Pavement design procedures, available in the literature, do not fully take advantage of mechanistic concepts, which make them heavily rely on empirical approaches. Because of the heavy dependence on empirical procedures, the existing design methodologies do not capture the actual behavior of Portland cement concrete (PCC) pavements. However, reliance on empirical solutions can be reduced by introducing mechanistic-empirical methods, which is now adopted in the newly released mechanistic-empirical pavement design guide (MEPDG). This new design procedure incorporates a wide range of input parameters associated with the mechanics of rigid pavements. To compare the sensitivity of these various input parameters on the performance of concrete pavements, two jointed plain concrete pavement (JPCP) sites were selected in Iowa. These two sections are also part of the Long Term Pavement Performance (LTPP) program where a long history of pavement performance data exists. Data obtained from the Iowa Department of Transportation (Iowa DOT) Pavement Management Information System (PMIS) and LTPP database were used to form two standard pavement sections for the comprehensive sensitivity analyses. The sensitivity analyses were conducted using the MEPDG software to study the effects of design input parameters on pavement performance of faulting, transverse cracking, and smoothness. Based on the sensitivity results, ranking of the rigid pavement input parameters were established and categorized from most sensitive to insensitive to help pavement design engineers to identify the level of importance of each input parameter. The curl/warp effective temperature difference (built-in curling and warping of the slabs) and PCC thermal properties are found to be the most sensitive input parameters. Based on the comprehensive sensitivity analyses, the idea of developing an expert system was introduced to help the pavement design engineers identify the input parameters that they can modify to satisfy the predetermined pavement performance criteria. Predicted pavement distresses using the MEPDG software for the two Iowa rigid pavement sites were compared against the measured pavement distresses obtained from the Iowa DOT's PMIS and comparison results are discussed in this study.

The AASHTO Guide for Design of Pavement Structures is the primary document used by the state highway agencies to design new and rehabilitated highway pavements. Currently the Kansas Department of Transportation (KDOT) uses the 1993 edition of the AASHTO pavement design guide, based on empirical performance equations, for the design of Jointed Plain Concrete Pavements (JPCP). However, the newly released Mechanistic-Empirical Pavement Design Guide (MEPDG) provides methodologies for mechanistic-empirical pavement design while accounting for local materials, environmental conditions, and actual highway traffic load distribution by means of axle load spectra. The major objective of this study was to predict pavement distresses from the MEPDG design analysis for selected in-service JPCP projects in Kansas. Five roadway sections designed by KDOT and three long term pavement performance (LTPP) sections in Kansas were analyzed. Project-specific construction, materials, climatic, and traffic data were also generated in the study. Typical examples of axle load spectra calculations from the existing Weigh-in-Motion (WIM) data were provided. Vehicle class and hourly truck traffic distributions were also derived from Automatic Vehicle Classification (AVC) data provided by KDOT. The predicted output variables, IRI, percent slabs cracked, and faulting values, were compared with those obtained during annual pavement management system (PMS) condition survey done by KDOT. A sensitivity analysis was also performed to determine the sensitivity of the output variables due to variations in the key input parameters used in the design process. Finally, the interaction of selected significant factors through statistical analysis was identified to find the effect on current KDOT specifications for rigid pavement construction. The results showed that IRI was the most sensitive output. For most projects in this study, the predicted IRI was similar to the measured values. MEPDG analysis showed minimal or no faulting and was confirmed by visual observation. Only a few projects showed some cracking. It was also observed that the MEPDG outputs were very sensitive to some specific traffic, material, and construction input parameters such as, average daily truck traffic, truck percentages, dowel diameter, tied concrete shoulder, widened lane, slab thickness, coefficient of thermal expansion, compressive strength, base type, etc. Statistical analysis results showed that the current KDOT Percent Within Limits (PWL) specifications for concrete pavement construction are more sensitive to the concrete strength than to the slab thickness. Concrete slab thickness, strength, and truck traffic significantly influence the distresses predicted by MEPDG in most cases. The interactions among these factors are also almost always evident.

As AASH is expected to eventually adopt the MEPDG at its primary pavement design method, it is critical that the SDDOT become familiar with the MEPGD documentation and associated design software. The research conducted under this project was a first step toward achieving this goal.

"Abstract: This report completes a sensitivity analysis of the MEPDG based on Oklahoma pavements, provides a literature review of base material best practices, increases the Oklahoma weather data available for the MEPDG, investigates the impact of curing on curling from drying shrinkage and from temperature differentials in concrete pavements, provides regional input guidance for strength, coefficient of thermal expansion, and shrinkage for Oklahoma concrete mixtures. This research will speed the adoption of the MEPDG in Oklahoma."--Technical report documentation page.