Use of NDT Equipment for Construction Quality Control of Hot Mix Asphalt Pavements

              USE OF NDT EQUIPMENT

FOR CONSTRUCTION

QUALITY CONTROL OF HOT MIX

ASPHALT PAVEMENTS

Research Report 574

Prepared by:

Manuel Celaya, MSCE

Soheil Nazarian, PhD, PE

Manuel Zea, BSCE

Vivek Tandon, PhD, PE

Center for Transportation Infrastructure Systems

The University of Texas at El Paso

El Paso, TX 79968- 0516

( 915) 747- 6925

August 2006

Prepared for:

Arizona Department of Transportation

205 South 17th Ave.

Mail Drop 614E

Phoenix, AZ 85007- 3212

in cooperation with

U. S. Department of Transportation

Federal Highway Administration

The contents of this report reflect the view of the authors, who are responsible for the

facts and the accuracy of the data presented herein. The contents do not necessarily

reflect the official views or policies of the Arizona Department of Transportation or the

Federal Highway Administration. This report does not constitute a standard,

specification, or regulation.

Technical Report Documentation Page

1. Report No.

FHWA- AZ- 2006- 574

2. Government Accession No.

3. Recipient's Catalog No.

4. Title and Subtitle

Use of NDT Equipment for Construction Quality Control of Hot Mix

Asphalt Pavements

5. Report Date

August 2006

6. Performing Organization Code

7. Author

Manuel Celaya, Soheil Nazarian, Manuel Zea, and Vivek Tandon

8. Performing Organization Report No.

Research Report

9. Performing Organization Name and Address

Center for Transportation Infrastructure Systems

The University of Texas at El Paso

El Paso, Texas 79968- 0516

10. Work Unit No.

11. Contract or Grant No.

SPR- PL- 1( 61) ITEM 574

12. Sponsoring Agency Name and Address

Arizona Department of Transportation

205 South 17th Ave.

Mail Drop 614E

Phoenix, AZ 85007- 3212

13. Type of Report & Period Covered

Technical Report

July, 2005 – July, 2006

14. Sponsoring Agency Code

15. Supplementary Notes

Research Performed in Cooperation with ADOT and FHWA

16. Abstract

The focus of the study has been to evaluate the utility of seismic methods in the quality management of the hot

mix asphalt layers. Procedures are presented to measure the target field moduli of hot mix asphalt ( HMA) with

laboratory seismic methods, conduct field tests with the Portable Seismic Pavement Analyzer ( PSPA) in the

field, validate the results in the laboratory with seismic tests on extracted cores and determine the design

modulus from measured values.

This report contains the results of an effort to address the issues related to the implementation of the

recommended methods and devices in the day- to- day operation of the pavement community ( in general) and

pavements managed by the Arizona Department of Transportation ( ADOT). Ten sites throughout Arizona with

different pavement conditions and structures were tested between August and December 2005. The results are

summarized in this report.

Based on the results presented, the combination of the lab and field seismic methods is a viable tool for the

quality management of HMA layers and can be easily implemented by ADOT. In addition, performing the

simplified seismic laboratory and field tests along with more traditional tests may result in a database that can be

used to smoothly unify the design procedures with pavement evaluation.

17. Key Words

Pavement Design, Modulus, Nondestructive

Testing, Flexible Pavements, Resilient Modulus,

Quality Control, Seismic Methods

18. Distribution Statement

No restrictions. This document is

available to the public through the

National Technical Information

Service, 5285 Port Royal Road,

Springfield, Virginia 22161

23. Registrant's Seal

19. Security Classification

Unclassified

20. Security Classification

Unclassified

21. No. of Pages

165

22. Price

SI* ( MODERN METRIC) CONVERSION FACTORS

APPROXIMATE CONVERSIONS TO SI UNITS APPROXIMATE CONVERSIONS FROM SI UNITS

Symbol When You Know Multiply By To Find Symbol Symbol When You Know Multiply By To Find Symbol

LENGTH LENGTH

in inches 25.4 millimeters mm mm millimeters 0.039 inches in

ft feet 0.305 meters m m meters 3.28 feet ft

yd yards 0.914 meters m m meters 1.09 yards yd

mi miles 1.61 kilometers km km kilometers 0.621 miles mi

AREA AREA

in2 square inches 645.2 square millimeters mm2 mm2 Square millimeters 0.0016 square inches in2

ft2 square feet 0.093 square meters m2 m2 Square meters 10.764 square feet ft2

yd2 square yards 0.836 square meters m2 m2 Square meters 1.195 square yards yd2

ac acres 0.405 hectares ha ha hectares 2.47 acres ac

mi2 square miles 2.59 square kilometers km2 km2 Square kilometers 0.386 square miles mi2

VOLUME VOLUME

fl oz fluid ounces 29.57 milliliters mL mL milliliters 0.034 fluid ounces fl oz

gal gallons 3.785 liters L L liters 0.264 gallons gal

ft3 cubic feet 0.028 cubic meters m3 m3 Cubic meters 35.315 cubic feet ft3

yd3 cubic yards 0.765 cubic meters m3 m3 Cubic meters 1.308 cubic yards yd3

NOTE: Volumes greater than 1000L shall be shown in m3.

MASS MASS

oz ounces 28.35 grams g g grams 0.035 ounces oz

lb pounds 0.454 kilograms kg kg kilograms 2.205 pounds lb

T short tons ( 2000lb) 0.907 megagrams

( or “ metric ton”)

mg

( or “ t”)

mg megagrams

( or “ metric ton”)

1.102 short tons ( 2000lb) T

TEMPERATURE ( exact) TEMPERATURE ( exact)

º F Fahrenheit

temperature

5( F- 32)/ 9

or ( F- 32)/ 1.8

Celsius temperature º C º C Celsius temperature 1.8C + 32 Fahrenheit

temperature

º F

ILLUMINATION ILLUMINATION

fc foot candles 10.76 lux lx lx lux 0.0929 foot- candles fc

fl foot- Lamberts 3.426 candela/ m2 cd/ m2 cd/ m2 candela/ m2 0.2919 foot- Lamberts fl

FORCE AND PRESSURE OR STRESS FORCE AND PRESSURE OR STRESS

lbf poundforce 4.45 newtons N N newtons 0.225 poundforce lbf

lbf/ in2 poundforce per

square inch

6.89 kilopascals kPa 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

TABLE OF CONTENTS

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

I. INTRODUCTION......................................................................................................... 3

Objectives ...................................................................................................................... 3

Organization................................................................................................................... 4

II. BACKGROUND.......................................................................................................... 5

Traditional Methods for Measuring HMA Modulus ..................................................... 6

Diametral Resilient Modulus ................................................................................... 6

Dynamic Modulus Tests .......................................................................................... 7

Free- free Resonant Column Tests............................................................................ 8

Ultrasonic Tests ....................................................................................................... 8

Falling Weight Deflectometer ( FWD) ..................................................................... 9

Seismic Field Methods........................................................................................... 10

Empirical Models................................................................................................... 10

Impact of Temperature and Frequency .................................................................. 12

III. PORTABLE SEISMIC PAVEMENT ANALYZER............................................. 15

IV. SEISMIC METHODOLOGY FOR QUALITY MANAGEMENT

OF HOT ASPHALT .................................................................................................. 21

Step 1: Selecting Suitable Materials and Mix for a Given Project ............................. 21

Step 2: Determining a Target Modulus for the Mix ................................................... 22

Step 3: Characterizing the Variation in Modulus with Temperature.......................... 23

Step 4: Determining Modulus of Material for Structural Design ............................... 24

Step 5: Field Quality Tests.......................................................................................... 25

V. EXAMPLE IMPLEMENTATION OF QUALITY MANAGEMENT

IN ARIZONA............................................................................................................. 27

Step 1: Selecting Suitable Materials and Mix for a Given Project ............................. 27

Step 2: Determining a Target Modulus for the Mix ................................................... 27

Step 3: Characterizing the Variation in Modulus with Temperature.......................... 28

Step 4: Determining Modulus of Material for Structural Design ............................... 29

Step 5: Field Quality Tests.......................................................................................... 30

Validation of Results.................................................................................................... 33

VI. PRESENTATION OF RESULTS........................................................................... 39

Description of Sites Investigated ................................................................................. 39

Description of Sites...................................................................................................... 39

General Results ............................................................................................................ 41

Step 1: Selecting Suitable Materials and Mix for Each Project............................ 41

Step 2: Determining a Target Modulus for Each Mix .......................................... 41

Step 3: Characterizing the Variation in Modulus with Temperature.................... 44

Step 4: Determining Modulus of Each Mix for Structural Design ....................... 46

Step 5: Field Quality Tests.................................................................................... 48

Validation............................................................................................................... 53

VII. SUMMARY, CONCLUSIONS AND RECOMMENDATIONS ........................ 57

REFERENCES................................................................................................................. 60

APPENDIX A. DYNAMIC MODULUS TEST ........................................................... 63

Test Procedure and Calculations for Dynamic Modulus Test ..................................... 64

Time- Temperature Relationship .................................................................................. 65

APPENDIX B. INTRODUCTION TO WAVE PROPAGATION THEORY........... 69

Seismic Body Waves ................................................................................................... 69

Seismic Surface Waves................................................................................................ 69

Seismic Wave Velocities ............................................................................................. 71

Elastic Constants.......................................................................................................... 72

APPENDIX C. VARIATION IN MODULUS WITH AIR VOIDS FOR ALL SITES73

APPENDIX D. VARIATION IN MODULUS WITH TEMPERATURE

FOR ALL SITES................................................................................... 78

APPENDIX E. MASTER CURVES FOR ALL SITES............................................... 82

APPENDIX F. GRADATION RESULTS .................................................................... 87

APPENDIX G. CONTOUR MAPS............................................................................... 97

APPENDIX H. MODULUS CONTROL CHARTS .................................................. 107

APPENDIX I. CUMULATIVE DISTRIBUTION CHARTS ................................... 116

APPENDIX J. VALIDATION OF RESULTS........................................................... 125

APPENDIX K. PAY FACTOR CALCULATIONS .................................................. 129

APPENDIX L. VARIATION IN LAB SEISMIC MODULUS

WITH AIR VOIDS ............................................................................. 134

APPENDIX M. MONTE CARLO SIMULATION RESULTS................................ 139

APPENDIX N. PHOTO ALBUM................................................................................ 144

LIST OF TABLES

Table 2.1 – Summary of Material Models ......................................................................... 11

Table 5.1 – Job Mix Formula from Project........................................................................ 27

Table 5.2 – Comparison of Moduli from PSPA and Lab Tests on Cores.......................... 34

Table 5.3 – Comparison of Air Voids for Cores Extracted at the Site .............................. 35

Table 5.4 – Variation in Constituents of Mix from Field Samples.................................... 36

Table 5.5 – Gradation Results for Selected Cores from the Site ....................................... 37

Table 5.6 – Gradation Results for Loose Materials Sampled at Site ................................. 37

Table 6.1 – Job Mix Formula from All Sites..................................................................... 42

Table 6.2 – Variation in Seismic Modulus with Air Voids for Lab Specimens ................ 43

Table 6.3 – Variation in Seismic Modulus with Temperature for Lab Specimens

at Placement Air Voids ................................................................................. 44

Table 6.4 – Master Curve Parameters for All Sites ........................................................... 47

Table 6.5 – Design Modulus and Modulus Ratios for All Sites ........................................ 48

Table 6.6 – Average Gradations, AC Content and Air Voids at Sites............................... 49

Table 6.7 – Comparison of As- Built and Target Moduli................................................... 51

Table 6.8 – Variation in Core Seismic Modulus with Air Voids....................................... 54

Table 6.9 – Variation in Mix Constituents for All Sites .................................................... 55

Table F. 1 – Comparison of Air Voids for Cores Extracted at Site 1 ................................. 87

Table F. 2 – Gradation Results for Selected Cores from Site 1.......................................... 87

Table F. 3 – Gradation Results for Loose Materials Sampled at Site 1.............................. 87

Table F. 4 – Comparison of Air Voids for Cores Extracted at Site 2 ................................. 88

Table F. 5 – Gradation Results for Selected Cores from Site 2.......................................... 88

Table F. 6 – Gradation Results for Loose Materials Sampled at Site 2.............................. 88

Table F. 7 – Comparison of Air Voids for Cores Extracted at Site 3 ................................. 89

Table F. 8 – Gradation Results for Selected Cores from Site 3.......................................... 89

Table F. 9 – Gradation Results for Loose Materials Sampled at Site 3.............................. 89

Table F. 10 – Comparison of Air Voids for Cores Extracted at Site 4 ............................... 90

Table F. 11 – Gradation Results for Selected Cores from Site 4........................................ 90

Table F. 12 – Gradation Results for Loose Materials Sampled at Site 4............................ 90

Table F. 13 – Comparison of Air Voids for Cores Extracted at Site 5 ............................... 91

Table F. 14 – Gradation Results for Selected Cores from Site 5........................................ 91

Table F. 15 – Gradation Results for Loose Materials Sampled at Site 5............................ 91

Table F. 16 – Comparison of Air Voids for Cores Extracted at Site 6 ............................... 92

Table F. 17 – Gradation Results for Selected Cores from Site 6........................................ 92

Table F. 18 – Gradation Results for Loose Materials Sampled at Site 6............................ 92

Table F. 19 – Comparison of Air Voids for Cores Extracted at Site 7 ............................... 93

Table F. 20 – Gradation Results for Selected Cores from Site 7........................................ 93

Table F. 21 – Gradation Results for Loose Materials Sampled at Site 7............................ 93

Table F. 22 – Comparison of Air Voids for Cores Extracted at Site 8 ............................... 94

Table F. 23 – Gradation Results for Selected Cores from Site 8........................................ 94

Table F. 24 – Gradation Results for Loose Materials Sampled at Site 8............................ 94

Table F. 25 – Comparison of Air Voids for Cores Extracted at Site 9 ............................... 95

Table F. 26 – Gradation Results for Selected Cores from Site 9........................................ 95

Table F. 27 – Gradation Results for Loose Materials Sampled at Site 9............................ 95

Table F. 28 – Comparison of Air Voids for Cores Extracted at Site 10 ............................. 96

