Cont inuing Inves tigatio n of Polishin g and · 2009-11-03 · Cont Fri inuing ction C Inves harac Aggre tigatio terist gate n of P ics of in Ohio Rober Ohio Dep Office of R U.S

ContFri

tinuingction C

g InvesCharacAggre

stigatiocteristegate

on of Pics of in Ohio

Rober

Ohio DepOffice of R

U.S. DepFeder

S

PolishinLimeso

rt Y. Liang

partment ofesearch an

partment ofral Highway

State Job N

FHWS

ng andstone

g, Ph.D.,

fof Transporta

nd Developm

andf Transportay Administra

Number: 134

Final ReWA/OH-200September 2

d

P.E.

or the ation ment

d the ation ation

4219

eport 09/10 2009

ii

iii

Continuing Investigation of Polishing and Friction Characteristics of Limestone

Aggregate in Ohio

Robert Y. Liang, Ph. D., P.E.

431 ASEC, Civil Engineering Department University of AKRON

Akron, OH, 44325

Credit Reference: Prepared in cooperation with the Ohio Department of Transportation and the U.S. Department of Transportation, Federal Highway Administration. Disclaimer Statement: The contents of this report reflect the views of the authors who are responsible for the facts and accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the Ohio Department of Transportation or the Federal Highway Administration .This report does not constitute a standard, specification or regulation.

September 2009

iv

ABSTRACT

Due to increased focus on maintaining highway operating safety and reducing wet weather

accidents, highway agencies have adopted a routing practice to monitor pavement surface

friction values. Skid Number (SN) is a measure of pavement surface friction determined

by LWST (Locked Wheel Skid Trailer). Once the SN falls below certain threshold criteria,

highway agencies would start a pavement resurfacing program to ensure that adequate

friction is maintained. The practice of monitoring and remedying the low skid resistance

pavement sections is important; however, it is a passive approach. A more proactive

approach would be to test the hot mix asphalt in the laboratory during its initial mix design

stage to ensure that aggregate combinations used in the mix design would provide

adequate friction over the expected life span of the pavement.

To achieve the screening task for polishing and friction behavior of the HMA during its

mix design stage, a laboratory-scale accelerated polishing device that can mimic the actual

abrasion and polishing behavior between the vehicle rubber tire and the HMA surface has

been developed. The developed polishing device possesses some practical characteristics.

These include the versatility of testing HMA specimens that can be prepared with the

roller compaction equipment or the gyratory Superpave compaction equipment, the test

duration is reasonably short, the test procedure including test specimen preparation and

v

friction measurements is relatively simple and repetitive, the developed test procedure

requires minimum labor efforts, and finally, the test results can provide a realistic

indication of the polishing and friction behavior of the hot mix asphalt specimens.

The validation of the developed accelerated polishing device included favorable

comparisons between the HMA polishing behavior from the new test device with the

aggregate polishing behavior from the British Polishing Wheel tests. Furthermore, a total

of eight pavement sections in service were identified for long–term friction and texture

measurements, which provide important data correlations between field performance and

laboratory obtained behaviour. The laboratory tests on the HMA samples prepared with

the job mix formula for the eight monitored pavement sections were completed and

analysed to confirm test repeatability of the new laboratory accelerated polishing device.

The statistical correlation analyses on laboratory and field data have resulted in the

development of useful empirical predictive equations for the Skid Number (SN) from the

DFT (Dynamic Friction Tester) measured skid number. Finally, the British Pendulum

Number (BPN) from the British Pendulum Tester (BPT) was strongly correlated with the

Mean Texture Depth (MTD) measured by the sand patch method.

Based on the correlation studies conducted in the study, together with other highway

agencies’ acceptance criteria for aggregate friction values, a set of tentative polishing and

friction screening criteria for use by Ohio DOT is presented in the report.

vi

TABLE OF CONTENTS

Page LIST OF TABLES..........................................................................................................xiii

LIST OF FIGURES…………………………………………………...........……..…....xv

CHAPTER

1. INTRODUCTION…………………………..………………………………………..1

1.1 Statement of Problem .................................................................................... 1

1.2 Objectives of the Study ................................................................................. 3

1.3 Scope of the Work ........................................................................................ 4

1.4 Outlines of the Report ................................................................................... 5

2. EXISTING LITERATURE METHODS AND EQUIPMENTE REVIEW…..……...9

2.1 Introduction ................................................................................................... 9

2.2 Background and Significance of Work ....................................................... 11

2.2.1 Mechanism of Polishing, Wearing and Skid Resistance ......................... 11

2.2.2 Factors Affecting Skid Resistance ........................................................... 14

2.2.3 Roughness and Texture ............................................................................ 16

2.2.4 Importance of Aggregate Characteristics to Surface Performance .......... 20

2.2.5 Aggregate Factors Affecting Pavement Friction ..................................... 22

vii

2.2.5.1 Aggregate Shape ................................................................................... 22

2.2.5.2 Aggregate Size and Gradation .............................................................. 23

2.2.5.3 Resistance to Polish-Wear Action ........................................................ 23

2.2.6 Models for Wet Pavement Friction .......................................................... 24

2.2.6.1 The Penn State Model ........................................................................... 24

2.2.6.2 The Rado Model ................................................................................... 26

2.2.6.3 The PIARC Model and the International Friction Index ...................... 28

2.2.7 Frictional Needs of Traffic ...................................................................... 30

2.2.8 Factors Affecting Wet-Pavement Safety ................................................. 31

2.2.9 Skid Resistance Requirements and Practices by Different Agencies.. .... 33

2.2.10 Air Void and Temperature Effect on Frictional Properties of Asphalt

Pavement Surface ………………………………………………… …………34

2.2.11 Overview of Polishing, Friction, and Texture Measurements ............... 37

2.2.11.1 Existing Accelerated Polishing Machines .......................................... 37

2.2.11.1.1 Polishing Devices for…………...:………………………………..38

2.2.11.1.1.1 British Polishing Wheel…………………………………………38

2.2.11.1.1.2 Michigan Indoor Wear Track ...................................................... 39

2.2.11.1.1.3 Micro-Deval Device .................................................................... 39

2.2.11.1.2 Polishing Devices for HMA:……………………………………..39

2.2.11.1.2.1 NCAT Polishing Machine ........................................................... 40

2.2.11.1.3 Polishing Devices for Aggregates and HMA:……………………40

2.2.11.1.3.1 North Carolina State University Wear and Polishing Machine .. 41

viii

2.2.11.1.3.2 Wehner/Schulze Polishing Machine ........................................... 41

2.2.11.1.3.3 Penn State Reciprocating Polishing Machine ............................. 42

2.2.11.2 Friction Measurement Methods .......................................................... 42

2.2.11.2.1 Locked Wheel Friction Devices…………………………………..44

2.2.11.2.2 Side Force Coefficient Devices…………………………………..46

2.2.11.2.3 Fixed Slip Devices………………………………………………..48

2.2.11.2.4 Variable Slip Devices……………………………………… ……53

2.2.11.2.5 Other Friction Measurement Methods……………………………55

2.2.11.2.5.1 Dynamic Friction Tester .............................................................. 55

2.2.11.2.5.2 Pendulum Devices ....................................................................... 56

2.2.11.2.5.3 Michigan Laboratory Friction Tester .......................................... 58

2.2.11.2.5.4 PTI Friction Tester ...................................................................... 59

2.2.11.2.5.5 Stopping Distance Method .......................................................... 60

2.2.11.2.5.6 Wehner/Schulze Friction Device ................................................. 61

2.2.11.3 Texture Measurement Methods .......................................................... 61

2.2.11.3.1 Microtexture Measurement……………………………………….62

2.2.11.3.2 Macrotexture Measurement………………………………………63

2.2.11.3.2.1 Volumetric Measurements .......................................................... 64

2.2.11.3.2.2 Outflow Meter ............................................................................. 65

2.2.11.3.2.3 Profile Tracers ............................................................................. 66

3. A NEW ACCELERATED POLISHING DEVICE FOR HMA SURFACES……...70

3.1 Introduction ................................................................................................. 70

ix

3.2 Existing Laboratory Scale Polishing Devices ............................................. 71

3.3 Equipment Development ............................................................................ 72

3.3.1 Equipment Description and Operational Procedure ................................ 73

3.3.2 Operation Conditions ............................................................................... 78

3.4 Equipment Characteristics and Validation ................................................. 79

3.4.1 Materials .................................................................................................. 80

3.4.2 Sample Preparation Procedure for HMA Specimens ............................... 80

3.4.3 Friction and Surface Texture Measurements ........................................... 81

3.4.4 Supplemental Image Analysis Techniques .............................................. 83

3.4.5 Repeatability of the Accelerated Polishing Equipment ........................... 83

3.4.6 Polishing Effect of the Accelerated Polishing Machine .......................... 84

3.4.7 Comparing HMA Surface and Aggregate Surface PolishingBehavior... 91

3.4.8 Comparing the Polishing Trend with the Aggregate Exposure Area ...... 93

3.4.9 Polishing Trend of HMA Samples Prepared by Two Compaction

Methods............................................................................................................. 96

3.4.10 Application of the Accelerated Polishing Device .................................. 97

3.4.10.1 Correlation with PV values ................................................................. 98

3.4.10.2 Correlation with SN values ............................................................... 100

3.5 Summary and Conclusions ....................................................................... 101

4. LABORATORY TEST RESULTS AND DATA ANALYSIS……………………104

4.1 Introduction ............................................................................................... 104

4.2 Pavement Sections and Material Properties .............................................. 105

x

4.3 Test Program ............................................................................................. 107

4.3.1 Sample Preparation Procedure for HMA Specimens ............................. 107

4.3.2 Friction and Texture Measurement Techniques .................................... 108

4.3.3 Accelerated Polishing Device ................................................................ 108

4.4 Laboratory Test Results ............................................................................ 109

4.5 Analysis of Test Results ........................................................................... 109

4.5.1 Analysis of Repeatability ....................................................................... 109

4.5.2 Analysis of Polishing Behavior (BPN) .................................................. 115

4.5.2.1 Rate of Friction Loss (Percent Hourly Drop in Polish Numbers) ....... 115

4.5.2.2 Absolute and Percent Value of Decrease (Initial Polish Number versus

Final Polish Number) ...................................................................................... 120

4.5.3 Surface Texture Behaviour .................................................................... 121

4.5.3.1 Rate of SurfaceTexture Loss(Percent Hourly Drop in TextureValues)121

4.5.3.2 Absolute and Percentage Value of Decrease (Initial Texture Value

versus Final Texture Value). ........................................................................... 125

4.5.4 Correlation Study between BPN and MTD ........................................... 125


5. LABORATORY STUDY OF AIR VOID AND TEMPERATURE EFFECTS ON

HMA FRICTIONOPERTIES…………………………………………………….…131

5.1 Introduction ............................................................................................... 131

5.2 Background ............................................................................................... 132

5.3 Laboratory Testing Program ..................................................................... 136

xi

5.3.1 Materials ................................................................................................ 136

5.3.2 Test Program .......................................................................................... 136

5.3.3 Accelerated Polishing Machine ............................................................. 137

5.3.4 Friction Measurement Method ............................................................... 138

5.4 Test Results and Analysis ......................................................................... 138

5.4.1 Air Voids Effects ................................................................................... 138

5.4.2 Temperature Effects ............................................................................... 143


6. CORRELATION STUDY BETWEEN FRICTION MEASUREMENTS BY LWST

AND DFT………………………..…………………………………………..……....149

6.1 Introduction ............................................................................................... 149

6.2 Friction and Texture Measurement Techniques in This Study ................. 151

6.3 Experimental Program .............................................................................. 152

6.4 Field Test Results and Data Analysis ....................................................... 155

6.4.1 Typical LWST, DFT, and CTM Test Results ........................................ 155

6.4.2 Analysis of Test Results......................................................................... 157

6.4.2.1 Simple Linear Regression ................................................................... 159

6.4.2.2 Multicollinearity ................................................................................. 162

6.4.2.3 Multiple Linear Regression................................................................. 162


7. POLISHING MACHINE BASED ON HIGH-PRESSURE WATER JET………..166

xii

7.1 Introduction ............................................................................................... 166

7.2 Equipment Development .......................................................................... 170

7.2.1 Equipment Description and Operational Procedure .............................. 170

7.3 Equipment Characteristics and Validation ............................................... 175

7.3.1 Materials ................................................................................................ 175

7.3.2 Sample Preparation Procedure for HMA Specimens ............................. 176

7.3.3 Friction and Surface Texture Measurements ......................................... 176

7.3.4 Work Plan .............................................................................................. 177

7.4 Polishing Effect of the Accelerated Polishing Machine ........................... 177


8. SUMMARY AND CONCLUSIONS……………………………………………..186

8.1 Summary of Work Done ........................................................................... 186

8.2 Observations and Conclusions .................................................................. 188

8.3 Recommendations for Implementation ..................................................... 194

8.4 Recommendations for Future Work ......................................................... 195

REFERENCES……………………………………………………………………….198

APPENDICES………………………………………………………………………..207

APPENDIX A. ................................................................................................ 207

APPENDIX B. ................................................................................................ 224

xiii

LIST OF TABLES

Table Page

3-1: A summary of the existing accelerated polishing machines .................................... 74

3-2: Range of and selected optimum operation parameters ............................................. 79

3-3: Repeatability tests for the limestone and gravel ........................................................ 86

3-4: Simple Linear Regression between Aggregate Friction Values (Liang and Chyi

2000) and H . MA Friction Values (This Study) for Columbus Limestone………...……92

3-5: Simple Linear Regression between Aggregate Friction Values (Liang and Chyi

2000) and HMA Friction Values (This Study) for Stocker Sand and Gravel .................. 92

3-6: Simple Linear Regression between Aggregate and HMA Friction Values and

Aggregate Exposure Area ................................................................................................. 96

3-7: Simple Linear Regression between Friction Values of Gyratory Compacted

Specimens and Friction Values of Roller Compacted Slab Specimens (Limestone

aggregate) ......................................................................................................................... 97

3-8: Simple Linear Regression between Friction Values of Gyratory Compacted

Specimens and Friction Values of Roller Compacted Slab Specimens (Sand and Gravel

aggregate) ......................................................................................................................... 97

3-9: TxDOT acceptance criterion of aggregates ............................................................... 99

3-10: Derived acceptance criteria of HMA based on BPN values ................................... 99

xiv

3-11: Derived acceptance criterion of HMA based on SN values ................................. 101

4-1: Asphalt concrete pavement sections and the associated JMFs ............................... 106

4-2: Repeatability tests for the eight different job mix formulas .................................... 111

4-3: Percent decrease in BPN and MTD between initial and final values ..................... 120

4-4: Percent decrease in BPN and MTD between initial and final values ..................... 126

4-5: Simple linear regression between BPN and MTD .................................................. 127

4-6: Simple linear regression between BPN and MTD.............................................. 128

5-1: Summary of the studies focused on the temperature effect on HMA frictional

properties ........................................................................................................................ 135

5-2: Test of Homogeneity of variances, 1-Way ANOVA Table, and Multiple

Comparisons for the Effect of HMA Air Void on BPN ................................................. 142

5-3: Test of Homogeneity of variances, 1-Way ANOVA Table, and Multiple

Comparisons for the Effect of Pavement, Rubber Slider, and Water Temperatures on

BPN ................................................................................................................................ 146

6-1: HMA Pavement sections identification .................................................................. 153

6-2: Sample of skid numbers measured using LWST for one pavement section ........... 156

6-3: Simple linear regression between SN(64)R and DFT64, DFT20, and MPD .......... 160

6-4: Multicollinearity check using Tolerance, VIF, and Condition Index on the

independent variables ..................................................................................................... 162

6-5: Multiple linear regression between MPD and DFT64, MPD and DFT20, and DFT20

and DFT64 ...................................................................................................................... 163

7-1: Work plan summary of the laboratory work .......................................................... 177

xv

LIST OF FIGURES

Figure Page

Figure 2-1: Schematic of adhesion and hysteresis of rubber-tire friction ......................... 13

Figure 2-2: The contribution of adhesion (microtexture) and hysteresis (macrotexture) to

the friction factor as a function of sliding speed (reproduced from Federal Aviation

Administration 1971) ........................................................................................................ 14

Figure 2-3: Texture wavelength influence on surface characteristics (reproduced from

PIARC 1987) .................................................................................................................... 18

Figure 2-4: Schematic representation of microtexture and macrotexture ......................... 19

Figure 2-5: Effect of microtexture and macrotexture on skid resistance as a function of

speed ................................................................................................................................. 19

Figure 2-6: Terms used to describe the texture of a road surface ..................................... 20

Figure 2-7: Weight phase diagram of Hot Mix Asphalt ................................................... 21

Figure 2-8: Penn State Model (NCHRP Synthesis 291, 2000) ......................................... 26

Figure 2-9: Rado Model .................................................................................................... 27

Figure 2-10: Friction-slip curve of a braking tire (reproduced from Federal Aviation

Administration 1971) ........................................................................................................ 43

Figure 2-11: Locked Wheel Skid Trailer .......................................................................... 45

Figure 2-12: Ribbed tire versus smooth tire ..................................................................... 45

Figure 2-13: Sideways Force Coefficient Routine Investigation Machine (SCRIM) ....... 47

Figure 2-14: Side force tester: the MuMeter (Tomita 1964) ............................................ 48

xvi

Figure 2-15: The Runway Friction Tester ........................................................................ 52

Figure 2-16: The Griptester device ................................................................................... 52

Figure 2-17: Saab Friction Tester ..................................................................................... 53

Figure 2-18: The portable friction tester for measuring the friction on small surfaces .... 53

Figure 2-19: Norsemeter road friction measurement trailer ............................................. 54

Figure 2-20: Dynamic Friction Tester: (a) bottom view, (b) general view, and (c)

controller ........................................................................................................................... 56

Figure 2-21: British Pendulum Tester ............................................................................... 58

Figure 2-22: North Carolina State University Variable Speed Friction Tester ................ 58

Figure 2-23: Michigan Laboratory Friction Tester ........................................................... 59

Figure 2-24: MTD determination using the sand patch method ....................................... 65

Figure 2-25: Outflow meter .............................................................................................. 66

Figure 2-26: Circular Texture Meter: (a) general view, and (b) bottom view .................. 68

Figure 2-27: Mean Segment Depth determination ............................................................ 68

Figure 3-1: Different views of the accelerated polishing machine using rubber shoes; all

units are in inches ............................................................................................................. 75

Figure 3-2: Overall view of the accelerated polishing machine using rubber shoes and

setups for testing slab specimen and gyratory compacted specimen ................................ 78

Figure 3-3: Gradation curves ............................................................................................ 80

Figure 3-4: Polishing, friction, and texture results of tests conducted on limestone slab

specimens .......................................................................................................................... 87

xvii

Figure 3-5: Polishing, friction, and texture results of tests conducted on limestone

gyratory compacted specimens ......................................................................................... 88

Figure 3-6: Polishing, friction, and texture results of tests conducted on Sand and Gravel

slab specimens .................................................................................................................. 89

Figure 3-7: Polishing, friction, and texture results of tests conducted on Sand and Gravel

gyratory compacted specimens ......................................................................................... 90

Figure 3-8: Image analysis results of tests conducted on Limestone gyratory compacted

specimens .......................................................................................................................... 94

Figure 3-9: Image analysis results of tests conducted on Sand and Gravel gyratory

compacted specimens ....................................................................................................... 95

Figure 4-1: Average percent hourly drop in BPN vs. polishing time for low polish

susceptibility aggregates ................................................................................................. 117

Figure 4-2: Average percent hourly drop in BPN vs. polishing time for medium polish


Figure 4-3: Average percent hourly drop in BPN vs. polishing time for high polish


Figure 4-4: Normalization of BPN wrt. the maximum difference in BPN for low polish


Figure 4-5: Normalization of BPN wrt. the maximum difference in BPN for medium

polish susceptibility aggregates ...................................................................................... 119

Figure 4-6: Normalization of BPN wrt. the maximum difference in BPN for high polish


xviii

Figure 4-7: Average percent hourly Drop in MTD vs. polishing time for low polish


Figure 4-8: Average percent hourly drop in MTD vs. polishing time for medium polish


Figure 4-9: Average percent hourly drop in MTD vs. polishing time for high polish


Figure 4-10: Normalization of MTD wrt. the maximum difference in MTD for low polish


Figure 4-11: Normalization of MTD wrt. the maximum difference in MTD for medium


Figure 4-12: Normalization of MTD wrt. the maximum difference in MTD for high


Figure 5-1: Gradation curve ............................................................................................ 137

Figure 5-2: BPN vs. polishing time at different air voids ............................................... 139

Figure 5-3: BPN vs. air voids ......................................................................................... 143

Figure 5-4: BPN vs. polishing time at different pavement, rubber slider, and water

temperatures .................................................................................................................... 144

Figure 5-5: BPN vs. temperature .................................................................................... 146

Figure 6-1: Simple linear regression ............................................................................... 160

Figure 7-1: GRAP polishing machine ............................................................................. 169

Figure 7-2: Schematic depiction of GRAP polishing machine concept ......................... 169

Figure 7-3: GRAP aggregate specimen .......................................................................... 170

xix

Figure 7-4: Schematic depiction of the concept of the high-pressure water jet polishing

machine using HMA specimens ..................................................................................... 171

Figure 7-5: Overall view of the accelerated polishing machine using high-pressure water

........................................................................................................................................ 173

Figure 7-6: Drum (chamber) for placing the test specimen ............................................ 174

Figure 7-7: Details on slab specimen mounting in the drum .......................................... 174

Figure 7-8: Details on gyratory compacted specimen mounting in the drum ................. 175

Figure 7-9: Aggregate gradation curve ........................................................................... 176

Figure 7-10: Friction values for trial number 1 (at 10 rpm and 1450 psi) ...................... 179

Figure 7-11: MPD trend for Trial number 1 (at 10 rpm and 1450 psi ) .......................... 180

Figure 7-12: Friction values for trial number 2 (at 10 rpm and 400 psi) ........................ 180

Figure 7-13: MPD trend for trial number 2 (at 10 rpm and 400 psi) .............................. 181

Figure 7-14: Friction values of trial number 3 (at 10 rpm 1000 psi) .............................. 181

Figure 7-15: MTD trend for trial number 3 (at 10 rpm 1000 psi) ................................... 182

Figure 7-16: Friction values for trial number 4 (at 10 rpm 500 psi) ............................... 182

Figure 7-17: MTD trend for trial number 3 (at 10 rpm 500 psi) ..................................... 183

Figure 7-18: Tested HMA roller-compacted slab specimen surface .............................. 183

Figure 7-19: Tested HMA roller-compacted slab specimen surface .............................. 184

1

CHAPTER I

1. INTRODUCTION

1.1 Statement of Problem

Asphalt concrete pavements, over passage of time and under traffic, gradually lose their

surface friction (skid resistance), creating a serious safety concern especially when

pavements are wet. Lack of adequate skid resistance of pavement surface can create a

serious safety concern to the travelling vehicles at high speed, especially when the

vehicle is braking suddenly on wet pavement surface where hydroplaning can occur.

Statistical data has shown that most of fatal accidents on highways are related to

hydroplaning when uncontrolled skidding and gliding of high speed vehicles occurs.

It has been known that skid resistance is affected by factors, such as bleeding of

asphalt, polished aggregate, smoothened macrostructure, rutting and inadequate cross

slope. However, aggregate and mixture characteristics remain the most dominant

controlling factor. The ability of different aggregates to resist polish and wear is related

to mineralogical and chemical compositions as well as physical properties, such as

texture, particle size, shape, and gradation.

2

In recognition of the importance of providing a high skid resistance pavement surface

to prevent hydroplaning, most highway agencies maintain a strong safety program in

enforcing regular measurement of skid resistance of asphalt pavement surface by the

use of the Locked Wheel Skid Trailer (LWST). Once the measured skid resistance is

below certain criteria specified by the highway agencies, a remedial action either in

terms of resurfacing of the pavement or rejuvenating surface texture would be taken to

restore the friction and skid resistance to the acceptable level. Although this practice is

commendable in that the highway pavement surface is maintained at adequate skid

resistance level; nevertheless, the cost associated with the regular

monitoring/measuring program and the remediation action could be extensively high.

An alternative approach would be to take a more proactive stand in screening the

polishing potential of aggregates and Hot Mix Asphalt (HMA) mix to ensure that the

final selected mix can provide sustained resistance to polishing while providing

adequate level of friction (or skid resistance) over the life span of the pavement. To

achieve this initial screening task during the mix design stage of the HMA, there is a

need to develop a laboratory-scale accelerated polishing device that can mimic the

actual abrasion and polishing behavior between the vehicle rubber tire and the HMA

surface. In developing this accelerated polishing device, there are some practical

considerations that ideally should be taken into account, including the versatility of

testing HMA specimens that can be prepared with the conventional compaction

methods (i.e., gyratory compaction or roller compaction), the specimens could be

prepared as part of mix design procedure (i.e., the gyratory compactor together with the

3

industry standard 6 inch diameter mold), test duration should be relatively short, test

procedure including test specimen preparation and friction measurement techniques

should be relatively simple and repetitive, the developed test procedure should require

minimum labor efforts, and finally, the test results should provide realistic indication

(screening outcome) of the polishing and friction behavior of the HMA specimens.

1.2 Objectives of the Study

The main objective of the research is to develop a practical, time efficient quality

control test procedure to screen potential polishing and friction performance of

aggregates during the mix design stage in the Superpave designed HMA. To this end,

the specific objectives are outlined below.

Develop new accelerated polishing equipment for Superpave HMA to facilitate rapid

simulation of polish and wear actions between vehicle tires and asphalt pavement

surface. The new accelerated polishing equipment should have the following attributes:

the capability to test small-size HMA specimens (e.g., gyratory compacted specimens

with 6 inch in diameter and 4 inch in height), the test can be completed in a reasonable

timeframe, simple procedure, and efficient test method with less labor effort.

Develop a complete test protocol to include sample preparation method, test sequence,

data precision and bias analysis, and acceptance criteria for adoption by the governing

state or federal highway agencies.

4

1.3 Scope of the Work

The research involved both laboratory experimental work and field measurements of

asphalt pavement friction/skid performance. In addition, significant development work

was involved in the design, fabrication, and trying out the new accelerated polishing

equipment for HMA specimens. The development work of appropriate test apparatus

has been subjected to several cycles of refinement and validation. Furthermore,

separate studies were carried out to investigate the air void and temperature effects on

Hot Mix Asphalt (HMA) frictional properties in laboratory settings.

For correlation study eight asphalt pavement sections at different locations in Ohio

were identified and the associated HMA mix design (Job Mix Formulas) were provided

by the Ohio Department of Transportation. The compacted Superpave HMA

specimens, using the provided mix formulas, were produced in large numbers for each

aggregate source for a series of laboratory tests using the developed accelerated

polishing equipment. The test sequence of each specimen was carried out as follows.

First, the initial value of British Pendulum Number (BPN) and surface texture

(roughness) of the newly compacted HMA specimens were measured. In addition,

image analysis was carried out to quantify the area of exposed aggregate surface. Next,

the specimen was subjected to accelerated polishing using the developed accelerated

polishing equipment. The entire test duration of each polishing action was optimized by

examining the evolution of BPN and texture values at various stages of test. The plan

was to polish until the specimen reached the residual state (in terms of friction and

5

texture values) is reached. The test results for all aggregate sources are plotted in terms

of BPN and texture values versus duration of polishing action.

The field work at the identified pavement sections involves annually measuring friction

and texturing using the Dynamic Friction Tester and the Circular Texture Meter,

respectively. The measured values are correlated with skid number measured by the

Locked Wheel Skid Trailer conducted by ODOT personnel at the same location.

Finally, the laboratory determined friction values at different test durations during

accelerated polishing are compared with history of skid number in the field. This

comparison serves as validation of the developed test procedure.

A different type of polishing equipment based on the concept of high-pressure water jet

has also been developed in this study to investigate the potential of using the high-

pressure water jet to accomplish the desired accelerated polishing on HMA surface.

