Implementation of the 2002 AASHTO design guide for pavement structures in KDOT

011217662794430722008Final reportPDFTech ReportKTRAN: KSU-04-4C1431Automatic vehicle classificationConcrete pavementsMechanistic designPavement designPavement distressPavement performanceRigid pavementsWeigh in motionAmerican Association of State Highway and Transportation OfficialsInternational Roughness IndexLong-Term Pavement Performance ProgramMechanistic-Empirical Pavement Design GuideJointed plain concrete pavementKansasKansas. Dept. of TransportationKhanum, TaslimaMulandi, James NHossain, MustaqueKansas State UniversityKansas. Dept. of TransportationNTL-HIGHWAY/ROAD TRANSPORTATION-Bridges and StructuresNTL-HIGHWAY/ROAD TRANSPORTATION-DesignNTL-HIGHWAY/ROAD TRANSPORTATION-Pavement Management and PerformanceNTL-HIGHWAY/ROAD TRANSPORTATION-Construction and MaintenanceNTL-HIGHWAY/ROAD TRANSPORTATION-MaterialsThe AASHTO Guide for the Design of Pavement Structures is the primary document used by 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 an 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