介绍使用设计钳口的沥青剪切强度实验模型,并通过遗传编程法介绍剪切强度预测模型

IF 2 4区 工程技术 Q2 ENGINEERING, CIVIL
Morteza Modarresi, Hassan Divandari, Mohsen Amouzadeh Omrani, Mojtaba Esmaeilnia Amiri
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引用次数: 0

摘要

道路建设中使用的主要材料是沥青。因此,认识沥青的力学方面是非常重要的。沥青的重要特性之一是抗剪强度,应准确测量。然而,已经提出的测量沥青这一重要因素的方法总是遇到弱点。因此,有必要寻找一种适合的方法来确定沥青的抗剪强度,使结果更准确,与实际吻合度高。因此,本研究的目的是设计钳口,以测量交通路径方向和反方向的抗剪强度,并提供利用发明钳口产生的马歇尔稳定性预测抗剪强度的模型。为了检验本研究中设计颚的准确性,使用了两种不同类型的沥青,Binder 0-25和Topeka 0-19级配。为此,在这些样品上进行了马歇尔方向和反马歇尔方向的稳定性和抗剪强度试验,共重复12次。采用遗传规划(GP)进化算法建立了抗剪强度预测模型。研究结果表明,在两种沥青类型中,应用所发明的颌口,马歇尔方向和反方向的马歇尔稳定性与抗剪强度之间存在显著的相关关系,其中Binder和Topeka在马歇尔方向的决定系数R2分别为0.93和0.97,在马歇尔方向的决定系数R2分别为0.96和0.95。GP方法的结果表明,Binder和Topeka沥青两种类型的抗剪强度预测值与实际值的关系在交通方向上R2分别为99.47%和99.21%,RMSE分别为8.0177和5.0143;在交通反方向上R2分别为97.45%和98.08%,RMSE分别为1.2684和0.7035。因此,GP为Binder和Topeka沥青的所有实验数据提供了更合适的拟合,可以说,在新设计的钳口的帮助下,可以高精度地估计Marshall方向和反方向的抗剪强度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Introducing an Experimental Model of Asphalt Shear Strength Using Designed Jaws and Presentation of Shear Strength Prediction Model by Genetic Programming Method

Introducing an Experimental Model of Asphalt Shear Strength Using Designed Jaws and Presentation of Shear Strength Prediction Model by Genetic Programming Method

The main material used in the construction of roads is asphalt. Therefore, the recognition of asphalt’s mechanical aspects is very important. One of the important features of asphalt is its shear strength, which should be measured accurately. However, the methods that have been presented to measure this important factor of asphalt always encounter weaknesses. So, it is necessary to find a suitable method to determine the shear strength of asphalt with more accurate results and high compatibility with reality. In this regard, the purpose of the present research was to design jaws in order to measure the shear strength in the direction and opposite direction of the traffic path and provide a model to predict shear strength using Marshall stability resulting from invented jaws. In order to examine the accuracy of the designed jaw in this study, two different types of asphalt, Binder 0–25 and Topeka 0–19 grading, were used. For this purpose, Marshall stability and shear strength tests in the direction and opposite direction of the Marshall were conducted with 12 repetitions on these samples. Also, the genetic programming (GP) evolutionary algorithm was applied in this study to provide a prediction model of shear strength. The results of this study indicated that there was a significant relationship between the Marshall stability and the shear strength in the direction and opposite direction of the Marshall applying the invented jaws in both asphalt types, and the coefficient of determination (R2) for the Binder and Topeka were 0.93 and 0.97 in the Marshall’s direction and 0.96 and 0.95 for the Marshall’s opposite direction, respectively. Also, the results of the GP method indicated that the relationships between predicted and actual values of shear strength for Binder and Topeka asphalt types were appropriately described by R2 of 99.47% and 99.21% with RMSE of 8.0177 and 5.0143 in the traffic direction, and R2 of 97.45% and 98.08% with RMSE of 1.2684 and 0.7035 in the traffic opposite direction, respectively. Therefore, GP provided a more suitable fit of all experimental data for both Binder and Topeka asphalts, and it can be said that with the help of new designed jaws, the shear strength in the direction and opposite direction of the Marshall can be estimated with high accuracy.

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来源期刊
Journal of Advanced Transportation
Journal of Advanced Transportation 工程技术-工程:土木
CiteScore
5.00
自引率
8.70%
发文量
466
审稿时长
7.3 months
期刊介绍: The Journal of Advanced Transportation (JAT) is a fully peer reviewed international journal in transportation research areas related to public transit, road traffic, transport networks and air transport. It publishes theoretical and innovative papers on analysis, design, operations, optimization and planning of multi-modal transport networks, transit & traffic systems, transport technology and traffic safety. Urban rail and bus systems, Pedestrian studies, traffic flow theory and control, Intelligent Transport Systems (ITS) and automated and/or connected vehicles are some topics of interest. Highway engineering, railway engineering and logistics do not fall within the aims and scope of JAT.
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