Pre-Implementation of Infrared and Ground-Penetrating Radar Technologies for Improving Asphalt Mixture Quality (2014) / Chapter Skim
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CONTENTS ABSTRACT EXECUTIVE SUMMARY Introduction Findings Conclusions Recommendations CHAPTER 1. BACKGROUND Problem Statement and Research Objective Scope of Study CHAPTER 2.
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AUTHOR ACKNOWLEDGMENTS The research reported herein was performed under the second Strategic Highway Research Program (SHRP 2) Project R06C by the Texas A&M Transportation Institute at Texas A&M University.
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ABSTRACT In this project, researchers performed pre-implementation of infrared (IR) and groundpenetrating radar (GPR)
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EXECUTIVE SUMMARY INTRODUCTION Placement of an asphalt mixture overlay remains a common practice for highway renewal activities. A new overlay can be used to extend a pavement's acceptable service with minimal disruption to the public due to the rapid nature of construction.
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GPR measurement occurs after all finish rolling and therefore measures the final in-place product. Based on promising initial results showing the utility of thermal profiling and GPR for evaluating asphalt mixture construction for density, uniformity, and segregation, SHRP 2 initiated a phase of work to conduct pilot projects with two departments of transportation (DOTs)
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2.5 GHz system tailored for asphalt mixture evaluation provided stable readings, rapid results, and easy operation as compared to the 1 GHz system. With the radar systems, the pilot projects also revealed: • The 1 GHz system may be limited to lift thicknesses of around 1.5 inches or greater.
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Figure ES.1 effectively quantified and documented thermal segregation. With the advent of WMA, the impact of thermal segregation on warm mixes could warrant additional research.
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density measurement system to detect and help eliminate segregation. The radar system developed during this project worked well to evaluate asphalt mixture density and uniformity.
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Figure ES.2. GPR System for measuring asphalt mixture uniformity.
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Substantial support and interest in further developing the thermal profile and radar technologies exist within departments of transportation. Several additional DOTs volunteered projects to participate in this SHRP 2 project.
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CHAPTER 1 BACKGROUND PROBLEM STATEMENT AND RESEARCH OBJECTIVE In-place density is a critical factor in determining pavement durability in HMA. Localized nonuniform zones of mix, termed segregation, often become low-density areas in the mat.
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CHAPTER 2 RESEARCH APPROACH INTRODUCTION This project built on prior SHRP 2 R06C work by moving the project into a preimplementation phase, in which the research team used the IR and GPR technologies to coordinate and conduct pilot projects with two state DOTs. The pilot projects served to provide interested states with experience using IR and GPR for uniformity assessment of asphalt mixture construction and allowed the RO6C contractor to further refine the state of the practice.
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• Task 13: Develop data collection protocols, including test procedures, in AASHTO-formatted language for both NDT technologies. • Task 14: Conduct pilot testing in the two DOTs that were selected.
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CHAPTER 3 FINDINGS AND APPLICATIONS SUMMARY The pre-implementation work conducted in this SHRP 2 project showed both the thermal profile and ground-penetrating radar technologies with great potential to evaluate the uniformity of asphalt mixture paving. In this pre-implementation effort, the SHRP 2 contractor worked with the Virginia Department of Transportation (VDOT)
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(GSSI) provides an easily understood operator interface, real-time data processing, and efficient field reporting to rapidly evaluate uniformity and density.
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½ in.
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Thermal profiles were collected from 38.10079 N, 78.46164 W to 38.08718 N, 78.47087 W The thermal data showed cyclical patterns of truck-end thermal segregation, with temperature differentials typically between 40°F and 60°F.
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Figure 3.2. Thermal profile from US-29.
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Figure 3.2. Thermal profile from US-29 (continued)
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From the core results, Figure 3.3 presents the relationship observed between placement temperature and in-place density after all compaction operations. The relationship shows that a 50-degree drop in placement temperature is expected to result in about a 2.2% increase in air voids with this mix and this paving operation.
