青层厚度，荷载作用次数，动态模量指标，行车速度等车辙影响因素，结合有限元计算，采用亚层变形叠加的思想，提出了一种新的车辙预估模型。进而用基因遗传算法基本原理，编写相应程序，根据试验数据对预估模型的相关系数进行了拟合。通过进一步的试验，利用不同温度，，不同荷载条件下的全厚式车辙试验数据验证了该模型，结果表明该模型能够反映不同条件下沥青面层的变形规律，也说明该预估模型具有较好的适用性，对实际沥青路面车辙病害的防治有较好的指导意义。
[Abstract]:Under the long-term repeated action of vehicle load, asphalt pavement will appear different degrees of rutting disease, especially in the summer high temperature conditions, this disease development faster, seriously affected the pavement service life and quality of service. For a long time, road researchers have started from the performance of asphalt mixture materials, asphalt pavement structure, or from the external conditions that affect road rutting. The mechanism of rutting on asphalt pavement is analyzed and the permanent deformation of asphalt pavement is predicted by different methods. Some researchers point out that the dynamic modulus and dynamic modulus index of asphalt mixture is closely related to its high temperature performance. At the same time, the correlation between dynamic modulus and dynamic modulus index and permanent deformation of asphalt pavement is verified, and the rutting problem of asphalt pavement is studied by using this dynamic index. Based on this, the rotating compaction test and dynamic modulus test of indoor asphalt mixture are carried out with the help of rotary compaction instrument and simple performance tester SPT, and the test temperature T and loading frequency f are analyzed. The effect of loading stress, volume index of mixture (such as porosity VV, effective asphalt dosage Vbeff, etc.) and mixture gradation on dynamic modulus and phase angle of mixture. According to the principle of time-temperature replacement, the shift factor between different temperatures is obtained by nonlinear least square regression, and the main curve of dynamic modulus is established. The main curve equation is obtained. Then, according to the Witczak dynamic modulus prediction model and the basic idea of Sigmoidal function equation, the test temperature, loading frequency and loading stress are considered. Based on the volume index and gradation characteristics of asphalt mixture, the dynamic modulus prediction model of asphalt mixture is obtained by using the optimization algorithm of McQuat method. The prediction model is verified and verified, which shows that the prediction model has good generality. Dynamic modulus and dynamic modulus index can reflect the dynamic characteristics of asphalt mixture under vehicle load. The analysis shows that it has a strong correlation with the rut deformation, and then through the indoor standard rutting test and the improved rutting instrument of the full-thickness rutting test to obtain different temperatures, thickness, grading, loading conditions under the single layer. The rutting deformation law of double-layer and full-thickness rutting plate is analyzed by analyzing the influence factors of asphalt layer thickness, loading times, dynamic modulus index, driving speed and so on, combined with finite element calculation. Based on the idea of superposition of sublayer deformation, a new rut prediction model is proposed, and the corresponding program is compiled using the basic principle of genetic algorithm. According to the test data, the correlation coefficient of the prediction model is fitted. Through further experiments, the full-thickness rutting test data under different temperature and different load conditions are used to verify the model. The results show that the model can reflect the deformation law of asphalt surface under different conditions, and it also shows that the prediction model has good applicability, and has a better guiding significance for the prevention and treatment of rutting diseases on actual asphalt pavement.
【学位授予单位】：西安建筑科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U414

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