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1/98 cJCIHCJDuoDmpGS-p.“

VERIFICATION OF SHRP (11) STUDY RESULTS FOR CONDITIONS OF
PAKISTAN AND PERFORMANCE ENHANCEMENT OF
AASHTO DESIGNED PAVEMENT SECTIONS
By

Ahmed J aved

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

MASTER OF SCIENCE

Department of Civil and Environmental Engineering

1998

 

ABSTRACT
VERIFICATION OF SHRP(11) STUDY RESULTS FOR CONDITIONS OF PAKISTAN
AND PERFORMANCE ENHANCEMENT OF AASHTO DESIGNED PAVEMENT
SECTIONS
By

Ahmed Javed

A total of 243 artificial pavement sections were
designed for the ranges of variables in Pakistan using AASHTO
DNPS—86 Computer Program. The mechanistic responses were then
analyzed to verify the accuracy and applicability of SHRP
results to conditions in Pakistan.

The performance of 9 out of 243 pavement sections and 3
additional pavement sections were compared relative to the
roughness, fatigue and rut. During the comparison, it was
found that the fatigue and rut performance of these 12
Pavement sections was very low as compared to their roughness
performance.

It was concluded that Pakistan needs to treat/stabilize
its Pavement bases to achieve fatigue/rut performance which

is equal to or greater than the roughness performance of the

pavement sections considered in this studY-

 

 

 

TABLE OF CONTENTS

LIST OF TABLES ......................................................................
LIST OF FIGURES .....................................................................

CHAPTER 1

INTRODUCTION ....................
1.1 GENERAL ....................
1.2 PROBLEM STATEMENT ................

 

1.3 CAUSES OF THE PROBLEM ...............

 

1.4 STUDY OBJECTIVE .................

CHAPTER 2
BACKGROUND ........................

 

2.1 INTRODUCTION ....................

2.2 STRUCTURAL COMPONENTS OF A FLEXIBLE PAVEMENT.

2.3 PAVEMENT DESIGN CONCEPTS ...................
2.3.1 Subgrade Stress ....................
2.3.2 Surface Deflection ....................
2.3.3 Tensile Stress .....................
2.3.4 Shear Stress ......................

2.4 DESIGN CRITERIA ......................

2.4.1 Ride Quality . ......................
2.4.2 Rutting .......................

 

 

2.4.3 Alligator or Fatigue Cracking .......................

 

iii

\lUIb-l

10
10
11
ll
12
12
13
13
15
15

2.5 DESIGN APPROACHES .........................

 

 

 

2.5.1 Empirical Design Approach .......................
2.5.1.1 Empirical Design Concept ............

2.5.1.2 Limitations of Empirical Design Procedures ........

2.5.2 Mechanistic-Empirical Design Approach ............

2.5.2.1 Mechanistic-Empirical Design Concept...............

Design Procedure ...............

 

2.5.2.3 Commonly used Empirical Statistical

 

 

 

Models ...................

2.6 DESIGN PROCEDURES .....................
2.6.1 Empirical Procedures ....................

2.6.1.1 AASHTO Design Procedure.

2.6.1.2 Road Note 29 .................

 

2.6.2 Mechanistic-Empirical Design Procedures”

 

 

 

2.6.2.1 VESYS (V isco-Elastic System) Method...............
2.6.2.2 Finite Element Methods .............
2.6.2.3 Elastic Layered Methods ............
CHAPTER 3
RESEARCH PLAN .........................
3.1 RESEARCH OBJECTIVES ...................

 

iv

l6

l6

16

18

18

l9

19

19

fi

26

26

27

29

41

41

 

 

 

 

3.2 RESEARCH PLAN AND METHODOLOGY .............
3.2.1 PART I .....................
3.2.2 PART II .......................
3.2.3 PART HI ......................
CHAPTER 4

AASHTO FLEXIBLE PAVEMENT DESIGN PROCEDURE

4.1

4.2

4.3

4.4

4.5

4.6

4.7

4.8

4.9

INTRODUCTION ........................

 

CHANGES IN THE 1986 AASHTO DESIGN GUIDE

OVERVIEW OF THE AASHO ROAD TEST ...............

 

DESIGN VARIABLES .......................

 

MATERIAL PROPERTIES FOR STRUCTURAL DESIGN ................

