个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:北卡州立大学
学位:博士
所在单位:交通运输系
联系方式:yanqing_zhao@dlut.edu.cn
电子邮箱:yanqing_zhao@dlut.edu.cn
Determination of axle load spectra based on percentage of overloaded trucks for mechanistic-empirical pavement design
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论文类型:期刊论文
发表时间:2021-01-12
发表刊物:ROAD MATERIALS AND PAVEMENT DESIGN
卷号:13
期号:4
页面范围:850-863
ISSN号:1468-0629
关键字:traffic characteristics; load distribution factor; pavement design; trucks
摘要:The mechanistic-empirical pavement design guide (MEPDG) developed under National Cooperative Highway Research Program Project 1-37A requires the use of axle load spectra or load distribution factors (LDFs) for pavement thickness designs. The MEPDG allows for various levels of LDF inputs, varying from site-specific (level 1) to regional average (level 2) and national average (level 3). There exists a concern that the MEPDG level 2 and level 3 inputs do not take any site-specific information into consideration and thus may result in erroneous thickness design. This study proposed a new approach to determine the axle LDF and number of axles per truck (NAPT) for level 2 and level 3 inputs. The proposed approach requires that the design guide provide default LDFs and NAPTs for both normally loaded and overloaded trucks for various axle types and vehicle classes. Thus, design engineers can estimate LDFs and NAPTs for a particular project site based on the percentages of overloaded trucks of that site which are readily available from historical traffic data. The effectiveness of the proposed approach was evaluated using weight-in-motion data collected from 26 sites in China. The LDFs and NAPTs obtained from various approaches were used to predict truck factors using the American Association of State Highway and Transportation Officials equation and to predict pavement distresses using the MEPDG software. The prediction errors from the proposed approach are substantially reduced when compared to those obtained using the MEPDG approach, indicating the proposed approach to be a more accurate way for traffic loading characterisation. The proposed level 2 inputs can further reduce the prediction errors when compared to the proposed level 3 inputs. Among the three types of pavement distresses analysed using the MEPDG software, namely rutting, bottom-up and top-down fatigue cracking, rutting is the least sensitive to the variations in axle LDF and NAPT, while top-down cracking is the most sensitive to the variations.