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Scaled physical modelling of ultra-thin continuously reinforced concrete pavement
Published in Andrew McNamara, Sam Divall, Richard Goodey, Neil Taylor, Sarah Stallebrass, Jignasha Panchal, Physical Modelling in Geotechnics, 2018
M.S. Smit, E.P. Kearsley, S.W. Jacobsz
In long-term pavement performance studies, pavements are monitored over extended periods of time. Accelerated Pavement Testing (APT) is popular because damage can be accumulated in a compressed timeframe (Metcalf 1998). Although some APT devices can be moved to different sites to test actual pavements (De Beer 1990, Van de Ven & De Fortier Smit 2000), they are also found in laboratories where controlled tests are conducted (Chan 1990, Juspi 2007). The fundamental feature is a loaded moving wheel. APT devices can run uni-directionally or bi-directionally and sometimes wander can be included (Donovan et al. 2016). Pavements can be tested at speeds up to 20 km/h and 800 passes per hour (CSIR 2017, Bowman & Haigh 2016, Dynatest 2017).
Machine learning analysis of overweight traffic impact on survival life of asphalt pavement
Published in Structure and Infrastructure Engineering, 2023
Jingnan Zhao, Hao Wang, Pan Lu
The long-term pavement performance (LTPP) program was established to collect pavement performance data to analyse various affecting factors, develop performance prediction models, and evaluate the effectiveness of pavement preservation and rehabilitation. Various pavement performance data have been analysed, including specific pavement distresses, pavement condition index, surface roughness, friction considering the interaction between pavement material and structure, traffic loading, and environmental conditions. Traditional regression models (Dong, Jiang, Huang, & Richards, 2013; Wang & Wang, 2017) and machine learning models (Fathi, et al., 2019; Ziari, Maghrebi, Ayoubinejad, & Waller, 2016) have been developed to analyse flexible pavement performance using the LTPP data. Survival analysis has been used to analyse pavement service life until the distress threshold is reached using parametric (Dong & Huang, 2015; Loizos & Karlaftis, 2005) or semi-parametric cox models (Guo, Wang, & Gagnon, 2021; Nakat & Madanat, 2008; Yu, Chou, & Yau, 2008) based on condition surveys of in-service pavements.
Impact of warming temperature on asphalt pavement overlay performance and cost: case study in New Jersey
Published in Road Materials and Pavement Design, 2022
A few studies have been conducted to address the issue of climate change impact on pavement performance. Meagher et al. (2012) found that the reduced transverse cracking and insignificant change of alligator cracking were expected with the rising air temperatures. Qiao et al. (2013) found that 5% increase in average temperature was responsible for the dramatic reduction of pavement service life in Virginia. Gudipudi et al. (2017) found that the projected climate changes would result in earlier pavement failure although variations were observed depending on the climate regions and the performance prediction models. Mallick et al. (2018) proposed a framework to understand the impact of climate change on pavement considering air temperature and precipitation, which can be used for the prediction of pavement life and evaluation of potential mitigation methods. Stoner et al. (2019) evaluated the impact of changing temperature and precipitation on flexible pavement performance using the projected temperature and precipitation data and found that the major increase in pavement distress is permanent deformation with the changing climate. Knott et al. (2019) investigated the impact of rising temperatures on seasonal and long-term pavement performance and concluded that later spring and summer contributed more than 90% of total pavement damage. Mohd Hasan et al. (2016) concluded that the mean annual temperature has a critical impact on fatigue cracking, transverse cracking and permanent deformation of flexible pavement. On the other hand, the study found that the mean annual precipitation had no significant impacts on pavement distresses.
Analysis of overweight vehicles on asphalt pavement performance using accelerated failure time models
Published in International Journal of Pavement Engineering, 2022
Miaomiao Zhang, Hongren Gong, Yuetan Ma, Rui Xiao, Baoshan Huang
This study aims to evaluate the impact of the number, weight, percentage of overweight vehicles on pavement performance, and to identify the most critical overweighting characteristics. Survival analyses implemented in gradient boosting tree models were employed for such a purpose. All data were collected from the long-term pavement performance (LTPP) program, and fatigue cracking and rutting were selected as the pavement performance indicators.