The preliminary results of the initial trial of the equipment are reported in this report

and some surprising outcomes of using this equipment has pointed to the possible use

of the technique for rejuvenating the texture of the worn out existing pavement surface.

1.4 Outlines of the Report

Presented in chapter II is a review of the literature on the concepts and theories of

polishing of aggregate and HMA, the frictional characteristics of aggregate and HMA,

as well as the interrelationship between aggregate source, HMA friction properties, and

HMA surface texture properties. Chapter II also provides information on the different

6

equipment used for accelerated polishing of aggregates and asphalt mixtures, as well as

different friction and texture measurement devices. Relevant research and practice by

the state and federal highway agencies on the related topics was also covered in this

chapter.

Chapter III presents the development of a new laboratory-scale accelerated HMA

polishing device for the purpose of screening the polishing and friction performance of

the HMA mix, in terms of differentiating the contributing factors of the aggregate

source, aggregate gradation, and binder type and content that constitute the important

constituents of the HMA. The operation principles along with the operation conditions

of this equipment are described in detail. The performance of this accelerated polishing

test device is evaluated and described in detail as well. The tentative acceptance criteria

based on other agencies’ acceptance criteria and the established correlations in this

study are presented for screening the HMA specimens from the polishing and friction

standpoint. The advantages and limitations of the developed accelerated polishing

device are presented at the conclusion of this chapter.

Chapter IV presents the laboratory test results and the associated data analysis

conducted on laboratory-prepared gyratory-compacted HMA specimens that are made

of eight different job mix formulas using the developed laboratory-scale accelerated

HMA polishing device for the purpose of examining the repeatability of the newly

developed accelerated polishing device and to investigate the relationship between

friction and texture values.

7

Chapter V introduces the controlled laboratory test results for quantifying the effects of

air void and temperature on the measured friction properties of the gyratory compacted

HMA surfaces. The laboratory test procedures, including the materials used in

preparing the HMA specimens, the method used to polishing the HMA surface, and the

friction measurement techniques, are described in detail. Statistical analysis was carried

out to determine the significance of these two variables (air void and temperature) on

the measured friction values. Finally, the method for extrapolating the friction values

measured at any density and temperature to the friction values at other density and

temperature is proposed at the end of the chapter.

The main objective of Chapter VI is to present the measurements that consist of the

skid numbers, the friction numbers measured using the dynamic friction tester, and the

mean profile depth measured using the circular texture meter at the same time for the

same pavement surface location at the long-term monitoring pavement sections. From

these measured data, a statistical study was conducted to develop the relationship to

predict the skid number at 64 km/h (40 mph) using the ribbed tire locked wheel skid

trailer (SN(64)R) from one or the combination of the following three measurements: (a)

the friction number at 64 km/h (40 mph) using the dynamic friction tester (DFT64), (b)

the friction number at 20 km/h (12.5 mph) measured by the dynamic friction tester

(DFT20), and (c) the mean profile depth measured by the circular texture meter (MPD).

Either one of the three predictive equations can be used successfully to predict the

SN(64)R values.

8

Chapter VII presents the development of a different accelerated polishing equipment

that involves the use of high-pressure water jet. The operation principles along with the

operation conditions and the performance of the developed accelerated polishing test

device are evaluated and described. The ability of the developed device to simulate the

tire-pavement interaction is discussed and presented in this chapter as well.

Chapter VIII provides the summary of work done as well as conclusions and

recommendations for implementation.

9

CHAPTER II

2. EXISTING LITERATURE METHODS AND EQUIPMENTE REVIEW

2.1 Introduction

Asphalt concrete pavements under traffic loads and environmental weathering can

gradually lose surface friction (or skid resistance) due to tire and pavement interaction

through polishing and wearing as well as freezing and thawing induced degradation.

Although weather effect may be present, the primary cause of polishing and loss of

friction can be attributed to loss of microtexture and macrotexture of the pavement

surface through prolonged abrasion action between the vehicle tires and pavement

surface. Lack of adequate skid resistance of a pavement surface can create a serious

safety concern to the travelling vehicles at high speed, especially when the vehicle is

braking suddenly on wet pavement surface where hydroplaning can occur. Statistical

data has shown that most of fatal accidents on highways are related to hydroplaning

when uncontrolled skidding and gliding of high speed vehicles occurs. Hydroplaning

results when vehicle tires move fast relative to the wet pavement surface, such that

there is insufficient time to channel the moisture away from the center of the tire. The

result is that the tire is lifted by the water away from the road and all traction is lost.

10

In recognition of the importance of providing high skid resistance pavement surface to

prevent hydroplaning, most highway agencies maintain a strong safety program in

enforcing regular measurement of skid resistance of asphalt pavement surface by the

use of the Locked Wheel Skid Trailer (LWST). Once the measured skid resistance is

below certain criteria specified by the highway agencies, a remedial action either in

terms of resurfacing of the pavement or rejuvenating surface texture would be taken to

restore the friction and skid resistance to the acceptable level. Although this practice is

commendable in that the highway pavement surface is maintained at adequate skid

resistance level; nevertheless, the cost associated with the regular

monitoring/measuring program and the remediation action could be extensively high.

An alternative approach would be to take a more proactive stand in screening the

polishing potential of aggregates and Hot Mix Asphalt (HMA) mix to ensure that the

final selected mix can provide sustained resistance to polishing while providing

adequate level of friction over the life span of the pavement. To achieve this initial

screening task during the mix design stage of the HMA, there is a need to develop a

laboratory-scale accelerated polishing device that can mimic the actual abrasion and

polishing behaviour between the vehicle rubber tire and the HMA surface. In

developing this accelerated polishing device, there are some practical considerations

that ideally should be taken into account, including the versatility of testing HMA

specimens that can be prepared with the conventional compaction methods (i.e.,

gyratory compaction or roller compaction), the specimens could be prepared as part of

mix design procedure (i.e., the gyratory compactor together with the industry standard

11

6 inch diameter mold), test duration should be relatively short, test procedure including

test specimen preparation and friction measurement techniques should be relatively

simple and repetitive, the developed test procedure should require minimum labour

efforts, and finally, the test results should provide realistic indication (screening

outcome) of the polishing and friction behaviour of the HMA specimens.

2.2 Background and Significance of Work

The background and the pertinent literature review concerning the significance of work

is presented herein.

2.2.1 Mechanism of Polishing, Wearing and Skid Resistance

Polishing of aggregates is defined as the loss of small asperities of road surfaces. These

asperities are called microtexture. Wearing, on the other hand, is the loss of

macrotexture or surface irregularities. Most researchers agree that the principal

mechanism of polishing is the abrasion of the small aggregate asperities as a result of

the rubbing action under loaded tires with the fine road detritus as the abrasive agent.

The principal mechanism of wearing involves continuous abrasion resulting from loads

and environmental changes such as freezing/thawing, wetting/drying, and oxidation.

Polishing and wearing generally involve similar processes that vary only in the degree

and the rate of material loss. Friction, which is the force that resists the relative motion

between two bodies in contact, is an essential part of the tire-pavement interaction. Not

only does friction allow a vehicle to accelerate and maneuver, but also it exerts a major

12

determining factor in the ability to stop a vehicle. The factors influencing the

development of friction between rubber tires and a pavement surface include the

texture of the pavement surface, vehicle speed, and the presence of water. However,

pavement skid resistance (or pavement friction) is defined as the ability of a travelled

surface to prevent the loss of traction with the vehicle rubber tires . Skid resistance and

texture of pavement surface are two important parameters often measured during the

service life of the pavement to ensure that they meet the minimum required criteria for

safety reason. Theoretically, the friction that develops between a rubber tire and a

travelled pavement surface consists of two components; namely, adhesion and

hysteresis (Kummer, 1966). As depicted in Figure 2-1, adhesion is the shear force

between the tire and the pavement surface generated when the tire rubber slides over

the aggregate surface asperities due to microtexture and the aggregate particles indent

onto the rubber. In essence, adhesion can be viewed as the molecular bonds generated

when the tire rubber deforms under load. The second friction component, hysteresis, is

developed when the tire rubber deforms due to macrotexture (or irregularities) of the

pavement surface. In essence, it can be viewed as energy loss that occurs as the rubber

is alternately compressed and expanded as it slides over the irregular pavement surface

texture.

13

Figure 2-1: Schematic of adhesion and hysteresis of rubber-tire friction

Figure 2-2 is a schematic diagram of the contribution of adhesion and hysteresis to the

friction factor. At low speed, friction is due mainly to adhesion. On the other hand, at

high speed, the contribution of hysteresis becomes more significant. A pavement that is

covered with a thin film of lubricant would provide only hysteresis.

14

Figure 2-2: The contribution of adhesion (microtexture) and hysteresis

(macrotexture) to the friction factor as a function of sliding speed (reproduced from

Federal Aviation Administration 1971)

2.2.2 Factors Affecting Skid Resistance

The fiction between the rubber tire and the pavement surface is dependent on the two

materials in contact viz. the type of rubber used and the pavement surface. The type of

rubber used is important because it’s damping characteristics change with the type of

rubber and its chemical composition. The pavement surface, as determined by the

surface texture and the visco-elasticity of asphalt pavement, is also important in

determining the magnitude of both adhesion and hysteresis.

15

The adhesion component is dependent upon the following factors:

Interface lubrication: dry surfaces provide higher adhesion than wet surfaces. The

presence of lubrication tends to decrease the interface shear strength.

Sliding speed of rubber: adhesion increases with speed and reaches a maximum at a

“critical speed”. The critical speed ranges from 0.1 to 10 mph depending on the rubber

type and temperature. For speed above this “critical speed”, adhesion decreases.

Adhesion also decreases as the loading pressure increases. Higher loading pressure is

associated with an increase in the actual contact area; but that increase is not

proportional to the increase in the loading pressure.

The adhesion at a particular speed may increase, decrease, or remain unaffected by

temperature changes at the interface due to the visco-elastic nature of the rubber and

asphalt pavements.

On the other hand, the hysteresis component (Bazlamit, 1993) is dependent upon the

following factors:

Hysteresis will increase with the increase in the damping ability of rubber.

Unlike adhesion, hysteresis decreases as the temperature of the interface increases.

Hysteresis is virtually independent of the loading pressure and lubrication.

16

2.2.3 Roughness and Texture

Pavement texture is the feature of the road surface that ultimately determines most tire-

pavement interactions, including wet friction, noise, splash and spray, rolling

resistance, and tire wear (NCHRP Synthesis 291, 2000). Pavement texture has been

categorized into four ranges based on the wavelength of its components: microtexture,

macrotexture, megatexture, and roughness or evenness. At the 18th World Road

Congress, the Committee on Surface Characteristics of the World Road Association

(PIARC) proposed the definitions of the wavelength range for each of the categories as

shown in Figure 2-3 (PIARC 1987). The committee further proposed the range of the

texture wavelengths that are important for various tire-pavement interactions, which are

also shown in Figure 2-3. Wet pavement friction is primarily affected by the range

described by microtexture and macrotexture, as can be seen in a vast number of recent

studies, for example, by Davis (2001), Do and Marsac (2002), McDaniel and Coree

(2003), Luo (2003), Flintsch et al. (2003), Hanson and Prowell (2004), Kuttesch

(2004), Wilson and Dunn (2005), and Goodman et al. (2006). Because the range of

microtexture and macrotexture affects noise, splash and spray, and tire wear,

pavements designed with high friction values may have adverse effects on these

characteristics.

A detailed description of microtexture and macrotexture is presented herein. Tiny

grains of fine aggregate and features that make up the surface of coarse aggregate

provide what is known as the pavement microtexture. Thus, microtexture is a function

17

of aggregate gradation. In functional terms, microtexture is the most significant

contributor to low speed skid resistance and provides a gritty surface to penetrate thin

water films and produce good frictional resistance between the tire and the pavement.

Microtexture describes wavelength that ranges from 0.1mm to 0.5mm and it is

correlated to low speed friction. Features of the pavement surface that range from

approximately 0.5 mm to 50mm in length are classified as macrotexture. Macrotexture

was shown to be the primary determining factor of high speed wet skid resistance

(McGhee and Flintsch, 2003; Chelliah et al., 2003; NCHRP Synthesis 291, 2000;

Janoo, and Korhonen, 1999; Dewey, et al., 2001; Abe et al., 2002). Macrotexture is a

result of the large aggregate particles in the mixture and it is a function of aggregate

type. Macrotexture provides drainage channels for water expulsion between the tire and

the pavement thus allowing better frictional resistance and preventing hydroplaning.

Macrotexture can be estimated using volumetric or laser-based methods. Both the

microtexture and macrotexture of asphalt concrete pavements are influenced by the

properties of the coarse aggregates exposed at the wear surface since the coarse

aggregate in bituminous mixtures is more influential than other mix constituents in

determining skid resistance (Dewey et al., 2001; Crouch et al., 1996). A schematic

illustration of microtexture and macrotexture is shown in Figure 2-4.

Figure 2-5, on the other hand, presents the effect of microtexture and macrotexture

properties on skid resistance as a function of speed (Janoo and Korhonen, 1999).

Clearly, to maintain a constant high skid resistance value at various speed levels, the

pavement surface should have both good microtextures and macrotexture (Janoo and

18

Korhonen, 1999; NCHRP Synthesis 291, 2000). The change in the texture depends on

the aggregate resistance to fragmentation, wear, and polishing. Aggregate

fragmentation and wear depend on the toughness and hardness of the aggregate

minerals and the aggregate itself. Polishing depends on the difference in hardness of the

different minerals present in the aggregate (Janoo and Korhonen, 1999). Surface

texture can be defined in terms of microtexture and macrotexture; the terms used to

describe the texture of a road surface are shown in Figure 2-6.

Figure 2-3: Texture wavelength influence on surface characteristics (reproduced

from PIARC 1987)

19

Figure 2-4: Schematic representation of microtexture and macrotexture

Figure 2-5: Effect of microtexture and macrotexture on skid resistance as a function

of speed

20

Figure 2-6: Terms used to describe the texture of a road surface

2.2.4 Importance of Aggregate Characteristics to Surface Performance

Aggregates constitute more than 90% by weight of asphalt pavement materials as

shown in Figure 2-7. Strength and durability of aggregates often hold the primary

concern of the designer, especially in the bituminous construction (Smith and Fager,

1991; NCHRP Report 405, 1998). Consequently, aggregate plays a very significant

role in surface performance. The role of aggregate is to provide a macrotexture that will

induce tire hysteresis and facilitate water drainage in the tire-pavement contact area. It

is also to provide a microtexture that will maintain a level of friction.

21

Aggregate

Binder + Void

90%

10%

Figure 2-7: Weight phase diagram of Hot Mix Asphalt

Within the service life of an asphalt pavement, surface aggregates are subjected to

various types of stresses. These stresses could induce differential wear that may be

beneficial in restoring surface friction, or they could cause cracking, scaling, etc. In

order for the aggregates to withstand wear that causes differential changes in surface

macrotexture, the aggregate must be hard and tough and possess well-bonded grains so

that it will not be easily crushed or fractured under traffic loading stresses. The

aggregate must also be chemically stable. If the aggregate resists excessive wear but

undergoes slow differential wear, the macrotexture will be preserved and the

microtexture will be improved.

According to Gandhi et al. (1991), among the aggregate properties that affect friction,

polish values and acid solubility (carbonate content) were statistically significant.

However, the carbonate content gave a better correlation than polish values. Also,

when texture depth was included as an additional variable in the models with either

Binder+Void

22

solubility or polish values, the correlation coefficients increased slightly. American

Association of State Highway and Transportation Officials (AASHTO) guidelines

recommended the use of either the Acid Insoluble or Polish test for evaluating

aggregates. Thus, a requirement of a minimum polish value from 45 to 48 and

maximum carbonate content of aggregate from 10 to 25 percent will be in accordance

with the accepted national and international practice.

2.2.5 Aggregate Factors Affecting Pavement Friction

Excluding those asphalt pavements produced mainly from fine aggregates, the skid-

resistant properties of asphalt pavements depend primarily on the coarse aggregates.

According to a study (Beaton, 1976), four characteristics should be evaluated in the

selection of aggregates for skid-resistant asphalt pavements. These are: texture, shape,

size, and resistance to polish-wear action. Texture was discussed in previous section,

the other three characteristics (i.e., shape, size, and resistance to polish-wear action) are

explained below.

2.2.5.1 Aggregate Shape

Shape of an aggregate particle significantly affects its skid-resistant properties. Shape

of the aggregates also influences factors like hardness of grains, strength of the matrix,

and overall aggregate resistance to abrasion. Processing procedures also govern the

shape of both natural and synthetic aggregates. Angularity contributes to skid-resistant

qualities, but retention of angularity depends on characteristics like mineralogical

composition and amount of polish-wear produced by traffic.

23

2.2.5.2 Aggregate Size and Gradation

Aggregate size influences skid resistance qualities of the pavement. However, it must

be considered in relation to pavement type and mix design. Generally, larger-size

aggregates in asphalt pavement mixes have greater control over skid resistance than

smaller-size aggregates. As per Dahir (1979), open grading has been successfully used

to facilitate fast drainage of wet pavements in the tire-pavement contact area, by

reducing skid resistance-speed gradient.

2.2.5.3 Resistance to Polish-Wear Action

The ability of an aggregate to resist the polish-wear action of traffic has long been

recognized as the most important characteristic for use in pavement construction. When

an aggregate becomes smooth, it will have poor skid resistance. Also, if it polishes and

wears (abrades) too rapidly, the pavement will be slippery under wet conditions

(Hosking, 1976).

A study (Sherwood, 1970) showed that coarse grain sizes and differences in grain

hardness appear to combine to lead to differential wear and plucking out or shearing of

grains that result in a constantly renewed abrasive surface.

According to Shupe (1958), certain minerals are associated with good skid resistance

qualities. For example, the superior performance of dolomitic limestone over relatively

pure carbonate limestone.

24

2.2.6 Models for Wet Pavement Friction

Wet pavement friction is a measure of the force generated when a tire slides on a wet

pavement surface. Wet pavement friction is often referred to as “skid resistance”, and

the two terms are used interchangeably (NCHRP Synthesis 291, 2000). Wet pavement

friction decreases with increasing speed. This was first recognized by Moyer in 1934.

More specifically, skid resistance decreases as the velocity of the tire surface relative to

the pavement surface increases. This relative velocity is called the slip speed. There are

several models for determining pavement friction. A few of the most commonly used

models are described in this section.

2.2.6.1 The Penn State Model

The Penn State Model (Leu and Henry, 1983) describes the relationship of friction ()

to slip speed (S) by an exponential function:

SPNG

e 100

(2-1)

Where o is the intercept of the friction at zero speed, and PNG is the percent

normalized gradient (the speed gradient times 100 divided by the friction) defined by:

dS

dPNG

100 (2-2)

It was demonstrated that PNG is constant with speed and therefore Equation 2-1

follows by rearranging Equation 2-2 and integrating from S = 0 to S. Furthermore, it

25

was discovered that PNG is highly correlated with macrotexture and that o can be

predicted from microtexture.

Later version of the Penn State Model replaced the term (100/ PNG) by a speed

constant Sp:

pS

S

e

(2-3)

The PIARC Model (PIARC 1995) adopted the Penn State Model, but shifted the

intercept to 60 km/h:

pS

S

eFSF

60

60)( (2-4)

Where F(S) is the friction at slip speed S in km/h, and F60 is the friction at 60 km/h (36

mph).

Figure 2-8 shows the Penn State Model for two cases that have the same level of

friction at 60 km/h (36 mph), but behave very differently at other speeds, because of

differences in texture, resulting in different values for PNG and Sp. This example

demonstrates the need for specifying more than a single value, such as the friction at 60

km/h (36 mph), to describe the skid resistance of a pavement.

26

Figure 2-8: Penn State Model (NCHRP Synthesis 291, 2000)

2.2.6.2 The Rado Model

The Rado Model, on the other hand, depicts the entire braking maneuver using the

following equation (NCHRP Synthesis 291, 2000):

2)/ln(

)(

C

SS

peak

peak

eS (2-5)

Where peak= peak friction level,

Speak = slip speed at the peak (typically 15% of the vehicle speed), and

C = shape factor related to the harshness of the texture.

Figure 2-9 is a plot of Equation 2-5 with some typical values: peak = 0.6, Speak = 15

km/h (9 mph), and C = 0.5, with the forward speed of the test vehicle of 120 km/h (66

mph).

27

Figure 2-9: Rado Model

As a tire proceeds from the free rolling condition to the locked wheel condition under

braking, the friction increases from zero to a peak value and then decreases to the

locked wheel friction. Anti-lock brake systems release the brakes to attempt to operate

around the peak level of friction.

The Penn State and Rado Models together can be used to simulate the complete vehicle

braking in an emergency situation. The Rado Model is used at the beginning of the

braking manoeuvre until wheels are fully locked. If braking continues after the locked

wheel condition is reached, the vehicle speed (which then is equal to the slip speed)

decreases and the friction follows the Penn State Model until the vehicle stops (Luo

2003; NCHRP Synthesis 291, 2000).

28

2.2.6.3 The PIARC Model and the International Friction Index

The International PIARC Experiment to Compare and Harmonize Texture and Skid

Resistance Measurements (PIARC 1995) was conducted in Belgium and Spain in the

fall of 1992. Each friction tester was operated at three speeds: 30, 60, and 90 km/h (18,

36, and 54 mph), and each tester made two operated runs at each speed. All texture

measurements were made on dry surfaces before any water was applied to the roadway.

As a control, a microtexture measurement was made before and after the skid testers

made their tests. These data were used to show that there were no statistically

significant changes occurring during the testing.

The Rado Model at slip speeds above the peak and the Penn State Model are similar

and are dependant on the pavement characteristics. Because the Penn State Model is

less complex, it was chosen as the basis for the analysis of the data from the experiment

and the development of the International Friction Index (IFI). The IFI was developed as

a common scale for the reporting of pavement friction measurements. IFI is currently

being adopted worldwide as the standard skid resistance measure.

The IFI consists of two terms: (1) the speed constant, Sp, of wet pavement friction

which is a function of pavement macrotexture, and (2) the wet friction of a pavement,

F60, at 60 km/h, that depends on a measured friction value, the slip speed, and the

speed constant.

The wet pavement speed constant Sp in km/h is determined from macrotexture

measurement (Tx in mm) as follows:

29

TxbaS p (2-6)

where a and b are calibration constants that are specified in ASTM E 1960 for the

results of macrotexture testing in accordance with ASTM E 2157 and ASTM E 965.

The calibrated wet friction parameter (F60) can be estimated from the results of friction

testing. The relationship for calculating F60, per ASTM E 1960, is:

TxCeFRSBAF pS

S

60

60 (2-7)

where A, B, and C are calibration constants, and FRS is the measured friction at some

slip speed, S in km/h. The calibration constants are specified in ASTM E 1960 for the

results of friction testing in accordance with ASTM E 1911 and ASTM E 274.

The termpS

S

eFRS

60

in equation 2-7 is known as the adjusted value of friction from a

slip speed of S in km/h to 60 km/h for the equipment.

After the determination of F60 and Sp, the calibrated friction at any other slip speed,

F(S), can be calculated using equation 2-4.

The resulting parameters that make up the IFI (F60 and Sp) are sufficient to describe

the friction as a function of slip speed using equation 2-4. Note that a macrotexture

measurement is required to apply the IFI. The two parameters (F60 and Sp) distinguish

the difference between the two pavements shown in Figure 2-8.

30

Another advantage of the IFI is that the value of F60 for a pavement will be the same

regardless of the slip speed. That permits the test vehicle to operate at any safe speed.

Finally, the standard ASTM E1960 describes a procedure to calibrate devices that did

not participate in the experiment.

2.2.7 Frictional Needs of Traffic

The minimum skid-resistant pavement is generally required to satisfy the normal needs

of traffic without skid-related accidents. Normal needs of traffic encompass all the

driving, cornering, and braking manoeuvres by the majority of drivers under normal

traffic conditions. In providing skid resistance, the normal frictional needs of traffic

must be satisfied before steps can be taken to accommodate more severe demands.

Minimum frictional requirements of a pavement are those that satisfy the normal needs

of traffic. “Minimum” refers to the lowest acceptable friction level and specifically

implies that the level should be higher whenever possible. Minimum frictional

requirements are, therefore, defined if the normal needs of traffic can be described. As

outlined in NCHRP No. 37 three methods of determining the minimum frictional

requirements are as follows:

For any standard skid-resistance measurement method, a comparative study can be

made between the skid resistance requirements of different pavement sections. For

example, the skid resistance rate observed on a large sample of pavement surfaces,

representing the entire design speed range from 48 to 129 km/h (30 to 80 mph) can be

compared with the skid-resistance measured on other surfaces under clearly defined

31

pavement conditions. This method determines the friction level, which separates

pavements susceptible to skidding and skid-resistant pavement surfaces.

Driver behaviour pattern of a large driver population during acceleration, driving,

cornering, and deceleration can be investigated by concealed recorders carried on board

or located near the site being surveyed. This method yields an acceleration spectrum,

which defines normal, intermediate, and emergency needs according to magnitude and

their frequency of occurrence.

The frictional needs can be deduced from vehicle design and highway geometry, or the

superposition of the two, whenever the limiting needs are determined by these factors

and not by the driver, as for instance by the full-throttle acceleration of a particular type

of vehicle. The frictional needs for this manoeuvre are solely dictated by vehicle factors

such as weight-to-horsepower ratio, transmission ratios, and center-of-gravity location.

2.2.8 Factors Affecting Wet-Pavement Safety

Skid Number (SN) alone is not a good measure of wet pavement safety. Many other

factors affect safety under wet-pavement conditions, and it is only when these

conditions demand a particular level of traction that SN becomes important. Some of

these factors according to Wambold and Kulakowski (1991) are listed below.

Vehicle Speed: Friction demand increases with speed. The centrifugal forces generated

during the vehicle cornering, which have to be counteracted by tire-pavement friction

forces to prevent the vehicle from skidding off the road are proportional to the square

32

of vehicle speed. Also, pavement resistance decreases with increasing speed in an

approximately exponential manner.

Road Geometry: Friction demand on straight sections of roads is low, if road is level,

vehicles travel at low speeds, and if there are no intersections. The demand for friction

increases significantly if a grade or a curve is to be negotiated. Page and Butas (1986)

concluded that wet-pavement accident rates are significantly higher on curves than any

other type of geometric alignment. The effect of curvature on wet-pavement accident

rates was found to be particularly significant on pavements with SN values less than

25. Furthermore, for SN values less than 25, wet-pavement accident rates were

significantly greater for both uphill and downhill slopes steeper than 3 percent than for

flatter terrain.

Traffic Flow: Traffic volume does not have a significant influence on wet-pavement

accident rates. However, under special circumstances, like on undivided highways with

SN values less than 25, wet-pavement accident rates increase significantly when

average daily traffic exceeded 15,000. Traffic composition, particularly the percentage

of trucks has a significant effect on friction demand, since the stopping distances of

trucks are 1.3 to 2.8 times longer than those of passenger cars.

Vehicle Type: If equal stopping distance is required for all vehicles, then the friction

demand for buses and trucks is higher than that for passenger cars. The friction demand

is also higher for vehicles with lower degrees of understeer.

33

Driver Skills: Few drivers can operate their vehicles with 100 percent efficiency, i.e.,

using 100 percent of the available friction. Olson et al. (1984) found that truck driver

efficiencies ranged from 62 to 100 percent, but most of the drivers had little or no

practice in emergency braking situations. The concern over emergency braking skills

will be considerably alleviated when antilock brake systems (ABS) become a more

common feature.

2.2.9 Skid Resistance Requirements and Practices by Different Agencies

For the sake of uniformity, skid number at 40 mph using the locked wheel skid

trailer is normally used to compare between the minimum requirements set by

different state agencies. The Florida Department of Transportation (FDOT) Safety

Improvement Program Manual calls for desirable skid number values of 35 and

greater for facilities with posted speed limits greater than 45 mph. On roadways with

a posted speed limit less than or equal to 45 mph, the desirable skid number value is

30 or greater. In addition, the FDOT Friction Testing and Action Program calls for

skid number values of 35 and above, and pavements having mean skid number

values below 35 must be re-tested in one year. These friction requirements are

generally consistent with other state transportation departments (Jackson, 2003).

