Preparation of Joint Faulting Data for the Local Calibration of AASHTO Pavement ME Design in Louisiana
Danny Xiao, University of Wisconsin, PlattevilleShow Abstract
Zhong Wu, Louisiana Department of Transportation and Development
Zhongjie Zhang, Louisiana Department of Transportation and Development
Louisiana utilized performance data from the pavement management system (PMS) to evaluate and calibrate the AASHTO Pavement ME Design. Analysis of the PMS faulting data revealed that there were no records between zero and 0.2 inch; others over 0.2 inch appeared to be much greater than engineering experience. Therefore, several tasks were completed to validate the PMS faulting data and prepare them for the local calibration purpose. This paper presents details of the problem, the approach, results, and lessons learned. First, faulting data from the PMS and Long Term Performance Pavement database were analyzed to have an overview of the common range of joint faulting. To validate and compensate the PMS faulting data, 43 representative projects across Louisiana were selected for further analysis. Longitudinal profiles were collected using high-speed profilers and analyzed using the AASHTO R36 automated faulting measurement (AFM) algorithms. Manual measurements were also conducted during site visit. The comparison of faulting from different methods showed that the PMS data extremely overestimated faulting comparing to either the AFM estimation or the manual measurement. Results from the AFM algorithm were much closer (in the same magnitude) to manual measurements. Therefore, faulting data from the AFM algorithm were used and the faulting model was successfully calibrated. It is recommended that PMS faulting data have to be carefully evaluated before being applied to calibrate the AASHTO ME design software. Automated faulting measurement based on high-speed profiles is a feasible approach.
Load Transfer Restoration with Diamond Grinding on Rigid Pavements: Short Term and Long-Term Effectiveness
Sharlan Montgomery, Purdue UniversityShow Abstract
Samuel Labi, Purdue University
John Haddock, Purdue University
The objectives of this research were to develop nonlinear regression models describing the initial effect and the effect over time of load transfer restoration and diamond grinding (LTR/DG) treatments on pavement serviceability. This research used field data previously collected by Washington State Department of Transportation on pavement sections receiving LTR/DG treatments between 1993-2006. Expanded and simplified models were developed to describe the initial performance change associated with LTR/DG treatment. Considering the simplified model requires knowledge of fewer variables and describes the performance change with less variation, it is recommended for application. Charts were provided to estimate the expected performance change associated with LTR/DG. To achieve the greatest change, LTR/DG treatments should be performed on pavement younger than 30 years. A model was developed to describe the performance loss over time occurring after LTR/DG treatment. The regression model shows a slight increase in pavement condition for the first year or two following treatment, which was a common trend among individual pavement sections. Charts were provided to estimate the expected performance loss associated with LTR/DG. The simplified performance change model can be combined with the performance loss model to estimate the extended service life a LTR/DG treatment provides a particular pavement section. Additional performance change and performance loss models are recommended for LTR/DG treatments in other states and for longer post-treatment periods.
Deployment of Next-Generation Concrete Surface in Minnesota
Bernard Izevbekhai, Minnesota Department of TransportationShow Abstract
Lev Khazanovich, University of Pittsburgh
Vaughan Voller, University of Minnesota, Twin Cities
Development of a quiet diamond grinding configuration commenced in an initial laboratory effort at Purdue University followed by research iterations from 2007 to 2010 at MnROAD research facility of the Minnesota Department of Transportation (MnDOT). This paper discusses two major concrete rehabilitation projects that deployed the final product called the Next Generation Concrete Surface (NGCS). It also catalogues the progression of the grinding configuration at the MnROAD facility and the simultaneous development of a tire-pavement noise predictive model. In 2010, a $66 million concrete rehabilitation project was built with the NGCS on interstate 35 in Duluth Minnesota where a tire pavement noise reduction of 6 decibels representing 70 percent actual sound intensity (watts/m2) reduction was obtained. In another major deployment at Interstate Highway 394 in Minneapolis Minnesota in 2015, pavement noise reduction in each of 14 segments of the NGCS ground section recorded average sound intensity reduction of 46% which is perceivable in the human auditory domain. Acoustic benefits were consequently derived from replacing the previous surfacing of transverse tining on Interstate Highway 35 and ultra-thin-bonded-wearing-course (UTBWC) on Interstate 394 with NGCS as each project recorded lower post-grinding tire pavement noise. In these projects, MnDOT exceeded their stated goals of not increasing pre-grind tire-pavement noise level by the rehabilitation. However, in Interstate Highway 394 full acoustic benefit of NGCS was attenuated by anomalous effect of undulations reminiscent of the previous concrete-UTBWC interface that had inadvertently conferred a background configuration to the new ground surface.
Structural Behavior of Permeable Interlocking Concrete Pavement Under Heavy Traffic Loading: Results from Accelerated Pavement Testing
Hui Li, Tongji UniversityShow Abstract
David Jones, University of California, Davis
Rongzong Wu, University of California, Davis
John Harvey, University of California, Davis
Although permeable pavements are becoming increasingly common for stormwater management across the world, they are mostly used in parking lots, basic access streets, recreation areas, and landscaped areas, all of which carry very light, slow moving traffic. Very little research has been undertaken on the behavior of permeable interlocking concrete pavement as a surface and structure to support more heavy trucks. To understand how permeable interlocking concrete pavements (PICP) perform under heavy traffic loading, a research project was conducted at the University of California Pavement Research Center (UCPRC) with funding from the interlocking concrete pavement industry. The results of this project were used to develop a mechanistic-empirical (M-E) design method for PICP. This method is based on mechanistic analysis and was partially validated with accelerated pavement testing (APT) results. This paper presents a summary of the structural performance of PICP under heavy traffic loading with a Heavy Vehicle Simulator (HVS). The results include the rutting performance of PICP sections with three different thicknesses of subbase layer (reservoir layer) under dry, wet and drained conditions and with different load levels. The rut development with loading repetitions in the surface, base and subgrade layers is discussed.