This session presents case studies in local calibration of pavement with mechanistic-empirical design, considering both data and materials issues. The session also includes a new proposed laboratory beam test that looks at mixture properties and joint-crack interaction.
Local Recalibration of JPCP Performance Models and Implementation Challenges in Michigan
Syed Haider, Michigan State UniversityShow Abstract
Neeraj Buch, Michigan State University
Wouter Brink, Applied Research Associates, Inc. (ARA)
A study was completed in 2014 to locally calibrate the performance prediction models for the AASHTOWare Pavement-ME Design Version 2.0. However, AASHTO has released Versions 2.2 and 2.3 of the software since the completion of the last study. In the newer versions, several bugs were fixed and some of the performance models were modified. As a result, the concrete pavement IRI predictions have impacted the PCC slab thicknesses. Thus, there was an urgent need to verify the performance predictions for rigid pavements in the State of Michigan for the Pavement-ME Versions 2.2 and 2.3. Rigid pavement performance model predictions between different Versions were compared which highlighted the changes in models. The measured performance data were compared with the performance predictions from the locally calibrated models to evaluate the need for re-calibration. Several challenges in the implementation of the Pavement-ME after re-calibration were encountered. The lessons learned while addressing these issues are documented in the paper.
The results showed performance models for rigid pavements (transverse cracking and IRI) have changed since the Pavement-ME Version 2.0. Because of these changes, and additional time series data being available, re-calibration of the models is warranted. The re-calibration of transvers cracking and IRI model reduced the SEE and bias for both the models. For a cumulative damage lower than 0.1, the cracking levels are negligible. The local calibration model coefficients can be further improved by considering the project specific permanent curl/warp value.
Practical Issues in Local Calibration and Implementation of AASHTOWare Pavement Me Design Procedure for Concrete Pavements
Shuvo Islam, Kansas State UniversityShow Abstract
Abu Sufian, University of Wisconsin, Madison
Mustaque Hossain, Kansas State University
Nat Velasquez, Kansas Department of Transportation
Ryan Barrett, Kansas Department of Transportation
This study was undertaken to locally calibrate the models in the AASHTOWare Pavement ME Design software and to compare the pavement designs done using the AASHTO 1993 and AASHTOWare Pavement ME Design software for jointed plain concrete pavement (JPCP) sections. Twenty-two newly constructed JPCP projects were selected to calibrate rigid pavement models; 17 of those projects were selected for calibration and five for validation. The traditional split sampling method was followed in calibration. MEPDG-predicted distresses of road segments were compared with the measured ones. Statistical analysis was performed using the Microsoft Excel statistical toolbox. The JPCP transverse joint faulting model was calibrated using sensitivity analysis and iterative runs of AASHTOWare to determine optimal coefficients that minimized bias. The International Roughness Index (IRI) model was calibrated using the generalized reduced gradient nonlinear optimization technique in Microsoft Excel Solver. The transverse slab cracking model could not be calibrated due to lack of measured cracking data. Eleven prospective and two in-service JPCP sections with varying design traffic levels were reanalyzed using both design methods. The results show that the 1993 AASHTO design guide yielded higher slab thickness than the AASHTOWare Pavement ME Design software for the projects with high traffic level. However, thinner slab thicknesses were obtained by the 1993 Design Guide for the projects with medium and low traffic.
Characterization of Concrete Materials for Rigid Pavement Design in New Mexico
Gauhar Sabih, University of New MexicoShow Abstract
Rafi Tarefder, University of New Mexico
The format of the design and performance prediction of rigid pavements was reformed with the advent of Pavement mechanistic-empirical (ME) design procedure, which now serves as the state-of-the-art tool in pavement design. Various state agencies are in the process of calibration of distress prediction models and characterization of concrete materials to provide accurate inputs required by Pavement ME design software. There are numerous concrete properties for which input data is required in ME design software, but with previous research, it was found that the concrete strength and thermal properties including elastic modulus, modulus of rupture and coefficient of thermal expansion (CTE) are the most important ones that affect the design and performance of rigid pavements. Accuracy of pavement design is heavily dependent on precision of these inputs. This study is part of a New Mexico Department of Transportation (NMDOT) research project that focuses on the development of guidelines for characterizing Portland cement concrete (PCC) materials for paving mixes being used in New Mexico. Concrete mixes with 5 different coarse aggregates were tested for these pivotal concrete strength properties at the curing age of 7, 14, 28 and 90 days, and for CTE at 28 days. The laboratory test results represent level 1 PCC material inputs. The data collected offered an excellent opportunity to validate and refine the ME default level 2 models for estimating flexural strength and elastic modulus based on compressive strength data. The data demonstrated a slight deviation from the nationally calibrated models. CTE values of concrete based on aggregate type were established for these material sources. Further analysis verified the benefit of using the level 1 inputs over the ME default models for accurate pavement design and performance prediction.
Small-Scale Test Method for Characterizing Joint/Crack Performance for Concrete Pavements
Manik Barman, University of Minnesota, Twin CitiesShow Abstract
Julie Vandenbossche, University of Pittsburgh
The joint performance of concrete slabs has a significant role on the development of faulting and corner cracks in conventional and unbonded concrete pavements and faulting, corner cracks and longitudinal cracks in bonded concrete overlays of asphalt pavements. The load transfer between the concrete slabs of undoweled joints or across cracks is realized through aggregate interlock, which largely depends on the crack width and crack surface texture. However, the concrete mixture plays an important role in the available aggregate interlock but is not currently characterized during the mixture design phase. The cost and time necessary for testing large size concrete slabs generally prevents such testing by designers. For this reason, a small-scale joint-performance testing method is introduced. The abrasive action that occurs on the slab face at the joints and cracks of in-service concrete pavement is simulated in this small-scale method. The potential joint performance for a concrete mixture can be tested using 152 mm x 152 mm x 610 mm (6 in x 6 in x 24 in.) beams. The loading configuration of the small scale test was established to simulate the deflection profile generated when a slab is load with 9-kip wheel load. The test setup was fabricated and a large number of beams were tested. The joint performance results obtained from beams are validated with the joint performance results from a full size slab test. It was found that the joint performance results from both the beams and the full size slab compare well with each other.