Realistic prediction of asphalt temperatures as a function of time during paving is essential for optimizing compaction operations. Continued compaction after the asphalt lift has dropped below a critical threshold temperature may result in particle breakage and degradation of the material properties. To address this issue, this study evaluates the feasibility of using Surface Acoustic Wave (SAW) based Radio-Frequency Identification (RFID) technology to measure HMA temperatures via wireless sensors during paving.
The survivability and temperature measurement capabilities of the SAW RFID sensors are demonstrated in the field. The measured asphalt cooling curves (temperature versus time) are compared with predictions from previously developed theoretical models for mat cooling. The prediction accuracy of these models is improved via a field calibration procedure using measured temperatures from the SAW RFID sensors. The predictions from the calibrated theoretical model are reasonable and agree well with the measured temperatures in the field.
Author:- Pfeiffer, Grant Howard