The development of a predictive tool to reduce experimentation time for the polishing and frictional evaluation of asphalt pavement surfaces

The laboratory simulation of asphalt pavement surface deterioration is usually a lengthy process. In this study, a predictive tool (or equation) was developed to calculate the steady state torque-based coefficient of friction (Tfr) and the onset of steady state. To this end, nonlinear regression was utilized and a Graphical User Interface (GUI) was built in MATLAB®. The purpose of the tool is to reduce experimentation time. Eight sets of data were used. Data was obtained from laboratory testing conducted on eight Job Mix Formulas (JMFs) of highway materials obtained from the State of Ohio. The data was collected using a power unit (or motor) attached to a newly developed asphalt polishing machine to detect surface deterioration. The experiment measures torque values that are directly related to friction values; the so called torque-based coefficients of friction. The main characteristic of the equation allows for calculating the steady state Tfr and the onset of steady state. This enables the experimenter to determine when steady state is reached at a desired tolerance during the test, thus reducing the time required for testing. It was concluded that testing time can be reduced significantly (a range of 40% to 50% savings), which may be received positively by Departments of Transportation and other highway material testing laboratories around the world.