Air void content is one of the most important characteristics of in-place asphalt concrete, substantially affecting early deterioration and long term performance. Destructive measures at limited locations, such as coring, are typically conducted as part of the air-void content evaluation after the pavement has been fully constructed. In this paper, use of an air coupled step-frequency array system for nondestructive assessment of air-void variability is explored. The dielectric properties of the asphalt were determined from the asphalt surface reflection amplitude of all 21 adjacent transmitting and receiving pairs of the array and related to air void content through plotting of dielectric changes with core measured air void content. This approach is an extension of the procedure developed for a single bistatic antenna pair determining properties within top millimeters of the asphalt surface. While cores provide information concerning bulk properties across the depth, the proposed method with an array system provides an opportunity for increased lateral coverage. The case study demonstrated good repeatability and correspondence with core measured air void content. The array-based method improves the coverage and productivity of the measurements, making it an attractive alternative to current state-of-the-practice procedures

Asphalt pavement compaction quality control and quality assurance (QC/QA) are traditionally based on destructive drilled cores and/or nuclear gauge results, which both are spot measurements representing significantly less than 1 percent of the in-service pavement. Ground penetrating radar (GPR) is emerging as a tool that can be used for nondestructive continuous assessment of asphalt pavement compaction quality through measuring the pavement dielectric constant. Previous studies have established that asphalt pavement dielectric constant measurements are inversely proportional to the air void content for a given asphalt mixture. However, field cores are currently required to calibrate the measured dielectric constant to the pavement density. In this paper, a method is proposed to eliminate the need for field calibration cores by measuring the dielectric constant of asphalt specimens compacted to various air void contents. This can be accomplished with a superpave gyratory compactor (SGC), which is routinely used in the pavement industry to fabricate 6 in. (15.2 cm.) diameter specimens. However, this poses difficulties with the GPR antenna height, direct coupling, and the Fresnel zone in relation to the asphalt specimen dimension limitation. These challenges are overcome by employing a plastic spacer with a known dielectric constant between the SGC specimen and the antenna. The purpose of the spacer is to reduce GPR wave speed so that the signal reflected from the specimen is separated from the direct coupling effects at an antenna height where the Fresnel zone of the GPR is not affected by the specimen dimension. The specimen dielectric constant can then be measured using the reflection coefficient-based surface reflection method (SR) or the pulse velocity-based time-of-flight method (TOF). Also, The Hoegh–Dai model (HD model) is demonstrated to reasonably predict pavement density based on the results of field measurements and corresponding core validation, especially as compared to the conventional exponential model. Results are presented from multiple days of paving on one project, as well as a single paving day on a project with significantly different mix properties. The agreement between the HD model, coreless prediction, and field cores shows the promise for implementation of dielectric-based asphalt compaction evaluation without the need for destructive field core calibration.

Traditional measures of asphalt compaction rely primarily on random cores that only measure a small fraction of the pavement. Recently, the use of ground penetrating radar was indicated to be usable as a nondestructive means for the continuous assessment of asphalt compaction. A proposed Hoegh-Dai (HD) model has been successful in predicting air void content within typically achieved field compaction levels but has reduced accuracy at the extremes. This paper proposes an enhanced Minnesota DOT (MnDOT) model to address this issue. A method for assessing modeling quality is proposed to quantify the improvement of the MnDOT model. The procedure is based on the accuracy of fits when run through a Monte Carlo simulation. The developed procedure indicates that the MnDOT model has improved accuracy—with 0.74% air void variation at a dielectric of 4 compared with 3.83% for the HD fit. Additionally, the MnDOT model is more stable for replicate days of the same mix design and falls within the uncertainty of more of the field cores across several projects than the HD model.

Air void content is a crucial parameter affecting long term pavement performance. Ground penetrating radar (GPR) offers a nondestructive method of determining relative asphalt air void content cheaply, quickly, and over an entire project. Previous implementations of GPR for the determination of air void content, including demonstrations as part of a recent SHRP2 study, were mostly positive, but suggested the need for a testing protocol. To explore various survey methodologies, a large-scale case study was conducted on U.S. HWY 52 in Minnesota using the rolling density meter (RDM), a commercially available device developed specifically for air void analysis in asphalt pavements. The lessons learned from the SHRP2 studies and initial Minnesota pilot projects were used on a full coverage trial implementation. The full coverage trial allowed for determination of the potential of the technology for improved QA/QC and resulted in development of best practice recommendations. This paper illustrates information provided by the full coverage data and outlines recommendations related to survey coverage, data file standardization and organization, verification of location and GPR measurements, and a rigid core collection procedure. The application of these recommendations allow an RDM crew to collect valuable relative compaction data for real time feedback without interfering with paving operations or traffic closures. Additionally, core calibration can be performed after surveying to convert data to air void content and project data analysis can be used to determine the construction practices most crucial to achieving sufficient compaction.