 

 

4.5.1 Effective Roadbed Soil Resilient Modulus
4.5.2 Pavement Layer Materials Characterization....................
LAYER COEFFICIENTS .....................
PAVEMENT STRUCTURAL NUMBER ................
COMPUTATION OF REQUIRED PAVEMENT THICKNESS ..........
4.8.1 Determination of the Required Structural Number ........
4.8.2 Selection of Trial Pavement Thickness Design
4.8.3 Layered Design Analysis ................

 

LIMITATIONS OF THE AASHTO FLEXIBLE PAVEMENT DESIGN

PROCEDURE . ........................

 

48

51

53

S3

53

54

58

65

71

75

75

77

79

4.10 MECHANISTIC EVALUATION/CALIBRATION............................... 84

 

 

4.10.1 Observations of the AASHTO Outputs 87
4.10.2 Mechanistic Evaluation of the AASHTO

Design Equation .................... 88
4.10.3 Conclusions ...................... 101
4.10.4 Important Concepts Relative to the Calibration

of the AASHTO Flexible Design Equations 102

 

4.11 AASHTO LAYER COEFFICIENTS ................. 104
CHAPTER 5
STUDY RESULTS SENSITIVITY ANALYSIS ................ 107

 

5.1 SENSITIVITY OF THE AASHTO EQUATION TO THE DESIGN

VARIABLES . ......................... 107

 

5.2 MECHANISTIC EVALUATION OF AASHTO FLEXIBLE PAVEMENT
DESIGN PROCEDURE - VERIFICATION OF SHRP (11) STUDY
FOR HIGHER LEVELS OF TRAFFIC .................. 114

5.2.1 Outputs from AASHTO Design Procedure. 114

 

5.2.2 Mechanistic Analysis ..................... 117
5.2.3 Verification of SHRP Results ................... 122

 

5.2.4 Mechanistic Evaluation of the AASHTO Drainage

Coefficients ......................... 152

 

vi

5.2.4.1 Layer Thickness Modification Method................. 153

5.2.4.2 Layer Coefficient Modification Method 160

CHAPTER 6

STUDY RESULTS - PREDICTED FATIGUE AND RUT PERFORMANCE OF THE

 

 

 

AASHTO DESIGNED PAVEMENT SECTIONS .................. 168
6.1 OUTPUTS FROM AASHTO DESIGN PROCEDURE 168
6.2 MECHANISTIC RESPONSES FROM ELSYMS 168
6.3 PREDICTED FATIGUE AND RUT PERFORMANCE OF THE AASHTO

DESIGNED PAVEMENT SECTIONS ................. 175
CHAPTER 7

STUDY RESULTS - ENHANCEMENT OF FATIGUE/RUT PERFORMANCE OF

 

 

THE AASHTO $86} BASED DESIGNS .................... 194
7.1 GENERAL .......................... 194
7.2 TRIAL 1, REPLACING GRANULAR BASE WITH AN AC STABILIZED

7.3

7.4

BASE (Layer Modulus equal to or greater than 250 Ksi) .... 195
TRIAL 2, ELIMINATING SUBBASE AND REPLACING GRANULAR
BASE WITH ASPHALT TREATED BASE ( Layer Modulus less than

or equal to 200 ksi) .......................... 212

 

TRIAL 3, INCREASING THE LAYER MODULI (through compaction)

OF THE GRANULAR BASE AND SUBBASE LAYER 229

vii

CHAPTER 8

CONCLUSIONS AND RECOMMENDATIONS

8.1 CONCLUSIONS

 

 

8.2 RECOMMENDATIONS

OOOOOOOOOOOOOOOO

 

viii

Table 1.1
Table 3.1
Table 3.2
Table 3.3
Table 4.1

Table 4.2

Table 4.3

Table 4.4

Table 4.5
Table 4.6
Table 4.7

Table 4.8

Table 5.1

Table 5.2

Table 5.3

Table 5.4

LIST OF TABLES

Page
Truck Factors at Taxila on N-S (Loaded Vehicles). 6
Variables for Sensitivity Analyses. 42
Sensitivity Analysis - Study variables 45
Sensitivity analysis - constant design variables. 47

Axle weight and distributions used on various loops of 57
the AASHO road test.

Recommended level of reliability for various pavement 61
functional classifications.