Oklahoma Department of Transportation (OKDOT) requires a minimum field skid

number of 35 which confirms the previous conclusion, while New York Department

of Transportation (NYDOT) uses a design target of minimum skid number of 32 at a

speed of 40 mph using ribbed tire. Indiana Department of Transportation (INDOT),

34

on the other hand, established a uniform minimum friction requirement of 20 for the

standard smooth tire at 40 mph. It was indicated that by the seven-year friction

measurements, this friction requirement can guarantee a reasonable and consistent

friction performance for INDOT network pavement (Li et al. 2004). One more

important thing to mention is that many state highway agencies have established

their minimum friction requirements based on the recommendation of the minimum

friction requirement by NCHRP-37 (Kummer and Meyer, 1967). Using standard

ribbed tire, NCHRP-37 recommended a minimum friction number of 37.

Texas Department of Transportation has done extensive research and summarized the

guidelines that different State Departments of Transportations follow for testing and

acceptance of aggregates for adequate provision of skid-resistant pavements

(Jayawickrama, et. al, 1998). The same has been reproduced and can be found in Liang

(2003).

2.2.10 Air Void and Temperature Effect on Frictional Properties of Asphalt Pavement

Surfaces

In recent years, a few notable research efforts have directed toward a better

understanding of the influencing factors on the HMA surface friction properties. In

2006, Goodman et al. reported that initial field BPN can be correlated with the

following variables: fineness modulus (FM), voids in mineral aggregate (VMA),

percent passing the 4.75mm sieve (P4.75) and bulk relative density (BRD).

Interestingly, the bulk relative density was found to significantly affect the measured

35

BPN values. Specifically, an increased BPN was observed through the use of more

densely graded aggregates (reduced FM), less void space between aggregate particles

(less VMA), use of finer gradation (more P4.75), and higher compactive effort

(increased BRD).

There have been some recent research efforts toward quantifying the temperature

effects on the measured pavement friction values. For example, Runkle and Mahone

(1980), Burchett and Rizenbergs (1980), and Bazlamit and Reza (2005) have found that

an increase in temperature can result in a corresponding decrease in skid resistance of a

pavement surface.

A very noteworthy study was conducted in connection with the Virginia Smart Road to

investigate the friction properties as affected by seasonal temperature differences.

Wang and Flintsch (2007) studied the surface friction and texture properties of 12

asphalt pavement sections placed at the Virginia Smart Road pavement facility over a

6-year time period. Both short-term (seasonal) and long-term (multi-year) variations of

the surface characteristics were investigated in terms of temperature and time effects.

Their investigation showed that pavement skid resistance decreases in summer (high

temperatures) and thus confirming that temperature can exert significant effects on the

seasonal and multi-year variations of pavement surface friction. Other studies related to

Virginia Smart road include Flintsch et al. (2005) and Luo (2003). In both reports, the

effect of pavement temperature on frictional properties of HMA pavement surfaces at

36

the seven HMA surfaces was confirmed. Their analysis showed that pavement friction

tends to decrease with an increase in pavement temperature.

An Indiana study conducted by Elkin et al. (1980) also confirmed that there was a

noticeable loss of skid resistance as pavement surface temperature increases beyond 32

°C ( F90 ) and especially above 38 °C ( F100 ). Hill and Henry (1978) conducted a

study on twenty one test surfaces in State College, Pennsylvania. The testing program

included daily skid measurements according to ASTM E 274 and the collection of daily

weather data. Pavement temperature was chosen as the temperature parameter. It was

found that an increase in pavement temperature of C10 (50 °F) can result in a decrease

in SN at 64 kmph (40 mph) of about 1.2 skid numbers. This decrease, however, is

outweighed by measurement error, particularly lateral placement of the test tire, which

accounts for as much as 4 skid numbers at a speed of 64 kmph (40 mph).

Despite the significant number of reports cited above to indicate the significant effects

of temperature on pavement surface friction values, there are contradictory findings

reported by Dahir et al. (1979) and Mitchell et al. (1986) as well. Dahir et al. (1979)

conducted a study at the Pennsylvania State University to investigate the short-term

(seasonal) variations of skid resistance. In this study, skid resistance measurements

according to ASTM E 274 were made on dry pavements. In addition, tire and pavement

temperatures were continuously monitored by using radiometers mounted on the tester.

Ambient and water temperatures were measured using appropriate thermometers. It

was concluded that temperature variations of the magnitude experienced in the study do

37

not seem to significantly affect the skid resistance measurements. Mitchell et al. (1986)

conducted a study on the pavement surfaces incorporated into Maryland’s highway

system. The primary objective of Mitchell’s study was to determine the parameters that

could be used to predict the influence of seasonal variations. In addition to friction

numbers measured according to ASTM E274, data relating to weather conditions and

pavement temperature were also recorded. Mitchell and his co-workers found that the

effect of pavement temperature on skid resistance appears to be of no significance

whatsoever.

2.2.11 Overview of Polishing, Friction, and Texture Measurements

Many equipment types and methods have been used over the years to achieve

accelerated polishing on aggregate and HMA specimens and to quantify friction and

texture properties (Wallman and Astrom, 2001). A review of these equipment and

methods is summarized in the following sections.

2.2.11.1 Existing Accelerated Polishing Machines

A review of the existing laboratory-scale accelerated polishing devices reveals that they

can be categorized into three groups: one is capable of polishing the aggregate samples,

the other one is capable of polishing the HMA samples, and the third is capable of

polishing both (aggregate and HMA specimens). A brief review of the existing devices

in each category follows.

38

2.2.11.1.1 Polishing Devices for Aggregates:

Within this category, there are three existing devices: British Polishing Wheel,

Michigan Indoor Wear Track, and Micro-Deval device.

2.2.11.1.1.1 British Polishing Wheel

Most polishing machines on aggregates specimens work on the principle of reducing

the microtexture of the aggregate. For example, the ASTM D3319 British Polishing

Wheel method allows the curved specimens (aggregate coupons) clamped around the

periphery of the wheel assembly to form a continuous strip of aggregate particles. The

wheel is then rotated against a rubber-tire wheel that provides the polishing action.

Silicon carbide grit No. 150, with a feeding rate of 6 ± 2 g/min along with distilled

water at a rate of 50 - 75 ml/min, is used to help accelerate the polishing. The aggregate

specimens are formed by mounting uniformly-sized coarse aggregate particles by hand

in a curved mold and holding them in place with a bonding agent (polyester or epoxy

resin). A catalyst could be used for faster curing of the resin. The companion British

Pendulum Tester (BPT) specified in ASTM E303-93 is used to measure specimen

friction values. The British polishing wheel is used for polishing microtexture of

aggregate coupons only; however, it does not have the ability to alter macrotexture of

aggregates or to test HMA specimens. In addition and as described above, the

procedure used to prepare the aggregate coupons for polishing test is tedious and time

consuming.

39

2.2.11.1.1.2 Michigan Indoor Wear Track

The Michigan Department of Transportation (MDOT) wear track device uses the full-

scale smooth tires to polish coarse aggregate specimens. After polishing, the specimens

are subsequently tested by a laboratory version of the ASTM towed friction tester.

According to Dewey et al. (2001), the circular wear track is very large, with a diameter

of 7 ft. It accommodates 16 trapezoidal specimens. The individual specimens have

parallel sides of 15.5 and 19.5 inch and non-parallel sides of 11 inch. Two wheels, with

normal forces of 800 lb, pivot around the center. This device is used for polishing

coarse aggregates only. It is by far the largest polishing device found. As can be

imagined, sample preparation procedure is not only cumbersome but also time-

consuming.

2.2.11.1.1.3 Micro-Deval Device

The Texas Transportation Institute (Luce et al., 2007) uses the Micro-Deval device as

the mechanism to polish aggregates. The results showed that the Micro-Deval test is an

effective method for polishing aggregates within a short time (180 minutes). The

Micro-Deval device can only polish aggregates and not HMA specimens.

2.2.11.1.2 Polishing Devices for HMA:

Within this category there is one device that is the National Center for Asphalt

Technology.

40

2.2.11.1.2.1 NCAT Polishing Machine

The National Center for Asphalt Technology (NCAT) laboratory-scale accelerated

polishing device is designed to polish the HMA surface. The NCAT (Voller and

Hanson, 2006) follows the same polishing principle as a Circular Track Polishing

Machine. The NCAT machine could polish the area sufficiently large to accommodate

the required measurements with the Dynamic Friction Tester (DFT) and Circular

Texture Meter (CTM) to measure friction and texture, respectively. The NCAT

polishing equipment uses three pneumatic tires made of resin or hard rubber, 8 inch in

diameter, to polish an annulus that occupies a nominal 24 inch square slab. With rubber

tires, water is used to wash the abraded rubber particles off the specimen surface during

polishing. Dead weights are used to produce a total vertical force of 150 lb through the

three wheels. Up to 100,000 revolutions at 40 rpm have been successfully applied to

reach the terminal friction values of the HMA surface. NCAT uses a modified linear

compactor to produce the slabs (24 inch square area) for polishing test. A somewhat

prolonged test time, up to 41.7 hours, has been recorded by NCAT in order to reach the

terminal friction values.

2.2.11.1.3 Polishing Devices for Aggregates and HMA:

Three devices exist within this category: NCSU Wear and Polishing Machine,

Wehner/Schulze Polishing Machine, and Penn State Reciprocating Polishing Machine.

41

2.2.11.1.3.1 North Carolina State University Wear and Polishing Machine

Circular Track Polishing Machines represent yet another type of polishing concept.

Some of these polishing machines can be used for polishing either aggregate specimens

or HMA specimens. The North Carolina State University (NCSU) Wear and Polishing

Machine, as specified in ASTM E660, utilizes four individually mounted, free rolling

wheel assemblies that pivot about a central shaft. The four wheels are loaded to 72 lb in

vertical force. The tires are 11 inch in diameter and made of smooth nylon. Twelve

specimens (aggregate or HMA mixes) are arranged around the perimeter of the track

for polishing. The overall diameter of the track, to the center of the polishing wheels, is

36 inch. After 8 hours of polishing action, the surface friction of each specimen is

measured using either the British Pendulum Tester (BPT) or the Variable Speed

Friction Tester (VST). The test does not use slurry or water. Although the device is

fairly large, it nevertheless polishes only a relatively small area of the specimen

surface.

2.2.11.1.3.2 Wehner/Schulze Polishing Machine

The Wehner/Schulze polishing machine was developed in Germany 30 years ago (Do

et al., 2007). It is comprised of two heads to facilitate polishing and friction

measurement, respectively. Specimens are cores with the diameter of 8.9 inch. They

can be taken from asphalt pavement or laboratory-prepared slabs (aggregate or asphalt

specimens). The polishing action is achieved by means of three rubber cones mounted

on a rotary disc, which rolls on the specimen surface. The rotation frequency is 500

rpm, giving a linear speed of (17 km/h) 10.6 mph. The contact pressure between the

42

cones and the specimen surface is 58.0 psi. The slip between the cone and the specimen

surface is between 0.5% and 1%, which is roughly the slip between rolling tires and

roads. A mix of water with quartz powder is sprayed on the specimen surface during

the polishing action. The surface is polished on a ring of roughly 6.3 inch in diameter

and 2.4 inch in width. At each stop, water is sprayed on the specimen surface and 500

rotations are performed using the cones to wash all debris. This machine is not

designed to handle typical specimen size compacted from the gyratory compactor.

2.2.11.1.3.3 Penn State Reciprocating Polishing Machine

The Penn State Reciprocating Polishing Machine (Nitta et al., 1990), ASTM E 1393,

represents a different style of polishing concept. It can be used in a laboratory or in the

field to polish aggregates or HMA. In essence, a 3.5 by 3.5 inch rubber pad is oscillated

back and forth on the specimen surface on which abrasive slurry is sprayed as well.

Some of the critiques about this device include the relatively small polishing area (4.5

inch by 6.5 inch), the polishing action can only affect the aggregate macrotexture, and

reciprocal movement.

2.2.11.2 Friction Measurement Methods

When a tire is braked from free rolling situation to locked wheel the friction force

experienced by the wheel hub changes depending on the slip (the ratio between slip

speed and operating speed). This is illustrated in the typical friction-slip curve shown in

Figure 2-10. The maximum friction is normally found at a slip rate of about 7-20% and

can be considerably higher than the locked wheel friction (100% slip).

43

Figure 2-10: Friction-slip curve of a braking tire (reproduced from Federal Aviation

Administration 1971)

Pavement surface friction can be measured using one out of four different principles:

locked wheel (100% slip), side force, fixed slip (normally between 10 and 20% slip),

and variable slip (0 to 100% slip). In addition, some of the systems detect the peak

friction and some vary the slip in an attempt to operate around the peak friction level.

Each method of measuring friction has advantages. Direct use of the values produced

by any one type of measurement relates to a different scenario. The locked wheel

method simulates emergency braking without anti-lock brakes, the side force method

measures the ability to maintain control in curves, and the fixed slip and variable slip

methods relate to braking with anti-lock brakes. These friction-measuring methods and

the respective devices are summarized and discussed herein.

44

2.2.11.2.1 Locked Wheel Friction Devices

The pavement surface skid resistance is most often measured by the skid trailer (Luo,

2003). The skid trailer consists of a truck containing a large water tank for wet testing

and a trailer with a locking mechanism on one wheel (see Figure 2-11). The locked

wheel trailer can be used to test the frictional properties of the pavement surface at any

speed up to 96.6 km/h (60 mph). The standard test procedure for the locked wheel skid

trailer is described in detail in the ASTM E274 specification. The test begins with the

attainment of the desired test speed, usually at 64 km/h (40 mph). An activator, located

inside the truck, is used to initiate the test sequence beginning with the application of a

thin layer of water to the pavement surface. Usually, a nominal water film of 0.5 mm is

used. After the correct amount of water has been applied, the test wheel is locked and

instrumentation on the trailer records the sliding force of the locked tire. This test

allows for the computation of the skid number by dividing the tractive force applied to

the tire to the vertical load applied to the tire.

Measuring skid resistance of wet pavement by the standard locked wheel skid trailer

device involves a complex tire-pavement interaction, affected by the variables such as

the tire used, pavement surface texture, age of pavement in service, and temperature of

the contacting surfaces (Davis, 2001). Among the testing variables of a locked wheel

device, one critical decision would be whether to use the ribbed (ASTM E501) or

smooth tires (ASTM E524). The smooth tire is sensitive to both the microtexture and

macrotexture of the pavement. On the other hand, the grooves in the ribbed tire provide

channels much larger than the pavement macrotexture for water flow. Consequently,

45

the friction measurement by the ribbed tire is insensitive to the macrotexture, but

sensitive to microtexture (Li et al., 2003). Figure 2-12 shows pictures of ribbed tire and

smooth tire.

Figure 2-11: Locked Wheel Skid Trailer

Figure 2-12: Ribbed tire versus smooth tire

46

2.2.11.2.2 Side Force Coefficient Devices

The side force coefficient is measured by a test that uses a freely rolling wheel to

determine the frictional properties of the pavement. This type of test uses a wheel that

is mounted at an angle to the direction of motion of the test vehicle. The force that is

produced on the sideways mounted wheel is used to calculate the friction coefficient of

the pavement surface. This method has been used for many years and can be performed

using a motorcycle and a sidecar (Alsopp, 1985).

Two examples of equipment that utilize the side force coefficient methodology to

measure surface friction are the Sideways Force Coefficient Routine Investigation

Machine (SCRIM) and the MuMeter. Both of these pieces of equipment were

developed in Britain (NCHRP Synthesis 291, 2000). The SCRIM (Figure 2-13) was

originally developed by Transport and Road Research Laboratory (TRRL) in United

Kingdom about 1953 and is a rebuilt truck with a measuring wheel placed between the

front and the rear axle. The measuring wheel is a special motorcycle wheel mounted

with a constant side slip angle of 20 degrees. During measurement the wheel is rotating

freely and the road surface friction is evaluated as the lateral force acting on the free

rolling wheel divided by the load on the wheel, the results is called the Sideway-Force

Coefficient (SFC). SCRIM uses the sideway-force method of measuring resistance to

skidding because it is more suitable for routine measurement (Hosking and Woodford,

1976b) than the locked wheel method. Tests are normally carried out at 50 km/h (31

mph).

47

Figure 2-13: Sideways Force Coefficient Routine Investigation Machine (SCRIM)

The MuMeter (shown in Figure 2-14) is used for airports and has been used since the

1970’s by the Department of Transportation in Arizona. The MuMeter is a lightweight

three-wheeled trailer that does not require a special towing vehicle. Two of the smooth-

treaded wheels on the trailer are used to measure the friction of the surface while the

third wheel is a stabilizing wheel. The two test tires are at an angle of 15 degrees to

allow for the sideways force coefficient to be measured. Attached to the trailer is a unit

that records the friction values as the test occurs. The MuMeter measures the dry

friction of the pavement surface, as well as the wet pavement friction if a wetting

system were included in the towing vehicle. The side force coefficient that is obtained

from this type of equipment is calculated by dividing the sideway force to the vertical

reaction between the test wheel and the road surface (Alsopp, 1985).

48

Figure 2-14: Side force tester: the MuMeter (Tomita 1964)

2.2.11.2.3 Fixed Slip Devices

Fixed slip friction measurement devices are primarily used in European countries.

Fixed slip testers operate with a constant rate of slip, typically around 10% to 20%.

This allows for the maximum friction value of the roadway surface to be measured.

The amount of slip is controlled by hydraulics or by allowing the chain drive of the

tester to be lower than that of the testing vehicle. Examples of fixed slip devices

include the Runway Friction Tester, the Griptester, the Saab Friction Tester, and the

Portable Friction tester.

The Runway Friction Tester (RFT) is an accurate and repeatable, self contained

continuous friction measuring equipment that provides continuous self-wetted

49

coefficients of friction on airport runways. The RFT, shown in Figure 2-15, is designed

for both maintenance and operational testing to evaluate surface friction changes due to

weather, high usage, aging, and contaminants. The RFT uses a two axis force

transducer mounted on a retractable fifth wheel assembly mounted under the rear truck

bed. The test assembly provides real time vertical load and horizontal tractive force

measurement. System electronics include a laptop computer and ink-jet printer. User-

friendly WindowsXP software allows the operator to control the entire test procedure

including test speed, self wetting or dry testing, test method, test type (manual or

automatic), and annotate airfield test conditions for later reference. All data is stored for

further processing in user-determined formats. Data stored includes the raw load and

traction data, speed, water flow, optionally GPS coordinates and texture data. Friction

numbers can be printed at any desired intervals. Friction data and speed are visible real

time during the test on both the laptop computer and the dash mounted information

display. The system includes 1000 litre (250 U.S. gallon) built in water tank, water

pump and laminar flow water nozzle for self wetting testing of up to 11,000 m (36,000

ft) of runway without refilling. The RFT uses the continuous peak friction test method.

First, the operator selects whether the test is to be dry or self-wetted. Next, the operator

should bring the vehicle up to a test speed of 65 km/h (40 mph) or 95 km/h (60 mph)

prior to reaching the test site. At 65 km/h (40 mph), the friction survey recording

should begin at 152 m (500 ft) from the threshold end of the runway, and terminated

approximately 152 m (500 ft) from the opposite end of the runway. At 95 km/h (60

mph), the friction survey recording should begin at 305 m (1000 ft) from the threshold

50

end of the runway, and terminated approximately 305 m (1000 ft) from the opposite

end of the runway. At the same distances for the respective speeds, the fifth wheel

should be lowered onto the runway pavement surface. While conducting the friction

survey, the vehicle must be held at a constant speed. Peak friction is continuously

calculated by the system’s on-board computer for each test run. Friction measurements

are displayed both graphically and numerically on the laptop’s 15-inch screen and/or

printer and stored on hard disk drive for later transfer to a memory stick.

The Griptester is an excellent small three-wheeled device with the "normal" axle being

connected to the recording wheel by a pair of gears that causes a braking effect on the

axle of the third wheel that can be measured as a "Grip Number". This equipment

(shown in Figure 2-16) can be pushed by hand on a pre-wetted road surface for small

area surveys. Test speeds can vary from 5 km/h to 130 km/h (3 mph to 81 mph)

depending upon application. The measured values can be affected by the test speed.

One can obtain more information on the use of the Griptester from (Lund, 1997 and

Wambold et al., 1995).

The Saab Friction Tester, used in Sweden, operates at a constant slip rate of 17% (see

Figure 2-17). A retractable test wheel subjected to a constant vertical load is located

behind the rear axle of the test car. A chain driven transmission, which allows for the

constant slip rate, is connected to the rear axle and the test wheel. The Saab Friction

Tester measures the wet friction of the pavement surface with the aid of a water pump

attached to the test vehicle. Computers inside the vehicle record the forces acting on the

51

wheel as a result of the slip. The frictional properties of the pavement are reported as

the Brake Force Coefficient (BFC) and are calculated by dividing the retarding or

braking force to the vertical reaction between the tire and the road (Alsopp, 1985).

The Portable Friction Tester (PFT) is a portable manually driven instrument for

measuring the friction on small surfaces (down to 1 m in length) and has been

developed at the Swedish National Road and Transport Research Institute (VTI). It

uses a fixed slip, usually between 17 and 21%. The PFT consists of a three-wheeled

pushcart with the measuring wheel mounted in front of the others (see Figure 2-18).

The friction between the measuring wheel and the surface of interest is presented by the

PFT as the friction coefficient, which is the frictional force on the measuring wheel

divided by the normal load on the same wheel. This friction coefficient is henceforth

referred to as the PFT friction value. Operating the PFT can sometimes be difficult,

especially when measuring on slopes and curves. The PFT is equipped with a

speedometer indicating the appropriate speed, as an aid to the operator. Before the

measurements are started, the cart should be pushed until a certain speed is reached that

should then be kept constant during the entire measurement. Pushing a button on the

handle of the cart starts the measurement; when the section has been measured, the

process is stopped by again pushing the button. The PFT has been compared with the

British pendulum tester (Lundkvist and Linden, 1994; Centrell, 1995; Astrom, 2000)

with the result that it is possible to convert friction values measured by the PFT into

British pendulum numbers, at least in the measurement conditions considered.

52

Furthermore, the repeatability of the PFT measurement has proved to be good and

measurement time is less than with the pendulum.

Figure 2-15: The Runway Friction Tester

(a) Underside of Griptester (b) Griptester attached to towing vehicle

Figure 2-16: The Griptester device

53

Figure 2-17: Saab Friction Tester

Figure 2-18: The portable friction tester for measuring the friction on small surfaces

2.2.11.2.4 Variable Slip Devices

Variable slip friction measurement devices measure the friction of the pavement

surface in a manner similar to the fixed slip devices. During testing, the slip rate of the

test wheel is varied to allow for a range of friction values to be recorded. Japan and

Norway are the primary users of variable slip friction devices to measure the condition

of pavement surfaces.

54

Some examples of variable slip friction measurement devices include the Norsemeter

ROAR used in Norway and the IMAG system used in Japan (NCHRP Synthesis 291,

2000). In Norway Norsemeter has developed a flexible friction measurement unit

called ROAR (Schmidt, 1999). In Figure 2-19, it can be seen in the form of a friction

measurement trailer, including the water supply for wet friction measurements. The

measuring wheel has a smooth tire with an outer diameter of 410 mm (16 inch), ASTM

E1551. It is placed on a separate unit, which include all mechanical parts necessary for

the measurement so that this small unit can act alone and for example measure dry

friction placed directly on a road maintenance truck. During one measurement cycle

(about 1 second), ROAR measures the complete friction-slip curve, from pure rolling to

locked wheel. The device can operate at speeds between 20 and 130 km/h (12.5 and 81

mph).

Figure 2-19: Norsemeter road friction measurement trailer

55

2.2.11.2.5 Other Friction Measurement Methods

In addition to what precedes, there are more available equipment and methods used for

friction measurements.

2.2.11.2.5.1 Dynamic Friction Tester

The measurement of surface friction can also be done by the dynamic friction tester

shown in Figure 2-20. Per ASTM E1911, the test equipment consists of a disk fitted

with three spring-loaded rubber sliders at a diameter of 284 mm (11.2 inch). The disk is

initially suspended above the pavement surface and is driven by a motor until the

desired tangential speed of the sliders is attained. Water then flows over the surface

being tested, so that wet friction is measured similar to the operation of the skid trailer.

The rotating disk is then dropped onto the wet surface with an applied vertical force of

3.6 kg (8 Ib) while the friction is continuously measured as the disk slows down to zero

speed. The friction force and the speed during the spin down are recorded in a file. The

DFT can be used to measure the friction as a function of speed over the range of zero to

90 km/h (0 to 55 mph). The DFT system can be used not only in the field but also on

the laboratory prepared HMA specimen that is at least 450 by 450 mm (17.75 by 17.75

inches) in surface area.

56

(a) Bottom view (b) General view (c) Controller

Figure 2-20: Dynamic Friction Tester: (a) bottom view, (b) general view, and (c)

controller

2.2.11.2.5.2 Pendulum Devices

The British Pendulum Tester per ASTM E303-93 is used widely to measure friction. It

can be used on the curved coupons from the polishing wheel, on flat specimens from a

circular polishing track or reciprocating polisher, or on actual roadway surfaces. The

British Pendulum tester consists of a rubber slider attached to the end of a pendulum

arm as shown in Figure 2-21. As the pendulum swings, it is propelled over the surface

of the specimen. As the rubber slider contacts the surface of the specimen, the kinetic

energy of the pendulum decreases due to friction. This energy loss is measured and

reported as the British pendulum number (BPN) on flat surfaces or the polished stone

value (PSV) for curved aggregate coupons from the polishing wheel. The slider travels

at roughly 10 km/h (6 mph), so is only capable of measuring low-speed friction. Due to

the small size of the rubber slider and its low speed, however, it is widely recognized as

a measure of the microtexture only. The benefits of higher macrotexture cannot be

evaluated. The test procedure is as follows. Typically, the specimen is first immersed

57

in water and then the test surface is cleaned. Next, the BPT device is levelled and

adjusted so that the contact path during the swing of the slider is within the range of

6.1125 mm ( 063.092.4 inch). The rubber slider is cleaned and wetted. Five

swings are made for each specimen, from which an average of the last four readings is

recorded as the BPN.

The North Carolina State University Variable Speed Friction Tester is another

pendulum-type tester; see Figure 2-22. Instead of a rubber slider there is a locked-

wheel smooth rubber tire at the end of the pendulum. A stream of water is sprayed at a

specific velocity in the path of contact of the wheel. By adjusting the velocity of the

water stream, different vehicle speeds can be simulated in the laboratory or in the field.

However, uneven pavement surfaces in the field may provide inaccurate

measurements.

The advantages of this device are that it is portable, has a low initial cost, and can test

in different orientations. Its disadvantages include that results from coarse macrotexture

are questionable, it can only simulate low-speed skidding, and it requires laborious

calibration.

58

Figure 2-21: British Pendulum Tester

Figure 2-22: North Carolina State University Variable Speed Friction Tester

2.2.11.2.5.3 Michigan Laboratory Friction Tester

As a companion to the wear track, the Michigan Department of Transportation

(MDOT) uses a laboratory scale version of a towed friction trailer to measure the

frictional resistance of specimens polished on the wear track. The device, shown in

Figure 2-23, consists of a tire in a stationary frame that is rotated at the equivalent of 64

km/h (40 mph) then is dropped onto a specimen clamped onto the frame under a spray

59

of water. The torque produced as the tire slows due to friction with the specimen is

measured, and the peak torque is used as an indicator of the surface friction of the

specimen (McDaniel and Coree, 2003). A major problem with this method for the

purposes of this study is that it is used on uniformly sized coarse aggregate only. It

provides no assessment of macrotexture effects, and there is no history of using it for

pavement specimens instead of aggregates only.

Figure 2-23: Michigan Laboratory Friction Tester

2.2.11.2.5.4 PTI Friction Tester

Along with the Penn State Reciprocating Polishing Machine, the Pennsylvania

Transportation Institute (PTI) also developed a companion friction tester. The PTI

friction tester used a freefalling weight to propel a rubber slider in a linear path along a

surface. The frictional resistance is determined from the speed of the slider across the

surface. A surface with higher friction would slow the slider more than a smooth

surface.

