Use of Radio Frequency Identification

Tags in Pavements 

PUBLICATION NO. FHWA-HRT-14-061 APRIL 2015

Research, Development, and Technology

Turner-Fairbank Highway Research Center

6300 Georgetown Pike

McLean, VA 22101-2296
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 RFIDbased 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 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. Realtime 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 Classif. (of this report)

Unclassified

20. Security Classif. (of this page)

Unclassified

21. No. of Pages

208

22. Price

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
SI* (MODERN METRIC) CONVERSION FACTORS 

APPROXIMATE CONVERSIONS TO SI UNITS

Symbol When You Know Multiply By To Find Symbol 

LENGTH

in inches 25.4 millimeters mm 

ft feet 0.305 meters m 

yd yards 0.914 meters m 

mi miles 1.61 kilometers km 

AREA 

in2 square inches 645.2 square millimeters mm2

ft2 square feet 0.093 square meters m2

yd2 square yard 0.836 square meters m2

ac acres 0.405 hectares ha

mi2 square miles 2.59 square kilometers km2

VOLUME 

fl oz fluid ounces 29.57 milliliters mL 

gal gallons 3.785 liters L 

ft3 cubic feet 0.028 cubic meters m3 

yd3 cubic yards 0.765 cubic meters m3 

NOTE: volumes greater than 1000 L shall be shown in m3

MASS oz ounces 28.35 grams g

lb pounds 0.454 kilograms kg

T short tons (2000 lb) 0.907 megagrams (or "metric ton") Mg (or "t") 

TEMPERATURE (exact degrees) o

F Fahrenheit 5 (F-32)/9 Celsius o

C 

or (F-32)/1.8 

ILLUMINATION 

fc foot-candles 10.76 lux lx

fl foot-Lamberts 3.426 candela/m2 cd/m2

FORCE and PRESSURE or STRESS 

lbf poundforce 4.45 newtons N 

lbf/in2 poundforce per square inch 6.89 kilopascals kPa 

APPROXIMATE CONVERSIONS FROM SI UNITS 

Symbol When You Know Multiply By To Find Symbol 

LENGTH mm millimeters 0.039 inches in 

m meters 3.28 feet ft 

m meters 1.09 yards yd 

km kilometers 0.621 miles mi 

AREA mm2 square millimeters 0.0016 square inches in2 

m2 square meters 10.764 square feet ft2 

m2 square meters 1.195 square yards yd2 

ha hectares 2.47 acres ac

km2 square kilometers 0.386 square miles mi2 

VOLUME 

mL milliliters 0.034 fluid ounces fl oz 

L liters 0.264 gallons gal 

m3 cubic meters 35.314 cubic feet ft3 

m3 cubic meters 1.307 cubic yards yd3 

MASS 

g grams 0.035 ounces oz

kg kilograms 2.202 pounds lb

Mg (or "t") megagrams (or "metric ton") 1.103 short tons (2000 lb) T 

TEMPERATURE (exact degrees) o

C Celsius 1.8C+32 Fahrenheit oF 

ILLUMINATION 

lx lux 0.0929 foot-candles fc 

cd/m2 candela/m2 0.2919 foot-Lamberts fl

FORCE and PRESSURE or STRESS 

N newtons 0.225 poundforce lbf 

kPa kilopascals 0.145 poundforce per square inch lbf/in2

*SI is the symbol for the International System of Units. Appropriate rounding should be made to comply with Section 4 of ASTM E380. 

(Revised March 2003)

ii
TABLE OF CONTENTS

EXECUTIVE SUMMARY ................................................................................................................. 1

PROJECT OBJECTIVES................................................................................................................1

RFID TECHNOLOGY.....................................................................................................................1

PRACTICAL APPLICATIONS OF RFID TECHNOLOGY ......................................................2

KEY FINDINGS ...............................................................................................................................2

RFID Tracking of HMA Placement................................................................................................2

RFID Tracking of PCC Placement..................................................................................................3

Pavement Temperature Measurement Using SAW RFID ..............................................................4

Reflection Crack Detection.............................................................................................................4

Guidance on Data Integration .........................................................................................................4

CONCLUSIONS AND RECOMMENDATIONS..........................................................................5

CHAPTER 1: INTRODUCTION....................................................................................................... 7

PROJECT OBJECTIVES................................................................................................................7

REPORT ORGANIZATION...........................................................................................................7

RFID TECHNOLOGIES IN THIS STUDY.................................................................................10

UHF RFID Technology.................................................................................................................10

SAW RFID Technology................................................................................................................10

CHAPTER 2: FEASIBILITY EVALUATION............................................................................... 13

LITERATURE REVIEW...............................................................................................................13

IDENTIFICATION OF APPROPRIATE RFID TECHNOLOGY ...........................................13

Preliminary Evaluations................................................................................................................14

RFID System.................................................................................................................................17

PROTOTYPE TAG DEVELOPMENT AND EVALUATION ..................................................19

Fabrication ....................................................................................................................................19

Evaluation of Read Range.............................................................................................................22

CONCLUSIONS FROM FEASIBILITY EVALUATION .........................................................31

CHAPTER 3: RFID TRACKING OF HMA PLACEMENT ........................................................ 33

INTRODUCTION...........................................................................................................................33

UMD PARKING LOT XX1 ...........................................................................................................35

UMD PARKING LOT EE .............................................................................................................40

UMD PARKING LOT T................................................................................................................42

HAMPSTEAD BYPASS/MD 30....................................................................................................42

November 2007 Paving.................................................................................................................46

April 2008 Paving .........................................................................................................................51

CONCLUSIONS .............................................................................................................................55

CHAPTER 4: EVALUATION OF SURFACED TAGS................................................................. 57

INTRODUCTION...........................................................................................................................57

DENSITY TESTING......................................................................................................................57

Methodology .................................................................................................................................57

Density Results .............................................................................................................................58

Conclusions Regarding In-Place Density......................................................................................64

iii
PERMEABILITY TESTING.........................................................................................................64

Methodology .................................................................................................................................64

Permeability Results......................................................................................................................65

Conclusions Regarding In-Place Permeability..............................................................................66

OVERALL CONCLUSIONS REGARDING SURFACED TAGS ............................................66

CHAPTER 5: RFID TRACKING OF PCC PLACEMENT.......................................................... 67

INTRODUCTION...........................................................................................................................67

LABORATORY EVALUATION..................................................................................................67

FIELD EVALUATION ..................................................................................................................68

Methodology .................................................................................................................................69

Field Test Results..........................................................................................................................71

FURTHER INVESTIGATIONS ...................................................................................................72

Laboratory Evaluation...................................................................................................................72

The Dielectric Constant of Cement Paste .....................................................................................75

CONCLUSIONS REGARDING PCC TRACKING ...................................................................77

CHAPTER 6: PAVEMENT TEMPERATURE MEASUREMENT USING SAW RFID .......... 79

INTRODUCTION...........................................................................................................................79

PREVIOUS WORK........................................................................................................................80

Heat Flow Formulations................................................................................................................80

Thermal Property Values..............................................................................................................85

LABORATORY EVALUATION OF SAW RFID TAGS...........................................................86

Tag Encapsulation.........................................................................................................................86

Signal Strength and Readability....................................................................................................87

Thermal Sensitivity.......................................................................................................................95

FIELD EVALUATION ..................................................................................................................98

Site Information ............................................................................................................................99

Testing Procedure .......................................................................................................................100

Field Test Results........................................................................................................................103

Variability and Reliability...........................................................................................................107

Conclusions: Field Evaluation ....................................................................................................110

COMPARISONS BETWEEN PREDICTED AND MEASURED MAT COOLING.............111

Analysis Inputs............................................................................................................................112

Conclusions: Comparisons Between Predicted and Measured Mat Cooling ..............................119

SENSITIVITY ANALYSIS AND CALIBRATION TECHNIQUES.......................................119

Thermal Diffusivity and Conductivity........................................................................................120

Convective Heat Transfer Coefficient.........................................................................................121

Emissivity....................................................................................................................................122

Input Parameter Optimization Via Calibration ...........................................................................123

Conclusions: Sensitivity Analysis and Calibration Techniques..................................................125

OVERALL CONCLUSIONS AND LESSONS LEARNED REGARDING TEMPERATURE 

MEASUREMENT............................................................................................................125

Laboratory Evaluation.................................................................................................................126

Field Evaluation ..........................................................................................................................126

iv
Comparisons Between Measured and Predicted Mat Cooling Response....................................127

Sensitivity Analysis and Calibration Techniques........................................................................128

Lessons Learned..........................................................................................................................128

CHAPTER 7: EARLY DETECTION OF REFLECTION CRACKS........................................ 129

INTRODUCTION.........................................................................................................................129

CRACK DETECTION SENSOR DESIGN................................................................................131

Conductive Paint Antennae.........................................................................................................133

Antennae With Mechanical “Microswitch” ................................................................................147

PROTOTYPE DESIGN ...............................................................................................................152

Fabrication ..................................................................................................................................152

Field Survivability and Read Range ...........................................................................................153

Laboratory Evaluation.................................................................................................................157

CONCLUSIONS AND RECOMMENDATIONS FOR REFLECTION CRACK 

DETECTION....................................................................................................................159

Conclusions.................................................................................................................................159

Recommendations.......................................................................................................................160

CHAPTER 8: GUIDANCE ON DATA INTEGRATION............................................................ 161

INTRODUCTION.........................................................................................................................161

GUIDELINES FOR INTEGRATING MMS AND PMS DATABASES..................................163

Linkage of RFID Identifier to Material Samples........................................................................164

Linkage of GPS Coordinates to RFID Identifier/Material Sample .............................................168

Conversion of Latitude/Longitude to Roadway Location...........................................................170

Combining MMS and PMS Data by Location............................................................................171

Display of Extracted Data ...........................................................................................................173

DATA INTEGRATION SUMMARY .........................................................................................175

CHAPTER 9: CONCLUSIONS ..................................................................................................... 177

PROJECT OBJECTIVES............................................................................................................177

KEY FINDINGS ...........................................................................................................................177

RFID Tracking of HMA Placement............................................................................................177

RFID Tracking of PCC Placement..............................................................................................179

Pavement Temperature Measurement Using SAW RFID ..........................................................179

Reflection Crack Detection.........................................................................................................180

Guidance on Data Integration .....................................................................................................180

RECOMMENDATIONS FOR FUTURE WORK.....................................................................181

REFERENCES................................................................................................................................. 183

ANNOTATED BIBLIOGRAPHY.................................................................................................. 187

v
LIST OF FIGURES

Figure 1. Equation. Definition of relative permittivity or dielectric constant ..................... 15

Figure 2. Equation. Electric field E ........................................................................................ 15

Figure 3. Equation. Displacement vector D............................................................................ 15

Figure 4. Equation. Complex relative permittivity (dielectric constant). ............................... 15

Figure 5. Equation. Relationship between imaginary portion of complex dielectric 

constant and electrical conductivity.................................................................................. 16

Figure 6. Photo. Voids between epoxy and CPVC pipe wall after filling at room 

temperature ....................................................................................................................... 20

Figure 7. Photo. Air bubbles at ends of epoxy filler after room temperature curing.............. 20

Figure 8. Photo. Extrusion of epoxy from end of pipe after oven curing. .............................. 21

Figure 9. Photo. Bulge in sidewall of encapsulated tag after oven curing.............................. 21

Figure 10. Photo. Post-mortem examination of tags retrieved from compacted HMA 

with bulges in encapsulated tags circled........................................................................... 22

Figure 11. Diagram. Read range for flat Alien® 2x2 tags in air with tags oriented parallel 

to reader antenna ............................................................................................................... 24

Figure 12. Diagram. Read range for curled Alien® 2x2 tags in CPVC pipe before 

encapsulation and curing with tags oriented in horizontal direction. ............................... 24

Figure 13. Diagram. Read range for curled Alien® 2x2 tags in CPVC pipe before 

encapsulation and curing with tags oriented in vertical direction..................................... 25

Figure 14. Diagram. Read range for curled Alien® 2x2 tags in CPVC pipe after 

encapsulation and curing with tags oriented in horizontal direction. ............................... 26

Figure 15. Diagram. Read range for curled Alien® 2x2 tags in CPVC pipe after 

encapsulation and curing with tags oriented in vertical direction..................................... 26

Figure 16. Drawing. Orientation options for RFID tags inside CPVC pipe molds (axis of 

CPVC pipe mold is vertical in all drawings). ................................................................... 28

Figure 17. Diagram. Read performance for sample 7 as evaluated using standardized 

laboratory procedure. ........................................................................................................ 29

Figure 18. Diagram. Read performance for sample 8 as evaluated using standardized 

laboratory procedure. ........................................................................................................ 29

Figure 19. Diagram. Read range for curled Alien® 2x2 tags in CPVC pipe after HMA 

oven heating and gyratory compaction............................................................................. 31

Figure 20. Map. Location of UMD parking lot paving projects............................................. 34

Figure 21. Map. Location of Hampstead Bypass project........................................................ 35

Figure 22. Photo. Location of pre-placed RFID tags in UMD Lot XX1 ................................ 36

Figure 23. Photo. Pre-placement of tags at UMD Lot XX1 paving project ........................... 37

Figure 24. Photo. Paving over pre-placed encapsulated tags.................................................. 37

Figure 25. Photo. Encapsulated tag beneath paver ................................................................. 38

Figure 26. Photo. Hand cart for reading RFID tags in UMD parking lots with antenna in 

the lower position (10 inches above pavement surface). .................................................. 39

ε

vi
Figure 27. Chart. Summary of read success rates for tags in Parking Lot EE........................ 41

Figure 28. Photo. Examples of surfaced RFID tags in Lot EE............................................... 41

Figure 29. Photo. Worst-case example of surfaced RFID tag in Lot EE................................ 42

Figure 30. Map. Location of Hampstead Bypass project with star marking approximate 

location of southern entrance to construction site............................................................. 43

Figure 31. Drawing. UPM Raflatac® RFID tag. .................................................................... 44

Figure 32. Photo. Hampstead Bypass project site................................................................... 45

Figure 33. Photo. Magnified view of study area at the Hampstead Bypass project site 

(boxed area in figure 32)................................................................................................... 46

Figure 34. Photo. Vehicle-mounted antennae and RFID reader............................................. 49

Figure 35. Chart. Percentage of UPM Raflatac® tags read in each truck versus height of 

antennae (Hampstead Bypass, November 2007) .............................................................. 50

Figure 36. Chart. Percentage of Alien® 2x2 tags read in each truck versus height of 

antennae (Hampstead Bypass, November 2007) .............................................................. 51

Figure 37. Chart. Overall read success rate for lower base lift at Hampstead Bypass 

(November 2007).............................................................................................................. 51

Figure 38. Photo. RoadTec® SB-2500D material transfer vehicle used in April 2008 

paving at the Hampstead Bypass project .......................................................................... 52

Figure 39. Chart. Delivery and read locations for RFID tags paved into the upper base lift 

at the Hampstead Bypass (April 2008)............................................................................. 53

Figure 40. Chart. Influence of antennae orientation on read success rate. ............................. 54

Figure 41. Graph. Influence of vehicle speed on read success rate ........................................ 54

Figure 42. Photo. Location of permeability and density tests at parking Lot EE at UMD..... 57

Figure 43. Photo. Troxler® Model 3440 nuclear density gauge ............................................ 58

Figure 44. Diagram. Location of tests relative to tag ............................................................. 58

Figure 45. Graph. Density as a function of radial distance for tag 1 (slope=0.12)................. 60

Figure 46. Graph. Density as a function of radial distance for tag 2 (slope=0.04)................. 60

Figure 47. Graph. Density as a function of radial distance for tag 3 (slope=0.18)................. 61

Figure 48. Graph. Density as a function of radial distance for tag 4 (slope=0.11)................. 61

Figure 49. Graph. Density as a function of radial distance for tag 5 (slope=0.04)................. 62

Figure 50. Graph. Density as a function of radial distance for tag 6 (slope=0.03)................. 62

Figure 51. Graph. Density as a function of radial distance for tag 7 (slope=0.08)................. 63

Figure 52. Photo. In-place permeability test setup ................................................................. 65

Figure 53. Equation. Permeability determination from falling head permeability test .......... 65

Figure 54. Chart. Coefficient of permeability on top of the tags and at random locations..... 66

Figure 55. Photo. Location on the Syracuse project where the RFID tags were embedded... 69

Figure 56. Photo. Finished concrete pavement....................................................................... 70

Figure 57. Photo. Antenna configuration................................................................................ 70

Figure 58. Photo. Tags located 8 inches (200 mm) from the bottom and 4 inches 

(100 mm) from the sides................................................................................................... 73

vii
Figure 59. Photo. Tags located 12 inches (300 mm) from the bottom and 12 inches 

(300 mm) from the sides................................................................................................... 73

Figure 60. Photo. Tags located 8 inches (200 mm) from the top and 8 inches (200 mm) 

from the sides.................................................................................................................... 74

Figure 61. Photo. Box filled with aggregate and 12 RFID tags.............................................. 74

Figure 62. Chart. Average read range of four sides of the box for the RFID tags embedded 

in coarse aggregate............................................................................................................ 75

Figure 63. Drawing. Cross section of an HMA overlay indicating directional flow of 

thermal energy. ................................................................................................................. 80

Figure 64. Equation. Differential equation for transient heat flow......................................... 80

Figure 65. Equation. Definition of thermal diffusivity........................................................... 80

Figure 66. Drawing. Typical incremental elements of HMA overlay used in numerical 

solution.............................................................................................................................. 81

Figure 67. Equation. Finite difference approximation to heat balance equation.................... 81

Figure 68. Equation. Equation for Ti,j+1 .................................................................................. 82

Figure 69. Equation. Energy balance equation for convective and radiation heat losses at 

pavement surface. ............................................................................................................. 82

Figure 70. Equation. Definition of Biot number..................................................................... 82

Figure 71. Equation. Modified version of finite difference energy balance for heat flows 

at surface of mat................................................................................................................ 83

Figure 72. Equation. Modified equation for Tn,j+1 at mat surface ........................................... 83

Figure 73. Equation. Relationship for forced convection....................................................... 84

Figure 74. Equation. Relationship for estimating solar heat flux ........................................... 84

Figure 75. Photo. Unencapsulated RFID tags (left: single patch, right: monopole)............... 87

Figure 76. Photo. Encapsulated RFID tags before finish sanding (left: single patch, right: 

monopole) ......................................................................................................................... 87

Figure 77. Diagram. Unencapsulated single patch tag, linear polarization. ........................... 89

Figure 78. Diagram. Unencapsulated single patch tag, circular polarization. ........................ 89

Figure 79. Diagram. Unencapsulated monopole tag, linear polarization ............................... 89

Figure 80. Diagram. Unencapsulated monopole tag, circular polarization ............................ 90

Figure 81. Diagram. Encapsulated single patch tag, linear polarization. ............................... 91

Figure 82. Diagram. Encapsulated single patch tag, circular polarization ............................. 91

Figure 83. Diagram. Encapsulated monopole tag, linear polarization.................................... 91

Figure 84. Diagram. Encapsulated monopole tag, circular polarization................................. 92

Figure 85. Drawing. Orientation guide for tags within asphalt specimens............................. 93

Figure 86. Drawing. Rotation scheme for tags within asphalt specimens (monopole and 

single patch)...................................................................................................................... 93

Figure 87. Graph. Orientation #1 for monopole tag using circular polarization .................... 94

Figure 88. Graph. Orientation #1 for single patch tag using circular polarization ................. 94

Figure 89. Drawing. Thermal testing apparatus...................................................................... 95

viii
Figure 90. Graph. Thermal response from tag 0A21 using hot aggregate.............................. 96

Figure 91. Graph. Thermal response from tag 0443 using hot aggregate............................... 96

Figure 92. Graph. Thermal response from tag 09FE using hot aggregate.............................. 97

Figure 93. Graph. Thermal response from tag 0A21 using hot HMA.................................... 97

Figure 94. Graph. Thermal response from tag 0443 using hot HMA..................................... 98

Figure 95. Graph. Thermal response from tag 09FE using hot HMA .................................... 98

Figure 96. Map. Approximate location of project site............................................................ 99

Figure 97. Drawing. Plan view of test section...................................................................... 100

Figure 98. Drawing. Detailed plan view of a single group of SAW RFID tags................... 101

Figure 99. Photo. Placement of SAW RFID tags on surface of existing milled 

pavement......................................................................................................................... 102

Figure 100. Photo. Paving operation and test setup during construction.............................. 103

Figure 101. Graph. Temperature versus time at bottom of mat (cross section B-E-G-I) ..... 104

Figure 102. Graph. Temperature versus time at middle of mat (cross section B-E-G-I) ..... 105

Figure 103. Graph. Temperature versus time at surface of mat (cross section B-E-G-I)..... 105

Figure 104. Graph. Temperature versus time segregated by location (cross section 

B-E-G-I).......................................................................................................................... 106

Figure 105. Graph. Temperature versus time averaged across depth (cross section 

B-E-G-I).......................................................................................................................... 107

Figure 106. Equation. Exponential cooling equation at cross section B-E-G-I.................... 107

Figure 107. Equation. Exponential cooling equation at cross section A-D-F-H .................. 107

Figure 108. Graph. Comparison of temperatures by tag type (cross section A-D-F-H, 

bottom of mat)................................................................................................................. 108

Figure 109. Graph. Comparison of temperatures by tag type (cross section B-E-G-I, 

bottom of mat)................................................................................................................. 108

Figure 110. Graph. Surface temperatures measured by SAW RFID tags versus Fluke® 

infrared thermometer ...................................................................................................... 110

Figure 111. Equation. Stability requirement for Euler time integration algorithm. ............. 112

Figure 112. Graph. Finite difference solutions for bottom, middle, and surface of mat ...... 113

Figure 113. Graph. Cooling trends at the bottom and surface of the asphalt mat. ............... 114

Figure 114. Graph. Base material temperatures cooling over time due to conductive heat 

transfer. ........................................................................................................................... 114

Figure 115. Graph. Impact of lower boundary depth on average predicted temperature 

profile.............................................................................................................................. 115

Figure 116. Graph. Predicted versus measured temperatures at cross section A-D-F-H. .... 116

Figure 117. Graph. Predicted versus measured temperatures at cross section B-E-G-I. ...... 116

Figure 118. Graph. Predicted versus measured surface temperatures.................................. 116

Figure 119. Graph. Average measured versus predicted mat cooling at cross section 

A-D-F-H.......................................................................................................................... 117

ix
Figure 120. Graph. Average measured versus predicted mat cooling at cross section 

B-E-G-I. .......................................................................................................................... 117

Figure 121. Graph. Average measured versus average predicted mat cooling..................... 118

Figure 122. Graph. Measured curves compared with calculated average curve with 

175 °F line....................................................................................................................... 119

Figure 123. Graph. Sensitivity analysis for thermal diffusivity............................................ 121

Figure 124. Graph. Sensitivity analysis for thermal conductivity ........................................ 121

Figure 125. Graph. Sensitivity analysis for the convective heat transfer coefficient. .......... 122

Figure 126. Graph. Sensitivity analysis for emissivity......................................................... 123

Figure 127. Graph. Comparing both sets of optimized input parameters for the mat 

cooling model.................................................................................................................. 124

Figure 128. Drawing. Horizontal and vertical movement of concrete slabs causing 

Mode I and Mode II cracking. ........................................................................................ 129

Figure 129. Equation. Paris’s Law for crack growth............................................................ 130

Figure 130. Photo. RFID tag AD-223................................................................................... 132

Figure 131. Photo. RFID chip with 0.075 inches (2 mm) of antenna on each side .............. 132

Figure 132. Photo. One-wavelength loop antenna................................................................ 133

Figure 133. Photo. Two-wavelength loop antenna. .............................................................. 134

Figure 134. Photo. Three-wavelength loop antenna. ............................................................ 134

Figure 135. Equation. Wavelength calculation..................................................................... 134

Figure 136. Photo. Dipole carbon paint antenna................................................................... 135

Figure 137. Photo. Silver dipole antenna with one side snipped at 0.8 inches (20 mm)...... 137

Figure 138. Photo. C-shaped silver dipole antenna. ............................................................. 138

Figure 139. Photo. Silver and carbon dipole antenna. .......................................................... 139

Figure 140. Drawing. Beam dimensions for the four-point bending test. ............................ 141

Figure 141. Photo. Thin film test setup................................................................................. 142

Figure 142. Photo. Painted Aquadag® ETM on the two abutting PMMA sheets.................. 143

Figure 143. Photo. Painted dipole tag on one side and painted Aquadag® ETM only on 

other side of the polycarbonate sheet.............................................................................. 144

Figure 144. Drawing. Dogbone specimen dimensions......................................................... 145

Figure 145. Photo. Direct tension test setup. ........................................................................ 145

Figure 146. Photo. Direct tension test specimen attachment. ............................................... 146

Figure 147. Photo. Conductive paint on the dogbone specimen........................................... 146

Figure 148. Photo. Read range tests in parking lot E............................................................ 148

Figure 149. Photo. Symmetric dipole used in the read range study. .................................... 148

Figure 150. Graph. Read range for the symmetric dipole in each direction connected and 

disconnected.................................................................................................................... 149

Figure 151. Photo. Asymmetric dipole used in the read range study ................................... 150

Figure 152. Graph. Read range for tags disconnected and connected in the north 

direction. ......................................................................................................................... 150

x
Figure 153. Graph. Read range for tags disconnected and connected in the south 

direction .......................................................................................................................... 151

Figure 154. Graph. Read range for tags disconnected and connected in the east 

direction. ......................................................................................................................... 151

Figure 155. Graph. Read range for tags disconnected and connected in the west 

direction. ......................................................................................................................... 152

Figure 156. Photo. Parts for encapsulating the RFID tag ..................................................... 153

Figure 157. Photo. H-sensor for reflection crack detection .................................................. 153

Figure 158. Photo. Encapsulated tags placed in the roadway prior to paving. ..................... 154

Figure 159. Photo. Close-up view of one of the encapsulated tags. ..................................... 155

Figure 160. Photo. Two H-sensors in the pavement prior to paving .................................... 155

Figure 161. Photo. Paving in progress.................................................................................. 156

Figure 162. Photo. Read range test setup.............................................................................. 156

Figure 163. Photo. RFID tag glued to the asphalt beam....................................................... 158

Figure 164. Photo. Crack propagation when the RFID tag stopped reading. ....................... 159

Figure 165. Illustration. Referencing problem in linking pavement construction and 

pavement management data............................................................................................ 162

Figure 166. Screen Capture. Assign Sample Tests screen from SiteManagerTM LIMS. ...... 165

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....................................... 165

Figure 168. Screen Capture. Schematic for associating a single sample 

(Sample_ID=54321) with multiple test specimens/material properties (Microsoft® 

Access 2007): Query....................................................................................................... 166

Figure 169. Screen Capture. Schematic for associating a single sample 

(Sample_ID=54321) with multiple test specimens/material properties (Microsoft® 

Access 2007): Query results. .......................................................................................... 166

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). ..................................................................................................... 167

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................................................................. 167

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..................................................... 167

Figure 173. Screen Capture. MarylandWare example of direct entry of latitude and 

longitude location for a material sample (boxed area of screen).................................... 169

xi
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) ...................................................................................................... 169

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............................................................................................................................... 170

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. .................................................................................................................. 170

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)......................... 171

Figure 178. Screen Capture. Schematic for extracting MMS data along a portion of 

roadway (I-70 between milepoints 83 and 84): Query. .................................................. 171

Figure 179. Screen Capture. Schematic for extracting MMS data along a portion of 

roadway (I-70 between milepoints 83 and 84): Query results........................................ 172

Figure 180. Screen Capture. Schematic for extracting PMS data along a portion of 

roadway (I-70 between milepoints 83 and 84): IRI table. .............................................. 172

Figure 181. Screen Capture. Schematic for extracting PMS data along a portion of 

roadway (I-70 between milepoints 83 and 84): Query. .................................................. 173

Figure 182. Screen Capture. Schematic for extracting PMS data along a portion of 

roadway (I-70 between milepoints 83 and 84): Query results........................................ 173

Figure 183. Screen Capture. Roadware iVision charts screenshot ....................................... 174

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). .............................. 175

xii
LIST OF TABLES

Table 1. Characteristics of different RFID technologies........................................................ 14

Table 2. Typical dielectric constant (relative permittivity) values for common materials..... 17

Table 3. Candidate RFID tags (all passive) ............................................................................ 18

Table 4. Maximum read range (ft) for Alien® 1x1 tags after 24-h oven cure at 248 oF 

(120 °C), cooling, then reheating for 1.5 h at 247 °F (175 °C)......................................... 28

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)......................................... 28

Table 6. RFID tag identification in UMD Parking Lot XX1.................................................. 36

Table 7. Read success for RFID tags in UMD Parking Lot XX1........................................... 39

Table 8. Log of tags in lower 4-inch (100-mm) base lift at Hampstead Bypass project 

(November 2007).............................................................................................................. 48

Table 9. Slopes of in-place density versus distance trend lines with and without data 

at r = 0 ............................................................................................................................... 63

Table 10. The t- and F-test results for in-place density tests.................................................. 63

Table 11. Read range for vertically positioned cylinders....................................................... 68

Table 12. Read range for horizontally positioned cylinders................................................... 68

Table 13. Dielectric constants for various cement pastes (after Wen and Chung .................. 76

Table 14. Typical thermal property values............................................................................. 85

Table 15. Typical values for thermal diffusivity .................................................................... 85

Table 16. Typical values for thermal conductivity ................................................................. 86

Table 17. Tags employed in thermal testing........................................................................... 96

Table 18. Weather data recorded near the project site for July 22–23, 2009 ....................... 100

Table 19. Tag read rates........................................................................................................ 104

Table 20. Temperature comparisons at bottom of mat ......................................................... 109

Table 21. Temperature comparisons at top of mat ............................................................... 110

Table 22. Input parameters used in models .......................................................................... 112

Table 23. Input parameters used in finite difference solution .............................................. 113

Table 24. Comparison of convective heat transfer coefficients............................................ 122

Table 25. Results of Optimization #1—h constant............................................................... 124

Table 26. Results of Optimization #2—h optimized ............................................................ 124

Table 27. Read range for the carbon paint loop antenna tags............................................... 135

Table 28. Read range for the carbon dipole tag with one side shortened ............................. 136

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 ................................................... 138

Table 30. Read range for the silver and carbon dipole antenna as one side is shortened..... 140

Table 31. Description of the conductive paints tested to determine failure strains.............. 141

Table 32. Field test results.................................................................................................... 157

xiii
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

xiv
EXECUTIVE SUMMARY

PROJECT OBJECTIVES

The original objective of this project was to demonstrate that inexpensive expendable radio 

frequency identification (RFID) tags could be used to identify the spatial location along the 

pavement alignment of specific truckloads of hot mix asphalt (HMA) production. These tags are

placed in the truckload as it leaves the production plant, pass through the paver, and are

compacted into the finished mat. Cross-referencing these tags with Global Positioning System 

(GPS) latitude and longitude coordinates after construction allows spatial referencing of quality 

assurance (QA) material property data measured at the production plant, enabling linkage to 

other spatially referenced in-place test results and pavement management system (PMS)

pavement performance data. This use of the large QA and PMS datasets already collected by 

highway agencies will permit more robust analyses and insights into the relationships between 

HMA material properties and actual pavement performance.

Phases I and II of this project addressed the development of techniques for making the RFID tags 

sufficiently rugged to withstand the harsh thermal and mechanical conditions of HMA paving 

and for evaluating the survival and read performance of the tags after construction. Phase I 

focused on identifying feasible RFID devices for HMA tracking, identifying candidate projects 

for field testing, and formulating a field evaluation work plan. Phase II executed the work plan 

developed in Phase I.

During the Phase I and II work, some additional applications of RFID technologies to pavements 

were identified for evaluation:

• Evaluation of potential problems caused by surfaced tags.

• Exploration of surface acoustic wave (SAW) RFID technology for improved performance 

of small format tags.

• Demonstration of RFID tracking of placement of Portland cement concrete (PCC) loads 

in pavements.

• Provision of guidance to agencies on data integration.

The evaluation of these additional topics was the focus of the additional and final Phase III of the 

project.

This report documents all work done over all three phases of the project. 

RFID TECHNOLOGY

Two types of RFID technology were employed in this study: conventional passive ultrahigh 

frequency (UHF) RFID tags and the newer SAW RFID tags. The passive UHF RFID technology 

encodes a digital signature on a small microchip attached to a copper foil antenna—the RFID 

“tag.” This passive tag receives energy from UHF radio waves transmitted by a RFID “reader”; 

the tag harvests this incoming radio frequency (RF) energy to transmit its encoded digital 

1
signature back to the reader. These RFID tags, although small, can be read several yards away 

from the reader’s antenna. 

SAW RFID tag consists of an interdigital transducer (IDT) and a series of acoustic reflector traps 

etched into a piezoelectric substrate. The tag reader emits a radio wave pulse to the IDT that is 

converted piezoelectrically into a nanoscale acoustic wave. The wave travels past the reflectors 

to produce a unique pattern of reflected pulses. These travel back to the IDT, where they are 

piezoelectrically converted into an encoded electronic reply signal to the reader. The SAW chip 

operates in a purely passive mode and does not require supplementary direct current (DC) power 

(i.e., battery). The principal advantages of the SAW RFID technology for pavement construction 

include better inherent ruggedness, smaller formats, and longer read ranges for a given tag 

antenna size compared with conventional RFID. In addition, and most relevant to this study, 

SAW RFID technology is capable of wireless measurement of temperature via the perturbation 

of the return wave signal caused by the influence of thermal strains on the spacing of the acoustic 

reflectors.

PRACTICAL APPLICATIONS OF RFID TECHNOLOGY

RFID technology is widely used today for supply chain inventory management, security, 

equipment tracking, among other applications. However, in construction, RFID technology is 

primarily used for tracking equipment and materials. Specific RFID applications identified in the 

literature review include the following:

• Tracking of PCC test specimens.

• Maturity monitoring of in-place PCC.

• Tracking of construction materials at project site (e.g., fabricated pipe).

• Construction tool inventory/usage control/monitoring.

• Location identification of buried infrastructure (cables and pipes).

Several new applications of RFID technology to pavements were evaluated in this study: RFID 

tracking of HMA and PCC placement, measurement of pavement temperature with depth and 

time during intelligent compaction, and early detection of reflection cracks in HMA overlays.

KEY FINDINGS

Key findings of this work are summarized here, organized by the following topical areas:

• RFID tracking of HMA placement (chapters 2, 3, and 4).

• RFID tracking of PCC placement (chapter 5).

• Pavement temperature measurement using SAW RFID (chapter 6).

• Reflection crack detection (chapter 7).

• Guidance on data integration (chapter 8).

RFID Tracking of HMA Placement

The feasibility of using RFID tags to track HMA placement was evaluated via: 1) literature 

review, 2) identification of appropriate RFID technology, and 3) prototype tag development and 

2
evaluation. The feasibility evaluation identified UHF passive RFID technology as best suited to 

the hot mix asphalt paving application. After considerable research of available products, a 

ThingMagic Mercury® 5 RFID system and related hardware were acquired for use in this 

project. Suitable RFID tags were identified, and a feasible encapsulation system was developed 

that adequately protects the RFID tags from the temperatures and compaction stresses inherent in 

HMA transport and paving. An Alien® Gen 2 2x2 RFID tag curled and encapsulated in hightemperature epoxy inside a 3⁄4-inch (19-mm) nominal outside diameter chlorinated polyvinyl 

chloride (CPVC) pipe provided a hardened tag of appropriate size and adequate read range.

The encapsulated RFID tags were field tested to evaluate the following issues: survivability in 

real-world paving scenarios, read range under actual field conditions; required redundancy,

construction practicality issues, and construction quality issues. The encapsulated RFID tags 

were evaluated at three parking lot locations on the University of Maryland (UMD) campus and 

in two stages in a new pavement constructed by the Maryland State Highway Administration

(MDSHA). The field trials confirmed the very high survival rate of the encapsulated tags. Read 

success rates varied significantly with tag size and less significantly on other details such as 

antenna configuration and vehicle speed. The field trials consistently demonstrated that postconstruction read success rates of 60 to 80 percent or higher are achievable from a bumpermounted antenna array, even on a vehicle moving at traffic speeds.

It was observed during the HMA field trials that some of the encapsulated RFID tags “floated” to 

the surface of the compacted mat. This raised the possibility of a decrease in in-place compacted 

density or an increase in the in situ permeability or both in the local region around the tag. 

Extensive density and permeability testing was performed to evaluate these possibilities. No 

localized decrease in density, increase in permeability, or any detrimental effects of the surfaced 

tags were found. These findings confirm that the encapsulated RFID tags are a successful lowimpact and inexpensive technology for tracking placement of HMA in the roadway.

RFID Tracking of PCC Placement

The successful application of RFID tags to track placement of HMA immediately suggested the 

parallel use for PCC placement. Preliminary laboratory evaluation of the passive UHF RFID tags 

in concrete cylinders showed promise. The reconstruction of a section of I-90 near Syracuse,

NY, provided an opportunity for field evaluation. A large number of RFID tags similar to those 

used in the HMA application were placed in the PCC delivery trucks as they left the batch plant 

near the paving site. These tags were deposited with the PCC ahead of the slip form paver and 

incorporated into the concrete slabs. Unfortunately, on the return visit to the site about 1 month 

after paving, none of the tags could be read. The causes of this surprising and disappointing 

result were investigated in the laboratory. The most plausible explanation supported by the 

laboratory results is that the hydrated cement paste causes the cured concrete to have a very high 

dielectric constant. The penetration depth (i.e., read range) of the UHF RFID radio waves 

diminishes sharply as the dielectric constant increases. A different technology is therefore 

needed for the PCC tracking application.

3
Pavement Temperature Measurement Using SAW RFID 

SAW RFID technology has the intrinsic capability to measure thermal expansion and thus 

temperature. Real-time measurement of pavement temperature distributions is necessary to 

interpret the stiffness feedback data in intelligent compaction because the stiffness of HMA is 

extremely temperature dependent. The temperature measurement capability of SAW RFID was 

evaluated through laboratory and field testing. For the field testing, various configurations of 

SAW RFID tags were encapsulated in thermally conductive epoxy, attached with quick-set 

epoxy to the surface of a milled existing pavement, and then covered with a 1.5-inch (38-mm) 

thick compacted HMA overlay. Although limitations of the SAW RFID reader system made it 

difficult to measure the temperature versus time trends during the first few minutes after 

placement, mat temperatures were recorded starting at about 10 min after placement until the mat 

was too cool for continued compaction. The measured temperatures versus time compared 

favorably with predictions from analytical/numerical models, and an approach for using the 

SAW RFID field temperature measurements for calibrating these analytical/numerical models is 

proposed. Overall, the SAW RFID technology has potential for in situ temperature measurement 

in HMA pavement layers.

Reflection Crack Detection

Reflection cracking is a dominant distress in rehabilitation overlays. Early detection of these 

cracks before they reach the pavement surface can be important to highway agencies both for 

rehabilitation planning purposes and for enforcing construction contract warranties. The 

development of an early-onset reflection crack detector was originally intended as another 

application of the SAW RFID technology. However, it was subsequently determined that 

conventional RFID was a more appropriate technology choice, in part because of the current 

relatively high cost of SAW RFID tags. 

The reflection crack sensor concept is to implement a switch in the antenna circuit of the RFID 

tag: when there is no crack, the RFID tag signal can be read at a distance, but after a crack forms 

the signal becomes too weak to be read. A prototype reflection crack detector was developed and 

tested in the laboratory and, under more limited conditions, in the field. In the laboratory, the 

prototype detector was shown to be capable of detecting a reflection crack before it reached the 

pavement surface. The limited field trials also showed that the detector had the required 

survivability and read range for real-world applications. This approach shows considerable 

promise, but it will require additional and more rigorous field evaluation that was beyond the 

scope and resources of the present project.