Recommended values of standard deviation. 62
Recommended m values for modifying structural layer 74

coofficients of untreated base and sub-base materials
in flexible pavements.

Minimum Layer Thickness. 78
Truck Factor at Taxila on N-S (Loaded Vehicles). 82
Traffic Loading Comparison AASHO Road Test

and PAKISTAN. 83
The outputs of the AASHTO design method and the 89

mechanistic responses of pavement sections 60, 87,
141, 150, 159 and 222.

Effect on thickness of variation in traffic (18-Kips 108
ESAL in millions) and layer material properties.

Layer thicknesses and moduli of the pavement sections
of Figure 5.22. 134

The mechanistic responses for 27 pavement sections of
Figure 5.22 due to 18-Kip ESAL. 136

The pavement surface deflections for 27 pavement
sections of Figure 5.22. 139

Table 5.5

Table 5.6

Table 5.7

Table 5.8

Table 5.9

Table 5.10

Table 6.1

Table 6.2

Table 6.3

Table 6.4

Table 6.5

LIST OF TABLES (Continued)

The vertical compressive stress and vertical strains
at the top tof layer for 27 sections of Figure 5.22.

The tensile stress at the bottom of the AC layer and
the ratio of the tensile stress to the AC modulus
for 27 pavement sections of Figure 5 .22.

The AASHTO outputs of the pavement sections
of cells 156, 159 and 162 of Figure 3.1 (performance
period =10 years, 18 Kip ESAL = 75,000,000).

Mechanistic reponses of the pavement sections
of cells 156, 159 and 162 of Figure 3.1.

Layer thickness, moduli, and mechanistic
responses for five values of drainage coefficients
for seciton 159 (thickness modification method).

Layer thickness, moduli, and mechanistic responses
for five values of the drainage coefficient of section
159 (Layer coefficient modification method).

Ouputs from AASHTO DNPSS6 computer program for the
pavement sections of Figure 3.2.

Mechanistic responses from ELSYMS for pavement
sections of Figure 3.2 for different axle loads
and tire pressure.

The fatigue life (Million repetitions) of AASHTO
designed pavement sections of Figure 3.2.
Axle load = l8-Kip, Tire pressure = 80 psi.

The fatigue life (Million repetitions) of AASHTO
designed pavement sections of Figure 3.2.
Axle load = 23-Kip, Tire pressure = 120 psi.

The fatigue life (Million ESALs) of AASHTO designed
pavement sections of Figure 4.2.
Axle load = 28-Kip, Tire pressure = 120 psi.

141

145

149

150

154

161

169

170

176

177

178

Table 6.6
Table 6.7
Table 6.8

Table 6.9
Table 6.10

Table 7 .1

Table 7 .2

Table 7.3

Table 7 .4

LIST OF TABLES (Continued)

Rut life (Million repetions) AASHTO designed pavement
sections of Figure 3.2.

Axle load = 18 Kip, Tire pressure 80 psi.

Rut life (Million repetitions) of AASHTO designed
pavement sections of Figure 3.2.
Axle load = 23 Kip, Tire pressure 120 psi.

Rut life (Million ESALs) of AASHTO designed Pavement
sections of Figure 3.2.
Axle load = 28 Kip, Tire pressure 120 psi.

Summary of fatigue lives (Million repetitions) of
pavement sections of Figure 3.2

Summary of rut lives (Million repetitions) of the
pavement sections of Figure 3.2

Fatigue life (Million repetitions) of AASHTO designed
sections of Figure 3.2 (Granular Base Replaced by
Asphalt stabilized Base) with respect to various fatigue
models. Axle load = 18 Kip, Tire pressure = 80 psi.

Rut life (Million repetitions) of AASHTO designed
sections of Figure 3.1 (Granular Base replaced with
Asphalt Stabilized Base) with respect to various rut
models. Axle load = 18-Kip, Tire pressure = 80 psi.

Fatigue life (Million repetitions) of AASHTO designed
sections of Figure 3.2 (Granular Base replaced with
Asphalt Stabilized Base) with respect to various rut
models. Axle load = 23-Kips, Tire pressure = 120 psi.

Rut life (Million repetitions) of AASHTO designed

sections of Figure 3.2 (Granular Base replaced with

Table 7.5

Asphalt Stabilized Base) with respect to various rut
models. Axle load = 23-Kips, Tire pressure = 120 psi.