Table F. 29 – Gradation Results for Selected Cores from Site 10...................................... 96

Table F. 30 – Gradation Results for Loose Materials Sampled at Site 10.......................... 96

Table J. 1 – Comparison of Moduli from PSPA and Lab Tests on Cores Extracted

from Same Locations on Site 1................................................................... 125

Table J. 2 – Comparison of Moduli from PSPA and Lab Tests on Cores Extracted

from Same Locations on Site 2................................................................... 125

Table J. 3 – Comparison of Moduli from PSPA and Lab Tests on Cores Extracted

from Same Locations on Site 3................................................................... 126

Table J. 4 – Comparison of Moduli from PSPA and Lab Tests on Cores Extracted

from Same Locations on Site 4................................................................... 126

Table J. 5 – Comparison of Moduli from PSPA and Lab Tests on Cores Extracted

from Same Locations on Site 5................................................................... 126

Table J. 6 – Comparison of Moduli from PSPA and Lab Tests on Cores Extracted

from Same Locations on Site 6................................................................... 127

Table J. 7 – Comparison of Moduli from PSPA and Lab Tests on Cores Extracted

from Same Locations on Site 7................................................................... 127

Table J. 8 – Comparison of Moduli from PSPA and Lab Tests on Cores Extracted

from Same Locations on Site 8................................................................... 127

Table J. 9 – Comparison of Moduli from PSPA and Lab Tests on Cores Extracted

from Same Locations on Site 9................................................................... 128

Table J. 10 – Comparison of Moduli from PSPA and Lab Tests on Cores Extracted

from Same Locations on Site 10................................................................. 128

Table K. 1 – Pay Factor Calculations for Buckeye Site ................................................... 129

Table K. 2 – Pay Factor Calculations for Show Low Site ................................................ 129

Table K. 3 – Pay Factor Calculations for Holbrook Site .................................................. 130

Table K. 4 – Pay Factor Calculations for Burro Creek Site.............................................. 130

Table K. 5 – Pay Factor Calculations for Cordes JCT Site .............................................. 131

Table K. 6 – Pay Factor Calculations for Roosevelt Site ................................................. 131

Table K. 7 – Pay Factor Calculations for Safford Site ..................................................... 132

Table K. 8 – Pay Factor Calculations for Holbrook ( B) Site............................................ 132

Table K. 9 – Pay Factor Calculations for Payson Site...................................................... 133

Table K. 10 – Pay Factor Calculations for Tucson Site.................................................... 133

LIST OF FIGURES

Figure 2.1 – Three Layer Pavement Model ......................................................................... 5

Figure 2.2 – Diametral Resilient Modulus Test................................................................... 6

Figure 2.3 – Dynamic Modulus Test Setup ......................................................................... 7

Figure 2.4 – Typical Master Curve from Dynamic and Seismic Modulus Test Results ..... 7

Figure 2.5 – Ultrasonic Test Device for AC Specimens...................................................... 9

Figure 2.6 – Schematic of Falling Weight Deflectometer ................................................... 9

Figure 2.7 – Variation in AC Modulus with Frequency and Temperature ....................... 12

Figure 2.8 – Frequency Dependency of AC Modulus ....................................................... 13

Figure 3.1 – Portable Seismic Pavement Analyzer............................................................ 14

Figure 3.2 – Typical Time Records from the Portable Seismic Pavement Analyzer ........ 14

Figure 3.3 – Schematic of Ultra Sonic Surface Wave Method.......................................... 16

Figure 3.4 – Typical Dispersion Curve Obtained from Time Records in Figure 3.2 ........ 17

Figure 3.5 – Typical Phase Spectra Obtained from Time Records in Figure 3.2 .............. 17

Figure 3.6 – Typical Time Records as Demonstrated by PSPA Software......................... 18

Figure 3.7 – Typical Interpreted Results as Demonstrated by PSPA Software................. 19

Figure 4.1 – Process of Determining Ideal Target Modulus.............................................. 22

Figure 4.2 – Process of Characterizing Variation in Modulus with Temperature ............. 23

Figure 4.3 – Master Curve Concept for Defining Design Modulus .................................. 24

Figure 4.4 – Process of Field Testing for HMA Materials ................................................ 25

Figure 5.1 – Variation in Seismic Modulus with Air Voids from Laboratory Testing ..... 28

Figure 5.2 – Variations in Seismic Modulus with Temperature at .................................... 29

Figure 5.3 – Master Curve for Estimating Design Modulus.............................................. 29

Figure 5.4 – Typical Marking of Sites ............................................................................... 30

Figure 5.5 – Contour Plots of Variations in Design Modulus with PSPA along Site........ 31

Figure 5.6 – Modulus Control Charts from Site ................................................................ 32

Figure 5.7 – Distribution of Equivalent Design Moduli along Site................................... 33

Figure 5.8 – Comparison of Moduli from PSPA and Lab Tests on Cores ........................ 34

Figure 5.9 – Variation in Design Modulus with Air Voids at Core Locations.................. 35

Figure 5.10 – Distribution of Moduli due to Change in Gradation and

Asphalt Content of Mixes during Paving .................................................. 36

Figure 6.1 – Location of Sites Tested ................................................................................ 39

Figure 6.2 – Variations in Modulus with Temperature ( Slopes) for Lab Specimens

at Design and In- place Air Voids.................................................................. 45

Figure 6.3 – Master Curves for Specimens Prepared at Design Air Voids ....................... 46

Figure 6.4 – Master Curves for Specimens Prepared at Placement Air Voids .................. 46

Figure 6.5 – Comparisons of Target and As- Built Binder Contents at Arizona Sites ....... 49

Figure 6.6 – Comparisons of Target and As- Built Air Voids at Arizona Sites ................. 50

Figure 6.7 – Cumulative Distributions of Moduli ............................................................. 51

Figure 6.8 – Cumulative Distribution of Ratios of As- Built and Target Moduli

from all Arizona Tests .................................................................................. 52

Figure 6.9 – Comparison of Moduli from PSPA and Lab Tests on Cores ........................ 53

Figure A. 1 – Variations in Stress and Strain with Time for Different Materials

due to a Sinusoidal Load............................................................................... 63

Figure A. 2 – Sketch of Dynamic Modulus Test Setup ...................................................... 65

Figure A. 3 – Typical Dynamic Modulus versus Frequency Plot

at Different Temperatures ............................................................................. 67

Figure A. 4 – Typical Log Shift Factor versus Temperature Plot ...................................... 67

Figure A. 5 – Shifted Dynamic Modulus Curve................................................................. 68

Figure A. 6 – Typical Master Curve with Curve Fitting..................................................... 68

Figure B. 1 – Description of Different Waves.................................................................... 70

Figure C. 1 – Variation in Modulus with Air Voids for Buckeye ( Site 1) ......................... 73

Figure C. 2 – Variation in Modulus with Air Voids for Show Low ( Site 2)...................... 73

Figure C. 3 – Variation in Modulus with Air Voids for Holbrook ( Site 3) ........................ 74

Figure C. 4 – Variation in Modulus with Air Voids for Burro Creek ( Site 4).................... 74

Figure C. 5 – Variation in Modulus with Air Voids for Cordes JCT ( Site 5) .................... 75

Figure C. 6 – Variation in Modulus with Air Voids for Roosevelt ( Site 6) ....................... 75

Figure C. 7 – Variation in Modulus with Air Voids for Safford ( Site 7) ........................... 76

Figure C. 8 – Variation in Modulus with Air Voids for Holbrook B ( Site 8) .................... 76

Figure C. 9 – Variation in Modulus with Air Voids for Payson ( Site 9)............................ 77

Figure C. 10 – Variation in Modulus with Air Voids for Tucson ( Site 10)........................ 77

Figure D. 1 – Variation in Modulus with Temperature for Buckeye ( Site 1)..................... 78

Figure D. 2 – Variation in Modulus with Temperature for Show Low ( Site 2) ................. 78

Figure D. 3 – Variation in Modulus with Temperature for Holbrook ( Site 3) ................... 79

Figure D. 4 – Variation in Modulus with Temperature for Burro Creek ( Site 4)............... 79

Figure D. 5 – Variation in Modulus with Temperature for Cordes JCT ( Site 5)................ 79

Figure D. 6 – Variation in Modulus with Temperature for Roosevelt ( Site 6)................... 80

Figure D. 7 – Variation in Modulus with Temperature for Safford ( Site 7)....................... 80

Figure D. 8 – Variation in Modulus with Temperature for Holbrook B ( Site 9)................ 80

Figure D. 9 – Variation in Modulus with Temperature for Payson ( Site 9) ....................... 81

Figure D. 10 – Variation in Modulus with Temperature for Tucson ( Site 10)................... 81

Figure E. 1 – Master Curves for Buckeye Mix ( Site 1) ...................................................... 82

Figure E. 2 – Master Curves for Show Low Mix ( Site 2)................................................... 82

Figure E. 3 – Master Curves for Holbrook Mix ( Site 3)..................................................... 83

Figure E. 4 – Master Curves for Burro Creek Mix ( Site 4) ................................................ 83

Figure E. 5 – Master Curves for Cordes JCT Mix ( Site 5) ................................................. 84

Figure E. 6 – Master Curves for Roosevelt Mix ( Site 6) .................................................... 84

Figure E. 7 – Master Curves for Safford Mix ( Site 7) ........................................................ 85

Figure E. 8 – Master Curves for Holbrook B Mix ( Site 8) ................................................. 85

Figure E. 9 – Master Curves for Payson Mix ( Site 9) ........................................................ 86

Figure E. 10 – Master Curves for Tucson Mix ( Site 10) .................................................... 86

Figure G. 1 – Contour Plots of Variation in Design Modulus with PSPA

for Buckeye ( Site 1) ...................................................................................... 97

Figure G. 2 – Contour Plots of Variation in Normalized Modulus

( PSPA/ Target Modulus) for Buckeye ( Site 1) .............................................. 98

Figure G. 3 – Contour Plots of Variation in Design Modulus with PSPA ( a)

and Normalized Modulus ( b) for Show Low ( Site 2) ................................... 99

Figure G. 4 – Contour Plots of Variation in Design Modulus with PSPA ( a)

and Normalized Modulus ( b) for Holbrook ( Site 3) ................................... 100

Figure G. 5 – Contour Plots of Variation in Design Modulus with PSPA ( a)

and Normalized Modulus ( b) for Burro Creek ( Site 4)............................... 101

Figure G. 6 – Contour Plots of Variation in Design Modulus with PSPA ( a)

and Normalized Modulus ( b) for Cordes JCT ( Site 5) ............................... 102

Figure G. 7 – Contour Plots of Variation in Design Modulus with PSPA ( a)

and Normalized Modulus ( b) for Roosevelt ( Site 6) .................................. 103

Figure G. 8 – Contour Plots of Variation in Design Modulus with PSPA ( a)

and Normalized Modulus ( b) for Safford ( Site 7) ...................................... 104

Figure G. 9 – Contour Plots of Variation in Design Modulus with PSPA ( a)

and Normalized Modulus ( b) for Holbrook B ( Site 8) ............................... 105

Figure G. 10 – Contour Plots of Variation in Design Modulus with PSPA ( a)

and Normalized Modulus ( b) for Tucson ( Site 10)..................................... 106

Figure H. 1 – Modulus Control Charts from Buckeye ( Site 1)......................................... 107

Figure H. 2 – Modulus Control Charts from Show Low ( Site 2) ..................................... 108

Figure H. 3 – Modulus Control Charts from Holbrook ( Site 3) ....................................... 109

Figure H. 4 – Modulus Control Charts from Burro Creek ( Site 4)................................... 110

Figure H. 5 – Modulus Control Charts from Cordes JCT ( Site 5).................................... 111

Figure H. 6 – Modulus Control Charts from Roosevelt ( Site 6)....................................... 112

Figure H. 7 – Modulus Control Charts from Safford ( Site 7)........................................... 113

Figure H. 8 – Modulus Control Charts from Holbrook B ( Site 8).................................... 114

Figure H. 9 – Modulus Control Charts from Tucson ( Site 10)......................................... 115

Figure I. 1 – Distribution of Design Moduli for Buckeye ( Site 1) ................................... 116

Figure I. 2 – Distribution of Normalized Moduli ( PSPA/ Target Modulus)

for Buckeye ( Site 1) .................................................................................... 116

Figure I. 3 – Distribution of Design Moduli for Show Low ( Site 2)................................ 117

Figure I. 4 – Distribution of Normalized Moduli ( PSPA/ Target Modulus)

for Show Low ( Site 2)................................................................................. 117

Figure I. 5 – Distribution of Design Moduli for Holbrook ( Site 3) .................................. 118

Figure I. 6 – Distribution of Normalized Moduli ( PSPA/ Target Modulus)

for Holbrook ( Site 3)................................................................................... 118

Figure I. 7 – Distribution of Design Moduli for Burro Creek ( Site 4).............................. 119

Figure I. 8 – Distribution of Normalized Moduli ( PSPA/ Target Modulus)

for Burro Creek ( Site 4) .............................................................................. 119

Figure I. 9 – Distribution of Design Moduli for Cordes JCT ( Site 5) .............................. 120

Figure I. 10 – Distribution of Normalized Moduli ( PSPA/ Target Modulus)

for Cordes JCT ( Site 5)............................................................................... 120

Figure I. 11 – Distribution of Design Moduli for Roosevelt ( Site 6) ............................... 121

Figure I. 12 – Distribution of Normalized Moduli ( PSPA/ Target Modulus)

for Roosevelt ( Site 6) .................................................................................. 121

Figure I. 13 – Distribution of Design Moduli for Safford ( Site 7) ................................... 122

Figure I. 14 – Distribution of Normalized Moduli ( PSPA/ Target Modulus)

for Safford ( Site 7)...................................................................................... 122

Figure I. 15 – Distribution of Design Moduli for Holbrook B ( Site 8) ............................ 123

Figure I. 16 – Distribution of Normalized Moduli ( PSPA/ Target Modulus)

for Holbrook B ( Site 8)............................................................................... 123

Figure I. 17 – Distribution of Design Moduli for Tucson ( Site 10).................................. 124