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and lab-determined air void content for the eight cores collected. The job mix formula (JMF)
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Table 3.4. Summary Air Void Statistics from GPR on US-29 Statistic 1 GHz Prototype 2.5 GHz Average 7.38 10.45 Standard Deviation 1.13 1.66 Min 4.29 3.78 Max 18.2 18.75 Using the large quantity of air void measurements, Figure 3.5 presents the expected statistical distribution of air voids in the test section from each radar system.
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. Figure 3.5.
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Figure 3.6. Shift in 2.5 GHz results during US-29 testing.
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With the known offsets of each GPR run, the radar data can also be presented as a contour plot. Figure 3.8 presents this plot for US-29 from the 1 GHz radar system.
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Figure 3.8. Geospatial distribution of air voids on US-29.
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Figure 3.8. Geospatial distribution of air voids on US-29 (continued)
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measuring and mapping the final density of the in-place mat. Both devices worked well for evaluating uniformity and showed: • Cyclical truck-end segregation existed, with temperature differentials typically between 40°F and 60°F.
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PILOT PROJECT ON ROUTE 3 On June 13, 2013, the SHRP 2 R06C research team conducted pilot implementation of thermal profiling and ground-penetrating radar on Route 3 in coordination with the Virginia Department of Transportation. This pilot implementation served to illustrate how these technologies could be used in quality control applications for evaluating a paving process and measuring the uniformity and density of the mat with near full-coverage testing.
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Paving Operation The contractor transported the mix in bobtail trucks, which offloaded into a Roadtec SB 1500D to transfer the mix into a Roadtec RP 190 paver. Figure 3.9 shows the paving train.
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was assigned at the start point of the test section. The temperatures measured with Pave-IR at subsequent core locations are also annotated in Figure 3.10 and presented in Table 3.6.
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Figure 3.10. Thermal profile from Route 3.
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placement temperatures. Figure 3.11 shows the Route 3 project had much less thermal variability than the project on US-29.
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core air void content. The JMF-reported Rice gravity of 2.673 g/cc was used in calculation of lab air voids.
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Using the calibrations in Figure 3.12, researchers predicted the in-place air void content at each measurement location in the three GPR runs, resulting in about 2200 points of air void estimation with the 1 GHz system and almost 4500 points of air void estimation with the prototype 2.5 GHz system. These predictions yielded the statistics in Table 3.8.
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. Figure 3.13.
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Figure 3.14. Geospatial distribution of air voids on Route 3 from 1 GHz GPR.
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Figure 3.15. Geospatial distribution of air voids on Route 3 from 2.5 GHz GPR.
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• Within the placement temperatures observed, the final in-place air voids did not seem sensitive to temperature. This could have resulted from the warm-mix technology employed, or it could be simply because significant thermal irregularities did not occur.
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GPR analysis. The research team also evaluated the project with a 1 GHz air-coupled GPR system for comparison.
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finish rolling. The contractor paved a 12 ft wide lane with a 4 ft wide inside shoulder for a total width of 16 ft.
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mean placement temperature generally is not as much a cause for concern as other types of thermal segregation patterns, such as truck-end segregation or random segregation. Figure 3.17.
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Figure 3.18. Thermal profile from last 1,000 ft of SR-220 placed 09/06/2013.
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GPR Survey Result On the morning of September 7, 2013, the TTI team collected GPR data at six different transverse offsets on the last 1,000 ft of the pull that was placed 1 day prior. The transverse offsets were at 2, 4, 6, 8, 10, and 14 ft from the outside mat edge, yielding five passes in the lane and one pass in the shoulder.
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shows the GPR-measured surface dielectric values (ε) , lab-determined air void content, transverse offset from the outside mat edge, and longitudinal distance from the start of the 1000 ft section for the cores collected.
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Figure 3.20. Calibration of air voids to GPR from SR-220.
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• Both GPR systems predicted a similar portion of the mat met PennDOT's desired compaction range of 3% to 8% air voids. The 1 GHz system estimated 77% met the target compaction, while the 2.5 GHz system estimated 80% met the target compaction.