Fatigue life (Million repetitions) of AASHTO designed
sections of Figure 3.2 (Granular Base replaced with
Asphalt Stabilized Base) with respect to various fatigue
models. Axle load = 28-Kips, Tire pressure = 120 psi.

xi

 

179

180

181

182

183

200

202

205

207

LIST OF TABLES (Continued)

Table 7.6 Rut life (Million repetitions) of AASHTO designed 210
sections of Figure 3.2 (Granular Base replaced with
Asphalt Stabilized Base) with respect to various rut
models. Axle load = 28-Kips, Tire pressure = 120 psi.

Table 7.7 Fatigue life (Million repetitions) of AASHTO designed 214
sections of Figure 3.2 (Subbase eliminated and granular
base replaced with asphalt treated base) with respect.
to various fatigue models. Axle load = 18-Kip, Tire
pressure = 80 psi.

Table 7.8 Rut life (Million repetitions) of AASHTO designed 216
sections of Figure 3.2 (Subbase eliminated and granular
base replaced with asphalt treated base) with respect
to various rut models. Axle load = l8-Kip, Tire
pressure = 80 psi.

Table 7.9 Fatigue life (Million repetitions) of AASHTO designed 219
sections of Figure 3.2 (Subbase eliminated and granular
base replaced with asphalt treated base) with respect
to various fatigue models. Axle load = 23-Kip, Tire
pressure = 120 psi.

Table 7.10 Rut life (Million repetitions) of AASHTO designed 222
sections of Figure 3.2 (Subbase eliminated and granular
base replaced with asphalt treated base) with respect
to various rut models. Axle load = 23-Kip, Tire
pressure = 120 psi.

Table 7.11 Fatigue life (Million repetitions) of AASHTO designed 224
sections of Figure 3.2 (Subbase eliminated and granular
base replaced with asphalt treated base) with respect
to various fatigue models. Axle load = 28-Kip, Tire
pressure = 120 psi.

Table 7.12 Rut life (Million repetitions) of AASHTO designed 227
sections of Figure 3.2 (Subbase eliminated and granular
base replaced with asphalt treated base) with respect
to various rut models. Axle load = 28-Kip, Tire
pressure = 120 psi.

x'ii

Table 7.13

Table 7.14

Table 7.15

Table 7.16

Table 7.17

Table 7.18

LIST OF TABLES (Continued)

Fatigue life (Million repetitions) of AASHTO designed
sections of Figure 3.2 (Granular Base and subbase but with
Increased Modulus) with respect to various fatigue models.
Axle load = l8-Kip, Tire pressure = 80 psi.

Rut life (Million repetitions) of AASHTO designed

sections of Figure 3.2 (Granular Base and subbase but with
Increased Modulus Values) with respect to various fatigue.
models. Axle load = l8-Kip, Tire pressure = 80 psi.

Fatigue life (Million repetitions) of AASHTO designed
sections of Figure 3.2 (Granular Base and subbase but with
Increased Modulus) with respect to various fatigue models.
Axle load = 23-Kips, Tire pressure = 120 psi.

Rut life (Million repetitions) of AASHTO designed

sections of Figure 3.2 (Granular Base and subbase but with
Increased Modulus) with respect to various fatigue models.
Axle load = 23-Kip, Tire pressure = 120 psi.

Fatigue life (Million repetitions) of AASHTO designed
sections of Figure 3.2 (Granular Base and subbase but with
Increased Modulus) with respect to various fatigue models.
Axle load = 28-Kip, Tire pressure = 120 psi.

Rut life (Million repetitions) of AASHTO designed

sections of Figure 3.2 (Granular Base and subbase but with
Increased Modulus) with respect to various fatigue models.
Axle load = 28-Kip, Tire pressure = 120 psi.

xiii

231

233

236

238

241

244

Figure 1.1
Figure 2.1

Figure 2.2

Figure 2.3
Figure 2.4
Figure 2.5

Figure 2.6

Figure 2.7

Figure 2.8

Figure 2.9
Figure 3.1

Figure 3.2

Figure 4.1
Figure 4.2

Figure 4.3

Figure 4.4

LIST OF FIGURES

Decision makers influence costs.

