performance evaluation of dynamic modulus predictive models for asphalt mixtures

Dynamic modulus characterizes the viscoelastic behavior of asphalt materials and is the most important input parameter for design and rehabilitation of flexible pavements using mechanistic–empirical pavement design guide (mepdg). laboratory determination of dynamic modulus is very expensive and time consuming. to overcome this challenge, several predictive models were developed to determine dynamic modulus of asphalt mixtures instead of laboratory testing. present study utilizes a large database of 1320 dynamic modulus test results developed at the university of maryland to evaluate the performance and accuracy of different dynamic modulus predictive models. for this purpose, six conventional dynamic modulus predictive models including witczak, modified witczak, hirsch, alkhateeb, global and simplified global models were considered and dynamic moduli of asphalt mixtures were determined. these moduli were then compared with those determined from laboratory test results. performance evaluation of the models showed high prediction accuracy and low prediction bias with good correlation between predicted moduli and measured values for witczak and global models.