Investigation of significant inputs for pavement rehabilitation design in the Pavement-ME.

The Pavement-ME can design different flexible or rigid pavement rehabilitation scenarios. A set of quantitative and qualitative input variables are considered to characterize the new and existing pavement layers and predict the damage accumulation in these layers. To evaluate the impact of the inputs on the predicted performance for the rehabilitation options, sequential analyses were performed to assess the main and interactive effects of each input. Continuous responses surface models for interactive effects were obtained using artificial neural network. Furthermore, a normalized sensitivity index was used to quantify the significance of main and interactive effects. The following rehabilitation options were included in this paper: hot mix asphalt (HMA) over HMA, HMA over jointed plain concrete pavement (JPCP), HMA over fractured JPCP, and JPCP over JPCP. The results of the study can assist the highway agencies' efforts to implementing the Pavement-ME, especially when the majority of pavement designs are related to rehabilitation of the existing highways. [ABSTRACT FROM AUTHOR]