60

2.2.11.2.5.5 Stopping Distance Method

Stopping distance methods is a field technique in characterizing pavement surface skid

resistance (ASTM E445/E445M). In this method, a four-wheel passenger vehicle is

used in which all four wheels are equipped with a braking system. The pavement in the

test lane is wetted. The test vehicle is brought above the desired testing speed and is

permitted to coast onto the wetted section until the proper speed is attained. The brakes

are then promptly and forcefully applied to cause a quick lockup of the wheels and to

skid to a stop. The distance required to stop is recorded with the aid of instrumentation

and reported as the stopping distance (SD). Using the recorded stopping distance and

the velocity of the vehicle upon application of the brakes, the stopping distance number

(SDN) can be calculated:

100255

2

SD

VSDN (2-8)

Where:

SDN = Stopping Distance Number,

V = Speed of the vehicle at the moment of brake application in km/h, and

SD = Stopping distance in meters.

The SDN can be used to evaluate pavement friction but does not report a coefficient of

friction. It is helpful in determining the relative adequacy of friction of different

61

pavement surfaces but does not correlate to other skid resistance measurements (ASTM

E445).

2.2.11.2.5.6 Wehner/Schulze Friction Device

As mentioned earlier, this machine comprises two heads for the polishing and the

friction measurement. After the washing period, the specimen is moved manually to the

friction-measuring head. This head is composed of three small rubber pads (0.6 in2 area

for each pad) disposed at 120 on a rotary disc. The contact pressure between the

rubber pads and the specimen surface is approximately 29 psi. For the friction

measurement, the disc is launched until a speed of 100 km/h (62 mph) at its

circumference is reached. When the speed reaches 90 km/h (55.9 mph), water is

projected on the specimen surface. At 100 km/h (62 mph), the motor is stopped and the

disc is dropped until the rubber pads touch the specimen surface. The rotation is

stopped by friction between the rubber pads and the specimen surface and then the

friction–time curve is recorded.

2.2.11.3 Texture Measurement Methods

The levels of pavement texture that affect friction are microtexture and macrotexture. If

both microtexture and macrotexture are maintained at high levels, they can provide

resistance to skidding on wet pavements (NCHRP Synthesis 291, 2000). A study

conducted in Europe (Roe et al., 1998) reported that increased macrotexture reduces

total accidents, under both wet and dry conditions. There are a variety of ways to

measure pavement texture, ranging from simple, indirect estimates to extremely high-

62

tech direct measurements. Technological advances make direct measurement more

feasible now than in the recent past. Literature pertaining to these methods was

collected and is presented herein.

2.2.11.3.1 Microtexture Measurement

Currently there is no system capable of measuring microtexture profiles at highway

speeds. A profile of the microtexture of an in-service pavement surface also could be

misleading (NCHRP Synthesis 291, 2000). The portions of the pavement surface that

contact the tires are polished by traffic, and it is the microtexture of the surface of the

exposed aggregate that comes into contact with the tire that influences the friction. The

valleys are not subjected to polishing and their contribution to the overall microtexture

should not be included in prediction of friction.

Because of the difficulty in measuring microtexture profiles, a surrogate for

microtexture is generally preferred. In research at the Pennsylvania State University

(Henry and Leu, 1978), it was found that the British Pendulum Numbers (BPNs) were

highly correlated with the parameter o of the Penn State Model (Equation 2-1). The

parameter, o, is the zero speed intercept of the friction-speed curve and characterizes

the friction at low slip speeds. The slider of the BPT engages only the portion of the

asperities that are subject to polishing by traffic and therefore the BPN values could be

considered as the surrogate for microtexture.

The values of the friction measured by the dynamic friction tester when the slip speed

is 20 km/h (12.5 mph) are highly correlated with BPN values (NCHRP Synthesis 291,

63

2000). This indicates that DFT friction values at 20 km/h (12.5 mph) could also be used

as an indirect measurement of the microtexture or as the surrogate for microtexture.

In the United Kingdom, the SCRIM values are synonymous with microtexture. The

SCRIM is a side force coefficient measuring device and therefore the sliding speed of

the test tire is relatively low. The SCRIM operates at traffic speeds; however, because

the slip speed is low, it serves as a surrogate for a microtexture measurement.

The PIARC Model for the IFI avoids the need for measuring microtexture, if

macrotexture measures are available. A friction measurement at any slip speed,

together with the macrotexture parameter, determines the friction as function of slip

speed.

There is currently no practical procedure for the direct measurement of the

microtexture profile in traffic. Such a procedure would possibly enable testers to avoid

the friction measurement altogether by measuring microtexture and macrotexture in

order to predict the wet pavement friction as a function of speed. This would eliminate

the need to carry water and use a high-powered host vehicle (NCHRP Synthesis 291,

2000).

2.2.11.3.2 Macrotexture Measurement

The different macrotexture measurement methods are summarized below.

64

2.2.11.3.2.1 Volumetric Measurements

The Sand Patch Method (ASTM E965) is used to measure macrotexture of the

specimen surface. This method involves taking a known volume of a spreadable

material and spreading it out in a circle on the surface of the specimen. Measuring the

diameter gives the area of the circle. The Mean Texture Depth (MTD) is determined by

dividing the volume by the area. Figure 2-24 illustrates the procedure followed to

measure the MTD and the required tools for the sand patch method.

Another volumetric measure of macrotexture is the grease patch method developed by

the National Aeronautics and Space Administration (NASA). This method is similar in

concept to the sand patch, except that grease is spread over the surface in a rectangular

area between parallel strips of masking tape. Again, the average macrotexture depth is

determined by dividing the known volume of grease by the area covered.

A third volumetric approach uses the same concept of spreading a known volume of

material over a measured area is the silicone putty, or Silly Putty. In this method, a

fixed amount of putty is pressed onto the surface using a plastic disk with a round

recess whose volume equals that of the putty. When pressed onto a surface with

texture, the amount of macrotexture is indicated by the diameter of the putty.

T

su

cy

w

th

th

a

ou

an

ou

b

B

Fi

2.2.11.3.2.2

The outflow

urface macro

ylinder is sup

with water, a

hrough the v

hat water wil

smooth text

utflow mete

ny additiona

utflow mete

etween the b

Buhlmann, 19

gure 2-24: M

2 Outflow M

meter, show

otexture. A c

pposed to m

and the time

voids and ch

ll flow faster

ture that seal

er gives an a

al informati

r to truly giv

bottom of th

982 and NCH

MTD determ

Meter

wn in Figure

cylinder is p

meet the pave

e for a know

hannels on th

r if the pave

ls better to th

average value

on about th

ve an indicat

he rubber gas

HRP Synthe

65

mination usin

e 2-25, uses

placed on the

ement surface

wn volume o

he pavement

ment has a r

he rubber rin

e for the pav

he distributio

tion of surfa

sket and the

sis 291, 200

g the sand p

the rate of

e pavement.

e as would a

of water to

t surface is

rough texture

ng. As with t

vement mac

on or nature

ace macrotex

top of the p

0).

patch method

flow of wat

A rubber ri

a tire. The cy

escape from

measured. T

e than if the

the volumetr

crotexture, bu

e of the tex

xture, the wa

pavement lay

d

ter to estima

ing around th

ylinder is fill

m the cylind

The concept

pavement h

ric devices, th

ut cannot giv

xture. For th

ater must dra

yer (Yager an

ate

he

ed

der

is

has

he

ve

he

ain

nd

66

Figure 2-25: Outflow meter

2.2.11.3.2.3 Profile Tracers

The development of this method has been attempted by many investigators. In 1980,

Gillespie reported on a profile tracing device and showed some correlation between

profile parameters and skid resistance. In 1967, Hankins reported in the development

and testing of a highly sensitive profile tracing device to be used in the laboratory. By

analysing the plot of the profile parameters and skid resistance, it revealed a wide

scatter of points which limit the usefulness of this approach.

The pavement surface macrotexture can be accurately measured by an advanced laser

profiling technology. The circular texture meter (CTM) shown in Figure 2-26

represents one of such advanced laser based profiler or macrotexture measurement

device. The test procedure using the CTM has been standardized in ASTM E 2157. In

essence, the CTM uses a laser to measure the profile of a circle 284 mm (11.2 inch) in

diameter or 892 mm (35 inch) in circumference. The circumference is divided into

eight segments of 111.5 mm (4.4 inch) arc. The average MPD is determined for each of

67

the segments of the circle. The data process is carried out as follows: (a) the

circumferential annulus is divided into eight segments of 4.4 inch arc, (b) the Mean

Segment Depth is determined according to the schematic diagram in Figure 2-27 for

each segment in accordance to ASTM E1845, and (c) the final reported MPD of the

test specimen is the average of all eight Mean Segment Depths. In addition to the MPD

reported by the CTM, Root Mean Square (RMS) can also be reported. RMS is a

statistical value of how much the actual measured profile deviates from a best fit

modelled profile of the data. The capability of the CTM to quantify MPD and RMS

allows for the assessment of the “orientation” of texture, which in turn enables the

engineer to determine what types of features are supplying the macrotexture; i.e.,

negatively, positively, or neutrally textured (McGhee and Flintsch, 2003).

In 2004, Hanson et al. evaluated the circular texture meter for measuring surface

macrotexture of pavements. They reported that the CTM produces comparable results

to the ASTM E965 Sand Patch Test. When open-graded mixtures were excluded; this

study indicated that the offset was non-significant between CTM and Sand Patch test

results. The slope of the best fit line comparing the results was statistically significant,

and ranged from 0.93 (2003 data) to 1.01 (2000 data).

T

T

p

tr

(a

Figure 2-

The Kansas H

This method

otentiometer

ransversely u

a) Bottom vie

-26: Circular

Figure 2

Highway Co

uses a mo

r attached t

under the m

ew

r Texture M

2-27: Mean S

ommission d

otorized lath

to the micro

microscope.

68

eter: (a) gen

Segment De

developed a m

he and a ste

oscope focu

The operat

(b) G

neral view, an

epth determin

method calle

ereo microsc

using shaft.

or keeps th

General view

nd (b) bottom

nation

ed linear tra

cope with t

The specim

he surface u

w

m view

averse metho

the shaft of

men is mov

under consta

od.

f a

ed

ant

69

focus, thus changing the potentiometer voltage. This results in a tracing of the surface

macrotexture.

Texas Transportation Institute developed a device called texturemeter, consisting of a

series of evenly spaced vertical parallels in a frame. With the exception of two, the rods

can move vertically and are independent of one another. A string is attached to the

movable end and to the frame. The texturemeter produces a straight line on a smooth

surface and a dial indicator has been calibrated to zero. If there are any irregularities,

the string produces a zigzag line and results in a dial reading greater than zero. The

reading is proportional to the coarseness of the macrotexture: the coarser the surface,

the higher the reading.

70

CHAPTER III

3. A NEW ACCELERATED POLISHING DEVICE FOR HMA SURFACES

3.1 Introduction

With time and traffic, asphalt concrete pavements gradually lose their skid resistance,

creating a serious safety concern especially when pavements are wet. As the driving

speed and the Average Daily Traffic (ADT) increases, the chances of having skid-

related accidents also increase rapidly (Beaton, 1976 and Brilett, 1984). Thus, the

Federal Highway Administration has issued a Wet Skid Accident Reduction Program

to encourage each state highway agency to minimize wet weather skidding accidents

by identifying the sections of roadways with high occurrence of skid accidents and then

by either resurfacing of the pavement or rejuvenating surface texture to bring the

asphalt pavement surface to an adequate skid resistance properties. However, the cost

associated with the regular identifying and the remediation action could be extensively

high. An alternative approach would be to take a more proactive stand in screening the

polishing potential of aggregates and hot mix asphalt to ensure that the final selected

mix can provide sustained resistance to polishing while providing adequate level of

friction over the life span of the pavement. To achieve this initial screening task during

the mix design stage of the HMA, there is a need to develop a laboratory scale

71

accelerated polishing device that can mimic the actual abrasion and polishing behavior

between the vehicle rubber tire and the HMA surface.

The main objective of this chapter is to present a laboratory-scale accelerated HMA

polishing device for the purpose of screening the polishing and friction performance of

the HMA mix, in terms of aggregate source, aggregate gradation, and binder type and

content that constitute the important physical constituents of the HMA. This polishing

device should be capable of reproducing the tire-pavement interaction in a reasonable

timeframe, easy to operate with less labor effort, and has the ability to test small size

HMA specimens (e.g., 6 inch in diameter gyratory compacted specimens). The

operation principles along with the operation conditions of the polishing device are

described in detail. The performance of the accelerated polishing test device is

evaluated and described in detail as well. The acceptance criteria are presented for

screening the HMA specimens from the polishing and friction standpoint. The

advantages and limitations of the developed device are presented at the conclusion of

the chapter.

3.2 Existing Laboratory Scale Polishing Devices

In the past efforts in developing laboratory-scale accelerated polishing devices, several

key mechanisms involved in polishing either aggregate or HMA have been identified.

As reviewed in Ibrahim (2007), the skid resistance of asphalt concrete can be affected

by bleeding and flushing of bituminous binder to the surface, surface wear due to

studded tires, polishing of surface aggregate, rutting due to compaction, lateral

72

distortion, contamination (rubber, oil, water, etc.), smoothened macrostructure, and

inadequate cross slope. Among these factors, however, aggregate and mixture

characteristics remain the most dominant controlling factors. Research focused on

polishing and friction characteristics of aggregates (Colony, 1984; Colony, 1992; Liang

and Chyi, 2000; Liang, 2003; Dewey et al., 2001; and Do et al., 2003) have shown

strong correlations between the time history of skid number (SN) at the monitored

pavement sections and the factors such as traffic conditions, properties of asphalt

mixes, and geological features; i.e., predominant aggregate and physiographic area. In

the research on aggregate friction loss (Liang and Chyi, 2000), the aggregate polishing

propensity can be identified by means of a suite of test procedures, including the use of

mineralogical analysis using thin sections and Acid Insoluble Residue test (ASTM D

3042-03). Thus, the current understanding of aggregate polishing and friction behavior

is well established.

A review of the existing laboratory-scale accelerated polishing devices reveals that they

can be categorized into three groups: one is capable of polishing the aggregate samples,

one is capable of polishing the HMA samples, and the third is capable of polishing both

(aggregate and HMA specimens). A brief review of the existing devices is summarized

in Table 3-1.

3.3 Equipment Development

In the following section, the newly developed equipment and its operational procedure

along with the operation conditions are discussed in detail.

73

3.3.1 Equipment Description and Operational Procedure

The guiding principle of developing the laboratory-scale accelerated polishing

equipment is that the evolution history of friction loss of the asphalt pavement surface

can be accurately replicated and measured in realistic short test duration. In essence, the

abrasive action between the rubber tire of a vehicle and asphalt concrete pavement

surface will be enacted in the accelerated polishing device. The deign of the polishing

equipment allows for pressing polishing shoes (pads) made of Styrene-Butadiene-

Rubber (SBR) onto the surface of the HMA specimen at a constant vertical force while

rotating these rubber pads at a constant rotational speed. It should be noted that the

polishing device is designed to accommodate two specific specimen dimensions: an 18

inch by 18 inch by 2 inch high roller compacted slab specimen or a 6 inch diameter by

4 inch high Superpave gyratory compacted specimen. As a result of different specimen

sizes, the rubber pads are designed differently. For the gyratory compacted specimen, a

solid rubber disk of 6 inch in diameter and 1.5 inch thick is used. For the slab

specimen, a rubber ring of approximately 13 inch in outside diameter and 9 inch in

inside diameter is used to fit with the required polishing area for the DFT and CTM.

The schematic diagram of the equipment is presented in Figure 3-1, in which Figure

3-1(a) and Figure 3-1(b) show the top view and elevation view, respectively.

Details of the rubber pad dimension for the gyratory specimen and large slab

specimen are shown in Figure 3-1(c) and Figure 3-1(d), respectively. A photograph

of the completely fabricated accelerated polishing device is shown in

74

Figure 3-2(a), with the close-up view of two types of specimens mounted in

positions shown in Figure 3-2(b) and Figure 3-2(c),respectively.

Table 3-1: A summary of the existing accelerated polishing machines

75

1.5 HP MOTOR

ADD WEIGHTFOR ADDITIONALPRESSURE

A33.75

33.75

(a) Top view of the accelerated polishing machine using rubber shoes

34.25

20.00

14.25

42.625

26.375

9.437

ADJUST HEIGHT OFRUBBER PADS WITH CRANK

1/2 NPT NIPPLEFOR FLUID

HMA SAMPLE

SHROUD

BUILT FORM

DOLLY28.00

ELECTRIC BOX

B BB1B1

(b) Section A-A for the machine details

Figure 3-1: Different views of the accelerated polishing machine using rubber

shoes; all units are in inches

76

( 13.75 DRIVE PLATE)

( 1.500 OD X 0.075 ID SHAFT)

( 0.25 HOLES FOR WATER, 2 PLACES)

( 13.50 OD OF RUBBERBLOCK MOUNT RING)

( 8.75 ID OF RUBBERBLOCK MOUNT RING)

(13 OD X 9 ID RUBBER SHOE)

(c) Slab specimen rubber shoe

(13.75 DRIVE PLATE)

( 13.50 OD X 8.75 IDSPACER RINGS)

( 0.25 HOLES FOR WATER, 2 PLACES)

( 6.00 SBR RUBBER SHOE)

( 1.500 OD X 0.075 ID SHAFT)

(GROOVE FOR WATER)

(d) Gyratory specimen rubber shoe

Figure 3-1: Different views of the accelerated polishing machine using rubber

shoes; all units are in inches

77

(a) Overall view of the accelerated polishing machine using rubber shoes

(b) Details on slab specimen mounting

78

(c) Details on gyratory compacted specimen mounting

Figure 3-2: Overall view of the accelerated polishing machine using rubber shoes

and setups for testing slab specimen and gyratory compacted specimen

3.3.2 Operation Conditions

The design of the device includes individual control for the vertical force on the

specimen, the rotational speed of the rubber pad, and the rate of water spray on the

specimen surface during polishing. The range of these individual controls is presented

in Table 3-2.

In an effort to determine an optimum operation condition, the authors have conducted a

series of tests on the HMA specimens using different combinations of operation

79

conditions, including the type of rubber to be used for the rubber pads, the rotational

speed of the rubber pad, the vertical force applied by the rubber pad to the HMA

specimens, and the rate of water spray. The final selected operation conditions are

summarized in Table 3-2 as well. These optimum operation conditions would ensure

that the rubber pad would not experience rocking motion, and that more or less flat

contact surface between the rubber pad and the specimen is maintained. Furthermore,

the water spray is to ensure that the rubber debris was washed off and that rubber-

specimen surface was not overheated.

Table 3-2: Range of and selected optimum operation parameters

3.4 Equipment Characteristics and Validation

In this section, the repeatability of the test results from the developed accelerated

polishing device is discussed. Furthermore, the ability of the polishing device to

replicate the polishing trend of the aggregate is demonstrated.

80

3.4.1 Materials

In the evaluation study of the developed device, two aggregate sources (limestone and

gravel) and two asphalt binder grades (PG 70-22 and PG 64-22) were used to compact

the HMA specimens. The gradation curve for the aggregate is shown in Figure 3-3. The

optimum binder content is determined by using Marshall Design method. The optimum

binder content is 5.9% and 6.3% for the mix consisting of limestone and PG 70-22

binder and the mix consisting of gravel and PG 64-22 binder, respectively.

Figure 3-3: Gradation curves

3.4.2 Sample Preparation Procedure for HMA Specimens

The mixing procedure of the loose mix is as follows. First, the aggregates are separated

by dry sieving into the desired sizes using the mechanical shaker. The aggregates are

then washed and heated to about 330˚F. Aggregates are weighed and blended according

0

20

40

60

80

100

120

0.001 0.01 0.1 1

Grain size (in)

Pe

rce

nt

fine

r

Limestone

Sand & Gravel

81

to the gradation curve shown in Figure 3-3. The weighed aggregate mix is then put in

the oven at 330˚F for 3 hours for achieving a uniform aggregate temperature. The

mixing bowl and the mixing paddle are also heated to 300˚F. The asphalt binder is

heated in the oven at a temperature of 350˚F for 2-3 hours. At this point, the aggregate

is placed in the mixing bowl and blended quickly with the asphalt binder until a

uniform blend is obtained.

The gyratory compactor is used to compact the loose mix into a 6-inch cylindrical

specimen, while a roller compactor is used to compact the loose mix into a 18 inch by

18 inch by 2 inch slab specimen.

3.4.3 Friction and Surface Texture Measurements

Different types of measuring techniques are used to measure friction and texture of the

HMA surface for the two types of specimen sizes due to different polishing rubber pads

used (see the description of the rubber polishing pads). For the 6 inch cylindrical

gyratory compacted HMA specimens, the British Pendulum Tester and the sand patch

method are used for measuring friction and surface texture. For the 18 inch by 18 inch

by 2 inch roller compacted specimens, the DFT and CTM are used for measuring

friction and texture, respectively. A brief description of each measurement technique is

presented herein.

The BPT (ASTM E303-93) test procedure is as follows. Typically, the specimen is

first immersed in water and then the test surface is cleaned. Next, the BPT device is

82

levelled and adjusted so that the contact path during the swing of the slider is within the

range of 063.092.4 inch. The rubber slider is cleaned and wetted. Five swings are

made for each specimen, from which an average of the last four readings is recorded as

the British Pendulum Number (BPN).

The sand patch method (ASTM E965) is a technique to measure macrotexture of the

HMA surface. This method involves taking a known volume of a spreadable material

and spreading it out in a circle on the surface of the specimen. The Mean Texture

Depth (MTD) is determined by dividing the volume of the spread material by the

surface area covered by the spread material. This technique is used for the 6 inch

gyratory compacted specimen due to the ease associated with a small area to cover.

The test procedure of DFT is given in ASTM E1911. The DFT device consists of a disk

fitted with three spring-loaded rubber sliders at a diameter of 11.2 inch. The disk is

initially suspended above the pavement surface and is driven by a motor until the

desired tangential speed of the sliders (about 55 mph) is attained. Water is then flowed

over the test surface. The rotating disk is then dropped onto the wet surface with the

applied vertical force of 8 lb while the friction force and speed of the rotating disk are

continuously measured and recorded as the disk slows down to stop (zero speed).

The CTM is described in ASTM E2157. In essence, it uses laser techniques to measure

the surface texture profile of an annulus surface area (i.e., 11.2 inch in outside diameter

and 10 inch in inside diameter). The data process is carried out as follows: (a) the

circumferential annulus is divided into eight segments of 4.4 inch arc, (b) the Mean

83

Segment Depth is determined for each segment in accordance to ASTM E1845, and (c)

the final reported MPD of the test specimen is the average of all eight Mean Segment

Depths.

3.4.4 Supplemental Image Analysis Techniques

Digital image analysis techniques are used to quantify the percentage of the exposed

aggregate area of the specimen surface after being subjected to polishing by the

accelerated polishing device. The percent of exposed aggregate area is defined as the

area of the exposed aggregate surface divided by the total area of the HMA specimen

surface that is being polished by the device. The typical image analysis procedure

involves first taking the digital images of the specimen surface using the Olympus C-

5060 Wide Zoom high-performance 5.1-megapixel digital camera. The digital images

are then opened in the software (Scion image provided by National Institutes of Health)

and converted into binary images for the subsequent calculation of exposed aggregate

area.

3.4.5 Repeatability of the Accelerated Polishing Equipment

The repeatability of the polishing results using the developed accelerated polishing

device was examined. For each set of specimens made of the same mix formula

(aggregate source, aggregate gradation, optimum binder content, binder type, and

compaction method and effort), three replicate specimens were tested. The friction

values obtained from the BPT, the MTD measured by the sand patch method and the

84

image analysis results (Agg. %) from the three replicates are statistically analyzed

using Homogeneity of Variance (Levene statistic), one-way Analysis of Variance

(ANOVA), and Multiple Comparisons to check for the repeatability of test results.

Homogeneity of Variance and one-way ANOVA are used to check if there is any

significant difference between the variances and the means of at least two specimens

for each set of specimens (three specimens) made of the same JMF. Multiple

Comparisons, on the other hand, is used to check if there is any significant difference

between the means of different two-specimen combinations of the three specimens

made of the same JMF. The software Statistical Package for the Social Sciences

(SPSS) was employed for obtaining the statistical analysis results. Table 3-3

summarizes the statistical analysis results. It can be seen that the difference between the

variances and the means of the results (in terms of BPT, MTD, and IA) for the three

replicate specimens is insignificant for all cases when considering the friction values

(BPN) and aggregate exposure area (IA) and insignificant for the vast majority of the

cases when considering the macrotexture values (MTD), thus supporting the

repeatability of the polishing action provided by the accelerated polishing device.

3.4.6 Polishing Effect of the Accelerated Polishing Machine

The polishing effect of the accelerated polishing machine is examined in this section.

For the HMA slab specimens made with limestone aggregates, the friction values (FN)

obtained from the DFT at different measuring speeds versus the polishing duration is

shown in Figure 3-4(a). The MPD measured by the CTM is plotted versus duration of

85

polishing in Figure 3-4(b). It can be seen from Figure 3-4(a) that friction decreases with

polishing duration until it reaches the residual value. Corresponding to the friction

decrease, there is a similar trend of MPD decrease as well.

For the 6-inch HMA gyratory compacted specimens made with limestone aggregates,

the friction values (BPN) obtained from the BPT and the MTD measured by the sand

patch method are plotted against the polishing duration in Figure 3-5(a) and Figure

3-5(b), respectively. It can be seen that both the friction values and the MTD decrease

as the polishing duration increases.

The test results of HMA specimens made of the sand and gravel aggregates are shown

in Figure 3-6(a) and (b) and Figure 3-7(a) and (b) for the slab specimens and the

gyratory compacted specimens, respectively. The general trend of the polishing

behavior for the specimens made of the limestone and the sand and gravel is similar.

Furthermore, it can be seen that the polishing behavior for large slab specimens and

gyratory compacted specimens exhibit the similar decreasing pattern.

86

Table 3-3: Repeatability tests for the limestone and gravel

a. significant at the p-value smaller than 0.05

87

(a) FN by DFT vs. polishing time at different speeds

(b) MPD by CTM vs. polishing time


slab specimens

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 1000

Polishing Time (min.)

FN

me

as

ure

d u

sin

g D

FT

0 km/hr

10 km/hr

20 km/hr

30 km/hr

40 km/hr

50 km/hr

64 km/hr

0.85

0.90

0.95

1.00

1.05

0 200 400 600 800 1000


MP

D (

mm

)

Friction Measurement

Speed

88

(a) BPN by BPT vs. polishing time

(b) MTD by sand patch technique vs. polishing time


gyratory compacted specimens

45

50

55

60

65

70

75

80

0 100 200 300 400 500


BP

N

0.1

0.12

0.14

0.16

0 100 200 300 400 500


MT

D (cm

)

89

(a) FN by DFT vs. polishing time at different speeds

(b) MPD by CTM vs. polishing time

Figure 3-6: Polishing, friction, and texture results of tests conducted on Sand and

Gravel slab specimens

0.60

0.65

0.70

0.75

0 200 400 600 800 1000


MP

D (m

m)


Speed

90

(a) BPN by BPT vs. polishing time

(b) MTD by sand patch technique vs. polishing time

Figure 3-7: Polishing, friction, and texture results of tests conducted on Sand and

Gravel gyratory compacted specimens

55

60

65

70

75

0 100 200 300 400 500


BP

N

0.075

0.077

0.079

0.081

0.083

0.085

0 100 200 300 400 500


MT

D (

cm)

91

3.4.7 Comparing HMA Surface and Aggregate Surface Polishing Behavior

In a previous study (Liang and Chyi, 2000), different aggregates sources were tested

for polishing and friction behavior using the accelerated British Polishing Wheel

(ASTM E3319). The results of polishing behavior of two aggregates from (Liang and

Chyi, 2000) and the current study of the HMA specimens made with the same two

aggregate sources are statistically compared in Table 3-4 and Table 3-5 for Limestone

and Sand and Gravel aggregates, respectively. It can be seen that the polish (friction)

values of the aggregates, denoted by PV, are highly correlated to the friction values of

the HMA made with the same aggregates, denoted by either BPN for the gyratory

compacted specimens or FN_SPEED (where SPEED refers to the friction at that

measuring speed) for the roller compacted slab specimens with friction measured at

different speeds. The fact that aggregates constitute more than 90% by weight of the

HMA leads us to believe that aggregate would be a dominant controlling factor on

friction of HMA surface. The high correlations presented in Table 3-4 and Table 3-5

support this observation. Based on the ANOVA analysis results presented in Table 3-4

and Table 3-5 for the Limestone and Sand and Gravel aggregates, respectively, the

overall significance of the models as indicated by the F-value (i.e., as F goes up, P goes

down, thus indicating more regression confidence in that there is a difference between

the two means) and the P-value (the probability of getting a value of the test statistic as

extreme as or more extreme than that observed by chance alone, if the null hypothesis

Ho, is true) is found to be significant at the 0.05 significance level. Based on the

comparisons presented in this section, the developed laboratory-scale accelerated

92

polishing device is shown to be able to polish the HMA surface and provide similar test

results as if the polishing tests were performed on the aggregates only.

