- Sponsor
- Department of Civil and Environmental Engineering
- Originating Calendar
- CEE Seminars and Conferences
Monitoring of Asphalt Concrete Construction Quality Using Ground-Penetrating Radar
Advisor: Professor Imad L. Al-Qadi
Abstract
Despite the consensus agreement on asphalt concrete (AC) density as an acceptance quality characteristic (AQC) across the US, quality control and acceptance practices such as coring remain highly labor-intensive, costly, localized, and limited to post-construction. These shortcomings often result in disputes between agencies and contractors, penalties for contractors, and premature pavement distresses and failures.
To overcome these challenges, a roller-mounted ground-penetrating radar (GPR) setup was proposed to continuously monitor the quality of AC during construction. The setup covers the entire AC mat and provides real-time feedback for the roller operator to take remedial actions while AC is still workable. An Illinois aggregate dielectric constant database was established to bypass mix-specific calibrations and allow real-time predictions of AC density. A prototype roller-mounted GPR was designed including both hardware and software components. The prototype was tailored to roller operators through minimizing visual obstruction and providing clear visualizations for timely decision-making (e.g., colored heatmaps and progression curves).
Application-specific interferences, including surface moisture from water nozzles, roller electromagnetic fields, AC temperature variations, and antenna overheating, were addressed. The surface-moisture correction, based on singular value decomposition (SVD), reduced compaction prediction error from 8.9% to 1.3%. The antenna-overheating correction, based on linear regression, reduced absolute compaction prediction errors by 1–5%. The roller-mounted GPR prototype and algorithms were verified on three field projects around Illinois with different contractors, mix designs, and site conditions. Roller-mounted GPR achieved an absolute error of 0.4% in compaction prediction compared point-to-point to core measurements.
A Markov decision process (MDP) was formulated to represent rolling patterns on an AC mat. The developed MDP was demonstrated for decision-support on a real project and indicated saving up to 40% in construction time and 2% in revenue when used for optimizing rolling pattern in real-time compared to an experienced operator. In addition, GPR coupled with an inertial measurement unit (IMU) was successfully applied to predict pavement roughness with a mean absolute error of 3.63% at low speeds comparable to commercial rollers.
The deployment of roller-mounted GPR for real-time quality control and decision-support underscores the cost, labor, and time savings of proactive AC quality monitoring for both contractors and agencies.