The adoption and implementation of the Mechanistic-Empirical Pavement Design Guide (M-E PDG) by various states highway agencies require validation and calibration of its performance models. However, to facilitate the use of the guide, sensitivity analyses are warranted as a preliminary step. Such an analysis will identify significant input variables required for the design process. The results from the sensitivity analysis will also highlight the needs for resources required to quantify the input variables. The calibration of performance models will assist the state highway agencies to customize the design process to reflect local practices. The results ofsensitivity analyses showed that effect of Portland cement concrete (PCC)slab thickness, joint spacing and edge support on performance were significant among design variables while the coefficient of thermal expansion (CTE), modulus of rupture (MOR), base and subgrade characteristics played animportant role among material-related properties. The significant variables identified by sensitivity analyses can only be used to determine their relative effects on the pavement performance. For quantifying the impact of input variables on the pavement performance, simplified jointed plain concrete pavement (JPCP) performance models are presented in this paper. Theuse of simplified models is demonstrated by quantifying the impact of design-related input variables on expected performance at the initial design stage. It is useful to quantify the influence of variations in the levels of design inputs on JPCP predicted performance. While such information canhelp in reducing initial construction costs, it may also assist design engineers to estimate future maintenance and rehabilitation expenditures. Furthermore, comparison of different design alternates can be assessed usinglife cycle cost analyses to finalize the most cost-effective design alternative.
Abstract