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PREDICTION OF RESILIENT MODULUS MODEL FOR WEARING ASPHALT PAVEMENT LAYER

机译:磨损沥青路面层的弹性模量模型预测

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摘要

Resilient modulus for pavement layers is a key design parameter for pavement systems and permits for determination of how the pavement system will react to traffic loadings. It can be defined shortly as elastic modulus of a material under repeated loads. Several factors have effects on the elastic modulus of the layers of asphalt pavements. The indirect repeated axial load test was carried out by using the pneumatic repeated load system (PRLS) at Transportation Laboratory at Baghdad University to test seventy two cylindrical specimens prepared by the gyratory device. SPSS program was used to predict the resilient modulus model which contains many factors like asphalt content, asphalt viscosity, air voids, surface area, and temperature. Multiple linear regression is used to build the model of resilient modulus because it is a function of more than independent variables. F statistical significance value from the results of ANOVA table is smaller than 0.05 in the predicted model then the independent variables in the predicted model explain the variation in the resilient modulus variable. The coefficient of determination (R2) is 0.886 for the predicted model which is referred to a very good relation obtained. The predicted model shows that the modulus of resilience is highly affected by variation of temperature and moderately by viscosity of the asphalt whereas the stress level, types of filler, and the asphalt content have smaller effect on resilient modulus. The predicted model shows that there is a positive relationship among the resilient modulus and the two variables viscosity and the surface area whereas the three variables temperature, asphalt content, and air voids have inverse relationship with resilient modulus. Two asphalt types (40-50) and (60-70) from Dora refinery were used; the average value of resilient modulus corresponding to asphalt grade (40- 50) is almost 21.331% times the value for asphalt grade (60-70). Three asphalt contents (optimum asphalt content, optimum asphalt content±0.5) were used; when the content of asphalt was increased from 4% to 4.5%, the average resilient modulus decreased by 2.923% whereas increasing the percent of asphalt content from 4.5 to 5 the average resilient modulus decreased by 1.737%. Two types of mineral fillers (cement and limestone) were used, and when cement was used as mineral filler, the average resilient modulus increased by 4.422% rather than using limestone as filler in the asphalt mixture. Three temperatures for test were used 10, 25, and 40 oC. The results showed that when temperature was increased from 10 to 25 ◦C, the average resilient modulus decreases by 65.738%; whereas when the test temperature was increased from 25 to 40 oC, the average resilient moduli decreased by 97.715%. The results also showed that the average resilient modulus increased by 9.69% when the stress level increased from 6.5 psi to 13 psi.
机译:对于路面层回弹模量为路面系统和判定的路面系统将如何对交通负荷反应允许一个关键的设计参数。它可以在短期内定义为反复载荷下的材料的弹性模量。几个因素对沥青路面的各层的弹性模量的影响。间接重复轴向负荷试验使用在交通实验室气动重复载荷系统(PRLS)巴格达大学到测试由回转设备制备72个个的圆柱形试样进行。 SPSS程序是用来预测回弹模​​量模型,其包含了许多因素,如沥青含量,沥青的粘度,空气空隙,表面积,和温度。多重线性回归是用来建立弹性模量的模型,因为它是比独立变量更多的功能。从ANOVA表的结果双F统计显着性值是在预测模型小于0.05则在预测模型中的独立变量解释弹性模量变量的变化。决定系数(R 2)是0.886对于其被称为获得非常良好的关系的预测模型。预测模型显示,回弹模量是高度受温度影响的变化和适度由沥青而应力水平,类型的填料,和沥青含量的粘度对回弹模量更小的效果。预测模型表明,有弹性模量之间和正相关关系的两个变量的粘度和表面面积,而三个变量温度,沥青含量,和空气空隙与回弹模量反比关系。两种类型的沥青从多拉炼油厂中使用(40-50)和(60-70);对应于沥青级(40-50)的回弹模量的平均值为沥青级(60-70)几乎21.331%倍的值。三项沥青内容(最佳沥青含量,最佳沥青含量±0.5)被用来;当沥青的含量从4%提高到4.5%,平均回弹模量而增加的沥青含量从4.5至5百分比的平均回弹模量下降了1.737%下降2.923%。两种类型的矿物填料(水泥和石灰石)的使用,并且当水泥被用作矿物填料的平均回弹模量增加4.422%而不是使用石灰石作为沥青混合料的填料。三个温度为试验中使用10,25,和40摄氏度。结果表明,当温度从10提高到25?C,平均回弹模量由65.738%减小;而当测试温度从25提高到40摄氏度,平均弹性模量下降了97.715%。结果还表明,平均回弹模量增加了9.69%时的应力水平从6.5磅增加到13磅。

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    Miami Hilal;

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  • 年度 2018
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  • 正文语种 eng
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