Author: Arif ChowdhuryPublisher:
ISBN:
Category : Aggregates (Building materials)
Languages : en
Pages : 154
Book Description
Pavement skid resistance is primarily a function of the surface texture, which includes both microtexture and macrotexture. Earlier, under the Texas Department of Transportation (TxDOT) Research Project 0-5627, the researchers developed a method to predict asphalt pavement skid resistance based on inputs including aggregate texture before and after polishing, gradation of asphalt mixture, and traffic levels. In this study, the researchers validated and revised the skid prediction model for asphalt pavements and developed oped a skid prediction model for seal coat surfaces. The researchers investigated and examined the surface friction characteristics of 70 test sections of asphalt mixtures and surface-treated roads in Texas. The test sections covered a wide range of mixtures and aggregate types. The researchers measured pavement macrotexture and microtexture of these sections and revised the traffic calculation. Historical skid numbers were obtained from TxDOT's Pavement Management Information System database and measured using a skid trailer. Aggregate texture and angularity was quantified using the aggregate image measurement system. Statistical methods were used to develop a prediction model for skid numbers, and the predicted values were compared to the measured ones in the field. The revised model describes the skid resistance of asphalt pavements as a function of aggregate characteristics, mixture gradation, and traffic level. The researchers incorporated aggregate angularity as an additional parameter in the model. Similarly, the researchers developed a skid prediction model for seal coat surfaces using the same parameters. A Microsoft Access--based Visual Basic desktop application was developed to automatically calculate the predicted skid numbers by incorporating the skid prediction mode ls. Using this standalone application, one can input the basic aggregate characteristics and traffic data to predict the pavement's skid resistance during its service life.
