High quality predictive program provides an alternative to assess the long-term performance of asphalt pavements if well-evaluated based on field performance. The asphalt pavement performance models embedded in the Pavement ME Design program were developed based on hot mix asphalt (HMA) pavements, and the predictive quality varies depending on specific conditions. The applicability of the Pavement ME Design program as well as the embedded performance models to warm mix asphalt (WMA) pavements is even unclear. In addition, the ability of the Pavement ME Design program in differentiating HMA and WMA performance, if any, has not been evaluated. Therefore, the objectives of this study are to determine the predictive quality of the Pavement ME Design program for the field performance of WMA pavements, and further to evaluate the capability of Pavement ME Design program in detecting performance difference between HMA and WMA pavements if there is any. A total of 43 asphalt pavements (both HMA and WMA) from 16 projects were evaluated based on their field measured and predicted performance, in terms of rutting, transverse cracking and top-down longitudinal cracking. Results indicate that (1) The Pavement ME Design program can predict the field rut depth well for HMA and WMA pavements, in terms of both numerical values and rankings. However, the software in general over-estimates the field rut depth; (2) The Pavement ME Design program cannot predict field transverse cracking or field longitudinal cracking correctly irrespective of pavement type; (3) The results suggest that the effect of moisture should be considered in the Pavement ME cracking models for both HMA and WMA pavements, and (4) Overall, the predictive quality of the Pavement ME Design program for HMA and WMA is similar, either in good or poor prediction results. The WMA technology does not fundamentally alter the behavior of asphalt materials in pavement application. We suggest treating WMA similarly as HMA while applying the Pavement ME Design program for performance prediction. However, the corresponding WMA material properties should be used as input values.
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Building and Construction
- Materials Science(all)