Development of predictive model to determine the dynamic modulus for hot mix asphalt

The release of the AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) increased the importance of the dynamic modulus (E*) of asphalt mixes. However, E* evaluation methods such as Super Performance Tester (SPT) were found to be overly sophisticated for mix design and quality control stages. This research addresses the development of a simple and effective prediction model of E*.;To achieve this goal, a wide range of commonly used mixes in the State of Idaho was evaluated, a total of seventeen mixes. Seven additional different field mixes were selected for model validation. Dimensional analysis was used to determine the proposed model general form. Using 408 test data points, a prediction model was developed with a correlation coefficient R 2 of 0.962. The model was later verified using the seven additional field mixes. In addition, the proposed model results were compared to the two well-known Witczak's revised 1996 and 2006 models; it was found that the proposed model had better predictions, especially when used in MEPDG as Level-1 input. As a last step of validation, reliability simulation was conducted utilizing the MEPDG permanent deformation prediction models. The reliability of using the proposed model instead measured E* in MEPDG was found to be 95%.;In conclusion, the predicted E* values had a very high correlation with measured E* values. Hence, the model can be utilized in design stage when running MEPDG as Level-1 input instead of laboratory E* data, to eliminate any low performance mixes before conducting sophisticated tests.