Table 3-4: Simple Linear Regression between Aggregate Friction Values (Liang

and Chyi 2000) and HMA Friction Values (This Study) for Columbus Limestone

Table 3-5: Simple Linear Regression between Aggregate Friction Values (Liang

and Chyi 2000) and HMA Friction Values (This Study) for Stocker Sand and

Gravel

93

3.4.8 Comparing the Polishing Trend with the Aggregate Exposure Area

Image analysis is carried out to quantify the area of exposed aggregate (Agg. %) of

the gyratory compacted HMA specimen surface during different stages of the

polishing test. The percent of aggregate exposure area of Limestone specimens is

measured from the digitized images shown in Figure 3-8(a) and then plotted against

the polishing duration in Figure 3-8(b). Similarly, the digitized images of the Sand

and Gravel specimens shown in Figure 3-9(a) are used to plot the percent of

aggregate exposure area versus the polishing duration in Figure 3-9(b). From

Figures 3-8(b) and 3-9(b), one can see that the more polishing duration the

specimen is subjected to, the more aggregates area is exposed until reaching the

maximum percentage.

A statistical analysis is conducted to exam the correlations between the friction values

of aggregate (PV) and HMA (BPN) and the percent of exposed aggregate area (Agg.

%) at different stages of polishing. The regression models and the coefficient of

determination (R2) for each model are presented in Table 3-6 together with the

ANOVA analysis results. It can be seen that PV and BPN correlates well with the

percent of exposed aggregate area at different stages of polishing.

94

(a) The captured images shown on the left and the digitized images shown on the

right at different polishing times

(b) Aggregate exposure area vs. polishing time

Figure 3-8: Image analysis results of tests conducted on Limestone gyratory

compacted specimens

0

5

10

15

20

25

0 100 200 300 400 500 600


Ag

gre

ga

te e

xp

os

ure

(%

)

0 min

240 min

480 min

95

(a) The captured images shown on the left and the digitized images shown on the

right at different polishing times

(b) Aggregate exposure area versus polishing time

Figure 3-9: Image analysis results of tests conducted on Sand and Gravel gyratory

compacted specimens

0

5

10

15

20

25

0 100 200 300 400 500 600


Ag

gre

gate

exp

osu

r (%

)

0 min

240 min

480 min

96

3.4.9 Polishing Trend of HMA Samples Prepared by Two Compaction Methods

The friction values of the two types of specimen sizes (slab specimens and 6-inch

specimens) each with different type of compaction method (i.e., roller compaction vs.

gyratory compaction) have been found to be correlated and the coefficients of

determination have been found to be significant as can be seen from Table 3-7 and

Table 3-8 for Limestone and Sand and Gravel aggregates, respectively. It is very

interesting to note that the correlativity is more significant between BPN and

FN_SPEED at low speeds; for example, at 0, 6, and 12.5 mph. This high correlation is

reasonable considering that BPT actually measures the friction values at low speed; i.e.,

at 6 mph. Based on the ANOVA analysis shown in Tables 6 and 7, the overall

significance of the models as presented by the F-value and P-value was found to be

significant at the 0.05 significance level.

Table 3-6: Simple Linear Regression between Aggregate and HMA Friction Values

and Aggregate Exposure Area

97

Table 3-7: Simple Linear Regression between Friction Values of Gyratory

Compacted Specimens and Friction Values of Roller Compacted Slab Specimens

(Limestone aggregate)

Table 3-8: Simple Linear Regression between Friction Values of Gyratory

Compacted Specimens and Friction Values of Roller Compacted Slab Specimens

(Sand and Gravel aggregate)

3.4.10 Application of the Accelerated Polishing Device

In order to use the test results from the developed accelerated polishing device in

screening the aggregate source and mix design, there is a need to correlate the friction

values measured on the HMA surface in the laboratory to the friction values measured

either on the aggregate samples in the laboratory or the skid number measured on

98

pavement surface. This is because there are more experiences in using either the PV

values determined from BPT or SN determined from LWST. In this section, different

paths will be developed to allow the use of the developed accelerated polishing device

for qualifying the aggregate source and mix design from the polishing and friction

point of view.

3.4.10.1 Correlation with PV values

Texas Department of Transportation (TxDOT) has adopted Table 3-9 for acceptance of

aggregate. These standards were based on the polish values (PV) and the Average

Daily Traffic (ADT).

Through the developed correlation between aggregate polish values (PV) from a

previous study (Liang and Chyi, 2000) and gyratory compacted HMA friction numbers

(BPN, shown in Tables 3-4 and 3-5), the TxDOT criteria based on PV values can be

transformed to represent acceptance criteria of HMA based on BPN values. The

derived acceptance criteria, based on BPN values of HMA surfaces, are shown in Table

3-10. Accordingly, four categories of acceptance criteria can be formulated.

Highly acceptable (BPN greater than 51 for HMA prepared using limestone aggregate

and 62 for HMA prepared using gravel aggregate).

Acceptable (BPN greater than 47 for HMA prepared using limestone aggregate and 60

for HMA prepared using gravel aggregate).

99

Marginally acceptable (BPN greater than 43 for HMA prepared using limestone

aggregate and 57 for HMA prepared using gravel aggregate).

Unacceptable (BPN less than 43 for HMA prepared using limestone aggregate and 57


Table 3-9: TxDOT acceptance criterion of aggregates

Table 3-10: Derived acceptance criteria of HMA based on BPN values

100

3.4.10.2 Correlation with SN values

Friction values measured by the British Pendulum Tester (BPN) and skid numbers

measured by the skid trailer (SN) do not correspond exactly; nevertheless, Kissoff

(1988) has developed an approximate relationship (see Equation 3-1) that could be used

to relate BPN to SN. Therefore, the above acceptability criteria based on BPN values

can be altered according to Kissoff’s relationship to develop SN-based acceptability

criteria as summarized below. The derived acceptance criteria, based on SN values of

HMA surfaces, are shown in Table 3-11. Accordingly, four categories of acceptance

criteria can be formulated.

690.9)(862.0 BPNSN (3-1)

Highly acceptable (BPN greater than 34 for HMA prepared using limestone aggregate

and 44 for HMA prepared using gravel aggregate).

Acceptable (BPN greater than 31 for HMA prepared using limestone aggregate and 42


Marginally acceptable (BPN greater than 27 for HMA prepared using limestone

aggregate and 39 for HMA prepared using gravel aggregate).

Unacceptable (BPN less than 27 for HMA prepared using limestone aggregate and 39


101

Table 3-11: Derived acceptance criterion of HMA based on SN values

3.5 Summary and Conclusions

Presented in this chapter is the development of an accelerated laboratory-scale

polishing device that is capable of mimicking the polishing action of the HMA surface

by a vehicle tire in a short duration, thus allowing for screening the aggregate source

and mix design formula to ensure adequate friction (or skid resistance) of the HMA

over the expected life span of the pavement surface. The accelerated polishing machine

is capable of testing two different sizes of HMA specimens: 18 inch by 18 inch by 2

inch high slab specimens compacted using the roller compactor and 6 inch diameter

and 4 inch high gyratory compacted HMA specimens. Although the device can handle

two different specimen dimensions, each with different type of compaction method, the

intended routine test sequence is geared toward the testing of 6 inch gyratory

compacted HMA specimens due to its ease of sample preparation. The design

principles of the testing device, together with the optimized operation conditions, are

outlined in detail in this chapter. Evaluation of the capability of the developed

102

accelerated polishing device has been conducted through a series of designed testing

and comparisons, as summarized below.

Repeatability of the machine was checked and affirmed using one-way ANOVA test.

The polishing effect of the machine was confirmed through examination of the test

results conducted on Limestone and Sand and Gravel aggregates.

Good correlation of the polishing and friction behavior was found between aggregate

specimens and the HMA specimens made with the same aggregates. Therefore, it

maybe reasonable to conclude that the new accelerated polishing machine can

accomplish the intended tire/pavement wearing and polishing mechanisms.

Image analysis validated the polishing action.

Good correlation was found between the two specimen sizes using different

compaction methods.

The developed accelerated polishing device can be used effectively for screening

polishing and friction properties of HMA mix (i.e., aggregate source, binder type and

content, etc.) during the HMA mix design stage. Furthermore, the device possesses the

following advantages:

●Tests are repeatable.

●The device can test small-size HMA specimens (i.e., 6 inch diameter and 4 inch high

gyratory compacted specimens).

103

●The test can be completed in a reasonable timeframe.

●The test procedure is simple.

●The test method is efficient (i.e., less labor effort).

●The device can simulate the tire/pavement interaction.

The correlation study between friction values measured by DFT at low measuring

speed and the BPT suggests that the BPT can be used for measuring friction of HMA at

low speeds.

A set of tentative acceptance criteria of gyratory compacted HMA specimens was

developed through two different correlations (i.e., by correlating BPN with PV or

relating BPN with SN). These acceptance criteria are divided into two parts based on

the aggregate type used; i.e., limestone or gravel. The acceptance criteria consist of four

categories: 1. highly acceptable, 2. acceptable, 3. marginally acceptable, and 4.

unacceptable, which can be used to screen and select pertinent aggregate and HMA

mix design for adequate polishing resistance and friction values.

104

CHAPTER IV

4. LABORATORY TEST RESULTS AND DATA ANALYSIS

4.1 Introduction

In adequate friction on the pavement surface is a major cause for wet weather related

accidents on highways. To minimize wet weather related accidents, most highway

agencies have developed a strategic goal of maintaining high skid resistance on the

pavement surface. In general, the state DOTS have maintained a friction measurement

program, through the use of the locked wheel skid trailer (LWST), to measure the skid

number (SN). Once the measured SN is below a threshold value, then state DOTs

would take remedial actions by resurfacing the pavement surface with high skid

resistance HMA (hot mix asphalt) to ensure driving safety.

Although the practice of monitoring pavement surface friction by means of SN and

taking remedial actions by pavement resurfacing is important; nevertheless, it is a

passive solution toward the problem. A more proactive approach to solving the

problem would be to use high polish-resistant and high friction aggregate and the

accompanied HMA (hot mix asphalt) mix design during the initial stage of the material

acceptance process. A significant number of research efforts have been devoted toward

the development of appropriate mix design protocols, such as SuperPave mix design

105

but there has been a lack of more intensive research efforts to develop appropriate test

procedures to screen polishing and friction behavior of HMA. As described in chapter

3, the authors developed a laboratory scale accelerated polishing device for HMA and

for simulating the actual tire-asphalt polishing action. The friction measurement of the

laboratory prepared HMA specimens, however, can only be carried out by laboratory

scale portable devices such as British Pendulum Tester (BPT) or the Dynamic Friction

Tester (DFT). Since the BPT is widely used by highway agencies in developing

acceptance criteria for friction, there is a need to gain a better understanding of the

numerous influencing factors on the measured BPN (British Pendulum Number)

thorough the BPT. The main objective of this chapter is to examine the relationship

between the BPN, measured by the BPT, and the texture properties (i.e., MTD, Mean

Texture Depth) of the HMA surface, measured by the sand patch method.

4.2 Pavement Sections and Material Properties

To facilitate the selection of the aggregates and the accompanied JMF for mix design of

HMA, the authors have consulted with the Ohio Department of Transportation’s

pavement construction records to identify a total of eight pavement sections for long-

term monitoring of friction behavior. The selection of these pavement sections is based

on the criteria that each of the pavement sections provides adequate documentation of

traffic counts as well as the construction materials used and the mix design. Table 4-1

provides information on these identified pavement sections. Based on field friction

data, these aggregate sources can be roughly classified into three categories: low (L),

106

medium (M), and high (H). Details of the JMF of each mix design can be found in

Appendix A.

Table 4-1: Asphalt concrete pavement sections and the associated JMFs

107

4.3 Test Program

The eight job mix formulas obtained from these eight pavement sections are used to

prepare the gyratory compacted HMA specimens that are 6 inch in diameter and 4 inch

in height for the accelerated laboratory polishing and the accompanied measurement of

BPN and MTD. Once the gyratory compacted specimens are prepared, the initial

values of BPN and MTD are measured. Each specimen is then subjected to polishing in

the accelerated polishing machine. After each hour of polishing, the BPN and MTD are

taken again. This polishing and measuring process continues for 8 hours for each

specimen tested.


The mixing procedure of the loose mix is as follows. First, the aggregates are separated

by dry sieving into the desired sizes using the mechanical shaker. The aggregates are

then washed and heated to about 330˚F. Aggregates are weighed and blended according

to the specified gradation curve. The properly proportioned aggregate mix is then put in

the oven at 330˚F for 3 hours for achieving a uniform aggregate temperature. The

mixing bowl and the mixing paddle are also heated to 300˚F. The asphalt binder is

heated in the oven at a temperature of 350˚F for 2 to 3 hours. At this point, the

aggregate is placed in the mixing bowl and blended quickly with the asphalt binder

until a uniform blending is obtained. The gyratory compactor is used to compact the

108

loose mix into a 6 inch diameter and 4 inch high cylindrical specimen according to the

ODOT compaction specifications.

4.3.2 Friction and Texture Measurement Techniques

The BPT (ASTM E303-93) can be described as follows. Typically, the test specimen is

first immersed in water and then the test surface was cleaned. Next, the BPT device is

levelled and adjusted so that the contact path between the rubber slider and specimen

surface is within the range of 063.092.4 inch. The rubber slider is cleaned and wetted.

Five swings are made for each specimen being tested, from which an average of the last

four readings is recorded as the BPN.

The sand patch method (ASTM E965) is a technique to measure macrotexture of the

HMA surface. This method involves taking a known volume of a spreadable material

and spreading it out in a circle on the surface of the specimen. The Mean Texture

Depth (MTD) is determined by dividing the volume of the spread material by the

surface area covered by the spread material.

4.3.3 Accelerated Polishing Device

The accelerated polishing device uses the rubber pad to brush against the HMA

specimen surface at constant rotational speed and constant normal pressure. Different

surface friction and texture properties can be produced by subjecting the HMA

specimens to different duration of polishing action that represents the entire lifespan of

109

the pavement surface in the field. Details of the accelerated polishing device can be

found in Chapter III.

4.4 Laboratory Test Results

The laboratory-prepared, gyratory-compacted HMA specimens are subjected to

accelerated polishing using the developed accelerated polishing machine. Typically,

after each one hour of polishing, the specimens are taken out from the polishing

machine for measuring the friction value (i.e., BPN) and texture properties (i.e., MTD)

It should be noted that for each mix type (JMF) studied, a total of three replicate

specimens are prepared and tested to ascertain the repeatability of the test results as

well as to obtain quantitative data for correlation analysis between BPN and MTD.

Appendix B provides the numerical values of the BPN and MTD for each hour of

polishing for all eight hours using the eight different JMFs labelled according to their

polish susceptibility.

4.5 Analysis of Test Results

The conducted analysis of the obtained results is shown below.

4.5.1 Analysis of Repeatability

The repeatability of the test results was examined in this section. For each set of

specimens made of the same JMF, three replicate specimens were tested. The friction

(BPN) values obtained from the BPT and the MTD measured by the sand patch method

from the three replicates are statistically analysed using Homogeneity of Variance

110

(Levene statistic), one-way Analysis of Variance (ANOVA), and Multiple

Comparisons to check for the repeatability of test results. Homogeneity of Variance

and one-way ANOVA are used to check if there is any significant difference between

the variances and the means of at least two specimens for each set of specimens (three

specimens per set) made of the same JMF. Multiple Comparisons, on the other hand, is

used to check if there is any significant difference between the means of different two-

specimen combinations of the three specimens set made of the same JMF. The software

Statistical Package for the Social Sciences (SPSS) was employed for obtaining the

statistical analysis results. Table 4-2 summarizes the statistical analysis results. It can

be seen that the difference between the variances and the means of the results (in terms

of BPT and MTD) for the three replicate specimens is insignificant for all cases when

the friction values (BPN) is considered, and insignificant for the vast majority of the

cases when the macrotexture values (MTD) is considered. Therefore, the repeatability

of the test results is confirmed.

111

Table 4-2: Repeatability tests for the eight different job mix formulas


112

Table 4-2: Repeatability tests for the eight different job mix formulas (continued)

a . significant at the p-value smaller than 0.05

113



114



115

4.5.2 Analysis of Polishing Behavior (BPN)

The polishing behavior in terms of the friction values (BPNs) was analyzed and

presented herein.

4.5.2.1 Rate of Friction Loss (Percent Hourly Drop in Polish Numbers)

The percent hourly drop in BPN is calculated by Equation (4-1).

hournBPNat

hournBPNathournBPNatPNrlyDropinBPercentHou

th

thth

)(

)1()( (4-1)

The percent hourly drop in BPN was calculated for each of the eight mixes. The

average percent hourly drop for the aggregates in each of the three categories (i.e., L,

M, and H) of polish susceptibility is calculated for further analysis.

The calculated average percent hourly drop in BPN was plotted against the polishing

duration in minutes as shown in Figure 4-1, Figure 4-2, and Figure 4-3 for low (L),

medium (M), and high (H) polish susceptibility aggregates, respectively. It can be seen

that the percent decrease in polish number is the highest during the first hour of

polishing. With the passage of time, the drop in BPN decreases up to the sixth hour of

polishing. After 6 hours of polishing, the BPN appears to have reached a constant value

even with additional polishing action (duration). The pattern of the BPN loss over time

may be explained in the following manner. The exceedingly high rate of drop of BPN

values in the first hour of polishing could be attributed to the presence of surface

impurities on the HMA specimen surface. With the passage of time during which

116

further sacrificial polishing occurs, these aggregates are cleaned off. Also certain

angular protrusions on the surface of the aggregates wear off or break off during this

time to reveal a much smoother surface. As a result, the rate of drop of BPN values

decreases to eventually reaching a negligible rate.

The normalized results of measured BPN values are prepared based on the loss of BPN

values at any given time of polishing divided by the maximum loss of BPN values at

the end of eight hours of polishing. Figure 4-4, Figure 4-5, and Figure 4-6 show the

plots of each polish susceptibility level (low, medium, and high). It can be seen from

these curves that they follow a similar trend of polishing with time. Roughly, those

HMA classified as low susceptibility (L) lost 51 to 62% of the total BPN loss in the

first hour of polishing. Those medium polish susceptibility aggregate (M) lost in the

first hour of polishing the 21 to 41% of the total BPN loss. The high polish

susceptibility aggregate (H) lost in the first hour of polishing about 44% of the total

BPN loss.

117

Figure 4-1: Average percent hourly drop in BPN vs. polishing time for low polish

susceptibility aggregates

Figure 4-2: Average percent hourly drop in BPN vs. polishing time for medium

polish susceptibility aggregates

0

2

4

6

8

10

12

60 120 180 240 300 360 420 480


Pe

rce

nt

Dro

p in

BP

N (L

ow

Po

lish

ing

)

0

2

4

6

8

10

60 120 180 240 300 360 420 480


Pe

rce

nt

Dro

p in

BP

N (

Me

diu

m P

olis

hin

g)

118

Figure 4-3: Average percent hourly drop in BPN vs. polishing time for high polish


Figure 4-4: Normalization of BPN wrt. the maximum difference in BPN for low


0

2

4

6

8

10

12

14

16

18

60 120 180 240 300 360 420 480


Per

cen

t Dro

p in

BP

N (

Hig

h P

olis

hin

g)

(BPNi-BPNt)/(BPNi-BPNf)

0

0.25

0.5

0.75

1

1.25

0 50 100 150 200 250 300 350 400 450 500


No

rmal

ized

BP

N L1

L2

L3

119

Figure 4-5: Normalization of BPN wrt. the maximum difference in BPN for

medium polish susceptibility aggregates

Figure 4-6: Normalization of BPN wrt. the maximum difference in BPN for high



0

0.25

0.5

0.75

1

1.25

0 50 100 150 200 250 300 350 400 450 500


No

rma

lize

d B

PN

M1

M2

M3

M4


0.00

0.25

0.50

0.75

1.00

1.25

0 50 100 150 200 250 300 350 400 450 500


No

rma

lize

d B

PN

H1

120

4.5.2.2 Absolute and Percent Value of Decrease (Initial Polish Number versus Final

Polish Number)

Table 4-3 presents the absolute decrease and the percent decrease in BPN between

initial and final values for different HMA mixes. As expected, for low polish

susceptibility aggregates the percent decrease between initial and final BPN is less than

medium polish susceptibility aggregates which, in turn, is less that high polish

susceptibility aggregates. The same conclusion can be drawn when the average

absolute decrease and the average percent decrease of each polish susceptibility

aggregate (i.e., L1, L2, and L3, and M1, M2, M3, and M4, and H1) is calculated.

Table 4-3: Percent decrease in BPN and MTD between initial and final values

121

4.5.3 Surface Texture Behaviour

The polishing behaviour in terms of the texture values (BPNs) was analysed and

presented herein.

4.5.3.1 Rate of Surface Texture Loss (Percent Hourly Drop in Texture Values)

For each polish susceptibility aggregate, the average percent hourly drop in

macrotexture (MTD) is plotted against the polishing duration in Figure 4-7, Figure 4-8,

and Figure 4-9, respectively. It is observed that the percent decrease in macrotexture is

the maximum during the first hour of polishing. With the passage of time, the drop in

MTD decreases and stabilizes after the fifth hour of polishing. After which, the HMA

surface is said to have reached the residual state that further polishing action will not

significantly reduce the macrotexture. The normalized plot in terms of the loss of

macrotexture at a polishing duration divided by the maximum loss of macrotexture at

the end of eight hours of polishing is presented in Figure 4-10, Figure 4-11, and Figure

4-12 for three polish susceptibility categories. It can be seen from these curves that for

all polish susceptibility categories that they follow a similar trend of MDT versus

polishing duration. In the first hour of polishing for the low polish susceptibility

aggregate, the loss of MTD values is anywhere between 38 to 58% of the total loss. For

the medium polish susceptibility aggregate, the loss of MTD values is anywhere

between 40 to 59% of the total loss. For the high polish susceptibility aggregate, the

loss of MTD values in the first hour is 69% of the total loss.

122

Figure 4-7: Average percent hourly Drop in MTD vs. polishing time for low polish


Figure 4-8: Average percent hourly drop in MTD vs. polishing time for medium


0

2

4

6

8

10

12

60 120 180 240 300 360 420 480


Pe

rce

nt

Dro

p in

MT

D (

Lo

w P

olis

hin

g)

0

2

4

6

8

10

12

14

60 120 180 240 300 360 420 480


Pe

rce

nt

Dro

p in

MT

D (

Me

diu

m P

olis

hin

g)

123

Figure 4-9: Average percent hourly drop in MTD vs. polishing time for high polish


Figure 4-10: Normalization of MTD wrt. the maximum difference in MTD for low


0

5

10

15

20

25

60 120 180 240 300 360 420 480


Pe

rce

nt

Dro

p in

MT

D (

Hig

h P

olis

hin

g)

(MTDi-MTDt)/(MTDi-MTDf)

0

0.25

0.5

0.75

1

1.25

0 50 100 150 200 250 300 350 400 450 500


No

rmal

ize

d M

TD L1

L2

L3

124

Figure 4-11: Normalization of MTD wrt. the maximum difference in MTD for

medium polish susceptibility aggregates

Figure 4-12: Normalization of MTD wrt. the maximum difference in MTD for high



0

0.25

0.5

0.75

1

1.25

0 50 100 150 200 250 300 350 400 450 500


No

rma

lize

d M

TD

M1

M2

M3

M4


0

0.25

0.5

0.75

1

1.25

0 50 100 150 200 250 300 350 400 450 500


No

rmal

ized

MT

D

H1

125

4.5.3.2 Absolute and Percentage Value of Decrease (Initial Texture Value versus

Final Texture Value)Table4-4 presents the absolute decrease and the percent

decrease in MTD between initial and final values for different HMA mixes

studied. As expected, the percent decrease between initial and final MTD for

low polish susceptibility aggregates is less than that for medium polish

susceptibility aggregates which, in turn, is less that for high polish

susceptibility aggregates. The same conclusion can be drawn when the

average absolute decrease and the average percent decrease for each polish

susceptibility aggregate is calculated.

4.5.4 Correlation Study between BPN and MTD

A simple linear regression analysis was performed between the corresponding BPN and

MTD values. The regression analysis results shown in Table 4-5 confirm that BPN and

MTD are highly correlated with high coefficient of determination (R2), In addition,

good correlation was observed in Table 4-6 between the change in BPN (BPN) and

the change in MTD (MTD).

126

Table 4-4: Percent decrease in BPN and MTD between initial and final values

127

Table 4-5: Simple linear regression between BPN and MTD

128

Table 4-6: Simple linear regression between BPN and MTD

129


In this chapter, the polishing behavior of laboratory-prepared, gyratory-compacted

HMA specimens made of eight different job mix formulas has been studied in terms of

friction values (BPN) and macrotexture data (MTD). In addition, the potential

relationship between BPN and MTD has also been investigated. The conclusions that

can be drawn from this study are summarized below.

It has been observed that the decrease in friction (BPN values) and surface

macrotexture (MTD values) is the maximum during the first hour of polishing in the

accelerated polishing equipment. With the passage of time, the drop in BPN and MTD

decreases and eventually becomes negligible at the 6th hour of polishing. This behavior

is attributed to the presence of surface impurities on the HMA specimen surface. With

the passage of polishing time during which further sacrificial polishing occurs, these

aggregates are cleaned off. Also certain angular protrusions on the surface of the

aggregates wear off during this time to reveal a much smoother surface. As a result, the

rate of decrease in both BPN and MTD becomes smaller with polishing time and

eventually becomes negligible at the 6th hour of polishing action.

The macrotexture (MTD values) of HMA surface was found to be strongly correlated

with the surface friction (BPN values). In addition, good correlation was also found

between change in BPN values (BPN) and change in surface texture (MTD) for each

130

HMA mix as well as for each polish susceptibility category. Therefore, the results

presented in this chapter provide strong quantitative evidence in supporting the strong

interrelationship between the friction and texture properties of the HMA surfaces.

131

CHAPTER V

5. LABORATORY STUDY OF AIR VOID AND TEMPERATURE EFFECTS ON

HMA FRICTION PROPERTIES

5.1 Introduction

Friction is often considered to be governed by the surface characteristics of Hot Mix

Asphalt (HMA) surface; however, some recent studies by Goodman et al. (2006),

Wang and Flintsch (2007), Flintsch et al. (2005), and Luo (2003) have shown that other

factors, such as density (air void) and temperature, may also affect surface friction

properties of HMA surfaces. Pavement skid resistance is generally defined as the

ability to prevent the loss of traction between the tire and pavement surface. Pavement

friction is the result of a complex interplay between two principal frictional force

components: adhesion and hysteresis (Figure 2-1). Although there are other

components of pavement friction (e.g., tire rubber shear), they are insignificant when

compared to the adhesion and hysteresis force components. Thus, friction can be

viewed as the sum of the adhesion and hysteresis frictional forces.

