Doctoral Dissertations
Date of Award
12-2022
Degree Type
Dissertation
Degree Name
Doctor of Philosophy
Major
Civil Engineering
Major Professor
Baoshan Huang
Committee Members
Timothy Truster, Shuai Li, Xiaoyang Jia
Abstract
The Traffic Speed Deflectometer (TSD) overcomes the Falling Weight Deflectometer (FWD) limitations in terms of traffic interruption and testing inefficiency, which has been used for network-level pavement structural evaluation. However, some challenges exist as applying the TSD for routine survey works. This study proposed an effective temperature correction method to achieve the speed and temperature correction of TSD deflections simultaneously based on the time-temperature superposition principle. To match the existing FWD-based pavement structure number (SN) records, an enhanced AASHTO method was proposed for calibrating TSD-based SN by the asphalt thickness. In addition, this study discussed potential uses of TSD slopes in terms of replacing deflection indices, estimating the inflection point location, and calculating the deflection lag distance. The feasibility of estimating pavement fatigue conditions from TSD lag distance was also evaluated. Finally, this study proposed an autoencoder to extract crack features and performed structure classification based on pavement crack images. Results from the present analyses suggest that TSD deflections are more sensitive to test temperatures than to test speeds. For normal TSD operating speeds, a 10 mph increase in test speed is approximately equivalent to a 1°C drop in temperature. The difference in AASHTO SN between TSD and FWD essentially came from the difference in the equivalent loading frequency, and the asphalt layer exhibited lower stiffness under TSD than under FWD. The lag distance can be used as an implicit indicator of the fatigue condition of the pavement to predict the initiation and growth of fatigue cracks. Fatigue cracking is expected to occur where the lag distance is relatively large. For crack images with more than 20% cracks, longitudinal cracks on wheel paths play the most important role in the structure classification, and their presence indicates potential pavement structural weakness.
Recommended Citation
Zhang, Miaomiao, "Network-level Pavement Evaluation Utilizing Traffic Speed Deflectometer. " PhD diss., University of Tennessee, 2022.
https://trace.tennessee.edu/utk_graddiss/11570
Included in
Civil Engineering Commons, Construction Engineering and Management Commons, Transportation Engineering Commons