Guidance on Data Integration

The motivation for this entire study was the application of RFID technology for tracking HMA 

placement. This is also the application that is most suited to near-term commercial 

implementation. The major benefit of this application is the integration of agency QA materials 

testing data with their pavement management database. This integration could provide insights 

into the relationships between good material properties and construction techniques and superior 

pavement performance. This integration could also permit much more powerful forensic 

investigations of poorly performing road sections by enabling easy and quick access to the 

4
associated material properties measured during construction. However, several steps are needed 

to effect this data integration, and given the wide range of materials and pavement management 

systems in use among the States, these steps will be slightly different for each agency. General 

guidelines are provided for the data integration steps that can be easily adapted to each agency’s 

specific databases and policies and procedures.

CONCLUSIONS AND RECOMMENDATIONS

RFID tracking of HMA placement was the most successful application in this study and the one 

with the most 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.

Recommendations for additional research and development include the following:

• Commercialization of the RFID system for tracking HMA placement. This research has 

demonstrated the success of the concept. However, it was impossible to generate 

commercial interest in it during the course of the project.

• Evaluation of other RFID systems (e.g., different frequency range, active instead of 

passive system) for use in tracking PCC placement. The high dielectric constant of the 

cement paste coating the aggregates in PCC makes it impossible to pass a sufficiently 

strong signal to/from the passive UHF RFID tags used so successfully for HMA tracking.

• Refinement of the techniques for temperature measurement using SAW RFID tags. More 

work is required to determine the minimum thickness of the epoxy coating to maximize 

tag readability and minimize thermal lag while still ensuring survivability. Additional 

work in collaboration with the SAW RFID system manufacturer is required to optimize 

the temperature window in the reader so that the early rapid cooling trends of the mat can 

be captured. Field trials should also be repeated on thicker HMA layers in which the 

variation of temperature with depth is more pronounced.

• Laboratory evaluation of the reflection crack detector should be conducted using a Texas 

Overlay Tester instead of three-point bending to better simulate how overlays fail. 

Through these tests, the crack mouth opening displacement (CMOD) as a function of 

vertical crack propagation can be determined more accurately and the crack detector 

design can be adjusted as needed. Laboratory evaluation should then be followed by field 

trials on in-service pavements. The duration of these field trials would need to be on the 

order of 5 to 10 years to allow sufficient time for reflection cracks to initiate and 

propagate.

5

CHAPTER 1: INTRODUCTION

PROJECT OBJECTIVES

The original objective of this project was to demonstrate that inexpensive expendable RFID tags

can be used to identify the spatial location along the pavement alignment of specific truckloads 

of HMA production. These tags are placed in the truckload as it leaves the production plant, pass 

through the paver, and are compacted into the finished mat. Cross-referencing these tags with 

GPS latitude and longitude coordinates after construction allows spatial referencing of QA

material property data measured at the production plant, enabling linkage to other spatially 

referenced in-place test results and PMS pavement performance data. This use of the large QA

and PMS datasets already collected by highway agencies will permit more robust analyses and 

insights into the relationships between HMA material properties and actual pavement 

performance.

Phases I and II of this project addressed the development of techniques for making the RFID tags 

sufficiently rugged to withstand the harsh thermal and mechanical conditions of HMA paving 

and for evaluating the survival and read performance of the tags after construction. Phase I 

focused on identifying feasible RFID devices for HMA tracking, identifying candidate projects 

for field testing, and formulating a field evaluation work plan. Phase II executed the work plan 

developed in Phase I. 

During the Phase I and II work, some additional applications of RFID technologies to pavements 

were identified for evaluation:

• Evaluation of potential problems caused by surfaced tags.

• Exploration of SAW RFID technology for improved performance of small format tags.

• Demonstration of RFID tracking of placement of PCC loads in pavements.

• Provision of guidance to agencies on data integration.

The evaluation of these additional topics was the objective of the additional and final Phase III of 

the project.

REPORT ORGANIZATION

This report documents the work and findings from all three phases of the project. The subsequent 

chapters, along with brief descriptions of the work in each and highlights of the findings, are 

described below. Each chapter is intended as standalone document of its respective work area.

Chapter 2: Feasibility Evaluation. The feasibility of using RFID tags to track HMA placement 

was evaluated via: 1) literature review, 2) identification of appropriate RFID technology, and 

3) prototype tag development and evaluation. The feasibility evaluation identified UHF passive 

RFID technology as best suited to the hot mix asphalt paving application. After considerable 

research of available products, a ThingMagic Mercury® 5 RFID system and related hardware 

were acquired for use in this project. Suitable RFID tags were identified and a feasible 

encapsulation system was developed that adequately protects the RFID tags from the 

temperatures and compaction stresses inherent in HMA transport and paving. An Alien® Gen 2 

7
2x2 RFID tag curled and encapsulated in high-temperature epoxy inside a 3⁄4-inch (19-mm) 

nominal outside diameter CPVC pipe provided a hardened tag of appropriate size for adequate 

read range.

Chapter 3: RFID Tracking of HMA Placement. The encapsulated RFID tags were field tested 

to evaluate the following issues: survivability in real-world paving scenarios, read range under 

actual field conditions, required redundancy (i.e., how many tags must be added to a truckload to 

locate the mix reliably along the pavement alignment; this is related to the survivability issue, but 

also includes delays in passing through the paver), construction practicality issues (e.g., do the 

tags interfere with normal paving operations), and construction quality issues (e.g., do the tags 

impair the quality of the compacted mat by inducing segregation or other defects). The 

encapsulated RFID tags were evaluated at three parking lot locations on the UMD campus and in 

two stages in a new pavement constructed by the MDSHA. The field trials confirmed the very 

high survival rate of the encapsulated tags. Read success rates varied significantly with tag size 

and less significantly on other details such as antenna configuration and vehicle speed. The field 

trials consistently demonstrated that post-construction read success rates of 60 to 80 percent or 

higher are achievable from a bumper-mounted antenna array, even on a vehicle moving at traffic 

speeds.

Chapter 4: Evaluation of Surfaced Tags. It was observed during the HMA field trials that 

some of the encapsulated RFID tags “floated” to the surface of the compacted mat. This raised 

the possibility of a decrease in in-place compacted density or an increase in the in situ

permeability or both in the local region around the tag. Extensive density and permeability 

testing was performed to evaluate these possibilities. No localized decrease in density, increase 

in permeability, or any detrimental effects of the surfaced tags were found. These findings 

confirm that the encapsulated RFID tags are a successful low-impact and inexpensive technology 

for tracking placement of HMA in the roadway.

Chapter 5: RFID Tracking of PCC Placement. The successful application of RFID tags to 

track placement of HMA immediately suggested the parallel use for PCC placement. The 

reconstruction of a section of I-90 near Syracuse, NY, provided an opportunity to evaluate this in 

the field. A large number of RFID tags similar to those used in the HMA application were placed 

in the PCC delivery trucks as they left the batch plant near the paving site. These tags were 

deposited with the PCC ahead of the slip form paver and incorporated into the concrete slabs. 

Unfortunately, on the return visit to the site about 1 month after paving, none of the tags could be 

read. The causes of this surprising and disappointing result were investigated in the laboratory. 

The most plausible explanation supported by the laboratory results is that the hydrated cement 

paste causes the cured concrete to have a very high dielectric constant. The penetration depth 

(i.e., read range) of the UHF RFID radio waves diminishes sharply as the dielectric constant 

increases. A different technology is therefore needed for the PCC tracking application.

Chapter 6: Pavement Temperature Measurement Using SAW RFID. SAW RFID 

technology has the intrinsic capability to measure thermal expansion and thus temperature within 

a pavement layer as a function of depth and time. This is particularly useful for intelligent 

compaction, where estimates of HMA stiffness using sensor data from the vibrating roller must 

consider the instantaneous distribution of temperature in the mat. The temperature measurement 

capability of SAW RFID technology was evaluated through laboratory and field testing. For the 

8
field testing, various configurations of SAW RFID tags were encapsulated in thermally 

conductive epoxy, attached with quick-set epoxy to the surface of a milled existing pavement, 

and then covered with a 1.5-inch (38-mm) thick compacted HMA overlay. Although limitations 

of the SAW RFID reader system made it difficult to measure the temperature versus time trends 

during the first few minutes after placement, mat temperatures were recorded starting at about 

10 min after placement until the mat was too cool for continued compaction. The measured 

temperatures versus time compared favorably with predictions from analytical/numerical models, 

and an approach for using the SAW RFID field temperature measurements for calibrating these 

analytical/numerical models is proposed. Overall the SAW RFID technology was judged to have 

high potential for in situ temperature measurement in HMA pavement layers.

Chapter 7: Reflection Crack Detection. Reflection cracking is a dominant distress in 

rehabilitation overlays. Early detection of these cracks before they reach the pavement surface 

can be important to highway agencies both for rehabilitation planning purposes and for enforcing 

construction contract warranties. The development of an early-onset reflection crack detector 

was originally intended as another application of the SAW RFID technology. However, it was 

subsequently determined that conventional RFID was a more appropriate technology choice, in 

part because of the current relatively high cost of SAW RFID tags. A prototype reflection crack 

detector was developed and tested in the laboratory and, under more limited conditions, in the 

field. The prototype detector was shown in the laboratory to be capable of detecting a reflection 

crack before it reached the pavement surface. The limited field trials also showed that the 

detector had the required survivability and read range for real-world applications. This approach

shows considerable promise, but it will require additional and more rigorous field evaluation that 

was beyond the scope and resources of the present project.

Chapter 8: Guidance on Data Integration. The motivation for this entire study was the 

application of RFID technology for tracking HMA placement. This is also the application that is 

most suited to near-term commercial implementation. The major benefit of this application is the 

integration of agency QA materials testing data with their pavement management database. This 

integration could provide insights into the relationships between good material properties and 

construction techniques and superior pavement performance as well as enable more powerful 

forensic investigations of poorly performing pavements. This integration could also permit much 

more powerful forensic investigations of poorly performing road sections by enabling easy and 

quick access to the associated material properties measured during construction. However, 

several steps are needed to effect this data integration, and given the wide range of materials and 

pavement management systems in use among the States, these steps will be slightly different for 

each agency. General guidelines are provided for the data integration steps that can be easily 

adapted to each agency’s specific databases and policies and procedures.

Chapter 9: Conclusions. The key findings and recommendations from each topic area are 

consolidated and summarized.

Chapters 2 and 3 summarize the work completed in Phases I and II, and chapters 4 through 8 

document the work completed in Phase III.

9
RFID TECHNOLOGIES IN THIS STUDY

RFID technology is widely used today for supply chain inventory management, security, 

equipment tracking, among other applications. However, in construction, RFID technology is 

primarily used for tracking equipment and materials. General surveys of RFID applications in 

construction are provided by Jaselskis et al., Jaselskis and El-Misalami, and Sawyer.

(1,2,3) Two 

types of RFID technology were employed in this study: conventional UHF passive RFID tags 

and the newer SAW RFID tags. Each of these technologies is briefly described in the following 

subsections.

UHF RFID Technology

The UHF RFID technology employed in this study is the basis for the work in Phases I and II. 

The RFID technology encodes a digital signature on a small microchip attached to a copper foil 

antenna—the RFID “tag.” This passive tag receives energy from UHF radio waves transmitted 

by a RFID “reader”; the tag harvests this incoming RF energy to transmit its encoded digital 

signature back to the reader. These RFID tags, although small, may be read several yards away 

from the reader’s antenna. The primary objectives of Phases I and II were to evaluate the 

feasibility of using UHF RFID tags in laboratory asphalt specimens and in the field during 

paving construction.

SAW RFID Technology

One of the major objectives of Phase III was to evaluate the feasibility of using SAW-based 

RFID technology to measure HMA temperatures. SAW-based RFID sensors are inherently 

capable of measuring and transmitting temperatures as well as a digital signature. This is in 

contrast to the conventional RFID technology used in Phases I and II, which is capable of only 

transmitting digital signatures. In addition, the SAW RFID technology is inherently capable of 

operating successfully at lower energy inputs than the conventional silicon-based integrated 

circuit RFID technology.

SAW RFID tag consists of an IDT and a series of acoustic reflector traps etched into a 

piezoelectric substrate. The tag reader emits a radio wave pulse to the IDT that is converted 

piezoelectrically into a nanoscale acoustic wave. The wave travels past the reflectors to produce 

a unique pattern of reflected pulses. These travel back to the IDT, where they are 

piezoelectrically converted into an encoded electronic reply signal to the reader. The SAW chip 

operates in a purely passive mode and does not require supplementary DC power (i.e., battery).(4)

Overall, the principal advantages of the SAW RFID technology for pavement construction 

include better inherent ruggedness, smaller formats, and longer read ranges for a given tag 

antenna size compared with conventional RFID. Unlike conventional RFID tags, the incoming 

RF signal does not need to be converted to DC in SAW RFID. Therefore, the incoming RF 

signal strength does not need to exceed the minimum threshold required for the rectifier 

operation. This is the principal theoretical reason for the inherently longer read ranges in the 

SAW RFID technology.

10
In addition, and most relevant to this study, SAW RFID technology is capable of wireless 

measurement of temperature via the perturbation of the return wave signal caused by the 

influence of thermal strains on the spacing of the acoustic reflectors. 

11

CHAPTER 2: FEASIBILITY EVALUATION

The feasibility evaluation encompassed the following components: 1) literature review,

2) identification of appropriate RFID technology, and 3) prototype tag development and 

evaluation. Each of these is described in the following sections.

LITERATURE REVIEW

The literature review focused on RFID technology and applications in the general areas of civil 

engineering and construction. Specific RFID applications identified in these areas include the 

following:

• Tracking of PCC test specimens.

• Maturity monitoring of in-place PCC.

• Tracking of construction materials at project site (e.g., fabricated pipe).

• Construction tool inventory/usage control/monitoring.

• Location identification of buried infrastructure (cables and pipes).

An annotated bibliography of the reviewed articles is provided at the end of this report.

IDENTIFICATION OF APPROPRIATE RFID TECHNOLOGY

Aspects of RFID technology of relevance to this project include the following:

• Physical size of the tag.

• Operating frequency (low, high, ultrahigh, and microwave; this influences tag size and 

read range).

• Type of tag (active or passive; this influences cost, power consumption, and maximum 

read range).

• Read range (including high-gain antenna design).

• Durability/survivability (e.g., strength of tag encapsulation; maximum/operating 

temperature ranges).

• Cost of the expendable tag.

Some light was shed on these aspects by articles from the literature review. However, other lines 

of inquiry were also pursued: 1) consultations with Dr. Marc Cohen, a research scientist at the 

Center for Engineering Logistics and Distribution in UMD’s Institute for Systems Research and 

2) exploratory laboratory studies.

Dr. Cohen has extensive experience in RFID technology. Discussions with him confirmed and 

expanded the conclusions reached from the literature review (see also table 1): 

13
1. For a physical tag size on the order of 1 inch (25 mm), the UHF range is optimal. 

2. Passive tags, which are preferred because of their cost differential relative to active tags, 

should be able to provide the requisite read range performance.

3. Commercial RFID readers are readily available for vehicle mounting (e.g., antennas on a 

front bumper) with read ranges on the order of 3 ft (1 m) or more, which is sufficient for 

this study’s applications.

4. Possible attenuation of the RFID signal by the asphalt concrete could be an issue and 

therefore needed to be explored early. 

5. Thermal and mechanical survivability are key challenges. The maximum temperature 

range tolerable for short periods (e.g., the time required to truck a load of asphalt from 

the production plant to the paver) is significantly higher than the typical rated operating 

and/or storage temperatures for RFID tags. 

Table 1. Characteristics of different RFID technologies.

Type Frequency Pros/Cons Read Range (ft)

Passive Active

Low 

Frequency

125 KHz Requires less power, better 

penetration of nonmetallic, and/or 

high water content substances

1 —

High 

Frequency

13.56 MHz Works well on metal objects 3 —

UHF 860–960 MHz Better range, faster data transfer. 

Uses more power. More “directed,”

requires a clear path between tag and 

reader. Largest application area, 

widest installed base in industry.

10–20 100–300

Microwave 2.45 GHz Little experience to date. — —

— Indicates no information available

1 ft = 0.0305 m

KHz = kilohertz

MHz = megahertz

GHz = gigahertz

Preliminary Evaluations

Potential attenuation of the RFID signal by the asphalt surrounding the embedded tag could have 

a major impact on read range and thus system practicality. Because this aspect is vital to the 

project, it was evaluated early on in a very preliminary way as part of the identification of 

appropriate RFID technologies. Jaselskis et al. describe the theoretical aspects of electromagnetic 

wave interaction with materials, with a particular focus on asphalt concrete.(2) The key material 

property governing the transmission of dielectric materials is the permittivity. A dielectric 

material is an electrical insulator. A vacuum is the ideal insulator, but many materials (e.g., 

asphalt concrete) also fall into this category. When an electric field interacts with a dielectric 

14
medium, redistribution of charges within its atoms or molecules alters the shape of the field both 

inside and around the medium. The absolute permittivity, , is the fundamental physical quantity 

governing the interaction between and electric field and a dielectric medium. It is a measure of 

the ability of the medium to polarize and thus reduce the strength of the field. In other words, 

permittivity defines a materials ability to transmit or “permit” an electric field. The relative 

permittivity or dielectric constant, , is the permittivity of a material relative to that of an ideal 

vacuum, , as shown in the equation in figure 1.

Figure 1. Equation. Definition of relative permittivity or dielectric constant .

According to Maxwell’s equations for nonmagnetic media, the electric field E induced by the 

incident electromagnetic wave is defined in the equation in figure 2.

Figure 2. Equation. Electric field E.

The displacement vector D is calculated using the equation shown in figure 3:

Figure 3. Equation. Displacement vector D.

where:

= circular frequency of the wave. ε0 = permittivity of vacuum.

= frequency dependent dielectric constant of the medium

 = / , where = absolute permittivity.

i = .

The displacement field D represents how the electric field E influences the organization of 

electrical charges in a given medium. The total current flowing within a medium is divided into 

conduction and displacement components. The displacement current can be thought of as the 

elastic response of the material to the applied electric field. As the magnitude of the applied field 

is increased, an increasing amount of energy is stored in the displacement field. If the electric 

field is subsequently decreased, the material will release the stored energy. 

Owing to inertia processes in fluctuating electromagnetic fields, the displacement field D for 

most materials is not in phase with the electric field E. As a consequence, the dielectric constant 

is the complex frequency-dependent quantity defined in the equation in figure 4.

Figure 4. Equation. Complex relative permittivity (dielectric constant).

εa

ε

ε0

ε

E = E0e

iω

D = ε0

ε(ω)E

ω

ε(ω)

εa(ω) ε0 εa(ω)

−1

ε*(ω)

15
The real part of the permittivity, , is a measure of polarization and is thus a measure of the 

energy stored in the medium while the imaginary part, , defines the average power absorbed 

and/or scattered by the medium and thus is a measure of energy loss. This energy loss can also 

be related to the electrical conductivity σ for the given frequency as shown in the equation in 

figure 5.

Figure 5. Equation. Relationship between imaginary portion of complex dielectric constant 

and electrical conductivity.

The net effect of all of the above is that electromagnetic wave propagation is impeded as the 

permittivity increases. Maximum RFID read range occurs when the RFID electromagnetic waves 

travel through a material with a low dielectric.

For asphalt concrete, both the real and imaginary permittivity components will be functions of 

the mixture composition, moisture content, and density. Jaselskis et al. measured the complex 

relative permittivity components as functions of frequency and temperature for several asphalt 

concrete mixtures.(2) Values of the real and imaginary relative permittivity components for a sand 

asphalt mixture varied between about 4.5 and 5.5, and 0.2 and 0.3, respectively.

The theoretical description of electromagnetic wave propagation and losses in terms of relative 

permittivity is placed in better context through comparisons with other materials. Table 2

summarizes relative permittivity values for construction and related materials. Asphalt concrete 

typically has a relative permittivity of between 3.5 and 5.0, comparable to Portland cement 

concrete, aggregates, and other similar materials. This range lies closer to the properties of good 

UHF media (e.g., vacuum and air), and relatively far away from poor UHF media (e.g., water)—

suggesting that attenuation losses of RFID signals through asphalt concrete should be modest.

ε ω′( )

ε ω′′( )

16
Table 2. Typical dielectric constant (relative permittivity) values for common materials.

Material Dielectric Constant Frequency Range

Vacuum 1.0 —

Air 1.00054 —

Teflon (polytetrafluorethelene) 2.0 to 2.1 —

Polyethylene 2.25 —

Bitumen 2.38 —

Polystyrene 2.4 to 2.7 —

Polyvinylchloride 3.3 to 4.55 —

Porous asphalt concrete 3.6 to 4.1 50 MHz to 1.6 GHz

Dense graded asphalt concrete 4.4 to 5.0 50 MHz to 1.6 GHz

Concrete 4.5 —

Quartzite aggregate 4.95 —

Granite 6.25 to 5.75 60 MHz to 1.4 GHz

Glass 6.775 —

Rubber 7 —

Silicon 11.68 —

Cement mortar 20 to 30 1 MHz to 300 MHz

Water 80 —

— Indicates no information available

Note: Bold font indicates materials most relevant to the present study.

MHz = megahertz

GHZ = gigahertz

RFID System

Based on a careful review of the specifications and available product reviews for various 

manufacturers’ systems, the Mercury® 5 RFID reader from ThingMagic was selected as most 

suitable for this project. Key specifications of the Mercury® 5 reader include the following:

Hardware

Name: ThingMagic Mercury® 5

Processors: Intel© IXP4xx Network Processor

Texas Instruments Digital Signal Processor

Memory: 64 Megabyte (MB) DRAM, 16 MB FLASH

Connectivity: RS-232 serial interface

10/100 Base-T Ethernet interface

Mechanical and Environmental

Dimensions: 10 by 10 by 1.5 inches (250 by 250 by 38 mm)

Temperature: 32–104 °F (0–40 °C) operating

-4–158 °F (-20–70 °C) storage

Humidity: 0–90 percent relative humidity (noncondensing)

Weight: 3 lb 10 oz (1.6 kg)

Power: 24V DC 2A unregulated

17
Radio Frequency

Operating Frequencies: 902–928 MHz

Air Interface Protocols: EPC Class 0

EPC Class 1

EPC Generation 2

ISO 18000-6B/Unicode 1.19

Rewritable Class 0+

RF Power: +32.5 dBm (1 Watt (30 dBm)) in accordance with Federal

Communications Commission Part 1.5;

+2.5 dB attenuation due to antenna cables)

The ThingMagic Mercury® 5 was purchased as a complete start-up system, including the reader, 

two bistatic circular antennas, four 25-ft (7.6-m) cables, a startup CD, and a selection of RFID 

tags.

Suitable tags compatible with the Mercury® 5 reader and meeting size limits were also 

identified. Key features of these tags are summarized in table 3. Sample quantities were obtained 

for the Alien® Gen 2 1x1 and Alien® Gen 2 2x2 tags. Attempts to purchase small trial quantities 

of the Avery-DennisonTM AD-812 tags were unsuccessful. 

Table 3. Candidate RFID tags (all passive).

Vendor Model Frequency

(MHz)

Size 

(inches)

Temperature Range

(

o F)

Comments

Operating Storage

Alien® Gen 2 1x1 902–928 1 by 1 -13 to +149 — Small form factor 

optimized for plastic 

packaging such as pill 

bottles; nominal read 

range of 1.25 to 2.5 m.

Alien® Gen 2 

MiniSquiggle®

902–928 1.1 by

0.39

-13 to +149 — Nominal read range of 

1 to 1.5 m.

Alien® Gen 2 2x2 860–960 1.85 by

1.65

-13 to +149 — Omni-directional

AveryDennisonTMAD-812 902–928 1 by 1 -40 to +149 -40 to +185 Designed for superior 

edge-on read 

performance.

— Indicates no information available

MHz = megahertz

°C = (°F – 32)/1.8

1 m = 3.28 ft

Linking the RFID tag identifier with GPS latitude and longitude coordinates is also an important 

component of this project. A GarminTM GPS 12 transponder was initially evaluated for linking 

GPS with RFID. Preliminary findings suggested that a data logger would be an easier technology 

for linking the RFID tag data to latitude and longitude coordinates. A GPS data logger records a 

constant stream of latitude/longitude/time values that can then be matched post facto to the time 

stamps on the RFID tag data. An inexpensive Pocket Tracker Pro system from Brickhouse®

Security (www.brickhousesecurity.com) was therefore acquired for use on the project. Key 

features of the Pocket Tracker Pro system useful for this project include: 1) location accuracy to 

18
within 8.2 ft (2.5 m); 2) read rate of one location point per second; 3) magnetic vehicle mount; 

4) universal serial bus computer interface; 5) 100-h battery life (AAA batteries); and 6) low cost.

PROTOTYPE TAG DEVELOPMENT AND EVALUATION

Fabrication

Encapsulation of the RFID tags to protect them from temperature extremes and compaction 

stresses is key to their use in asphalt paving applications. Two candidate encapsulation media 

were considered: ceramics and high-temperature epoxy. Upon evaluation of these two materials, 

the ceramics were discarded because of high cost and fabrication difficulties. A high temperature 

epoxy, DurapotTM 866 from Contronics, Inc. (www.contronics.com), was selected as a suitable 

encapsulating material. DurapotTM 866 is a thermally and electrically insulating compound that 

forms a low-density nonporous foam for high-temperature applications. This two-part epoxy, 

after proper curing at room temperature for 24 h followed by oven curing at 248 °F (120 °C) for 

4 h, has an upper temperature limit of 500 °F (260 oC), more than adequate for asphalt 

applications.

Suitable molds for encapsulating the RFID tags in the high-temperature epoxy are also required. 

CPVC pipe was found to be suitable for this purpose. CPVC is a thermoplastic commonly used 

for cold and hot piping systems in building construction. It has a glass transition temperature of 

approximately 230 °F (110 °C) and a melting point of 414 °F (212 °C), which is sufficient for 

use with hot mix asphalt. The Alien® 1x1 and 2x2 tags were curled respectively inside 1-inch

(25-mm) and 2-inch (50 mm) long sections of 3/4-inch (19-mm) nominal diameter CPVC pipe. 

The inside diameter of this pipe is sufficiently large that the ends of the curled tags did not 

overlap. Curling the tag with the antenna facing outward or inward had no influence on the read 

range. The pipe with tag was then filled with the high-temperature epoxy and cured. Because the 

CPVC pipe is transparent to the RFID signal and has a melting point higher than the HMA 

compaction temperature, there was no need to extrude the tag after curing of the epoxy.

The epoxy molding and curing process was further refined to minimize problems caused by air 

bubbles during curing. The original procedure followed the epoxy manufacturer’s suggestions: 

the mold was filled with epoxy at room temperature, then cured at room temperature for 24 h 

followed by oven curing at 248 °F (120 °C) for 4 h. This process often resulted in voids between 

pipe wall and tag during filling (figure 6) and air bubbles within the epoxy during the room 

temperature curing (figure 7). These defects would then expand and cause tag failure during the 

subsequent oven curing (figure 8 and figure 9). A post-mortem examination of tags compacted 

into gyratory HMA cylinders also found bulges along the edges of the encapsulated tags 

(figure 10). However, the compaction force of 88 psi (608 kPa) over 160 gyrations did not

appear to cause any significant damage to the tag encapsulation.

In the refined encapsulation method, the epoxy resin is first preheated for 15 to 30 min at 104 °F 

(40 °C) to reduce its viscosity. The hardener is then added to the preheated resin. The tags are 

placed in CPVC pipe molds in a circumferential orientation (see figure 16 later) and the bottom 

pipe opening is sealed with duct tape. Epoxy is then poured in three lifts into the pipe, with the 

pipe tapped vigorously on the laboratory bench after each lift to eliminate any trapped air 

bubbles. The encapsulated tags are then placed upright in the oven at 122 °F (50 °C) for up to 1 h 

19
until hardened. Occasionally, escaping air bubbles could be observed during this stage, and in a 

few cases (fewer than 1 in 10), some of the epoxy was pushed out of the pipe owing to entrapped 

air. After hardening, the tags are removed from the oven, the duct tape seal removed, and the 

tags cooled for 2 h at room temperature. The tags are then checked for survival through the first 

stage of the curing process. Observed survival rates at this stage were very high, especially for 

the Alien® 2x2 tags. Surviving tags are then cured in a second stage at 257 °F (125 °C) for 4 h.

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.

20
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.

21
Figure 10. Photo. Post-mortem examination of tags retrieved from compacted HMA with

bulges in encapsulated tags circled.

Evaluation of Read Range

Initial Evaluation

Read range was evaluated initially using the Alien® 2x2 tags curled in the CPVC pipe sections. 

During this initial evaluation, it was discovered that there are several sources of interference that 

can alter the measured effective read range as follows:

1. There appears to be a “body antenna” effect. Tags held by hand were discovered to have 

different read ranges than tags placed on an inanimate object with all persons removed to 

a distance. Even body movements 8 ft (2.5 m) away from the tag would trigger a read 

when none had been observed before.

2. Placing the tags on the floor and then stepping some distance away gave more controlled 

conditions and consistent read data. The disadvantage of placing the tags on the floor and 

then reading them in a horizontal direction to determine maximum read distance is that 

the tags are slightly off the centerline of the antenna. This tends to decrease the measured 

read range. The advantage, of course, is that placing everything on the laboratory floor is 

much easier than elevating everything several feet off the floor.

3. When a half-filled bucket of aggregate was accidentally placed behind one of the tags, 

the read range increased considerably. This may have beneficial implications for field 

versus laboratory performance of the tags.

The read range tests were designed to minimize these compounding influences. The 1 by 2 ft 

(0.3 by 0.6 m) RFID antenna was oriented perpendicular to the floor, supported along its long 

edge directly on the floor. A grid was laid out on the floor in front of the antenna. Tags were 

placed at each grid point, and the observer stepped aside before tag read success was assessed. 

22
Replicate specimens and multiple reads were employed to improve the robustness of the test 

results.

The first series of tests employing this protocol were conducted on flat Alien® 2x2 tags before 

curling or encapsulation. Six read attempts were made at each grid point. Three of these were 

with the tag facing the antenna, and three were with the tag facing away. The tag orientation was 

found to have no effect on the read success rate. Each grid point was assigned a value of 1 if the 

read success rate was greater than 50 percent for the six read attempts, a value of 0.5 if the tag 

could be read but the success rate was less than 50 percent, and a value of 0 if the tag could not 

be read at all. A total of six tags were tested using this scheme. The results from this test series 

are summarized in figure 11. Each block in the figure represents a 1 by 1 ft (0.3 by 0.3 m) cell on 

the floor as viewed from above. The antenna is perpendicular to the floor (i.e., vertical), resting 

along its 2-ft (0.6-m) long edge. Note that the antenna assembly contains separate transmit and 

receive antennas along its length, as indicated by the “T” and “R” designations in the figure. The 

numeric values in figure 11 represent the total score in each cell for the six tags, and the color 

coding depicts the read success rate category (all tags read, >50 percent tags read, <50 percent

tags read, no tags read). Overall, the results in figure 11 suggest an effective read range of 

approximately 7 ft (2.1 m) for the flat Alien® 2x2 tags in air. There is some slight asymmetry in 

the read success pattern that may be due to experimental variability, local interference, and/or the 

asymmetric antenna design.

The next series of tests was conducted on the curled Alien® 2x2 tags inside the CPVC pipe but 

before encapsulation in epoxy. This test series was designed to evaluate the effects of the curved 

tag geometry on read success. The pipes containing the curved tags were placed on the floor and 

parallel to the plane of the antenna in all tests. However, two orientations of the tags relative to 

the antenna were considered: 1) the pipe axis horizontal with respect to the floor and parallel to 

the long axis of the antenna and 2) the pipe axis vertical and parallel to the short axis of the 

antenna. The results from this test series are summarized in figure 12 and figure 13 for the 

horizontal and vertical orientations, respectively. It is clear from these figures that curling the 

tags does reduce the read range, and by a larger amount for the vertical orientation. Maximum 

effective read range in air in front of the antenna is approximately 5 ft (1.5 m) for the horizontal 

orientation and 3 ft (1 m) for the vertical, compared with approximately 7 ft (2.1 m) for the flat 

tag configuration.

23
All distances in ft (1 ft = 0.305 m) 

T=transmit side of antenna 

R=receive side of antenna

Figure 11. Diagram. Read range for flat Alien® 2x2 tags in air with tags oriented parallel 

to reader antenna. 

All distances in ft (1 ft = 0.305 m)

T=transmit side of antenna

R=receive side of antenna

Figure 12. Diagram. Read range for curled Alien® 2x2 tags in CPVC pipe before 

encapsulation and curing with tags oriented in horizontal direction.

-4 -3 -2 -1 T R 1 2 3 4

1 2 6 6 6 6 2

2 5 6 6 6 6 6 1 N=6

3 4 6 6 6 6 6 All tags read

4 2 6 6 6 6 6 6 5 >50% tags read

5 1 6 6 6 6 4 1 <50% tags read

6 5 6 6 6 5 No tags read

7 5 5 6 5 3

8 3 1 2 2 2

Antenna

-4 -3 -2 -1 T R 1 2 3 4

1 1 6 6 6 0.5

2 6 6 6 1 N=6

3 1.5 5 6 6 4.5 All tags read

4 1.5 3.5 6 6 5.5 2 >50% tags read

5 3 4.5 5 6 6 2.5 <50% tags read

6 2.5 2.5 3.5 4.5 5 3.5 No tags read

7 1.5 1 3 2.5 2 0.5

8 2.5 1 3.5 1 0.5

Antenna

24
All distances in ft (1 ft = 0.305 m)

T=transmit side of antenna

R=receive side of antenna

Figure 13. Diagram. Read range for curled Alien® 2x2 tags in CPVC pipe before 

encapsulation and curing with tags oriented in vertical direction.

Read ranges after encapsulation with epoxy and curing, the next stage in the fabrication process, 

are summarized in figure 14 and figure 15 for the horizontal and vertical tag orientations, 

respectively. Effective read range limits are reduced even further by the epoxy and curing 

process to approximately 2 ft (0.6 m) for the horizontal orientation and 1 ft (0.3 m) for the 

vertical. This may be because the Alien® 2x2 tags were curled with the antenna and chip facing 

inward and the paper backing facing outward. It is possible that there may have been some signal 

leakage from the antenna into the epoxy that is responsible for the reduced read range. 

Unfortunately, the initial supply of tags was nearly exhausted when this phenomenon was 

discovered. 

-4 -3 -2 -1 T R 1 2 3 4

1 0.5 5.5 6 5.5

2 6 6 6 1 N=6

3 4.5 4.5 5 4 All tags read

4 1 3 2 5 1 >50% tags read

5 1 1 3 1.5 <50% tags read

6 1 0.5 No tags read

7 0.5 0.5

8

Antenna

25
All distances in ft (1 ft = 0.305 m) 

T=transmit side of antenna 

R=receive side of antenna

Figure 14. Diagram. Read range for curled Alien® 2x2 tags in CPVC pipe after 

encapsulation and curing with tags oriented in horizontal direction.

All distances in ft (1 ft = 0.305 m)

T=transmit side of antenna.

R=receive side of antenna

Figure 15. Diagram. Read range for curled Alien® 2x2 tags in CPVC pipe after 

encapsulation and curing with tags oriented in vertical direction.

Additional Evaluation

After receiving more RFID tags, additional evaluations were performed to examine the effects on 

read performance of orientation of the tag within the CPVC mold cylinder and of the 

-4 -3 -2 -1 T R 1 2 3 4

1 5 5 2.5

2 1 5 2.5 N=5

3 All tags read

4 >50% tags read

5 <50% tags read

6 No tags read

7

8

Antenna

-4 -3 -2 -1 T R 1 2 3 4

1 5 5 2.5

2 1 3.5 2.5 N=5

3 All tags read

4 >50% tags read

5 <50% tags read

6 No tags read

7

8

Antenna

26
encapsulated cylindrical tag relative to the antenna geometry. All tags were now curled with the 

antenna surface outward and against the CPVC pipe wall. As shown in figure 16, two 

orientations can be defined for the tags depending on whether the antenna dipoles are oriented in 

an axial or circumferential direction with respect to the CPVC pipe axis (CPVC pipe axis is 

vertical in figure 16). In addition, the cylindrical encapsulated tag itself can have varying 

orientations relative to the antennae. Two limiting cases were considered: both had the axis of 

the cylindrical encapsulated tag parallel to the plane of the antenna unit, but in one orientation,

the axis was parallel to the line connecting the centers of the transmit and receive antennae (i.e., 

parallel to the long dimension of the antenna unit) and in the other, the axis was perpendicular to 

this line (i.e., parallel to the short dimension of the antenna unit). Note that in reality, one can 

only control the orientation of the RFID tag within the CPVC mold; the orientation of the 

cylindrical tag relative to the antenna geometry will depend on the final random orientation of 

the encapsulated tag within the compacted pavement.1

Table 4 summarizes the influence of tag and cylinder orientation on maximum read range for the 

encapsulated Alien® 1x1 tags after oven curing at 248 °F (120 °C) for 24 h and subsequent oven 

heating to 247 °F (175 °C) for 1.5 h. Table 5 presents similar data for the Alien® 2x2 tags. 

Recall that the maximum read range for the nonencapsulated flat tags through air ranged between 

2.5 to 4 ft (0.6 to 1.2 m) and 6 to 13 ft (2 to 4 m) for the Alien® 1x1 and 2x2 tags, respectively. 

Conclusions that can be drawn from these data include the following:

• The maximum read range of the Alien® 1x1 tags is substantially less than that of the 

Alien® 2x2 tags under all conditions. 

• Regardless of orientation details, curling the RFID tag inside the CPVC pipe and/or 

encapsulating it in high-temperature epoxy significantly degrades the maximum read 

range. The 4-ft (1.2-m) maximum read range of the flat Alien® 1x1 tag decreased to a 

maximum of 2-ft (0.6-m) when encapsulated; the 13-ft (4-m) maximum read range of the 

flat Alien® 2x2 tag decreased to a maximum of 9 ft (2.7 m) when encapsulated.

• In nearly all cases the circumferential orientation of the RFID tag inside the CPVC pipe 

gives longer maximum read ranges. The differences between circumferential and axial 

orientation are modest to nonexistent for the smaller Alien® 1x1 tags but significant for 

the larger Alien® 2x2 geometry.

• The effect of orientation of the tag axis relative to the T-R antenna line appears to be 

quite small, with no consistent trends except for a small benefit of the perpendicular 

alignment for the circumferentially oriented Alien® 2x2 tags. It is fortunate that this 

influence is small because there is no way to consistently control the orientation of the 

tags relative to the antennae in the field.

 1 During the subsequent field trials (chapter 3), it was observed that most of the in-place tags appeared to lie 

within a horizontal plane, i.e., parallel to the plane of the antenna unit during field reading.

27

 
Figure 16. Drawing. Orientation options for RFID tags inside CPVC pipe molds (axis of 

CPVC pipe mold is vertical in all drawings).

Table 4. Maximum read range (ft) for Alien® 1x1 tags after 24-h oven cure at 248 o

F 

(120 °C), cooling, then reheating for 1.5 h at 247 °F (175 °C).

Alignment of RFID 

Tag Within CPVC 

Pipe (Figure 16)

Orientation of Cylindrical Tag Axis Relative to 

T-R Antenna Line

Parallel Perpendicular

Axial 1–1.6 0.5–1

Circumferential 0.5–1 1.6–2

Note: Cylindrical tag axis parallel to plane of antenna unit in all cases.