Figure I. 18 – Distribution of Normalized Moduli ( PSPA/ Target Modulus)

for Tucson ( Site 10) .................................................................................... 124

Figure L. 1 – Variation in Lab Seismic Modulus with Air Voids at Core Locations

from Buckeye ( Site 1)................................................................................. 134

Figure L. 2 – Variation in Lab Seismic Modulus with Air Voids at Core Locations

from Show Low ( Site 2) ............................................................................. 134

Figure L. 3 – Variation in Lab Seismic Modulus with Air Voids at Core Locations

from Holbrook ( Site 3)................................................................................ 135

Figure L. 4 – Variation in Lab Seismic Modulus with Air Voids at Core Locations

from Burro Creek ( Site 4) ........................................................................... 135

Figure L. 5 – Variation in Lab Seismic Modulus with Air Voids at Core Locations

from Cordes JCT ( Site 5)............................................................................ 136

Figure L. 6 – Variation in Lab Seismic Modulus with Air Voids at Core Locations

from Roosevelt ( Site 6)............................................................................... 136

Figure L. 7 – Variation in Lab Seismic Modulus with Air Voids at Core Locations

from Safford ( Site 7)................................................................................... 137

Figure L. 8 – Variation in Lab Seismic Modulus with Air Voids at Core Locations

from Holbrook ( Site 8)................................................................................ 137

Figure L. 9 – Variation in Lab Seismic Modulus with Air Voids at Core Locations

from Payson ( Site 9) ................................................................................... 138

Figure L. 10 – Variation in Lab Seismic Modulus with Air Voids at Core Locations

from Tucson ( Site 10) ................................................................................. 138

Figure M. 1 – Distribution of Moduli due to Change in Gradation and

Asphalt Content of Mixes for Buckeye ( Site 1).......................................... 139

Figure M. 2 – Distribution of Moduli due to Change in Gradation and

Asphalt Content of Mixes for Show Low ( Site 2) ...................................... 139

Figure M. 3 – Distribution of Moduli due to Change in Gradation and

Asphalt Content of Mixes for Holbrook ( Site 3) ........................................ 140

Figure M. 4 – Distribution of Moduli due to Change in Gradation and

Asphalt Content of Mixes for Burro Creek ( Site 4).................................... 140

Figure M. 5 – Distribution of Moduli due to Change in Gradation and

Asphalt Content of Mixes for Cordes JCT ( Site 5) .................................... 141

Figure M. 6 – Distribution of Moduli due to Change in Gradation and

Asphalt Content of Mixes for Roosevelt ( Site 6)........................................ 141

Figure M. 7 – Distribution of Moduli due to Change in Gradation and

Asphalt Content of Mixes for Safford ( Site 7)............................................ 142

Figure M. 8 – Distribution of Moduli due to Change in Gradation and

Asphalt Content of Mixes for Holbrook B ( Site 8) .................................... 142

Figure M. 9 – Distribution of Moduli due to Change in Gradation and

Asphalt Content of Mixes for Payson ( Site 9)............................................ 143

Figure M. 10 – Distribution of Moduli due to Change in Gradation and

Asphalt Content of Mixes for Tucson ( Site 10).......................................... 143

Figure N. 1 – View of Site 1 ............................................................................................. 144

Figure N. 2 – ADOT Personnel Collection Loose Samples on Site 1 .............................. 144

Figure N. 3 – Surface Temperature at Time of Collection on Site 1 ................................ 145

Figure N. 4 – PSPA Collecting Information on Site 1...................................................... 145

Figure N. 5 – PSPA Collecting on Core Location at Site 1.............................................. 145

Figure N. 6 – View of Site 2 ............................................................................................. 146

Figure N. 7 – Detail of Site 2............................................................................................ 146

Figure N. 8 – PSPA Collecting on Site 2.......................................................................... 146

Figure N. 9 – View of Site 3 ............................................................................................. 147

Figure N. 10 – PSPA Testing on Core Location at Site 3................................................. 147

Figure N. 11 – Construction Operations at Site 3............................................................. 147

Figure N. 12 – View of Site 4........................................................................................... 148

Figure N. 13 – PSPA Colleting on Core Location of Site 4 ............................................. 148

Figure N. 14 – Segregated Area on Site 4 ........................................................................ 148

Figure N. 15 – PSPA Testing at Site 5.............................................................................. 149

Figure N. 16 – PSPA Collecting Data on Core Location of Site 5................................... 149

Figure N. 17 – View of Site 6........................................................................................... 149

Figure N. 18 – PSPA Testing on Site 6 ............................................................................ 150

Figure N. 19 – PSPA Collecting Data on Core Location of Site 6................................... 150

Figure N. 20 – View of Site 7........................................................................................... 150

Figure N. 21 – PSPA Testing on Core Location of Site 7 ................................................ 151

Figure N. 22 – View of Site 8........................................................................................... 151

Figure N. 23 – PSPA Testing on Core Location of Site 8 ................................................ 151

Figure N. 24 – View of Site 9........................................................................................... 152

Figure N. 25 – Nuclear Density Gage Testing on Site 9 .................................................. 152

Figure N. 26 – Coring at Site 9......................................................................................... 152

Figure N. 27 – Pavement Construction of Site 10 ............................................................ 153

Figure N. 28 – ADOT Staff Gathering Loose Samples on Site 10................................... 153

Figure N. 29 – PSPA Testing on Core Location of Site 10 .............................................. 153

Acknowledgements

The authors would like to give their sincere appreciation to Christ Dimitroplos for

managing this project. We would also like to thank the constructive advice from the

Project Advisory Team, especially Chad Auker, David Burbank, and Scott Weinland.

Their hard work and ever- present support and arranging of the logistics for the field tests

made the execution of this project much easier than expected.

We would also like to thank the hard working people from the four ADOT districts that

generously offered their time to sample and prepare cores for us. They are too numerous

to name.

1

EXECUTIVE SUMMARY

State highway agencies, such as the Arizona Department of Transportation ( ADOT),

have implemented quality control/ quality assurance programs to improve the quality of

placed hot- mix asphalt ( HMA) pavements. The quality of the HMA is assessed through

field inspection, and testing of pavement cores ( for density and thickness) and loose

materials ( for binder content and gradation).

One of the primary parameters considered in the design of flexible pavements is the

modulus of the HMA layer. Unfortunately, current quality management programs do not

provide any information about the modulus of the layer. To successfully implement a

mechanistic pavement design procedure or to develop realistic performance based

specifications, a method of monitoring the modulus of placed HMA is needed. Simple

performance tests, such as the dynamic modulus tests, on specimens prepared from

material retrieved during construction has been advocated for quality control. These test

procedures are time consuming, the costs of acquiring the equipment are high, and well-trained

laboratory staff is needed. Moreover, these tests are conducted on laboratory-prepared

specimens that are not representative of the as- placed HMA.

New devices and procedures overcome some of the shortcomings indicated above. These

procedures allow rapid data collection and interpretation in the lab and in the field. The

focus of the study has been on measuring the modulus of HMA with two nondestructive

devices: an ultrasonic device for testing HMA cores and briquettes, and a Portable

Seismic Pavement Analyzer ( PSPA) for testing the newly- constructed HMA layer.

The major advantage of seismic methods is that similar results are anticipated from the

field and laboratory tests as long as the material is tested under comparable conditions.

This unique feature of seismic methods in material characterization is particularly

significant for implementing performance- based specifications.

This report contains the results of an effort to address the issues related to the

implementation of the recommended seismic methods and devices in the day- to- day

operation of ADOT. The major issues addressed are the utility of the methods, means of

relating the measured parameters to the design moduli, and relating the parameters to

performance of the pavement

The outcomes from this project exhibit that the proposed equipment and methodologies

strike a balance between laboratory and field testing. Performing the simplified

laboratory and field tests along with more traditional tests may result in a database that

can be used to smoothly unify the design procedures and construction quality control.

2

3

I. INTRODUCTION

Quality assurance- quality control ( QA/ QC) of hot mix asphalt ( HMA) projects is mostly

oriented to the constructability and durability of the materials through process control.

Typical QA/ QC consists of ensuring the proper gradation, adequate asphalt content,

adequate voids- in- mineral aggregates ( VMA), and finally the desired in- place density of

the finished mat ( hot mix asphalt layer). Even though this process control is vital to the

success of a project, it does not provide all the information necessary to ensure a

high- quality product. Existing practices need to be supplemented with methods that will

provide continuity between the design, construction, and laboratory testing, so that

performance- based specifications can be implemented.

Several interrelated parameters have to be considered in a comprehensive QA/ QC

protocol. First, major parameters considered in the process need to be correlated to the

parameters used in the design ( modulus of HMA in this case). Based on the selected

design parameters, pre- construction laboratory tests need to be carried out to determine

the suitability of a material in terms of modulus. Adequate target moduli should be

established based on the results of the laboratory tests. The last step involves the quality

control during construction, ensuring that the target moduli have been achieved. In this

project, seismic methods are presented to demonstrate the usefulness of these techniques

to overcome some of these concerns.

A quality control device should have four major features to be effective in practical use.

First, it should measure fundamental properties of materials ( i. e., it should not be an

index test). Second, the device should be sensitive enough to the parameter of interest so

that poor and high quality materials can be readily delineated. Third, the measurements

should be accurate enough so that they can provide feedback to the pavement designer

and the laboratory personnel. Fourth, the device should be precise enough so that it can

be readily used in the QA/ QC process.

The focus of this project is to demonstrate the utility of the Portable Seismic Pavement

Analyzer ( PSPA) for in- situ modulus measurement of the HMA. The PSPA allows rapid

data collection and interpretation. Procedures have been presented to measure the moduli

of HMA with PSPA, calibrate and validate the results with simplified laboratory tests on

extracted cores or lab- prepared specimens, and as a side issue, determine the design

modulus from the measured values.

OBJECTIVES

The goal is to develop a pilot construction HMA quality management program for ADOT

based on seismic moduli. The equipment and protocols discussed here were developed

primarily through funding from the Texas Department of Transportation ( Nazarian et al.

2004). This quality management program is similar to the one that the Texas Department

of Transportation is considering for implementation.

4

The primary objective of this project is to demonstrate the utility of seismic field test

protocols and equipment, which in a rational manner, combine the results from laboratory

and field tests with those used for quality control during construction. A series of

simplified seismic laboratory tests that are compatible with the field tests have been

recommended. All these tests have several features in common. They can be performed

rapidly ( less than three minutes), they are inexpensive and their data reduction processes

are simple and almost instantaneous. The major advantage of seismic methods is that

similar results are anticipated from the field and laboratory tests as long as the material is

tested under comparable conditions.

These types of tests are one of the major components needed to develop a mechanistic

pavement design and performance- based construction specifications. A gradual

transition from the existing specifications to performance- based specifications may be

necessary. Performing the simplified laboratory and field tests on pavement materials

will allow us to develop a database that can be used to smoothly unify the design

procedures and construction quality control. Moreover, PSPA may be used to monitor

the condition of highway projects at any time after construction for quality control,

acceptance or management of such projects.

ORGANIZATION

The report consists of seven chapters and several appendixes. A brief description of the

background information is included in Chapter 2. The field seismic test setup is

discussed in Chapter 3. The overall test protocols are summarized in Chapter 4. A

comprehensive example of implementing the process is included in Chapter 5. Chapter 6

is dedicated to test results and analysis from ten sites. Summary, conclusions and the

future work plan are described in Chapter 7.

5

II. BACKGROUND

Current mechanistic- empirical flexible pavement design procedures are based on

modeling a pavement system as an elastic multi- layered and/ or viscoelastic system. The

remaining life of flexible pavements is mainly based on predicting the strains or stresses

at the interfaces of different layers. For instance, for a three- layer pavement composed of

an HMA layer, a base course, and a subgrade layer ( Figure 2.1), the two main strains

considered are the tensile strain at the bottom of the HMA layer and the compressive

strain on top of the subgrade.

HMA, 1

Subgrade, E3

Base, E2

H 1

H 2

ε r

ε z

Figure 2.1 – Three Layer Pavement Model

The fatigue cracking of a thin HMA layer is mainly due to the tensile strain at the bottom

of the HMA layer and to the modulus of the HMA layer ( Finn et al. 1977). The subgrade

rutting is a function of the compressive strain on top of the subgrade ( Shook et al. 1982).

The strains developed within a pavement system are strongly related to the moduli of

different layers. As a result, moduli of all layers should be accurately determined.

The general form for most distress models, which are used to estimate the fatigue damage

and the rutting failure, may be expressed as Equations 2.1 and 2.2 ( Ayres and Witczak

1998)

NF = K1 ( ε t) K2 ( E HMA ) K3 ( 2.1)

NR = K4 ( ε c) K5 ( 2.2)

where NF is the number of equivalent single axle loads ( ESAL), εt is the tensile strain at

the bottom of the HMA layer, and EHMA is the modulus of the HMA layer. Therefore,

one of the most important parameters in a mechanistic design procedure is the strains and

the modulus of the HMA layer.

6

TRADITIONAL METHODS FOR MEASURING HMA MODULUS

Daniel and Kim ( 1998) defined several field and laboratory tests for determining HMA

moduli. These tests range from modeling the viscoelastic behavior of HMA to indirect

( nomograph based) methods. The most common laboratory tests are the resilient

modulus, creep, dynamic modulus, free- free resonant column, and ultrasonic wave

velocity tests. The main field tests are the falling weight deflectometer ( FWD) and wave

propagation ( or seismic) tests. The most common and practical test methods are

reviewed in this section.

Diametral Resilient Modulus

The diametral resilient modulus is perhaps the only practical traditional method for

measuring the modulus of field cores. A picture of the test setup used is shown in Figure

2.2. A cyclic compressive load, P, is applied to the specimen vertically along one

diameter. This compressive load induces tensile stresses along the diameter of the

specimen in line with the load. These tensile stresses cause horizontal deformation of the

specimen, ΔH. The resilient modulus of the specimen, ERT is calculated from

ERT = P ( ν+ 0.27) / t ( 2.3)

where t = core thickness and ν = Poisson’s ratio.

There is a strong consensus amongst pavement engineers that this testing procedure is

rather time- consuming and results are not very repeatable ( Shah 1993, 7- 16). The

estimated repeatability of the test is about 15% to 20%, depending on the sophistication

of the test system, and the quality of the specimens.