Typical asphalt pavement with agranular base showing
the critical stress/strain locations.

Typical asphalt pavement with stabilized base showing
the critical stress/strain location.

Terminal Screen: Elastic Layer Data.
Temiinal Screen: Load Data.
TemIinal Screen: Evaluation Location Data.

Terminal Screen: Output option, stresses, normal and
shear and principal.

Terminal Screen: output option 2, strains normal and
shear and principal.

Terminal Screen: output option 3, displacements.
Terminal Screen: Results Menu.

Full factorial design matrix showing layer moduli
and levels of traffic volume in terms of 18-Kip ESAL's.

Matrix representing nine pavement sections from Figure
3.1 and three additional pavement sections with roadbed
modulus of 15 ksi.

Layout of the AASHO road test.

Chart for estimating structural layer coefficient of

dense graded asphalt concrete based on the elastic
(resilient) modulus (3).

Variation in granular base layer coefficient (a2) with
various base strength parameters.

Variation in granular subbase layer coefficient (a3) with
various subbase strength parameters.

xiv

Page

20

21

32
33

35

37
38

50

56
68

69

70

Figure 45

Figure 4.6

Figure 4.7

Figure 4.8

Figure 4.9

Figure 4.10

Figure 4.11

Figure 4.12

Figure 4.13

Figure 4.14

Figure 4.15

Figure 4.16

Figure 4.17

Figure 5.1
Figure 5.2

LIST OF FIGURES (Continued)

Page

Variation in ‘a' for cement-treated bases with base strength 72

parameter.

Variation in a; for bituminous-treated bases with base
strength parameter.

Design chart for flexible pavements based on using same
values for each input.

Full factorial design matrix showing layer moduli and
levels of traffic volume in terms of 18-KIP ESAL.

Peak pavement surface deflections of the seven indicated
pavement sections.

The amount of compression in the AC layer of the seven
indicated pavement sections.

The amount of compression in the base layer of the seven
indicated pavement sections.

The amount of compression in the subbase layer of the
seven indicated pavement sections.

The amount of compression in the roadbed soil of the
seven indicated pavement sections.

The vertical strains induced at the top of each pavement
layer for the indicated pavement sections.

The vertical strains induced at the bottom of each
pavement layer for the indicated pavement sections.

Tensile stress at the bottom of AC layer of the seven
indicated pavement sections.

The ratio of the stress at the bottom of the AC layer to
its resilient modulus for the seven indicated pavement
sections.

73

76

86

91

93

94

95

96

97

98

99

100

Effect of variation in traffic on pavement layer thickness. 109

Effect of variation in AC modulus on pavement layer
thickness.

XV

110

Figure 5.3

Figure 5 .4

Figure 5.5

Figure 5.6

Figure 5.7

Figure 5.8

Figure 5.9

Figure 5.10

Figure 5.11

Figure 5.12

Figure 5.13

Figure 5.14

Figure 5.15.

Figure 5.16

LIST OF FIGURES (Continued)

Page

Effect of variation in base modulus on pavement layer thickness. 111

Effect of variation in subbase modulus on pavement layer
thickness

Effect of variation in roadbed modulus on pavement layer
thickness.

The AASHTO produced structural numbers of 243
pavement sections from design matrix in Figure 3.1 when
subbase softer than roadbed soil is omitted from analysis.

The AASHTO produced structural numbers of 243
pavement sections from design matrix in Figure 3.1 when
subbase softer than roadbed soil is included in analysis.

The AASHTO produced thicknesses (inches) of the
asphalt layers for 243 pavement sections of Figure 3.1.

The AASHTO produced thicknesses (inches) of the base
layers for 243 pavement sections of Figure 3.1.

The AASHTO produced thicknesses (inches) of the subbase
layers for 243 pavement sections of Figure 3.1.

The AASHTO produced total thicknesses (inches) for 243
pavement sections of Fig 3.1.

The vertical deflections at the top of the AC layer for
the 243 pavement sections Figure 3.1.

The vertical deflections at the top of the base layers
for the 243 pavement sections of Figure 3.1.

The vertical deflections at the top of the roadbed soil
for the 243 pavement sections of Figure 3.1.

The vertical compressive stress (psi) at the top of the
base layer for 243 pavement sections of Figure 3.1.