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).

Alignment of RFID 

Tag Within CPVC 

Pipe (Figure 16)

Orientation of Cylindrical Tag Axis Relative to 

T-R Antenna Line

Parallel Perpendicular

Axial 2–2.5 0.5–2

Circumferential 5–7 8–9

Note: Cylindrical tag axis parallel to plane of antenna unit in all cases.

Evaluation of the tag read performance continued to be plagued by sporadic problems with RF 

interference/reflections, proximity of the floor and/or people in the laboratory, and other factors. 

Consequently, an improved procedure for evaluating read performance and range in the 

laboratory was standardized. Nonconductive supports were constructed for the RFID antenna and 

tags to elevate them approximately 3.28 ft (1 m) above the laboratory floor. All laboratory 

personnel move several meters away from the antenna and tags prior to conducting read tests to 

minimize body interference.

Figure 17 and figure 18 summarize typical read rate performance as measured using the new 

standardized procedure. The two samples represent Alien® 2x2 tags encapsulated in CPVC 

molds and compacted into a single gyratory HMA cylinder. At each position, the cylinder was 

28
oriented horizontally (axis parallel to floor) and then rotated through six different angles relative 

to the antenna. The figure summarizes the read success rate over all angles at various positions 

from the antenna for the two embedded tags. In general, the tags in these trials could be read up 

to a distance of approximately 5 ft (1.5 m) from the antenna and at angles off the antenna axis. 

Note that there are some slight differences in the read performance between the two samples; 

variability in individual tag read performance has been observed consistently throughout this 

study. Note also that the read success rate is biased toward the transmitter (“T”) side of the 

antenna. Apparently, it is important to position the tag closer to the transmitter antenna so that it 

receives maximum impinging RF energy.

All distances in ft (1 ft = 0.305 m)

Figure 17. Diagram. Read performance for sample 7 as evaluated using standardized 

laboratory procedure. 

All distances in ft (1 ft = 0.305 m)

Figure 18. Diagram. Read performance for sample 8 as evaluated using standardized 

laboratory procedure. 

Thermal Survivability

Thermal survivability is the first hurdle for the RFID tags because typical mixing and 

compaction temperatures in HMA of up to 356 °F (180 °C) are well above their operating and 

long-term storage temperature limits. Thermal survivability was investigated in a preliminary 

way using the Alien® 1x1 encapsulated tags. Only one replicate was tested for each condition. 

-2 -1 T R 1 2

Antenna

1 5 6 5 3 N=6

2 1 5 6 6 3 100% read

3 2 4 6 4 3 >50% read

4 2 4 2 1 <50% read

5 2 No read

6

Axial Offset (ft)

Lateral Offset 

(ft, from antenna edge)

2

5

5

5

6

-2 -1 T R 1 2

Antenna

1 5 5 6 6 5 N=6

2 4 5 6 6 5 100% read

3 3 5 6 6 5 >50% read

4 3 3 3 4 2 <50% read

5 1 2 2 1 No read

6

6

Lateral Offset 

(ft, from antenna edge)

6

4

Axial Offset (ft)

2

1

1

1

6

29
All tags were left in the oven for 1.5 h at the target temperature. The time duration was chosen to 

duplicate the longest time between placement of the tags in the truckload of hot mix at the plant 

to final cooling of the compacted mat in the field. Immediately after removal from the oven, 

none of the tags could be read. However, all tags could be read to a distance of 3 ft (1 m) in air 

after being allowed to cool for 20 min. This is very similar to the baseline read for the Alien®

1x1 encapsulated tag prior to heating. 

The preliminary investigation of thermal survivability was repeated with two encapsulated 

Alien® 2x2 tags. The first was heated for 1.5 h at 302 °F (150 °C); as with the Alien® 1x1 tags, 

the 2x2 tag could not be read immediately after removal from the oven but was readable up to a 

range of 10 ft (3 m) after 20 min of cooling. The second Alien® 2x2 tag was heated to 347 °F 

(175 °C) and appeared to fail because it could not be read even after cooling. However, visual 

inspection suggested that the encapsulation may have been flawed, directly exposing part of the 

tag to the high temperatures.

Mechanical Survivability

Mechanical survivability was independently evaluated via gyratory compaction of the 

encapsulated tags into a cold mix asphalt product. Mechanical survivability was investigated in a 

preliminary way using the Alien® 1x1 encapsulated tags. Each tag was placed in the loose cold 

mix near the center of the mold and then compacted to between 50 and 100 gyrations in the 

compactor. This is intended to simulate the stresses that the tags would feel during compaction in 

the mat in the field. All of the encapsulated tags survived the compaction. The average read 

range of 26 inches (670 mm) represents an approximately 30-percent decrease from the greater 

than 3 ft (1 m) baseline read range prior to compaction. It is speculated that this reduction is due 

to the additional attenuation of the RFID signals through the asphalt rather than any effect from 

the compaction itself. 

The preliminary investigation of mechanical survivability was repeated with one encapsulated 

Alien® 2x2 tag compacted in the cold mix asphalt to 100 gyrations. Read range after compaction 

was approximately 10 ft (3 m). Again, this represents a decrease from the baseline read range 

through air of approximately 25 ft (7.6 m) for the 2x2 tag.

One of the cold mix gyratory plugs was saturated in water after initial testing to evaluate the 

influence of pavement moisture on signal attenuation. No significant difference in read range 

was discerned between the dry and wet conditions.

Combined Thermal and Mechanical Survivability

Once the survivability of the tags under only thermal or mechanical torture had been established, 

the final test was survivability under combined conditions in the laboratory. This test is intended 

to simulate the actual field scenario of transport of the tag in the truckload of hot mix asphalt 

followed by compaction into the mat behind the paver.

The hot mix asphalt used for this evaluation was a dense graded mix with a PG 64-22 

unmodified binder. Tags were placed in an oven along with the loose mix for 1.5 h at a 

temperature of 320 °F (160 °C) before compaction. Two tags were placed in the loose mix in 

each gyratory mold near the axis at approximately the third points of the mold height. After 

30
compaction, the gyratory plugs were extruded from the molds and then scanned in the axial 

direction by the RFID reader. 

Figure 19 summarizes the read tests for three gyratory plugs, each containing two tags that had 

been encapsulated in the CPVC pipe. For two of the plugs, only one of the two tags survived the 

heating and compaction. During the read tests, the gyratory plug was rotated through six

different positions (12:00, 2:00, 4:00, 6:00, 8:00, and 10:00). Each of the tags was read in each 

position. Given that there were only four surviving tags among the three gyratory plugs, there 

was a maximum of 24 possible successful reads. For the one plug in which both tags survived, 

there were no trends in read success or range between the closer versus more distant tag. As 

shown in the figure, the maximum effective read range was approximately 2 ft (0.6 m). This is 

roughly consistent with the effective read range for this tag type through air after encapsulation 

and curing (figure 14 and figure 15). In other words, the additional heating and compaction for 

the tags depicted by figure 19 did not significantly degrade the effective read range.

Six tags in all were oven heated and compacted into gyratory plugs. Of these, four survived and 

were able to transmit their identification numbers to the RFID reader when scanned. This 

corresponds to a survival rate of 75 percent. This is sufficient for field application because it is 

envisioned that multiple tags will be tossed into the truckload of HMA for redundancy.

All distances in ft (1 ft = 0.305 m)

T=transmit side of antenna

R=receive side of antenna

Figure 19. Diagram. Read range for curled Alien® 2x2 tags in CPVC pipe after HMA oven 

heating and gyratory compaction.

CONCLUSIONS FROM FEASIBILITY EVALUATION

• Conventional passive UHF (860–960 MHz) RFID technology was determined as the 

most promising for paving applications. The advantages of passive UHF RFID included 

small tag size, low cost, adequate read range, and wide commercial availability. Potential 

attenuation of the UHF radio signals by HMA and survivability of the tags in the harsh 

-4 -3 -2 -1 T R 1 2 3 4

1 22 24 14

2 12 19 7 N=24

3 1 4 1 All survived tags read

4 >50% survived tags read

5 <50% survived tags read

6 No survived tags read

7

8

Antenna

31
thermal and mechanical environment during paving were identified as the two key 

challenges to be addressed in the research.

• Based on theoretical considerations and data from the literature, it was determined that 

HMA was likely a good UHF medium in terms of attenuation losses. This was confirmed 

through laboratory studies, which concluded that UHF RFID signal attenuation by asphalt 

concrete should not be a serious issue in the field.

• Based on a careful review of the specifications and available product reviews for various 

manufacturers’ systems, a Mercury® 5 RFID reader system from ThingMagic, Inc. was 

purchased for this project. Alien® Technologies Gen 2 1x1 and 2x2 tags were selected 

for initial evaluation because of their compatibility with the Mercury® 5 reader and their 

suitable dimensions.

• Various encapsulation schemes were evaluated for hardening the RFID tags against the 

thermal and mechanical stresses of paving. The final scheme consisted of encapsulation 

of rolled tags inside 3⁄4-inch (19-mm) nominal outside diameter CPVC pipe subsequently 

filled with cured Cotronics DurapotTM 866 high-temperature epoxy. 

• The read ranges of the encapsulated tags were thoroughly evaluated. The read range for 

the Alien® 1x1 tags in the optimal circumferential orientation inside the CPVC pipe 

varied between 0.5 and 2 ft (0.15 and 0.6 m), which is inadequate for the intended 

application. The corresponding read range for the Alien® 2x2 tags varied between 5 and 

9 ft (1.5 and 2.7 m), which is more than adequate for the HMA tracking application.

• Thermal and mechanical survivability of the encapsulated tags was evaluated in the 

laboratory via oven heating and gyratory compaction. The encapsulated tags survived 

oven heating for 1.5 h at temperatures up to 347 °F (175 °C), adequate for paving 

applications. Survival rate for combined thermal and mechanical effects was 

approximately 75 percent. This is sufficient for field application because multiple tags 

will be placed into each truckload of HMA for redundancy.

• One gyratory plug was saturated in water after initial testing to evaluate the influence of 

pavement moisture on signal attenuation. No significant difference in read range was 

discerned between the dry and wet conditions.

32
CHAPTER 3: RFID TRACKING OF HMA PLACEMENT

INTRODUCTION

The encapsulated RFID tags were field tested to evaluate the following issues:

• Survivability under real-world paving scenarios.

• Read range under actual field conditions.

• Required redundancy (i.e., how many tags must be added to a truckload to locate the mix 

reliably along the pavement alignment; this is related to the survivability issue, but also 

includes delays in passing through the paver).

• Construction practicality issues (e.g., do the tags interfere with normal paving 

operations?).

• Construction quality issues (e.g., do the tags impair the quality of the compacted mat by 

inducing segregation or other defects?).

The pavement sections selected for the Phase II field trials included the following:

1. UMD Parking Lot XX1 (figure 20).

2. UMD Parking Lot EE (figure 20).

3. UMD Parking Lot T (figure 20).

4. Hampstead Bypass/MD 30 (figure 21).

33
Source: http://dots.umd.edu/parking/maps/map_campus.pdf

Annotations added study team.

Figure 20. Map. Location of UMD parking lot paving projects.

34
Original image: ©2015 Google®; map annotations provided by University of Maryland

Figure 21. Map. Location of Hampstead Bypass project.

(5)

UMD PARKING LOT XX1

UMD Parking Lot XX1 is across Paint Branch Drive from the Civil Engineering Department’s 

Pavement Materials Laboratory. The August 2007 paving work was to patch a large trench from 

storm drain replacement. Paving consisted of both a base and surface course. The paving 

contractor for the job was College Park Paving (foreman: Mr. Dennis Wilder). 

Construction was begun just as Phase II of this project got underway, so there was insufficient 

time to prepare any tags for the base course paving and only a limited number of tags were ready 

in time for placement in the surface course. Six Alien® 2x2 and six Alien® 1x1 tags were preplaced on top of the previously paved HMA base course and/or milled existing pavement. Preplacement was performed in this initial trial so that the locations of the tags could be determined 

precisely during post-construction reading. The tags and their locations are summarized in 

table 6 and figure 22. 

All tags were successfully heat tested at 347 °F (175 °C) for 1.5 h prior to placement in the field. 

Initially, half of the tags were placed before application of the tack coat (figure 23). However, 

because of the risk of sticky tags being picked up by the tires on the asphalt delivery trucks, the 

remaining tags were placed immediately ahead of the paver as it approached (figure 24). The 

35
tags were then covered with a 2-inch (50-mm) thick lift of 0.5-inch (12.5-mm) surface mix by 

the paver (figure 25) and compacted under the rollers. In a few locations, the surface lift 

thickness was less than 2 inches (50 mm). None of the tags protruded above or were visible 

within the pavement surface after compaction.

Table 6. RFID tag identification in UMD Parking Lot XX1.

Tag Type Label Digital Signature

Alien® 1x1

2 0200989E

3 0300ABAF

4 04003238

5 05000109

6 0600545A

7 0700676B

Alien® 2x2

AB 01ABC94C

AD 01ADA98A

BD 01BDBBBB

BE 01BE8BD8

CA 01CAB5CB

CE 01CEF54F

Original image: ©2015 Google®; map annotations provided by University of Maryland

Note: Locations are approximate. Image predates August 2007 paving; the HMA patch evident in the 

image is not the patch in which the encapsulated RFID tags were embedded.

Figure 22. Photo. Location of pre-placed RFID tags in UMD Lot XX1.(6)

36
Figure 23. Photo. Pre-placement of tags at UMD Lot XX1 paving project.

Figure 24. Photo. Paving over pre-placed encapsulated tags.

37
Figure 25. Photo. Encapsulated tag beneath paver.

The tags were read in the field a few days after construction. A rolling support for the electronics 

was improvised using a plastic laboratory cart with one RFID antenna secured using nonmetallic 

rope to cantilevered wooden boards. The RFID reader and laptop computer were also placed on 

the cart. Power was supplied from an automobile via a power inverter and long extension cable. 

The cart was manually pushed in overlapping passes over the paved area. Figure 26 illustrates 

the final improvised apparatus for reading the RFID tags in the UMD parking lots. One 

complication was that Parking Lot XX1 was placed back in service immediately after paving, so 

the read evaluation had to be conducted at night when there were few parked cars.

The read success rate was evaluated at two antenna heights of 32 inches (810 mm) and 10 inches

(250 mm) above the pavement surface. At the time of the field data collection, a portion of the 

parking lot containing one each of the Alien® 2x2 and Alien® 1x1 tags was fenced off and 

inaccessible, leaving only five each of the 2x2 and 1x1 tags available for evaluation. Details of 

the read success for all of the tags are given in table 7. The read success rate at the 32 inches

(810 mm) antenna height was 100 percent for the Alien® 2x2 tags (i.e., all five of the 2x2 tags 

could be read), and 0 percent for the Alien® 1x1 tags. The lower 10-inch (250-mm) antenna 

height yielded better results, with 100 percent of the Alien® 2x2 tags and 40 percent (i.e., two of 

the five) of the 1x1 tags successfully read.

38
Figure 26. Photo. Hand cart for reading RFID tags in UMD parking lots with antenna in 

the lower position (10 inches above pavement surface).

Table 7. Read success for RFID tags in UMD Parking Lot XX1.

Tag 

Type Label Digital Signature

Read From 

32-Inch

Height?

Read From 

10-Inch

Height?

Alien®

1x1

2 0200989E No No

3 0300ABAF No No

4 04003238 No Yes

5 05000109 No No

6 0600545A Inaccessible Inaccessible

7 0700676B No Yes

Alien®

2x2

AB 01ABC94C Yes Yes

AD 01ADA98A Yes Yes

BD 01BDBBBB Yes Yes

BE 01BE8BD8 Inaccessible Inaccessible

CA 01CAB5CB Yes Yes

CE 01CEF54F Yes Yes

1 inch = 25.4 mm

39
UMD PARKING LOT EE

This parking lot is immediately adjacent to the Pavement Materials Laboratory. Similar to the 

work on Parking Lot XX1, paving consisted of base and surface courses to patch a large trench 

from storm drain replacement. This paving was originally scheduled for late September 2007. 

However, construction was subsequently delayed until October. The 4-inch (100-mm) thick layer 

of 0.75-inch (19-mm) dense-graded base mix was placed on October 16; the 2-inch (50-mm) 

thick lift of 0.5-inch (12.5-mm) dense-graded surface mix was paved the following day, October 

17. The paving contractor for the job was College Park Paving (foreman: Mr. Dennis Wilder). 

Two methods of tag placement were employed in Lot EE. For the base lift, 10 each of the 

Alien® 1x1 and 2x2 tags were pre-placed ahead of the paver, and an additional 10 each of both 

tag sizes were placed in the paver hopper and run through the paver. For the surface course, 

10 each of both tag sizes were tossed in the paver hopper and run through the paver; none of the 

tags was pre-placed ahead of the paver for the surface lift. All tags were compacted into the mat 

by rollers behind the paver. A total of 40 tags were placed in the base course and 20 in the 

surface layer.

After paving of the surface lift was complete, the mobile cart with antenna, RFID reader, and 

computer (figure 26) was used to evaluate the read success rate for the tags. Based on the 

findings from Lot XX1, the height of the antennae above the pavement surface was kept constant 

at approximately 10 inches (250 mm). The read success rates for the different tag sizes as a 

function of layer (base versus surface) and method of placement (pre-placed versus through-thepaver) are summarized in figure 27. In this figure, “Placed” refers to the pre-placed tags (base lift 

only), and “Paver” designates the tags tossed into the pavement hopper (both base and surface 

lifts). Some key observations that can be drawn from figure 27 include the following:

• The Alien® 1x1 “Paver” tags in the base lift had a higher read success rate (70 percent) 

than did the same size tags placed in the surface lift (40 percent), despite the fact that the 

surface lift was at a shallower depth and thus closer to the antenna and had less potential 

for signal attenuation through the HMA. It is believed that this simply illustrates the high 

variability inherent in the small format Alien® 1x1 tags.

• The Alien® 2x2 “Paver” tags in the base lift had a slightly lower read success rate 

(90 percent) than did the same size tags placed in the surface lift (100 percent). This 

matches physical reasoning, but again the discrepancy could also be simply due to 

variability among the different sets of tags.

• The discrepancies between the read rates for the Alien® 1x1 and the 2x2 tags in the base 

lift was greater for the “Placed” set (100 percent versus 10 percent) than for the “Paver”

set (100 percent versus 70 percent). There is no objective physical reason for this because

none of the pre-placed tags was observed to be damaged by truck and/or paver tires, etc. 

Again, this may simply be a consequence of variability among the different sets of tags.

• Overall, the Alien® 1x1 tags had an average read success rate of about 40 percent while 

the larger Alien® 2x2 tags had a much higher read success rate of more than 95 percent.

These rates are comparable to those observed in Lot XX.

40
Some of the tags in Lot EE were observed to have migrated to the surface of the mat. While no 

tags were seen on the surface of the finished base course, one of the small tags and three of the 

larger tags were observed at the top of the surface course. Examples are shown in figure 28 and 

figure 29. Other than aesthetics, it is unclear whether these surfaced tags will have any 

detrimental effect on the performance of the pavements. They arguably could provide a 

preferential pathway for local intrusion of water into the asphalt that could produce accelerated 

stripping or other problems. This issue should be investigated further in the future.

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.

1x1

Paver, 

AC Surface

1x1

Paver,

 AC Base

1x1 

Paver,

 All courses

2x2

Paver,

 AC surface 2x2

Paver,

AC Base

2x2

Paver, 

All Courses

1x1

Placed,

AC Base

2x2

Placed, 

AC Base

All tags

Placed,

All Courses

All tags

Paver,

All Courses

0%

20%

40%

60%

80%

100%

 

Percentage Reads

1x1

Paver, 

AC Surface

1x1

Paver,

 AC Base

1x1 

Paver,

 All courses

2x2

Paver,

 AC surface 2x2

Paver,

AC Base

2x2

Paver, 

All Courses

1x1

Placed,

AC Base

2x2

Placed, 

AC Base

All tags

Placed,

All Courses

All tags

Paver,

All Courses

0%

20%

40%

60%

80%

100%

 

Percentage Reads

2x2 Tag

 

41
Figure 29. Photo. Worst-case example of surfaced RFID tag in Lot EE.

UMD PARKING LOT T

This parking lot is near the Pavement Materials Laboratory. Paving conditions are similar to 

those for Lots XX1 and EE, although the area of patch is smaller, and therefore only a few tags 

were placed. This area was paved in late October 2007. Results were comparable to those from 

Lot XX1 and Lot EE.

HAMPSTEAD BYPASS/MD 30

The Hampstead Bypass project lies to the east of MD 30 around the town of Hampstead, MD 

(figure 30). The route runs from south of Wolf Hill Drive to north of the town of Hampstead.

The project included construction of two lanes of MD 30 on new alignment for approximately 

4.4 mi (7 km). The new alignment incorporates three roundabouts: one near the southern 

terminus to provide a connection to existing MD 30; one at MD 482; and one near the northern 

terminus to provide a connection to existing MD 30. 

42
Original image: ©2015 Google®; map annotations provided by University of Maryland

Figure 30. Map. Location of Hampstead Bypass project with star marking approximate 

location of southern entrance to construction site.

(5)

The new pavement construction consisted of two 4-inch (100-mm) thick base lifts and a 2-inch

(50-mm) surface layer. Nominal maximum sizes for the HMA mixtures were 0.75 inches

(19 mm) for the base lifts and 0.5 inches (12.5 mm) for the surface layer. Project specifications 

called for a material transfer vehicle (MTV) as an intermediary between the unloading trucks and 

the paver. Because this project involved multiple lifts and was scheduled to be closed to traffic 

for several months after paving, it was ideal for detailed field evaluations.

A significant problem developed with regard to tag availability prior to construction. The smaller 

Alien® 1x1 tags were taken out of production by Alien Technologies. A search of RFID tag 

suppliers identified several alternatives. The most promising of these were an approximately 

1 by 2 inches (30 by 50 mm) “Rafsec® Web” tag from UPM Raflatac® (figure 31—see also 

http://www.upmraflatac.com/). Sample quantities of these tags were ordered for laboratory 

evaluation. The UPM Raflatac® tags had the advantage that they could still be curled into the 

pipe molds similar to the Alien® 1x1 tags. Laboratory read performance of the UPM Raflatac®

tags was comparable to, and in some cases slightly better than, that for the Alien® 1x1 tags. The 

read performance of the UPM Raflatac® tags was still lower than for the larger Alien® 2x2 tags, 

however.

43
Figure 31. Drawing. UPM Raflatac® RFID tag.

The Hampstead Bypass project was constructed in phases, the first phase of which was the leg 

near the southern terminus with MD 30 (figure 32). Construction delays postponed the start of 

paving until November 2007, and as a consequence, only the lower base lift could be placed 

before the end of the construction season. Both UPM Raflatac® and Alien® 2x2 tags were 

placed in this lower 4-inch (100-mm) base lift. Additional Alien 2x2 tags were placed in the 

upper 4-inch (100-mm) base lift in April 2008 at the start of the new construction season. All 

tags were placed in the section of pavement just north of the lane merge at the southern terminus 

roundabout. This is designated as the “Study Area” in figure 33.

44
University of Maryland

Image from http://www.sha.state.md.us/WebProjectLifeCycle/ProjectMaps.asp?projectno=CL416536# with annotations by 

Figure 32. Photo. Hampstead Bypass project site.

. 
Image from 

http://www.sha.state.md.us/WebProjectLifeCycle/ProjectMaps.asp?projectno=CL416536# 

with annotations by the University of Maryland

Figure 33. Photo. Magnified view of study area at the Hampstead Bypass project site

(boxed area in figure 32).

November 2007 Paving

Both UPM Raflatac® and Alien® 2x2 tags were placed in the lower base lift of the southbound 

travel lane in the study area (figure 33) during paving on November 28, 2007. Paving and tag 

placement began at the lane merge at the southern edge of the study area and proceeded 

northward. Note that the MTV was not used for the lower base lift because it was too heavy for 

the unprotected aggregate base. 

The experimental plan for this field trial was as follows:

1. Ten Alien® 2x2 tags with prerecorded digital IDs were placed into each of six sequential 

truckloads. The tags were placed between the second and third drop in each load. The 

license plate number of the truck was recorded by a student research assistant and 

46
reported by telephone to other student research assistants at the job site awaiting its 

arrival.

2. Upon arrival of each tagged truck at the paving site, the license plate number of the truck 

and the station and GPS coordinates at which it began unloading into the paver were 

recorded. The GPS coordinates were recorded both with a conventional handheld GPS 

transceiver (Garmin® GPS-12) and with a GPS logger (Pocket Track Pro Magnetic from 

Brickhouse® Security) cross-referenced by time stamp. A log of all tag locations is 

provided in table 8.

3. Steps 1 and 2 were repeated using 40 UPM Raflatac® tags (10 each in 4 sequential 

trucks).

4. The mat was inspected visually for surfaced tags. Although few tags were observed at the 

surface after extrusion of the mat behind the paver, more were observed on the surface 

after compaction. 

47
Table 8. Log of tags in lower 4-inch (100-mm) base lift at Hampstead Bypass project (Novemb

Truck 

Number

Truck 

License 

Plate

Tag 

Size 

(inches)

Tag 

IDs

Time at 

Unload

Station 

at 

Unload

Coordinates of Unload Point

Handheld GPS GPS 

N W N 

1 109-ED97 2x2 1–10 02:00pm 320+50 39o 44' 59.6'' 76o 50' 44.1'' 39° 34'5 9.6431" 

2 039-ED20 2x2 11–20 02:04pm 321+00 39o 35' 00.0'' 76o 50' 44.6'' 39° 34' 59.7440" 

3 152-ED09 2x2 21–30 02:09pm 321+50 39o 40' 70.8"* 76o 22' 37.0''* 39° 35' 00.1638" 

4 127-ED60 2x2 31–40 02:21pm 322+50 39o 35' 01.0''* 76o 50' 774''* 39° 35' 00.6391" 

5 052-ED56 2x2 51–60 02:30pm 323+00 39o 35' 01.0'' 76o 50' 47.0'' 39° 35' 01.0212" 

6 152-ED10 2x2 41–50 02:43pm 325+50 39o 35' 02.4'' 76o 50' 49.8'' 39° 35' 02.3407" 

1 162-ED77 1x2 1–10 02:45pm 326+25 39o 35 '02.6'' 76o 50' 50.4'' 39° 35' 02.4377" 

2 155-ED61 1x2 11–20 02:50pm 328+50 39o 35' 03.9'' 76o 50' 53.2'' 39° 35' 02.5480" 

3 039-ED17 1x2 21–30 — — — — — 

4 092-ED62 1x2 31–40 03:02pm 329+50 39o 35' 04.2'' 76o 50' 54.3'' 39° 35' 04.2766" 

* Indicates coordinates were read with a different GPS device

— Indicates no data collected

Note: Italics indicates possible error in data recording

1 inch = 25.4 mm

48 
The project team returned to the Hampstead Bypass site on December 3 for preliminary read 

trials. The vehicle-mounted read system consisted of an adjustable wooden frame suspending the 

antennae above the pavement surface behind the test vehicle (figure 34). A slow vehicle speed of 

less than about 5 mi/h (8 km/h) was maintained for all trials. The antennae were arranged with 

the transmitter sides inboard (i.e., toward the centerline of the car) and the receiver ends 

outboard. Two antenna heights of approximately 3 inches (75 mm) and 12 inches (300 mm) were 

evaluated. Because the limited tag read range and antenna configuration made it unlikely that the 

entire lane width could be read successfully from a single position, three vehicle passes along the 

southbound travel lane were made for each antenna at each height. Note that a production data 

collection system could be designed with a wider antenna array that would minimize or eliminate 

the need for multiple passes.

Figure 34. Photo. Vehicle-mounted antennae and RFID reader.

Key observations from the read trials include the following:

• No overlap of tags was observed—i.e., the tags were ordered in the same order as the 

truck deliveries to the paver.

• For the Alien® 2x2 tags, six tags that were detected at the 3-inch (75-mm) antenna height 

were not detected at the 12-inch (300-mm) height, and 12 tags detected at the 12-inch

(300-mm) height were not detected at the 3-inch height.

• For the UPM Raflatac® tags, three tags each were detected from one antenna height but 

not from the other antenna height.

49
• One truck containing UPM Raflatac® tags (tag numbers 21 to 30) was “lost” at the job 

site during paving, and the station location at which it unloaded was not recorded. 

However, from the RFID tag read, it was confirmed that it unloaded between the trucks 

containing tags 1 to 10 and 11 to 20. This confirms the effectiveness of RFID in 

providing a definitive location for the load when manual methods fail for any reason

(paper record errors, miscommunication, etc.).

• Fifteen percent of the Alien® 2x2 tags were observed at the surface of the base lift.

• No UPM Raflatac® tags were observed at the surface of the lift.

• For the UPM Raflatac® tags, 10 percent or more of the tags in all truckloads were 

detected at both antenna heights (figure 35).

• For the Alien® 2x2 tags, 30 percent or more of the tags in all truckloads were detected at 

the 3-inch (75-mm) antenna height, and 50 percent or more of the tags in all truckloads 

were detected at the 12-inch (300-mm) antenna height (figure 36).

• Overall read success rates were slightly less than 20 percent for the UPM Raflatac® tags,

and approximately 60 percent for the larger Alien® 2x2 format (figure 37).

Figure 35. Chart. Percentage of UPM Raflatac® tags read in each truck versus height of 

antennae (Hampstead Bypass, November 2007).

Tags Percentage

Read

50
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).

April 2008 Paving

Thirty-two Alien® 2x2 tags were placed in the upper base lift of the northbound travel lane in 

April 2008. The experimental plan for this field trial was similar to that for the lower base lift Truck1-10 Truck11-20 Truck21-30 Truck31-40 Truck41-50

3 inch

Truck51-60

12 inch

(3" U 12")

80%

80%

100%

80%

60%

60%

80%

80% 70%

60%

60% 50%

60% 50%

90%

70%

40%

30%

0%

20%

40%

60%

80%

100%

Tags Percentage 

Read 

Trucks

Height of Antenna

3in

12in

1x2

2x2

56.7%

66.7%

17.5%

17.5%

0%

20%

40%

60%

80%

100%

Percentage of Tags Read

Antenna Height 

Tag 

Dimension

51
placed the preceding November: eight Alien 2x2 tags with prerecorded digital IDs were placed 

into each of four sequential truckloads, and spatial location of each truck along the alignment 

during unloading was recorded. A key difference for the upper base lift paving was the use of the 

MTV. The RoadTec® SB-2500D MTV used on this project (figure 38) is more than 50 ft (15 m) 

long and has a 25-T (22.7-t) surge capacity; potential spatial lag and mixing of HMA truckloads 

because of the use of the MTV were among the issues evaluated in this field trial.

Figure 38. Photo. RoadTec® SB-2500D material transfer vehicle used in April 2008 paving 

at the Hampstead Bypass project.

The vehicle-mounted read system (figure 34) was again used to scan the tags immediately after 

construction. The antenna configurations were similar to those in the November 2007 trials 

except that only the lower 3-inch (75-mm) antenna height was used, and the influence of antenna 

orientation (receive sides inbound/outbound) was evaluated. Three passes (edge, centerline, and 

edge of lane) were performed at each of several vehicle speeds. Additional passes were made 

over the southbound travel lane containing the tags placed during the November 2007 paving to 

ascertain whether they were still functioning and readable. 

The delivery and read locations for all tags that could be read are summarized in figure 39. 

Overall, 78 percent of the Alien® 2x2 tags placed in the upper base lift could be found by the 

reader; this is a slightly higher percentage than for the lower base lift paved the preceding 

November. GPS coordinates were not recorded during this field trial, so instead, all position 

information is referenced to station. The station at which the haul truck began unloading into the 

MTV defines the beginning of the delivery range, and the station at which the unloaded haul 

truck pulled away from the MTV defines the end. Read locations are recorded only within a 

station (100 ft (30 m)) interval, although many of the tag locations could be pinpointed more 

precisely. The data in figure 39 indicate that most of the tags were found in roughly the correct 

52
sequence in the completed mat. The fact that the MTV itself is more than 50 ft (15 m) long and 

that it can carry (and potentially mix) more than one truckload of HMA means that there will 

inevitably be a spatial lag of unknown length between the truck unloading range and the final 

location of the tags in the mat. Tag IDs in bold italics in figure 39 indicate tags that were offset 

more than one station interval from the delivery range; 80 percent of the tags were found within 

one station interval of their delivery, with the longest offset of the remaining 20 percent between 

four to five stations (tags 81, 90).

Note: Bold italics identify tag IDs that are displaced more than one station (100 ft (30 m)) from their 

delivery location.

Figure 39. Chart. Delivery and read locations for RFID tags paved into the upper base lift 

at the Hampstead Bypass (April 2008). 

Note that even without the MTV, there will always be a significant spatial distribution of tags 

from a given truckload along the alignment. One truckload of HMA for a 4-inch (100-mm)-thick 

lift corresponds to approximately 70 lane-ft (21 lane-m) of paving; tags in the truckload can end 

up anywhere along this length. This lack of spatial resolution—even when magnified by use of 

an MTV—is not significant in practical terms because the material properties from the sampled 

truckload are intended to represent an entire lot of material (e.g., 1,000 T (907 t), corresponding 

to about 0.5 lane-mi (0.8 lane-km) of paving).

Some of the tags in figure 39 are in the incorrect sequence. For example, tag 81 from the first 

truckload was found in the same interval of pavement as tags 106, 110, and 111 from the fourth 

truck. Similarly, tag 90 from the second truck and tags 101 and 103 from the third truck appear 

in the same interval as tag 105 from the fourth truck. This may be due to the variable nature of 

the spatial lag between delivery and read location, or it may be a consequence of mixing of HMA 

from different loads in the MTV. Regardless of the cause, this incorrect sequencing would not be 

an issue for production use when only random (as opposed to sequential) truckloads would be 

tagged.

Additional key observations drawn from the read trials in April 2008 include the following:

• As summarized in figure 40, the read success rate was significantly better when the dual 

antennae were oriented with their receive (R) ends inboard (and therefore their transmit

(T) ends outboard). Placing the transmit ends of the antennae outboard may provide a 

better distribution of incoming RF energy to the tags. 

• Read success rate decreased slightly with increasing vehicle speed. As shown in 

figure 41, the read success rate at 45 mi/h (72 km/h) was approximately 65 percent of the 

rate at slow speeds. 

Station:

Delivery Location:

Read Location:

320 321 322 323 324 325 327

105,107,108, 

109

90,101,103, 

105 112

326

85,86 84,88,92,93, 

94,95,98 99,100,102 81 ,106,110, 

111

81-88 89-96 97-104 105-112

53
• The read success rate for the Alien® 2x2 placed in the southbound lane paved the 

preceding November was approximately 60 percent when read in April. This was 

approximately equal to the read success rate during the initial reading in early December 

2007, suggesting little degradation of the embedded RFID tags during the intervening 

4 months.

R = receive

Figure 40. Chart. Influence of antennae orientation on read success rate.

1 mi/h = 1.6 km/h

Figure 41. Graph. Influence of vehicle speed on read success rate. 

0%

10%

20%

30%

40%

50%

60%

70%

80%

R Outboard R Inboard

Antenna Configuration

Read Success Rate

0%

20%

40%

60%

80%

100%

0 10 20 30 40 50

Vehicle Speed (mph)

Read Success (Relative to 0 mph)

Vehicle Speed (mi/h)

Read Success (Relative to 0 mi/h)

54
CONCLUSIONS

Field trials at several projects confirmed the very high survival rate of the encapsulated tags. 

Read success rates varied significantly with tag size and less significantly on other details such 

antenna configuration and vehicle speed. Nonetheless, the field trials consistently demonstrated 

that post-construction read success rates of 60 to 80 percent or higher are achievable from a 

bumper-mounted antenna array, even on a vehicle moving at traffic speeds. A major secondary 

advantage of the approach is its minimal intrusion in the usual paving construction sequence. 

The only potential drawback observed was the occasional surfacing of tags at the top of the 

compacted mat. All surfaced tags were aligned parallel to the mat surface; no tags were observed 

in an upright orientation protruding above the mat in any of the trials.

55

CHAPTER 4: EVALUATION OF SURFACED TAGS

INTRODUCTION

During field trials for tracking HMA placement described in chapter 3, a small number of the 

RFID tags rose to the surface of the compacted pavement. This raised the question of whether 

this would compromise the durability of the pavement by increasing water infiltration or 

decreasing density locally. 

The in-place permeability and density in the local area surrounding surfaced RFID tags were 

measured to answer this question. The assumption in this evaluation is that if the permeability 

and density of the pavement around the surfaced tags are similar to that in other areas, it can be 

assumed that the surfaced tags will not compromise the integrity of the pavement. All of the 

density and permeability tests were conducted in the UMD Parking Lot EE, where multiple tags 

surfaced in the 2-inch (50-mm)-thick lift of 0.5-inch (12.5-mm) surface mix (see figure 42).

Original image: ©2015 Google®; map annotations provided by University of Maryland

Figure 42. Photo. Location of permeability and density tests at parking Lot EE at UMD.

(7)

DENSITY TESTING

Methodology

In-place density measurements were obtained using the Troxler® Model 3440 nuclear density 

gauge shown in figure 43. Dr. Nelson Gibson and Mr. Dennis Sixbey of the Federal Highway 

Administration (FHWA) Turner-Fairbank Highway Research Center (TFHRC) provided the 

nuclear density gauge and performed the readings at the UMD campus. Mr. Sixbey is a certified 

nuclear gauge technician as well as the Radiation Safety Officer at the TFHRC. Testing was 

conducted on July 29, 2009, under generally clear weather conditions.

All nuclear density measurements were conducted in the backscatter mode. It was not possible to 

calibrate the nuclear gauge because the mix properties were unknown. As a consequence, the 

absolute density measurements would not be accurate. However, because the main focus of these 

tests is the relative density near the surfaced tag relative to the density at some distance away, an 

accurate absolute density reading is not necessary. Two readings were recorded on top of each 

tag, and 4 additional readings were recorded at distances of approximately 5 inches (125 mm), 

9 inches (225 mm), and 16 inches (400 mm) away from the tag (see pattern in figure 44) for a 

total of 98 readings. Another eight readings were taken at random locations remote from any of 

57
the tags. All density measurements were based on 1-min readings. Care was taken to ensure that 

no vehicles, people, or other potential sources of interference were near the nuclear gauge during 

the readings. Some of the readings may have suffered some indeterminable loss of accuracy 

when the roughness of the asphalt surface made it difficult to completely stabilize the device.

Figure 43. Photo. Troxler® Model 3440 nuclear density gauge.

Figure 44. Diagram. Location of tests relative to tag.

Density Results

Figure 45 through figure 51 summarize the full set of density readings taken on top of and 

around each tag. These graphs also indicate which readings might be compromised because of 

irregularities in the pavement surface. 

A linear regression analysis of density versus distance from the surfaced tag was performed for 

each set of test results. The results are shown as the trend lines in figure 45 through figure 51. 

The regression line was fit to the entire density data at each distance. However, the slopes of 

density trends versus distance are the key indicator of interest. The slopes ranged from a 

minimum of 0.03 for Tag 6 (i.e., essentially no variation of density with distance) to a maximum 

of 0.18 for tag 3 (i.e., modest variation of density with distance).