D

P

P

AC Specimen

a

Rubber Membrane

( Optional)

Rubber Membrane

( Optional)

P = applied load

t = thickness of specimen

D = diameter of specimen

a = width of loading strip

= 13 mm for 102 mm diameter specimen

= 19 mm for 152 mm diameter specimen

Figure 2.2 – Diametral Resilient Modulus Test

7

Dynamic Modulus Tests

Since the dynamic modulus tests were utilized in this study, they are described in detail in

Appendix A. The schematic of the test set up is shown in Figure 2.3. In the dynamic

modulus test, stresses and strains under sinusoidal loading are measured. Assuming that

the material behaves linearly viscoelastic, the dynamic modulus is determined. By

varying the frequency and temperature over a wide range, a “ master curve” can be

developed. A typical master curve, as shown in Figure 2.4, can be used to estimate the

modulus of the HMA at any loading frequency or temperature.

Stainless Steel

Cylinder

Bottom End

Platen

LVDT Cable

Load Cell

Actuator

Load Cell

Top End Platen

LVDT

Steel

Ball

External

Target and

Magnet

LVDT

Figure 2.3 – Dynamic Modulus Test Setup

1

10

100

1000

10000

0.0001 0.01 1 100 10000 1000000 100000000

Reduced Frequency, Hz

Dynamic Modulus, ksi

Dynamic

Seismic

Master Curve

Figure 2.4 – Typical Master Curve from Dynamic and

Seismic Modulus Test Results

1.77

Log( E*) = 1.75 +

1+ e- 5.5+ 0.67> dog( 1/ Hz)

8

Since the dynamic modulus tests are comprehensive and time- consuming, they are not

suitable for testing a large number of specimens. Even under the simplified version of

the test provided by the National Cooperative Highway Research Program ( NCHRP), not

more than a few specimens can be tested in one day. Based on an extensive study by

Tandon et al. ( 2006), the variability of the tests is less than 5% on synthetic specimens

and more than 15% on actual briquettes.

The dynamic modulus test is a fundamental test that provides comprehensive insight into

the behavior of the materials. One of the limitations of the method as a quality

management tool is that the length of the specimen has to be at least 6 in. Since most

HMA layers are constructed in lifts of about 2 to 3 in., a specimen from loose materials

has to be compacted for testing. As indicated by Tashman et al. ( 2001), the internal

structure of the specimens prepared with a compactor may be different than those in the

field, resulting in different moduli ( typically greater on lab specimens).

Free- free Resonant Column Tests

In the free- free resonant column test ( a. k. a. impact resonance test), the specimen is

impacted with a hammer, and the resonant frequency associated with the standing waves

within the specimen is measured ( Nazarian et al. 2004; Kim and Kweon 2006). The

resonant frequency along with the length of the specimen can be used to determine the

modulus ( ASTM C215).

For this test to be effective, a specimen with a length- to- diameter ratio from 1.5 to 2

is required. As such, these tests cannot be conducted on cores retrieved from the field.

Ultrasonic Tests

The ultrasonic setup used in this study is shown in Figure 2.5. The elastic modulus of

a specimen is measured using a device ( marketed as a V- meter) containing a pulse

generator and a timing circuit, coupled with piezoelectric transmitter. Special removable

epoxy coupling caps are used on both transducers to ensure full contact between the

transducers and a specimen. To secure the specimen between the transducers, a loading

plate is placed on top of it, and a spring- supporting system is placed underneath the

transmitting transducer. The compression wave ( P- wave) receiving transducer is placed

on top of the specimen, on the opposite end from the transmitter. The timing circuit

digitally displays the time needed for a wave to travel through, tv. The modulus, Mv, is

then calculated using

,

( R t )

M = WH 2

v

v 2 π

( 2.4)

where W, R and H are the mass, radius, and height of the specimen. The size of the

sensors used with the test device is large relative to the wave travel path. The modulus

9

Receiver Transducer

Holding Plate

Holding Base

Transmitting Transducer

Springs V- Meter

12.0

AC Specimen

Figure 2.5 – Ultrasonic Test Device for AC Specimens

measured with the V- meter, Mv, is the so- called constraint modulus. The constraint

modulus, Mv can then be converted to Young’s modulus, Ev through a theoretically-correct

relationship in the form of

( 1- )

Ev = M v ( 1+ )( 1- 2 ) ν

ν ν

( 2.5)

where ν is Poisson’s ratio. Tandon et al. ( 2006) estimated that the uncertainty in the

measurements is about 2%.

Falling Weight Deflectometer ( FWD)

The FWD measures the response ( surface deflections) of a pavement from an applied

impulse load. A schematic of a FWD is shown in Figure 2.6. The impulse load is

created by dropping a weight from predetermined heights. The deflections at the surface

of the pavement are measured through seven geophones, which are automatically lowered

onto the pavement.

Figure 2.6 – Schematic of Falling Weight Deflectometer

10

To analyze the measured load and deflections, the pavement is modeled as a multi-layered

linear elastic system. The measured deflections are compared to predicted

deflections generated with a computer program that performs a linear elastic analysis.

The modulus of each layer is obtained when the measured and predicted deflections

compare well. The analysis is mainly conducted by comparing the measured and

predicted deflections until they compare well, which is known as deflection basin- fitting.

The main advantages to the FWD are that tests are conducted in the field and that the

method is practical for daily use. However, several combinations of moduli and layer

thickness may generate predicted deflections that match measured deflections.

Furthermore, many studies have shown that with the current configuration of the

receivers in the FWD it may be difficult to accurately determine the modulus of the top

layer in the pavement.

Seismic Field Methods

The seismic methods are based on generating and detecting stress waves in the pavement.

Several automated devices are available for this purpose. The Portable Seismic

Pavement Analyzer ( PSPA) is one of them. The seismic methodology is described in the

next chapter.

Empirical Models

A number of empirical models for estimating the dynamic modulus of the HMA from the

volumetric properties of the mixes have been suggested. These models can be used in the

absence of laboratory testing with an understanding that they are approximate in nature.

A series of popular models, known as the “ Witczak” models, have been proposed for this

purpose. These models are summarized in Table 2.1. The latest Witczak model is in the

form of ( Witczak et al. 2003):

( )

( )

[ ( ) ]

( 0.603313 0.31335 log ( ) 0.393532 log ( η ))

34

2

4 38 38

4

2

200 200

1

3.871977 0.0021 0.003958 0.000017 0.00547

0.002841 0.058097 - 0.808808

log | | 1.249937 0.029232 0.001767

+ − − −

− + − +

+

+

+ −

= − + −

f

beff a

beff

a

AC

e

P P P P

V V

V

P V

E P P

( 2.6)

where EAC is the dynamic modulus of the asphalt concrete ( AC) mix ( in 105 psi), η is the

bitumen viscosity ( in 106 poise), f is the load frequency ( in Hz), Vv is the percent air voids

in the mix by volume, Pac is the percent effective bitumen content by volume, and P200 is

the percent passing No. 200 sieve by total aggregate weight. The “ Witczak” model is

part of the new mechanistic- empirical design guide being developed by the National

Cooperative Highway Research Program. A new model called the Hirsch Model

( Chirstiansen et al. 2003) has also been proposed. This model is provided in Table 2.1.

11

Table 2.1 – Summary of Material Models

Witczak 1982 Model

( Asphalt Institute, 1982).

( )

( ) + + ∋

+ + −

= + −

+ −

+

0.02774

1.1

0.5

1.3 0.49825 log

1.3 0.49825 log 0.5

0.17033

200

0.00189 0.931757

0.070377 0.000005

log 5.553833 0.028829 0.03476

f

f

t P

t P

V

f

E P

f ac

p

ac

f

p

AC V

η

EAC = dynamic modulus of AC mix ( in psi), η = bitumen viscosity ( in 106 poise) at 70oF, f = load

frequency ( in Hz), Vv = percent air voids in the mix by volume, Pac = percent effective bitumen

content by volume, and P200 = percent passing No. 200 sieve by total aggregate weight.

Witczak 1995 Model

( Andrei et al., 1999)

( )

( )

[ ( ) ]

( 0.716 log ( ) 0.7425 log ( η ))

34

2

4 38 38

4

2

200 200

1

1.87 0.002808 0.00000404 0.0001786 0.0164

0.00196 0.03157 - 0.415

log | | 0.261 0.008225 0.00000101

+ − −

+ + − +

+

+

+ −

= − + −

f

beff a

beff

a

AC

e

P P P P

V V

V

P V

E P P

EAC = dynamic modulus of AC mix ( in 10^ 5 psi), η = bitumen viscosity ( in 106 poise) at 70oF, f =

load frequency ( in Hz), Va = percent air voids in the mix by volume, Vbeff = percent effective bitumen

content by volume, and P200 = percent passing No. 200 sieve by total aggregate weight, P4 =

cumulative percent retained No. 4 sieve by total aggregate weight, P34 = cumulative percent retained

No. 3/ 4 sieve by total aggregate weight, and P3/ 8 = cumulative percent retained No. 3/ 8 sieve by total

aggregate weight.

Witczak 2000 Model

( NCHRP, 2004)

( )

( )

[ ( ) ]

( 0.603313 0.31335 log ( ) 0.393532 log ( η ))

34

2

4 38 38

4

2

200 200

1

3.871977 0.0021 0.003958 0.000017 0.00547

0.002841 0.058097 - 0.808808

log | | 1.249937 0.029232 0.001767

+ − − −

− + − +

+

+

+ −

= − + −

f

beff a

beff

a

AC

e

P P P P

V V

V

P V

E P P

Hirsch Model

( Chirstiansen, et al., 2003)

⎥ ⎥ ⎥ ⎥

⎦

⎤

⎢ ⎢ ⎢ ⎢

⎣

⎡

+

⎟⎠

⎞

⎜⎝

⎛ −

−

+ ⎥⎦

⎤

⎢⎣

⎡

⎟⎠

⎞

⎜⎝

⎛ + ⎟⎠⎞

⎜⎝

= ⎛ −

binder

c

mix c binder

VFA G

VMA

VMA

E P VMA G VFA xVMA P

4,200,000 3 | * |

100

1

1

10,000

3 | * |

100

| * | 4,200,000 1

0.58

0.58

3 | * |

650

3 | * |

20

⎟⎠

⎞

⎜⎝

+ ⎛

⎟⎠

⎞

⎜⎝

⎛ +

=

VMA

VFAx G

VMA

VFAx G

P

binder

binder

c

VMA = Voids in mineral aggregates (%), VFA = Voids filled with asphalt (%), and | G*| binder = shear

complex modulus of binder ( psi)

12

Impact of Temperature and Frequency

Several parameters affect the dynamic modulus of HMA. The most important parameters

are the rate of the loading ( i. e., frequency of loading), temperature, and air void content.

The typical frequency range at which HMA moduli measured with seismic methods is

about 10 kHz to 25 kHz; whereas, the actual traffic load has a dominant frequency of

about 10 to 30 Hz. Aouad et al. ( 1993) clearly demonstrated the importance of

considering the impact of frequency on modulus. Typically, the modulus measured with

seismic methods should be reduced by a factor of about 3 to 15 depending on the

temperature, as shown in Figure 2.7. Daniel and Kim ( 1998) and Kim and Lee ( 1995)

used the results from several laboratory and field tests ( such as FWD, ultrasonic, uniaxial

sweep, and creep) to show the frequency dependence of modulus. The results from

Daniel and Kim are shown in Figure 2.8. Again, the frequency dependence is

temperature related.

The HMA modulus is strongly dependent on temperature. Von Quintus and Kilingsworth

( 1998) demonstrated the importance of temperature gradient within a pavement section.

Aouad et al. ( 1993), Li and Nazarian ( 1994) and several other investigators have studied

the variation in modulus with temperature.

15

12

9

6

3

0

Frequency Adjustment Factor

30 60 90 120 150

E1 5 k H z / E30Hz

Temperature, T, o F

Aouad ( 1993)

Extrapolated from Sousa

and Monismith ( 1988)

Potential Adjustment Curve

Figure 2.7 – Variation in AC Modulus with Frequency and

Temperature ( from Aouad et al. 1993)

13

1. E+ 05

1. E+ 04

1. E+ 03

1. E+ 02

1. E+ 00 1. E+ 01 1. E+ 02 1. E+ 03 1. E+ 04 1. E+ 05

Frequency ( Hz)

Stiffness ( MPa)

Oct 96, 13 C

May 95, 25 C

MN/ Road

Uniaxil Freq

Sweep

FWD

Impact

Resonance

Surface Wave

Figure 2.8 – Frequency Dependency of AC Modulus ( from Daniel and Kim 1998)

14

Figure 3.1 – Portable Seismic Pavement Analyzer

- 0.8

- 0.6

- 0.4

- 0.2

0

0.2

0.4

0.6

0.8

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Time ( milliseconds)

Amplitude

Sensor 1

Sensor 2

Source

Figure 3.2 – Typical Time Records from the Portable Seismic Pavement Analyzer

15

III. PORTABLE SEISMIC PAVEMENT ANALYZER

The Portable Seismic Pavement Analyzer ( PSPA) measures the average modulus of the

ex- posed surface layers within a few seconds in the field. The operating principle of the

PSPA is based on generating and detecting stress waves in a layer. The Ultrasonic

Surface Wave ( USW) interpretation method is used to determine the modulus of the

material. Description of the measurement and implementation techniques is the subject

of the next few pages.

The PSPA, as shown in Figure 3.1, consists of two transducers ( accelerometers in this

case) and a source packaged into a hand- portable system. The source package is also

equipped with a transducer for consistency in triggering. The device is operable from a

computer tethered to the hand- carried transducer unit through a cable that carries

operational com- mands to the PSPA and returns the measured signals to the computer.

To collect data with the PSPA, the technician initiates the testing sequence through the

computer. All the other data acquisition tasks are handled automatically by the computer.

The source, which is a computer- controlled solenoid, is activated four to six times. Pre-recording

impacts of the source are used to adjust the amplifiers in a manner that

optimizes the dynamic range of the electronics. The outputs of the three transducers from

the final three impacts are saved and averaged for more reliability. Typical voltage

outputs of the three accelerometers are shown in Figure 3.2. In any seismic method, the

goal is to deter- mine the velocity of propagation of waves within a material. These

records are used to determine the velocity of propagation of waves in the HMA layer.

