Date of Award
Spring 2025
Project Type
Dissertation
Program or Major
Civil Engineering
Degree Name
Doctor of Philosophy
First Advisor
Jo E Sias
Second Advisor
Fei Han
Third Advisor
Kyle Hoegh
Abstract
Achieving proper asphalt concrete pavement density, through combination of rigorous field and laboratory practices, is one of the top priorities of state agencies and contractors due to its significant impact on pavement performance and longevity. The field and laboratory traditional methods have limitations and pose challenges in terms of equipment and measurements which can influence the accuracy and efficiency of pavement density evaluation. In the field, various methods such as field coring, nuclear and non-nuclear density gauges are costly, time-consuming and only provide limited coverage of density assessment. In the lab, methods for evaluating the bulk specific gravity (Gmb) of gyratory-compacted asphalt specimens, such as saturated surface dry (SSD) and Corelok vacuum sealing, require multiple pieces of equipment and multiple measurements. Not to mention, the utilized methods also differ based on the porosity of asphalt mixtures or the absorptive properties of aggregates. Ground penetrating radar (GPR) based systems, such as Density Profiling System (DPS) and Laboratory Dielectric Measurement System (LDMS), have been studied and utilized for more accurate and efficient pavement density evaluation in the field and laboratory respectively. However, there lack established protocols for conducting DPS and LDMS based on measurement repeatability and reliability which translate to accurate dielectric-to-density conversion. This research used a combination of in-situ testing of DPS and laboratory testing of LDMS to develop protocols for conducting field and laboratory dielectric measurement respectively. The developed protocols for conducting DPS and LDMS involve evaluation of equipment performance and utilization of various data collection patterns to collect repeatable and reliable dielectric measurements for more accurate and efficient pavement density evaluation. The research also focused on developing a prediction model for evaluating Gmb of dense-graded asphalt specimens by incorporating various mixture properties including gradation, geology, binder content and most importantly, dielectric measurements collected using LDMS. Rigorous regression analysis and machine learning approaches were employed to develop the model.
Recommended Citation
Tran, Anh, "Analysis and Procedures for Conducting Laboratory and Field Dielectric Measurements for Asphalt Pavement Density Evaluation" (2025). Doctoral Dissertations. 2882.
https://scholars.unh.edu/dissertation/2882