Test Location

RFID Tag

5 

16 

9 

58
There are two reasons to suspect that the measurements directly on top of the tags (i.e., radial 

distance r equal to 0) may be biased: 1) the tags themselves have lower density than the HMA, so 

even if the HMA were completely uniform surrounding the tag, the measurements directly on the 

tag would indicate a lower density for the zone; and 2) the surface irregularities directly 

surrounding the tag made it more difficult to place the nuclear gauge in a stable configuration 

directly on top of the tags than in locations away from the tags. To investigate this potential bias, 

the regression analyses were rerun with the points at r = 0 removed. The slopes for the trend lines 

with the r = 0 data retained and with the r = 0 data removed are compared in table 9. It is clear 

that removing the data at r=0 significantly reduces the slope of the density versus distance trend, 

with some tags now even showing a decrease in density with increasing distance (i.e., tags 5 

and 7). The average slope of the trend lines across all tags drops from 0.09 when the r = 0 data 

are retained to 0.03 when the r = 0 data are removed. In either case, these small slope values 

suggest very little impact of the tags on in-place density. 

As a further check, t- and F-tests were conducted to determine whether there were any 

statistically significant differences in density at different distances from the tags. These tests 

compare the means (t-test) and variances (F-test) of two groups of data. 

Data for all tags were combined for the purposes of performing the t- and F-tests. To compensate 

for normal spatial variability of in-place density, the measured density at each location for a 

given tag was normalized by the average of all density readings for that tag. Any remaining 

spatial variability after this normalization can then be attributed to distance from the tag. The 

t- and F-tests were conducted in pairs of datasets: r = 0 (i.e., on top of the tag) and r = 5 inches

(125 mm); r = 0 and r = 9 inches (225 mm); r = 0 and r = 16 inches (400 mm); and r = 16 inches

(400 mm) and random far-field readings. The results of the t- and F-tests are shown in table 10. 

The tcrit and Fcrit values in the table are for a significance level =0.01. In all but one case, both 

the t- and F-test statistics are smaller than the critical values, indicating that the differences in the 

means and variances respectively of the two datasets in each pair are not statistically significant.

The only exception is the 0 versus 125 mm (5 inches) pair, where the F-test is satisfied but the 

t value slightly exceeds tcrit. The overall conclusion is that there is very little statistical difference 

between the density measurements at the various locations from the tag.

α

59
pcf = pounds per cubic ft

1 inch = 25.4 mm

Figure 45. Graph. Density as a function of radial distance for tag 1 (slope=0.12). 

pcf = pounds per cubic ft

1 inch = 25.4 mm

Figure 46. Graph. Density as a function of radial distance for tag 2 (slope=0.04). 

R2 = 0.06

137

138

139

140

141

142

143

144

145

146

147

0 5 10 15 20

Distance from Tag (in)

Density Reading (pcf)

On Tag Stable

On Tag Unstable

South Stable

South Unstable

West Stable

West Unstable

North Stable

North Unstable

East Stable

East Unstable 

R2 = 0.0092

143

144

145

146

147

148

149

150

151

152

0 5 10 15 20

Distance from Tag (in)

Density Reading (pcf)

On Tag Stable

On Tag Unstable

South Stable

South Unstable

West Stable

West Unstable

North Stable

North Unstable

East Stable

East Unstable

 

60
pcf = pounds per cubic ft

1 inch = 25.4 mm

Figure 47. Graph. Density as a function of radial distance for tag 3 (slope=0.18). 

pcf = pounds per cubic ft

1 inch = 25.4 mm

Figure 48. Graph. Density as a function of radial distance for tag 4 (slope=0.11). 

R2

 = 0.5066

144

145

146

147

148

149

150

0 5 10 15 20

Distance from Tag (in)

Density Reading (pcf)

On Tag Stable

On Tag Unstable

South Stable

South Unstable

West Stable

West Unstable

North Stable

North Unstable

East Stable

East Unstable

 

R2

 = 0.0867

141

142

143

144

145

146

147

148

149

150

151

0 5 10 15 20

Distance from Tag (in)

Density Reading (pcf)

On Tag Stable

On Tag Unstable

South Stable

South Unstable

West Stable

West Unstable

North Stable

North Unstable

East Stable

East Unstable

 

61
pcf = pounds per cubic ft

1 inch = 25.4 mm

Figure 49. Graph. Density as a function of radial distance for tag 5 (slope=0.04). 

pcf = pounds per cubic ft

1 inch = 25.4 mm

Figure 50. Graph. Density as a function of radial distance for tag 6 (slope=0.03). 

R2 = 0.0172

143

144

145

146

147

148

149

150

0 5 10 15 20

Distance from Tag (in)

Density Reading (pcf)

On Tag Stable

On Tag Unstable

South Stable

South Unstable

West Stable

West Unstable

North Stable

North Unstable

East Stable

East Unstable

 

R2 = 0.0021

138

140

142

144

146

148

150

152

154

156

0 5 10 15 20

Distance from Tag (in)

Density Reading (pcf)

On Tag Stable

On Tag Unstable

South Stable

South Unstable

West Stable

West Unstable

North Stable

North Unstable

East Stable

East Unstable

 

62
Pcf = pounds per cubic ft

1 inch = 25.4 mm

Figure 51. Graph. Density as a function of radial distance for tag 7 (slope=0.08). 

Table 9. Slopes of in-place density versus distance trend lines with and without data at 

r = 0.

Tag

Slope

With r = 0 Data 

Points

Without r = 0 Data 

Points

1 0.12 0.05

2 0.04 0.02

3 0.18 0.15

4 0.11 0.10

5 0.04 -0.08

6 0.03 0.06

7 0.08 -0.08

Average 0.09 0.03

r = radial distance

Table 10. The t- and F-test results for in-place density tests. 

Combination t tcrit F Fcrit

0 versus 5 inches 2.833 2.704 1.265 4.06

0 versus 9 inches 1.741 2.704 1.538 4.06

0 versus 16 inches 2.173 2.704 3.417 4.06

16 inches versus far field 0.465 2.727 1.049 3.86

1 inch = 25.4 mm

R2 = 0.0332

140

142

144

146

148

150

152

154

0 5 10 15 20

Distance from Tag (in)

Density Reading (pcf)

On Tag Stable

On Tag Unstable

South Stable

South Unstable

West Stable

West Unstable

North Stable

North Unstable

East Stable

East Unstable

 

63
Conclusions Regarding In-Place Density

The linear regression analyses of density versus distance at each tag produced very small slope 

and R2 values in nearly all cases. These both imply little or no relationship between density and 

distance from the RFID tag. In other words, there do not appear to be any localized variations in 

in-place density caused by the RFID tags.

The t-tests of the pooled in-place density measurements for all distance combinations except the 

0 versus 5 inches (125 mm) case found that any differences in the means were not statistically 

significant. Even for the 0 versus 5 inches (125 mm) case, the t-statistic exceeded the tcrit value at 

the 0.01 significance level by only a very small margin. The F values were smaller than Fcrit for 

all distance combinations, indicating that any differences in variance are not statistically 

significant. As with the linear regression results, the t- and F-test results suggest that there are no 

localized variations in in-place density caused by the RFID tags.

PERMEABILITY TESTING

Methodology

In-place permeability tests were conducted on each of the seven surfaced tags using an National 

Center for Asphalt Technology (NCAT) (Auburn University) field permeameter. The device is 

centered over the tag and measures the permeability over a diameter of approximately 

5.75 inches (145 mm). Seven additional tests were conducted at random locations in the parking 

lot far from any tags. 

The procedure used to conduct the in-situ permeability tests followed the test protocol developed 

by NCAT.

(8) As shown in figure 52, the permeameter consists of four tiers of different diameter 

cylinders separated in two sections. The sealant used for these tests was plumber’s putty. A small 

1 ft (0.3 m) square area was identified and brushed clear of debris. A thin layer of the moldable 

sealant was applied to the rubber gasket on the base plate of the permeameter. Next, a uniform 

0.5-inch (12.5-mm)-thick layer of moldable sealant is applied approximately 3 inches (76.2 mm)

around the outside diameter on the base plate. Some sealant was reused in other tests after slicing 

off the top part contaminated by debris. The permeameter is carefully placed on the asphalt test 

area so that the rubber gasket surrounds the outside diameter of the base plate. Uniform foot 

pressure is then applied around the perimeter of the base to create a watertight seal with the 

asphalt. 

Many tests were redone because of concern that water observed outside the test area was a leak 

in the sealant rather than lateral drainage through the HMA. It was sometimes difficult to create a 

watertight seal because the pavement was uneven. In an effort to improve the seal, four 5-lbf

(22.25 N) weights were distributed on the base plate to compensate for the head pressure from 

the water column. Extra weight was exerted by placing four bricks on the base plate as shown in 

figure 52.

A thin layer of sealant was used to connect the two sections of the permeameter. The filling tube 

assembly was inserted all the way to the bottom, and water was added at a steady rate while 

minimizing bubbles. Water was added until it filled a tier that made it possible for accurate 

64
observation of head drop. The time required for the water to drop a given distance in the selected 

tier was recorded. 

Figure 52. Photo. In-place permeability test setup.

Using the measured time and distance for the water drop, the coefficient of permeability was 

calculated using the falling head permeability equation shown in figure 53:

Figure 53. Equation. Permeability determination from falling head permeability test.

where:

k = coefficient of permeability.

a = inside area of standpipe (depends on tier used for testing).

L = thickness of asphalt mat.

A = area of permeameter base through which water can flow into the pavement.

h1 = initial head.

h2 = final head.

t = elapsed time between h1 and h2.

Permeability Results

Figure 54 summarizes the results of the 14 permeability tests, which consisted of 7 tests on top of 

the surfaced RFID tags and 7 random readings far from the tags. Only the reading on top of tag 1 

showed a more permeable surface compared with all the other readings. This could be caused by 

segregation because larger size aggregates were observed on the surface at this location only. 

Excluding this tag, the readings on top of the RFID tags ranged from 4.92x10-5 to 41.6x10-5

65
inches/s (12.5x10-5 to 105.6x10-5 cm/s), which is very similar to the random far-field readings,

which ranged from 4.76x10-5 to 36.8x10-5 inches/s (12.1x10-5 to 93.4x10-5 cm/s). Statistical tand F-tests were performed to see whether there was any significant difference between the 

means and standard deviations of these two sets of data. The t-test gave a value of t=0.00813

with tcrit=3.055 at a significance level =0.01. The F-test gave a value of F=6.87 and Fcrit=8.89. 

In both cases, the test statistics were less than the critical values, implying no statistically 

significant differences in the means and variances for the in-place permeability values on top of 

the RFID tags versus values at random far-field locations.

1 inch/s = 25.4 mm/s

Figure 54. Chart. Coefficient of permeability on top of the tags and at random locations.

Conclusions Regarding In-Place Permeability 

Based on the very similar ranges in measured permeabilities and the results from the t- and 

F-tests, it is concluded that there is no detrimental effect of the surfaced RFID tags on in-place 

permeability for the HMA.

OVERALL CONCLUSIONS REGARDING SURFACED TAGS

The test results show that there are no practical or statistical impacts on in-place density or 

permeability from the surfaced RFID tags. Consequently, the tags should not be causes of local 

damage due to reduced stiffness/strength (correlated with density) or water inflows (related to 

permeability). Other than aesthetic concerns, the surfaced RFID tags do not appear to have a 

detrimental effect on asphalt pavements.

There is the possibility for long-term deterioration around the tags due to degradation of the 

bonds between the asphalt binder and the CPVC pipe encapsulation. However, qualitative 

observations of the surfaced tags in Lot EE at the time of this writing show no evidence of 

deterioration over the intervening 6 years.

α

0.001056

0.000934

0.000125 0.000121

0.000495 0.000486

0.0000

0.0002

0.0004

0.0006

0.0008

0.0010

0.0012

On Tag Random

Location

Permeability (cm/s)

Highest

Lowest

Average

66
CHAPTER 5: RFID TRACKING OF PCC PLACEMENT

INTRODUCTION

To ensure and ideally to improve the performance of concrete pavements, it is vital that the 

influence of material properties on performance be clearly understood. Correlations between asconstructed properties of PCC in construction databases and field performance in PMSs can 

quantify the link between material quality and pavement performance. 

PCC is produced at a production facility and then trucked to the highway construction site for 

offloading. As part of an overall QA program, PCC producers sample their production 

periodically from delivery trucks as they leave the plant to perform various quality control (QC) 

tests to ensure that the mixture properties remain within acceptable limits. Agencies typically 

take additional samples for quality acceptance testing to corroborate the producer’s QC test 

results and to establish pay factors.

Knowledge of where the sampled truckload of material is deposited along the roadway is critical 

when attempting to correlate as-constructed material properties with measured performance from 

a PMS because pavement management data are typically referenced to a specific spatial location 

(milepoint, latitude/longitude). Unless the PCC QA data can also be tied to a spatial location 

along the pavement, they cannot be correlated accurately with pavement management data.

Similar to the HMA tracking application considered in chapters 2 through 4, sensors based on 

RFID technology could be used to tag truckloads of PCC as they left the production plant. The 

sensors would be cast into the slab during the concrete paving operation. After construction, a 

vehicle-mounted scanner would be used to electronically “read” the identity tags to link them to 

the material properties measured from samples obtained from the truck that brought the concrete 

to that location. The data could then be directly linked to future pavement performance data in 

the agency’s PMS, enabling robust statistical analyses of the correlations between material 

properties and actual performance.

LABORATORY EVALUATION

A preliminary laboratory evaluation of read range was conducted by embedding conventional 

UHF passive RFID tags in 4-inch (100-mm) diameter by 12-inch (300-mm)-high concrete

cylinders. Alien® Gen 2 2x2 and Alien® Gen 2 1x1 tags were encapsulated using the same 

techniques as for the HMA tracking tags and then embedded in the middle of the cylinders in an 

upright position. Two replicates of each tag type were embedded in a one tag per cylinder basis. 

After the tags were embedded, read ranges were measured periodically as the cylinders were 

curing. All readings were conducted using a Mercury® 5 ThingMagic reader. No relationship 

between the curing of the cylinders and the read range of the RFID tags was observed. To 

determine the orientation effect on the readings, the read range was recorded for the cylinders in 

vertical and horizontal positions relative to the antennae. The results are shown in table 11 and 

table 12 for readings taken at 20-s intervals after 13 days of curing. The best read range results 

obtained when the RFID tags where in front of the transmit side of the antenna are given. 

67
Table 11. Read range for vertically positioned cylinders. 

Size

Maximum 

Distance

Number of 

Readings

2x2 3 ft 12

2x2 4 ft 2

1x1 1 ft 5

1x1 1.5 ft 8

1 ft = 0.305 m

Table 12. Read range for horizontally positioned cylinders. 

Size

Maximum 

Distance

Number of 

Readings

2x2 5 ft 26

2x2 1 ft 215

1x1 1 ft 5

1x1 0 0

1 ft = 0.305 m

Based on these results, it can be seen that the larger format 2x2 tags have much longer read 

ranges through concrete compared with the smaller format 1x1 tags. Orientation is also a very 

important factor in the consistency of the readings. The read range for the second replicate of the 

2x2 tags in the horizontal position was only 1 ft (0.3 m). Because the orientation of the tags in 

the field is purely random, it should be anticipated that some of the tags could end up in the 

worst orientation and may not be readable; this appears to be what happened for one of the 

1x1 tags. Nonetheless, these preliminary results show the potential of this application in PCC 

tracking. 

FIELD EVALUATION

The concept of PCC tracking was evaluated in the field in conjunction with the reconstruction of 

a section of the New York State Thruway I-90 outside Syracuse, NY. The Syracuse Project was 

located between exits 39 and 40 on I-90 as shown in figure 55. Three different types of tags were 

studied: Alien® Gen 2 Higgs® 2 2x2, Alien® Gen 2 1x1, and Gen 2 TitanTM tags. A total of 

80 tags were used in this project, with seven Alien® 2x2, seven Alien® 1x1, and six TitanTM tags 

in each truck. 

68
Original image: ©2015 Google®; map annotations provided by University of Maryland

Figure 55. Photo. Location on the Syracuse project where the RFID tags were embedded.

(9)

Methodology

The Syracuse field trial was performed in two steps. The first was the embedment of the RFID 

tags in the concrete pavement, which took place on October 8, 2009. Four sets of tags, each 

consisting of three different types of tag, were used for this project. The Alien® Gen 2 Higgs® 2 

2x2 and 1x1 tags were pre-encapsulated in CPVC pipes with high-temperature epoxy following 

the procedure explained in chapter 2. The tags were curled inside of the CPVC pipes in an effort 

to keep the final product in the size and shape of an aggregate, thus maintaining the integrity of 

the concrete. The TitanTM tags were already encapsulated by the manufacturer to endure high 

humidity and pressure.

The first three sets of tags, each including seven Alien® Gen 2 2x2 tags, seven Alien® Gen 2 

1x1 tags, and six Gen 2 TitanTM tags, were sown in three consecutive trucks as they were being 

loaded with concrete at the plant. These were the last trucks to unload before a bridge deck. After 

unloading, the tags in the concrete mix went through the slip form paver and were finished into 

the 13-inch (325-mm) slab. Some concern was raised about whether the concrete unloaded from 

these three trucks would be cut and replaced with manually finished concrete next to the bridge

deck because bridge obstacles might interfere with the progress of the slip form paver. However, 

it was later confirmed that there was no slip form concrete removed from in front of the bridge. 

The fourth set of tags was sown in the sixth truck after the bridge. The finished pavement with 

the tags embedded is shown in figure 56.

69
The second step was to read the embedded tags after the concrete had cured for 24 days. Two 

antennae were connected to the reader and mounted on the outside of a cargo van at a height of 

approximately 6 inches (150 mm) from the pavement, as shown in figure 57. The antennae each 

contain a receive side and a transmit side. In the laboratory evaluation, the best readings were 

received when the tags were in front of the transmit side of the antenna. Therefore, the most 

efficient way to cover the pavement area was to position the antenna sequence across the width 

as T/Transmit-R/Receive-T/R. Overlapping passes at very low speeds were performed to cover 

the entire width of the pavement. The overlapping passes were repeated three times. The 

pavement area was also manually checked for tags by moving the antennae by hand over the 

pavement surface.

Figure 56. Photo. Finished concrete pavement.

Figure 57. Photo. Antenna configuration.

70
Field Test Results

None of the embedded tags were read in any of the passes. This was not unexpected for the 

Alien® Gen 2 1x1 tags because as shown in table 11 and table 12, their read range was much 

lower than that of the Alien® 2x2 tags. However, the inability to read any of the Alien® Gen 2 

2x2 or the TitanTM tags was a surprise. The TitanTM tags could be read up to approximately 6 ft 

(1.8 m) in air. 

It is unlikely that the failure to read any tags was due to equipment malfunction. The reader was 

checked and worked in the laboratory immediately before and after the test, and it passed all 

diagnostics in the field on the day of the test. The possibility that all of the tags ended up in the 

bottom of the 13-inch (325-mm) slab and could not be read because of severe attenuation was 

also highly unlikely. 

The inability to read any of the tags in the field was particularly surprising because RFID tags 

have been used successfully in tracking precast concrete. Trackcon®, a division of International 

Coding Technologies (ICT), uses passive UHF tags to track precast concrete components. The 

tags are UPM Raflatac® Dogbone tags incorporating the Monza® 3 chip, the newest chip at the 

time from Impinj®, Inc. They are molded into the surface of precast concrete components. 

Trackcon® has also tried to embed them in concrete, and according to Tom Tilson, CEO of ICT, 

the tags can be read through 6 inches (150 mm) of concrete and sporadically even through 

12 inches (300 mm) of concrete. However, for these tags to be read, the 9090 Motorola®

handheld reader had to be no farther than 3 to 4 inches (75 to 100 mm) away from the tag. 

Falken Secure Networks, Inc. markets another commercial system for tracking precast concrete 

components using RFID. Company representatives confirm reading through precast concrete of 

thicknesses of 6 to 8 inches (150 to 200 mm) using the latest generation tags such as Alien®

Higgs® 3 or UPM Raflatac® Dogbone Monza® 3 with the 9090 Motorola® handheld reader.

The following are two possible reasons that these two companies were able to read tags through 

concrete but the current study could not: 

• The two companies used tags incorporating the newest chips available such Monza® 3 

and Higgs® 3.

• The tags they used are encapsulated flat instead of curled as the ones used for PCC 

tracking in this study were.

Even though ICT was able to read some tags through concrete, the company is not pursuing the 

idea of inserting passive tags in concrete because it has concluded that the read ranges and read 

success are not good enough for successful application. ICT continues to place RFID tags only 

on the surface of precast components. 

Because these puzzling insights from similar applications were inconclusive, further

investigations were conducted to determine why the tags in the present study could be read 

satisfactorily through HMA but not at all through PCC. 

71
FURTHER INVESTIGATIONS

Laboratory Evaluation

Encapsulated RFID tags were embedded in a concrete block in the laboratory to simulate 

conditions in the field. Only the Alien® Gen 2 2x2 tags were used for the laboratory evaluation 

because they had the best read range in air. An 8-ft3 (0.23-m3) wooden box was built for the 

laboratory evaluation. 

Because coarse aggregate is the largest component of concrete and often has a high dielectric 

constant, 12 tags were first placed in known positions inside the box as it was filled with coarse 

aggregate. The coarse aggregate was a limestone from the Millville quarry in West Virginia. This 

aggregate had an estimated dielectric constant of 7 (dry) or 8 (wet).

(10) The RFID tags were 

placed in three layers as shown in figure 58 through figure 61. The box was then read with the 

antenna positioned at the mid-height of the box at distances of 1 and 2 ft (0.3 and 0.6 m) away 

from the box. The antenna was positioned horizontally with the transmitter on the right side. 

Readings were taken with the middle of the antenna located between 24 inches (600 mm) to the 

left of the box and 24 inches (600 mm) to the right in 4-inch (100-mm) intervals for all four 

sides. All the read ranges were conducted in the laboratory, so there was the inevitable random 

interference due to metal objects. 

Because the box is symmetrical, the readings on each side should have theoretically been 

identical. However, owing to interferences and possible inconsistencies when placing the tags in 

the box, there were slight variations in the readings from one side to the other. 

The number of tags read at each offset averaged for each side is shown in figure 62. It can be 

seen that the number of tags read is skewed, with more tags being read on the left side of the box 

(negative values for distance). From previous read range studies, it was known that the RFID 

tags read best if they are closer to or in front of the T (transmit) side of the antenna. Because the 

T side of the antenna was on the right, increasing the offset on the right side increased the 

distance from the T side to the tags, which explains the skewed readings. 

Another important fact is that, although the antenna was placed only 1 or 2 ft (0.3 or 0.6 m) away 

from the box, that is not the actual antenna-to-tag distance. The distance to the tags also included 

an extra 4 to 20 inches (100 to 500 mm) of coarse aggregate based on their position inside the 

box. 

The maximum distance at which any of the tags was read was generally on the order of 6 ft

(1.8 m).

72
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.

73
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.

74
1 ft = 0.305 m 

1 inch = 25.4 mm

Figure 62. Chart. Average read range of four sides of the box for the RFID tags embedded 

in coarse aggregate. 

Next, the same tags were placed in the same locations as in the aggregate tests as the box was 

filled with concrete. None of the tags could be read after encapsulation in concrete, even after the 

concrete had cured for 1 month. To check the survivability of the tags, they were extracted from 

the concrete block via demolition. The tags could be read after extraction, so survivability was 

not the issue.

Additional tests were performed in an effort to determine the reason these passive RFID tags 

could not be read through concrete. Because the tags could be read through the coarse aggregate, 

the next logical step was to determine whether the moisture present in the concrete attenuated the 

electromagnetic waves enough so that the chip could not be activated. The dielectric constant of 

water is about 80, which makes it one of the most difficult media for the electromagnetic waves 

to penetrate. 

A 32 gal (121 L) plastic bucket was filled with sand at about 9.5-percent water content, which 

was similar to the water content for the concrete mixture. Sixteen tags were embedded at various 

depths in the sand at a maximum of 7 inches (175 mm) in from the sides of the bucket. All of 

these tags were read successfully from at least 2 ft (0.6 m) away. This finding shows that 

moisture by itself is not the reason there were no readings through concrete. 

As a final test, six tags were embedded at three different depths in a 5-gal (19 L) plastic bucket 

of cement paste prepared at a water-to-cement (w/c) ratio of 0.4. The tags closest to the surface 

were embedded only to about 3.5 to 4 inches (87 to 100 mm). None of these tags could be read 

even after 12 days of hydration. These findings clearly indicated that the cement paste was the 

reason for the unsuccessful readings through concrete. 

The Dielectric Constant of Cement Paste

Using mixture theory, the dielectric constant of concrete is approximately 11, which alone would 

not account for the poor read performance. Therefore, in an effort to determine the reasons that

Average Number of Tags Read at Various Lateral Offsets for 

Four Sides

0

2

4

6

8

10

-28 -24 -20 -16 -12 -8 -4 0 4 8 12 16 20 24 28

Lateral Offset (in)

Number of Tags Read

1 ft

2 ft

 

75
the RFID tags could not be read through the cement paste and ultimately through the concrete 

block, a thorough literature review was performed on the dielectric constant of cement. 

Zhang et al. used a microwave technique to determine the dielectric constant of cement pastes 

with different w/c ratios at frequencies between 8.2 and 12.4 GHz for up to 30 hours of 

hydration.(11) The w/c ratio of 0.4 is the closest to the one used in the present study. Because 

attempts to read the tags embedded in the concrete block were made after 1 month of 

hydration—i.e., after most of the water was hydrated—the dielectric constant of interest from 

Zhang et al.’s study was the latest one after 30 hours of hydration. Zhang et al.’s measured

dielectric constant for the cement paste was about 20 at 8.5 GHz, which is the closest frequency 

to the 915 MHz UHF frequency used in the present study. Other results by Zhang et al. show that 

the dielectric constant increases as frequency decreases, which means that the dielectric constant 

will be greater than 20 for frequencies close to 1 GHz. 

Wen and Chung examined the dielectric constant of cement pastes with different admixtures.(12)

Table 13 summarizes their key results. The first row gives the dielectric constant of Portland 

cement mixed only with water, which is the value of interest for the present study. At 1 MHz, 

this value is 23.7±2.8. For frequencies of about 1 GHz, the dielectric constant would be slightly 

lower, approaching perhaps 20. 

From these two papers, it is seen that the dielectric constant of cement is much higher than that 

of the coarse aggregate and coarse aggregate and water as estimated using mixture theory. 

Although the coarse aggregate is the main component of concrete, the cement paste covers all of 

the aggregate. The electromagnetic waves coming from the antenna must first go through the 

cement paste, which could strongly attenuate the signal due to its high dielectric constant. After 

that, the electromagnetic waves experience still more attenuation from the aggregate, making it 

hard for the signal to reach the RFID tags and power the chip.

Table 13. Dielectric constants for various cement pastes (after Wen and Chung(12)).

Fiber 

Type

Fiber Content

Admixture

Relative Dielectric Constant

Percentage by 

Mass of 

Cement

Percentage 

by Volume 10 KHz 100 KHz 1 MHz

— 0 0 — 28.6 + 3.4 24.8 + 3.6 23.7 + 2.8

— 0 0 SF 20.8 + 3.4 19.6 + 3.2 16.5 + 0.8

— 0 0 L 34.9 + 4.5 31.5 + 2.9 24.3 + 2.9

Carbon 0.5 0.48 SF 53.7 + 7.0 38.3 + 4.8 28.1 + 2.9

Carbon 0.5 0.41 L 63.2 + 5.2 40.4 + 5.9 33.2 + 6.8

Carbon 1.0 0.95 SF 48.7 + 4.8 29.6 + 5.0 25.0 + 5.0

Steel 0.5 0.10 — 19.6 + 4.8 19.0 + 1.0 13.7 + 2.4

— Not applicable

Admixtures: L = Lime, SF = Slag Flyash

KHz = kilohertz

MHz = megahertz

76
CONCLUSIONS REGARDING PCC TRACKING

Preliminary laboratory evaluation of concrete cylinders suggested that the Alien® Gen 2 

2x2 tags could be read through about 2 inches (50 mm) of concrete at a distance of up to 5 ft 

(1.5 m). Although this suggests that PCC tracking should therefore be successful, negative 

results were obtained during the Syracuse project field trials. None of the encapsulated RFID 

tags embedded in the concrete pavement were read even after 24 days of concrete curing. 

In an effort to determine the reason for this failure, an extensive laboratory evaluation was 

conducted. Twelve encapsulated RFID tags were embedded in three layers in an 8-ft3 (0.23-m3

)

box filled with coarse aggregate. These tags were all successfully read as the antenna was moved 

around all sides of the box. This suggests that attenuation of the radio signals by the coarse 

aggregate, the main component of concrete, is not the reason the tags could not be read in the 

field.

Next, the same configuration as for the aggregate box was applied to the box filled with concrete. 

None of the tags could read after 1 month of curing, even though four tags were embedded only 

4 inches from the box side. All tags could be successfully read when extracted after demolition 

of the concrete box. 

The next test consisted of inserting 16 tags in a bucket filled with sand and water. All of the tags 

could be read from at least 2 ft (0.6 m) away. Finally, six RFID tags were embedded at different 

depths in a 5-gal (19-L) bucket of cement paste. None of the tags could be read even after 

12 days of hydration. This indicates that the cement paste, which has a dielectric constant of 

about 20, is the main factor attenuating the electromagnetic waves in the concrete. 

In light of these results, it can be said that passive RFID tags, although successful in tracking 

HMA, are not suitable for tracking PCC. Active tags, with their much higher transmitting power,

could possibly work for this application; however, because they are needed in large quantities, 

their high price would make them unsuitable for the PCC tracking application.

77

CHAPTER 6: PAVEMENT TEMPERATURE MEASUREMENT USING SAW RFID

INTRODUCTION

There have been efforts since the late 1960s to model HMA temperatures as a function of time as 

an aid to optimizing compaction. Compaction is a densification process in which the air voids in 

an HMA mixture are reduced by the application of mechanical energy, commonly via a vibratory 

steel-drum roller. It is widely recognized that compaction is a critical factor in flexible pavement 

performance. Achieving optimal compaction for any particular mix depends primarily on 

temperature (for a given asphalt viscosity) and compactive effort. Inadequate compaction may 

result in reduced pavement stiffness, fatigue life, and durability.

Temperature versus time during compaction is especially important when using state-of-the-art 

intelligent compaction techniques. One of the principal advantages of intelligent compaction is 

the estimated stiffness of the compacted material as determined from the feedback sensors on the 

vibrating drum. The stiffness of HMA (and also warm mix asphalt) is extremely dependent on 

temperature. Analysis of the feedback data from the sensors on the intelligent compactor thus 

requires knowledge of the temperature distributions with depth and time in the cooling mat. The 

conventional infrared temperature measurements taken during compaction measure only the 

temperature at the surface—the coolest location in the mat—and may be biased by the water 

sprayed on the rollers. A technique for measuring temperature throughout the mat thickness in 

real time has potential for improving the effectiveness of intelligent compaction for asphalt 

concrete. 

The specific objectives of the investigations reported in this chapter are as follows:

1. Evaluate the feasibility of using SAW-based RFID technology to measure HMA 

temperatures versus depth and time via wireless sensors.

2. Demonstrate, both in the laboratory and the field, the survivability and temperature 

measurement capabilities of the SAW RFID sensors.

3. Perform analyses of the measured field data to develop asphalt cooling curves 

(temperature versus time) and compare these results with analytical mat cooling models. 

The coupling of some limited field measurement data with analytical models leverages 

the value of the sensor data.

4. Perform a sensitivity analysis on the input parameters for the traditional mat cooling 

models and calibrate, via the sensitivity analysis, input parameters that provide 

reasonable and close agreement with the measured temperatures from the field.

This work was performed in conjunction with the FHWA Pooled Fund Study on Intelligent 

Compaction and specifically with an intelligent compaction demonstration project conducted in 

Maryland.(13)

79
PREVIOUS WORK

A literature review of all previous work related to the development mat cooling models was 

performed. Although numerous journal articles and technical reports were reviewed, only the 

most relevant to the present study are discussed here. 

Heat Flow Formulations

Corlew and Dickson pioneered methods for predicting HMA temperatures as a function of time 

from when the asphalt leaves the paver to the end of compaction.(14) Their mat cooling model is 

based on the principles of one-dimensional transient heat flow as illustrated in figure 63. 

Figure 63. Drawing. Cross section of an HMA overlay indicating directional flow of 

thermal energy.

Transient heat flow is described by the partial differential equation (PDE) relating temperature T, 

time t, and depth y shown in figure 64.

Figure 64. Equation. Differential equation for transient heat flow.

The parameter α in figure 64 is the thermal diffusivity—the ability of a material to conduct 

thermal energy compared with its ability to store thermal energy. The equation in figure 65

defines thermal diffusivity:

Figure 65. Equation. Definition of thermal diffusivity.

where:

k = thermal conductivity of the material.

ρ = material density.

Cp = specific heat capacity. 

80
The units for thermal diffusivity are area per unit of time (e.g., ft2

/h).

Although Corlew and Dickson proposed an analytical solution to the equation in figure 64, they 

found that the interactions of the various modes of thermal energy transfer at the pavement 

surface were better modeled using numerical techniques. 

Figure 66 illustrates the numerical solution scheme for the transient heat flow analysis. The 

pavement thickness is divided into sublayers (sections divided by isothermal lines) and the PDE 

in figure 64 is approximated using finite difference equations at the nodes located at the 

midpoints of each sublayer. As shown in figure 66, the nodes extend from the pavement surface 

boundary through the overlay and continue for some depth through the asphalt base to the lower 

boundary. The boundary conditions consist of a constant ambient air temperature (TAir) above the 

surface of the overlay (depth location i=n) and a constant base temperature at the bottom of the 

analysis domain (i=1). The lower boundary is located at a sufficient depth where conduction no 

longer affects the temperature of the base material over the duration of the transient analysis—

i.e., the bottom boundary condition is T1j = TInitial for all time steps j. 

Figure 66. Drawing. Typical incremental elements of HMA overlay used in numerical 

solution.

Figure 67 expresses the finite difference approximation of the heat balance equation within the 

mat:

Figure 67. Equation. Finite difference approximation to heat balance equation.

where:

i =2...n-1 = the node number in the interior.

Tij = temperature (oF) at node i and time j. 

The equation in figure 68 solves for Ti,j+1.

81
Figure 68. Equation. Equation for Ti,j+1.

These one-dimensional conduction equations are used to calculate temperatures within both the 

HMA overlay and the asphalt base. Corlew and Dickson point out that the thermal diffusivity 

might be different for the two materials. However, this difference is expected to be small for 

most asphalt mixtures. Therefore, the thermal diffusivity is assumed uniform for the overlay and 

base material. 

Similarly to conduction, heat loss from the surface i=n due to convection and radiation is based 

on the energy balance equation shown in figure 69:

Figure 69. Equation. Energy balance equation for convective and radiation heat losses at 

pavement surface.

where:

NB = Biot number (described below).

k = thermal conductivity (BTU/ft2

-h-°F/ft).

TAir = ambient air temperature (o

F).

a = solar absorptivity.

HS = solar heat flux (BTU/ft2-h).

ε = emissivity.

σ = Stefan-Boltzman constant—1.713x10-9 (BTU/ft2

-h-°R4).

The Biot number is a dimensionless value commonly used in transient heat flow and mass 

transfer analysis.

(15) It is the ratio of heat transfer resistances within and at the surface of a mass 

undergoing convection. This number indicates whether temperatures within the body will vary 

significantly in space while the mass heats or cools over time due to thermal energy transfers at

its surface. Mathematically, the Biot number is defined as the equation shown in figure 70.

(15)

Figure 70. Equation. Definition of Biot number.

The convective heat transfer coefficient h in figure 70 relates convective heat flow with 

temperature difference and surface area via Newton’s law of cooling. The effective length s is 

the ratio between volume and surface area, and k is the thermal conductivity. The final radiation 

term in figure 69 includes parameters that account for the absorption of radiant solar energy

(a HS) and for the radiant energy emitted by the pavement (ε σ).

82
Corlew and Dickson developed a computer program to simulate mat cooling based on this finite 

difference formulation. To validate this model, they performed field experiments in which 

thermocouples were embedded throughout the depth of an HMA overlay to measure mat cooling 

versus time. Wind velocity, ambient air temperature, initial base temperature, solar radiation, and 

overlay thickness were also measured in their experiments. Corlew and Dickson found very close 

correlations between measured and predicted temperatures.

Overall, Corlew and Dickson’s study suggested the following:

1. When using proper environmental conditions, modeling mat cooling is feasible and 

accurate using finite difference analysis techniques.

2. The heat flux from the overlay into the underlying base layer is initially greater than the 

heat flux into the atmosphere. Therefore, the lower region of the overlay expels heat

faster than the upper region. However, Jordan and Thomas found that with increasing 

time, the cooling of the surface becomes dominant.(16)

Wolfe and Colony expanded on Corlew and Dickson’s approach and converted the mat cooling 

models into a format more suitable for the portable handheld computers of the time and for 

tabular and graphical summary.(17) In an attempt to streamline the conductive heat flow 

calculations in figure 68, Wolfe and Colony used Saul’yev’s method for conduction, a numerical 

technique based on forward and backward finite differences. Saul’yev’s method requires less 

memory than that needed by Corlew and Dickson’s formulation and thus was better suited to the 

comparatively primitive handheld computers available in the 1970s. Wolfe and Colony also 

developed an explicit form of convective heat transfer energy balance at the mat surface. 

Wolfe and Colony also employed the slightly different finite difference energy balance equation 

shown in figure 71 for the heat flows at the surface of the mat. All terms were as defined 

previously.

Figure 71. Equation. Modified version of finite difference energy balance for heat flows at 

surface of mat.

Figure 71 includes energy losses due to radiation and convection and gains from solar radiation. 

Figure 71 can then be rearranged as shown in figure 72 to solve for the temperature at the next 

time step, Tn,j+1.

Figure 72. Equation. Modified equation for Tn,j+1 at mat surface.

Figure 68 and figure 72 are used in this study as the finite difference solution for the transient 

heat flow in the overlay.

83
Wolfe and Colony argued that both free and forced convection effects should be included when 

calculating the convective heat transfer coefficient.(17,18) Free convection occurs when there is no 

wind velocity, as opposed to forced convection that includes wind velocity. Wolfe, Heath, and 

Colony recommended the relationship shown in figure 73 for convection(19):

Figure 73. Equation. Relationship for forced convection.

where V is the wind velocity in mi/h.

Wolfe and Colony state that solar heat flux emitted by the Sun can range up to about 400 BTU

(422 kJ) per hour at local solar noon.

(17) However, it is dependent on the time of the year, the 

Sun’s declination, and the location (latitude) of the surface being considered. They suggest the 

the equation in figure 74 for estimating solar heat flux(18):

Figure 74. Equation. Relationship for estimating solar heat flux.

where:

R =incident solar radiation (direct and diffuse).

N = a cloud base factor, which varies from 0.80 to 0.90.

W = percentage cloud cover, which is visually estimated. 

The value for incident radiation is obtained from historical data. The authors provide a graph of 

solar heat flux versus time for typical incident radiation in Ohio between 38°50’ and 42°00’

latitude (the location of their study).

Alternative methods for determining solar heat flux have been proposed in the literature. Rather 

than modifying solar radiation for cloud effects and cover, radiation can also be quantified in 

terms of the effective sky temperature.

(20)

Wolfe, Heath, and Colony performed laboratory and then field tests to demonstrate that their 

numerical predictions correlated favorably to measured mat cooling curves.(19) The field trials 

were performed in November 1979 at a project site in Ohio. The field instrumentation at the 

project site included a radiation pyrometer to measure base surface temperatures, a pyrheliometer 

to measure solar insolation, an anemometer to measure wind speed, temperature probes, and 

recording devices. Field temperatures were measured near and at the interface of the newly 

placed HMA and its base layer. Surface temperatures were also measured but were dismissed 

because of instrument inaccuracies. The field test found generally close correlations between 

calculated and measured temperatures.

