Impact of the variation in dynamic vehicle load on flexible pavement responses

The purpose of this research was to evaluate the dynamic variation in asphalt pavement critical responses due to dynamic tire load variations. An attempt was also made to develop generalized regression equations to predict the dynamic response variation in flexible pavement under various dynamic load conditions. The study used an extensive database of computed pavement response histories for five different types of sites (smooth, rough, medium rough, very rough and severely rough), two different asphalt pavement structures (thin and thick) at two temperatures (70 °F and 104 °F), subjected to a tandem axle dual tire at three speeds 25, 37 and 50 mph (40, 60 and 80 km/h). All pavement responses were determined using the 3D-Move Analysis program (Version 1.2) developed by University of Nevada, Reno. A new term called Dynamic Response Coefficient (DRC) was introduced in this study to address the variation in critical pavement responses due to dynamic loads as traditionally measured by the Dynamic Load Coefficient (DLC). While DLC represents the additional varying component of the tire load, DRC represents the additional varying component of the response value (standard deviation divided by mean response). In this study, DRC was compared with DLC for five different sites based on the roughness condition of the sites. Previous studies showed that DLC varies with vehicle speed and suspension types, and assumes a constant value for the whole pavement structure (lateral and vertical directions). On the other hand, in this study, DRC was found to be significantly varied with the asphalt pavement and function of pavement structure, road roughness conditions, temperatures, vehicle speeds, suspension types, and locations of the point of interest in the pavement. A major contribution of the study is that the variation of pavement responses due to dynamic load in a flexible pavement system can be predicted with generalized regression equations. Fitting parameters (R2) in the rage of 0.60 to 0.87 were observed the DRC predictive equations. In addition, verification of those generalized equations was evaluated using different sets of asphalt pavement structures and pavement materials. The differences between calculated and predicted values were found to be within +/-20% for the maximum tensile strain and +/-30% for the maximum compressive strain in the asphalt layer.