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REPORT
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Publication Number:  FHWA-HRT-14-061    Date:  August 2014
Publication Number: FHWA-HRT-14-061
Date: August 2014

 

Radio Frequency Identification Applications in Pavements

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FOREWORD

This document presents the results of evaluations of radio frequency identification (RFID) for a set of pavement applications: tracking of placement of truckloads of hot mix asphalt (HMA) in the pavement, tracking of placement of truckloads of Portland cement concrete (PCC) in the pavement, real-time measurement of pavement temperature versus depth and time during intelligent compaction, early detection of reflection cracking in overlays, and guidelines for integration of material property data from construction and pavement performance data during service via RFID-assisted geolocation. RFID tracking of HMA placement was the most successful application and the one with potential for immediate commercial implementation. RFID tracking of PCC placement was unsuccessful, at least with the RFID systems evaluated in this study; the high dielectric constant of the hydrated cement paste severely attenuates the RFID signals. Real-time measurement of pavement temperatures with depth and time during intelligent compaction shows promise, but further work is required to develop faster and more reliable reader software/hardware and RFID tags. Laboratory and limited field evaluation of an RFID-based sensor for early detection of reflection cracks in HMA overlays also shows promise, but additional development work and field trials are required. The guidelines for data integration outline in generic terms the necessary steps to integrate RFID-tagged material property data collected during construction with pavement management system data collected during service; implementation details will be dependent on the materials and pavement systems used by each individual agency. The intended audience for this report is transportation engineers involved in pavement construction, quality acceptance testing for paving materials, pavement design, and pavement management.

Jorge E. Pagán-Ortiz
Director, Office of Infrastructure
Research and Development

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The U.S. Government assumes no liability for the use of the information contained in this document.

The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers' names appear in this report only because they are considered essential to the objective of the document.

Quality Assurance Statement

The Federal Highway Administration (FHWA) provides high-quality information to serve Government, industry, and the public in a manner that promotes public understanding. Standards and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically reviews quality issues and adjusts its programs and processes to ensure continuous quality improvement

 

 

Technical Report Documentation Page

1. Report No.

FHWA-HRT-14-061

2. Government Accession No. 3 Recipient's Catalog No.
4. Title and Subtitle

Radio Frequency Identification Applications in Pavements

5. Report Date

August 2014

6. Performing Organization Code
7. Author(s)

Charles W. Schwartz, Junaid S. Khan, Grant H. Pfeiffer, Endri Mustafa

8. Performing Organization Report No.

 

9. Performing Organization Name and Address

University of Maryland-College Park
Department of Civil and Environmental Engineering
1173 Glenn L. Martin Hall
College Park, MD 20742

10. Work Unit No. (TRAIS)

11. Contract or Grant No.

DTFH61-06-D-00036

12. Sponsoring Agency Name and Address

Office of Infrastructure Research and Development
Federal Highway Administration
6300 Georgetown Pike
McLean, VA 22101-2296

13. Type of Report and Period Covered

Final Report, September 2006-July 2013

14. Sponsoring Agency Code

 

15. Supplementary Notes

The Contracting Officer's Technical Representative (COTR) was Katherine Petros.

16. Abstract

Radio frequency identification (RFID) technology is widely used for inventory control, tool and material tracking, and other similar applications where line-of-sight optical bar codes are inconvenient or impractical. Several applications of RFID technology to pavements are evaluated in this report: tracking of placement of truckloads of hot mix asphalt (HMA) within the pavement, tracking of placement of truckloads of Portland cement concrete (PCC) within the pavement, real-time measurement of pavement temperature versus depth and time during intelligent compaction, and early detection of reflection cracking in overlays. RFID tracking of HMA placement was the most successful application and the one with potential for immediate commercial implementation. RFID tracking of PCC placement was unsuccessful, at least with the RFID systems evaluated in this study; the high dielectric constant of the hydrated cement paste severely attenuates the RFID signals. Real-time measurement of pavement temperatures with depth and time during intelligent compaction shows promise but further work is required to develop reader software/hardware and RFID tags with more reliable and faster response rates. Laboratory and limited field evaluation of an RFID-based sensor for early detection of reflection cracks in HMA overlays also shows promise, but additional development work and field trials are required. Guidelines for integration of material property data from construction and pavement performance data during service via RFID-assisted geolocation are also provided. The necessary steps required to integrate RFID-tagged material property and pavement management data are outlined in generic terms. Implementation details will depend on the materials and pavement systems used by each individual agency.