Wolfe, Heath, and Colony concluded that their predictive equations were adequate for the 

purpose of making “go/no-go” decisions in the field for placing and compacting HMA under 

adverse site conditions.(19) Specific findings from the study included the following:

84
• Based on the simulation results, solar radiation and cloud cover are not major influences 

on the placement of HMA. In other words, solar radiation should not be considered in 

making a “go/no-go” decision in the field.

• The convective heat transfer coefficient is relatively difficult to measure. There are 

numerous equations and experimental methods to estimate this parameter. However, the 

study generally confirmed the recommendations in figure 73 for this value.

• Prior to the actual paving, the surface of the base material is subjected to heat from the 

paver as it passes. The authors suggested that, depending on the speed of the paver (and if 

it pauses), the initial interface temperature between the asphalt and base material may not 

be accurate. Temperatures should be recorded once the paver passes the test area.

Thermal Property Values

Wolfe and Colony, based on a review of several sources, recommended typical values for other 

thermophysical material properties of asphaltic mixtures.(17) These are summarized in table 14.

Table 14. Typical thermal property values.(17)

Property Units Symbol Suggested

Minimum

Value

Maximum

Value

Thermal conductivity BTU/ft-h-°F k 0.80 0.58 1.01

Thermal diffusivity ft2/h α 0.0215 0.0215 0.0337

Absorptivity Dimensionless a 0.85 0.85 0.90

Emissivity Dimensionless ε 0.95 0.90 0.95

Stefan-Boltzman 

constant

BTU/ft2-h-°F

(R4W/m2-K-4) σ

1.713x10-9

(5.670x10-8) N/A N/A

N/A = Not Applicable

1 BTU/ft-ho

F = 1.73 W/moK

1 ft2

/h = 0.093 m2/h

Luca and Mrawira performed a series of laboratory tests to measure the thermal diffusivity and 

thermal conductivity k for Superpave HMA mixtures and compared their measured values with 

values reported previously in the literature.(21) Their measured values generally agreed favorably 

with those in the literature; the values fit within a general range of 1.35x10-2 to 3.20x10-2 ft2/h

(1.25x10-3 to 2.98x10-3 m

2

/h) for thermal diffusivity and 0.70 to 2.24 BTU/ft-h-°F (1.21 to 

3.88 W/moK) for thermal conductivity. The authors highlight that these parameters are generally 

difficult to measure. Table 15 and table 16 summarize Luca and Mrawira’s findings.

Table 15. Typical values for thermal diffusivity.(21)

Author Year Thermal Diffusivity, , x 10-2 (ft2/h)

Luca and Mrawira(21) 2005 1.56–2.13

Wolfe et al.(19) 1983 1.99–3.20

Fwa et al.(22) 1997 2.07–2.24

Highter and Wall(23) 1983 1.35–2.90

Corlew and Dickson(14) 1968 2.27

1 ft2/h = 0.093 m2/h

α

α

85
Table 16. Typical values for thermal conductivity.(21)

Author Year Thermal Conductivity, k (BTU/ft-h-°F)

Luca and Mrawira(21) 2005 0.94–1.19

Wolfe et al.(19) 1983 0.58–1.01

Fwa et al.(22) 1997 2.07–2.24

Highter and Wall(23) 1983 0.75–0.82

Corlew and Dickson(14) 1968 0.70

1 BTU/ft-hoF = 1.73 W/moK

LABORATORY EVALUATION OF SAW RFID TAGS

The differences between surface SAW and conventional RFID were described in chapter 1. A 

series of laboratory tests were performed to evaluate the suitability of SAW RFID technology for 

pavement applications. These tests were organized into the following subtopics:

• Development of an encapsulation process using thermally conductive epoxy that will 

promote the transfer of thermal energy while protecting the tag from physical damage. 

• A read range study to evaluate the signal strength/readability of the SAW RFID tags. The 

read range study includes testing for tag orientation (including rotation) to the antenna 

and position/distance from the antenna.

• A thermal sensitivity study to evaluate the thermal response of the tags when exposed to 

elevated temperature transients. More specifically, this study evaluates the time required 

for a tag to heat up and then equilibrate to the temperature of the surrounding material/

environment. 

Tag Encapsulation

Encapsulating the RFID tags with a thin coating of thermally conductive epoxy protects them 

from paving and compaction stresses while only minimally interfering with heat transfer during 

mat cooling. The encapsulation medium selected for this study is Durapot 865TM epoxy from 

Cotronics, Inc. This encapsulant has a thermal conductivity of about 1 BTU/ft-h-oF 

(1.73 W/mo

K) and is electrically insulating. To put this parameter into perspective: the thermal 

conductivity of copper is about 230 (400), standard epoxy is about 0.20 (0.35), and asphalt is 

about 0.433 BTU/ft-h-oF (0.75 W/moK). Durapot 865TM is a two-component epoxy (resin and 

hardener) that cures at room temperature. The following encapsulation procedure was used:

• The epoxy resin component is preheated for about 40 min at 122 oF (50 °C) to reduce its 

viscosity.

• The epoxy components are then combined at 100 parts resin to 21 parts hardener and 

thoroughly mixed.

• The wooden mold (fabricated in advance) is lined with standard kitchen plastic wrap 

secured using masking tape.

86
• A layer of epoxy is poured at the bottom of the mold prior to tag placement to create a 

thin protective base layer.

• The tag is placed in the mold on top of the bottom epoxy layer and pressed downward 

into the encapsulant. The tag is then covered in the epoxy to completely encase it.

• The wood mold, with epoxy and tag, is then placed in a vacuum dessicator to remove any 

air pockets in the epoxy.

• After removing the air and curing for 24 hours, the tags are removed and sanded for 

smoothness.

Figure 75 shows the unencapsulated tags used in this study. As will be described more fully later, 

the larger tag on the left of figure 75 is the single patch antenna tag (with larger receiving 

antenna) approximately 45 by 45 mm (13⁄4 by 13⁄4 inches) in size. The tag on the right is the 

monopole antenna tag approximately 8 by 45 mm (1

/3 by 13⁄4 inches) in size. Figure 76 shows the 

encapsulated tags prior to final sanding. Both unencapsulated and encapsulated tags were 

evaluated in the read range and thermal sensitivity studies.

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).

Signal Strength and Readability

A series of read range tests were performed to evaluate the signal strength and readability of the 

SAW RFID tags in both the monopole and single patch antenna configurations. The monopole 

87
and single patch tag antennae differ primarily in the shape of their RF field distributions (for 

transmission) and sensitivities (for reception). 

The monopole antenna is formed by replacing half of its dipole antenna with a ground plane 

normal to the antenna axis. If the ground plane is sufficiently large, the monopole behaves like a 

dipole with its reflection in the ground plane providing the missing symmetric half. A dipole 

antenna has a toroidal field strength/sensitivity distribution with omnidirectional field strength/

sensitivity in the midplane and normal to the antenna axis, and with dead zones at the ends of the 

dipole.

Patch antennae, on the other hand, are designed for a more directional RF radiation/sensitivity. A 

simple patch antenna consists of a looped antenna one-half wavelength long, separated by a 

constant thickness over a ground plane. The ground plane is typically only modestly larger than 

the active patch. The simple patch antennae of this type radiate a linearly polarized wave. The 

typical radiation pattern for a linearly polarized patch antenna is unidirectional with a beam 

width angle of about 65 degrees. An infinitely large ground plane would prevent any radiation 

toward the back of the antenna. But, with the more usual finite ground plane, power loss through

the back side of the antenna is about -20 dB compared with the front side.

Two types of reader antennae were supplied with the SAW RFID system—linearly and 

circularly polarized. Both reader antenna types were evaluated for the following tag 

configurations: unencapsulated tags in air, encapsulated tags in air, and encapsulated tags in an 

asphalt specimen.

Unencapsulated Tags in Air

To determine the full read range capacity of the unaltered SAW RFID tags, an “open-floor” read 

range study was performed. The following diagrams illustrate the read range capacity for the 

unencapsulated tags in air. Each cell within the diagram represents a 1 ft (0.3 m) interval of 

lateral offset or distance ahead of the antenna. Note that the antenna is fixed 1 ft (0.3 m) away 

from the test grid in front of cells L-A and R-A. For example, cell “-2, B” is located 2 ft (0.6 m) 

to the left and 3 ft (1 m) ahead of the face of the antenna. The numbers in each cell are the 

number of read responses from the tag at that location during a 20s interval. 

A uniform tag orientation was used throughout this study. The tag was affixed to the back of a 

plastic board, antenna oriented vertically, facing toward the reader antenna (unless otherwise 

noted). Figure 77 and figure 78 display the results of the read range study performed on a single 

patch tag using a linearly polarized antenna and circularly polarized antenna, respectively. The 

green cells indicate strong reliable readings, yellow are more unpredictable, and red are zero or 

unlikely readings. Figure 79 and figure 80 summarize the corresponding read range results for 

unencapsulated monopole tags using a linearly and circularly polarized antenna.

Comparing these four figures, it is apparent that the single patch tags have a stronger readability 

than the monopole tags, both in terms of the number of reads and the width of the readable zone 

ahead of the antenna. This is because of the larger size and higher sensitivity of their antennae. 

However, all of the unencapsulated tags (patch and monopole) exhibited read ranges greater than 

8 ft (2.4 m) in air. 

88
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.

Strong Read Zone

Fair Read Zone

Poor Read Zone

All distances in ft (1 ft = 0.305 m)

L = Left side of antenna

R = Right side of antenna

Strong Read Zone

Fair Read Zone

Poor Read Zone

All distances in ft (1 ft = 0.305 m)

L = Left side of antenna

R = Right side of antenna

Strong Read Zone

Fair Read Zone

Poor Read Zone

All distances in ft (1 ft = 0.305 m)

L = Left side of antenna

R = Right side of antenna

89
Figure 80. Diagram. Unencapsulated monopole tag, circular polarization.

Encapsulated Tags in Air

Similar read range testing was performed on tags after encapsulation in thermally conductive 

epoxy. Figure 81 and figure 82 summarize the measured read ranges for the encapsulated single 

patch tag using linear and circular reader antenna polarization, respectively. Figure 83 and

figure 84 summarize similar results for the encapsulated monopole tag.

Based on the results in these figures, it is again apparent that the single patch tags have better

readability than the monopole tags. In addition, the polarization of the reader antenna influences

read performance. A linearly polarized antenna has more directionality than the circularly 

polarized antenna. This means that, all else being equal, the linearly polarized antenna will have 

better read performance for some orientations of the tag (relative to the plane of the antenna 

polarization) and worse read performance for others, compared with the circularly polarized 

antenna. In general, the circularly polarized antenna will have slightly lower read performance 

but with much less sensitivity to the orientation of the tag relative to the antenna. The latter

characteristic is more important for field applications, so all subsequent testing was conducted 

using only the circularly polarized reader antenna.

It is also apparent from these results that while encapsulating the RFID tags within epoxy 

increases their likelihood of survival in the field, it is detrimental to their readability in air. Based 

on the read range results, the encapsulated monopole tags are likely to perform marginally for 

field use while the encapsulated patch tags are anticipated to perform well.

Strong Read Zone

Fair Read Zone

Poor Read Zone

All distances in ft (1 ft = 0.305 m)

L = Left side of antenna

R = Right side of antenna

90
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.

Strong Read Zone

Fair Read Zone

Poor Read Zone

All distances in ft (1 ft = 0.305 m)

L = Left side of antenna

R = Right side of antenna

Strong Read Zone

Fair Read Zone

Poor Read Zone

All distances in ft (1 ft = 0.305 m)

L = Left side of antenna

R = Right side of antenna

Strong Read Zone

Fair Read Zone

Poor Read Zone

All distances in ft (1 ft = 0.305 m)

L = Left side of antenna

R = Right side of antenna

91
Figure 84. Diagram. Encapsulated monopole tag, circular polarization.

Encapsulated Tags Within Asphalt

In an effort to simulate survivability and readability under field conditions, the SAW tags were 

placed in HMA at about 392 °F (200 °C) and compacted in a gyratory compactor. All specimens 

were compacted at about 88 psi (600 kPa) pressure for 150 gyrations. Initially, unencapsulated

patch and monopole tags were positioned in the gyratory specimens to evaluate their inherent 

survivability. Two of three unencapsulated tags were destroyed during compaction. Therefore, 

all subsequent tags evaluated in this read range study were encapsulated in thermally conductive 

epoxy.

The encapsulated tags were placed near the center of the gyratory plugs. As shown in figure 85, a 

variety of tag orientations were explored to determine which would provide the best readability. 

In addition to these orientations, the encapsulated tags were also rotated about the cylinder’s axis 

to evaluate any further potential signal degradation. Figure 86 depicts the rotational positions of 

the asphalt sample.

Overall, the testing revealed that the strongest signal strength and readability were produced in 

orientation #1 (face side of the tag facing the antenna) for both the single patch and monopole 

tags. In this orientation, rotation #1 (figure 86) provided the best and most consistent results.

Figure 87 and figure 88 summarize typical testing results for orientation #1 for both the 

monopole and single patch tags. Note that the single patch tag was read up to about 12 ft (3.6 m) 

from the antenna using this orientation. Although not shown, orientations #2 and #4 were also 

considered strong and reliable for both types of tags. In addition, the monopole tags performed 

well in orientations #4 and #6. 

Strong Read Zone

Fair Read Zone

Poor Read Zone

All distances in ft (1 ft = 0.305 m)

L = Left side of antenna

R = Right side of antenna

92
Figure 85. Drawing. Orientation guide for tags within asphalt specimens.

Figure 86. Drawing. Rotation scheme for tags within asphalt specimens (monopole and 

single patch).

93
R.O. = rotational orientation

1 ft = 0.305 m

Figure 87. Graph. Orientation #1 for monopole tag using circular polarization. 

R.O. = rotational orientation

1 ft = 0.305 m

Figure 88. Graph. Orientation #1 for single patch tag using circular polarization. 

Conclusions: Signal Strength and Readability

Overall, both the encapsulated monopole and patch antenna tags showed acceptable performance 

when encased in HMA. The monopole tags, while more practical and compact in size, did not 

perform as reliably as the patch tags in terms of signal strength and readability. Based on the 

entire laboratory read performance testing, both the monopole and patch tags warrant further 

0

5

10

15

20

25

30

35

40

45

0 2 4 6 8 10

Distance from Antenna (Feet)

Number of Readings in Twenty 

Seconds

R.O. 1

R.O. 2

R.O. 3

R.O. 4

 

0

5

10

15

20

25

30

35

40

45

50

0 5 10 15

Distance from Antenna (Feet)

Number of Readings in Twenty 

Seconds

R.O. 1

R.O. 2

R.O. 3

R.O. 4

 

94
investigation in field trials. Because they are to be pre-positioned ahead of the asphalt paver, they 

can be placed in the optimum location: orientation #1/rotational position #1.

Thermal Sensitivity

To simulate field conditions within a laboratory, the testing apparatus shown in figure 89 was 

developed for measuring the temperature sensitivity and transient response of the SAW RFID 

tags. As shown in the figure, the SAW RFID tags were pre-positioned on a flat wood plank 

covered in foil (to isolate temperatures and increase signal strength) and exposed to preheated 

materials. The selected materials used for testing included generically graded asphalt aggregate 

and HMA with about 5-percent binder content by weight. These materials were preheated to 

about 284 to 338 °F (140 to 170 °C) and placed over the test tag at room temperature. Upon 

exposure, tag temperatures were recorded over time via the RF SAW reader and software. 

Independent temperature measurements were collected using a Fluke® thermocouple probe 

affixed to the foil adjacent to the tag. Because our initial small supply of SAW RFID tags was 

limited, the tags tested here were the same as those used previously for the survivability and read 

performance testing; they were recovered from the gyratory plugs after completion of the 

survivability testing.

Figure 89. Drawing. Thermal testing apparatus.

Table 17 describes the tags used for this study. figure 90 through figure 92 summarize the 

thermal sensitivity study results for hot aggregate material. Time zero corresponds to ambient 

(room temperature) conditions immediately before covering the RFID tag and Fluke®

thermocouple with the hot aggregate. The test results show that the unencapsulated monopole tag 

(tag 0A21, figure 90) quickly matched the temperature readings from the thermocouple. The 

encapsulated monopole tag (tag 0443, figure 91) required about 5 to 6 min to reach aggregate 

temperature, as measured by the thermocouple. This thermal lag is assumed to be due to the 

additional thermal mass and relatively low thermal conductivity from the encapsulating epoxy. 

The thermal lag even more pronounced for the encapsulated patch tag (tag 09FE, figure 92) 

because of its larger format and corresponding larger mass of encapsulating epoxy. Even after 

6 min, the encapsulated patch was 104 °F (40 °C) cooler than the reference measurement. Note 

that no unencapsulated patch tag was evaluated in this thermal study because it had been 

destroyed in the gyratory compactor during the first stage of the testing.

95
Table 17. Tags employed in thermal testing.

Tag Name Type Encapsulated

0A21 Monopole No

0443 Monopole Yes

09FE Single Patch Yes

°C = (°F – 32)/1.8

Figure 90. Graph. Thermal response from tag 0A21 using hot aggregate.

°C = (°F – 32)/1.8

Figure 91. Graph. Thermal response from tag 0443 using hot aggregate.

0

20

40

60

80

100

120

0 2 4 6

Time (mins)

Deg. Celcius

Tag

Fluke

248

212

176

140

104

 68

 

96
°C = (°F – 32)/1.8

Figure 92. Graph. Thermal response from tag 09FE using hot aggregate.

Figure 93 through figure 95 summarize the thermal sensitivity study results for the HMA

material. Similar conclusions can be drawn here as for the hot aggregate: the unencapsulated 

monopole tag responds quickly and accurately, the encapsulated monopole tag responds with an 

acceptable time delay, and the encapsulated patch tag responds much more slowly and was still 

far from the equilibrium temperatures when the measurements ended at 6 min. This thermal lag 

may prove to be detrimental for field use. 

Once the tags have equilibrated from the initial thermal shock (i.e., starting at ambient 

temperature and being covered with 284 to 338 °F (140 to 170 °C) HMA, they then match the 

thermocouple measurements for the continued slow cooling with time. This is most evident for 

the monopole tags (figure 93 and figure 94); readings were not continued for a long enough time 

period to completely confirm this for the encapsulated single patch tag (figure 95).

°C = (°F – 32)/1.8

Figure 93. Graph. Thermal response from tag 0A21 using hot HMA.

0

20

40

60

80

100

120

140

0 2 4 6

Time (mins)

Deg. Celcius

Tag

Fluke

284

248

212

176

140

104

 68

 

Tag

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6

Time (mins)

Deg. Celcius

Tag

Fluke

212

176

140

104

 68

 

97
°C = (°F – 32)/1.8

Figure 94. Graph. Thermal response from tag 0443 using hot HMA.

°C = (°F – 32)/1.8

Figure 95. Graph. Thermal response from tag 09FE using hot HMA.

Overall, the thermal sensitivity study suggests that, given an adequate amount of time after HMA 

placement before compaction, all of the tested SAW RFID tags have transient thermal response 

sufficiently rapid for field use. The unencapsulated monopole tag performed more effectively 

than the others. Nonetheless, further field evaluation of all of the tags is justified.

FIELD EVALUATION

Field trials were conducted to evaluate the suitability of SAW RFID technology for wireless 

measurement of in-place HMA temperatures during intelligent compaction. These trials, hosted 

by MDSHA in conjunction with the FHWA Intelligent Compaction Pooled Fund Study, were 

conducted on July 23, 2009, during placement of a 1.5 inches (38 mm) pavement overlay.(13)

0

10

20

30

40

50

60

70

80

90

0 2 4 6

Time (mins)

Deg. Celcius

Tag

Fluke

194

140

 86

 32

Tag

98
Site Information

The project site for the field trials was located on United States Route 15/Maryland Route 340 in 

Frederick County, Maryland. More specifically, the site was located in the outer (right) 

northbound lane between Mt. Zion Road and the Jefferson Street Bridge. Figure 96 maps the 

general location of the project site.

Original image: ©2015 Google®; map annotations provided by University of Maryland

Figure 96. Map. Approximate location of project site.

(24)

Construction and activities related to the intelligent compaction field trial were conducted at the 

project site from about July 20 to July 24, 2009. An initial attempt was made on the evening of 

July 22 to perform the field evaluation of the SAW RFID temperature measurement system. 

However, all construction activities were cancelled because of an unexpected thunderstorm. The 

encapsulated tags for the field trial had already been affixed to the milled surface using epoxy 

putty before the storm. After cancellation, the tags were pried from the road surface and the 

epoxy putty was carefully ground off so that the tags could be reused on July 23. The field 

evaluation was completed on July 23 from about 0200 to 0300 h. Weather conditions were clear, 

mild, and windless. Table 18 summarizes weather data recorded just prior to testing from two 

nearby weather stations.

99
Table 18. Weather data recorded near the project site for July 22–23, 2009. 

Time Station

Temperature

(°F)

Dew Point 

(°F)

Relative 

Humidity (%)

Wind 

Speed 

(mi/h)

20:55 Walnut Ridge 74.8 64.0 68 0

Middletown 71.4 66.0 82 0

00:53 Walnut Ridge 71.4 63.0 75 0

Middletown 70.5 64.9 82 0

01:47 Walnut Ridge 70.5 63.0 82 0

Middletown 70.5 64.0 81 0

Note: Walnut Ridge and Middletown stations are about 8 (12.88 km) and 36 mi (57.96 km), respectively,

from the project site.

°C = (°F – 32)/1.8

1 mi/h = 1.61 km/h

Testing Procedure

The test section was about 51 ft (15.5 m) long and was located near the interchange with Mt. 

Zion Road. Ten single patch tags and 30 monopole SAW RFID tags were pre-positioned ahead 

of the paver. In an effort to measure temperature through the depth of the overlay, three 

elevations were considered: bottom of the mat (elevation 0 inches), middle of the mat (elevation 

0.75 inches (19 mm)), and surface of the mat (elevation 1.5 inches (38 mm)). The middle tags 

were elevated using a thicker layer of thermally conductive epoxy underneath the tag. Layout 

schematics for the test section are shown in figure 97 and figure 98.

1 ft = 0.305 m

Figure 97. Drawing. Plan view of test section. 

100
1 ft = 0.305 m

1 inch = 25.4 mm

Figure 98. Drawing. Detailed plan view of a single group of SAW RFID tags. 

As previously described, all of the tags except for eight “top of mat” surface tags were 

encapsulated in a relatively rigid thermally conductive epoxy. All tags other than those used for 

the surface were affixed to the milled existing pavement surface using quick-hardening epoxy 

putty (Loctite® 5-Minute Epoxy Putty). The mounted tags were oriented so that their ceramic 

chip and antenna were facing upward to enhance their readability. The unencapsulated surface 

tags were placed face down into the asphalt by the contractor immediately after passage of the 

paver. Figure 99 shows the tags being placed on the milled surface.

The RF SAW tag reader and circularly polarized antenna were mounted on a long-handled 

wheeled carriage to read the tags from the side of the road during compaction operations. The 

antenna was elevated about 1 ft (0.3 m) above the pavement surface. The wheeled apparatus was 

manually operated to minimize any disturbance to the hot asphalt or disruption of the compaction 

operations while the lift was cooling and being compacted. The reader was cabled to a laptop 

computer that recorded temperature and tag signal strength during testing. 

101
Figure 99. Photo. Placement of SAW RFID tags on surface of existing milled pavement.

The reader software requires that the operator specify a temperature window prior to reading the 

tags; the manufacturer recommends a 86 °F (30 °C) temperature window. This temperature 

window may be widened; however, the software signal processing time becomes longer. A 

longer signal processing time has been known to decrease the signal strength/response of the tag, 

especially when the tag is embedded in attenuating materials. 

Thermal lag added another complication to obtaining good early temperature readings from the 

encapsulated tags immediately after they were covered with hot HMA. As described previously, 

thermal lag is the time required for the encapsulated tags to “heat up” to the temperature of the 

surrounding material. Results from the laboratory study suggested that the thermal lag for 

encapsulated tags is about 3 to 8 min, depending on the tag type; encapsulated single patch tags 

experience the longest thermal lag. The laboratory thermal sensitivity study also suggested that 

unencapsulated tags at the surface would exhibit only about 1 to 2 min of thermal lag.

The estimated temperature window immediately after placement of the overlay was set at

230 to 284 °F (110 to 140 °C). Initially, no response could be obtained from any tag. After the 

temperature window on the reader was adjusted downward to 176 to 230 °F (80 to 110 °C), some 

tags were read successfully at about 8 min after paving. The manufacturer-recommended

temperature window of 86 °F (30 °C) was used throughout the field trials. However, during the 

initial heating of the tags (thermal lag) and rapid cooling of the mat immediately after placement, 

it proved difficult to adjust the temperature window on the reader quickly enough to capture the 

initial tag temperatures.

The wheeled reader and antenna apparatus was initially passed over the “Group A” tags (see 

figure 97 and figure 98), then “Group B,” then “Group C,” and so on, after which the cycle was 

102
repeated. The data collected during testing included the tag identification number, the time/date 

stamp of the last reading during the antenna pass, the tag distance from the antenna at the last 

reading, and the temperature at the last reading. Note that even if multiple reads were obtained 

from a tag during a given pass, the reader software saved only the data from the last read. Four 

full cycles of readings from Groups A through I were performed until the mat had cooled 

sufficiently that the vibratory compactors moved on to other sections. Prior to each pass, the 

reader software temperature window was adjusted for the decreasing temperature conditions. 

Figure 100 shows the paving operation and test setup during construction.

Figure 100. Photo. Paving operation and test setup during construction.

Field Test Results

After the hot-mix asphalt had been placed on the first groups of tags (Groups A through C), the 

vibratory compactors passed the testing area for a few minutes. Additional time was required to 

configure the reader software with a proper temperature window to read the tags. Consequently, 

the first tag reads were obtained about 8 min (± 1 min) after the tags were covered with asphalt. 

Readings were than taken for approximately the next hour, continuing after the vibratory 

compactors had moved on to subsequent sections of pavement.

Overall, the temperatures at the bottom of the mat decreased from 198 to 135 °F (92 to 57 °C)

during the cooling period monitored in this study. At the middle of the mat and on the surface, 

103
temperatures generally decreased from 208 to 133 °F (98 to 56 °C) and from 219 to 111 °F 

(104 to 44 °C), respectively. Table 19 summarizes the read success rates for the tags. Five of the 

30 preplaced tags could not be read successfully during system testing prior to paving operations. 

This is likely owing to damage caused by their removal from the roadway surface the night 

before and/or their preparation for reuse by grinding off the hardened epoxy putty. The read rates 

after asphalt placement and during compaction increased from 28 percent during the first pass to 

52 percent in the fourth. This should not, however, be interpreted as an increase in the inherent 

read rate with time. Rather, this increase is because it was easier to set an appropriate 

temperature window in the reader software during the slower cooling of the later passes than 

during the rapid cooling in the first pass.

Table 19. Tag read rates.

Paver Pass Tag Count Total Possible

Reading

(percent)

Pre-Paving 25 30 83

Pass 1 11 40 28

Pass 2 19 40 48

Pass 3 22 40 55

Pass 4 21 40 52

Evaluations of the cooling HMA temperatures with depth and time were performed at two 

transverse cross sections: Groups A-D-F-H and B-E-G-I. Results from cross section B-E-G-I are 

described here; the results from cross section A-D-F-H were very similar. Plots illustrating 

temperature versus time since paving are given in figure 101 through figure 103 for the bottom, 

mid-thickness, and surface of the mat, respectively. “Time since paving” is the estimated elapsed 

time after the tags are covered with the asphalt by the paver.

°C = (°F – 32)/1.8

Figure 101. Graph. Temperature versus time at bottom of mat (cross section B-E-G-I).

0

10

20

30

40

50

60

70

80

90

0 2 4 6

Time (mins)

Deg. Celcius

Tag

Fluke

194

140

 86

 0

Tag

0

20

40

60

80

100

120

0 10 20 30 40 50 60

Time Since Paving (Mins)

Temperature (°C)

Pass 1 Temp

Pass 2 Temp

Pass 3 Temp

Pass 4 Temp

 

248

212

176

140

104

 68

 32

104
°C = (°F – 32)/1.8

Figure 102. Graph. Temperature versus time at middle of mat (cross section B-E-G-I).

°C = (°F – 32)/1.8

Figure 103. Graph. Temperature versus time at surface of mat (cross section B-E-G-I).

As shown in the figures, the temperatures measured by the tags decreased with every compaction 

pass. Based on these test results and theoretical expectations for typical mat cooling trends, 

exponential regression lines were fit to the data. Figure 104 summarizes the cooling trends 

segregated by location within the mat thickness.

0

20

40

60

80

100

120

0 10 20 30 40 50 60

Time Since Paving (Mins)

Temperature (°C)

Pass 1 Temp

Pass 2 Temp

Pass 3 Temp

Pass 4 Temp

248

212

176

140

104

 68

 

 

105
°F = (°C x 1.8) + 32

Figure 104. Graph. Temperature versus time segregated by location (cross section

B-E-G-I).

The similarities between the regression lines shown on figure 104 are not suggestive of any 

systematic variations in temperature through the depth of the mat. This is likely because of the 

thinness of the overlay (1.5 inches (38 mm)) and other limitations of the test (inaccuracies in the 

depth of the tags and nonuniformity of initial paving temperatures). Therefore, all depth 

locations were combined, and a single exponential regression equation was fit to the combined 

dataset, as shown in figure 105.

.

°F = (°C x 1.8) + 32

y = 97.473e-0.0109x

R2 = 0.9307

y = 106.87e-0.0125x

R2 = 0.8518

y = 119.83e-0.0196x

R2 = 0.7486

0

20

40

60

80

100

120

0 10 20 30 40 50 60

Time Since Paving (Mins)

Temperature (°C)

Bottom

Middle

Surface

Expon. (Bottom)

Expon. (Middle)

Expon. (Surface)

 

y = 103.16e-0.0129x

R2 = 0.7366

0

20

40

60

80

100

120

0 10 20 30 40 50 60

Time Since Paving (Mins)

Temperature (°C)

All Pts B-E-G-I

Expon. (All Pts

B-E-G-I)

 

106
Figure 105. Graph. Temperature versus time averaged across depth (cross section

B-E-G-I).

The exponential regression equation for the mat cooling at cross section B-E-G-I is shown in 

figure 106.

Figure 106. Equation. Exponential cooling equation at cross section B-E-G-I.

The corresponding regression equation for the mat cooling at cross section A-D-F-H is shown in 

figure 107:

Figure 107. Equation. Exponential cooling equation at cross section A-D-F-H.

These regression equations for the combined data are the basis for evaluating the traditional mat 

cooling models from the literature.

Variability and Reliability

In an effort to determine the reliability of the field test results and the consistency of the data 

collected, the following additional evaluations were made:

• Comparison of measured temperatures reported by single patch and monopole SAW 

RFID tags placed at the same location at the bottom of the mat.

• Comparisons of surface temperatures measured with the SAW RFID tags against 

independent measurements using a Fluke® infrared thermometer.

• Additional laboratory testing to determine the variability of temperature measurements 

from the SAW RFID tags based on errors generated by the reader.

These variability and reliability analyses were performed on the temperature data recorded from 

cross sections B-E-G-I and A-D-F-H.

To determine whether there were any systematic differences between the single patch and 

monopole tags, pairs of each were placed at the bottom of the mat approximately 2 ft (0.6 m)

apart within each group (see figure 97 and figure 98). A comparison of the temperatures 

measured by each tag type is presented in figure 108, figure 109, and table 20.

107
°C = (°F – 32)/1.8

Figure 108. Graph. Comparison of temperatures by tag type (cross section A-D-F-H, 

bottom of mat).

°C = (°F – 32)/1.8

Figure 109. Graph. Comparison of temperatures by tag type (cross section B-E-G-I, bottom 

of mat).

194

176

159

140

 

50

55

60

65

70

75

80

85

90

20 25 30 35 40 45 50

Time Since Paving (Mins)

Temperature (°C)

Monopole

Single

Patch

 

194

176

159

140

122

108
Table 20. Temperature comparisons at bottom of mat.

Cross Section A-D-F-H Cross Section B-E-G-I

Monopole Single Patch Monopole Single Patch

Temperature

(

o

F)

Temperature

(

o

F)

Time 

(min)

Difference

(percent)

Temperature

(

o

F)

Temperature

(

o

F)

Time 

(min)

Difference 

(percent)

166.5 169.0 21 1.84 167.5 163.6 28 2.92

172.8 172.8 25 0.00 148.5 151.0 32 2.12

169.2 182.7 28 8.96 153.9 148.1 39 4.73

149.0 153.3 31 3.56 143.4 137.7 49 5.17

157.1 162.0 36 3.74 — — — —

154.8 167.2 39 9.19 — —— — —

134.6 139.3 43 4.36 — — — —

153.9 155.1 45 1.02 — — — —

145.6 149.9 47 3.66 — — — —

144.9 156.7 48 9.52 — — — —

— Indicates no data collected

°C = (°F – 32)/1.8

The maximum difference in temperature measured by the two types of tags at the bottom of the 

mat was about 9 percent for cross section A-D-F-H at 28, 39, and 48 min after paving. The 

average temperature difference for all of the tags was 4.6 percent at cross section A-D-F-H 

(standard deviation of 3.5 percent) and 3.7 percent at cross section B-E-G-I (standard deviation 

of 1.4 percent). These differing temperatures may be due to a general inaccuracy of the tags 

(possibly a systematic bias) or to spatial variability. However, on average, the temperatures were 

consistent within a 5-percent difference.

Comparisons were also made between surface temperatures measured using the SAW monopole 

RFID tags and independent measurements using a Fluke® infrared digital thermometer are 

summarized in figure 110 and table 21. More significant temperature variations are exhibited in 

this comparison; the maximum temperature difference was about 30 percent at 22 and 45 min 

and about 25 percent at 32 min. In addition, the difference is widely sporadic and inconsistent 

(ranging from approximately 7 to 30 percent). This may be the result of the different 

technologies between the Fluke® thermometer and the SAW RFID tags or spatial variability of 

the temperature distributions as the locations of the infrared readings were as much as several 

feet from the corresponding SAW RFID measurements. A more thorough explanation may 

require additional laboratory and/or field testing.

An additional laboratory study was performed to determine the inherent variability of the 

temperature measurements from the SAW RFID tags. The study was performed at constant room 

temperature. Repeated readings were taken to determine any fluctuating temperature readings 

caused by the SAW tags and reader rather than the environment. The result of the test found a 

negligible fluctuation of about ± 0.36 °F (± 0.2 °C). The manufacturer also states that 

transmission interferences (wireless communication and magnetic fields) may contribute to 

inaccuracies. However, this is unlikely to have been a major factor in the field trials.

109
°C = (°F – 32)/1.8

Figure 110. Graph. Surface temperatures measured by SAW RFID tags versus Fluke®

infrared thermometer.

Table 21. Temperature comparisons at top of mat.

Fluke® Readings Surface Tag Readings

Time 

(min)

Temperature

(°F) Time

Temperature

(°F)

Difference 

(percent)

8 286 — — —

15 234 13 220 6.8

17 230 — — —

19 223 — — —

22 219 22 164 29.4

25 198 25 170 17.0

28 183 — — —

30 176 — — —

32 178 33 142 24.9

35 172 — — —

36 163 36 150 10.4

38 154 — — —

40 147 — — —

41 146 — — —

45 147 44 112 30.7

— Indicates data not available

°C = (°F – 32)/1.8

Conclusions: Field Evaluation

The overall findings from the field trials indicate that the SAW RFID tags can be used for 

measuring mat cooling temperatures during HMA construction. It is important, however, to 

understand that SAW RFID is still a developing technology—certain limitations and 

imperfections exist, but improvements in the technology are to be expected in the future. Specific 

conclusions related to various aspects of the field evaluation are described below. 

20

40

60

80

100

120

140

160

0 10 20 30 40 50

Time Since Paving (Mins)

Temperature (°C)

FLUKE

RF SAW

 

320

284

248

212

176

140

104

 

FLUKE®

110
Field Test Performance

• A temperature window must be specified in the RF SAW reader software to be able to 

read the in-place tags. This requirement may and did lead to operational issues in the 

field, particularly during the early stages of mat cooling when the temperature dropped 

rapidly, causing difficulty in setting the correct temperature window.

• The manufacturer recommends a 86 °F (30 °C) temperature window based on their 

calibration techniques at room temperature. The temperature window may be widened, 

but the software signal processing time then becomes longer and the signal 

strength/response of the tags decreases. The manufacturer’s recommended temperature 

window of 86 °F (30 °C) was used for all of the field trials.

• There was difficulty differentiating physically damaged tags from those that simply could 

not be read immediately after paving/compaction. In other words, if a tag is 

nonresponsive to the reader, it might not be caused by destruction by vibratory 

compaction. It may be that the reader cannot get a response because the temperature 

window is incorrect or the tag signal is severely attenuated.

Field Test Results

• The field results generally show an exponential relationship between cooling 

temperatures and time. This generally agrees with theoretical considerations that suggest 

exponential cooling.

• No systematic temperature variations with depth were observed during mat cooling. In 

other words, the measured temperatures at the bottom, middle, and top of the asphalt mat, 

at any given location and time, were all within the variability range of the sensors. This 

may simply be a consequence of the thinness of the lift on this particular project.

Variability and Reliability

• Based on the comparative study at the bottom of the mat between the two types of tags 

(single patch and monopole) and previous laboratory testing, the temperatures recorded 

by the two tag types are reasonably consistent and accurate.

• The comparative study at the surface of the mat between the Fluke® infrared 

thermometer and monopole tag found inconsistencies between the two sets of readings.

This may due to spatial variability. Additional field and/or laboratory testing are required 

for further explanation.

COMPARISONS BETWEEN PREDICTED AND MEASURED MAT COOLING

The mat cooling response measured using the SAW RFID tags is compared with the predicted 

temperatures versus time and depth from theoretical/numerical models. As will be described 

later, these comparisons require some field calibration of the model input parameters, given that 

there are no laboratory-measured values of the thermal properties for the mix placed at the field 

test site. The principal objectives of the comparisons between measured and predicted cooling 

response are the following:

111
• Determine whether the use of RFID technology to measure HMA cooling temperatures 

was accurate and successful.

• Identify improvements in the overall process of measuring mat cooling temperatures 

using RFID technology.

• Calibrate via a sensitivity analysis the values for the model input parameters that provide 

reasonable and close agreement with the field measured temperatures.

Analysis Inputs

The finite difference calculations for the analyses are based on figure 68 for the conduction 

calculations at the interior points and figure 72 for the heat balance at the mat surface. Table 22

summarizes the input parameter values used for the model predictions. These were selected 

based on recommendations from previous investigations and the results of the input parameter 

optimization presented later. Because the field construction was performed at night, the impacts 

of solar radiation (HS) and absorptivity (a) are negligible. The convective heat transfer 

coefficient value corresponds to free convection at zero wind velocity. This is consistent with 

weather station data at the time of paving.

Table 22. Input parameters used in models. 

Property Units Symbol Used

Thermal conductivity BTU/ft-h-°F k 0.64

Thermal diffusivity ft2/h α 0.0213

Convective heat transfer coefficient Dimensionless h 1.30

Thermal emissivity Dimensionless ε 0.95

1 BTU/ft-hoF = 1.73 W/moK

1 ft2

/h = 0.093 m2/h

The depth and time increments for the finite difference calculations are summarized in table 23. 

Temperatures are calculated every 0.25 inches (6.4 mm) of depth through the 1.5-inch (38-mm) 

overlay and for an additional 6 inches (150 mm) into the underlying asphalt base. This is 

assumed to be a sufficient depth across which conductive heat flows are negligible over the 

duration of the analyses. The time step shown in figure 111 was selected to satisfy the stability

requirement for the Euler time integration algorithm:

Figure 111. Equation. Stability requirement for Euler time integration algorithm.