The vertical compressive stress (psi) at the top of the
roadbed soil for 243 pavement sections of Figure 3.1.

xvi

112

113

115

116

118

119

120

121

123

124

125

126

127

Figure 5.17

Figure 5.18

Figure 5.19

Figure 5.20

Figure 5.21

Figure 5.22

Figure 5.23

Figure 5.24

Figure 5.25

Figure 5.26

Figure 5.27

Figure 5.28

Figure 5.29

Figure 5.30

LIST OF FIGURES (Continued)

The vertical strain (microstrains) at the top of the AC
layer for 243 pavement sections of Figure 3.1.

The vertical strain (microstrains) at the top of the
base layer for 243 pavement sections of Figure 3.1.

The vertical strain (microstrains) at the top of the
roadbed soil for 243 pavement sections of Figure 3.1.

The radial stress (psi) at the bottom of the AC layer
for 243 pavement sections of Figure 3.1.

The radial tensile strain (microstrains) at the bottom
of the AC layer for 243 pavement section of Figure 3.1.

27 cells experiment matrix with material properties
and levels of traffic volume in terms of 18-kip ESAL’s.

The peak pavement surface deflections of indicated
pavement sections.

The vertical compression stress at top of layer for
indicated pavement sections.

The vertical strains at top of layer for indicated

pavement sections.

The radial tensile stress at the bottom of AC layer
for indicated pavement sections.

The ratio of the tensile stress to the value of AC
modulus for indicated pavement sections.

Peak surface deflection at top of layer for indicated
pavement sections.

The peak deflections at top of layer versus drainage
coefficients of base and subbase.

The amount of compression in each layer versus drainage
coefficients of base and subbase.

xvii

128

129

130

131

132

133

140

142

143

146

147

151

155

156

Figure 5.31

Figure 5.32

Figure 5.33

Figure 5.34

Figure 5.35

Figure 5.36

Figure 6.1

Figure 6.2

Figure 6.3

Figure 6.4

Figure 6.5

Figure 6.6

Figure 6.7

Figure 6.8

LIST OF FIGURES (Continued)
The vertical strain at top of layers versus drainage
coefficients of base and subbase.

The radial tensile stress at bottom of the AC layer versus
drainage coefficient of base and subbase.

The peak deflections at top of layer versus drainage
coefficients of base and subbase.

The amount of compression in each layer versus drainage
coefficients of base and subbase.

The vertical strain at top of layers versus drainage
coefficients of base and subbase.

The radial tensile stress at bottom of the AC layer versus
drainage coefficients of base and subbase.

Effect of axle loads on radial tensile strain at bottom
of AC layer for the indicated pavement sections.

Effect of roadbed soil on radial tensile strain
at bottom of AC layer for different levels of 18 Kip ESAL.

Effect of axle load on vertical compressive strain at top
of roadbed for the indicated pavement sections.

Comparison of predicted performances of pavement
section 199 (18 - Kip ESAL).

Comparison of predicted performances of pavement section
200 (18 - Kip ESAL).

Comparison of predicted performances of pavement section
201 (18 - Kip ESAL).

Effect of axle load on predicted fatigue performance of
pavement section 199 (Al Fatigue Model).

Effect of axle load on predicted fatigue performance of
pavement section 199 (MICHPAVE Model).

xviii

157

158

162

163

164

165

171

172

174

184

185

186

187

188

Figure 6.9

Figure 6.10
Figure 6.11
Figure 6.12

Figure 7 .1
Figure 7 .2
Figure 7 .3
Figure. 7 .4
Figure 7.5
Figure 7 .6
Figure 7.7

Figure 7.8

LIST OF FIGURES (Continued)

Effect of axle load on predicted fatigue performance of
pavement section 199 (NAASRA Fatigue Model).

Effect of axle load on predicted rut performance of
pavement section 199 (Al Rut Model).

Effect of axle load on predicted rut performance of
pavement section 199 (TRRL Rut Model).

Effect of axle load on predicted rut performance of
pavement section 199 (ERSE Rut Model).

Comparison of original and enhanced fatigue life of
pavement section 199. Axle load = 18 Kip, Tire
pressure = 80 psi, Base Type = Asphalt stabalized.

Comparison of original and enhanced rut life of pavement
section 199. Axle load = 18 Kip, Tire pressure = 80 psi,
Base Type = Asphalt stabalized.