A short primer on wave propagation theory and propagation velocity is included in

Appendix B. Three common types of seismic waves are compression waves, shear

waves and surface ( Rayleigh) waves. Surface waves contain about two- thirds of the

seismic energy making them the easiest to measure. For this reason, Rayleigh wave

velocity is used in the PSPA.

For pavement engineering, the interest is to determine the modulus, not the velocity of

propagation. Young’s modulus, E, and Rayleigh wave velocity, VR, are theoretically

related through:

E = 2 ( 1 + ν ) ρ [ V R ( 1.13 - 0.16ν )] 2 ( 3.1)

where ν is Poisson's ratio, and ρ is the density of the material.

The next question is how to determine the propagation velocity from waveforms such as

those shown in Figure 3.2. In the most general term, the velocity of wave propagation,

V, can be determined by obtaining the travel time of waves, Δt, and receiver spacing, ΔX,

from:

t

V = X

Δ

Δ

( 3.2)

Several techniques are available for obtaining the travel time, Δt. The Ultrasonic Surface

Wave ( USW) method ( Nazarian et al. 1993) is the one utilized in the PSPA for this

purpose. In the USW method, the variation in the phase velocity with wavelength is

16

measured. A plot of the phase velocity vs. wavelength is called a dispersion curve. At

wavelengths less than or equal to the thickness of the uppermost layer, the travel time

( and as such velocity of propagation) of surface waves is independent of wavelength, as

sketched in Figure 3.3. Therefore, if one simply generates high- frequency ( short-wavelength)

waves and if one assumes that the properties of the uppermost layer are

uniform, the phase velocity of the upper layer can be determined. The wavelength at

which the phase velocity, i. e. phase velocity of individual frequency components, is no

longer constant is closely related to the thickness of the top layer ( NCHRP 1996).

0

1

2

3

4

5

6

7

8

3000 3200 3400 3600 3800 4000

Phase Velocity ( ft/ s)

Wavelength ( in.)

h

Dispersion

Curve

VR1

VR2

Asphalt

( VR1)

Pavement Layout

Base

( VR2)

Figure 3.3 – Schematic of Ultra Sonic Surface Wave Method

An actual dispersion curve from the time record shown in Figure 3.2 is included in Figure

3.4a. As approximated by the solid line, the phase velocity ( labeled as velocity in the

soft- ware) is reasonably constant for the first 3 in. below which the phase velocity tends

towards lower values with depth. Comparing this figure with the idealized one in Figure

3.3, the average phase velocity is about 4200 fps and the approximate thickness is about 3

in. To obtain the average modulus, the dispersion curve from a wavelength of about 1 in.

to slightly less than the nominal thickness of the layer is used.

For practical inspection of dispersion curve in the field ( see Figure 3.4b), the velocities in

Figure 3.4a are converted to moduli using Equation 3.1, while the wavelength is simply

relabeled as depth. In that manner, the operator of the PSPA can get a qualitative feel for

the variation in modulus with depth.

The dispersion curve shown in Figure 3.4 is developed from the phase spectra shown in

Figure 3.5. The phase spectrum can be considered as an intermediate step between the

time records shown in Figure 3.3 and the dispersion curve shown in Figure 3.4 ( Nazarian

and Desai. 1993). This step makes the determination of the velocity with wavelength

much easier. The phase spectrum is determined by conducting Fourier transform and

spectral analysis on the time records from the two sensors.

17

a) Actual

b) Practical

Figure 3.4 – Typical Dispersion Curve Obtained from Time Records in Figure 3.2

Two phase spectra are shown, one measured from the time records, and the other that

represents the best estimation of the phase when the effect of other waves are removed.

The second one is used to compute the dispersion curve as described above and detailed

in Nazarian and Desai ( 1993).

- 180

- 120

- 60

0

60

120

180

0 5000 10000 15000 20000 25000 30000 35000 40000

Frequency, Hz

Phase, degree

Measured

Predicted

Figure 3.5 – Typical Phase Spectra Obtained from Time Records in Figure 3.2

The software that operates and reduces the PSPA data is called the Spa Manager. The

screens of the software that can be used in the field during data collection are shown next.

18

A typical waveform screen from the Spa Manager at one point is shown in Figure 3.6.

Three time records are shown in the figure. The red record is the time history of the sensor

placed in the source, with the amplitude heavily attenuated. This record is useful to the

advanced user for ensuring that the source is functioning properly. The black record

depicts the time history as recorded by the sensor closer to the source ( near receiver), and

the green record is the time history from the far sensor. The black and green receiver

records are used in the determination of the modulus with the USW method. Both records

demonstrate the typical arrival of the surface wave energy as depicted by an initial almost

zero- amplitude record followed by a full sine- wave cycle in the left hand of the records.

These full- sine waves are followed by a region of virtually zero amplitude as depicted in

the right hand side of the graph. On the left side of the figure, under the “ Results” section,

the modulus obtained for this section ( i. e. 1090 ksi) is presented as soon as the data

collection is completed.

Figure 3.6 – Typical Time Records as Demonstrated by PSPA Software

In the next step, the operator has the option of viewing the reduced data, as shown in Figure

3.7. Several items can be inspected in the figure. The graph at the bottom is the phase

spectrum as discussed above. This curve should represent a saw- tooth pattern ( Nazarian et

al. 2004). The green record is the measured phase spectrum and the red one is the best fit to

the data by the software. The two curves follow one another quite well.

The upper graph labeled “ Dispersion Curve is a representation of the variation in modulus

( horizontal axis) with wavelength ( vertical axis). The dispersion curve, which is directly

calculated from the phase spectrum, is represented by green dots. The red vertical solid line

Time Records

Sensor 1

Sensor 2

Source

19

in this graph corresponds to the range of thickness along which the average modulus is

calculated. This average value is the number shown in the “ Results” section ( i. e., 1090 ksi,

where 1 ksi = 1000 lbs. force per square inch). The shortest thickness is controlled by the

spacing between the receivers, the top aggregate size of the mixture and the shortest

wavelengths measured by the PSPA at this transducer spacing. The longest thickness is

input by the user as a nominal value. In this case the nominal thickness and the actual

thickness of the layer coincide quite well, as the measured dispersion curve is uniform up to

a thickness of 2.5 in. beyond which the curve breaks towards lower moduli.

Data Reduction

Dispersion Curve

Measured

Range Used

for average

Modulus

Figure 3.7 – Typical Interpreted Results as Demonstrated

by the Portable Seismic Pavement Analyzer Software

Because the temperature varies from location to location, it is measured at each point

with a laser temperature gun to adjust the AC moduli to 77 ° F. The relationship

suggested by Li and Nazarian ( 1994) can be used for adjusting the modulus of AC to a

reference temperature of 77 ° F ( 25 ° C) in the absence of mix- specific modulus-temperature

relationship. That relationship is in the form of

E77° = Et / ( 1.60 - 0.0078 t) ( 3.3)

where E77 and Et are the moduli at 77 ° F and measured temperature ( in Fahrenheit).

However, the modulus- temperature relationship established for a given mix can be

utilized for more accurate results. The process of developing a mix- specific relationship

is discussed in the next chapter.

20

21

IV. SEISMIC METHODOLOGY FOR QUALITY MANAGEMENT

OF HOT ASPHALT

The goal of any highway agency is to construct a durable longer lasting layer of HMA.

Another recent goal of most highway agencies is to shift from the prescriptive ( method-based)

specifications to performance- based specifications. To achieve these two goals, the

following three inter- related activities have to be performed adequately and in harmony:

1. The pavement engineer should verify that the thickness and modulus of the layer

are adequate, so that structural failure would not happen.

2. The laboratory engineer should select material and mix ( job mix formula) that can

provide durable pavement with adequate modulus.

3. The construction and lab engineers should perform lab and field tests to ensure

that the layer is adequately constructed and the material delivered is as designed

in the laboratory so that the mat is durable.

Since these three items are inter- related, a close coordination among the pavement en-gineer,

lab engineer, and construction engineer is necessary. This means that the modulus

assumed for the HMA by the pavement engineer should be verified by the lab engineer

during mix design and by the resident engineer during construction. Under the current

specifications of almost all highway agencies, the modulus is hardly ever measured in the

laboratory during mix selection or on the completed mat during construction. The pro-posed

quality management protocol will provide a convenient process by which the three

bullet items above can be harmonized.

The proposed quality management procedure consists of the following five steps.

1. Selecting suitable materials and mix for a given project.

2. Determining a target modulus for the mix.

3. Characterizing the variation in modulus with temperature.

4. Determining modulus of material for structural design.

5. Field quality tests ( measuring field moduli and comparing them with the target modulus).

Each step is described below.

Step 1: Selecting Suitable Materials and Mix for a Given Project

The process of volumetric design of an HMA, from the simplest ( Marshall method) to the

most sophisticated ( Strategic Highway Research Program method), ensures a construct-ible

and durable material. The durability of a material cannot be directly included in the

structural design of a pavement, even though durability definitely does impact perform-ance.

The characteristics of a durable material depend on the collective experience of a

large and diverse group of scientists and practitioners. Each highway agency’s specifica-tions

clearly define how to obtain a durable HMA material by considering parameters

such as angularity of the aggregates, the hardness of aggregates, percent allowable fines,

the type of binder, and the degree and method of compaction. This practice should be

continued to ensure a durable mix. Current ADOT specifications, such as Items 416 and

417 ( ADOT 2000) are appropriate for this purpose. In addition, to tie the structural

design of a mix to the laboratory mix selection, the modulus of the HMA has to be

measured. Methods to measure the modulus of the mix are described in the next steps.

22

Step 2: Determining a Target Modulus for the Mix

After the material is selected and the job mix formula is ascertained, the next step is to

determine its target modulus. The modulus can be related to one of the primary

construction parameters such as the compaction effort ( i. e., air voids). This activity can

be carried out in conjunction with the determination of the job mix formula. The

following steps are involved in this activity:

• Prepare four or five specimens from the JMF with different air voids. This can be

achieved by controlling the number of gyrations used for compaction or by

controlling the height of the specimen. The range of air voids from as low as 2% to

as high as 12% is recommended.

• Measure the air voids and the modulus of each specimen at about 75oF. The

ultrasonic device shown in Figure 2.5 is recommended to measure the seismic

modulus of each specimen in less than one minute. The current ADOT Test Method

424a ( similar to AASHTO T- 269) can be used to measure the air voids.

• Develop a plot of seismic modulus vs. air voids. An example is shown in Figure 4.1.

• Select the modulus corresponding to the target air voids at placement ( typically 7-

8%). Ideally, this is the target modulus for field quality control. However, because

of the differences in the nature of field and laboratory compaction, this ideal

modulus should be multiplied by an adjustment factor. This adjusted modulus is

used by the construction engineer for field quality control as described in Step 5.

As an example, a seismic modulus of about 1523 ksi is selected as the field target

modulus for the mix shown in Figure 4.1; as such, the seismic moduli measured in

the field should be equal to or greater than 1523 ksi1.

Figure 4.1 – Process of Determining Ideal Target Modulus

1. an adjustment factor of 1 is used in this report. However, based on this study, an adjustment factor of

0.85 is recommended. The justification is provided in Chapter 6.

0

400

800

1200

1600

2000

2 4 6 8 10 12

Air Voids, %

Lab Seismic Modulus, ksi

Placement

Air Voids

Design

Air Voids

Target Modulus

for Field QC

23

Step 3: Characterizing the Variation in Modulus with Temperature

The modulus of a layer varies with temperature of the mat. It is difficult to know the

temperature of the mat during field quality control, since it is a function of the ambient

temperature and the time of day that the tests are performed. The following steps can be

followed to relate modulus to temperature:

• Prepare a specimen at the target placement air voids. Since the lab tests are

nondestructive, the same specimen used in Step 2 can be used in this step.

• Place the specimen in a temperature- control chamber. Vary the temperature at

least four times and allow the specimen to equilibrate to the desired temperature.

The suitable temperature range can be determined based on the guidelines set

forward by SHRP for selecting the regional air temperature extremes to

determine the appropriate performance grade ( PG) binder2.

• Measure the seismic modulus of the specimens at each temperature with the

ultrasonic device.

• Develop a plot of seismic modulus vs. temperature. An example is shown in

Figure 4.2. Determine the slope of the best- fit relationship between modulus and

temperature. The slope of the best- fit line is used to adjust the field modulus to a

uniform design temperature ( 75oF in this study).

For example, a slope of 9.63 ksi/ oF is obtained for the mix shown in Figure 4.2.

y = - 9.63x + 2208

R 2 = 0.99

0

400

800

1200

1600

2000

50 70 90 110 130 150 170

Temperature, F

Lab Seismic Modulus, ksi

Minimum

Temperature

Specimen at Placement Air Voids

Maximum

Temperature

Figure 4.2 – Process of Characterizing Variation in Modulus with Temperature

2. The short- term exposure of the specimen to high temperatures ( up to 160oF) does not seem to cause

any degradation ( such as slumping) to the specimen. However, it would be advisable to check the

dimensions of the specimens to ensure that the specimen has not slumped.

24

Step 4: Determining Modulus of Material for Structural Design

Moduli obtained with seismic measurements are low- strain, high- strain rate values. Vehi-cular

traffic causes high strain deformation at low strain rates. Because of these differences,

the pavement community has been concerned with how to implement seismic moduli in the

design. This concern has been resolved by implementing the master curve concept, which

tracks the modulus over a wide frequency and temperature range.

Tandon et al. ( 2006) and Kim and Kweon ( 2006) have shown that the seismic modulus and

the master curve from dynamic modulus can be combined together. A typical master curve

from a specimen with combined results from both the ultrasonic and dynamic modulus tests

is shown in Figure 4.3. The moduli from the two tests complement one another in defining

one master curve. As such, the results of the combined seismic / dynamic modulus tests can

be used with confidence in the structural design.