The temperature at the lower boundary was fixed at 81 °F and the ambient air temperature was

set at 71 °F. The initial conditions are a uniform 305 °F temperature for the HMA in the overlay 

and a uniform 81 oF temperature in the underlying base asphalt. The base asphalt and ambient air 

temperatures were measured during the field trials. The initial HMA temperature of the overlay 

was provided by MDSHA. 

Δt ≤

Δyy2

2αα

112
Table 23. Input parameters used in finite difference solution. 

Calculation Parameter

Minimum

Value

Maximum

Value

Step 

Increment

Depth step, y (inches) 0 71⁄2 1⁄4

Time step, t (min) 0 60 ~ 0.3

1 inch = 25.4 mm

Predicted Mat Cooling Response

Figure 112 illustrates the predicted temperature versus time trends at the bottom, middle, and 

surface of the overlay and the average predicted temperature through the overlay thickness. As 

shown in the figure, the bottom of the mat expels the most heat initially, but as time elapses, the 

surface expels more heat than the bottom. These trends are consistent with those observed by 

Jordan and Thomas.(16) Figure 113 displays these cooling trends more explicitly as changes in 

temperature per time step versus time. The temperature at the bottom of the mat initially drops 

more than 20 °F (11.2 °C) and then exponentially drops another 1 °F (0.56 °C) over the rest of 

the cooling process. The temperature of the surface of the mat initially drops about 13 °F

(7.2 °C) and then, at about 2 min, begins to expel more heat than the bottom of the mat.

°C = (°F – 32)/1.8

Figure 112. Graph. Finite difference solutions for bottom, middle, and surface of mat.

Δ

Δ

0

50

100

150

200

250

300

350

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins.)

Temperature in Fahrenheit

FD, Surface

FD, Middle

FD, Bottom

Average

 

113
°C = (°F – 32)/1.8

Figure 113. Graph. Cooling trends at the bottom and surface of the asphalt mat. 

Figure 114 displays the temperature trends of the asphalt base as it heats and then cools as a 

result of conductive heat transfer from/to the HMA overlay. The asphalt base has an initial 

temperature of 81 °F and, upon placement of the hot HMA overlay, rapidly heats up via 

conduction. Over time, as the HMA overlay cools by convection and radiation, the heated base 

material cools along with the overlay. These cooling trends are logical and match physical

expectations. 

1 inch = 25.4 mm

°C = (°F – 32)/1.8

Figure 114. Graph. Base material temperatures cooling over time due to conductive heat 

transfer. 

The decrease in temperature changes versus time at increasing depths within the base layer 

suggests that the arbitrary 6-inch (150-mm) depth for the lower fixed temperature boundary is 

0

2

4

6

8

10

12

14

16

18

20

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins.)

Change in Temperature by Time Step 

(Fahrenheit/Minutes)

Heat Loss,

Bottom

Heat Loss,

Surface

 

0

50

100

150

200

250

300

350

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins)

Temperature in Fahrenheit

0.3-inch below HMA

0.6-inch below HMA

1.2-inch below HMA

2.3-inch below HMA

4.7-inch below HMA

Bottom of Overlay

 

114
sufficiently distant. As additional confirmation, figure 115 compares predicted cooling curves 

assuming base thicknesses of 0, 1, 3, 6, and 8 inches (0 25, 75, 150, and 200 mm). The cooling 

curves stabilize once the thickness of the base material exceeds 3 inches (75 mm). 

1 inch = 25.4 mm

°C = (°F – 32)/1.8

Figure 115. Graph. Impact of lower boundary depth on average predicted temperature 

profile. 

The results in figure 112 through figure 115 all suggest that the finite difference solutions are 

correct and a relatively accurate representation of field conditions. Figure 116 and figure 117

compare the calculated temperature trends at the surface, middle, and bottom of the mat with the 

corresponding measured data from cross sections A-D-F-H and B-E-G-I, respectively. As an 

additional check on accuracy of the predictions, Figure 118 compares the calculated 

temperatures at the surface against measured values obtained using the Fluke® infrared 

thermometer.

°C = (°F – 32)/1.8

0

50

100

150

200

250

300

350

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins.)

Temperature in Fahrenheit

0-inch base

1-inch base

3-inch base

6-inch base

8-inch base

 

0

50

100

150

200

250

300

350

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins.)

Temperature in Fahrenheit

FD, Surface

FD, Middle

FD, Bottom

A-D-F-H, Surface

A-D-F-H, Middle

A-D-F-H, Bottom

 

115
Figure 116. Graph. Predicted versus measured temperatures at cross section A-D-F-H. 

°C = (°F – 32)/1.8

Figure 117. Graph. Predicted versus measured temperatures at cross section B-E-G-I. 

°C = (°F – 32)/1.8

Figure 118. Graph. Predicted versus measured surface temperatures. 

The results in figure 116 and figure 117 show generally good agreement between measured and 

predicted temperatures over time. However, it is difficult to discern any systematic correlations 

between the calculated curves and the measured temperature values as a function of depth. This 

is most likely due to the thinness of the overlay and the imprecision in locating the RFID 

temperature sensors at specific depths. The comparison in figure 118 between the predicted 

temperatures at the surface and the measured values as obtained by the infrared thermometer are

good in terms of trends, but the measured temperatures are consistently higher than the predicted 

values. This may indicate either errors in the finite difference predictions at the surface or, as 

0

50

100

150

200

250

300

350

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins.)

Temperature in Fahrenheit

FD, Surface

FD, Middle

FD, Bottom

B-E-G-I, Surface

B-E-G-I, Middle

B-E-G-I, Bottom

 

0

50

100

150

200

250

300

350

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins.)

Temperature in Fahrenheit

FD, Surface

Thermometer

 

116
described previously, inaccuracies in the infrared temperature measurements due to spatial 

variability.

Because it was impossible to detect any systematic variations in measured temperatures through 

the depth, all depth locations were combined and fit with an exponential regression equation at 

each cross section as presented earlier in figure 106 and figure 107 for cross sections A-D-F-H

and B-E-G-I, respectively. Figure 119 and figure 120 show the comparisons between the 

predicted temperatures and the exponential fits to the measured temperatures at the respective 

cross sections; figure 121shows the combined results from the two cross sections. 

°C = (°F – 32)/1.8

Figure 119. Graph. Average measured versus predicted mat cooling at cross section 

A-D-F-H.

°C = (°F – 32)/1.8

Figure 120. Graph. Average measured versus predicted mat cooling at cross section

B-E-G-I. 

0

50

100

150

200

250

300

350

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins.)

Temperature in Fahrenheit

FD, Bottom

FD, Middle

FD, Surface

Cross-section

A-D-F-H

 

0

50

100

150

200

250

300

350

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins.)

Temperature in Fahrenheit

FD, Bottom

FD, Middle

FD, Surface

Cross-section

B-E-G-I

 

117
°C = (°F – 32)/1.8

Figure 121. Graph. Average measured versus average predicted mat cooling.

The following observations can be made from the results in figure 119 through figure 121:

• The curvatures of the measured exponential curves are relatively close to the calculated 

curve, with the exception of the early portion of the response. However, in terms of 

temperature accuracy, the average curve and exponential curves begin to show a close 

correlation only after about 15 to 20 min after paving. The early-stage comparisons are 

complicated by the fact that the tags did not return any data until about 8 min after 

paving. Nonetheless, it seems clear that the tag and calculated temperatures are not 

consistent in trend and curvature during the early stages of cooling. Further field 

investigations may be required determine the causes for this inconsistency.

• Experience suggests that an average mat temperature of 175 °F (79 °C) is the threshold 

below which compaction is no longer economical or may even be injurious to the 

pavement (e.g., because of aggregate breakage). Therefore, temperature data from the 

time of initial paving to when it reaches 175 °F (79 °C) are considered the most valuable. 

Figure 122 superimposes the 175 °F (79 °C) line on the data from figure 122. The 

predicted and measured temperature data show close agreement only for about the last 

5 to 10 min before the curves meeting the 175 °F (79 °C) threshold.

0

50

100

150

200

250

300

350

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins.)

Temperature in Fahrenheit

Average

Cross-Section

A-D-F-H

Cross-Section

B-E-G-I

 

118
°C = (°F – 32)/1.8

Figure 122. Graph. Measured curves compared with calculated average curve with 175 °F 

line. 

Conclusions: Comparisons Between Predicted and Measured Mat Cooling

The SAW RFID tags and equipment were successful in measuring the mat cooling temperatures 

during hot-mix asphalt placement. Comparisons with predictions from the finite difference 

computational models were generally favorable. However, there are inconsistencies between the 

predicted and measured temperatures, particularly during the early stages of the cooling response 

that may be due to limitations in technology, operator error, modeling error, or other causes. 

Further study is recommended to investigate and/or address the following:

• Recording temperature data immediately after paving rather than a few minutes 

afterward. This may be accomplished by preheating the tags to the initial asphalt 

temperature. The RF SAW reader software can then be adjusted more easily to read the 

tags immediately after paving.

• Improvement in the RF SAW reader and software to eliminate the need to set a 

temperature window. 

• Performance of more field trials that incorporate traditional temperature measuring 

instrumentation (e.g., thermocouples). Comparing the SAW RFID with the traditional 

instrumentation should identify any limitations or inaccuracies in the SAW RFID 

technology in this application.

• Determine an encapsulation method and material that optimizes the functionality of the 

tag in terms of readability, thermal response, and physical survivability.

SENSITIVITY ANALYSIS AND CALIBRATION TECHNIQUES

No laboratory tests to determine the input parameter values for the mat cooling model were 

performed in this study. Instead, typical initial estimates of the input parameter values were 

obtained from the literature. However, these values varied widely among the citations, and the 

0

50

100

150

200

250

300

350

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins.)

Temperature in Fahrenheit

Average

Cross-Section

A-D-F-H

Cross-Section

B-E-G-I

175°F Line

 

119
appropriateness of some of the recommended values was suspect. A series of sensitivity and 

calibration analyses were therefore performed to determine better values for the model input 

parameters to use in the numerical simulations described in the preceding section. These analyses 

provided additional confidence and validation that the numerical solutions are logical and correct 

as well as producing field-calibrated values for the inputs. The following subsections detail 

sensitivity analyses for the following inputs: thermal diffusivity and thermal conductivity, 

convective heat transfer coefficient, and emissivity. A calibration procedure to determine the 

input parameter values that produce the best fit between the measured and calculated 

temperatures is also described. This field calibration technique enables accurate predictions from 

the mat cooling model in the absence of laboratory measured input parameters.

Thermal Diffusivity and Conductivity

As described earlier, Luca and Mrawira conducted laboratory experiments to identify thermal 

properties for Superpave mixtures.(21) They measured thermal diffusivity and thermal 

conductivity k and compared their measured values with ranges cited in the literature (table 15

and table 16, respectively). 

The sensitivity analyses aim to determine how changes in thermal diffusivity and conduction 

affect the curvature, rate of cooling, and other characteristics of the predicted cooling response. 

Note that changes in thermal diffusivity also imply changes in the analysis time step to satisfy 

the stability requirement for the Euler time-integration algorithm as given by figure 111.

As shown in table 15, Luca and Mrawira found that thermal diffusivity may range from 

1.35x10-2 to 3.20x10-2 ft2

/h (1.25x10-3 to 2.98x10-3 m

2

/h). Five sample values within this range 

were therefore selected for the sensitivity analysis: 1.35 x10-2

, 1.56 x10-2, 2.13 x10-2, 2.24 x10-2, 

and 3.20 x10-2 ft2

/h (1.25x10-3, 1.45x10-3, 1.98x10-3, 2.08x10-3, and 2.98x10-3 m

2

/h). Similarly, 

Luca and Mrawira found that thermal conductivity may range from 0.58 to 2.24 BTU/fth-°F 

(1.0 to 3.9 W/moK) (table 16). Four sampled values within this range were therefore selected for 

the sensitivity analysis: 0.58, 0.64, 1.01, 1.19, and 2.24 BTU/fth-°F (1.00, 1.11, 1.75, 2.06, and 

3.88 W/mo

K). Luca and Mrawira emphasized that thermal diffusivity and conductivity are 

generally difficult to predict and measure. Therefore, parameter values that fall outside the 

ranges in table 15 and table 16 should not be considered infeasible. 

Figure 123 and figure 124 illustrate the results of the sensitivity analyses for thermal diffusivity 

and conductivity. Changing either the thermal diffusivity or the thermal conductivity values 

significantly affects the curvature and rate of cooling of the predicted mat cooling response. 

When interpreting the results in figure 123 and figure 124, it is important to remember that 

thermal diffusivity and conductivity are interrelated (see figure 65). Figure 123 shows that the 

rate of cooling increases with increasing thermal diffusivity. This is sensible; from figure 65, 

increasing at constant k implies a decreasing specific heat capacity Cp, i.e., decreasing thermal 

inertia, hence a faster cooling rate. Figure 124 shows that the rate of cooling decreases with 

increasing thermal conductivity. At first glance, this appears paradoxical, because one would 

intuitively expect that an increased ability to conduct heat would lead to faster cooling. However, 

the observed behavior is indeed sensible given the relationship in figure 65: increasing k at 

constant implies increasing specific heat capacity, i.e., increasing thermal inertia, hence a 

slower cooling rate.

α

α

α

120
k = 0.64 BTU/ft-ho

F (1.10W/moK)

°C = (°F – 32)/1.8

Figure 123. Graph. Sensitivity analysis for thermal diffusivity.

α = 2.13x10-2 ft2/h (1.98x10-3 m2/h)

°C = (°F – 32)/1.8

Figure 124. Graph. Sensitivity analysis for thermal conductivity.

Convective Heat Transfer Coefficient

Wolfe and Colony developed a relation for estimating convective heat transfer coefficients for an 

open highway construction environment that considered both free and forced convection 

principles.(17,18) After studying various methods for estimating the convective heat transfer 

coefficient h, Wolfe, Heath, and Colony recommended the relation in figure 73.

(19)

The sensitivity analysis for the convective heat transfer coefficient aims to determine how

changes in convection affect the curvature, rate of cooling, and other characteristics of the 

0

50

100

150

200

250

300

350

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins.)

Temperature in Fahrenheit

α=2.13

α=1.35

α=1.56

α=2.24

α=3.20

 

0

50

100

150

200

250

300

350

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins.)

Temperature in Fahrenheit

k=0.64

k=0.58

k=1.01

k=1.19

k=2.24

 

121
predicted cooling response. Table 24 displays a series of increasing wind velocities and their 

correlating value for the convective heat transfer coefficient when using the equation in 

figure 73. These convective heat transfer coefficients are used as input parameters for the 

sensitivity analysis. Figure 125 illustrates the results.

Table 24. Comparison of convective heat transfer coefficients.

Wind Velocity 

(mi/h)

Convective Heat 

Coefficient. (h) 

(BTU/ft2-h-°F)

0 1.30

2 2.34

4 3.05

6 3.68

8 4.25

10 4.79

1 BTU/ft-hoF = 1.73 W/moK

1 mi/h = 1.61 km/h

°C = (°F – 32)/1.8

Figure 125. Graph. Sensitivity analysis for the convective heat transfer coefficient. 

Based on the results in figure 125, altering the convective heat transfer coefficient does affect the 

curvature and rate of cooling of the mat cooling model. However, it is less pronounced than in 

the case of thermal diffusivity (figure 123) or thermal conductivity (figure 124). As the 

convective heat transfer coefficient increases, the curvature and rate of cooling increases. This is 

sensible; an increasing convective heat transfer coefficient means that more heat is lost through 

the surface, which, in turn, will cause the mat to cool more quickly.

Emissivity

Emissivity is the pavement surface’s relative ability to emit heat energy via radiation. It is 

defined as the ratio of the actual heat energy radiated by the pavement to the heat energy radiated 

0

50

100

150

200

250

300

350

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins.)

Temperature in Fahrenheit

h=1.30

h=2.34

h=3.05

h=3.68

h=4.25

h=4.79

 

122
by an idealized object that emits all radiation at the given temperature, i.e., a “perfect 

radiator.”

(15) Wolfe and Colony recommend a relatively narrow range of 0.90 to 0.95 for the 

emissivity of an asphalt surface.(17) Therefore, a sensitivity analysis comparing values 0.90 

through 0.95 was performed to determine its effect on the curvature, rate of cooling, and other 

characteristics of the predicted temperature response. The results displayed in figure 126 suggest 

that altering the input value for emissivity has little impact on the curvature and rate of cooling 

of the predicted cooling response.

°C = (°F – 32)/1.8

Figure 126. Graph. Sensitivity analysis for emissivity. 

Input Parameter Optimization Via Calibration

An optimization was performed on the input parameters using Microsoft® Excel Solver to 

determine the input values providing the best agreement between the measured and calculated 

temperatures. Based on the literature, it is known that the input parameters (thermal diffusivity, 

thermal conductivity, convective heat transfer coefficient, and emissivity) are not easily 

predicted or measured. Determination of these values through a field calibration process may 

expedite use of the mat cooling models by eliminating the need for laboratory testing to 

determine the input parameters.

To perform the optimization, the predicted temperatures from the mat cooling model are 

compared with the actual field-measured temperatures. The sum of the squared residual values 

between the predicted and measured temperatures is minimized in the Microsoft® Excel Solver 

tool by changing the input parameters for thermal diffusivity, thermal conductivity, convective 

heat transfer coefficient, and emissivity. Constraints are set within Solver to prevent negative 

values. 

Two optimizations were performed: one that held the convective heat transfer coefficient h

constant at 1.3 (figure 73 for the negligible wind speed observed in the field) and one that also 

optimizes h. Table 25 and table 26 summarize the results from both optimizations. Figure 127

compares the predicted cooling curves using the input values from the two optimizations. Both 

0

50

100

150

200

250

300

350

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins.)

Temperature in Fahrenheit

ε=0.90

ε=0.91

ε=0.92

ε=0.93

ε=0.94

ε=0.95

 

123
sets of optimized input parameters produce identical calculated average cooling curves. 

Therefore, based on the sensitivity analysis and recommendations from the literature, the 

selected input parameters used in this study have been taken from table 25, with the value of the 

convective heat transfer coefficient as recommended by Wolfe, Heath, and Colony.

(19) However, 

table 26 would have equally sufficed.

°C = (°F – 32)/1.8

Figure 127. Graph. Comparing both sets of optimized input parameters for the mat cooling 

model. 

Table 25. Results of Optimization #1—h constant. 

Property Units Symbol Used

Thermal conductivity BTU/ft-h-°F k 0.64

Thermal diffusivity ft2/h 0.0213

Convective heat transfer coefficient Dimensionless h 1.30

Thermal emissivity Dimensionless 0.95

1 BTU/ft-hoF = 1.73 W/moK

1 ft2

/h = 0.093 m2/h

Table 26. Results of Optimization #2—h optimized. 

Property Units Symbol Used

Thermal conductivity BTU/ft-h-°F k 0.49

Thermal diffusivity ft2/h 0.0212

Convective heat transfer coefficient Dimensionless h 0.42

Thermal emissivity Dimensionless 0.93

1 BTU/ft-hoF = 1.73 W/moK

1 ft2

/h = 0.093 m2/h

These successful optimizations demonstrate that it is possible to field-calibrate thermal 

diffusivity, thermal conductivity, convective heat transfer coefficient, and emissivity. For a 

specific paving construction project, these input parameters can be determined by field 

0

50

100

150

200

250

300

350

0 10 20 30 40 50 60

Time Elapsed Since Paving (Mins.)

Temperature in Fahrenheit

ε=0.90

ε=0.91

ε=0.92

ε=0.93

ε=0.94

ε=0.95

 

α

ε

α

ε

124
calibration to limited field temperature measurements at the beginning of the project, eliminating 

the need for complex laboratory testing. 

Conclusions: Sensitivity Analysis and Calibration Techniques

Each of the major input parameters was analyzed for its individual impact on the predicted 

cooling response. These sensitivity analyses provide added confidence that the numerical 

solutions are logical and correct. The following results were obtained:

• Thermal diffusivity: Based on the results shown in figure 123, altering the thermal 

diffusivity significantly affects the curvature and rate of cooling of the predicted 

response. As the value for thermal diffusivity increases, the curvature and rate of cooling 

increases. 

• Thermal conductivity: Based on figure 124, altering the thermal conductivity 

significantly affects the curvature and rate of cooling of the model. As the value for 

thermal conductivity increases, the curvature and rate of cooling decreases. 

• Convective heat transfer coefficient: Based on the results shown in figure 125, altering 

the convective heat transfer coefficient affects the curvature and rate of cooling of the 

mat cooling model. As the value for the convective heat transfer coefficient increases, the 

curvature and rate of cooling increases.

• Emissivity: Based on the results shown in figure 126, altering the emissivity has little 

impact on the curvature and rate of cooling of the mat cooling model.

A field calibration procedure using the Microsoft® Excel Solver tool successfully determined the 

optimum input parameter values for this study. For a specific paving construction project, the 

thermal diffusivity, thermal conductivity, convective heat transfer coefficient, and emissivity 

values may be determined by calibration to limited field temperature measurements at the 

beginning of the project, eliminating the need for complex laboratory testing.

OVERALL CONCLUSIONS AND LESSONS LEARNED REGARDING 

TEMPERATURE MEASUREMENT

The overall purpose of this study was to evaluate RFID-based wireless temperature sensors and 

traditional asphalt mat cooling models to predict temperature versus depth and time to better 

interpret stiffness feedback data from intelligent compactors. This work was done in conjunction 

with the FHWA Pooled Fund Study on Intelligent Compaction.

(25) More specifically, the 

objectives are as follows:

• Evaluate the feasibility of using SAW-based RFID technology to measure HMA 

temperatures via wireless sensors.

• Demonstrate, in the field, the survivability and temperature measurement capabilities of 

the SAW RFID sensors during a pavement overlay.

• Consolidate data to develop asphalt cooling curves of measured temperature versus time.

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• Compare measured cooling response with predictions from theoretical mat cooling 

models.

• Perform a sensitivity analysis of the effect of relevant input parameters in the theoretical 

mat cooling models on the predicted cooling response. From the sensitivity analysis, 

explore field-calibration techniques to expedite the use of the mat cooling models without 

requiring laboratory measured input parameters.

Based on the evaluations and experiments performed in this thesis, the following conclusions 

were reached regarding the above-mentioned objectives:

Laboratory Evaluation

Through laboratory analysis and information from the literature, an encapsulation process was 

developed to protect the SAW RFID tags from physical damage (during construction) while 

promoting heat transfer. It is recommended that additional work be performed to determine the 

minimum thickness of the epoxy coating to optimize tag readability while ensuring survivability.

In terms of signal strength and readability, both the encapsulated monopole and patch antenna 

tags showed acceptable performance when encased in HMA specimens. The monopole tags,

while more practical and compact in size, do not perform as reliably as the patch tags in terms of 

signal strength and readability. Both tags performed the best when aligned closely to “orientation 

#1/rotation #1” (see figure 85 and figure 86). Regarding thermal response, a thermal lag was 

observed after exposing the encapsulated tags to hot material. This lag is defined as the time 

required for the tag to “heat up” to match its environment. The encapsulated single patch tags 

required the longest thermal lag of about 5 min.

Field Evaluation

Overall, the findings from the field evaluation were that the RF SAW RFID tags can measure 

asphalt mat cooling temperatures during paving and compaction. It is important to note SAW 

RFID is a developing technology—certain constraints and imperfections exist, and 

improvements in the technology are expected in the future. The following subsections 

summarize the conclusions from the field evaluation in terms of field test performance, field test 

results, and variability and reliability:

Field Test Performance

The RF SAW tag reader requires a narrow temperature window to read the in-place tags. This 

requirement led to operational issues in the field, especially during the early stages of the asphalt 

cooling when temperatures dropped rapidly. The manufacturer recommends a 86 °F (30 °C)

temperature window based on their calibration techniques at room temperature. It is 

recommended that additional future field tests be performed to more closely monitor the initial 

temperature of the HMA, perhaps by preheating the tags so that they can be read immediately 

after paving. Alternatively, the manufacturer of the SAW RFID technology could eliminate the 

use of a temperature window from the reader software.

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There was also difficulty differentiating permanently damaged tags from those that simply could

not be read immediately after paving/compaction. In other words, if a tag is nonresponsive to the 

RF SAW reader, it might not be caused by destruction due to high temperatures or vibratory 

compaction. It may be that the reader cannot get a response because the temperature window is 

incorrect or the tag’s signal is severely attenuated.

Field Test Results

The field results generally show an exponential relationship between cooling temperatures and 

time. This generally agrees with theoretical considerations that suggest exponential cooling. No 

systematic temperature variations with depth were observed during mat cooling. In other words, 

the measured temperatures at the bottom, middle, and top of the asphalt mat, at any given 

location and time, were all within the variability range of the sensors. This may simply be a 

consequence of the thinness of the lift on this particular project.

Variability and Reliability

Based on the comparative study at the bottom of the mat between two sets of tags (single patch 

and monopole) and previous laboratory testing, the temperatures recorded by the two tag types 

are reasonably consistent and accurate. The comparative study at the surface of the mat between 

the Fluke® infrared thermometer and monopole tag found larger inconsistencies between the two 

sets of readings. This may be the result of testing at different locations on the mat surface.

Additional field and/or laboratory testing are recommended to resolve this issue.

Comparisons Between Measured and Predicted Mat Cooling Response

RF SAW RFID tags and equipment can be used for measuring the mat cooling temperatures 

during hot-mix asphalt placement. Predicted temperatures from the theoretical heat transfer 

model (using input parameters obtained from the literature and through field calibration) agreed 

with field measurements. However, there are inconsistencies between the two that may either be 

due to limitations in the technology or to operator error. Further testing is recommended to 

investigate and remediate the following:

• Recording temperature data immediately after paving rather than a few minutes 

afterward. This may be accomplished by preheating the tags to the initial asphalt 

temperature—during laboratory testing, the tags exhibit a thermal lag in meeting their 

intended temperature. The RF SAW reader software can then be adjusted to read the tags 

accordingly; or simply improved by the manufacturer.

• Incorporating traditional thermocouple temperature sensors that have been used 

successfully in the past. Comparing the SAW RFID with the traditional equipment can 

better identify any limitations in the SAW RFID technology for this application.

• Refining the encapsulation process to optimize readability and survivability. During the 

field trials, there was difficulty differentiating physically damaged tags from those that 

simply could not be read immediately after paving/compaction. In other words, if a tag is 

nonresponsive to the reader, it might not be caused by destruction by vibratory 

127
compaction. It may be that the reader cannot get a response because the temperature 

window is incorrect or the tag’s signal is severely attenuated.

Sensitivity Analysis and Calibration Techniques

Sensitivity analyses were performed on key input parameters, and a field calibration procedure 

was developed to optimize the accuracy of the theoretical cooling response predictions. The 

following conclusions were drawn from these analyses:

• Increasing thermal diffusivity increases the curvature of the cooling curve and the rate of 

cooling. 

• Increasing thermal conductivity reduces the curvature of the cooling curve and the rate of 

cooling.

• Increasing the convective heat transfer coefficient increases the curvature of the cooling 

curve and the rate of cooling.

• Emissivity has little impact on the predicted cooling response.

• The input parameter values for this study were determined through a field calibration 

process. Microsoft® Excel Solver can be used to optimize the thermal diffusivity, 

thermal conductivity, convective heat transfer coefficient, and emissivity values to 

minimize the discrepancies between predicted and measured temperatures. For any 

specific paving construction project, these input parameters can be determined by field 

calibration to limited field temperature measurements at the beginning of the project, 

eliminating the need for complex laboratory testing.

Lessons Learned

Based on the experiences and results of this study, the following lessons were learned:

• The encapsulation of the tags should be uniformly and minimally thin. In this study, the 

thickness of the encapsulant for each tag varied slightly, causing variability in the 

laboratory and field test results.

• To determine whether there is the possibility of systematic variation within a pavement 

layer, future testing should be performed on thicker pavement overlays. It was difficult to 

discern systematic variations in temperature versus depth for the very thin 1.5-inch

(38-mm) overlay examined in this study.

• Future field trials should be performed under daytime conditions so that the solar 

absorption terms in the mat cooling models can be exercised and evaluated.

128
CHAPTER 7: EARLY DETECTION OF REFLECTION CRACKS

INTRODUCTION

HMA overlays are among the most common rehabilitation methods for a deteriorated pavement. 

A properly designed overlay increases the structural capacity of the pavement, inhibits water 

from penetrating into the subgrade, and restores friction resistance. Rehabilitation using HMA 

overlays is also advantageous because of the short construction time required, which minimizes 

travel delays for road users. 

One of the most common distresses in HMA overlays is the development of new cracks in the 

overlay over the existing cracks or joints in the underlying deteriorated pavement. These are 

termed reflection cracks. Although reflection cracks can occur in HMA overlays over HMA 

pavements, they are most commonly experienced in HMA overlays over PCC pavements 

because of the regular transverse joints in the underlying layer. This latter type of reflection 

cracking is the focus here. Such cracks start at the bottom of the HMA layer at the joint locations 

between slabs and then propagate to the surface. 

The two most critical movements of the concrete slabs are shown in figure 128. Horizontal 

movements are caused by changes in temperature; these cause Mode I or opening mode 

cracking. Vertical movements are caused by wheel loading; these cause Mode II or shear mode 

cracking. A good overview of Mode I and Mode II fracture mechanics can be found in Broek.(26)

Figure 128. Drawing. Horizontal and vertical movement of concrete slabs causing Mode I 

and Mode II cracking.

Reflection cracks begin at the bottom of the HMA overlay and gradually grow toward the 

surface. Once the fully propagated reflection cracks are observed at the surface, the damage is 

done. Water can penetrate through the reflection cracks in the asphalt layer to the subgrade, 

decreasing its structural capacity. During low temperature conditions, the entrapped water in the 

cracks expands as a result of freezing, causing further crack growth. As these cracks get wider, 

smoothness decreases and damage to vehicles increases.

Early detection of reflection cracks before they reach the surface is especially important for 

warranty projects. Cui et al. provide an overview of the implementation of warranties on 

highway projects.(27) In 1990, FHWA initiated Special Experiment Project Number 14 to 

129
encourage State transportation departments to implement contracting techniques that would 

lower overall project costs. By 2004, more than 30 States had used warranties in some of their 

projects. The use of warranties helps reduce lifecycle cost, improve quality, and encourage 

contractor innovation. 

The warranty period for HMA overlays has typically been 2 to 4 years. Reflection cracking may 

start during this period but may not become visible at the surface until later. The use of crack 

sensors can give the State transportation departments the ability to detect reflection cracking 

early, enabling them to make a more informed decision on holding the contractor responsible for 

either repairing the damage if still under warranty or allowing the department more time to set 

aside sufficient funds to cover damages.

Some research has been conducted on the use of RFID tags to detect cracks. However, most has 

not gone beyond the proposal stage. Morita and Noguchi envisioned the use of RFID tags to 

detect structural cracks in combination with electrically conductive paint or an electrically 

conductive sheet affixed to the structure and connected to the RFID tag using copper wire.(28)

When a crack initiates, the conductive paint breaks, resulting in an increase in resistance. The 

crack width could theoretically be predicted based on the reader–tag communication because the 

electrical resistance changes with varying crack width. However, Morita and Noguchi did not 

pursue this application any further than the proposal stage. Rather than using an RFID tag and 

reader, they directly measured the resistance of the electrically conductive paint strip as the crack 

propagated through the structure. 

Wood and Neikirk proposed a passive sensor to provide information about the condition of 

welded connections in steel structures after earthquakes.(29) Although they acknowledged the 

possibility of using RFID technology for this application, they did not explore this idea and 

instead pursued evaluation of electronic article surveillance stickers. Neither Morita and Noguchi 

nor Wood and Neikirk went further than hypothesizing that RFID technology could work in 

detecting fatigue cracks in concrete or steel structures. 

Growth of an initiated crack due to cyclic loading is classically expressed using Paris’ Law.(30)

As shown in figure 129, Paris’ Law relates the rate of crack growth to repeated loading cycles:

Figure 129. Equation. Paris’s Law for crack growth.

Where:

C = crack length.

N = number of loading cycles.

A, n = fracture properties of HMA.

ΔK = change in stress intensity factor during cyclic loading.

The stress intensity factor is a measure of the driving force for crack propagation. It depends on 

the geometry of the structure, the loading conditions and magnitudes, and the crack length. The 

130
stress intensity factor is very difficult to measure. In practice, it is often replaced by a proxy such 

as the CMOD. 

Lee et al. measured crack opening and crack growth in conjunction with tests to determine the 

optimum rubblized depth for preventing reflection cracking.(31) The tests were conducted in 

Mode I bending loading on 12- by 8- by 2-inch (300- by 200- by 50-mm) asphalt slabs. Two 

PCC slabs were separated by 0.4 inches (10 mm) to simulate an open joint. The concrete slabs 

were, in turn, supported on an engineered synthetic rubber pad 1.2 inches (30 mm) thick to 

simulate the foundation conditions. A crack gauge was used to measure the horizontal 

deformation at mid-depth of the asphalt slab. The results of the horizontal deformation and 

vertical propagation of the crack were measured as a function of loading cycles. The crack was 

observed to have propagated about 60 percent through the 2-inch (50-mm) overlay at about 

200,000 cycles. This corresponded to a horizontal deformation of about 0.018 inches (0.45 mm). 

This information provides some basis for estimating the range of displacement that must be 

considered during development of the crack sensor. 

This chapter describes the conceptual development of an RFID-based wireless sensor to detect 

reflection cracks before they reach the surface of the pavement and become visible. One of the 

great advantages in trying to detect reflection cracks in pavements is that the potential crack 

locations are well defined (i.e., over the joints in the underlying slabs) as opposed to 

conventional fatigue cracks, which can develop almost anywhere. Because of the potentially very 

low cost of RFID crack detection systems, they could conceivably be placed at all potential

reflection crack locations along an overlay rehabilitation project (i.e., at all joints in the 

underlying rigid pavement slabs).

The concept for the RFID-based wireless reflection crack sensor is to configure the RFID tag so 

that when a crack has grown to some critical length, the antenna circuit is broken, thus causing 

the tag to stop transmitting. Two possibilities where explored: a conductive paint that would 

crack at a certain strain, and an overlapped copper antenna “microswitch” that would open at a 

certain CMOD. Key factors in the sensor development are read range and survivability. In the 

field, the sensor must be readable through the thickness of the asphalt overlay and at least 1 to 

2 ft (0.3 to 0.6 m) of air. The sensor must be able to survive the high temperatures and 

compaction stresses of paving operations. 

As documented in this chapter, the RFID-based wireless crack detection system has been 

developed well beyond the basic conceptual stage. Prototypes were developed and successfully 

evaluated via laboratory testing and field trials. Unfortunately, project schedule and resources 

preluded comprehensive field evaluation over sufficiently long time periods to validate the 

ability of the system to detect early-onset reflection cracks under in-service pavement conditions. 

CRACK DETECTION SENSOR DESIGN

The concept for early detection of reflection cracks is to adapt an RFID tag to “fail” in the sense 

that it can no longer be read once a significant crack initiates. To achieve this functionality, a 

short section of the antenna link is replaced with a conductive but frangible link. The modified 

RFID tag is placed above a joint in an existing PCC pavement layer before paving the HMA

overlay. When the frangible antenna link fails at a prescribed strain level, the RFID tag stops 

131
working, indicating the initiation of a reflection crack. RFID tags could be placed in pairs at the 

bottom of the HMA overlay, one crossing the joint in the underlying PCC slab and one parallel 

and slightly away from the joint. Failure of the tag crossing the joint while the companion tag 

remains readable would be a clear indicator of early reflection crack formation.

The RFID tags used for this project are the Avery DennisonTM AD-223 shown in figure 130. 

These are UHF Gen 2 tags with the Monza® 3 chip, the newest chip developed from Impinj®. 

The chip is cut from the tag, leaving about 0.075 inches (2 mm) of the original antenna as shown 

in figure 131. The modified antenna is then connected to the 0.075-inch (2-mm) stub. The reader 

used for all of the tests in this chapter is the Mercury® 5 ThingMagic reader. 

The efficiency of an antenna is governed by its electrical reactance. Reactance is a measure of 

the effect of capacitance and inductance on a time-varying current. A half-wave dipole has a 

reactance of zero. A shorter than half-wave antenna has a capacitive reactance, and a longer one 

has an inductive reactance. In this chapter, all the read range tests have been conducted for a 

half-wave dipole and shorter. 

When shortening the tag from the half-wave dipole, capacitive reactance is introduced, which 

causes deterioration of the tag’s read range performance. This is because part of the signal is 

“wasted” as stored electromagnetic energy in the reactive capacitance. 

Note: Overall tag length is approximately 6 inches (150 mm).

Figure 130. Photo. RFID tag AD-223. 

Figure 131. Photo. RFID chip with 0.075 inches (2 mm) of antenna on each side.

132
In practice, the length of the RFID dipole antenna can be shortened by introducing a frangible 

link that breaks at a target strain or displacement level. Two types of frangible antenna links 

were investigated. The first one is based on electrically conductive paint designed to break at a 

critical strain level. The second uses slightly overlapped metal strips to form a microswitch in the 

antenna that opens—i.e., breaks the antenna connection—at a critical CMOD. In both cases, the 

modified RFID tag is required to work/give a readable signal from a given distance before a 

crack has initiated and give no readable signal from the same distance after a crack has initiated 

but not yet appeared on the surface of the pavement. 

Conductive Paint Antennae

Read Range

A conductive paint was initially thought to be the best choice for the frangible link, in large part 

because of the ease and flexibility of its application. The read ranges for three possible antenna 

configurations were evaluated: a loop antenna, a dipole antenna, and a C-shaped antenna. 

As a first attempt, Aquadag® ETM, a conductive carbon paint from M.E. Taylor Engineering, 

Inc., was used to paint a 0.2-inch (5-mm)-wide loop antenna connected to the RFID chip from 

the Avery DennisonTM tags. The loop antennae were painted on a flexible plastic substrate made 

from conventional transparency stock. Small dabs of a thicker silver conductive paint were used

to create better connections between the Aquadag® ETM paint and the chip. Three tags were 

made with loop antennae of one wavelength, two wavelengths, and three wavelengths as shown

in figure 132 through figure 134. 

Figure 132. Photo. One-wavelength loop antenna.

133
Figure 133. Photo. Two-wavelength loop antenna.

Figure 134. Photo. Three-wavelength loop antenna.

The loop antennae were 0.2 inches (5 mm) wide and 12.9, 25.8, and 38.7 inches (328, 656, and 

984 mm) in total length based on the wavelength calculation shown in figure 135:

Figure 135. Equation. Wavelength calculation.

Where:

= wavelength.

c = speed of light = 1.18x1010 inches/s.

ν = frequency = 915 MHz for UHF tags.

λ

134
The maximum read distance was evaluated for all tags, with results shown in table 27. All the 

readings were taken over 20-s intervals on the T (transmit) side of the antenna. 

Table 27. Read range for the carbon paint loop antenna tags.

Number of 

Wavelengths

Maximum Read Distance

Inches Meters

1 1.3 0.41

2 1.6 0.50

3 1.4 0.44

The maximum read range for the loop antennae through air was 1.6 ft (0.5 m), which is marginal

in the field when the tag is placed at the bottom of the HMA overlay. In an effort to extend the 

read range, the loop antennae were replaced with dipole antennae. Typically, dipole antennae are 

created by two quarter-wavelength conductors extending from a central connection; this was 

done using the conductive paint. As with the loop antennae, silver paint was used to create better 

connections between the Aquadag® ETM paint and the chip. Figure 136 illustrates one of the 

fabricated dipole antennae and RFID chip. The maximum read distance for the dipole tag was 

approximately 4 ft (1.2 m). 