17. Key Words

Radio frequency identification; pavement instrumentation; pavement construction; materials management; pavement management; intelligent compaction; reflection cracking

18. Distribution Statement

No restrictions. This document is available to the public through NTIS:
National Technical Information Service
5301 Shawnee Road
Alexandria, VA 22312

19. Security Classification
(of this report)

Unclassified

20. Security Classification
(of this page)

Unclassified

21. No. of Pages

208

22. Price
Form DOT F 1700.7 Reproduction of completed page authorized

SI* (Modern Metric) Conversion Factors

ADDITIONAL CONTENT OR TABLE OF CONTENTS IF REQUIRED

LIST OF FIGURES

Figure 1. Equation. Definition of relative permittivity or dielectric constant .
Figure 2. Equation. Electric field E.
Figure 3. Equation. Displacement vector D.
Figure 4. Equation. Complex relative permittivity (dielectric constant).
Figure 5. Equation. Relationship between imaginary portion of complex dielectric constant and electrical conductivity.
Figure 6. Photo. Voids between epoxy and CPVC pipe wall after filling at room temperature.
Figure 7. Photo. Air bubbles at ends of epoxy filler after room temperature curing.
Figure 8. Photo. Extrusion of epoxy from end of pipe after oven curing.
Figure 9. Photo. Bulge in sidewall of encapsulated tag after oven curing.
Figure 10. Photo. Post-mortem examination of tags retrieved from compacted HMA with bulges in encapsulated tags circled.
Figure 11. Diagram. Read range for flat Alien® 2x2 tags in air with tags oriented parallel to reader antenna.
Figure 12. Diagram. Read range for curled Alien® 2x2 tags in CPVC pipe before encapsulation and curing with tags oriented in horizontal direction.
Figure 13. Diagram. Read range for curled Alien® 2x2 tags in CPVC pipe before encapsulation and curing with tags oriented in vertical direction.
Figure 14. Diagram. Read range for curled Alien® 2x2 tags in CPVC pipe after encapsulation and curing with tags oriented in horizontal direction.
Figure 15. Diagram. Read range for curled Alien® 2x2 tags in CPVC pipe after encapsulation and curing with tags oriented in vertical direction.
Figure 16. Drawing. Orientation options for RFID tags inside CPVC pipe molds (axis of CPVC pipe mold is vertical in all drawings).
Figure 17. Diagram. Read performance for sample 7 as evaluated using standardized laboratory procedure.
Figure 18. Diagram. Read performance for sample 8 as evaluated using standardized laboratory procedure.
Figure 19. Diagram. Read range for curled Alien® 2x2 tags in CPVC pipe after HMA oven heating and gyratory compaction.
Figure 20. Map. Location of UMD parking lot paving projects.
Figure 21. Map. Location of Hampstead Bypass project.
Figure 22. Photo. Location of pre-placed RFID tags in UMD Lot XX1.
Figure 23. Photo. Pre-placement of tags at UMD Lot XX1 paving project.
Figure 24. Photo. Paving over pre-placed encapsulated tags.
Figure 25. Photo. Encapsulated tag beneath paver.
Figure 26. Photo. Hand cart for reading RFID tags in UMD parking lots with antenna in the lower position (10 inches above pavement surface).
Figure 27. Chart. Summary of read success rates for tags in Parking Lot EE.
Figure 28. Photo. Examples of surfaced RFID tags in Lot EE.
Figure 29. Photo. Worst-case example of surfaced RFID tag in Lot EE.
Figure 30. Map. Location of Hampstead Bypass project with star marking approximate location of southern entrance to construction site.
Figure 31. Drawing. UPM Raflatac® RFID tag.
Figure 32. Photo. Hampstead Bypass project site.
Figure 33. Photo. Magnified view of study area at the Hampstead Bypass project site (boxed area in figure 32).
Figure 34. Photo. Vehicle-mounted antennae and RFID reader.
Figure 35. Chart. Percentage of UPM Raflatac® tags read in each truck versus height of antennae (Hampstead Bypass, November 2007).
Figure 36. Chart. Percentage of Alien® 2x2 tags read in each truck versus height of antennae (Hampstead Bypass, November 2007).
Figure 37. Chart. Overall read success rate for lower base lift at Hampstead Bypass (November 2007).
Figure 38. Photo. RoadTec® SB-2500D material transfer vehicle used in April 2008 paving at the Hampstead Bypass project.