Air voids of the newly laid asphalt pavement layers generally decreases from original

7-8% to 3-4% due to compaction by traffic. Therefore, the possible magnitude of

friction change as the air void decreases by 50% over the life span of a pavement needs

132

to be investigated. Furthermore, surface temperature may vary greatly (e.g., from -11.1

°C to 50 °C or 12 °F to 122 °F) during a life span of the pavement, there is a need to

quantify the temperature effect on the measured friction values as well.

This chapter presents the controlled laboratory test results for quantifying the effects of

air void and temperature on the measured friction properties of the gyratory compacted

HMA surfaces. The laboratory test procedures, including the materials used in

preparing the HMA specimens, the method used to polishing the HMA surface, and the

friction measurement techniques, are described in detail. Statistical analysis was used

to determine the significance of these two variables (air void and temperature) on the

measured friction values. Finally, the method for extrapolating the friction values

measured at any density and temperature to the friction values at other density and

temperature is proposed at the end of the chapter.

5.2 Background

In the United States, the most common method of measuring the skid resistance of a

pavement surface is by means of the skid trailer (Luo 2003). The standard test

procedure for the Locked Wheel Skid Trailer (LWST) is described in detail in the

ASTM E 274 specification. The test begins with the skid trailer reaching the desired

test speed; usually 64 km/h (40 mph). An activator, located inside the truck, is used to

initiate the test sequence by starting with spraying a thin layer of water to the pavement

surface. After a correct amount of water has been applied, the test wheel is locked

(usually the left tire) and instrumentation in the trailer records the sliding force of the

133

locked tire. This test allows for the computation of the skid number (SN) by dividing

the tractive force applied to the tire by the vertical load applied to the tire.

A different method for friction measurement that can be conducted on pavement

surface or on laboratory prepared HMA surface is the British Pendulum Tester (BPT)

specified in ASTM E 303. Recent studies by Goodman et al. (2006) and Bazlamit and

Reza (2005) have utilized BPT for their respective friction studies. Although British

Pendulum Numbers (BPNs) and SNs do not correspond exactly; nevertheless, Kissoff

(1988) has developed an approximated relationship that could be used to relate BPN to

SN. Therefore, the BPN values studied in this chapter could be extrapolated to the SN

values based on Kissoff correlations.

In recent years, a few notable research efforts have been directed toward a better

understanding of the influencing factors on the HMA surface friction properties. In

2006, Goodman et al. reported that initial field BPN can be correlated with the

following variables: fineness modulus (FM), voids in mineral aggregate (VMA),

percent passing the 4.75mm sieve (P4.75) and bulk relative density (BRD).

Interestingly, the bulk relative density was found to significantly affect the measured

BPN values.

There have been some recent research efforts toward quantifying the temperature

effects on the measured pavement friction values. For example, Runkle and Mahone

(1980), Burchett and Rizenbergs (1980), and Bazlamit and Reza (2005) have found that

an increase in temperature can result in a corresponding decrease in skid resistance of a

134

pavement surface. Despite the significant number of reports cited above to indicate the

significant effects of temperature on pavement surface friction values, there are

contradictory findings reported by Dahir et al. (1979) and Mitchell et al. (1986) as well.

It was concluded that temperature variations do not seem to significantly affect the skid

resistance measurements. A comprehensive summary of the studies focused on the

temperature effect on HMA frictional properties is presented in Table5-1 It should be

noted that Ta, Tp, Tt, and Tw stand for air temperature, pavement temperature, tire

temperature, and water temperature, respectively.

135

Table 5-1: Summary of the studies focused on the temperature effect on HMA

frictional properties

Based on the review presented, it seems that the effect of air void on surface friction is

qualitatively understood. However, a quantitative assessment has not been reported in

the literature. Regarding the temperature effects on surface friction, the contradictory

conclusions found in the reports may need further clarification. As the effects of

temperature on the measured pavement skid resistance can be broken down into four

components: air temperature, water temperature, tire temperature, and pavement

136

temperature, it could be argued that a controlled laboratory test program may provide

quantitative temperature effects that could not be readily obtained from field study. The

contribution of this chapter lies in providing the controlled laboratory study results to

augment existing knowledge on the effects of air void and temperature on the friction

properties of the compacted HMA surface.

5.3 Laboratory Testing Program

The testing program of the laboratory experiments is shown herein.

5.3.1 Materials

The aggregate used in this study was a limestone with a gradation curve shown in

Figure 5-1. The asphalt binder used was PG 64-22. Based on the Superpave

Specifications adopted by Ohio Department of Transportation, an optimum binder

content of 6.1% was used to compact the HMA specimens. To achieve the desirable air

void, the number of gyrations was varied in preparing the test specimens for friction

measurement.

5.3.2 Test Program

The test program consists of varying the air voids and temperature as test variables.

Each test variable condition (either air void or temperature) is tested in triplicate

specimens to ensure data repeatability. The effect of air void was assessed by preparing

gyratory compacted specimens (6 inches in diameter) at different densities (air voids)

by compacting the specimens to different numbers of gyrations. The range of air voids

137

studied in the test program is 0.8% to 5.4%. The effect of temperature was studied by

varying the temperature of the test specimen, the rubber pad of the friction measuring

device (BPT), and the spraying water. The temperature range studied in this test

program is 4.4 °C (40 °F) to 48.9 °C (120 °F).

Figure 5-1: Gradation curve

5.3.3 Accelerated Polishing Machine

The present study utilizes a laboratory-scale accelerated polishing machine to polish

the HMA specimens to mimic different stages of the actual pavement surface under

traffic induced polishing and wearing. The accelerated polishing machine uses the

rubber pad to brush against the HMA specimen surface at constant rotational speed and

constant normal pressure (refer to Chapter III). Different surface friction and texture

properties can be produced by polishing the initially compacted HMA specimens to

different durations of polishing as was demonstrated in Chapter III. The accelerated

0

20

40

60

80

100

120

0.001 0.01 0.1 1

Grain size (in)

Pe

rce

nt

pa

ss

ing

138

polishing machine allowed the polishing of the laboratory prepared HMA specimens to

different stages of polishing action, thus mimicking the actual pavement surface under

traffic polishing over the entire life span of the pavement surface.

5.3.4 Friction Measurement Method

The measurement of surface friction values of HMA specimens follows the procedures

outlined in ASTM E 303 for the BPT. It should be noted that five measurements were

made for each specimen, from which an average of the last four readings was recorded

as the BPN.

5.4 Test Results and Analysis

The test results and data analysis of the air void and temperature effects on HMA

frictional properties are discussed in the following sections.

5.4.1 Air Voids Effects

For the effects of air voids, the friction measurement was made for the HMA

specimens compacted to three different air voids (0.8%, 2.8%, and 5.4%) and polished

to three different polishing stages: 0 minutes (initial unpolished stage), 240 minutes

(partially polished stage), and 480 minutes (completely polished stage). These air voids

were chosen to cover a wide range of realistic densities in pavement surface during the

life span of the pavement.

139

The variation of friction with air void in the unpolished, partially polished, and

completely polished conditions is plotted in Figure 5-2. At each air void and polishing

stage, the average from 12 readings (i.e., 3 specimens x 4 repeated readings) is plotted.

It can be seen that the friction (BPN) value increases with an increase in air void at all

polishing stages.

Figure 5-2: BPN vs. polishing time at different air voids

A set of statistical analysis was conducted using the Statistical Package for the Social

Sciences (SPSS) windows based program, including homogeneity of variances test,

One-Way Analysis of Variance (ANOVA), and Post Hoc tests. Levene's test is used to

test if n samples would have equal variances (homogeneity of variance). The analysis

of variance assumes that variances are equal across groups or levels. The Levene test is

intended to verify the validity of that assumption. One-Way ANOVA is used to

compare the means of several populations. Post Hoc test is used to evaluate whether the

Pavement Density Effect on BPN

45

50

55

60

65

70

75

80

0 100 200 300 400 500


BP

N

at 5.4% air void

at 2.8% air void

at 0.8% air void

140

levels or groups within the factor are significantly different or not. It can be performed

for factors with three or more levels or groups (Kutner et al. 2004). Table 5-2 provides

a summary of statistical analyses performed to support and validate that the effect of

changing HMA air voids on the measured friction values at three polishing stages is

significant. From Table 5-2 under the column of homogeneity of variances, it can be

seen that variances are not significantly different (i.e., equal variances). It is also

evident from the One-Way ANOVA table that the difference between means is

significant. Finally, it can be seen that the mean difference between any two groups is

significant for most of the cases, as seen from the column with the heading of multiple

comparisons. It is noted that the column “Group” under “Multiple Comparisons” in

Table 5-2 refers to the different air voids (AV) used; in other words, I denotes AV of

0.8%, II denotes AV of 2.8%, and III denotes AV of 5.4%. All observations are made

at the 0.05 significance level.

As reviewed in the background section of this chapter, the LWST test is conducted on

the actual pavement surface to monitor the friction values in terms of SN. Therefore, a

useful equation is developed herein to enable extrapolating SN obtained at a given air

void to the SN at other air voids Toward this goal, a linear curve fit is developed and

shown in Figure 5-3, where BPN is taken from the intermediate (partially) polished

state (after 240 minutes of polishing) that is typical of a pavement that has been in

service. The value of the coefficient of determination, R2, is 0.9967. The slope of the

fitting line is 1.4192. Thus, one can deduce the following general equation that relates

the BPN at any other air void (BPNAV) to the BPN at measured air void (BPNMAV)

141

)5(419.1 AVBPNBPN MAVAV (5-1)

The relationship between SN and BPN, such as the one proposed by Kissoff (1988)

given in Equation 5-2, can be used to convert Equation 5-1 into Equation 5-3.

690.9)(862.0 BPNSN (5-2)

)5(223.1 AVSNSN MAVAV (5-3)

Equation 5-3 can be used for obtaining the SN at any air void (SNAV) given the

SN at the measured air void (SNMAV) and vice versa.

142

Table 5-2: Test of Homogeneity of variances, 1-Way ANOVA Table, and Multiple

Comparisons for the Effect of HMA Air Void on BPN

143

Figure 5-3: BPN vs. air voids

5.4.2 Temperature Effects

For the temperature effect, the test results obtained from the laboratory work include

friction (BPN) at three different temperatures: 40, 75, and 140 F , and three stages of

polishing. The variation of temperature was achieved by placing the HMA specimen,

the rubber slider of the BPT, and water in the oven.

The variation of friction (BPN) values with temperatures in the unpolished, partially

polished, and completely polished conditions is plotted in Figure 5-4, in which HMA

specimen, sliding rubber pad, and water temperatures are controlled. It can be seen that

the BPN values decrease with an increase in temperature.

y = 1.4192x + 50.742

R2 = 0.9967

51

52

53

54

55

56

57

58

59

0 1 2 3 4 5 6

Air Voids (%)

BP

N

144

Figure 5-4: BPN vs. polishing time at different pavement, rubber slider, and water

temperatures

A set of statistical analysis was conducted similar to the analysis carried out for the air

void effects. The statistical analysis results of temperature effects on BPN values are

summarized in Table 5-3. It can be seen that variances are not significantly different

(i.e., equal variances). It can also be seen from the One-Way ANOVA analysis that the

difference between means is significant. Finally, the mean difference between any two

groups is significant, as can be seen from the multiple comparisons column in the table.

A linear curve fit between the BPN and test temperature is shown in Figure 5-5, where

BPN is taken at an intermediate (partially) polished state. The value of the coefficient

of determination, R2, is 0.9951. The straight line of the best fit has a slope of -0.042.

45

50

55

60

65

70

75

80

0 100 200 300 400 500


BP

Nat 40 Fat 75 F

at 140 F

145

Thus, a linear relationship as given in Equation 5-4 can be used to reflect the

temperature effect on the BPN values

)68(042.0 TBPNBPN MTT (5-4)

where BPNT is the BPN at any temperature and BPNMT is the BPN at the measured

temperature. Using the same correlation equation (Equation 5-2), Equation 5-4 can be

converted into Equation 5-5 for modifying the SN values for the temperature effect

)68(036.0 TSNSN MTT (5-5)

where SNT is the value of skid number at any temperature and SNMT is the value of

skid number at the measured temperature.

146

Table 5-3: Test of Homogeneity of variances, 1-Way ANOVA Table, and Multiple

Comparisons for the Effect of Pavement, Rubber Slider, and Water Temperatures on

BPN

Figure 5-5: BPN vs. temperature

y = -0.042x + 62.069

R2 = 0.9951

55

56

57

58

59

60

61

0 20 40 60 80 100 120 140 160

Temperature (F)

BP

N

147


This chapter presented the test results of a laboratory test program to investigate the

effects of the air void and temperature on the HMA surface friction properties. The

surface friction values were determined using the British Pendulum Tester, while an in-

house accelerated polishing machine was used to polish the laboratory prepared Hot

Mix Asphalt specimen surfaces to mimic different stages of actual pavement surface

during the life span of the pavement. The laboratory HMA specimens were prepared

using the gyratory compactor with different number of gyrations to achieve different air

void of the test specimens. The temperature of the test specimens and the rubber slider

of the BPT, as well as the spraying water temperatures were carefully controlled in the

laboratory test program. The laboratory test results were analyzed statistically to

ascertain the significance of each test variable (air void and temperature) on the

measured friction values. Finally, a linear regression analysis of test data has yielded

useful equations for extrapolating the measured BPN or SN values at a given air void

or temperature to other different air void and/or temperature. Specific conclusions from

this chapter are enumerated below.

The effect of air voids on the measured HMA frictional properties (BPN values) was

found to be statistically significant at the 0.05 significance level. Basically, there was

an increase in friction (BPN values) corresponding to an increase in air void.

For the air void difference between 3.5% and 7.5%, the corresponding difference in

BPN is about 5.7 and the corresponding difference in SN is 4.9. Therefore, the

148

extrapolation relationships given in Equations 5-1 and 5-3 are recommended to correct

the measured BPN or SN for the desired air void other than the one during the

measurement.

The effect of temperature of the HMA surface, the rubber slider of BPT, and the

spraying water on the measured HMA friction (BPN values) was found to be

statistically significant. Essentially, there was a decrease in friction corresponding to an

increase in temperature.

For temperature difference between -11.1 °C to 50 °C (12 °F to 122 °F), the

corresponding difference in BPN is about 4.6 and the corresponding difference in SN is

4.0. Therefore, the extrapolation relationships given in Equations 5-4 and 5-5 are

recommended to correct the measured BPN or SN for the desired temperature other

than the one during the measurement.

149

CHAPTER VI

6. CORRELATION STUDY BETWEEN FRICTION MEASUREMENTS BY

LWST AND DFT

6.1 Introduction

As a part of a safety monitoring program, pavement surfaces require frequent

measurement of friction by means of some types of devices and standard procedures.

Among the widely used friction measuring devices and the corresponding standardized

procedures are the Locked Wheel Skid Trailer (LWST) and Dynamic Friction Tester

(DFT). The LWST (ASTM E 274) can only be used on actual pavement surface due to

the nature of operation. The DFT (ASTM E 1911), on the other hand, is a portable

device and therefore can be used on both field pavement surface as well as in the

laboratory prepared Hot Mix Asphalt (HMA) surface that is 0.6 m by 0.6 m (2 ft by 2

ft) surface area. The LWST is carried with either ribbed or smooth tire with skid

number measured at the speed of 64 kmph (40 mph). The DFT utilizes the standardized

rubber pads to measure the friction values at the speed ranging from 0 to 90 kmph (0 to

55 mph). There is a growing trend among the highway engineers to seek possible

correlations between the friction values measured by the LWST and the DFT so that

150

the findings obtained in the laboratory study through DFT can be related to actual

pavement performance measured through both LWST and DFT.

If the correlation can be developed accurately between the SN measured by LWST and

the DFT measured friction values, some advantages may be realized. For example, we

could use the portable Dynamic Friction Tester for pavement friction monitoring while

enjoying the advantages of DFT (i.e., easy to use, quick, accurate, and portable).

Additionally, the correlation between laboratory measured DFT and field measured SN

would allow for better interpretation of laboratory test results by relating them to field

observed performance in terms of SN values. Finally, the DFT provides friction values

at both high speed and low speed range, i.e., the friction at high speeds (DFT64, where

64 means 64 km per hour) is known to reflect macrotexture effect, while DFT friction

values at low speeds (DFT20) is known to reflect microtexture effect. One additional

advantage of the DFT device is that a companion texture measurement device (Circular

Texture Meter) can be used to measure the Mean Profile Depth (MPD) of the same

surface area of the DFT measurement.

Researchers have developed correlations between the friction properties measured by

different friction measuring devices. For instance, Wambold et al. (1998) developed a

regression equation between Friction Number (FN) measured by the DFT when the slip

speed is 20 kmph (12.5 mph) and British Pendulum Numbers (BPNs); the coefficient

of determination was found to be 86%. Henry et al. (2000) determined the regression

equation of the friction number F60 calculated from MPD and DFT measurement

151

values (i.e., DFT20, at a slip speed of 20 km/hr and DFT60, at a slip speed of 60

kmph). The resulting regression equation is found accurate provided that pavements

have Mean Profile Depth (MPD) in the range of 0.2 - 2.2 mm. Also, there has been

work to correlate the skid numbers (SN) measured by the LWST with the friction

numbers measured using the DFT (Wambold et al., 1995).

The main objective of this chapter is to present the measurements, compiled by the

authors that consist of the SN, DFT friction numbers and MPD measured by the CTM

at the same time for the same surface. From these measured data, a statistical study

was conducted to develop the relationship to predict the skid number at 64 kmph (40

mph) using the ribbed tire Locked Wheel Skid Trailer (SN(64)R) from one or the

combination of the following three measurements: the friction number at 64 kmph (40

mph) using the Dynamic Friction Tester (DFT64), the friction number at 20 kmph

(12.5 mph) measured by the Dynamic Friction Tester (DFT20), and the mean profile

depth measured by the Circular Texture Meter (MPD).

6.2 Friction and Texture Measurement Techniques in This Study

In this chapter, the techniques used for measuring friction are the locked wheel skid

trailer (ASTM E 274) using the ribbed tire and the dynamic friction tester according to

ASTM E 1911. On the other hand, the circular texture meter (ASTM E 2157) was used

to measure the macrotetexture (MPD) of the pavement surfaces.

152

6.3 Experimental Program

The experimental program is designed to conduct field work on several

selected pavement sections throughout the state of Ohio. The pertinent

information of the selected pavement sections for this study is summarized

in Table 6-1, which include information such as aggregate polish

susceptibility (extracted from previous study by Liang and Chyi, 2000) and

aggregate source used in each pavement section, the location of the tested

pavement section such as route and section milemarker, and the number of

data points obtained so far from each pavement section, among other

information. Each data point represents one set of measurement, which

consists of the skid number measured using the LWST, the friction number

measured using the DFT, and the mean profile depth measured using the

CTM. In general, all field measurements are taken on the left wheel path.

The DFT and CTM measurements are the average of two runs on the left

wheel path.

153

Table 6-1: HMA Pavement sections identification

Polish Susceptibility

Aggregate Source DistrictLocation:

Route (Section)

No. of Measurements

Data Collected in 2006

Existing Pavement Sections

Possible High Polish (Gravel)

Chesterville @ Stockport

10 007 (37.3-

39.0) 8

Possible Medium Polish (Limestone)

Sandusky Crushed @ Parkertown

3 250 (3.55-

5.11) 6

Possible Medium Polish (Dolomite)

Stoneco @ Maumee 2 025(15.68-22) 40

Possible Low Polish (Gravel)

Martin Marietta @ Apple Grove

11 250 (22.5-

25.5) 10





10 007 (37.3-

39.0) 8



3 250 (3.55-

5.11) 6


Stoneco @ Maumee 2 025(15.68-22) 36



11 250 (22.5-

25.5) 10

New Pavement Sections



3 162 (14.00-

19.00) 18


Stocker Sand & Gravel @

Gnadenhutten 11 022(5.00-8.00) 12


Stoneco @ Maumee 2 064 (8.90-

12.40) 14

Low Polish (Trap Rock)

Ontario Trap Rock @ London

12 090 (28.25-

29.21) 6

154





10 007 (37.3-

39.0) 8



3 250 (3.55-

5.11) 6


Stoneco @ Maumee 2 025(15.68-22) 36



11 250 (22.5-

25.5) 10

New Pavement Sections



3 162 (14.00-

19.00) 18


Stocker Sand & Gravel @

Gnadenhutten 11 022(5.00-8.00) 12


Stoneco @ Maumee 2 064 (8.90-

12.40) 14

Low Polish (Trap Rock)

Ontario Trap Rock @ London

12 090 (28.25-

29.21) 6

The sequence of field work at each selected pavement section generally involves three

tasks. The first task involves the use of locked wheel skid trailer to measure the skid

number at 64 kmph (40 mph) using the ribbed tire. The second task involves the

measurement of the MPD, at the same spot of skid number measurement, using the

CTM. The third task involves the measurement of the friction number using the DFT

over the speed range of 0 to 90 kmph (0 to 55 mph). In carrying out the field work at

155

each selected pavement section, the authors were careful to ensure that the same spots

(as close as possible) on each pavement section were used for all three measurements.

Further, to minimize the short-term (weather-related) and long-term (traffic-related)

effects on the three measurements, they were all conducted at about the same time.

6.4 Field Test Results and Data Analysis

A summary of the field-test results and data analysis is shown herein.

6.4.1 Typical LWST, DFT, and CTM Test Results

A sample of SN measured by the LWST for one pavement section is shown in Table

6-2 . It can be seen that general information about the location, milemarker, speed at

which the test was conducted, test date, pavement condition at the time of the test,

temperature, and the direction are provided. A sample output of a DFT run is shown in

Table 6-2(a) . The coefficient of friction can be obtained from the DFT software at the

desired speed. The sample output of one CTM run is shown in 6-2(b) with MPD in mm

plotted on the y-axis. The SN, DFT friction values at different speed and the MPD

obtained at the selected pavement sections are used in the subsequent data analysis to

establish appropriate predictive equations for SN.

156

Table 6-2: Sample of skid numbers measured using LWST for one pavement

section

a)Dynamic Friction Tester output

157

(b) Circular Texture Meter output

Figure 6-2: Dynamic Friction Tester and Circular Texture Meter outputs

(continued)

6.4.2 Analysis of Test Results

In order to develop correlations between the variables studied it is reasonable to start

with simple linear regression analysis to assess any noticeable relationship between the

individual variables and to get rid of any possible multicollinearity (linear dependency

between individual variables). Subsequently, multiple linear regression analysis was

158

performed along with some diagnostics for capturing outliers and potential influential

data points. In summary, the statistical data analyses performed include the following

five sets of analysis.

Simple linear regression analysis was performed among the following variables: SN

measured using LWST at 64 kmph (SN(64)R), FN measured using the DFT at 64

kmph (DFT64), FN measured using the DFT at 20 kmph (DFT20), and MPD measured

using the CTM (MPD). DFT64 was thought to reflect the macrotexture effect while

DFT20 was to account for microtexture effect (Wambold, 1995).

Multicollinearity analysis was carried out to detect any variable interdependency.

Multiple linear regression analysis was carried out in order to predict SN(64)R from

the following combinations of variables: (a) MPD and DFT20, (b) MPD and DFT64,

(c) DFT20 and DFT64, and (d) MPD, DFT20 and DFT64.

Problem points diagnostic for detecting any outliers and potential influential points was

also conducted.

Normality check and constant variance check on the residuals (i.e., measured -

predicted) of the dependent variable were performed to ensure that assumptions of a

normal distribution and constant variance were valid for regression analyses.

The software Statistical Package for the Social Sciences (SPSS) was used to carry out

the statistical analyses.

159

It should be noted that in presenting the statistical analysis results, not only the

coefficient of determination (R2) is reported, but also the adjusted coefficient of

determination (R2a) value. Readers can consult a typical statistical textbook for the

definition of R2 and R2a.

6.4.2.1 Simple Linear Regression

The obtained simple linear regression models for the identified variables, along

with the corresponding R2 and the R2a , are summarized in Table 6-3 and shown in

Fifure6-2(a),Figure 6-2(b),and Figure 6-2(c). It can be seen that there is a linear

relationship between the dependant variable and the independent variables. This

observation is further validated by the Analysis of Variance (ANOVA) that is used

to assess the usefulness of a model presented in Table 3, specifically by the F-value

(i.e., as F goes up, P goes down, thus indicating more regression confidence in that

there is a difference between the two means) and the P-value (the probability of

getting a value of the test statistic as extreme as or more extreme than that observed

by chance alone, if the null hypothesis Ho, is true) based on the 0.05 significance

level.

The SN(64)R is found to be significantly correlated to DFT64 (R2 = 63%). This could

be explained by the elimination of the speed effect when using the same speed in both

friction measurements, i.e. at 64 kmph (40 mph). The observed low R2 between

SN(64)R and MPD could be attributed to the fact that friction measurement by the

ribbed tire is insensitive to the macrotexture represented by MPD. The relatively higher

160

R2 between SN(64)R and DFT20, which can be viewed as an indirect measurement of

the microtexture, can be attributed to the fact that the ribbed tire is more sensitive to

microtexture than to macrotexture.

Table 6-3: Simple linear regression between SN(64)R and DFT64, DFT20, and

MPD

Correlation Model R2 (%)

R2a

(%) ANOVA Table

F P-valuea SN(64)R vs.

MPD SN(64)R=46.334+7.8

56 MPD 7.8 7.4 23.239 0

SN(64)R vs. DFT20

SN(64)R=27.174+0.441 DFT20 50.9 50.8 286.472 0

SN(64)R vs. DFT64

SN(64)R=15.460+0.726 DFT64 63 62.9 470.126 0

Figure 6-1: Simple linear regression(continued)

161

Figure 6-1: Simple linear regression

162

6.4.2.2 Multicollinearity

Prior to any multiple linear regression analysis, multicollinearity needs to be checked.

Multicollinearity can be a problem when test of significance for regression coefficient

is run. Three multicollinearity diagnostics that can be run using the SPSS are:

tolerance, Variation Inflation Factor (VIF), and condition index. Multicollinearity is

considered a problem when tolerance is less than 0.1, VIF is greater than 10, and/or

condition index is greater than 30. From analysis presented in Table 6-4 and the above

mentioned criteria, one can conclude that multicollinearity is not a problem for the data

set examined herein.

Table 6-4: Multicollinearity check using Tolerance, VIF, and Condition Index on

the independent variables

Model Collinearity Statistics

Tolerance VIF

MPD 0.900 1.11

DFT20 0.146 6.867

DFT64 0.150 6.687

6.4.2.3 Multiple Linear Regression

Several multiple linear regression analyses were performed. The first multiple linear

regression was carried out in order to predict SN(64)R from MPD, DFT20, and DFT64

using the entire data set. The outcome of the multiple linear regression is shown in the

following regression equation:

163

SN(64)R=13.748+2.216(MPD)-0.95(DFT20)+0.836(DFT64) (6-1) Where

SN(64)R= skid number measured using LWST at 64 kmph (40 mph) with ribbed tire

DFT64= friction number measured using the dynamic friction tester at 64 kmph (40

mph)

DFT20= friction number measured using the dynamic friction tester at 20 kmph (12.5

mph); and

MPD= mean profile depth measured using the circular texture meter (mm)

R2 and R2a were found to be 63.8% and 63.4%, respectively.

Table 6-5: Multiple linear regression between MPD and DFT64, MPD and DFT20,

and DFT20 and DFT64

Correlation Model R2 (%)

R2a

(%)

ANOVA Table

F P-valuea

SN(64)R vs. MPD and DFT20

SN(64)R=26.672 +1.726 MPD+0.429 DFT20

51.3 50.9 144.661 0

SN(64)R vs. MPD and DFT64

SN(64)R= 15.014+ 1.921MPD+0.709

DFT64 63.4 63.2 238.583 0

SN(64)R vs. DFT20 DFT64

SN(64)R=14.517 -0.075 DFT20+0.828 DFT64

63.2 63.4 236.453 0

a. Dependant Variable :SNLWST

164


The major objective of this chapter was to present a comprehensive set of data

collected by the authors and the accompanied statistical analyses of the data set to

develop predictive equations for SN from other variables, such as DFT and MTD. The

specific conclusions that can be made from the statistical analysis are summarized as

follows:

Skid numbers (SN(64)R) measured using LWST were correlated to friction numbers

measured using the DFT at different speeds. It was observed that SN(64)R could be

significantly correlated to DFT64. This could be explained by the fact that both

frictions were measured at the same measurement speed, thus eliminating the potential

of speed effect. In the same token, the low coefficient of determination observed for the

relationship between SN(64)R and DFT20 can be due to the difference in the

measuring speed.

