Development of a predictive model to estimate permeability of dense-graded asphalt mixture based on volumetrics

Asphalt mixtures with a coarser gradation typically provide greater rutting resistance due to a better structural network to resist shear, but they may present other issues, such as higher permeability. Increased permeability can facilitate water intrusion, which makes the pavement more vulnerable to moisture damage, stripping and erosion of unbound bases. Also, higher permeability promotes oxidation of asphalt binder, which may result in increased brittleness and susceptibility to cracking. The objective of this study was to develop a predictive model to estimate permeability of dense-graded asphalt mixture based on volumetrics. Eight Superpave mixtures were prepared: 9.5-mm fine and coarse graded, 12.5-mm coarse, 19-mm fine and coarse, 25-mm fine and 37.5-mm fine and coarse. Four target air void contents were defined for each mixture: 4%, 7%, 9% and 11%. Permeability tests were conducted using a falling head device according to the Florida Department of Transportation (FDOT) procedure FM 5-565. Permeability increased with air void content and nominal maximum aggregate size (NMAS); however, the effect of gradation was not conclusive as the primary control sieve point insufficiently defined gradation coarseness. In addition, voids filled with asphalt (VFA) exhibited a great correlation with permeability. Furthermore, two separate predictive models for 37.5-mm and 9.5 to 25-mm NMAS mixes were successfully developed based on regression analyses. These models provide a valuable decision tool to validate mixtures at a design stage on the basis of maximum permeability thresholds established by highway agencies. (C) 2016 Elsevier Ltd. All rights reserved.