Comparison of original and enhanced fatigue life of
pavement section 199. Axle load = 23 Kip, Tire
pressure = 120 psi, Base Type = Asphalt stabalized.

Comparison of original and enhanced rut life of pavement
section 199. Axle load = 23 Kip, Tire pressure = 120 psi,
Base Type = Asphalt stabalized.

Comparison of original and enhanced fatigue performance
of pavement section 1. Axle load = 28 Kip, Tire
pressure = 120 psi, Base Type = Asphalt stabalized.

Comparison of original and enhanced rut performance of
pavement section 199. Axle load = 28 Kip, Tire
pressure = 120 psi, Base Type = Asphalt stabalized.

Comparison of original and enhanced fatigue life of
pavement section 199. Axle load = 18 Kip, Tire
pressure = 80 psi, Base Type = Asphalt treated.

Comparison of original and enhanced rut life of pavement

section 199. Axle load = 18 Kip, Tire pressure = 80 psi,
Base Type = Asphalt treated.

. xix

 

189

190

191

192

198

201

203

206

208

211

215

217

Figure 7.9

Figure 7.10

Figure 7.11

Figure 7 .12

Figure 7 .13

Figure 7.14

Figure 7.15

Figure 7.16

Figure 7.17

Figure 7.18

LIST OF FIGURES (Continued)

Comparison of original and enhanced rut life of pavement
section 199. Axle load = 23 Kip, Tire pressure = 120 psi,
Base Type = Asphalt treated.

Comparison of original and enhanced rut life of pavement
section 199. Axle load = 23 Kip, Tire pressure = 120 psi,
Base Type = Asphalt treated.

Comparison of original and enhanced fatigue life of
pavement section 199. Axle load = 28 Kip, Tire
pressure = 120 psi, Base Type = Asphalt treated.

Comparison of original and enhanced fatigue life of
pavement section 199. Axle load = 28 Kip, Tire
pressure = 120 psi, Base Type = Enhanced Granular.

Comparison of original and enhanced fatigue life of
pavement section 199. Axle load = 18 Kip, Tire
pressure = 80 psi, Base Type = Enhanced Granular.

Comparison of original and enhanced rut life of
pavement section 199. Axle load = 18 Kip, Tire
pressure = 80 psi, Base Type = Enhanced Granular.

Comparison of original and enhanced fatigue life of
pavement section 199. Axle load = 23 Kip, Tire
pressure = 120 psi, Base Type = Enhanced Granular.

Comparison of original and enhanced rut life of
pavement section 199. Axle load = 23 Kip, Tire
pressure = 120 psi, Base Type = Enhanced Granular.

Comparison of original and enhanced fatigue life of
pavement section 199. Axle load = 28 Kip, Tire
pressure = 120 psi, Base Type = Enhanced Granular.

Comparison of original and enhanced rut life of

pavement section 199. Axle load = 28 Kip, Tire
pressure = 120 psi, Base Type = Enhanced Granular.

XX

Page
220

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245

CHLAPTTHII

INTRODUCTION

1.1 GENERAL

One of the most vital elements in the defence and socio-
economic development of any country is an effective transport
system. Today’s transport system includes road, rail, air and
marine transportation. In Pakistan, road transportation
overwhelmingly dominates the other three transportation modes .
The share of road freight and passenger traffic is estimated
at 80% and 85% respectively (1). The construction and
maintenance of the country’s road network consumes a large
proportion of the national budget. In the Seventh Five-Year
Plan (1988-93) an investment of Rupees 61.957 billion was made
in the road infrastructure and the Eight Five-Year Plan (1993-
98) envisages an investment of Rupees 74 .687 billion. The 3
budget allocations for road maintenance and new construction
schemes for financial years 1992—93 and 1993-94 are Rupees

15.556 billion and Rupees 11.323 billion respectively.

Road projects, thus, represent one of the most costly of
all public investments. In addition, road projects result in
a stream of costs that goes on for as long as the roadway
exists. This costs stream. includes not only' the initial

construction cost but other costs such as:

2

- Rehabilitation: Restoration
Resurfacing
Reconstruction

- Maintenance: Routine minor repairs

- Road User: Fuel consumption

Oil consumption

Tire wear

Parts replacement
Vehicle depreciation
Travel time

Accident

The above-mentioned costs are greatly affected by the

rate and amount of deterioration of the pavement structure.

