Abstract
During the planning of overlay construction activities, a contractor and/or state agency may be interested in selecting a tack coat material and application rate that would provide adequate interface bonding at the site. The objective of this study was to develop an interface shear strength (ISS) predictive model to estimate interface bonding between the hot-mix asphalt (HMA) overlay and the underlying pavement layer. To achieve this objective, 10 field rehabilitation projects were selected in six states that included 33 in-service test sections representing different traffic and climatic conditions. The overlay construction used different types of tack coat at various residual application rates. Field cores were obtained to measure ISS using a direct shear test device, referred to as the Louisiana Interlayer Shear Strength Tester (LISST). Influencing factors to be included in the model were pavement surface type and mean texture depth, residual application rate, and characteristics of tack coat residues. The experimental data were complemented with test results from a recently completed study for model development and validation. Two types of statistical regression models (linear and nonlinear) were evaluated. Results of the analysis showed that the predicted ISS obtained from the proposed models were in good agreement with the measurements. Further, the developed nonlinear model showed better prediction accuracy than the linear model. The nonlinear model can be used effectively for optimum selections of tack coats given the project conditions. The results presented herein were part of NCHRP Project 9-40A, Field Implementation of the Louisiana Interface Shear Strength Test.
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