Evaluation of the long-term performance of flexible pavements with respect to production and construction quality control indicators

This paper details the process to develop a framework for connecting pavement construction quality control indicators to long-term performance at the network level. The framework relies on creating a relational database using geo-referencing of individual quality data points collected from the Wisconsin Department of Transportation highway construction projects. This paper demonstrates the ability of the developed system to define the statistical correlation between quality during asphalt mix production and surface construction to in-service performance. The different sources of data relating to pavement design, mix production, asphalt concrete placement, quality control measurements, performance surveys were connected to build a holistic geo-relational database. Four types of distresses (transverse, longitudinal, alligator cracking and rutting) were isolated from the performance surveys to be used as performance indicators. The impact of these distresses on the pavement was calculated in the form of a Deterioration Index (DI). The statistical information in this paper showed that the proposed system could identify changes in the mix properties and assess their impacts on the existence and intensity of distresses. The potential correlations of quality indicators and the four distresses were investigated using linear regression analysis. Based on the results, rutting and alligator cracking are found to be sensitive to quality deviation in air voids (Va), voids in mineral aggregate (VMA), and in-place density. More importantly, the approach detailed in this paper provides the needed foundation for quantifying the dependency of pavement performance on quality control indicators. (C) 2019 Elsevier Ltd. All rights reserved.