Figure 39. Chart. Delivery and read locations for RFID tags paved into the upper base lift at the Hampstead Bypass (April 2008).
Figure 40. Chart. Influence of antennae orientation on read success rate.
Figure 41. Graph. Influence of vehicle speed on read success rate.
Figure 42. Photo. Location of permeability and density tests at parking Lot EE at UMD.
Figure 43. Photo. Troxler® Model 3440 nuclear density gauge.
Figure 44. Diagram. Location of tests relative to tag.
Figure 45. Graph. Density as a function of radial distance for tag 1 (slope=0.12).
Figure 46. Graph. Density as a function of radial distance for tag 2 (slope=0.04).
Figure 47. Graph. Density as a function of radial distance for tag 3 (slope=0.18).
Figure 48. Graph. Density as a function of radial distance for tag 4 (slope=0.11).
Figure 49. Graph. Density as a function of radial distance for tag 5 (slope=0.04).
Figure 50. Graph. Density as a function of radial distance for tag 6 (slope=0.03).
Figure 51. Graph. Density as a function of radial distance for tag 7 (slope=0.08).
Figure 52. Photo. In-place permeability test setup.
Figure 53. Equation. Permeability determination from falling head permeability test.
Figure 54. Chart. Coefficient of permeability on top of the tags and at random locations.
Figure 55. Photo. Location on the Syracuse project where the RFID tags were embedded.
Figure 56. Photo. Finished concrete pavement.
Figure 57. Photo. Antenna configuration.
Figure 58. Photo. Tags located 8 inches (200 mm) from the bottom and 4 inches (100 mm) from the sides.
Figure 59. Photo. Tags located 12 inches (300 mm) from the bottom and 12 inches (300 mm) from the sides.
Figure 60. Photo. Tags located 8 inches (200 mm) from the top and 8 inches (200 mm) from the sides.
Figure 61. Photo. Box filled with aggregate and 12 RFID tags.
Figure 62. Chart. Average read range of four sides of the box for the RFID tags embedded in coarse aggregate.
Figure 63. Drawing. Cross section of an HMA overlay indicating directional flow of thermal energy.
Figure 64. Equation. Differential equation for transient heat flow.
Figure 65. Equation. Definition of thermal diffusivity.
Figure 66. Drawing. Typical incremental elements of HMA overlay used in numerical solution.
Figure 67. Equation. Finite difference approximation to heat balance equation.
Figure 68. Equation. Equation for Ti,j+1.
Figure 69. Equation. Energy balance equation for convective and radiation heat losses at pavement surface.
Figure 70. Equation. Definition of Biot number.
Figure 71. Equation. Modified version of finite difference energy balance for heat flows at surface of mat.
Figure 72. Equation. Modified equation for Tn,j+1 at mat surface.
Figure 73. Equation. Relationship for forced convection.
Figure 74. Equation. Relationship for estimating solar heat flux.
Figure 75. Photo. Unencapsulated RFID tags (left: single patch, right: monopole).
Figure 76. Photo. Encapsulated RFID tags before finish sanding (left: single patch, right: monopole).
Figure 77. Diagram. Unencapsulated single patch tag, linear polarization.
Figure 78. Diagram. Unencapsulated single patch tag, circular polarization.
Figure 79. Diagram. Unencapsulated monopole tag, linear polarization.
Figure 80. Diagram. Unencapsulated monopole tag, circular polarization.
Figure 81. Diagram. Encapsulated single patch tag, linear polarization.
Figure 82. Diagram. Encapsulated single patch tag, circular polarization.
Figure 83. Diagram. Encapsulated monopole tag, linear polarization.
Figure 84. Diagram. Encapsulated monopole tag, circular polarization.
Figure 85. Drawing. Orientation guide for tags within asphalt specimens.
Figure 86. Drawing. Rotation scheme for tags within asphalt specimens (monopole and single patch).
Figure 87. Graph. Orientation #1 for monopole tag using circular polarization.
Figure 88. Graph. Orientation #1 for single patch tag using circular polarization.
Figure 89. Drawing. Thermal testing apparatus.
Figure 90. Graph. Thermal response from tag 0A21 using hot aggregate.
Figure 91. Graph. Thermal response from tag 0443 using hot aggregate.
Figure 92. Graph. Thermal response from tag 09FE using hot aggregate.
Figure 93. Graph. Thermal response from tag 0A21 using hot HMA.