Once the master curve is established, the design modulus can be readily determined from the

design vehicular speed and the design temperature as recommended in any mechanistic-empirical

design guide. If the modulus assumed by the designer and the one obtained from

this analysis significantly differ, either an alternative material should be used, or the layer

thickness should be adjusted. That way, the design and material selection can be harmonized.

10

100

1000

10000

0.01 0.1 1 10 100 1000 10000 100000

Reduced Frequency, Hz

Dynamic Modulus, ksi

Dynamic

Seismic

Master Curve

Design

Modulus

Design

Frequency

Figure 4.3 – Master Curve Concept for Defining Design Modulus

The ratio of moduli at 10 Hz ( typical of an FWD) and 10 kHz ( typical for the seismic meth-od)

from the master curve is 2.1: 1 for the example shown in Figure 4.3. One concern raised

is that the dynamic modulus tests are not routinely performed. In the absence of mix- specific

dynamic modulus test results, empirical relationships presented in Chapter 2 can be used.

Based on this discussion, the development of the master curve is desirable but optional.

Practically speaking, the design modulus obtained in Step 2 from the seismic modulus vs. air

25

voids plot can be divided by a factor obtained by dividing the moduli at 10 Hz ( typical of an

FWD) and 10 kHz ( typical for seismic) from the empirical relationships to obtain the modu-lus

used in the structural design, if the dynamic modulus tests are not performed on the mix.

Step 5: Field Quality Tests

Depending on ADOT policies, this step can be conducted by ADOT personnel as a part of

their quality assurance program, or can be performed by the contractor as a part of the

quality control program. PSPA tests are carried out at regular intervals ( for this project

every 100 ft) or at any point that the construction inspector suspects segregation, lack of

compaction or any other construction related anomalies. An example of seismic moduli

adjusted to a temperature of 75oF at one site is shown in Figure 4.4a.

0

200

400

600

800

1000

1200

1400

1600

1800

6542 6534 6526 6518 6510 6502 6494 6486 6478 6470 6462

Station Number

Seismic Modulus, ksi

Target Modulus ( from Step 2)

a) Moduli as Measured. Adjusted to 75 ° F

0

100

200

300

400

500

600

700

800

6542 6534 6526 6518 6510 6502 6494 6486 6478 6470 6462

Station Number Equivalent Design Modulus, ksi

Target Modulus

Average Field Modulus

b) Equivalent Design Modulus

Figure 4.4 – Process of Field Testing for HMA Materials

26

Alternatively, the field and lab seismic moduli shown in Figure 4.4a can be converted to

equivalent design modulus as discussed in Step 4 ( see Figure 4.4b) 3. The field moduli

should be equal to or greater than the target seismic modulus determined in Step 2. In

this case, moduli usually fall below the target value of 725 ksi. As reflected in Figure

4.4b, the average field equivalent design modulus is about 616 ksi, about 82% of the lab

value. This pattern is normally observed due to the compaction efforts associated with

laboratory specimens and field mats being different. Laboratory specimens usually yield

moduli that are greater than field specimens. This is another reason to rely on the in

place modulus rather than lab- prepared specimens. The relationship between field and

lab tests will be more rigorously established in Chapter 6.

3. From here on the report is generally based on the equivalent design moduli.

27

V. EXAMPLE IMPLEMENTATION OF QUALITY MANAGEMENT

IN ARIZONA

The five- step quality management procedure was adapted for evaluating the modulus of

the HMA. As a review, the steps that were taken are as follows:

1. Selecting suitable materials and mix for a given project.

2. Determining a target modulus for the mix.

3. Characterizing the variation in modulus with temperature.

4. Determining modulus of material for structural design.

5. Field quality tests

A sixth and final step, the validation of the results, was also carried out to ensure the

compatibility of field and lab processes. The procedure as applied to one site is discussed

in this chapter as an illustrative example.

Step 1: Selecting Suitable Materials and Mix for a Given Project

The job mix formulae for all sites were provided to the UTEP team by ADOT staff. The

mix design was either in accordance with Item 416 ( Marshall method) or Item 417

( SHRP method) of ADOT specifications ( ADOT 2000). The pertinent information for

the example site is shown in Table 5.1. For this example, the mix design was according

to Item 416. Three 5- gallon containers of the mix were sampled during the paving

operation for a variety of lab testing.

Table 5.1 – Job Mix Formula from Project

AC Type Type of

Aggregate

Nominal

Aggregate

Size

Target

Asphalt

Content

Design

Air

Voids

In- place

Air

Voids

Gmm Compaction

Temperature

PG- 76- 16 Granite 0.75 in. 4.6 % 6.0 % 8%* 2.460 310 º F

* Rounded to the nearest integer

Step 2: Determining a Target Modulus for the Mix

Ten4 specimens, each 4 in. in diameter and 6 in. in height, were prepared in the lab with

different air voids using materials collected from the site during construction. For both

Marshall and SHRP mixes, the specimens were prepared using a Superpave gyratory

compactor for uniformity and to be compliant with the specimen requirements for

dynamic modulus tests. The ultrasonic device was used to measure the seismic modulus

of each specimen in less than one minute. The variation in seismic modulus with air

4. Four specimens are adequate for normal operation

28

voids for a nominal temperature of 75° F is shown in Figure 5.1. The two parameters are

well- related with an R2 value of 0.96. Based on this figure, a target seismic modulus of

1523 ksi is anticipated at the target placement air voids of 8% shown in Table 5.1.

y = - 75.31x + 2125.47

R 2 = 0.96

0

400

800

1200

1600

2000

2400

0 2 4 6 8 10 12 14

Air Voids, %

Seismic Modulus, ksi

Target: 1523 Ksi

Uncertainty Boundary ± 4%

Best Fit

Figure 5.1 – Variation in Seismic Modulus with Air Voids from Laboratory Testing

The 95% confidence interval around the best fit line is also shown in Figure 5.1 assuming

that the lab prepared specimens are very similar in terms of gradation, asphalt content,

asphalt viscosity. The uncertainty is, therefore, primarily due to the uncertainty in the

measurements with the ultrasonic device. Tandon et al. ( 2006) determined the estimated

uncertainty in the measurements as 2%.

Step 3: Characterizing the Variation in Modulus with Temperature

The specimen prepared in Step 2 at the target placement air voids was then tested with the

ultrasonic device at a sequence of temperatures ranging from 70oF to about 160oF. Since the

lab tests are nondestructive, the same specimen can be tested repeatedly to minimize the

variability in the results due to sample preparation. The variation in modulus with tempera-ture

for that specimen is shown in Figure 5.2. Once the modulus- temperature relationship is

established for a given mix, it can be utilized in all project using similar mixes. The slope of

the best- fit relationship in Figure 5.2 can be used to adjust the modulus at the field tempera-ture

to a uniform design temperature ( 75oF in this study).

In this research project, a second specimen prepared at the design air voids was also tested to

determine how the change in air voids would impact the slope of modulus- temperature

relationship. That information is also shown in Figure 5.2. The slope for the specimen pre-pared

at the design air voids is 10.1 ksi/ oF and for the specimen at the placement air voids is

9.6 ksi/ oF. The rate of change in modulus with temperature is fairly similar at both air voids.

However, at a given temperature, the modulus at the design air voids is naturally greater than

the placement air voids. This affirms that testing one specimen at one air voids is reasonable

for practical use. Once this relationship is developed for one mix, it can be utilized for all

mixes placed with the same source of aggregates and binder type in the same region. As

such, this step is not necessary for all projects.

29

y = - 10.10x + 2460

R 2 = 0.98

y = - 9.63x + 2208

R 2 = 0.99

0

400

800

1200

1600

2000

50 70 90 110 130 150 170

Temperature, F

Lab Seismic Modulus, ksi

Specimen at Design Air Voids

Specimen at Placement Air Voids

Figure 5.2 – Variations in Seismic Modulus with Temperature at

Design and Placement Air Voids

Step 4: Determining Modulus of Material for Structural Design

The most rigorous way of calculating the design modulus is to develop a master curve

using dynamic modulus tests based on the recommendations of Witczak et al. ( 2002).

Master curves from two specimens prepared at the design and placement air voids are

shown in Figure 5.3. The data from the ultrasonic device and from the dynamic modulus

tests are shown separately. The results from the two devices integrate quite well. As

shown in Figure 5.3, the moduli at 10 Hz and 10 kHz are 3152 ksi and 1502 ksi,

respectively. The ratio of moduli at 10 Hz and 10 KHz from the master curve developed

for the placement air voids can be used to adjust the field seismic moduli to the

equivalent design modulus. In this case, this ratio is 2.1: 1.

100

1000

10000

0.1 1 10 100 1000 10000 100000

Reduced Frequency, Hz Dynamic Modulus, ksi

Dynamic Placement AV

Seismic Placement AV

Dynamic Design AV

Seismic Design AV

Placement AV

Alpha = 2.14

Beta =- 0.87

Gamma = 0.59

Delta = 1.44

Design AV

Alpha = 2.24

Beta =- 1.22

Gamma = 0.51

Delta = 1.4

1502 ksi

3152 ksi

Figure 5.3 – Master Curve for Estimating Design Modulus

30

If ADOT does not desire to carry out the dynamic modulus tests, simplified relationships

developed by Witczak and colleagues can be used. An example of such a relationship is

given in Chapter 2.

Step 5: Field Quality Tests

About 45 points divided in 15 stations were tested on the pavement as depicted in Figure

5.4. Of these points, fifteen were located on the left wheel path, fifteen on the right

wheel path and fifteen along the midlane of the road. The spacing between two

consecutive points was usually 100 ft. Each point was tested with the PSPA to obtain the

in place seismic modulus.

Midlane

Right Wheelpath

Left Wheelpath

6 ft

3 ft

9 ft

12 ft

Figure 5.4 – Typical Marking of Sites

Alternatively, the location of the points can be determined based on the principals of

random sampling as commonly done for determining the core locations.

The contour maps of the variation in field equivalent design modulus are shown in

Figures 5.5. Some variation in the modulus along the mat can be observed. The red

areas correspond to lower moduli. In that sense, the areas about Stations 6462 and 6486

are less stiff than the rest of the areas tested.

The modulus control charts associated with each wheel path are shown in Figure 5.6.

Also shown in the figure are the target moduli from laboratory testing corresponding to

placement air voids of 8%, 10%, and 12% obtained from Figure 5.1 and converted to the

equivalent design moduli using Step 4. In this case, the representative design modulus

for target air voids of 8% is about 725 ksi ( obtained from the seismic modulus of 1523

ksi indicated in Step 2). The moduli usually fall below the target lines. This pattern is

normally observed because the compaction efforts associated with laboratory specimens

and field mats are different. Laboratory specimens usually yield moduli that are greater

than field specimens. This is another reason to rely on the in place modulus rather than

lab- prepared specimens.

31

Design Modulus, ksi

Figure 5.5 – Contour Plots of Variations in Design Modulus with PSPA along Site

32

a) LWP

0

100

200

300

400

500

600

700

800

6542 6534 6526 6518 6510 6502 6494 6486 6478 6470 6462

Station Number

Equivalent Design

Modulus, ksi

b) Centerline

0

100

200

300

400

500

600

700

800

6542 6534 6526 6518 6510 6502 6494 6486 6478 6470 6462

Station Number

Equivalent Design

Modulus, ksi

PSPA 8% AV 10% AV 12% AV

c) RWP

0

100

200

300

400

500

600

700

800

6542 6534 6526 6518 6510 6502 6494 6486 6478 6470 6462

Station Number

Equivalent Design

Modulus, ksi

Figure 5.6 – Modulus Control Charts from Site

33

Finally, the cumulative distribution of design moduli along the site is included in Figure

5.7. On average ( corresponding to a cumulative distribution of 50%) the representative

modulus for this section of the road at the time of testing is about 595 ksi. Since the

target lab modulus is 725 ksi, the field modulus on the average is about 82% of the target

modulus for this project. This means that, the compaction effort obtained from the

Superpave gyratory compactor does not fully imitate the compaction effort provided by

the construction equipment used in the field. If the current acceptance criteria based on

density seems reasonable to ADOT, an allowance has to be given to the contractor for

this lack of compatibility between the lab and field methods. For this specific example,

this allowance is about 82%. A global allowance will be proposed in Chapter 6 based on

all sites tested in Arizona.

0%

25%

50%

75%

100%

450 500 550 600 650 700 750 800

Modulus, ksi

Cumulative Distribution

95% 525 595 ksi

ksi

Figure 5.7 – Distribution of Equivalent Design Moduli along Site

Validation of Results

To validate the results, ten additional points were tested with the PSPA and then the

pavement was cored for laboratory tests. The core locations were selected at random by

ADOT personnel as a part of their routine quality acceptance activity. At each location,

an additional core was retrieved and shipped to UTEP.

The equivalent design moduli obtained with the PSPA in the field are compared with the

corresponding lab moduli obtained from the ultrasonic testing in Figure 5.8 and Table

5.2. The results are typically within 10% of one another, with a maximum difference of

14% indicating close correspondence between the field PSPA results and lab seismic tests

on cores.

34

Figure 5.8 – Comparison of Moduli from PSPA and Lab Tests on Cores

Extracted from Same Locations

Table 5.2 – Comparison of Moduli from PSPA and Lab Tests on Cores

Extracted from Same Locations

Core Modulus, ksi

Number PSPA Lab Test on Cores Difference*

1 711 783 9.2%

2 635 704 9.8%

3 675 695 2.9%

4 671 742 9.6%

5 823 724 13.7%

6 693 690 0.4%

7 628 628 0.0%

8 710 620 14.4%

9 667 651 2.6%

10 639 605 5.6%

* Difference = ABS ( PSPA Modulus- Lab Modulus)/ Lab Modulus

The air voids of the ten cores tested by UTEP were measured using a Corelock device.

The air voids obtained from this activity are compared with those reported by ADOT in

Table 5.3. For this site, the air voids are fairly close in most cases with an average

difference of 0.7% and a maximum difference of about 1.5% in one occasion. The

differences can be mainly attributed to the different methods used by the two groups to

obtain the air voids.

