Sensitivity of Input Variables for Flexible Pavement Rehabilitation Strategies in the M-E PDG

The Mechanistic-Empirical Pavement Design Guide (M-E PDG) can be used to design different flexible rehabilitation options; namely HMA over HMA (overlay), HMA over JPCP (composite), and HMA over JPCP fractured (rubblized). Each rehabilitation option has different input variables for new and existing layers. The type and magnitude of the input parameters have significant impact on the predicted flexible pavement performance. In order to evaluate the impact of various design inputs on the predicted performance for the rehabilitation options, one-variable-at-atime (OAT), and detailed sensitivity analyses were performed. While the OAT sensitivity analysis investigated the input variables specific to the existing pavement layers, it also determined the variable effects on the overall pavement performance. The OAT results identified the significant input variables of the existing pavement layers. Subsequently, based on the results of OAT sensitivity analysis, a detailed sensitivity analysis was performed. Full factorial matrices were designed to determine statistically significant main and interaction effects. This paper highlights the process of identifying the most sensitive input variables for flexible rehabilitation design options. The results of the sensitivity analyses show that the existing pavement condition rating and existing thickness for HMA over HMA overlays is critical for all performance measures. On the other hand, existing PCC modulus and thickness are important in determining the performance of HMA overlay over intact and rubblized JPCP. Keyword: Pavement rehabilitation, M-E PDG, Sensitivity analysis, Input variables