Figure 94. Graph. Thermal response from tag 0443 using hot HMA.
Figure 95. Graph. Thermal response from tag 09FE using hot HMA.
Figure 96. Map. Approximate location of project site.(24)
Figure 97. Drawing. Plan view of test section.
Figure 98. Drawing. Detailed plan view of a single group of SAW RFID tags.
Figure 99. Photo. Placement of SAW RFID tags on surface of existing milled pavement.
Figure 100. Photo. Paving operation and test setup during construction.
Figure 101. Graph. Temperature versus time at bottom of mat (cross section B-E-G-I).
Figure 102. Graph. Temperature versus time at middle of mat (cross section B-E-G-I).
Figure 103. Graph. Temperature versus time at surface of mat (cross section B-E-G-I).
Figure 104. Graph. Temperature versus time segregated by location (cross section B-E-G-I).
Figure 105. Graph. Temperature versus time averaged across depth (cross section B-E-G-I).
Figure 106. Equation. Exponential cooling equation at cross section B-E-G-I.
Figure 107. Equation. Exponential cooling equation at cross section A-D-F-H.
Figure 108. Graph. Comparison of temperatures by tag type (cross section A-D-F-H, bottom of mat).
Figure 109. Graph. Comparison of temperatures by tag type (cross section B-E-G-I, bottom of mat).
Figure 110. Graph. Surface temperatures measured by SAW RFID tags versus Fluke® infrared thermometer.
Figure 111. Equation. Stability requirement for Euler time integration algorithm.
Figure 112. Graph. Finite difference solutions for bottom, middle, and surface of mat.
Figure 113. Graph. Cooling trends at the bottom and surface of the asphalt mat.
Figure 114. Graph. Base material temperatures cooling over time due to conductive heat transfer.
Figure 115. Graph. Impact of lower boundary depth on average predicted temperature profile.
Figure 116. Graph. Predicted versus measured temperatures at cross section A-D-F-H.
Figure 117. Graph. Predicted versus measured temperatures at cross section B-E-G-I.
Figure 118. Graph. Predicted versus measured surface temperatures.
Figure 119. Graph. Average measured versus predicted mat cooling at cross section  A-D-F-H.
Figure 120. Graph. Average measured versus predicted mat cooling at cross section B-E-G-I.
Figure 121. Graph. Average measured versus average predicted mat cooling.
Figure 122. Graph. Measured curves compared with calculated average curve with 175 °F line.
Figure 123. Graph. Sensitivity analysis for thermal diffusivity.
Figure 124. Graph. Sensitivity analysis for thermal conductivity.
Figure 125. Graph. Sensitivity analysis for the convective heat transfer coefficient.
Figure 126. Graph. Sensitivity analysis for emissivity.
Figure 127. Graph. Comparing both sets of optimized input parameters for the mat cooling model.
Figure 128. Drawing. Horizontal and vertical movement of concrete slabs causing Mode I and Mode II cracking.
Figure 129. Equation. Paris's Law for crack growth.
Figure 130. Photo. RFID tag AD-223.
Figure 131. Photo. RFID chip with 0.075 inches (2 mm) of antenna on each side.
Figure 132. Photo. One-wavelength loop antenna.
Figure 133. Photo. Two-wavelength loop antenna.
Figure 134. Photo. Three-wavelength loop antenna.
Figure 135. Equation. Wavelength calculation.
Figure 136. Photo. Dipole carbon paint antenna.
Figure 137. Photo. Silver dipole antenna with one side snipped at 0.8 inches (20 mm).
Figure 138. Photo. C-shaped silver dipole antenna.
Figure 139. Photo. Silver and carbon dipole antenna.
Figure 140. Drawing. Beam dimensions for the four-point bending test.
Figure 141. Photo. Thin film test setup.
Figure 142. Photo. Painted Aquadag® E™ on the two abutting PMMA sheets.
Figure 143. Photo. Painted dipole tag on one side and painted Aquadag® E™ only on other side of the polycarbonate sheet.
Figure 144. Drawing. Dogbone specimen dimensions.
Figure 145. Photo. Direct tension test setup.
Figure 146. Photo. Direct tension test specimen attachment.
Figure 147. Photo. Conductive paint on the dogbone specimen.
Figure 148. Photo. Read range tests in parking lot E.
Figure 149. Photo. Symmetric dipole used in the read range study.
Figure 150. Graph. Read range for the symmetric dipole in each direction connected and disconnected.
Figure 151. Photo. Asymmetric dipole used in the read range study.