0

100

200

300

400

500

600

700

800

900

1 2 3 4 5 6 7 8 9 10

Core Number

Modulus, ksi

PSPA Lab Tests

35

Table 5.3 – Comparison of Air Voids for Cores Extracted at the Site

Core Number Air Voids, %

ADOT UTEP Difference*

1 6.6 6.2 + 0.4

2 8.4 6.9 + 1.5

3 7.5 7.0 + 0.5

4 6.9 6.9 + 0.0

5 7.7 7.8 - 0.1

6 6.4 7.4 - 1.0

7 7.9 8.8 - 0.9

8 8.5 9.0 - 0.5

9 8.3 7.4 + 0.9

10 7.4 8.5 - 1.1

* Difference = ADOT Air voids – UTEP Air voids

The seismic moduli from the cores are compared with their corresponding in- place air

voids in Figure 5.9. The two parameters correlate reasonably well as judged with a R2 of

0.75. However, the modulus air voids results from lab- prepared specimens ( see Figure

5.1) yield a higher R2 of 0.96. This pattern is anticipated because of differences in

compaction patterns and possible variability in the mix constituents ( asphalt content,

aggregate gradation, etc.).

y = - 54.69x + 1098.74

R 2 = 0.76

0

200

400

600

800

1000

5 6 7 8 9 10

Air Voids, %

Lab Seismic Modulus, ksi

Uncertainty Boundary ± 12%

Best Fit

Figure 5.9 – Variation in Design Modulus with Air Voids at Core Locations

36

A study was carried out to verify the hypothesis that the change in the mix constituents

may contribute to the variability in the moduli, and as a result, a weaker correlation

between field modulus and air voids. Typical coefficients of variation ( cov) in the

gradation, asphalt content and asphalt viscosity from this example site are shown in Table

5.4. A Monte Carlo simulation was carried out to simulate 1500 cases where these

constituents were randomly varied within their corresponding COV. The set of values

obtained for all the parameters was then entered into the 1995 Witczak equation ( see

Table 2.1) to estimate the modulus. A frequency of 10 kHz and the average air voids

from the site were used in the equation. The distribution of modulus from that equation

for the 1500 cases is shown in Figure 5.10. The axis is normalized with respect to the

modulus obtained using the average values of the constituents. The modulus distribution

resembles a normal distribution with a COV of 6%. With a confidence level of 95%, the

moduli can vary by 12% just due to the variation in constituents along the project.

Table 5.4 – Variation in Constituents of Mix from Field Samples

Rotational

Viscosity

( G*/ Sinδ),

KPa

Asphalt

Content, %

Percent

Retained on

¾ in. Sieve

Percent

Retained on

3/ 8 in. Sieve

Percent

Retained on

No. 4 Sieve

Percent

Passing No.

200 Sieve

Mean COV Mean COV Mean COV Mean COV Mean COV

0.84

4.85 1.6% 2.5 51.6% 23.0 5.0% 39.5 2.5% 4.38 2.2%

0%

20%

40%

60%

80%

100%

0.70 0.80 0.90 1.00 1.10 1.20 1.30

Modulus Ratio

Cumulative Distribution

0%

1%

2%

3%

4%

5%

Distribution

Figure 5.10 – Distribution of Moduli due to Change in Gradation and Asphalt

Content of Mixes during Paving

37

The uncertainty bounds based on this analysis are shown in Figure 5.9. Since all data

points fall within the uncertainty bounds, the changes in constituents describe the lower

R2 achieved from the field cores. In this exercise, the uncertainty due to ultrasonic tests

was ignored since it is rather small as compared to the uncertainties due to changes in the

mix constituents.

In addition, four of the cores were first subjected to the ignition oven to obtain the asphalt

content, and the remaining aggregates were sieved for gradation. The results are

summarized in Table 5.5. The gradations and AC contents seem to be reasonably close

to the specifications.

Finally, to ensure appropriate gradation of the materials at the site, loose materials from

two locations sampled during paving were subjected to ignition oven and gradation tests.

The results from this exercise are summarized in Table 5.6. The gradations and AC

contents obtained by ADOT and UTEP are quite close and within the specifications.

Table 5.5 – Gradation Results for Selected Cores from the Site

Sieve # % Passing

Core 1 Core 2 Core 3 Core 4 Target

3/ 8" 82 76 75 77 77

8 48 39 43 43 46

40 17 15 16 16 16

200 3.5 2.8 2.9 2.4 4.5

Asphalt Content 4.6% 4.6% 4.9% 5.0% 4.6%

Table 5.6 – Gradation Results for Loose Materials Sampled at Site

% Passing

Sieve # Location 1 Location 2

UTEP ADOT UTEP ADOT Target

3/ 8" 78 78 80 76 77

8 42 45 41 44 46

40 16 17 16 17 16

200 2.4 4.5 2.4 4.3 4.5

AC Content 5.1% 4.8% 4.8% 4.9% 4.6%

38

39

VI. PRESENTATION OF RESULTS

DESCRIPTION OF SITES INVESTIGATED

Ten projects throughout the State of Arizona were subjected to the proposed quality

management process. The locations of the sites are shown in Figure 6.1. Tests were

carried out between August and December, 2005 on the layers placed the day before.

Results from the field and lab tests are reported herein.

2

Figure 6.1 – Location of Sites Tested

DESCRIPTION OF SITES

Site 1. Buckeye SR85 ( H595506C) was located on SR 85 near Buckeye ( about 40 miles

southwest of Phoenix) on the northbound section of two new lanes between MP 141.71

and 147.74 ( Lot # 16, Station Numbers 6540 to 6640). The top layer was about 2.5 in.

thick. Tests were carried out on July 28, 2005.

Site 2. Show Low SR61 ( H525001C) was located on SR 61 near Show Low ( about 120

miles northeast of Phoenix) on the westbound section of the two existing lanes between

Station Numbers 640 to 719 of Lot # 14. The top layer was about 2.5 in. thick. Tests

were carried out on August 2, 2005.

40

Site 3. Holbrook I- 40 ( H613901C) was located on Interstate 40 about 40 miles east of

Holbrook on the eastbound section of the two existing lanes between Station Numbers

2403 to 2418 of Lot # 6. Tests were carried out on September 7, 2005. The top layer at

this site was about 5 in. thick.

Site 4. Burro Creek US93 ( H549401C) was located on US 93 about 15 miles south of

Wikieup near the intersection with Burro Creek on the westbound section of the two

existing lanes between Station Numbers 2699 to 2684 of Lot # 53. Tests were carried out

on September 9, 2005. The top layer at this site was about 3 in. thick.

Site 5. Cordes JCT I- 17 ( H584501C) was located on Interstate 17 in the vicinity of

Cordes Junction ( about 50 miles north of Phoenix) on the northbound section of the two

existing lanes between Station Numbers 65+ 00 to 80+ 00 of Lot # 3. Tests were carried

out on September 8, 2005. The top layer at this site was about 5 in. thick.

Site 6. Roosevelt SR188 ( H407601C) was located on SR 188 in the vicinity of Roosevelt

( about 10 miles northwest of Globe) on the southbound section of two new lanes between

Station Numbers 722+ 25 and 650+ 63 of Lot # 22. Tests were carried out on August 4,

2005. The top layer at this site was about 2 in. thick.

Site 7. Safford US191 ( H503706C) was located on US 191 in the vicinity of Safford

( about 20 miles south of Safford) on the northbound section of two new lanes between

Station Numbers 573+ 00 to 588+ 00 of Lot # 10. Tests were carried out on September 1,

2005. The top layer at this site was about 2.5 in. thick.

Site 8. Holbrook I- 40B ( H613901C) was located on Interstate 40 in the vicinity of

Holbrook ( about 40 miles east of Holbrook) on the westbound section of the two existing

lanes between Station Numbers 2520 to 2505 of Lot # 28. Tests were carried out on

November 9, 2005. The top layer at this site was about 2.5 in. thick.

Site 9. Payson SR260 ( H615101C) was located on SR 260 in the vicinity of Payson

( about 15 miles east of Payson) on the southbound section of two new lanes between

Station Numbers 1519 to 1561 of Lot # 8. Tests were carried out on November 10, 2005.

The top layer at this site was about 2.5 in. thick.

Site 10. Tucson I- 10 ( H458201C) was located on Interstate 10 about 20 miles north of

Tucson on the westbound section of the two existing lanes between Station Numbers

4580 to 4565 of Lot # 69. Tests were carried out on December 14, 2005. The top layer

at this site was about 4 in. thick.

41

GENERAL RESULTS

The proposed quality management process described in Chapter 4 was applied to

all ten sites.

Step 1: Selecting Suitable Materials and Mix for Each Project

Table 6.1 contains the JMF for each of the sites as provided by ADOT. Four mixes were

developed based on Item 416 ( Conventional Volumetric Mix) and six mixes based on

Item 417 ( SHRP Volumetric Mix) ( ADOT 2000). The nominal aggregate size for all

mixes was 0.75 in. Four different types of binders were used. The target asphalt contents

of the mixes varied between 4.6% and 5.7%. The design air voids varied between 4.5%

and 6.1% while the target field air voids varied between 7% and 8%.

Step 2: Determining a Target Modulus for Each Mix

Based on the mix design for each site, several specimens were prepared in the lab with

different air voids using materials collected from the sites. The variations in seismic

modulus with air voids for a nominal temperature of 75° F were first determined for each

mix. The detailed results are included in Appendix C. As demonstrated in Figure 5.1

and Appendix C, a linear relationship can be used to describe the variation in seismic

modulus with air voids.

The slopes and intercepts of the seismic modulus- air voids relationships for all sites are

summarized in Table 6.2. The two parameters are well correlated, as judged with an

average R2 value of 0.95 from the regression equations.

The slope, which corresponds to the sensitivity of the modulus to change in air voids, is

influenced by a number of parameters such as the type and amount of binder, the

aggregate gradation and type. For the ten sites, the slope varied from 110 to 46 ksi per

percent air voids. The flatter the slope is, the smaller the change in modulus with air

voids will be. The global average of the slope for the ten sites in Arizona is 75 ksi per

percent air voids, with a coefficient of variation of about 27%.

The intercepts of the lines in Table 6.2 correspond to the modulus at an air void content

of zero. These values are basically used to estimate the moduli at any air void content.

The target moduli at placement air voids are summarized in Table 6.2 as well. The target

moduli varied from 1100 ksi to 1900 ksi. On average, the target modulus is about 1730

ksi with a coefficient of variation of about 16%. These target moduli can be utilized as a

guideline for the future projects with similar JMFs.

Table 6.1 – Job Mix Formula from All Sites

* ADOT. Standard Specifications for Road and Bridge Construction. 2000

* * Rounded to the nearest integer

Site Project

Number

Design

Type* AC Type Type of

Aggregate

Nominal

Aggregate

Size

Target

Asphalt

Content

Design

Air

Voids

In-place

Air

Voids

Max.

Theoretical

Specific

Gravity

Compaction

Temp

Buckeye H595506C 416 PG 76- 16 Granite 0.75 in. 4.6 % 6.0 % 8%** 2.442 310 º F

Show Low H525001C 417 PG 64- 22 Alluvial 0.75 in. 5.1 % 4.6 % 7% 2.410 295 º F

Holbrook H613901C 417 PG 64- 22 Basalt 0.75 in. 4.9 % 4.5 % 7% 2.564 298 º F

Burro

Creek H549401C 417 PG 76- 16 Alluvial 0.75 in. 4.6 % 5.1 % 7% 2.484 310 º F

Cordes JCT H584501C 416 PG 70- 10 Basalt 0.75 in. 5.7 % 5.8 % 8% 2.500 300 º F

Roosevelt H407601C 417 PG 70- 10 Alluvial 0.50 in. 4.7 % 5.0 % 7% 2.492 308 º F

Safford H503706C 416 PG 64- 22 Alluvial 0.75 in. 5.6 % 5.6 % 8% 2.373 295 º F

Holbrook

( B) H613901C 417 PG 64- 22 Basalt 0.75 in. 4.9 % 5.1 % 7% 2.566 298 º F

Payson H615101C 417 PG 64- 28 Alluvial 0.75 in. 5.4 % 4.9 % 7% 2.426 290 º F

Tucson H458201C 416 PG 70- 10 Alluvial 0.75 in. 5.2 % 6.1 % 8% 2.413 306 º F

42

43

Table 6.2 – Variation in Seismic Modulus with Air Voids for Lab Specimens

Site Slope,

ksi/% AV Intercept, ksi Modulus at

Placement AV, ksi R2

Buckeye - 75.3 2125 1523 0.96

Show Low - 69.5 2157 1670 0.98

Holbrook - 93.6 2301 1646 0.97

Burro Creek - 46.0 2010 1687 0.95

Cordes JCT - 92.6 2571 1830 0.96

Roosevelt - 68.9 2296 1813 0.95

Safford - 46.1 1511 1143 0.91

Holbrook ( B) - 79.3 2540 1985 0.91

Payson - 69.3 2272 1787 0.91

Tucson - 109.6 2904 2027 0.97

Average - 75.0 2269 1732 0.95

Standard

Deviation 20.0 372 280 --

Coeff. of

Variation 27% 16% 16% --

44

Step 3: Characterizing the Variation in Modulus with Temperature

The two specimens prepared at the design air voids and at the target placement air voids

were then tested at a sequence of temperatures ranging from 70° F to about 160° F to ob-tain

the variations in modulus with temperature. The results are included in Appendix D

and are summarized in Table 6.3. Once again, a linear relationship seems to describe

such relationships well. The average R2 value is about 0.97.

The slope of the best- fit relationship can be used to adjust the modulus measured at the

field temperature to a uniform design temperature ( 75° F in this study). The modulus-temperature

slope varies between 7 ksi/° F and 13.5 ksi/° F. For most sites, the average

value of 10 ksi/° F seems to be a reasonable value for Arizona.

The intercept in Table 6.3, which corresponds to the modulus at 0° F, is primarily used

along with the slope to estimate the modulus at any given temperature. The moduli at the

standard temperature of 75° F are also reported in Table 6.3. Naturally, these values are

very similar to the target moduli reported in Table 6.2.