Figure 136. Photo. Dipole carbon paint antenna.

The read performance of the half-wavelength dipole tag was evaluated as one of the antenna legs 

was shortened to simulate breakage by a reflection crack. A series of 0.2-inch (5-mm) cuts were 

made on one side of the dipole antenna, and the effect on maximum read range was evaluated. 

The results are shown in table 28. It can be seen that the maximum read distance starts dropping 

significantly after the antenna is shortened to about half of its original length. If the antenna is 

cut at about 0.4 inches (10 mm) away from the chip, the tag cannot be read at a distance beyond 

about 1.3 ft (0.4 m). This would imply that if the antenna were kept at a distance of 1.6 ft (0.5 m)

away from the embedded tag, the reader would be able to detect that the antenna had broken as a 

result of reflection cracking. A second dipole tag fabricated and tested in the same manner 

showed similar results. 

Close examination of the read ranges for the modified tag after cutting one side of the antenna 

(table 28) shows that the read range did not drop as precipitously as expected as the antenna 

length was shortened. Even when there was only about 0.8 inches (20 mm) left on one side the 

tag, it could still be read from about 2.0 to 2.6 ft (0.6 to 0.8 m). The larger the drop in read range 

135
after the antenna is broken, the easier it will be to detect whether a crack has initiated. For this 

reason, additional tests were conducted in which one side of the dipole antenna was already 

snipped at 0.8 inches (20 mm) as shown in figure 137. Read range was then measured as the 

other side of the antenna was progressively shortened. The antenna for these tests was made of 

silver conductive paint from Engineered Conductive Materials, LLC. The reason the tests were 

not continued with the carbon paint is because when one side of the antenna is only about 

0.8 inches (20 mm) in the half-wavelength carbon dipole, the maximum read distance is 

approximately 2.3 ft (0.7 m). This particular silver paint was used because it was thought that it 

might give better read ranges. 

Table 28. Read range for the carbon dipole tag with one side shortened. 

Antenna 

Length (inches)

Maximum Read 

Distance (ft)

3.2 4.0

3.0 4.0

2.8 4.0

2.6 4.0

2.4 4.0

2.2 4.0

2.0 4.0

1.7 4.0

1.5 3.8

1.3 3.0

1.1 2.8

0.9 2.7

0.7 2.6

0.6 2.1

0.5 1.5

0.3 1.2

0.1 0.7

0 0

1 inch = 25.4 mm

1 ft = 0.305 m

136
Figure 137. Photo. Silver dipole antenna with one side snipped at 0.8 inches (20 mm).

The results from these tests, summarized in table 29, show that it would be best to have both 

sides of the antenna break at a distance of 0.8 inches (20 mm) or less from the chip. Before

failure, this tag could be detectable at a read range of about 4.2 ft (1.3 m); after failure, the read 

range is about an order of magnitude smaller. Another similar test with the same silver paint was 

conducted for another possible configuration, a C-shaped antenna instead of a straight dipole, as 

shown in figure 138. The maximum read range for this tag with no cuts to the antenna was about 

8.2 ft (2.5 m). When one side of the antenna was trimmed to within 0.24 inches (6 mm) of the 

chip, the read range for the tag dropped to only about 1.5 ft (0.45 m). When both sides of the 

antenna were trimmed to within 0.24 inches (6 mm) of the chip, the tag could not be read at any 

distance. The reason for the C-shaped configuration is to cause the antenna to break 

simultaneously on both sides, which would give a much lower read range once the crack had

initiated than if it broke only on one side. However, the C-shaped antenna also keeps the size of 

the tag comparatively small, raising the concern that it cannot cover the entire area where a 

reflective crack might occur. This does not make it a good candidate for the crack sensor 

application. 

137
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. 

Left Side Antenna 

Length (inches)

Maximum Read 

Distance (ft)

3.2 4.2

3.0 4.0

2.8 3.8

2.6 2.8

2.4 2.7

2.2 2.5

2.0 2.1

1.9 2.0

1.7 1.4

1.5 1.2

1.3 1.1

1.1 1.0

0.9 0.8

0.7 0.4

0.5 0.3

0.3 0

0.1 0

0 0

1 inch = 25.4 mm

1 ft = 0.305 m

Figure 138. Photo. C-shaped silver dipole antenna.

The high conductivity of the silver paint allows evaluation of antenna effects for the “best 

case”—i.e., longest read range—conditions. However, as will be shown in a later section, the 

carbon paint was the only coating that broke anywhere near the target strain level and as a 

138
consequence, it is the coating that must ultimately be used to modify the RFID tag. For this 

reason, more modified tags having carbon paint dipole antennae were constructed and tested. As 

expected, the read ranges of the tags with the carbon paint were not as long as for the silver 

dipole antennae because of the lower conductivity of the carbon compared with the silver. The 

maximum read range of the tags with the carbon dipole antennae in these new tests was only 

about 1.6 ft (0.5 m) compared with about 3.9 ft (1.2 m) for the silver. Although in earlier tests 

(table 28), the carbon paint dipole also read up to 3.9 ft (1.2 m), because of variations from tag to 

tag it would be more cautious to base the decisions on the worst results. To capitalize on the 

properties of both materials, tags with hybrid dipole antennae combining both silver and carbon 

paint were fabricated. The 0.8 inches (20 mm) of the antenna closest to the RFID chip was 

painted with carbon and the rest of the dipole length was painted with silver paint, as shown in

figure 139. It was expected that this tag would have a maximum read range close to that of the 

pure silver dipole while at the same time have a frangible link at the critical location close to the 

chip that would fail at the target strain level. Read range test results for this hybrid silver and 

carbon dipole antenna tag are shown in table 30. The maximum read range before trimming the 

antenna length was 5.9 ft (1.8 m), comparable to the pure silver dipole antenna. The read range 

of the tag dropped by approximately 40 percent to 3.3 ft (1 m) or less as the remaining dipole leg 

was shortened to 0.8 inches (20 mm).

Figure 139. Photo. Silver and carbon dipole antenna.

139
Table 30. Read range for the silver and carbon dipole antenna as one side is shortened. 

Antenna Length 

(inches)

Maximum 

Read Distance 

(ft)

3.2 5.7

3.0 5.7

2.8 5.7

2.6 5.7

2.4 5.3

2.2 4.4

2.0 4.4

1.9 4.2

1.7 4.0

1.5 4.0

1.3 4.0

1.1 4.0

0.9 3.9

0.7 2.9

0.5 2.8

0.3 2.1

0.1 1.3

0 0.4

1 inch = 25.4 mm

1 ft = 0.305 m

The conclusion from these read range tests is that the dipole configuration is best for the crack 

sensor. Also, because of its higher initial read range before breakage and low read distance after 

the carbon paint is broken, the hybrid silver and carbon dipole antenna provides the best 

configuration for the reflection crack sensor. 

Fracture Strains

Initially, the critical strain at which the conductive paint was targeted to break was estimated to 

be about 1,000 based on elastic strain distributions at the bottom of an asphalt layer. 

Consequently, tests were conducted to find a conductive paint that broke at about that strain 

level. Two carbon conductive paints, two conductive silver paints, and one conductive silver 

epoxy were tested in the laboratory to determine the strain at which they would break. Details of 

these paints are given in table 31. They were strained in a four-point bending test using an

Instron® Model 1331 compression machine. A strip of each of the paints was painted on a 

plastic film. The painted film was then glued to the bottom of the beam. The adhesive used for 

this was SG496 (Omega® Engineering Inc.), a methyl-based cyanoacrylate 1-part glue 

commonly used for strain gages. A beam was fabricated from 7075-T6 aluminum, a material that 

remains elastic at strains up to 4,600 . The calculated beam dimensions to reach the target 

strain of 1,000 under reasonable applied load levels are shown in figure 140. An ohmmeter 

was used to measure the resistance in the painted strip of conductive paint to check for breakage. 

The complete test setup is shown in figure 141. Although the required critical strain was 

με

με

με

140
1,000 , the tests were run to the elastic limit of 4,600 . Unfortunately, none of the cured 

conductive paints broke at this strain level.

Table 31. Description of the conductive paints tested to determine failure strains.

Name Composition Supplier

Aquadag® ETM Water-based colloidal graphite M.E. Taylor 

Engineering, Inc.

Conductive Shielding Paint Carbon paint Stewart-MacDonald

Conductive Silver Paint 18-percent silver M.E. Taylor 

Engineering, Inc.

Conductive Silver Pen 45- to 50-percent silver M.E. Taylor 

Engineering, Inc.

Conductive Silver Epoxy Two-part electrically conductive 

silver epoxy

M.E. Taylor 

Engineering, Inc.

1 inch = 25.4 mm

1 ft = 0.305 m

Figure 140. Drawing. Beam dimensions for the four-point bending test. 

με με

141
Figure 141. Photo. Thin film test setup.

As a next step, another set of tests was developed to localize the strains similar to what occurs 

across the mouth of a fracture. Two polymethyl methacrylate (PMMA, trade name Plexiglas®) 

sheets were attached along the bottom of the beam; the sheets just touched each other, simulating 

the joints in the PCC slab in a pavement. This test specimen setup is shown in figure 142. Thin 

strips of the conductive paints were then painted across the simulated joint. The 18-percent silver 

conductive paint did not break. The carbon Aquadag® ETM conductive paint broke at about 

300 . Because the Aquadag® ETM paint actually broke, albeit at strain levels below the target, 

it was selected for the tag antenna studies described in the previous section.

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Figure 142. Photo. Painted Aquadag® ETM on the two abutting PMMA sheets.

Based on the read range tests from the previous sections, it was determined that the antenna 

needed to break close to the chip for the read distance to shorten significantly. In the PMMA 

plate test setup, the antenna would fail directly over the “pre-cracked” plates. However, this 

implies that in the field, one would need to paint directly on the top of PCC slabs or the 

underside of the overlay, which is not practical. A carrier for the paint was needed to force the 

maximum strains to occur next to the chip. Therefore, a new test configuration was developed. A 

4- by 9-inch (100- by 230-mm) polycarbonate polymer (trade name Lexan) sheet was fabricated 

with a 3.5-inch (90-mm)-diameter hole in its center to act as a stress/strain raiser. The 3.5-inch

(90-mm)-diameter hole in the 4-inch (100-mm)-wide Lexan sheet causes the elastic stresses and 

strains to increase by a factor of 10 in the ligaments at the edges of the hole. The plate length was 

chosen as 9 inches (230 mm) so that the Lexan sheet would fit between the middle rollers where 

the bending strains are constant in the four-point beam loading system. A continuous 0.2-inch

(5-mm) strip of Aquadag® ETM was painted along one edge of the plate (including over the 

ligament on one side of the hole), and a dipole tag with a 0.2-inch (5-mm)-wide antenna strip of 

Aquadag® ETM was painted along the other, as shown in figure 143. The dipole tag was painted 

so that the chip was slightly offset from the highest strain location in the ligament at the edge of 

the hole in order to break the antenna close to the chip. Two ohmmeters were used to monitor the 

conductivity in the painted strips to determine breakage. The antenna of the dipole tag broke 

about 0.2 inches (5 mm) away from the thinnest part of the ligament at a strain of about 

12,000 (after adjustment for strain magnification effects). The antenna broke very close to the 

chip as expected, after which the tag could not be read at long range. The continuous strip of 

paint on the other side of the plate did not break during the test. 

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143
Figure 143. Photo. Painted dipole tag on one side and painted Aquadag® ETM only on other 

side of the polycarbonate sheet.

Based on insights from an additional literature search on measurement of CMOD, a reasonable 

estimate is that a reflection crack will have initiated and grown partially but not completely

through an overlay at a CMOD on the order of 0.04 inches (1 mm). A CMOD of 0.04 inches

(1 mm) over a gauge length of 4 inches (100 mm) corresponds to a strain of 10,000 με. These 

strain levels cannot be achieved with the bending beam apparatus except when using the 

polycarbonate sheet with the hole for concentrating and magnifying the stress and strain levels. 

However, this apparatus was problematic in practice because of difficulties in getting a secure 

attachment to the bottom of the aluminum beam. For these reasons, direct tension tests were 

conducted to determine the failure strains of the paints. Direct tension dogbone specimens were 

fabricated from polycarbonate with the dimensions shown in figure 144. Two tests could be 

conducted simultaneously on the same specimen by coating the opposite sides. The test setup is 

shown in figure 145 and figure 146. The tests were run in displacement control mode at a rate of 

0.005 inches (0.127 mm) per min. Adhesion problems between the paint and the polycarbonate 

were observed in some of the previous bending tests; the paint in some cases would just fall off 

the polycarbonate sheet. To remedy this problem, the Aquadag® ETM carbon conductive paint 

was painted on a strip of watercolor art paper that had been glued to the polycarbonate specimen 

using strain gauge adhesive. The strips of paint were 0.2 inches (5 mm) wide. Figure 147 shows 

a typical strip of conductive paint on the polycarbonate specimen with wires for connecting the 

ohmmeters. 

144
1 inch = 25.4 mm

Figure 144. Drawing. Dogbone specimen dimensions. 

Figure 145. Photo. Direct tension test setup.

145
Figure 146. Photo. Direct tension test specimen attachment.

Figure 147. Photo. Conductive paint on the dogbone specimen.

146
The test was continued to a strain of 26,000 , well above the strain at which reflection cracks 

should initiate in an HMA overlay. The carbon paint did not break. There was some concern that 

the watercolor paper might be creeping and that therefore the carbon paint was not experiencing 

the true applied strains. To account for this possibility, the test was repeated with two strips of 

carbon paint applied directly on the polycarbonate specimen after its surface had been roughed 

with extra-fine sandpaper to enhance adhesion. The painted strips were 0.2 inches (5 mm) wide, 

similar to the first test. This test was continued to a strain of 25,000 , and the carbon paint still 

did not break, although some small cracks were visible.

One last tension test was conducted on the Aquadag® ETM carbon paint and the 18-percent silver 

conductive paint. The width of the painted strips was narrowed to 0.1 inch (2 mm) for this test on 

the assumption that a crack would propagate more easily over the narrower width. The test was 

run to 30,000 without any breakage/conductivity fault in either the carbon or the silver paint. 

The overall conclusion from all these tests is that while the carbon and the silver conductive 

paints can be used to make suitable antennae for the RFID chip, none was reliably brittle enough 

to serve as a frangible link. Therefore, the approach was changed from a strain-based brittle 

material concept to a simple displacement-based mechanical microswitch scheme for 

interrupting the antenna circuit, as explained in the following section. 

Antennae With Mechanical “Microswitch”

The final crack sensor design was based on modifying the antenna of an existing RFID tag using 

electrically conductive metal strips that overlap just enough so that the antenna mechanically 

opens or disconnects when a crack occurs. Essentially, the RFID crack sensor will behave like a 

switch, so when a crack occurs, the antenna circuit is broken and the tag turns off and gives no 

signal. 

It was decided that the crack sensor should be developed so that it detects cracks that have 

propagated through approximately 60 percent of the overlay. This corresponds to a 0.018-inch

(0.45-mm) overlap in the antenna microswitch.(26) One of the main reasons for this decision was 

to keep the crack sensor manufacturing as simple as possible. As the target overlap gets small, 

the fabrication becomes more difficult. 

A 36 gauge (0.005-inch (0.125-mm)-thick) copper sheet was cut into strips about 0.1 to 

0.15 inches (2 to 3 mm) wide for creating the dipole antenna of the RFID tag. One side of the 

dipole was connected to the 0.1-inch (2-mm) stub of the original antenna using the two-part

electrically conductive silver epoxy from M.E. Taylor Engineering, Inc., to assure a good 

connection. The other side of the dipole was fabricated to have a 0.018-inch (0.45-mm) overlap 

of the thin copper sheet over the stub of the original antenna.

To determine the best configuration of the dipole, read range studies were conducted for 

different antenna lengths as was done earlier with the conductive paint antenna. These tests were 

initially conducted in the Pavement Materials Laboratory at UMD. Because of inconsistencies in 

the indoor readings thought attributable to RF reflections from metal interior objects, the read 

range studies were moved outdoors to parking lot E behind the Engineering Laboratory Building 

at UMD to minimize any interference (figure 148). It was expected that the results would be less 

με

με

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147
variable and more reliable, and in addition, the outdoor conditions better represent the actual 

field scenario.

Figure 148. Photo. Read range tests in parking lot E.

The first set of tests was done for a symmetrical antenna, starting with a half-wavelength dipole 

with two sides of 3.2 inches (82 mm) each and then continuing by shortening each side of the 

dipole. For each length, readings were taken with one side alternately being connected and 

disconnected. The dipole tag was sandwiched between two thin polycarbonate pieces to keep it 

in place and to simulate the expected encapsulation of the sensor in the field. To create a good 

connection at the mechanical overlap, a wooden toothpick was sandwiched between the 

polycarbonate pieces on top of the overlap (figure 149). The readings were taken in four 

directions, north, south, east, and west. The tag was optimally placed in front of the transmit side 

of the antenna.

Figure 149. Photo. Symmetric dipole used in the read range study.

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The results for the symmetrical dipole read range are shown in figure 150. The maximum read 

distances are very similar in all four directions. Except for a slight anomaly at 6.7 inches

(170 mm), the maximum read distance consistently decreased as the total dipole length 

shortened. Some possible suitable configurations chosen from these results were the following:

• 4 inches (100 mm) dipole length;

Connected read at 7.6 ft (2.3 m);

Disconnected read at 1.6 ft (0.5 m).

• 3.5 inches (90 mm) dipole length;

Connected read at 5.2 ft (1.6 m);

Disconnected read at 1.3 ft (0.4 m).

• 3.1 inches (80 mm) dipole length;

Connected read at 4.4 ft (1.35 m);

Disconnected read at 1 ft (0.3 m).

Next, a read range study was conducted with one side of the dipole fixed at 3.2 inches (82 mm)

and the side other starting at 2 inches (50 mm) and then progressively shortened. The longer 

3.2-inch (82-mm) antenna leg contained the overlapped microswitch. The same testing method 

as for the symmetric antenna readings was followed. Readings were taken with the long side 

connected and disconnected. The dipole tag was put between two thin polycarbonate pieces and 

a toothpick was used as before to ensure a good connection at the overlapped microswitch

(figure 151). The readings were taken in four directions, north, south, east, and west. Two 

replicate tags were tested to evaluate reproducibility. Again, the tags were placed in front of the 

transmit side of the antenna for all readings. 

1 inch = 2.54 cm

Figure 150. Graph. Read range for the symmetric dipole in each direction connected and 

disconnected. 

Read Range Starting with a Half-Wave Length Dipole and Shortening 

Each Side by 1 cm

0

100

200

300

400

500

600

700

800

0 5 10 15 20

Symmetric Dipole Length (cm)

Maximum Read Distance (cm)

North Disconnected

South Disconnected

West Disconnected

East Disconnected

North Connected

South Connected

West Connected

East Connected

149
Figure 151. Photo. Asymmetric dipole used in the read range study.

The results of these tests are shown in figure 152 through figure 155. The read ranges for the 

four different directions were very similar, as were the readings from the two replicate tags. 

Based on these results, it was decided that the best dipole length for this application was 

3.2 inches (82 mm) on one side and 0.6 inches (15 mm) on the other. This configuration, when 

connected, could be read at more than 7 ft (2.1 m) but only at less than 1 ft (0.3 m) when 

disconnected. This difference in read ranges is large enough for the antenna to be read from a 

moving vehicle when connected and not read from that same distance when disconnected. The 

7-ft (2.1-m) read range when connected is actually greater than required in the field; however,

this adds a safety margin to help ensure that the tag can be read even after possible signal 

attenuation through the HMA overlay. 

1 inch = 2.54 cm

Figure 152. Graph. Read range for tags disconnected and connected in the north direction. 

150
1 inch = 2.54 cm

Figure 153. Graph. Read range for tags disconnected and connected in the south direction. 

1 inch = 2.54 cm

Figure 154. Graph. Read range for tags disconnected and connected in the east direction. 

151
1 inch = 2.54 cm

Figure 155. Graph. Read range for tags disconnected and connected in the west direction. 

PROTOTYPE DESIGN

Fabrication

Because the sensor must be placed on the surface of the existing pavement prior to the overlay, 

for practical field applications the RFID tag needs to be encapsulated to protect it from high 

temperatures and stresses during paving operations. However, the encapsulation must be able to 

transmit displacements to the antenna so that eventually the overlapped microswitch can open. 

Polycarbonate (LexanTM) was used for the encapsulation. Its melting temperature is 513 °F 

(267 °C) and its glass transition temperature is 302 o

F (150 oC), which are sufficient for paving 

conditions. The glue used for attaching the RFID tag to the polycarbonate and for assembling the 

polycarbonate parts was the SG496 strain gauge adhesive used previously in the laboratory 

studies.

The different parts used for encapsulating the tag are shown in figure 156, and the actual 

encapsulated tag is shown in figure 157. A 12-inch (300-mm)-long by 0.4-inch (10-mm)-wide 

piece of 0.095-inch (2.4-mm) thick polycarbonate was used as the top mounting plate for the 

RFID tag. This part transmits the crack opening movements in the overlay to the antenna. The 

12-inch (300-mm) length is sufficient to span the area where the reflection crack might initiate. 

A longitudinal groove deep enough to fit the RFID tag is cut into the mounting plate and the 

dipole ends are glued in the groove. Two small 0.6- by 2.0-inch (15- by 50-mm) cross pieces of 

0.18-inch (4.5-mm)-thick polycarbonate are glued to the end of the top mounting plate. The 

grooved polycarbonate bottom protection piece covers the dipole, and the mounting plate and is 

about 1.2 inches (30 mm) shorter than the top mounting plate. The bottom plate is glued only in 

one place to the top piece; the bottom plate provides a protection cover but does not interfere 

152
with the movements in the top plate and the sensor. Only the two cross pieces of the assembled 

sensor are to be affixed to the underside of the asphalt overlay. Once a crack initiates, these cross 

pieces begin to spread, putting the sensor into tension and decreasing the overlap in the 

microswitch until it opens and the RFID tag stops giving a readable signal. 

Figure 156. Photo. Parts for encapsulating the RFID tag.

Figure 157. Photo. H-sensor for reflection crack detection.

Field Survivability and Read Range

Field tests were conducted to determine the survivability of these tags when subjected to high 

temperatures and compaction stresses during paving. Another objective of the field tests was to 

finalize the length of the antenna by evaluating read ranges of various lengths of tags through an 

asphalt overlay. This would give a better understanding how the tags perform through HMA as 

opposed to just air. 

Eighteen RFID tags were prepared for the field tests. Two of them were encapsulated in the Hsensor configuration (figure 157). The other 16, however, were simply sandwiched between two 

0.4–inch (10-mm)-wide polycarbonate plates, one of which was grooved so that the chip would 

not be damaged. These tags were used to evaluate the optimum antenna length. To determine 

153
which antenna length would be the best for the crack sensor design, the maximum read distances 

for the connected case and disconnected case must be evaluated. The 16 tags were therefore 

paired in groups of two in which one tag was in the connected condition and the other 

disconnected. For simplicity, in the connected case, the copper antenna on either side of the chip 

was attached using conductive silver epoxy instead of overlapping one side. Six different 

lengths, as listed in table 32 , were evaluated. A 2-inch (50-mm) HMA milling and overlay 

project on Campus Drive at UMD was selected for the field trials. The encapsulated tags were 

placed longitudinally at 2-ft (0.6-m) intervals, as shown in figure 158. Quick set epoxy putty was 

used to make sure the tags were not displaced during the paving operations (figure 159 through 

figure 161). 

Two days after the paving was completed, a read range study was conducted (figure 162). The 

number of successful reads over a 20-s interval was recorded. Although some tags were run over 

by equipment during the paving operations, only 1 tag of 18 failed to give any readings. The 

results for the maximum read distances for the tags are given in table 32. The 5-ft (1.5-m) height 

entries do not necessarily represent the maximum distance at which the tags could be read; 5 ft 

was just the highest distance above the pavement that could be achieved in the field. Establishing 

the actual maximum read distance beyond 5 ft was not necessary because a bumper-mounted 

reader antenna would not be at a higher distance than that above the pavement. Based on the 

results, the symmetric dipole with a 1.6-inch (40-mm) antenna on each side of the chip was 

determined to be the best configuration. When connected, it read at least 5 ft (1.5 m), and when 

disconnected, it read at only about 0.6 ft (0.2 m). If the reader antenna were mounted anywhere 

from 1.6 to 5 ft (0.5 to 1.5 m) above the pavement, the tag would give a signal when there was 

no crack and would not read once there was a crack in the pavement. 

Figure 158. Photo. Encapsulated tags placed in the roadway prior to paving.

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Figure 159. Photo. Close-up view of one of the encapsulated tags.

Figure 160. Photo. Two H-sensors in the pavement prior to paving.

155
Figure 161. Photo. Paving in progress.

Figure 162. Photo. Read range test setup.

156
Table 32. Field test results. 

RFID 

Tag

Maximum 

Read 

Distance 

(ft)

Number 

of 

Readings

8x8 C 1.0 14

8x8 D 2.2 9

6x6 D 2.4 4

8x8 C 5.0 9

8x8 D 3.3 9

6x6 C 4.2 12

6x6 D 3.1 9

5x5 C 5.0 16

5x5 D 1.5 15

4.5x4.5 C 5.0 16

4.5x4.5 D 1.1 12

4x4 C 5.0 17

4x4 D 0.6 17

8x1.5 C 3.5 16

8x1.5 D 1.1 16

C = connected antenna 

D = disconnected antenna (simulating a crack) 

Note: Bold font indicates optimum antenna configuration. 

1 ft = 0.305 m

Laboratory Evaluation

A laboratory evaluation was undertaken to demonstrate that the crack sensor design can detect 

cracks in a 2-inch (50-mm) thick asphalt overlay. The end cross pieces of the encapsulated RFID 

tags were glued to the bottom of asphalt beams. The idea was that when the beam experienced a 

crack during three-point bending, the crack sensor microswitch would disconnect when the crack 

reached about 50 percent or more of the height of the beam. 

The asphalt specimens were prepared at the standard fatigue tests size of 15 inches (380 mm) 

length, 2.5 inches (63 mm) width, and 2.0 inches (50 mm) height. The sides of the asphalt beams 

where painted white to make it easier to observe cracking. The ends of the copper antenna were

glued to the grooved polycarbonate plate as shown in figure 163. Copper wires were glued to 

each side of the RFID tag antenna using conductive silver epoxy and then connected to an 

ohmmeter to measure resistance and determine at what point the conductivity was lost. The 

polycarbonate plate to which the RFID tag was glued was kept at a length equal to the effective 

length of the beam during bending. For the laboratory tests, the protective top cover for the tag 

was unnecessary and not used. However, to make sure the antenna overlap remained in place 

with a good connection, small polycarbonate pieces were glued across the groove over the 

microswitch.

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Figure 163. Photo. RFID tag glued to the asphalt beam.

The specimens were then loaded for three-point bending using an Instron® compression 

machine. The tests were run in displacement control mode at a rate of 0.2 inches (5 mm) per

minute. For the first three tests, the overlap of the copper antenna to the existing antenna was 

kept at about 0.02 inches (0.5 mm) as discussed previously. However, in all three instances the 

microswitch opened prior to a crack initiating. This could have been the result of several factors,

including the slow loading rate used during the three-point bending, the properties of the beam, 

and other details of the test setup. For this reason, the third test was continued until the crack 

propagated 50 percent through the beam thickness even though the antenna was disconnected. 

Based on this test, it was determined that an antenna overlap of about 0.06 inches (1.5 mm) was 

required.

The next step was to run a test that would more closely represent the use of the crack sensor in 

the field. Instead of measuring resistance, the reader and antenna were positioned close to the 

bending machine. Although even in air the 1.6- by1.6-inch (40 by 40 mm) RFID tag could not be 

read from further away than 5 ft (1.5 m), in the laboratory during the test it was read at a distance 

more than 6 ft (1.8 m). This was most probably because of wave reflections coming from the 

metal machines surrounding the antenna. The antenna was placed 6 ft (1.8 m) away from the 

RFID tag. The connection was lost at a vertical displacement of the asphalt beam of about 

0.8 inches (20 mm). At this point, the crack had propagated about 50 percent through the 2-inch

(50-mm) beam thickness at a CMOD of between 0.1 to 0.15 inches (2 to 3 mm) (figure 164). 

158
Figure 164. Photo. Crack propagation when the RFID tag stopped reading.

CONCLUSIONS AND RECOMMENDATIONS FOR REFLECTION CRACK

DETECTION

Conclusions

HMA overlays are the most common rehabilitation methods for deteriorated pavements, and the 

most common distresses in these rehabilitated pavements are reflection cracks. The development 

of a crack sensor for detecting early onset of reflection cracks would be beneficial to State 

transportation departments because they could hold the contractor responsible for repairs in 

warranty construction projects, and it would help them plan better for future rehabilitation 

activities. 

The reflection crack sensor concept is to implement a switch in the antenna circuit of the RFID 

tag: when there is no crack the RFID tag gives a signal that can be read at a distance, but after a 

crack forms, the signal becomes too weak to be read. The first design for the crack detection 

sensor employed conductive paint that would rupture at strain levels corresponding to a certain 

CMOD. The conductive paint dipoles had good read ranges, reaching about 6 ft (1.8 m). 

However, the drawback with the conductive paint was that none of the evaluated paints broke at 

the desired strain. The Aquadag® ETM carbon paint and the 18-percent silver paint survived 

strains up to 25,000 με without breaking.

The second sensor design was based on the use of copper antennae on both sides of the RFID 

tag, with one side having a mechanical overlap microswitch with the existing antenna cut from 

the original AD-223 RFID tags. A crack causes the antenna to be pulled in tension, eventually 

causing disconnection at the overlap microswitch and thus an open circuit in the antenna. 

The RFID tag was encapsulated between polycarbonate protective covers to protect it from the 

high stresses and temperatures of paving operations. The ends of the copper modified antenna 

159
were glued to the polycarbonate mounting plate, which is then affixed to the asphalt overlay. The 

plates both protect the tag and transmit displacements to the tag. 

A survivability check of the encapsulated tags was conducted by embedding them in a 2-inch

(50-mm)-thick overlay. Seventeen of 18 tags tested survived the paving operations; the tags 

could be read at distances of more than 5 ft in the optimal antenna configuration. Subsequent 

laboratory beam testing confirmed the concept of the overlapping copper antenna microswitch 

for the crack detection sensor. The sensor successfully detected the crack once it had grown to 

about 50 percent of the height of the beam.

As documented in this chapter, the RFID-based wireless crack detection system has been 

developed well beyond the basic conceptual stage. Prototypes were developed and successfully 

evaluated via laboratory testing and field trials. Unfortunately, project schedule and resources 

preluded comprehensive field evaluation over sufficiently long time periods to validate the 

ability of the system to detect early-onset reflection cracks under in service pavement conditions.

Recommendations

The tests to determine the amount of the overlap were conducted in a three-point bending 

configuration with a static load applied in the middle of the beam. This results in vertical 

deflections well beyond those expected in the field. Future tests should be conducted using a 

Texas Overlay Tester so that the beam fails in a way more similar to how the pavement would 

fail. Through these tests, the CMOD as a function of vertical crack propagation can be 

determined more accurately, and the overlap can be adjusted as needed. The flexibility of the 

design presented in this chapter allows one to use the sensor to detect small cracks or strains (less 

overlap) or detect larger cracks or strains (more overlap). 

Laboratory testing using the Texas Overlay Tester should be followed by field trials on inservice pavements. The duration of these field trials would need to be on the order of 5 to 

10 years to allow sufficient time for reflection cracks to initiate and propagate. 

160
CHAPTER 8: GUIDANCE ON DATA INTEGRATION

INTRODUCTION

To ensure—and ideally to improve—the performance of asphalt pavements, it is vital that the 

influence of material properties on performance be clearly understood. Correlations between asconstructed properties of asphalt concrete in construction databases and field performance of 

pavements in PMSs can quantify the link between material quality and performance. 

Unfortunately, the dissimilar ways in which these two sets of data are recorded with respect to 

location along the pavement alignment makes it difficult to establish these correlations. As 

depicted in figure 165, HMA concrete is produced at a production facility and then trucked to the 

highway construction site for offloading into the asphalt paver. HMA producers sample their 

production periodically from departing trucks and perform various QC tests to ensure that the 

mixture properties (gradation, volumetrics) remain within acceptable limits. As part of a QA 

program, agencies typically take additional samples for acceptance testing to corroborate the 

producer’s QC test results and to establish pay factors. QC and acceptance samples are typically 

taken at specified tonnage intervals from delivery trucks as they leave the asphalt plant. For 

example, in Maryland, a minimum of one QC sample (volume sufficient for the full suite of 

tests) is typically taken for each 1,000-T (909-t) sublot of production. This corresponds roughly 

to one truck out of every 50 leaving the plant production or approximately 1.25 lane-mi (2 lanekm) of paving for a 2-inch (50-mm) overlay. Test results from this sample are assumed to be 

representative of the entire 1,000-T (909-t) sublot. One acceptance sample is also taken for each 

day’s production (on the order of 4,000 T (3,636 t) or more). Additional in-place material 

sampling (cores for field density determination) is also typically performed on the compacted 

mat. All of these QA material property data can then be stored in the agency’s materials 

management system (MMS) by lot and sublot.

PMS data, on the other hand, are collected at regular intervals during the pavement life after 

construction and referenced to a specific location in the roadway. For example, in Maryland, an 

automated distress measurement vehicle (figure 165) collects roughness, rutting, and visual 

distress data for the entire State highway network on a 2-year cycle. These pavement 

management data are automatically referenced to the milepoint (or, alternatively, geospatial) 

location along the roadway. 

It is often desirable to compare the PMS distress data during the service life of the pavement 

with the material property data collected during construction—e.g., for forensic investigations 

into premature rutting, cracking, or other failures along a particular section of roadway. 

Unfortunately, at present there is no good practical way to determine precisely where in the 

roadway the sampled and tested lot/sublot of material was deposited. In many instances, the 

milepoint range for the entire 1,000 T (909 t) of production represented by the sampled truckload 

is not even recorded during construction. Unless the HMA QA data can also be tied to a spatial 

location along the pavement, it cannot be correlated with PMS data on anything better than a 

crude project-by-project basis.

These problems caused by mismatched referencing of pavement data were highlighted during a 

pilot implementation of the HMAView software by the MSHA. HMAView is a Web-based 

161
application for integrating construction, materials, pavement management, and other pavement 

data.

(27) For the pilot project implementation, the spatial location of the QA material property 

data measured during the original construction had to be laboriously and crudely estimated by 

hand.

Figure 165. Illustration. Referencing problem in linking pavement construction and 

pavement management data.

As described in chapters 2 through 4 of this report, inexpensive expendable electronic sensors 

based on passive RFID technology can be used to identify or tag truckloads of hot mix asphalt as 

they leave the production plant. These sensors pass through the paver and are compacted into the 

finished mat. After construction, a vehicle-mounted or handheld scanner is used to electronically 

“read” the identity tags and cross reference them with latitude and longitude coordinates using 

GPS technology. These geospatially referenced MMS data can then be directly linked to asconstructed in-place test results and thus to future pavement performance data recorded in the 

agency’s PMS, enabling robust statistical analyses of the correlations between material 

properties and observed performance.

The application of RFID technology for tracking HMA placement was the genesis for this entire 

research project. It is also the application that is most suited to near-term commercial 

implementation. Its major benefit is that it provides a simple and straightforward means for 

integrating an agency’s QA materials property data with its pavement performance 

measurements. However, several steps are needed to enable this data integration. Given the wide 

range of materials and pavement management systems in use among the States, the 

implementation of these steps will be different for each agency. The general guidelines provided 

162
in this chapter for the data integration steps can be adapted to each agency’s specific database 

structures, policies, procedures, and information technology infrastructure.

GUIDELINES FOR INTEGRATING MMS AND PMS DATABASES

A wide variety of MMSs and PMSs have been implemented by highway agencies nationwide. In 

some cases, these systems may have been developed in-house, either by agency personnel or by 

consultants, and subsequently modified and extended over time. This makes it difficult to 

develop a “one size fits all” set of guidelines for integrating these two sets of data. Therefore, the 

approach adopted here is to outline the general set of issues that must be addressed when 

integrating these two data sources and to illustrate them, where possible, using application 

examples from AASHTOWareTM’s SiteManagerTM product, Fugro’s Roadware/Vision software, 

the MSHA MarylandWare software, and other sources from the literature and, where 

appropriate, database examples using Microsoft® Access.

(28,29) (The Microsoft® Access 2007 

version is used.) The SiteManagerTM and Roadware/Vision software, in particular, are used by a 

significant number of State transportation departments for materials management and pavement 

management/data display, respectively.

The basic components required for implementing an RFID-based HMA materials tracking 

system and for integrating MMS and PMS databases are as follows:

1. Linkage of RFID identifiers to material samples collected at the plant or in the field. 

2. Linkage of GPS latitude and longitude coordinates to RFID identifier and thus to the 

material sample.

3. (Optional) Conversion of latitude/longitude to PMS location reference system (e.g., 

milepoints).

4. Extraction of MMS and PMS data by roadway location.

5. Display of extracted data for data analysis and other purposes.

Each of these components is discussed in more detail in the following subsections. The focus 

here is on QA material samples taken from RFID-tagged trucks as they leave the HMA 

production plant and the material property tests that are obtained from these samples. QA 

samples taken directly from the roadway are not considered here because the spatial location of 

these samples is known directly although they may not be recorded to allow linkage with the 

PMS. The terms used in these discussions are defined as follows:

• Tag: An RFID tag placed in a sampled transport truck as it leaves the HMA production 

plant. For redundancy, there will generally be multiple tags in a single transport truck.

• Tag ID: The digital identification label that is electronically coded into each RFID tag. 

• Material sample (or sample): The material sampled from a single truck as it leaves the 

HMA production plant. It is assumed here for simplicity that there is one sample per 

truck, but the logic could be easily generalized to multiple samples per truck.

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• Test: A QA material property test obtained for a material sample. There will in general be 

multiple QA material property tests (e.g., asphalt content, maximum specific gravity, 

etc.) associated with a material sample.

• Join: The relational database operation that combines information from multiple database 

tables based upon common data elements shared by the tables (e.g., ID fields).

Linkage of RFID Identifier to Material Samples

For redundancy, multiple RFID tags are deposited in each sampled truck as it leaves the plant 

because some of the tags may fail or be unreadable after being compacted into the roadway. In 

addition, multiple test specimens and test types may be associated with each sample in the MMS. 

The following two types of relationships must therefore be addressed:

• The many-to-one relationship between RFID tags and material samples.

• The one-to-many relationship between a material sample and the various test specimens 

that are prepared from the material sample.

Dealing with the second issue first, this classic one-to-many data relationship is incorporated 

directly into most MMSs, including the SiteManagerTM Laboratory Inventory Management 

System (LIMS) module. In SiteManagerTM LIMS, a sample ID is established first and then 

multiple test types are associated with it, as shown in figure 166. This can also be accomplished 

using a standard relational database join operation as illustrated schematically in figure 167

through Figure 169. The query, given both in terms of the Microsoft® Access 2007 query 

designer and its Structured Query Language equivalent, extracts the three material property 

values (two asphalt contents and one voids in the mineral aggregate measurement) from tests 

performed on material from sample 54321. Note that the query in figure 168 can be implemented 

in other and arguably more efficient ways; the particular query structure in 

figure 168 is designed to highlight the one-to-many relationship between material samples and 

material property tests.

164
Figure 166. Screen Capture. Assign Sample Tests screen from SiteManagerTM 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.