Figure 152. Graph. Read range for tags disconnected and connected in the north direction.
Figure 153. Graph. Read range for tags disconnected and connected in the south direction.
Figure 154. Graph. Read range for tags disconnected and connected in the east direction.
Figure 155. Graph. Read range for tags disconnected and connected in the west direction.
Figure 156. Photo. Parts for encapsulating the RFID tag.
Figure 157. Photo. H-sensor for reflection crack detection.
Figure 158. Photo. Encapsulated tags placed in the roadway prior to paving.
Figure 159. Photo. Close-up view of one of the encapsulated tags.
Figure 160. Photo. Two H-sensors in the pavement prior to paving.
Figure 161. Photo. Paving in progress.
Figure 162. Photo. Read range test setup.
Figure 163. Photo. RFID tag glued to the asphalt beam.
Figure 164. Photo. Crack propagation when the RFID tag stopped reading.
Figure 165. Illustration. Referencing problem in linking pavement construction and pavement management data.
Figure 166. Screen Capture. Assign Sample Tests screen from SiteManager™ LIMS.
Figure 167. Screen Capture. Schematic for associating a single sample (Sample_ID=54321) with multiple test specimens/material properties (Microsoft® Access 2007): Samples, Tests, and Test_Sample_Link tables.
Figure 168. Screen Capture. Schematic for associating a single sample (Sample_ID=54321) with multiple test specimens/material properties (Microsoft® Access 2007): Query.
Figure 169. Screen Capture. Schematic for associating a single sample (Sample_ID=54321) with multiple test specimens/material properties (Microsoft® Access 2007): Query results.
Figure 170. Screen Capture. Schematic for associating multiple RFID tags with a single material sample (Sample_ID=54321) having multiple test specimens/material properties (Microsoft® Access 2007): Tag_Sample_Link table (see figure 169 for other tables in query).
Figure 171. Screen Capture. Schematic for associating multiple RFID tags with a single material sample (Sample_ID=54321) having multiple test specimens/material properties (Microsoft® Access 2007): Query.
Figure 172. Screen Capture. Schematic for associating multiple RFID tags with a single material sample (Sample_ID=54321) having multiple test specimens/material properties (Microsoft® Access 2007): Query results.
Figure 173. Screen Capture. MarylandWare example of direct entry of latitude and longitude location for a material sample (boxed area of screen).
Figure 174. Screen Capture. Schematic for associating multiple sets of GPS coordinates with a single material sample (Sample_ID=54321) having multiple test specimens: Tags table, augmented with GPS coordinates (see figure 167 and figure 170 for other tables in query).
Figure 175. Screen Capture. Schematic for associating multiple sets of GPS coordinates with a single material sample (Sample_ID=54321) having multiple test specimens: Query.
Figure 176. Screen Capture. Schematic for associating multiple sets of GPS coordinates with a single material sample (Sample_ID=54321) having multiple test specimens: Query results.
Figure 177. Screen Capture. Schematic for extracting MMS data along a portion of roadway (I-70 between milepoints 83 and 84): Tags table, augmented with milepoint data elements (see figure 167 and figure 170 for other tables in query).
Figure 178. Screen Capture. Schematic for extracting MMS data along a portion of roadway (I-70 between milepoints 83 and 84): Query.
Figure 179. Screen Capture. Schematic for extracting MMS data along a portion of roadway (I-70 between milepoints 83 and 84): Query results.
Figure 180. Screen Capture. Schematic for extracting PMS data along a portion of roadway (I-70 between milepoints 83 and 84): IRI table.
Figure 181. Screen Capture. Schematic for extracting PMS data along a portion of roadway (I-70 between milepoints 83 and 84): Query.
Figure 182. Screen Capture. Schematic for extracting PMS data along a portion of roadway (I-70 between milepoints 83 and 84): Query results.
Figure 183. Screen Capture. Roadware iVision charts screenshot.(29)
Figure 184. Graph. Roughness (IRI) from PMS and asphalt content from MMS along a specified section of roadway (I-70 between milepoints 83 and 84).