The coefficient of determination between SN(64)R and MPD was found to be low. It

could be due to the fact that friction measurement by the ribbed tire of the LWST is

insensitive to the macrotexture. On the other hand, the coefficient of determination

between SN(64)R and DFT20 was high, suggesting that the ribbed tire is more

sensitive to microtexture than macrotexture, since DFT(20) reflects the effect of

microtexture.

165

Several regression equations were examined for predicting SN(64)R from (a) MPD and

DFT20, (b) MPD and DFT64, (c) DFT20 and DFT64, and (d) MPD, DFT20, and

DFT64. However, it was found that MPD did not add much to the regression model,

neither did the DFT20 (see conclusions 1 and 2). Therefore, SN(64)R can be directly

predicted from the DFT64 as shown in Table 6-3. For slightly higher accuracy

SN(64)R can be predicted from MPD, DFT20, and DFT64 as shown in equation 6-1.

166

CHAPTER VII

7. POLISHING MACHINE BASED ON HIGH-PRESSURE WATER JET

7.1 Introduction

The design concept of the first accelerated polishing device using rubber shoes

(discussed in details in Chapter III) is based on the Ohio Department of Transportation

requirements; that is, time efficient (test duration should be no longer than one day for

test to be completed), testing Hot Mix Asphalt specimens rather than just aggregate

samples (thus, providing more authentic indicator of the performance of HMA in the

field), ease of operation, and repeatability of test results. Based on the above set of

criteria, one version of accelerated polishing equipment (i.e., using the rubber pads as

polishing devices) was developed and verified in the previous chapters. The equipment

is based on a simple concept to duplicate the tire-pavement interaction in a laboratory

setting. The deign of the polishing equipment allows for pressing polishing shoes made

of Styrene-Butadiene-Rubber (SBR) onto the surface of the HMA specimen at a

constant vertical force while rotating the rubber shoes at a constant rotational speed. It

should be noted that the polishing device is designed to accommodate two specific

specimen dimensions: an 18 inch by 18 inch by 2 inch high roller-compacted slab

specimen or a 6 inch diameter by 4 inch high Superpave gyratory-compacted

167

specimen. As a result of different specimen sizes, the rubber shoes are designed

differently. For the slab specimen, a rubber ring of approximately 13 inch in outside

diameter and 9 inch in inside diameter is used to match with the area needed for the

dynamic friction tester (DFT) and circular texture meter (CTM). For the gyratory

compacted specimen, a solid rubber disk of 6 inch in diameter and 1.5 inch thick is

used. A means was provided to allow for controlled feeding of water onto the surface

of the specimen. A timing device was used to time the duration of the

polishing/abrasion action. Details of the design of the equipment and validation of the

equipment operation and test results on different HMA mixes are fully documented in

previous chapters.

In addition to the mechanical polishing device developed and studied in this

dissertation, a completely new polishing concept using the high pressure water jet is

also explored in this study. The use of a high pressure water jet in polishing HMA can

be traced to the work conducted jointly by the French LRPC (Laboratoir Ponts et

Chaussees) and Quebec MTQ (Ministere des Transport du Quebec). In their work, the

machine referred to as “GRAP” was shown to achieve the polishing action by

projecting a stream of water and very fine abrasive agent under pressure (around 1450

psi) with a given angle of incidence. Figure 7-1 provides a photograph of the prototype

machine in the laboratory. The test method is well described in Delalande (1992). The

polishing concept of the GRAP polishing machine is illustrated schematically in Figure

7-2. The water supply should be around 11.7 litters per minute (3 gallons per minute) .

The surface is swept by displacement of the projection nozzle due to a cross motion

168

table. Polishing is obtained after twenty sweep cycles (2 hours and 45 minutes

including preparation of specimens and friction measurements; however, the actual

polishing time is 45 minutes) of rectangular shape. The machine is composed of the

projection housing, volumetric powder measurer, generator for water under pressure,

water-abrasive projection nozzle, cross motion table, retrieval tray, and electric control

panel with programmable controller. Results from Delalande (1992) showed that the

limit polishing states achieved by the GRAP is comparable to that achieved by the

Accelerated British Polishing Equipment. Do et al (2001) also reported similar

reasonable test results form GRAP. The success reported by Delalande (1992) and Do,

et al (2001) provide inventive for an independent investigation of the water jet based

approach to polish HMA surface. The design of high pressure water jet based polishing

equipment and its fabrication conducted in this study is reported in this chapter,

together with some preliminary test results for assessing its applicability for HMA

surface polishing. This chapter also provides preliminary findings concerning the test

variables, such as the rotational speed, the water jet pressure, the abrasive agent used,

and the impact angel that were experimentally investigated in this study.

It is very important to note that the GRAP polishing equipment was designed to polish

aggregate specimens. Specimens are 100 mm by150 mm (4 inch by 6 inch) rectangular

plates. These specimens are made ofcoarse aggregates of similar sizes and fixed in a

resinmatrix, as shown in Figure 7-3. The new device developed in this study, however,

aims at polishing HMA surface.

169

Figure 7-1: GRAP polishing machine

Figure 7-2: Schematic depiction of GRAP polishing machine concept

170

Figure 7-3: GRAP aggregate specimen

7.2 Equipment Development

In the following section, equipment description and operational procedure are

discussed in detail.

7.2.1 Equipment Description and Operational Procedure

The guiding principle of the laboratory-scale accelerated polishing equipment using a

high-pressure water jet is that the evolution history of friction loss of the HMA surface

can be simulated and measured in a realistic short test duration. The deign of the

polishing equipment allows for projecting high-pressure water (around 1450 psi) and

fine abrasive agent onto the specimen surface at the desired angle (usually 40 degree).

A picture illustrating the proposed concept of the high-pressure water jet accelerated

polishing machine for HMA testing is shown in Figure 7-4. It should be noted that the

polishing device is designed to accommodate two specific specimen dimensions: an 18

171

inch by 18 inch by 2 inch high roller-compacted slab specimen or a 6 inch diameter by

4 inch high Superpave gyratory-compacted specimen. As a result of different specimen

sizes, the spray nozzle can polish different patterns (suitable for the different friction

and texture measuring devices) as the rotary platform rotates different specimens with

different dimensions. Therefore, the friction and texture properties of the HMA

specimen surface are determined by two approaches for the two specimen sizes: (a) the

dynamic friction tester and circular texture meter for 18 inch by 18 inch slab

specimens, and (b) British pendulum tester and sand patch method for 6 inch in

diameter gyratory compacted specimens.

Figure 7-4: Schematic depiction of the concept of the high-pressure water jet

polishing machine using HMA specimens

The high pressure asphalt polisher includes the following equipment components. The

tester includes a tubular steel frame, approximately 77 inch by 52 inch by 32 inch high,

172

to support a drum deck and a top deck. A rotary deck is inside the drum. The top deck

is double hinged which allows the deck to be lifted for access to the rotary deck. The

test specimens are placed and registered on the rotary deck for testing. The rotary deck

is inside a 45.5 inch diameter cylindrical drum that is used to help contain the water

and debris spray. The water spray nozzle is hosed inside the protection drum. Floor

levelers with antiskid pads are included for positioning the machine. A winch type

system is used to raise and lower the samples onto the rotary deck. The polisher is

equipped with a high pressure pump/5HP motor assembly, rated for 2000 PSI max, and

set at approximately 1450 PSI with 11.7 litters per minute (3.0 gallons per minute) of

water flow. The water pressure can be adjusted through a pressure gage. A nozzle

which sprays a 2 inch minimum fan type pattern and draws grit into the spray is used.

The nozzle is supported in such a way that it can be adjusted for use for either the 18

inch square specimen or the 6 inch in diameter specimen. A 56.7 litter (15 gallon) grit

tank and grit suction system is provided as well. The amount of grit mixed into the flow

can be adjusted as needed. An auxiliary spray nozzle is provided to washout residual

grit from the tank. A 2 inch NPT drain with fittings and a 2 inch hose are designed and

fabricated to drain water from the drum. A 1/2 HP variable speed drive motor with a

gear reducer is used to rotate the rotary deck at a speed of approximately 10 rpm. The

speed can be varied between approximately 6 to 16 rpm. Electrical circuit box housing:

Emergency-Stop, On Push Button for the sample rotation and the pump, and Time

Meter are provided. A motor drive to control the motor speed is also included.

173

A photograph of the completely fabricated accelerated polishing device using high-

pressure water jet with all components labeled is shown in Figure 7-5. The photograph

of the drum (chamber) used to hold either specimen size (18 inch by 18 inch by 2 inch

high roller-compacted slab specimen or 6 inch diameter by 4 inch high Superpave

gyratory-compacted specimen) is shown in Figure 7-6. The close up view of the

specimens of the two specimen sizes being subjected to high pressure water jet

polishing is shown in Figure 7-7 and Figure 7-8, respectively.

Figure 7-5: Overall view of the accelerated polishing machine using high-pressure

water

F

Figure 7-6: D

Figure 7-7: D

Drum (cham

Details on sla

174

mber) for pla

ab specimen

acing the test

n mounting i

t specimen

n the drum

In

su

In

an

sl

cu

co

th

Figure 7-

7.3 Equipm

n this section

urface are pr

7.3.1 Mater

n the evaluat

nd the aspha

lab specimen

urve of the

ontent of 5.9

he Marshall D

-8: Details o

ent Characte

n, the investi

resented.

ials

tion study of

alt binder gr

ns or the Sup

aggregate u

9% used for

Design meth

on gyratory c

eristics and V

igation resul

f the develop

rade (PG 70

perpave gyra

used for HM

r compacting

hod.

175

compacted sp

Validation

lts of using t

ped polishing

0-22) were u

atory-compa

MA is shown

g the HMA

pecimen mo

the develope

g device, a li

used to com

acted 6 inch

n in Figure

specimens w

ounting in the

ed polisher to

imestone agg

mpact the rol

specimens.

7-9. The op

were determ

e drum

o polish HM

gregate sour

ller-compact

The gradatio

ptimum bind

mined by usin

MA

rce

ed

on

der

ng

176

Figure 7-9: Aggregate gradation curve


The mixing procedure of the loose mix is identical to the mixing procedure method

presented in Chapter III.

7.3.3 Friction and Surface Texture Measurements

Different types of measuring techniques are used to measure friction and texture of the

HMA surface for the two types of specimen sizes. For the 18 inch by 18 inch by 2 inch

roller-compacted specimens, the dynamic friction tester and the circular texture meter

are used for measuring friction and texture, respectively. For the 6 inch cylindrical

gyratory-compacted HMA specimens, the British Pendulum Tester and the sand patch

method are used for measuring friction and surface texture, respectively.

0

20

40

60

80

100

120

0.001 0.01 0.1 1

Grain size (in)

Pe

rce

nt

pa

ss

ing

177

7.3.4 Work Plan

The work conducted in the development stage of the high pressure water jet based

accelerated polishing machine included the polishing of laboratory prepared HMA

specimens (i.e., roller-compacted HMA specimens and gyratory-compacted HMA

specimens) at variable rotational speed of the rotary deck housed inside the protection

drum. Also, the water pressure varied in the work plan. The water jet that impacts onto

the specimen surface is set at an angle of 40 degree to the horizontal specimen surface.

The fine grit was used. A summary of the trial test program designed to investigate the

feasibility of the developed machine is shown in Table 7-1.

Table 7-1: Work plan summary of the laboratory work

7.4 Polishing Effect of the Accelerated Polishing Machine

The polishing effect of the accelerated polishing machine is examined in this section.

For the HMA slab specimens made with limestone aggregate, the friction values (FN)

obtained from the DFT at different measuring speeds versus the polishing duration for

the trial number one (10 rpm rotation speed and 1450 psi of water pressure) are shown

178

in Figure 7-10. For the same test (Trial No. 1), the MPD measured by the CTM is

plotted versus duration of polishing in Figure 7-11. It can be seen from Figure 7-10 that

friction increases with polishing duration. Corresponding to the friction increase, there

is a similar trend of MPD increase with polishing duration as well. This polishing

behavior is opposite to what is expected. A similar trend is observed for trial number

two (10 rpm rotation speed and 400 psi of water pressure) when the slab specimen was

tested. Figure 7-12 and Figure 7-13 show the increasing trend of both friction and

texture values with the polishing duration for trial number 2 test results.

For the 6 inch HMA gyratory-compacted specimens made with limestone aggregate,

the friction values (BPN) obtained from the BPT and the MTD measured by the sand

patch method when the rotation speed was 10 rpm and the water pressure was 1000 psi

(trial number 3) are plotted against the polishing duration in Figure 7-14 and Figure

7-15, respectively. It can be seen that both the friction values and the MTD increase as

the polishing duration increases.

The test results of HMA specimens at 10-rpm rotation speed and the water pressure of

500 psi (trial number 4) are shown in Figure 7-16 and Figure 7-17. The similar trend as

trial number 3 is observed. Furthermore, one can see that the polishing behavior for

large slab specimens and gyratory-compacted specimens is similar.

The photographs of the tested HMA specimens are presented in Figure 7-18 and Figure

7-19 for the roller-compacted and gyratory-compacted specimens, respectively. It is

179

strikingly clear that high pressure water jet appears to have the effect of rejuvenate and

renew the surface such that there is the accompanied improvement of friction values.

Figure 7-10: Friction values for trial number 1 (at 10 rpm and 1450 psi)

40

60

80

100

120

0 20 40 60 80 100 120


FN

me

as

ure

d u

sin

g D

FT

0 km/hr

10 km/hr

20 km/h

30 km/hr

40 km/hr

50 km/hr

64 km/hr


Speed

180

Figure 7-11: MPD trend for Trial number 1 (at 10 rpm and 1450 psi )

Figure 7-12: Friction values for trial number 2 (at 10 rpm and 400 psi)

1.00

1.10

1.20

1.30

1.40

1.50

0 20 40 60 80 100 120


MP

D m

easu

red

usin

g C

TM

(m

m)

0

20

40

60

80

100

0 40 80 120 160 200 240


FN

me

asu

red

by

DF

T 0 km/hr

10 km/hr

20 km/h

30 km/hr

40 km/hr

50 km/hr

64 km/hr


Speed

181

Figure 7-13: MPD trend for trial number 2 (at 10 rpm and 400 psi)

Figure 7-14: Friction values of trial number 3 (at 10 rpm 1000 psi)

0.90

0.95

1.00

1.05

1.10

1.15

0 40 80 120 160 200 240


MP

D m

ea

su

red

by

CT

M (m

m)

65

70

75

80

85

0 50 100 150 200


BP

N m

easu

red

by B

PT

182

Figure 7-15: MTD trend for trial number 3 (at 10 rpm 1000 psi)

Figure 7-16: Friction values for trial number 4 (at 10 rpm 500 psi)

1.7

1.8

1.9

0 100 200 300 400 500


MT

D m

ea

sure

d b

y s

an

d p

atc

h m

eth

od

(m

m)

60

65

70

75

0 50 100 150 200


BP

N m

easu

red

by B

PT

Fig

Figu

1.

1.

1.

1.

MT

D m

ea

su

red

by

sa

nd

pa

tch

me

tho

d

(mm

)

gure 7-17: M

ure 7-18: Tes

.5

.6

.7

.8

0

MTD trend fo

sted HMA ro

50

183

or trial numb

oller-compac

100

Polishing Ti

ber 3 (at 10 r

cted slab spe

0

ime (min.)

rpm 500 psi)

ecimen surfa

150

)

ace

200

184

Figure 7-19: Tested HMA roller-compacted slab specimen surface


Presented in this chapter is the development of an accelerated laboratory-scale

polishing machine using the concept of high-pressure water jet to polish HMA surface

in a short duration, with the intention to use this equipment for screening the aggregate

source and mix design formula to ensure adequate friction (or skid resistance) of the

HMA over the expected life span of the pavement surface. The accelerated polishing

machine is designed such that it is capable of testing two different sizes of HMA

specimens: 18 inch by 18 inch by 2 inch high slab specimens compacted using the

roller compactor and 6 inch diameter and 4 inch high gyratory-compacted HMA

specimens. The design principles of the testing device, together with the evaluation

185

results of the capability of the developed polishing machine to simulate the real

polishing action, are described in detail in this chapter.

The preliminary findings based on four trial tests (two on large slab specimens and two

on small size gyratory compacted specimens), however, indicate that both friction and

texture values tend to increase with the polishing durations for two combinations of

pressure and rotation speed of the rotary deck. It seems that the more polishing action

the specimen is subjected to, the aggregate edges are created such that the surface

texture values are increased with the accompanied increase in friction values. It may be

of interest (but which is outside the scope of this study) to investigate if the similar

trend exists for HMA prepared with aggregate source that is sand and gravel.

One interesting side effect from the finding observed in this study is the concept of

using controlled high pressure water jet to rejuvenate (create) the desirable rough

surface texture for restoring the surface friction of those worn surface course made of

limestone aggregates. If this found to be technically feasible to carry out in the field

with confirmed friction restoration benefit, then it can be used to improve the friction

of the existing asphalt pavement surface, rather than the conventional approach of

resurfacing or reconstructing the pavement surface course. A substantial cost saving

can be realized in this approach of using high pressure water jet in maintaining or

improving surface friction.

186

CHAPTER VIII

8. SUMMARY AND CONCLUSIONS

Preserving adequate friction and texture values during the entire life expectancy of

asphalt pavements is of key importance in reducing skid-related accidents. The

important tasks accomplished in the course of this research are briefly summarized

below. Furthermore, conclusions and recommendations for practical implementation as

well as future research are presented at the end of this chapter.

8.1 Summary of Work Done

Presented in chapter II is a review of the literature on the concepts and theories of

polishing of aggregate and HMA, the frictional properties of aggregate and HMA, as

well as the interrelationship between aggregate source, HMA friction properties, and

HMA surface texture properties. Chapter II also provided information on the different

equipment used for accelerated polishing of aggregates and asphalt mixtures, as well as

different friction and texture measurement devices. Relevant research and practice by

the state federal highway agencies on the related topics was also covered in this

chapter.

187

Presented in Chapter III is the development of an accelerated laboratory-scale polishing

device that is capable of mimicking the polishing action of the HMA surface by a

vehicle tire in a short duration, thus allowing for screening the aggregate source and

mix design formula to ensure adequate friction (or skid resistance) of the HMA over

the expected life span of the pavement surface.

In Chapter IV, the polishing behavior of laboratory-prepared, gyratory-compacted

HMA specimens made of eight different job mix formulas was studied in terms of

friction values (BPN) and macrotexture data (MTD). In addition, the potential

relationship between BPN and MTD was also investigated.

Chapter V presented the test results of a laboratory test program to investigate the

effects of the air void and temperature on the HMA surface friction properties. The

surface friction values were determined using the British Pendulum Tester, while an in-

house accelerated polishing machine was used to polish the laboratory prepared Hot

Mix Asphalt specimen surfaces to mimic different stages of actual pavement surface

during the life span of the pavement. The laboratory HMA specimens were prepared

using the gyratory compactor with different number of gyrations to achieve different air

void of the test specimens. The temperature of the test specimens and the rubber slider

of the BPT, as well as the spraying water temperatures were carefully controlled in the

laboratory test program. The laboratory test results were analyzed statistically to

ascertain the significance of each test variable (air void and temperature) on the

measured friction values. Finally, a linear regression analysis of test data has yielded

188

useful equations for extrapolating the measured BPN or SN values at a given air void

or temperature to other different air void and/or temperature.

The major objective of Chapter VI was to present a comprehensive set of data

conducted by the authors and the accompanied statistical analyses of the data set to

develop predictive equations for SN from other variables, such as DFT and MTD.

Presented in Chapter VII is the development of an accelerated laboratory-scale

polishing machine using the concept of high-pressure water jet to polish HMA surface

in a short duration, with the intention to use this equipment for screening the aggregate

source and mix design formula to ensure adequate friction (or skid resistance) of the

HMA over the expected life span of the pavement surface. The accelerated polishing

machine is designed such that it is capable of testing two different sizes of HMA

specimens: 18 inch by 18 inch by 2 inch high slab specimens compacted using the

roller compactor and 6 inch diameter and 4 inch high gyratory-compacted HMA

specimens. The design principles of the testing device, together with the evaluation

results of the capability of the developed polishing machine to simulate the real

polishing action, are described in detail in this chapter.

8.2 Observations and Conclusions

The specific remarks or statements from the work conducted in this research can be

mentioned succinctly as follows:

189

The accelerated polishing machine is capable of testing two different sizes of

HMA specimens: 18 inch by 18 inch by 2 inch high slab specimens compacted

using the roller compactor and 6 inch diameter and 4 inch high gyratory

compacted HMA specimens. Although the device can handle two different

specimen dimensions, each with different type of compaction method, the

intended routine test sequence is geared toward the testing of 6 inch gyratory

compacted HMA specimens due to its ease of sample preparation.

Repeatability of the machine was checked and affirmed using one-way ANOVA

test.

The polishing effect of the machine was confirmed through examination of the

test results conducted on Limestone and Sand and Gravel aggregates.

Good correlation of the polishing and friction behavior was found between

aggregate specimens and the HMA specimens made with the same aggregates.

Therefore, it may be reasonable to conclude that the new accelerated polishing

machine can accomplish the intended tire/pavement wearing and polishing

mechanisms.

Image analysis validated the polishing action.

Good correlation was found between the two specimen sizes using different

compaction methods.

The developed accelerated polishing device can be used effectively for screening

polishing and friction properties of HMA mix (i.e., aggregate source, binder type

and content, etc.) during the HMA mix design stage.

190

The test procedure can be completed in a reasonable timeframe, and is simple

and efficient (i.e., less labor effort).

The correlation study between friction values measured by DFT at low

measuring speed and the BPT suggests that the BPT can be used for measuring

friction of HMA at low speeds.

A set of tentative acceptance criteria of gyratory compacted HMA specimens was

developed through two different correlations (i.e., by correlating BPN with PV or

relating BPN with SN). These acceptance criteria are divided into two parts

based on the aggregate type used; i.e., limestone or gravel. The acceptance

criteria consist of four categories: 1. highly acceptable, 2. acceptable, 3.

marginally acceptable, and 4. unacceptable, which can be used to screen and

select pertinent aggregate and HMA mix design for adequate polishing resistance

and friction values.

It has been observed that the decrease in friction (BPN values) and surface

macrotexture (MTD values) is the maximum during the first hour of polishing in

the accelerated polishing equipment. With the passage of time, the drop in BPN

and MTD decreases and eventually becomes negligible at the 6th hour of

polishing. This behavior is attributed to the presence of surface impurities on the

HMA specimen surface. With the passage of polishing time during which further

sacrificial polishing occurs, these aggregates are cleaned off. Also certain angular

protrusions on the surface of the aggregates wear off during this time to reveal a

much smoother surface. As a result, the rate of decrease in both BPN and MTD

191

becomes smaller with polishing time and eventually becomes negligible at 6th

hour of polishing action.

The macrotexture (MTD values) of HMA surface was found to be strongly

correlated with the surface friction (BPN values). In addition, good correlation

was also found between change in BPN values (BPN) and change in surface

texture (MTD) for each HMA mix as well as for each polish susceptibility

category. Therefore, the results presented in this report provide strong

quantitative evidence in supporting the strong interrelationship between the

friction and texture properties of the HMA surfaces.

The effect of air voids on the measured HMA frictional properties (BPN values)

was found to be statistically significant at the 0.05 significance level. Basically,

there was an increase in friction (BPN values) corresponding to an increase in air

void.

For the air void difference between 3.5% and 7.5%, the corresponding difference

in BPN is about 5.7 and the corresponding difference in SN is 4.9. Therefore, the

extrapolation relationships given in Equations 5-1 and 5-3 are recommended to

correct the measured BPN or SN for the desired air void other than the one

during the measurement.

The effect of temperature of the HMA surface, the rubber slider of BPT, and the

spraying water on the measured HMA friction (BPN values) was found to be

statistically significant. Essentially, there was a decrease in friction

corresponding to an increase in temperature.

192

For temperature difference between -11.1 °C to 50 °C (12 °F to 122 °F), the

corresponding difference in BPN is about 4.6 and the corresponding difference in

SN is 4.0. Therefore, the extrapolation relationships given in Equations 5-4 and

5-5 are recommended to correct the measured BPN or SN for the desired

temperature other than the one during the measurement.

Skid numbers (SN(64)R) measured using LWST were correlated to friction

numbers measured using the DFT at different speeds. It was observed that

SN(64)R could be significantly correlated to DFT64. This could be explained by

the fact that both frictions were measured at the same measurement speed, thus

eliminating the potential of speed effect. In the same token, the low coefficient of

determination observed for the relationship between SN(64)R and DFT20 can be

due to the difference in the measuring speed.

The coefficient of determination between SN(64)R and MPD was found to be

low. It could be due to the fact that friction measurement by the ribbed tire of the

SWLT is insensitive to the macrotexture. On the other hand, the coefficient of

determination between SN(64)R and DFT20 was high, suggesting that the ribbed

tire is more sensitive to microtexture than macrotexture, since DFT(20) reflects

the effect of microtexture.

Several regression equations were examined for predicting SN(64)R from (a)

MPD and DFT20, (b) MPD and DFT64, (c) DFT20 and DFT64, and (d) MPD,

DFT20, and DFT64. However, it was found that MPD did not add much to the

regression model, neither did the DFT20 (see conclusions 1 and 2). Therefore,

193

SN(64)R can be directly predicted from the DFT64 as shown in Table 6-3. For

slightly higher accuracy SN(64)R can be predicted from MPD, DFT20, and

DFT64 as shown in equation 6-2.

The preliminary findings based on four trial tests (two on large slab specimens

and two on small size gyratory compacted specimens), however, indicate that

both friction and texture values tend to increase with the polishing durations for

two combinations of pressure and rotation speed of the rotary deck. It seems that

the more polishing action the specimen is subjected to, the aggregate edges are

created such that the surface texture values are increased with the accompanied

increase in friction values. It may be of interest (but which is outside the scope of

this study) to investigate if the similar trend exist for HMA prepared with

aggregate source that is sand and gravel.

One interesting side benefit from the findings observed in this study is the

concept of using controlled high pressure water jet to rejuvenate (create) the

desirable rough surface texture for restoring the surface friction of those worn

surface course made of limestone aggregates. If this is found to be technically

feasible to carry out in the field with confirmed friction restoration benefit, then

it can be used to improve the friction of the existing asphalt pavement surface,

rather than the conventional approach of resurfacing or reconstructing the

pavement surface course. A substantial cost saving can be realized in this

approach of using high pressure water jet in maintaining or improving surface

friction.

194

8.3 Recommendations for Implementation

Using the current research results and with the eventual implementation of the friction

related Supplemental Specifications by ODOT, the contractors can develop their HMA

mix that is capable of providing satisfactory friction performance over the expected life

cycle of a pavement surface course. This in turn can eliminate any need for early

pavement resurfacing, even though the structural capacity of pavement is adequate, due

to premature loss of skid resistance. There should be tremendous cost saving as a result

of elimination of premature pavement resurfacing and prevention of unnecessary lane

closure due to resurfacing. More importantly, the wet weather related accidents can be

reduced because of maintaining high skid resistance pavement surface throughout

Ohio’s highways. Safety in the form of consistent and acceptable friction of pavement

over the life expectancy of pavement can be achieved.

The developed friction/polishing procedure can be easily incorporated as a part of

gyratory mix design procedure, as the polishing and friction test procedure only needs

the six inch diameter gyratory compacted HMA specimens. Therefore, there should be

no extra effort in preparing test specimens. Furthermore, the test duration is relatively

short, so that the final test results can be obtained on the same day of the test. Thus, the

test procedure minimizes the needs for additional labor or equipment for test specimen

preparation.