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Since the data in Table 3.12 suggest that the new 2.5 GHz radar system provided good estimates of overlay thickness, Figure 3.22 illustrates the estimated thickness from the 2.5 GHz system along with the measured surface dielectric from the 1 GHz system and 2.5 GHz system for comparison. The data indicate the lowest dielectric areas from the 1 GHz system were generally located at the locations of lowest overlay thickness (around 1 inch thick)
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Figure 3.22. Lift thickness and surface dielectrics from SR-220.
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void content for this mixture was between 3% and 8%. Figure 3.23 shows about 80% of the total mat area met PennDOT's desired compaction and also shows that, when only the travel lane area was analyzed, about 92% of that lane's area met the desired compaction.
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shoulder area. Regarding the outside edge, the project team observed the roller spanning the longitudinal joint at times when rolling in this vicinity.
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Figure 3.24. Expected geospatial distribution of air voids on SR-220.
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Conclusions from SR-220 Pilot Project The data from SR-220 showed • Thermal uniformity was good. Although truck exchanges were visible in the thermal profile, temperature differentials rarely exceeded 30°F.
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• Many overlays currently constructed are thinner than 2 inches. The 2.5 GHz system is ideally suited to these types of overlays and can evaluate the surface uniformity without influence of lower layers.
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CHAPTER 4 CONCLUSIONS AND SUGGESTED RESEARCH CONCLUSIONS This SHRP 2 project piloted two nondestructive techniques for measuring uniformity and segregation in new asphalt mixture construction. Both technologies, thermal profiling and ground-penetrating radar, tested essentially 100% of the new surfaces and provided rapid feedback on the quality of construction.
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• The second-generation 2.5 GHz radar system significantly advanced the state of the practice for evaluating asphalt mixture construction. This system provides an easily understood operator interface, real-time data processing, and efficient field reporting to rapidly evaluate uniformity and density.
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SUGGESTED RESEARCH The findings from work conducted indicate the following topics exist for further exploration: • The influence of thermal segregation on WMA remains unclear. Work investigating the impact of thermal segregation on different WMA technologies and at different temperatures is needed.
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1.3. It is not the intent of this specification to relieve the supplier from the final responsibility to provide an appropriate product for the intended function, nor is it intended to specify all the design details.
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3.1.4. Real-time indices: the number and percentage of thermal profiles with moderate and severe thermal segregation and each thermal profile's actual temperature differential.
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4.2. Measuring Thermal Profile: The thermal profile shall be measured in a manner to obtain at least 12 measurement points across the mat width.
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4.4. Calibration: The equipment shall have built-in provisions to facilitate the calibration and verification of each infrared temperature sensor(s)
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the longitudinal distance to any test point. Optionally, the equipment may also report in station format.
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Operation selection. Data collection and management.
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clearly indicating their functions. The selection shall be provided via a touchscreen, keypad, computer keyboard, or other input device.
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Table A.1. ID and Data Collection Properties for Thermal Profile Projects Project Property Description Operator The name of the person who creates the project.
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rolling radius. Distance Sensor Rotation Can be set to left or right to indicate which side of the paver the distance sensor is mounted.
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5.3.4.3. Infrared Temperature Sensor Calibration: The operational computer software shall allow for calibration of the infrared temperature sensor(s)
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Automated thermal profile testing shall continue until the operator selects to stop data acquisition. On stopping data acquisition, the software shall provide a module to input the correct ending distance or station, should a distance sensor calibration error exist.
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8.6. Stroup-Gardiner, M., and Brown, E
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4.1.2. Distance traveled during the density assessment shall be measured using a DMI.
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Figure B.1. Example calibration for calculating air voids.
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Upper Operating Temperature (°C) Not Available Lower Storage Temperature (°C)
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which converts dielectric constant to porosity Table B.3. GPR Information Output at Each Longitudinal Measurement Location Item Description Longitudinal Distance Distance relative to longitudinal starting location (ft/m)
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Figure B.2. Example post-process density assessment summary screen.
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9. REFERENCES 9.1 Sebesta, S., Saarenketo, T., and Scullion, T
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9.7. Saarenketo, T., and Roimela, P
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