LIST OF TABLES

Table 1. Characteristics of different RFID technologies.
Table 2. Typical dielectric constant (relative permittivity) values for common materials.
Table 3. Candidate RFID tags (all passive).
Table 4. Maximum read range (ft) for Alien® 1x1 tags after 24-h oven cure at 248 °F (120 °C), cooling, then reheating for 1.5 h at 247 °F (175 °C).
Table 5. Maximum read range (ft) for Alien® 2x2 tags after 24-h oven cure at 248 °F (120 °C), cooling, then reheating for 1.5 h at 247 °F (175 °C).
Table 6. RFID tag identification in UMD Parking Lot XX1.
Table 7. Read success for RFID tags in UMD Parking Lot XX1.
Table 8. Log of tags in lower 4-inch (100-mm) base lift at Hampstead Bypass project (November 2007).
Table 9. Slopes of in-place density versus distance trend lines with and without data at r = 0.
Table 10. The t- and F-test results for in-place density tests.
Table 11. Read range for vertically positioned cylinders.
Table 12. Read range for horizontally positioned cylinders.
Table 13. Dielectric constants for various cement pastes (after Wen and Chung).
Table 14. Typical thermal property values.
Table 15. Typical values for thermal diffusivity.
Table 16. Typical values for thermal conductivity.
Table 17. Tags employed in thermal testing.
Table 18. Weather data recorded near the project site for July 22-23, 2009.
Table 19. Tag read rates.
Table 20. Temperature comparisons at bottom of mat.
Table 21. Temperature comparisons at top of mat.
Table 22. Input parameters used in models.
Table 23. Input parameters used in finite difference solution.
Table 24. Comparison of convective heat transfer coefficients.
Table 25. Results of Optimization #1-h constant.
Table 26. Results of Optimization #2-h optimized.
Table 27. Read range for the carbon paint loop antenna tags.
Table 28. Read range for the carbon dipole tag with one side shortened.
Table 29. Read range for the silver dipole antenna with one side fixed at 0.8 inches length while the other side is progressively shortened.
Table 30. Read range for the silver and carbon dipole antenna as one side is shortened.
Table 31. Description of the conductive paints tested to determine failure strains.
Table 32. Field test results.

LIST OF ACRONYMS AND ABBREVIATIONS

CMOD Crack Mouth Opening Displacement
CPVC Chlorinated Polyvinyl Chloride
DC Direct Current
FHWA Federal Highway Administration
GPS Global Positioning System
HMA Hot Mix Asphalt
ICT International Coding Technologies
IDT Interdigital Transducer
IRI International Roughness Index
LIMS Laboratory Inventory Management System
LTS Log Track System
MB Megabyte
MDSHA Maryland State Highway Administration
MMS Materials Management System
MTV Material Transfer Vehicle
NCAT National Center for Asphalt Technology
PCC Portland Cement Concrete
PDA Personal Digital Assistant
PDE Partial Differential Equation
PMMA Polymethyl Methacrylate
PMS Pavement Management System
QA Quality Assurance
QC Quality Control
RF Radio Frequency
RFID Radio Frequency Identification
SAW Surface Acoustic Wave
TFHRC Turner-Fairbanks Highway Research Center
UHF Ultrahigh Frequency
UMD University of Maryland
W/C Water-to-Cement

 

 

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