195

The developed test procedure and equipment can also be adopted by other DOTs in

their friction polishing program to ensure safety in the form of consistent and adequate

friction of pavement using their respective available aggregate sources.

To reach full adoption and implementation of the current UA accelerated polishing

equipment by ODOT and paving contractors, the following areas need to be addressed.

The correlations need to be strengthened by including long-term data from

actual pavement performance in the field.

The time-scale difference between the laboratory friction-time curve and actual

pavement friction-time curve (as affected by traffic count and environment

condition) needs to be fully understood and incorporated in the acceptance

criteria.

The current accelerated test equipment (research grade) should be further

improved, ideally through partnership with commercial equipment

manufacturers, to develop the second generation for routine testing by the

general users such as contractors, testing agencies, and highway agencies.

The developed extrapolation relationships given in Chapter V are

recommended to correct the measured BPN or SN for the desired air void or

temperature other than the one during the measurement.

8.4 Recommendations for Future Work

196

Currently, the University of Akron research team, under the sponsorship of ODOT, has

developed an efficient accelerated laboratory polishing equipment with the

accompanied friction measurement method for determining the polishing and friction

behavior of HMA with Ohio typical aggregate used in the pavement surface course.

The test protocols of the accelerated laboratory polishing equipment with the associated

acceptance criteria were developed in the current project. However, it is imperative that

a long-term validation effort be established to continue to collect field performance

data (i.e., SN from Locked Wheel Skid Trailer, Friction number measured by the

Dynamic Friction Tester and British Pendulum Tester, and surface texture measured by

Circular Texture Meter) on existing test sections (a total of eight pavement sections

throughout Ohio have already been identified and monitored for two years under the

current project). The corresponding laboratory test data on the HMA from these eight

test sections have been compiled as well. However, since polish rates are non-linear

and mix gradation, aggregate source, and binder type and content are varied, a long-

term validation of the new method through correlation with field data is needed to

confirm whether or not the expected results match actual field performance. The focus

of this research would be on validation of the long-term applicability of the laboratory

accelerated polishing test method developed by the UA Research Team.

The main objectives of future research are to validate the applicability of the developed

laboratory test protocol and acceptance criteria associated with the newly developed

accelerated polishing equipment through a correlation and comparison study with field

performance data. If necessary, improved test protocol and the acceptance criteria need

197

to be developed based on the long-term laboratory vs. field correlation study results.

The specific objectives of the future effort can be enumerated as follows.

Continue to improve and refine the laboratory test protocols to ensure ease of

implementation by the potential users, such as the contractors, the aggregate

producers, and DOT material engineers.

Validate the acceptance criteria by relating laboratory measured time-series

friction loss behavior to the time history of field performance data in the

previously selected pavement test sections throughout Ohio.

Develop ODOT Supplemental Specifications incorporating the developed

equipment and test procedures for friction/polishing criteria during the mix

design of the hot mix asphalt for a surface course.

Finally, one interesting side effect from the findings observed in Chapter VII is the

concept of using controlled high-pressure water jet to rejuvenate (create) the desirable

rough surface texture for restoring the surface friction of those worn surface course

made of limestone aggregates. If this found to be technically feasible to carry out in the

field with confirmed friction restoration benefit, then it can be used to improve the

friction of the existing asphalt pavement surface, rather than the conventional approach

of resurfacing or reconstructing the pavement surface course. A substantial cost saving

can be realized in this approach of using high-pressure water jet in maintaining or

improving surface friction. In order to come to this worthy finding, further research is

needed in this area.

198

REFERENCES

1. Abe, H., Tamai, A., Henry, J. J., and Wambold, J. (2002) “Measurement of Pavement Macrotexture with Circular Texture Meter” In Transportation Research Record: Journal of the Transportation Research Board, No. 1764, TRB, National Research Council, Washington, D.C., pp. 201-209.

2. Alsopp, H. C. (1985) “Road Surface Friction Measurements, Methods, and Machines” Anti-Lock Braking Systems for Road Vehicles, Institution of Mechanical Engineers, London: Mechanical Engineering Publications Limited, pp. 61-72.

3. American Society for Testing and Materials “Measuring Pavement Macrotexture Depth Using a Volumetric Technique” ASTM Standard Test Method E-965-96 (2001), Book of ASTM Standards, Volume 04.03, Philadelphia, PA, 2005.

4. American Society for Testing and Materials “Measuring Surface Friction Properties Using the British Pendulum Tester” ASTM Standard Test Method E-303-93 (2003), Book of ASTM Standards, Volume 04.03, Philadelphia, PA, 2005.

5. American Society for Testing and Materials “Standard Practice for Calculating International Friction Index of a Pavement Surface” ASTM Standard Test Method E-1960-03, Book of ASTM Standards, Volume 04.03, Philadelphia, PA, 2005.

6. American Society for Testing and Materials, “Insoluble Residue in Carbonate Aggregates,” ASTM Standard Test Method D-3042-03, Book of ASTM Standards, Volume 04.03, Philadelphia, PA, 2003.

7. American Society for Testing and Materials, “Accelerated Polishing of Aggregates Using the British Wheel,” ASTM Standard Test Method D-3319, Book of ASTM Standards, Volume 04.03, Philadelphia, PA, 1999.

8. American Society for Testing and Materials, “Accelerated Polishing of Aggregates or Pavement Surfaces Using a Small-Wheel, Circular Track Polishing Machine,” ASTM Standard Test Method E-660, Book of ASTM Standards, Volume 04.03, Philadelphia, PA, 2005.

9. American Society for Testing and Materials, “Determining the Polishability of Bituminous Pavement Surfaces and Specimens by Means of the Penn State Reciprocating Polishing Machine,” ASTM Standard Test Method E-1393, Book of ASTM Standards, Volume 04.03, Philadelphia, PA, 2005.

199

10. American Society for Testing and Materials, “Standard Practice for Calculating Pavement Macrotexture Mean Profile Depth,” ASTM Standard Test Method E 1845-01, Book of ASTM Standards, Volume 04.03, Philadelphia, PA, 2005.

11. American Society for Testing and Materials, “Standard Specification for Special Purpose, Smooth-Tread Tire, Operated on Fixed Braking Slip Continuous Friction Measuring Equipment,” ASTM Standard Test Method E1551-06, Book of ASTM Standards, Volume 04.03, Philadelphia, PA, 2006.

12. American Society for Testing and Materials, “Standard Test Method for Measuring Pavement Macrotexture Properties Using the Circular Track Meter,” ASTM Standard Test Method E-2157-01, Book of ASTM Standards, Volume 04.03, Philadelphia, PA, 2005.

13. American Society for Testing and Materials, “Stopping Distance on Paved Surfaces Using a Passenger Vehicle Equipped With Full-Scale Tires,” ASTM Standard Test Method E445/E445M-88(2001), Book of ASTM Standards, Volume 04.03, Philadelphia, PA, 2001.

14. American Society for Testing and Materials, Measuring Pavement Surface Frictional Properties Using the Dynamic Friction Tester, ASMT Standard Test Method E 1911-98 (2002), Book of ASTM Standards, Volume 04.03, Philadelphia, PA, 2005.

15. American Society for Testing and Materials, Skid Resistant of Paved Surfaces Using a Full-Scale Tire, ASMT Standard Test Method E 274-97, Book of ASTM Standards, Volume 04.03, Philadelphia, PA, 2005.

16. American Society for Testing and Materials, Standard Specification for Standard Rib Tire for Pavement Skid-Resistance Tests, ASTM Standard Test Method E 501-94, Book of ASTM Standards, Volume 04.03, Philadelphia, PA, 2005.

17. American Society for Testing and Materials, Standard Specification for Standard Smooth Tire for Pavement Skid-Resistance Tests, ASTM Standard Test Method E 524-88, Book of ASTM Standards, Volume 04.03, Philadelphia, PA, 2005.

18. Astrom, H. (2000) “Evaluating the VTI portable friction tester for road marking friction measurement” [In Swedish], VTI notat 45-2000, Swedish National Road and Transport Research Institute, Linkoping, Sweden.

19. Bazlamit, S. M. (1993) “Normalization of Skid Number Observations for Improved Pavement-Management Decisions”.

200

20. Bazlamit, S. M., and Reza, F. (2005) “Changes in Asphalt Pavement Friction Components and Adjustment of Skid Number for Temperature” Journal of Transportation Engineering, Vol. 131, No. 6, PP. 470-476, ASCE.

21. Beaton, J. L. (1976) “Providing Skid Resistance Pavement” Transportation Research Record 622, TRB, National Research Council, Washington, D. C., pp. 39-50.

22. Brilett, F. (1984) “Skid Resistance of Highway Pavements: Assessment of Fourteen Years of National skid-Resistance surveying” Bulletin des Liaison des Ponts, Dec.

23. Burchett, J. L., and Rizenbergs, R. L. (1980) “Seasonal Variations in the Skid Resistance of Pavements in Kentucky” In Transportation Research Record: Journal of the Transportation Research Board, No. 788, TRB, National Research Council, Washington, D.C., 12p.

24. Centrell, P. (1995) “Road marking friction—A comparison between the SRT pendulum and the VTI portable friction tester” [In Swedish], VTI notat 57, Swedish National Road and Transport Research Institute, Linkoping, Sweden.

25. Chelliah, T., Stephanos, P., Shah, M. G., and Smith T. (2003) “Developing a Design Policy to Improve Pavement Surface Characteristics” CD-ROM, Transportation Research Board, National Research Council, Washington, D.C., 24p.

26. Colony, D. C. (1984) “Skid Resistance of Bituminous surfaces in Ohio” Final Report of ODOT Project No. 3775, Ohio Department of Transportation.

27. Colony, D. C. (1992) “Influence of Traffic, Surface Age and Environment on skid Number” Final Report of ODOT Project No. 14460(O), Ohio Department of Transportation.

28. Crouch, L. K., Shirley, G., Head, G., and Goodwin, W. A. (1996) “Aggregate Polishing Resistance Pre-Evaluation”, Transportation Research Record, TRB, 1530.

29. Dahir, S. H., Henry, J. J., and Meyer, W. E. (1979) “Final Report: Seasonal Skid Resistance Variations” Pennsylvania Department of Transportation (PENNDOT), Harrisburg.

30. David, A., Kuemmel, R. C., Sontag, J. A., Crovetti, Y. B., John R J., and Allex S. (2000) “Noise and Texture on PCC Pavements” Final report multi state study, Wisconsin Department of Transportation Kinsman Blvd., Madison, Report Number WI/SPR-08-99.

201

31. Davis, R. M. (2001) “Comparison of Surface Characteristics of Hot-Mix Asphalt Pavement Surfaces at the Virginia Smart Road” Virginia Polytechnic Institute and State University, MSc Thesis, 235p.

32. Delalande, G. (1992) “Résistance des granulats au polissage – Méthode d’essai par projection” Bulletin de Liaison des LPC, 177, 73-80.

33. Dewey, G. R., Robords, A. C., Armour, B. T., and Muethel, R. (2001) “Aggregate Wear and Pavement Friction” Transportation Research Board, Annual Meeting CD-ROM, 17p.

34. Do, M. T., and Marsac, P. (2002) “Assessment of the Polishing of the Aggregate Microtexture by Means of Geometric Parameters” CD-ROM, Transportation Research Board, National Research Council, Washington, D.C., 19p.

35. Do, M. T., Kerzreho, J. P., Balay, J. M., and Gothie, M. (2003) “Full Scale Tests for the Assessment of Wear of Pavement Surface” Transportation Research Board, Annual Meeting CD-ROM.

36. Do, M. T., Ledee V., and Hardy, D. (2001) “Tire/Road Friction – Assessment of the Polishing of Road Aggregates” LCPC, Route de Bouaye, BP 4129, 44341 Bouguenais, FRANCE; e-mail: [email protected].

37. Do, M., Tang, Z., Kane, M., and Larrad, F. (2007) “Pavement Polishing-Development of a Dedicated Laboratory Test and its Correlation with Road Results” Wear 263, pp. 36-42.

38. Elkin, B. L., Kercher, K. J., and Gulen, S. (1980) “Seasonal Variation in Skid Resistance of Bituminous Surfaces in Indiana” In Transportation Research Record: Journal of the Transportation Research Board, No. 777, TRB, National Research Council, Washington, D.C., pp. 50-58.

39. Federal Aviation Administration (1971) “Measurement of Runway Friction Characteristics on Wet. Icy, or Snow-Covered Runways” U.S. Department of Transportation. Report No. FS- 160-65-68-1.

40. Flintsch, G. W., Leon, E. D., McGhee, K. K., and Al-Qadi, L. L. (2003) “Pavement Surface Macrotexture Measurement and Application” CD-ROM, Transportation Research Board, National Research Council, Washington, D.C., 24p.

41. Flintsch, G. W., Luo, Y., and Al-Qadi, I. L. (2005) “Analysis of the Effect of Pavement Temperature on the Frictional Properties of Flexible Pavement

202

Surfaces” CD-ROM, Transportation Research Board, National Research Council, Washington, D.C., 15p.

42. Gandhi, P. M., Colucci, B., and Gandhi, S. P. (1991) “Polishing of Aggregates and Wet-Weather Accident Rates for Flexible Pavments”, Transportation Research Record, TRB, 1300.

43. Gillespie, T. D., et al. (1980) “Calibration of Response-Type Road Roughness Measuring Systems” National Cooperative Highway Research Program Report 228.

44. Goodman, S. N., Hassan, Y., and Abd El Halim, A. O. (2006) “Preliminary Estimation of Asphalt Pavement Frictional Properties from Superpave Gyratory Specimens and Mix Parameters” CD-ROM, Transportation Research Board, National Research Council, Washington, D.C., 14p.

45. Hanson, D. I., and Prowell, B. D. (2004) “Evaluation of circular texture meter for measuring surface texture of pavements” NCAT Report 04-05.

46. Henry, J. J. (2000) “Evaluation of Pavement Friction Characteristics” NCHRP Synthesis of Highway Practice 291, Transportation Research Board, National Research Council.

47. Henry, J. J., Abe, H., Kameyama, S., Tamai, A., Kasahara, A., and Saito, K. (2000) “Determination of the International Friction Index (IFI) Using the Circular Testure Meter (CTM) and the Dynamic Friction Tester (DFT)” Permanent International Association of Road Congresses (PIARC) IVth Symposium on Surface Characteristics, Nantes, France, Publication No. 109.01.06.B- 2000.

48. Henry, J. J., and Leu, M. C. (1978) “Prediction of Skid Resistance as a Function of Speed from Pavement Texture” Transportation Research Record 666, Transportation Research Board, National Research Council, Washington D. C., pp. 7-10.

49. Hill, B. J., and Henry, J. J. (1978) “Short Term, Weather-Related Skid Resistance Variation” In Transportation Research Record: Journal of the Transportation Research Board, No. 836, TRB, National Research Council, Washington, D.C., pp. 76-81.

50. Hosking, J. R. (1976) “Aggregates for Skid Resistant Roads” Report 693, Transport and Road Research Laboratory, Crowthorne, Berkshire, United Kingdom.

203

51. Hosking, J. R., and Woodford, G. C. (1976b) “Measurement of skidding resistance: Part I. Guide to the use of SCRIM” No. TRRL Report LR 737, Crowthorne, UK: Department of the Environment, Transport and Road Research Laboratory.

52. Ibrahim, M. A. (2007) “Evaluating Skid Resistance of Different Asphalt Concrete Mixes,” Building and Environment 42, pp. 325-329.

53. Jackson, N. M. (2003) “Evaluation of Variable Friction Properties of FDOT Friction Courses: Phase I” FDOT Contract # BD-273, University of North Florida, 23p.

54. Janoo, V. C., and Korhonen, C. (1999) “Performance Testing of Hot-Mix Asphalt Aggregates” Special Report 99-20, US Army Corps of Engineers Cold Regions Research & Engineering Laboratory.

55. Jayawickrama, P.W., and Thomas, B. (1998) “Correction of Field Skid Measurements for Seasonal Variations in Texas” Transportation Research Record 1639, Transportation Research Board, National Research Council, Washington, D.C., pp. 147-154.

56. Kandhal, P. S., and Parker, F. (1998) “Aggregate Tests Related to Asphalt Concrete Performance in Pavements” NCHRP Report No. 405, TRB, National Research Council, Washington, D.C.

57. Khasawneh, M. A., and Liang, R. (2008) “A New Accelerated Polishing Equipment for HMA Surface” under review to be submitted to Journal of Materials, ASTM, 2008

58. Khasawneh, M. A., and Liang, R. (2008) “Friction Measurements by Locked Wheel Skid Trailer and Dynamic Friction Tester: A Correlation Study” under review to be submitted to Journal of Transportation Engineering, ASCE, 2008.

59. Kissoff, N. V. (1988) “Investigation of regional differences in Ohio pavement skid resistance through simulation modeling” PhD dissertation, University of Toledo, Toledo, Ohio.

60. Kummer, H. W. (1966) “Unified Theory of Rubber and Tire Friction” Pennsylvania State University College of Engineering, University Park.

61. Kummer, H. W., and Meyer, W. E. (1967) “Tentative Skid-Resistance Requirements for Main Rural Highways” NCHRP-37, Highway Research Board, National Research Council.

204

62. Kutner, M. H., Nachtsheim, C. J., and Neter, J. (2004) “Applied Linear Regression Models” McGraw-Hill Irwin, Boston, MA.

63. Kuttesch, J. S. (2004) “Quantifying the Relationship between Skid Resistance and Wet Weather Accidents for Virginia Data” Virginia Polytechnic Institute and State University, MSc Thesis, 140p.

64. Leu, M. C., and Henry, J. J. (1983) “Prediction of Skid Resistance as a Function of Speed from Pavement Texture” Transportation Research Record 946, Transportation Research Board, National Research Council, Washington D. C.

65. Li, S., Zhu, K., Noureldin, S., and Kim, D. (2003) “Pavement Surface Friction Test Using Standard Smooth Tire: The Indiana Experience” CD-ROM, Transportation Research Board, National Research Council, Washington, D.C., 2003, 24p.

66. Liang, R. Y. (2003) “Blending Proportions of High skid and Low skid Aggregate” Final Report of ODOT Project No. FHWA/OH-2003/014, Ohio Department of Transportation.

67. Liang, R.Y., and Chyi, L. L. (2000) “Polishing and Friction Characteristics of aggregates Produced in Ohio” Final Report of ODOT Project No. FHWA/OH-2000/001, Ohio Department of Transportation.

68. Luce, A., Mahmoud, E., Masad, E., Chowdhury, A., and Little, D. (2007) “Relationship of Aggregate Texture to Asphalt Pavement Skid Resistance” Transportation Research Board, Annual Meeting CD-ROM.

69. Lund, B. (1997) “Friction Test. Comparative Testing with 3 Different Equipment Carried Out During the summer 1996” report 82, Road Directorate, Danish Road Institute.

70. Lundkvist, S. O., and Linden, S. A. (1994) “Road marking Friction – A Comparison between the SRT Pendulum and the VTI Portable Friction Tester” VTI Notat Nr 65A-1994, Vag- och transportforskningsinstitute, Linkoping.

71. Luo, Y. (2003) “Effect of Pavement Temperature on Frictional Properties of Hot-Mix-Asphalt Pavement Surfaces at the Virginia Smart Road” Virginia Polytechnic Institute and State University, MSc Thesis, 183p.

72. McDaniel, R. S., and Coree, B. J. (2003) “Identification of Laboratory Techniques to Optimize Superpave HMA Surface Friction Characteristics” Final Report (SQDH 2003 – 6 HL 2003 – 19)

205

73. McGhee, K. K., and Gerardo, W. F. (2003) “High-Speed Texture Measurement of Pavements” Final Report No VTRC 03-R9, Virginia Transportation Research Council, Charlottesville, VA.

74. Mitchell, J. C., Phillips, M. I., and Shah, G. N. (1986) “Seasonal Variation of Friction Numbers” Report No. FHWA/MD-86/02, Maryland Department of Transportation (MDOT), Baltimore.

75. Moyer, R. A. (1934) “Skidding Characteristics of Automobile Tires on Roadway Surfaces and Their Relation to Highway Safety” Bulletin 120, Iowa Engineering Experiment Station, Ames.

76. Nitta, N. Saito, K. and Isozaki, S. (1990) “Evaluating the Polishing Properties of Aggregates and Bituminous Pavement Surfaces by Means of the Penn State Reciprocating Polishing Machine” Surface Characteristics of Roadways, International Research and Technologies, ASTM SPT 1031, W. E. Meyer, and J. Reichert, Eds., American Society for Testing and Materials, Philadelphia, PA, pp. 113-126.

77. Olson, P. L., Cleveland, D. E., Fancher, P. S., Kostynick, L. P., and Schneiter, L. W. (1984) “NCHRP Report No. 270: Parameters Affecting Stopping Sight Distance” TRB, National Research Council, Washington, D.C.

78. Page, B. G., and Butas, L. F. (1986) “Evaluation of Friction Requirements for California State 25 Highways in Terms of Highway Geometrics” Report No. FHWA/CA/TL 86/01, Federal 26 Highway Administration, Washington, D.C.

79. Runkle, S. N., and Mahone, D. C. (1980) “Variation in Skid Resistance over Time” Virginia Highway & Transportation Research Council, pp. 10-13.

80. Schmidt, B. (1999) “Friktionsmalinger. Sammenlingende Malinger Mellem ROAR och Stradograf” Rapport 90, Vejdirektoratet, Vejteknisk Institut.

81. Sherwood, W. C., and Mahone, D. C. (1970) “Predetermining the Polish Resistance of Limestone Aggregates” Highway Research Board 341, HRB, National Research Council, Washington, D. C.

82. Shupe, J. W. (1958) “A Laboratory Investigation of factors Affecting the Slipperiness of Bituminous Paving Mixtures” JHRP report, Project No. C-36-53D. Purdue University.

83. Smith, B. J., and Fager, G. A. (1991) “Physical Characteristics of Polish Resistance of Selected Aggregates” Transportation Research Board, TRB, 1301.

206

84. Tomita, M. (1964) “Friction Coefficients between Tires and Pavement Surfaces” U.S. Navy Civil Engineering Laboratory, Technical Report R303.

85. Voller, T. W., and Hanson, D. I. (2006) “Development of Laboratory Procedure for Measuring Friction of HMA Mixtures – Phase I,” Final Report of NCAT No. 06-06, National Center for Asphalt Technology.

86. Wallman, C., and Astrom, H. (2001) “Friction Measurements Methods and the Correlation between Road Friction and Traffic Safety” Swedish National Road and Transport Research Institute, 47p.

87. Wambold, J. C., and Kulakowski, B. T. (1991) “Limitations of Using Skid Number in Accident Analysis and Pavement Management” Transportation Research Record 1311, , TRB, National Research Council, Washington, D.C. pp. 43-49.

88. Wambold, J. C., Antle, C. E., Henry, J. J., and Rado, Z. (1995) “International PIARC Experiment to Compare and Harmonize Texture and Skid Resistance Measurements” Final Report, PIARC, Paris, France.

89. Wambold, J. C., Henry, J. J., and Anderson, A. (1998) “Third Year Joint Winter Runway Friction Program” National Aeronautics and Space Administration (NASA), Washington, D.C.

90. Wang, H., and Flintsch, G. W. (2007) “Investigation of Short and Long-Term Variations of Pavement Surface Characteristics at the Virginia Smart Road” CD-ROM, Transportation Research Board, National Research Council, Washington, D.C., 17p.

91. Wilson, D. J., and Dunn, R. C. M. (2005) “Polishing Aggregate to Equilibrium Skid Resistance” Road and Transport Research, Vol. 14 No. 2, pp. 55-71.

92. World Road Association, PIARC (1987) “Report of the Committee on Surface Characteristics” XVIII World Road Congress, Brussels, Belgium.

93. Yager, T. J., and Bühlmann, F. (1982) “Macrotexture and Drainage Measurements on a Variety of Concrete and Asphalt Surfaces” Pavement Surface Characteristics and Materials, ASTM STP 763. C. M. Hayden, Ed., American Society for Testing and Materials, Philadelphia, PA, pp. 16-30.

207

APPENDICES

APPENDIX A.

JOB MIX FORMULAS

Eight pavement sections were identified in different Districts in Ohio during this

research project. The selection of these pavement sections is based on the criteria that

each of the pavement sections has adequate documentation of traffic counts as well as

the construction materials (i.e., Job Mix Formulas) used.

The eight JMFs for the current study were selected to have a wide range of polish

susceptibility: for example; three aggregate sources have possible low polish

susceptibility denoted by L1, L2, and L3, four aggregate sources have possible medium

polish susceptibility denoted by M1, M2, M3, and M4, and one aggregate source has

possible high polish susceptibility denoted by H1.

Appendix A summarizes all eight job mix formulas (aggregate gradation, optimum

binder content, and other volumetric properties of HMA) used in this research that were

provided by Ohio Department of Transportation.

208

Table A-1: Percent passing, optimum binder content and volumetric properties for

low polish susceptibility aggregate

209

Figure A-1: Gradation curve for low polish susceptibility aggregate (L1)

0

20

40

60

80

100

120

0.001 0.01 0.1 1

Grain size (in)

Pe

rce

nt

pa

ss

ing

210


low polish susceptibility aggregate (L2)

211


0

20

40

60

80

100

120

0.001 0.01 0.1 1

Grain size (in)

Pe

rce

nt

pa

ss

ing

212


low polish susceptibility aggregate (L3)

213


0

20

40

60

80

100

120

0.001 0.01 0.1 1

Grain size (in)

Pe

rce

nt

pa

ss

ing

214


medium polish susceptibility aggregate (M1)

215

Figure A-4: Gradation curve for medium polish susceptibility aggregate (M1)

0

20

40

60

80

100

120

0.001 0.01 0.1 1

Grain size (in)

Perc

ent passin

g

216



217


0

20

40

60

80

100

120

0.001 0.01 0.1 1

Grain size (in)

Pe

rce

nt

pa

ss

ing

218



219


0

20

40

60

80

100

120

0.001 0.01 0.1 1

Grain size (in)

Pe

rce

nt

pa

ss

ing

220



221


0

20

40

60

80

100

120

0.001 0.01 0.1 1

Grain size (in)

Pe

rce

nt

pa

ss

ing

222


high polish susceptibility aggregate (H1)

223

Figure A-8: Gradation curve for high polish susceptibility aggregate (H1)

0

20

40

60

80

100

120

0.001 0.01 0.1 1

Grain size (in)

Pe

rce

nt

pa

ss

ing

224

APPENDIX B.

LABORATORY TEST RESULTS

The laboratory-prepared gyratory-compacted HMA specimens are polished for eight

hours using the developed accelerated polishing machine. Specimens are then tested

after each hour of polishing by the British pendulum tester and sand patch method.

Three specimens are tested for each JMF and their average is reported as the BPN and

MTD, which is a measure of the polish value and macrotexture, respectively.

Appendix B provides information on numerical values of the BPN and MTD for each

hour of polishing for all eight hours using the eight different JMFs labelled according

to their polish susceptibility. For all the JMFs studied, a residual friction (BPN) and

macrotexture (MTD) values are found to be reached at the end of eight hours of

polishing.

225

Table B-1: BPN for 8-Hour Polishing for Job mix formula # 1 (L1)

226

Table B-2: MTD for 8-Hour Polishing for Job mix formula # 1 (L1)

227


228


229


230


231

Table B-7: BPN for 8-Hour Polishing for Job mix formula # 4 (M1)

232

Table B-8: MTD for 8-Hour Polishing for Job mix formula # 4 (M1)

233


234


235


236


237


238


239

Table B-15: BPN for 8-Hour Polishing for Job mix formula # 8 (H1)

240

Table B-16: MTD for 8-Hour Polishing for Job mix formula # 8 (H1)

Documents

Cont inuing Inves tigatio n of Polishin g and · 2009-11-03 · Cont Fri inuing ction C Inves harac Aggre tigatio terist gate n of P ics of in Ohio Rober Ohio Dep Office of R U.S