Pavement Rutting Dynamic Prediction Model

Rutting is one of major distresses affecting pavement performance. Most existing rutting models are based on a mechanistic-empirical (M-E) modeling approach or simply an empirical approach. M-E models use input parameters such as Poisson's ratio and either resilient modulus or dynamic modulus. Laboratory tests or other procedures conducted to determine these material parameters are expensive and time consuming. The cause of pavement deformation is very complicated and is affected by many variables, such as material properties, environmental conditions, and traffic loadings. Therefore, many of the models could not predict field data adequately. Thus, in this study, a pavement rutting dynamics prediction model (PRDPM) based on Grey System Theory is developed, based on rutting depth data obtained from laboratory tests. The developed model was verified using field test data obtained from domestic and other countries. The regression analysis results show that the predicted and measured value have more than 95% of linear relationship, and exhibit statistic significance. Therefore, the dynamic model can be used in Taiwan area with high degree of confidence. In addition, the model can predict rutting depths from the estimated traffic volumes to establish the threshold time for pavement maintenance, thus as a useful tool for pavement management system.

並列關鍵字

Grey system theory ； Mechanistic-empirical (M-E) model ； Permanent deformation ； Rutting

國際替代計量

全文下載

主題瀏覽