国际粗糙度指数
覆盖
预测建模
沥青
沥青路面
环境科学
材料科学
表面光洁度
岩土工程
结构工程
复合材料
工程类
计算机科学
统计
数学
机械工程
程序设计语言
作者
Jinsong Qian,Jin Chen,Jiake Zhang,Jianming Ling,Chao Sun
标识
DOI:10.1177/0361198118768522
摘要
Pavement performance prediction after maintenance and rehabilitation is important to pavement management. A two-parameter exponential international roughness index (IRI) regression model for thin hot mix asphalt overlay was developed based on information from the U.S. Long Term Pavement Performance (LTPP) database. The model influence parameters α and β, which represent the initial IRI as the thin overlay completion and shape factor of IRI deterioration curve, were statistically analyzed. The results suggested that the IRI deterioration trends in high-temperature and low-temperature regions are different. This is because β was mainly affected by the structural strength and equivalent single axle loads in the high and medium temperature region and mainly affected by the average annual precipitation in low temperature region. In-situ data from LTPP database was used to verify the IRI prediction model, and it was found that the predicted IRI and measured IRI exhibited similar trends.
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