Table 6.3 – Variation in Seismic Modulus with Temperature for Lab Specimens at

Placement Air Voids

Site Slope, ksi/ oF Intercept

( Modulus at 0° F), ksi

Modulus at

75° F, ksi R2

Buckeye - 9.6 2208 1485 0.99

Show Low - 10.9 2420 1601 0.98

Holbrook - 11.1 2507 1675 0.98

Burro Creek - 8.6 2360 1714 0.99

Cordes JCT - 9.7 2565 1835 0.97

Roosevelt - 9.1 2599 1915 0.99

Safford - 7.0 1658 1132 0.98

Holbrook ( B) - 11.7 2986 2108 0.88

Payson - 13.5 2885 1869 0.98

Tucson - 10.4 2764 1981 0.96

Average - 10.2 2495 1732 0.97

Standard

Deviation 1.8 378 280 --

Coeff. of

Variation 18% 15% 16% --

45

The modulus- temperature slopes for the specimens prepared at the design air voids are

compared with the corresponding slopes for specimens prepared at the placement air

voids in Figure 6.2. The two slopes are well correlated. This indicates that the rate of

change in modulus with temperature is fairly similar for the two air voids. Practically

speaking, it is sufficient to develop the modulus- temperature relationship only at the in-place

air voids.

Figure 6.2 – Variations in Modulus with Temperature ( Slopes) for Lab Specimens at

Design and In- place Air Voids

y = 1.00x

R2 = 0.91

5

7

9

11

13

15

5 7 9 11 13 15

Slope ( Design AV)

Slope ( In- place AV)

Buckeye

Show Low

Holbrook

Burro Creek

Cordes JCT

Roosevelt

Safford

Holbrook B

Payson

Tucson

46

Step 4: Determining Modulus of Each Mix for Structural Design

The master curves generated for each site at design and placement air voids are shown in

Appendix E. The data from the seismic and the dynamic modulus tests integrate quite

well in all cases as shown in Figure 5.3 and in Appendix E. Master curves from the ten

specimens prepared at the design air voids for all sites are shown in Figure 6.3. Figure

6.4 shows master curves for all sites except the placement air voids. In both cases, the

master curves vary significantly for different mixes. The material from Payson site

demonstrates the lowest modulus, whereas the materials from Tucson, Burro Creek and

Roosevelt are the stiffest.

100

1000

10000

0.1 1 10 100 1000 10000 100000

Reduced Frequency, Hz

Dynamic Modulus, ksi

Buckeye Show Low

Holbrook Burro Creek

Cordes JCT Roosevelt

Safford Holbrook ( B)

Payson Tucson

Figure 6.3 – Master Curves for Specimens Prepared at Design Air Voids

100

1000

10000

0.1 1 10 100 1000 10000 100000

Reduced Frequency, Hz

Dynamic Modulus, ksi

Buckeye Show Low

Holbrook Burro Creek

Cordes JCT Roosevelt

Safford Holbrook ( B)

Payson Tucson

Figure 6.4 – Master Curves for Specimens Prepared at Placement Air Voids

47

The parameters to generate the master curves are shown on Table 6.4. These values can

be used for future projects that utilize the mixes with similar JMF’s. Once the master

curve is established, the design modulus can be readily determined from the design

vehicular speed and the design temperature as recommended in the new Mechanistic-

Empirical Design Guide.

Table 6.4 – Master Curve Parameters for All Sites

Master Curve Parameters*

Site Design AV Placement AV

α β γ δ α β γ δ

Buckeye 2.24 - 1.22 0.51 1.40 2.14 - 0.87 0.59 1.44

Show Low 1.76 - 0.001 0.75 1.85 1.76 0.10 0.80 1.77

Holbrook 1.64 0.13 0.78 1.98 1.76 0.10 0.80 1.77

Burro Creek 1.44 - 0.65 0.74 2.15 1.43 - 0.45 0.74 2.14

Cordes JCT 1.53 - 0.45 0.86 2.02 1.53 - 0.30 0.80 1.97

Roosevelt 1.89 - 1.00 0.80 1.74 1.94 - 1.00 0.80 1.64

Safford 1.83 - 0.38 0.56 1.75 1.76 - 0.16 0.63 1.75

Holbrook ( B) 1.94 - 0.20 0.56 1.74 2.05 - 0.23 0.54 1.59

Payson 1.92 0.10 0.66 1.69 1.82 0.40 0.71 1.74

Tucson 1.56 - 0.85 0.94 1.98 1.66 - 0.79 0.90 1.85

*

e t r

E 1 log

log( *) + + ×

= + β γ

α

δ

Based on the master curves shown in Figure 6.3, the representative moduli that should be

used in the structural design of the materials from different sites are shown in Table 6.5.

As expected, the mixes with the stiffer binders yield higher moduli.

The adjustment factors from the seismic modulus to design modulus ( ratios of the moduli

at 10 kHz and 10 Hz) are also shown in Table 6.5. These adjustment factors varied from

1.73 to 3.22. The default adjustment factor of 3.2 recommended by Auoad et al. ( 2003)

seems to correspond to the upper limits of the values obtained for the ADOT mixtures.

The adjustment factors reflected in Table 6.5 can be used by ADOT for similar mixes.

48

For almost all mixes with PG 64 binders, the default value of 3.2 seems to be reasonable

in the absence of actual dynamic modulus tests. For the mixes with the PG 70 and higher

binders, the adjustment factor seems to be closer to 1.95.

Table 6.5 – Design Modulus and Modulus Ratios for All Sites

Site Modulus at Design AV, ksi

( Frequency 10 Hz)

Moduli Ratios at Placement AV

( Frequencies: 10KHz/ 10Hz)

Buckeye 1347 2.10

Show Low 537 3.22

Holbrook 558 3.22

Burro Creek 1247 1.94

Cordes JCT 900 2.17

Roosevelt 1323 1.76

Safford 686 2.73

Holbrook ( B) 640 3.00

Payson 400 4.21

Tucson 1183 1.73

Step 5: Field Quality Tests

The average variations in the gradations, binder contents and air void contents for the ten

sites are summarized in Table 6.6. The individual results are summarized in Appendix F.

The average gradations measured in the field are quite similar to the specified values for

nine sites, indicating a well- executed process control. The gradation from the Burro

Creek site seems to deviate with the specified gradation.

The variations in as- built binder contents at different sites are summarized in Figure 6.5.

The target binder contents are close to those measured during construction.

The as- built air voids are compared with the target values in Figure 6.6. The as- built air

voids at the Cordes Junction site are somewhat higher than the target value, and for the

Tucson site are somewhat less than target.

The contour maps of the variations in field seismic modulus with the PSPA converted to

equivalent design modulus are shown in Appendix G for each site. Some variation in the

modulus along the mats can be observed, with red areas corresponding to lower moduli.

Also shown in that appendix are the normalized moduli ( the ratio of the as- built measured

modulus with PSPA and the target modulus) to demonstrate how much the measured

moduli vary from the target values obtained in the lab.

The modulus control charts associated with each wheel path and the midlane are included

in Appendix H. The target moduli from laboratory testing corresponding to placement air

49

voids, 2% above placement air voids and 4% above placement air voids are depicted for

each site. For all cases, the moduli usually fall below the target lines.

Table 6.6 – Average Gradations, AC Content and Air Voids at Sites

ADOT Sieve # Results (% Passing)

Site

3/ 8” 8 40/ 30 200

AC

Content

(%)

Air

Voids

(%)

Buckeye 77 ( 77) 45 ( 46) 17 ( 16) 4.4 ( 4.5) 4.9 ( 4.6) 7.6 ( 8)

Show Low 77 ( 75) 46 ( 41) 22 ( 24) 5.2 ( 5.0) 5.4 ( 5.1) 7.0 ( 7)

Holbrook 71 ( 70) 43 ( 47) 25 ( 26) 5.0 ( 5.0) 4.8 ( 4.9) 6.3 ( 7)

Burro Creek 76 ( 62) 36 ( 29) 16 ( 14) 6.1 ( 5.0) 4.9 ( 4.6) 6.4 ( 7)

Cordes JCT 75 ( 77) 38 ( 42) 10 ( 11) 4.9 ( 5.1) 5.6 ( 5.7) 9.7 ( 8)

Roosevelt 72 ( 74) 32 ( 34) 19 ( 18) 4.7 ( 3.8) 5.1 ( 4.7) 6.6 ( 7)

Safford 72 ( 71) 40 ( 40) 13 ( 14) 3.9 ( 4.4) 5.6 ( 5.7) 7.9 ( 8)

Holbrook ( B) 73 ( 68) 32 ( 33) 17 ( 17) 4.3 ( 3.8) 5.1 ( 4.9) 6.7 ( 7)

Payson 71 ( 77) 40 ( 45) 21 ( 24) 4.7 ( 5.1) 5.2 ( 5.4) 6.5 ( 7)

Tucson 71 ( 68) 46 ( 43) 17 ( 15) 4.2 ( 4.1) 5.4 ( 5.2) 6.7 ( 8)

Numbers in parentheses correspond to the target values

Figure 6.5 – Comparisons of Target and As- Built Binder Contents at Arizona Sites

0

1

2

3

4

5

6

Buckeye

Show Low

Holbrook

Burro Creek

Cordes JCT

Roosevelt

Safford

Holbrook ( B)

Payson

Tucson

Site

Binder Content, %

Site Average

Target

50

Figure 6.6 – Comparisons of Target and As- Built Air Voids at Arizona Sites

The cumulative distribution of moduli along each site is included in Appendix I. The

results are summarized in Figure 6.7. The more vertical the lines are, the more uniform

the moduli of the sites would be. In most sites, the distribution of the moduli is

reasonably uniform.

The moduli associated with a cumulative distribution of 50% correspond to the average

moduli. The average moduli at the ten sites are compared with the target values in Table

6.7. The average moduli are less than the target moduli for all but one site.

The ratio of the as- built and target moduli are also reported in Table 6.7. This pattern is

normally observed because the compaction efforts associated with laboratory specimens

and field mats are different. Laboratory specimens usually yield moduli that are greater

than field specimens. These ratios vary from a low of about 0.7 to a high of 1.06.

The main two reasons for the field moduli being below the target lab moduli are less than

desirable construction practices, or the fact that the Superpave gyratory compactor yields

lab specimens that are stiffer than those achievable in the field. The contractor should be

held accountable for the quality of construction. However, allowance should be provided

to the contractor for the inconsistency between the lab and field compaction. To assist

ADOT in setting target moduli that provide allowance for the differences between lab and

field compaction methods, the ratios of the as- built and target moduli from all sites are

0

2

4

6

8

10

12

Buckeye

Show Low

Holbrook

Burro Creek

Cordes JCT

Roosevelt

Safford

Holbrook ( B)

Payson

Tucson Site

Air Voids, %

Site Average

Target

51

0%

20%

40%

60%

80%

100%

0 500 1000 1500

PSPA Modulus, ksi

Cumulative Distribution

Buckeye

Show Low

Holbrook

Burro Creek

Cordes JCT

Roosevelt

Safford

Holbrook B

Tucson

Figure 6.7 – Cumulative Distributions of Moduli

Table 6.7 – Comparison of As- Built and Target Moduli

Pay Factor ($/ ton)

Site

Average

Modulus,

ksi

Target

Modulus,

ksi

Ratio

( Avg./ Target) Mix Compaction

Buckeye 595 725 0.82 - 0.75 - 0.25

Show Low 358 518 0.69 1.00 1.00

Holbrook 441 511 0.86 0.25 1.00

Burro Creek 831 870 0.96 - 3.00 1.00

Cordes JCT 631 842 0.75 0.25 - 1.30

Roosevelt 869 1028 0.85 - 3.00 1.00

Safford 375 418 0.90 1.00 0.50

Holbrook ( B) 700 662 1.06 1.00 1.00

Payson N/ A* 425 N/ A* - 2.00 0.00

Tucson 1028 1171 0.88 1.00 0.50

* Results are not available because the site was opened to traffic before field testing

52

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4

Ratio of As- Built and Target Modulus

Cumulative Distribution

0.85

Figure 6.8 – Cumulative Distribution of Ratios of As- Built and

Target Moduli from all Arizona Tests

combined in Figure 6.8 for all data points. At a cumulative distribution of 50%, the ratio of

0.85 is obtained. This means that a reasonably achievable level of modulus should be set at

85% of the target modulus obtained from lab tests on specimens prepared at target air voids.

With a confidence level of 90%, a value of 75% should be used in the structural design.

The acceptance tests and associated bonuses and penalties associated with the lot for each

site tested in this study are included in Appendix J. ADOT imposes two types of pay

adjustments, one related to the mix quality and the other related to the construction

( compaction) quality.

The mix- related and construction- related pay adjustments are included in Table 6.7 and

Appendix K. Since all specimens tested by UTEP were prepared from mixes collected at the

site, it is not possible to quantify the impact of the mix- related pay adjustments on the quality

of the mix. In an actual project, it would be desirable for ADOT to prepare specimens for

Step 2 with the original job mix formula ( as opposed to specimens prepared from materials

retrieved from the site) to obtain the target modulus for each site. In that manner, the moduli

measured in the field with the PSPA would reflect the impact of both the mix- related and

construction- related parameters.

As reflected in Table 6.7, two projects incurred construction- related penalties under the

current ADOT specifications ( Buckeye and Cordes JCT). Under the seismic modulus

criterion using 85% of target modulus from Step 2, these projects are also considered sub-standard.

Under the seismic criterion a third project ( Show Low) is also sub- standard, even

53

though according to the current ADOT specification that site is eligible for a bonus. The

reason for this pattern is not known at this time.

Validation

To validate the results of the PSPA, ten additional points were tested and then cored for

laboratory tests at each sites. Detailed results from this activity are included in Appendix

J. The moduli obtained with the PSPA in the field are compared with the moduli

obtained with a lab ultrasonic device on the cores from all sites in Figure 6.9. The PSPA

moduli and lab seismic moduli are reasonably close, since the results are clustered close

to the line of equality. The largest difference at one individual point was 18%, with

average differences of about 9%.

Figure 6.9 – Comparison of Moduli from PSPA and Lab Tests on Cores

The variations in the measured seismic modulus with air voids are presented in Appendix

L and summarized in Table 6.8. As for the lab- prepared specimens, a linear relationship

was established between the modulus and air voids. As reflected in Table 6.8, the R2

values of the best- fit lines are typically around 0.8 unlike for the lab- prepared specimens

where the R2 va