165
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.

The second issue of associating potentially multiple RFID tags IDs to a single material sample 

can be handled in either of two ways: 

1. Because the multiple RFID tags are intended to be redundant, only one of the readable 

tags in the set can be selected as representing the entire set. The linkage between RFID 

tags and material samples then simplifies to a one-to-one relationship. The tag ID can 

then be simply included as another data element in the material samples table.

2. If it is desirable to maintain the redundancy between tags and samples, a linking table and 

associated join operations can be established between RFID tags and material samples 

and thus between tags and test specimens, as illustrated schematically in figure 170

through figure 172. The Tag_Sample_Link table captures the many-to-one relationship 

between tag IDs and samples. The query passes this additional information along, 

generating a table of tag IDs and the material property values measured for all tests from 

the sample associated with the tag IDs. 

166
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.

167
Linkage of GPS Coordinates to RFID Identifier/Material Sample

By definition, there is a one-to-one relationship between GPS coordinates and an RFID tag ID—

i.e., the RFID tag can only be in one spatial location. The GPS coordinates can be entered 

directly into the Tags table after the tag has been interrogated by the vehicle-mounted reader and 

antenna system after construction. 

The linkage of GPS coordinates to material samples is a bit more difficult. As described in the 

preceding section, there may be one or more RFID tag IDs associated with a single material 

sample. Consequently, there may be one or more sets of GPS coordinates associated with each 

single material sample. This issue can be addressed via one of three possible approaches:

1. Single RFID tag/single set of GPS coordinates: Most MMSs permit entry of one-to-one 

location links for material samples. The current version of the SiteManagerTM LIMS and 

the MarylandWare QC/QA module permit direct entry of latitude and longitude for a 

sample; an example from the MarylandWare QC/QA module is shown in figure 173. The 

single set of latitude and longitude coordinates can be simply entered manually into the 

material sample screens. Alternatively, software utilities can be developed locally to 

automate entry of the latitude and longitude coordinates from the tags table. 

2. Multiple RFID tags/sets of GPS coordinates: This can be handled in any of three ways:

a. Because the multiple RFID tags are intended to be redundant, only one of the 

readable tags in the set can be selected as representing the entire set. The linkage 

between the GPS coordinates for the selected RFID tag and material samples then 

simplifies to a one-to-one relationship. Entry and storage of the GPS coordinates in 

this case is similar to that in the preceding item 1.

b. Average or “best estimate” latitude and longitude values can be determined for the 

multiple redundant RFID tags associated with one sample. The linkage between the 

best-estimate GPS coordinates and material samples then simplifies to a one-to-one 

relationship. Entry and storage of the GPS coordinates in this case is similar to that in 

the preceding item 1.

c. If it is desirable to maintain the redundancy between tags/sets of GPS coordinates and 

samples, a linking table and associated join operations can be established between the 

RFID tags/GPS coordinates and material samples and thus between tags/GPS 

coordinates and test specimens, as illustrated schematically in figure 174 through 

figure 176. The new Tags table contains the tag ID and associated latitude and 

longitude. The Tag_Sample_Link table captures the many-to-one relationship 

between tag IDs/GPS coordinates and samples. The query then uses this information 

to generate an output table listing for each tag the multiple material property test 

results determined from the material sample associated with that tag. As before, the 

query in figure 175 can be implemented in other and arguably more efficient ways; 

the particular query structure in figure 175 is designed to highlight the many-to-one 

relationship between RFID tags and material samples and the one-to-many 

relationship between material samples and material property tests.

168
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).

169
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.

Conversion of Latitude/Longitude to Roadway Location

The spatial referencing of the tags, and therefore of the associated material samples and material 

property test results in the MMS, are in terms of two-dimensional latitude and longitude. 

However, PMS data are most commonly spatially referenced in terms of linear milepoints along 

a route. Therefore, it is necessary to convert latitude and longitude to route and milepoint if the 

MMS data are to be combined with the PMS data. This is typically done by pairing GPS 

coordinates with milepoint locations at key points along the route and then interpolating. More 

information can be found in Schwartz and Bentahar and in O’Neill and Harper.(30,31)

Fortunately, most PMS software (including Roadware/Vision) already incorporates such 

coordinate conversion routines. In part, this is because some important PMS data elements—e.g., 

falling weight deflectometer test data as collected using Dynatest® and other common 

commercial systems—are spatially located automatically in terms of GPS coordinates. The 

material property data measured during construction can thus be exported from the MMS and 

imported into the PMS, and the PMS conversion routines can translate the GPS coordinates to 

milepoints. All MMSs and PMSs incorporate some type of data export/import routines, although 

170
there may be formatting incompatibilities that would need to be resolved on an agency-byagency basis.

Combining MMS and PMS Data by Location

Once the GPS coordinates for the MMS data have been converted to milepoints within the PMS, 

they can be extracted and combined with any desired PMS data elements. This would typically 

be done using the query facilities built into the PMS. Figure 177 through figure 179 illustrate 

schematically how to extract both MMS and PMS data along a particular section of roadway. 

New Route_No and Milepoint data elements have been added to the Tags table; the latitude and 

longitude coordinates and the PMS spatial reference conversion routines are used to generate the 

values for populating these data elements. The query in figure 177 through figure 179 is similar 

to that in figure 174 through figure 176, with the only difference being the reporting of route 

number and milepoint instead of latitude and longitude for each material property test value.

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.

171
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 through figure 182 show a simple example query for extracting International 

Roughness Index (IRI) values from a PMS database. The output from the query lists the 

measured IRI values and associated milepoint along the specified section of roadway.

Figure 180. Screen Capture. Schematic for extracting PMS data along a portion of 

roadway (I-70 between milepoints 83 and 84): IRI table.

172
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.

Display of Extracted Data

Once the MMS and PMS data have been extracted as described in the preceding section, they 

can be displayed together, typically using the built-in data display routines in the PMS. 

Figure 183 shows a Roadware iVision display of multiple datasets versus milepoint location 

along the roadway. One of the data series in the lower left chart or the data series in the lower 

right chart in the figure could be replaced by one of the MMS data elements, e.g., asphalt content 

as measured during construction.

The exported MMS and PMS data can also be exported for subsequent external analyses. Most 

PMSs have the capability of exporting query results, often through some type of “report 

generator” feature. The available formats for the output data will vary from system to system.

Figure 184 is an example of using Microsoft® Excel for displaying the extracted PMS and MMS 

data. The PMS data elements (IRI) and MMS data elements (asphalt content) are displayed as 

separate series (and with separate y-axes). The data in figure 184 are consistent with those in the 

173
earlier schematic examples in figure 177 through figure 182. An examination of figure 184

suggests that the localized higher roughness around milepoint 83.9 may be associated with a low 

and/or variable asphalt content. These types of insights, many of which will be far more 

powerful than in these simple examples, are the key benefits of integrating MMS and PMS data.

Figure 183. Screen Capture. Roadware iVision charts screenshot.(29)

174
1 inch/mi = 0.041 m/km

1 mi = 1.61 km

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). 

DATA INTEGRATION SUMMARY

Maximum use of material property data collected during construction and pavement 

management data collected during service life is possible only when both sets of data can be 

related to a common spatial referencing system. Using RFID tags to track loads of sampled and 

tested material enables geospatial identification of the location of the delivered material in the 

pavement. These material properties can then be linked with the corresponding spatially located 

pavement performance data from the PMS.

Because of the wide variety of MMS and PMS used by agencies, it is possible only to outline the 

general steps to link these two datasets via geospatial coordinates. This chapter provides 

examples of the following necessary operations:

• Linkage of one or more RFID identifiers to material samples.

• Linkage of GPS coordinates to RFID identifier/material sample.

• Conversion of latitude/longitude to roadway location.

• Combining of MMS and PMS data by location.

• Display of extracted data.

The details of implementing these operations will depend on the particular MMS and PMS used 

by an agency.

175

CHAPTER 9: CONCLUSIONS

PROJECT OBJECTIVES

The original objective of this project was to demonstrate that inexpensive expendable radio 

RFID tags can be used to identify the spatial location along the pavement alignment of specific 

truckloads of HMA (or warm/cold mix asphalt) production. These tags are placed in the 

truckload as it leaves the production plant, pass through the paver, and are compacted into the 

finished mat. Cross referencing these tags with GPS latitude and longitude coordinates after 

construction allows spatial referencing of QA material property data measured at the production 

plant, enabling linkage to other spatially referenced in-place test results and PMS pavement 

performance data. This use of the large QA and PMS datasets already collected by highway 

agencies will permit more robust analyses and insights into the relationships between HMA 

material properties and actual pavement performance.

During the pursuit of this original objective, additional applications of RFID technologies to 

pavements were identified for evaluation:

• Evaluation of potential problems caused by surfaced tags.

• Exploration of SAW RFID technology for improved performance of small format tags.

• Demonstration of RFID tracking of placement of PCC loads in pavements.

• Provision of guidance to agencies on data integration.

These issues were pursued in the final phase of the project.

KEY FINDINGS

Key findings of this work are summarized here organized by the following topical areas:

• RFID tracking of HMA placement (chapters 2, 3, and 4).

• RFID tracking of PCC placement (chapter 5).

• Pavement temperature measurement using SAW RFID (chapter 6)

• Reflection crack detection (chapter 7).

• Guidance on data integration (chapter 8).

RFID Tracking of HMA Placement

The feasibility of using RFID tags to track HMA placement was evaluated via: 1) literature 

review, 2) identification of appropriate RFID technology, and 3) prototype tag development and 

evaluation. Key findings from the feasibility evaluation are as follows:

• UHF (860–960 MHz) passive RFID technology was determined to be best suited to the 

HMA paving application. The advantages of passive UHF RFID included small tag size, 

low cost, adequate read range, and wide commercial availability.

• A ThingMagic Mercury® 5 RFID system was evaluated as being most appropriate for 

use on this project and was therefore acquired. 

177
• Suitable RFID tags of appropriate size were identified. These included Alien® Gen 2 1x1 

and Alien® Gen 2 2x2 tags. The larger format Alien® Gen 2 2x2 tags had superior read 

performance and were adopted for most of the study. A UPM Raflatac® 1x2 tag was 

subsequently added to the study after the Alien® 1x1 tags were taken out of production 

by the manufacturer.

• An effective and inexpensive encapsulation system was developed that adequately 

protects the RFID tags from the temperatures and compaction stresses inherent in HMA 

transport and paving. The flexible RFID tag is curled inside a 3/4-inch (19-mm) nominal 

outside diameter CPVC pipe, which is subsequently filled with high-temperature epoxy 

(Cotronics® DurapotTM 866). An improved curing process for the epoxy was also 

developed that minimized the formation of air bubbles and void. 

• The read ranges of the encapsulated tags were thoroughly evaluated. The read range for 

the Alien® 1x1 tags in the optimal circumferential orientation inside the CPVC pipe 

varied between 0.5 and 2 ft (0.15 and 0.6 m), which is inadequate for the intended 

application. The corresponding read range for the Alien® 2x2 tags varied between 5 and 

9 ft (1.5 and 2.7 m), which is more than adequate for the HMA tracking application. 

• Thermal and mechanical survivability of the encapsulated tags was evaluated in the 

laboratory via oven heating and gyratory compaction. The encapsulated tags survived 

oven heating for 1.5 h at temperatures up to 347 o

F (175 oC), adequate for paving 

applications. Survival rate for combined thermal and mechanical effects was 

approximately 75 percent. This is sufficient for field application because multiple tags 

will be placed into each truckload of HMA for redundancy.

The encapsulated RFID tags were field tested to evaluate the following issues: survivability 

under real-world paving scenarios, read range under actual field conditions, required redundancy,

construction practicality issues, and construction quality issues. The encapsulated RFID tags 

were evaluated at three parking lot locations on the UMD campus and in two stages in a new 

pavement constructed by the MSHA for the Hampstead Bypass. Key findings from the field 

trials are as follows: 

• In the parking lot trials, the read success rate (percentage of tags that could be read) 

varied from about 60 percent for the Alien® 1x1 tags to 100 percent for the larger format 

Alien® 2x2 tags.

• In the Hampstead Bypass trial, the overall read success rates were slightly less than 

20 percent for the UPM Raflatac® tags and between 60 and 80 percent for the larger 

Alien® 2x2 format.

• Read success rate decreased slightly with increasing vehicle speed. The read success rate 

at 45 mi/h (72 km/h) was approximately 65 percent of the rate at slow speeds. 

• Approximately 15 percent of the RFID tags “floated” to the surface of the mat in all of 

the field trials.

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The field trials confirmed the very high survival rate of the encapsulated tags. Read success rates 

varied significantly with tag size and less significantly on other details such as antenna 

configuration and vehicle speed. The field trials consistently demonstrated that post-construction 

read success rates of 60 to 80 percent or higher are achievable from a bumper-mounted antenna 

array, even on a vehicle moving at traffic speeds.

It was observed during the HMA field trials that some of the encapsulated RFID tags “floated” to 

the surface of the compacted mat. This raised the possibility of a decrease in in-place compacted 

density or an increase in the in situ permeability or both in the local region around the tag. 

Extensive density and permeability testing was performed to evaluate these possibilities. No 

localized decrease in density, increase in permeability, or any detrimental effects of the surfaced 

tags were found. There is the possibility for long-term deterioration around the tags due to 

degradation of the bonds between the asphalt binder and the CPVC pipe encapsulation. 

However, qualitative observations of the surfaced tags in Lot EE at the time of this writing show 

no evidence of deterioration over the intervening 6 years. These findings confirm that the 

encapsulated RFID tags are a successful low-impact and inexpensive technology for tracking 

placement of HMA in the roadway.

RFID Tracking of PCC Placement

The successful application of RFID tags to track placement of HMA immediately suggested the 

parallel use for PCC placement. Preliminary laboratory evaluation of concrete cylinders 

suggested that the Alien® Gen2 2x2 tags could be read through about 2 inches (50 mm) of 

concrete at a distance of up to 5 ft (1.5 m). The reconstruction of a section of I-90 near Syracuse,

NY, provided an opportunity for field evaluation. A large number of RFID tags similar to those 

used in the HMA application were placed in the PCC delivery trucks as they left the batch plant 

near the paving site. These tags were deposited with the PCC ahead of the slip form paver and 

incorporated into the concrete slabs. Unfortunately, on the return visit to the site about 1 month 

after paving, none of the tags could be read. The causes of this surprising and disappointing 

result were investigated in the laboratory. The influences of aggregate, water, and cement on 

read range and read success were systematically investigated. The most plausible explanation 

supported by the laboratory results is that the hydrated cement paste causes the cured concrete to 

have a very high dielectric constant (about 20). The penetration depth (i.e., read range) of the 

UHF RFID radio waves diminishes sharply as the dielectric constant increases. 

Pavement Temperature Measurement Using SAW RFID 

SAW RFID technology has the intrinsic capability to measure thermal expansion and thus 

temperature. Real-time measurement of pavement temperature distributions is necessary to 

interpret the stiffness feedback data in intelligent compaction because the stiffness of HMA is 

extremely temperature dependent. 

The temperature measurement capability of SAW RFID was evaluated through laboratory and 

field testing. For the field testing, various configurations of SAW RFID tags were encapsulated 

in thermally conductive epoxy, attached with quick-set epoxy to the surface of a milled existing 

pavement, and then covered with a 1.5-inch (38-mm) thick compacted HMA overlay. Although 

limitations of the SAW RFID reader system made it difficult to measure the temperature versus

179
time trends during the first few minutes after placement, mat temperatures were recorded starting 

at about 10 min after placement until the mat was too cool for continued compaction. The 

measured temperatures versus time compared favorably with predictions from analytical/

numerical models, and an approach for using the SAW RFID field temperature measurements for 

calibrating these analytical/numerical models is proposed. Overall, the SAW RFID technology 

has potential for in situ temperature measurement in HMA pavement layers.

Reflection Crack Detection

The development of an early onset reflection crack detector was originally intended as another 

application of the SAW RFID technology. However, it was subsequently determined that 

conventional RFID was a more appropriate technology choice, in part because of the current 

relatively high cost of SAW RFID tags. 

The reflection crack sensor concept is to implement a switch in the antenna circuit of the RFID 

tag: when there is no crack, the RFID tag signal can be read at a distance, but after a crack forms,

the signal becomes too weak to be read. A prototype reflection crack detector was developed and 

tested in the laboratory and, under more limited conditions, in the field. In the laboratory, the 

prototype detector was shown to be capable of detecting a reflection crack before it reached the 

pavement surface. The limited field trials also showed that the detector had the required 

survivability and read range for real-world applications. Seventeen of 18 tags tested in the field 

survived the paving operations, and the tags could be read at distances of more than 5 ft in the 

optimal antenna configuration. This approach shows considerable promise, but will require 

additional and more rigorous field evaluation that was beyond the scope and resources of the 

present project.

Guidance on Data Integration

Maximum use of material property data collected during construction and pavement 

management data collected during service life is possible only when both sets of data can be 

related to a common spatial referencing system. Using RFID tags to track loads of sampled and 

tested material enables geospatial identification of the location of the delivered material in the 

pavement. These material properties can then be linked with the corresponding spatially located 

pavement performance data from the PMS.

Because of the wide variety of MMSs and PMSs used by agencies, it is possible only to outline 

the general steps needed to link these two datasets via geospatial coordinates. Generic examples 

are provided for the following necessary operations:

• Linkage of one or more RFID identifiers to material samples.

• Linkage of GPS coordinates to RFID identifier/material sample.

• Conversion of latitude/longitude to roadway location.

• Combining of MMS and PMS data by location.

• Display of extracted data.

The details of implementing these operations will depend on the particular MMS and PMS used 

by an agency.

180
RECOMMENDATIONS FOR FUTURE WORK

Recommendations for follow-on work after this project include the following:

• Commercialization of the RFID system for tracking HMA placement. This research has 

demonstrated the success of the concept. However, it was impossible to generate 

commercial interest in it during the course of the project.

• Evaluation of other RFID systems (e.g., different frequency range, active instead of 

passive system, etc.) for use in tracking PCC placement. The high dielectric constant of 

the cement paste coating the aggregates in PCC makes it impossible to pass a sufficiently 

strong signal to/from the passive UHF RFID tags used so successfully for HMA tracking.

• For temperature measurement using SAW RFID tags, more work should be done to 

determine the minimum thickness of the epoxy coating to maximize tag readability and 

minimize thermal lag while still ensuring survivability. Additional work in collaboration 

with the SAW RFID system manufacturer is required to optimize the temperature 

window in the reader so that the early rapid cooling trends of the mat can be captured. 

Field trials should also be repeated on thicker HMA layers in which the variation of 

temperature with depth is more pronounced.

• Laboratory evaluation of the reflection crack detector should be conducted using a Texas 

Overlay Tester instead of three-point bending to better simulate how overlays fail. 

Through these tests, the CMOD as a function of vertical crack propagation can be 

determined more accurately, and the crack detector design can be adjusted as needed. 

Laboratory evaluation should then be followed by field trials on in-service pavements. 

The duration of these field trials would need to be on the order of 5 to 10 years to allow

sufficient time for reflection cracks to initiate and propagate.

181

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30. Paris, P. and Erdogan, F. (1963). “A Critical Analysis of Crack Propagation Laws,”

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ANNOTATED BIBLIOGRAPHY

Anonymous (2002). “Tracking Concrete Cubes for QA,” RFID Journal, August 18, 2002. 

Available at http://www.rfidjournal.com/article/articleview/194.

RFID tags embedded in concrete test cubes were evaluated as an alternative to manual tracking 

to reduce human errors and costs for tracking QA test data. This “Cube Info” application 

employed passive 13.56 MHz tags with 228 bytes of storage. The tags were approximately the 

size of a quarter and were encapsulated in a hard plastic protective casing. A handheld reader/

writer was employed to scan the cubes at the job site and encode them with field information. 

Fixed reader/writers attached to the laboratory weigh scales and compression test machines were 

used to record QA test results. Read range is not reported in the article, but from the 

accompanying figures, it appears to be on the order of 1 m (3.28 ft).

Concrete mix information for an individual mixer truck was entered into the handheld reader/

writer via a barcode attached to the paper load slip. After a slump test was performed at the sight, 

the encapsulated active RFID tag was placed inside the freshly prepared 6-inch (152-mm) test 

cube. The handheld reader/writer then wrote the mix information, slump test results, and date to 

the active RFID tag. The cube was then sent to laboratory for curing. After curing, it was 

weighed, and the weight data were transferred from the weight machine RFID reader/writer to 

the tag embedded in the cube. A compression test was finally performed, and these results were 

also transferred by the associated RFID reader/writer to the tag. The protective plastic casing 

enabled the RFID tag to be retrieved intact after the test for download of the complete dataset. 

The encapsulated tags could be reused (more than 20 times). After verification of the test results, 

they were posted to a materials database and/or sent via email to the concrete producer and 

others.

The pilot implementation of the Cube Info system was reported as giving good results. No major 

technical problems were reported. Nonetheless, acceptance of this system does not appear to be 

speedy or widespread.

AXCESS, Inc. (2006). “AXCESS’ Active RFID Solution Utilized by Bechtel to Automate 

HAZMAT Truck Payload Management,” press release, May 9, 2006. Available at 

http://www.axcessinc.com/press/050509bechtel.doc.

In this application, RFID was used to monitor environmentally hazardous material movement 

with minimum hindrance in its transport. Active RFID tags were installed on trucks and drums. 

When the truck passed a weigh station, its load, contents, and other information was scanned and 

automatically uploaded to a database.

Collins, J. (2004). “Case Builds for RFID in Construction,” RFID Journal, January 5, 2004. 

Available at http://www.rfidjournal.com/article/articleview/720/1/4/.

RFID technology was evaluated as an alternative to bar coding for tracking the shipment and 

delivery of metal pipes from a fabrication plant in Texas to a construction site. The RFID system 

consisted of active UHF (915 MHz) RFID tags from Identec® and Phase IV Engineering, an 

Identec® handheld reader connected to an iPaqTM personal digital assistant (PDA), and a 

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CargoWatch® stationary reader. Read-write range in noninterfering environments was 

approximately 328 ft (100 m). Only tag identification information was evaluated. 

The focus of the study was to determine whether reliable readings could be obtained when the 

RFID tags were placed on a pipe surrounded by a large number of other pipes on the back of the 

truck. The tags were mounted on the pipes after loading onto the truck to avoid damage by the 

loading process. Two read modes were evaluated. Stationary loaded trucks were scanned by a 

worker with the handheld reader who moved around the truck trailer. Moving trucks were 

scanned as they were driven past a stationary reader location.

Tag reads for stationary trucks were 100-percent accurate up to a range of 10 ft (3.05 m). 

Accuracy dropped slightly for a moving truck passing the stationary reader. However, it 

rebounded to 100 percent when the truck stopped briefly near the stationary reader.

Ergin, E., and Hendrickson, C.T. (January 2007). “Utilization of Radio-Frequency 

Identification Tags for Transportation Infrastructure Management: Tracking Engineeredto-Order Elements and Materials Throughout Their Life-Cycles,” Transportation Research 

Board 86th Annual Meeting, Washington, DC, Paper No. 07-2788.

Information flow related to materials and components used in transportation infrastructure 

systems and their supply chains are plagued with inefficiencies caused by inadequate or late 

deliveries and installation of components at wrong locations. This paper provides a vision of how 

RFID tags could be used as a means to track components from long distances, store information 

on these components, and allow multiple parties to access this information. A requirements 

analysis and a limited set of field tests were performed to explore the technical feasibility of 

using RFID technology for these purposes. The experiments demonstrated that it was technically 

feasible to add intelligence to the components in transportation infrastructure systems to collect 

status information automatically within the supply chain.

Goodrum, P.M., McLaren, M.A., and Durfee, A. (2006). “The Application of Active Radio 

Frequency Identification Technology for Tool Tracking on Construction Job Sites,”

Automation in Construction, 15, 292–302.

The objective of this study was to improve the tracking of handheld power tools on construction 

sites to make them more easily available to a worker when needed. Commonly used tools 

(corded hammer drill, portable band saw, reciprocating saw) at three construction projects were 

identified and tagged. Active UHF (915 MHz) RFID tags with lithium/thionyl chloride 

(Li/SOCl2) and 32 Kb of memory were employed. The tags, approximately 1 by 5 inches in size, 

were mounted internally within the plastic tool housings. A handheld reader connected to a PDA 

was used to collect data. 

Contractors were allowed to move tools freely according to their needs. Readings were taken 

every week at the job sites. Readings were taken while the tools were stored in top-opening 

metal gang (tool storage) boxes with the lid open. Reading distance and direction from the tools 

in the gang box were noted. Evaluation included read range, integrity of stored inventory and 

maintenance data on the tag, and ability of reader to update that data. 

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Readings in environmentally controlled laboratory conditions were successful up to ranges 

between 49.2 to 82 ft (15 to 25 m). This range dropped in the field to between 9.84 to 19.52 ft 

(3 to 9 m). The variation in the field read ranges was attributed to temperature influences and 

metal interference. The electromagnetic field produced by the tool itself did not affect the RFID 

signal. It was also noted that the active RFID could be short-circuited when drenched in water. 

The largest read range decrease occurred at one site where temperatures fell to 10 °F (-12 °C). 

Battery performance in the active RFID tag was adversely affected by these low temperatures.

International Road Dynamics, Inc. (May 2004). “Wireless Concrete Maturity Meter,” news 

release. Available at 

http://www.identecsolutions.com/fileadmin/user_upload/PDFs/case_studies/News_Release_i

rd_-_Wireless_Concrete_Maturity_MonitorV2_Eng.pdf.

Concrete maturity time was predicted using measured temperatures from an embedded RFID 

sensor and as input to predictive techniques such as the Equivalent Age (Arrhenius) and/or 

Nurse-Saul models. The RFID technology for this application consisted of an Identec® i-QTM

active UHF tag and a handheld reader. The system can read tags up to 8 inches inside concrete. 

This system, in conjunction with the predictive models, gave estimates of the compressive 

strength of concrete onsite. This was more accurate than laboratory techniques that did not share 

the same environmental and other conditions (e.g., volume) as onsite.

Johns Hopkins University Applied Physics Laboratory (January 2005). “New Sensors 

Promise to Drive Down Highway Maintenance Costs,” news release. Available at 

http://www.jhuapl.edu/newscenter/aplnews/2002/highway.asp.

In this study, an RFID tag was combined with a conductivity sensor to monitor the corrosive 

environment in reinforced concrete bridge decks. The “Smart Aggregate” was a passive RFID 

tag roughly the size of a quarter that was encapsulated in a high compressive strength ceramic. 

During preliminary field trials, the Smart Aggregate tags were embedded in the concrete bridge 

deck for the Johns Hopkins/Gorman Road bridge over US Route 29 in Maryland. Results of 

these trials had not been located as of the time of this writing.

Jaselskis, E.J., Anderson, M.R., Jahren, C.T., Rodriguez, Y., and Njos, S. (June 1995). 

“Radio-Frequency Identification Applications in Construction Industry,” Journal of 

Construction Engineering and Management, ASCE, 121(2), 189–196.

This early paper on RFID applications in construction engineering begins with a basic 

description of the various technology options available and their respective advantages and 

limitations. Current and potential applications of this technology are then described. Although 

many of these applications are speculative, they suggest a broad impact of RFID technology in 

the construction industry.

189
Jaselskis, E.J., and El-Misalami, T. (November/December 2003). “Implementing Radio 

Frequency Identification in the Construction Process,” Journal of Construction 

Engineering and Management,. 129(6), 680–688. (see also Jaselskis, E.J., and El-Misalami, 

T. (2003). “RFID’s Role in a Fully Integrated, Automated Project Process,” Construction 

Research Congress in Construction: Wind of Change: Integration and Automation, ASCE.)

This paper is, in essence, an update of Jaselskis et al. (1995). The basic concepts and advantages 

and limitations of available RFID technologies are described. Key outcomes from a construction 

industry-RFID supplier workshop held to disseminate information and generate suitable 

application ideas in construction are summarized. This workshop generated one pilot application 

that was conducted to demonstrate the applicability of RFID to the material procurement process 

at a construction site. The pilot tests showed that RFID tags reduced the time required to 

download data into a company’s material tracking system and reduced the potential for duplicate 

data entries. The application demonstrated the benefits of the technology in the materials 

receiving process.

Jaselskis, E.J., Grigas, J., and Brilingas, A. (September/October 2003). “Dielectric 

Properties of Asphalt Pavement,” Journal of Materials in Civil Engineering, ASCE,15(5),

427–434.

Electromagnetic wave absorption, reflection, and transmission through asphalt concrete depend 

on the dielectric properties of the material. Asphalt concrete samples of different densities were 

studied in the frequency range from 100 Hz to 12 GHz to determine the temperature and 

frequency dependencies of the real and imaginary permittivity components. The principal 

findings were: 1) permittivity and loss depend on frequency and temperature, 2) permittivity 

increases with increasing pavement density, 3) permittivity slightly increases with temperature, 

4) moisture strongly increases permittivity and loss at low frequencies and only slightly at high

frequencies, and 5) the penetration depth of electromagnetic waves in asphalt pavements is about 

4.72–5.51 inches (12–14 cm) at 8 GHz and only about 1.57 inches (4 cm) at 30 GHz. Although 

the focus of this study was on microwave transmission (frequencies between about 1 GHz and 

300 GHz) to determine the density of in-place asphalt concrete, the data and results are also 

relevant to ground penetrating radar (frequencies between about 100 MHz and 1.6 GHz) and 

UHF RFID (frequency of approximately 900 MHz).

Naresh, A.L., and Jahren, C.T. (September 1997). “Communication and Tracking for 

Construction Vehicles,” Journal of Construction Engineering and Management, ASCE, 

123(3), 261–268.

This survey article describes the potential efficiency benefits of advanced communication and 

tracking systems for construction vehicle fleets such as dump trucks, concrete trucks, low boy 

trailers, and scrapers. Three advanced systems are covered: signaling systems, continuous 

communication and tracking systems, and RFID. Implementation and potential value of these 

systems for construction fleet management are described in conceptual terms only.

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O’Connor, M.C. (2006). “RFID Cures Concrete,” RFID Journal, October 30, 2006. 

Available at http://www.rfidjournal.com/article/articleview/2673.

The time taken for concrete to mature depends on volume and temperature. As a consequence, 

test cylinders overestimate maturity time. The objective of this study was to measure the actual 

concrete maturity time onsite by employing temperature-sensing RFID technology.

The RFID technology employed in this application was an Identec® i-QTM 915 MHz UHF active 

tag with an integrated temperature sensor. The RFID tag was placed in the wet concrete during 

construction. The temperature readings of concrete were transmitted to the handheld reader, 

which downloaded the information to a handheld computer capable of running concrete maturity 

time algorithms that model the relationship of maturity to temperature during curing. The RFID 

temperature sensor tag found that the required concrete strength at the actual site was achieved in 

only one-third of the time predicted by cylinder tests. This could significantly shorten the 

construction time for a building. 

Peyret, F., and Tasky, R. (2004). “A Traceability System between Plant and Work Site for 

Asphalt Pavements,” Computer-Aided Civil and Infrastructure Engineering, 19, 54–63.

This study, conducted as part of the European Open System for Road Information Support

project, evaluated the linkage of RFID and GPS technologies for associating asphalt mix data 

collected at the production plant with location of the material on the roadway. Of all of the 

material reviewed from the literature, this was the most relevant to the present project.

In this prototype system, the mix properties of a batch were stored in the plant computer. When a 

loaded transport truck fitted with an RFID tag left the plant, the plant computer transferred the 

mix properties, temperature, and weight of the load via the reader to the active RFID tag on the 

truck body. The paver at the job site was equipped with an RFID reader, GPS transponder, and a 

computer. When the transport truck arrived at the job site and unloaded into the paver, the paver 

instrumentation read the tag ID and other information and combined this information with GPS 

coordinates to record the starting and ending times and latitude/longitude coordinates along the 

roadway for that specific load 

The RFID technology employed in this application consisted of an active UHF (866 MHz) RFID 

tag having an approximate size of 0.15 by 0.03 by 0.02 m. Reported read ranges were 49.1 ft 

(15 m) effective and 98.4 ft (30 m) nominal. The 13- by 0.82- by 1-ft (0.4- by 0.25- by 0.3-m)

plant and paver antennas had coverage angles of approximately 120 degrees. An OMNISTAR®

Differential GPS mounted on the paver was used to determine latitude, longitude, and time data.

During the prototype implementation, some minor information was lost from the tags, but this 

was judged to have no significant impact on the test results because such losses were anticipated 

in the prototype. There were some occasional difficulties obtaining an accurate GPS reading 

when the satellite signal was obstructed. The software for the prototype system was not fully 

integrated, and therefore the data reading and recording processes were not fully automated. This 

was to be remedied in future phases of the project. However, it is unclear whether these future 

phases were ever conducted. The authors have been contacted via email to learn whether any 

191
additional work on the system has been completed, but no reply had been received at the time of 

this writing.

Sawyer, T. (2004). “Researchers Are Getting Serious About Electronic Tracking Tags,”

Engineering News Record, 253(23), December 13, 2004, pp. 28–29.

This article describes how large construction firms have been employing RFID technology for a 

variety of applications, including automatic inventory control, automated tool check-out, and 

tracking of construction components in storage yards.

Song, J., Haas, C.T., and Caldas, C.H. (September 2006). “Tracking the Location of 

Materials on Construction Job Sites,” Journal of Construction Engineering and 

Management, ASCE, 132(9), 911–918. (See also Song, J., Haas, C.T., Caldas, C.H., and 

Liapi, K. (2005). “Locating Materials on Construction Site Using Proximity Techniques,”

Construction Research Congress 2005: Broadening Perspectives, ASCE.)

This paper presents an approach by which construction materials can be tagged and then 

automatically identified and tracked on construction sites without interfering with regular site 

operations. A construction supervisor equipped with a portable RFID reader and a GPS 

transponder roved the site. A combination of proximity of reads from discrete ranges allowed the 

construction material item to be located within a two-dimensional grid overlaying the 

construction site. Off-the-shelf RFID passive technology was employed in this study, but 

specifics were not provided regarding operating frequency or other parameters.

Stone, W.C., Pfeffer, L., and Furlani, K. (March 2000). “Automated Part Tracking on the 

Construction Job Site,” Robotics 2000, ASCE Conference on Robotics for Challenging 

Environments, Albuquerque, NM. Available at 

http://fire.nist.gov/bfrlpubs/build00/PDF/b00003.pdf. 

This system design exercise was conducted as part of a National Institute of Standards and 

Technology initiative to develop Web-based techniques for tracking prefabricated components 

on construction site in real time. The basic concept was that each component to be shipped to a 

site was identified with a unique bar code or RFID tag. The bar code/RFID tag was scanned, and 

the identification information downloaded to a laptop when the component arrived on the job 

site. The component ID was then sent from laptop to the project database, where it was joined 

with the whole description of the component, e.g., from the manufacturer’s specification book. 

The site inspector also entered the 3D coordinates of the component’s onsite storage location 

using a 3D coordinate measuring tool. The component was tracked by sensors that automatically 

updated the project database. The project database information could be sent via the Web to a 

distant project management office, where all activity could be viewed in real time in threedimensional space.

A pilot test monitored site activity from an office located approximately 0.621 mi 1( km) away 

from the job site. However, only barcodes were used in the pilot. Although not implemented, the 

author anticipated much better performance using RFID technology. 

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Swedberg, C. (2006). “RFID Markers Track Buried Cables at Atlanta Airport,” RFID 

Journal, September 12, 2006. Available at

http://www.rfidjournal.com/article/articleview/2647/.

This application focused on locating underground cables and pipes at the Atlanta airport using 

RFID. Ball markers containing RFID tags were used to store identification, location, and other 

information for each utility cable and pipe. Different categories of utility cables and pipes were 

assigned different RFID tag frequencies. Passive RFID tags with 256 bits of memory and 

operating frequencies ranging from 66 to 169 MHz were employed for this application. The 

system was reported to work well, with tags readable up to five ft underground. 

Violino, B. (2007). “RFID Rocks at Graniterock,” RFID Journal, January 22, 2007. 

Available at http://www.rfidjournal.com/article/articleview/2905/1/4/.

RFID technology was employed to improve efficiency of movement of trucks at Graniterock 

quarries. The system was based on a TransCore® IP Ltd. passive RFID tag (approximate 

dimensions of 2 by 12 inches (5 by 30.5 cm) scanned using a fixed location TransCore® reader. 

A key focus of this implementation was integration of the RFID data with other Graniterock®

business operation software and databases.

The quarry operations staff was informed via telephone about the RFID tag identification, 

trucking company name, and other information as the truck approached the entrance. This 

information was fed into the operations database. As the truck entered the quarry weigh station, 

the fixed reader read the tag ID and combined this information with the empty truck weight and 

other information that was correlated with the pre-arrival information already stored in the 

database. As the loaded truck left, it again passed the reader, the tag ID was again read, and the 

corresponding loaded weight was automatically uploaded to the database. A hardcopy 

receipt/billing slip was printed for the truck operator. 

Although the details of the reader configuration and read range are not stated, the test trials of the 

system were reported as very successful. There was an initial problem distinguishing incoming 

and outgoing trucks passing the fixed reader simultaneously, but this problem was resolved 

through modification of the direction and power of reader. Overall, Graniterock® found that the 

automated RFID system dramatically reduced human input (i.e., staff time) and produced 

significant time savings.

Wasserman, E. “Construction’s Building Blocks: RFID,” RFID Journal. Available at 

http://www.rfidjournal.com/magazine/article/2922/1/394/.

A nontechnical survey article describing several applications of RFID technologies to the 

construction industry.

Wessel, R. (2006). “RFID Chops Timber Costs,” RFID Journal, April 3, 2006. Available at 

http://www.rfidjournal.com/article/articleview/2220/1/4/.

RFID technology was integrated into a Log Tracking System (LTS) to minimize logs lost in the 

forest and to improve the efficiency of timber log deliveries to sawmills. An RFID tag encased in 

a plastic nail was hammered into the base of a freshly cut log in the forest. The RFID 

193
identification number was scanned and downloaded to a handheld computer where it was 

combined with other manually-entered characteristics of the log. These data were transmitted 

wirelessly to a central main database. After the trees had been transported from the forest to the 

roadside, the tag was again scanned, and the identification number transmitted to the main 

database. The main database compared the ID numbers of the cut logs from the forest against the 

ID numbers of the logs along the roadside to reduce the chances of leaving a log in the forest. 

The ID numbers of logs were again scanned at the time of loading into the haul trucks and when 

delivered to the sawmill.

The RFID technology employed in this application consisted of a passive 125 KHz tag encased 

in a special plastic nail. The plastic nail was made of polyamide reinforced with glass fiber and 

was approximately 0.2 inches (0.5 cm) in diameter by 1.4 inches (35.6 cm) long. A special 

hammer was used to drive the RFID nail. The handheld reader was attached to a wristband and 

was connected to a handheld computer. Maximum read range was 1.2 inches (3 cm), which 

seems marginal, but the nails were clearly visible in the ends of the logs at all steps and could 

therefore be easily located and read at close range. Other data regarding the log were entered into 

the handheld computer using a voice input system via a microphone attached to the logger’s 

helmet. Data were transmitted wirelessly from the handheld computer using a wireless local area 

network connection or the GSM network.

The pilot implementation of this system was successful. No trunks were lost by using RFID. The 

LTS worked in rain and snow conditions. The RFID tags did have a small read range and stored

only an identification number, but any enhancements would make the tags economically 

infeasible. One problem encountered early on was damage to the nails when they were 

hammered into the log, particularly if the log was frozen. A special hammer was developed to 

solve this problem.

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HRDI-20/04-15(50)E Recycled

Recyclable