Document Type
Article
Publication Date
11-2017
Department
Department of Civil, Environmental, and Geospatial Engineering
Abstract
In China, the research on asphalt pavement deterioration was hindered by a lack of comprehensive investigations on field data collection of pavement performance within its service life. The problem of traditional methods that yield inadequate data can be addressed using a combination of the Pavement Mechanistic-Empirical (PME) system and matter-element analysis (MEA). Measured data for the rutting of a road section in the Shaanxi province was employed as the validation data in this study. The input parameter for PME was localized, and a decay model based on the predicted results of PME was established by the MEA method. The results from PME indicate that the predicted results of rutting show a “lagging” characteristic when compared with the measured data. Some optimization measures are employed to process the predicted results of PME so as to better fit the measured data. The predicted data for rutting resistance can be considered essential data for the MEA method to investigate the decay tendency of the rutting of asphalt pavement in its design life. A case study indicates that the rutting resistance of asphalt pavement will deteriorate from excellent to good, good to medium, medium to inferior, and inferior to bad in 13.8 months, 32.5 months, 43.8 months, and 55.2 months, respectively. The combination of PME and MEA proves to be appropriate to evaluate rutting potential in project level pavements. Follow-up research can be carried out on the developing trend of pavement damage, so as to better determine the maintenance time for a chosen road section.
Publication Title
International Journal of Pavement Research and Technology
Recommended Citation
Zhang, C.,
Wang, H.,
You, Z.,
Liu, Y.,
Yang, X.,
&
Xiao, J.
(2017).
Prediction on Rutting Decay Curves for Asphalt Pavement Based on the Pavement-ME and Matter Element Analysis.
International Journal of Pavement Research and Technology,
10(6), 466-475.
http://doi.org/10.1016/j.ijprt.2017.06.002
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/6565
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