Various studies have shown that the Asphalt Concrete

pavement deterioration is a function of:

- Pavement structural design

— Bituminous mixture design

- Traffic load and volume

- Construction practices and quality control
- Maintenance policy and procedures

- Environmental conditions

Pavement design, (pavement structural design

(AC)

and

bituminous mixture design) is the most influential factor
affecting the life-cycle cost of the pavement. Figure 1.1
shows that the pavement structural design has the most impact
on the life cycle cost of a pavement (2). Inadequate pavement
structural design and/or deficient bituminous mixture design
cause premature fatigue cracking, rutting and/or shear
failure of the pavement structure. These distress types lead
to accelerated nmintenance requirements and increased user
costs. The World bank study (3) has established that road user
costs due to rough and unsafe driving conditions are 8 to 10
fold higher than the increased maintenance costs borne by the
highway authorities. Moreover, due to the budgetary
constraints, highway authorities may not be able to carry out
timely preventive maintenance to arrest the premature pavement
deterioration. Lack of or inadequate maintenance lead to
premature failure of pavements. Thus, road networks, built at
great expense are lost due to inadequate pavement structural

and bituminous mixture designs.

1.2 PROBLEM STATEMENT

In recent years, premature manifestation of rutting and
fatigue cracking and their rapid.development to high-severity
levels have been observed on many AC pavements in Pakistan.
These prematurely deteriorated AC pavements represent a loss
of precious infrastructure worth billions of Rupees. If this
problem is continued to be neglected then new AC pavements

will also crumble prematurely and the associated avoidable

IMPACT

ON LIFE

CYCLE

COST

 

    
  
 
   
 

Concept Design
Facilities Planning
Phase

Plans and Specifications
Physical Design Phase

Construction Phase

Operation &

/- Maintenance

 

  

 

 

TIME (LIFE CYCLE)

Figure 1.1 : Decision makers influence cost

costs will form a formidable obstacle to the socio-economic

development of Pakistan.

1.3 CAUSES OF THE PROBLEM

In Pakistan, like in many other developing countries of
the world, the economics of truck transportation have
contributed to an increase in the average gross weight of
trucks such that the majority of the trucks are operating well
above the legal axle load limits. A recent axle load survey
carried out by the Military College of Engineering (MACE) at
Taxila, Rawat, Dina and Muridke on highway N-S shows gross
overloading of trucks (4). The degree of overloading in
Pakistan may be assessed from the Truck Factors (pavement
damage per pass in terms of 18,000 lbs single axle load) which
are presented in Table 1.1. As it can be seen, the highest
truck factor in U.S.A. is 1.59 compared to 15.82 in Pakistan.
As axle loads have increased, the use of higher tire pressure
has become more popular in the trucking industry to support
the increased axle loads. Heavy axle loads and high tire
pressures cause higher levels of jplastic strains in .AC
pavements, which, in turn, result in accelerated fatigue
damage and rutting failure.

The pavement structural and bituminous mixture design
procedures being currently used in Pakistan, the AASHTO and
the MARSHALL mix design are empirical and were developed for
much lighter loads and. lower tire jpressures. Hence, in

Pakistan, where trucks are heavily overloaded the use of this

Table 1.1: Truck Factors at Taxila on N-S (Loaded vehicles)

 

 

 

Truck Axle Configuration Truck TTuck Factors
Type Factor' Range in USA
2—axle Both single 4.757 0.15 — 0.21
3-axle One single & one tandem 11.850 0.29 - 1.59
4-axle All single 6.996 0.43 — 1.32
4-axle Two single & one tandem 4.380 0.43 — 1.32
S-axle One single & two tandem 14.730 0.71 - 1.39
6-axle One single, one tandem 15.820 0.71 — 1.39
& one tridem

 

 

 

 

 

procedure for designing AC pavements requires an extensive
extrapolation and thus, it is highly questionable. In
addition, since the AASHTO procedure disregards the effects of
traffic loads on pavement system behavior (i.e., stresses,
strains and deflections), the procedure is not capable of
providing adequate designs for traffic loading conditions

existent in Pakistan.

1.4 STUDY OBJECTIVES

In View of the limitations of the AASHTO empirical model
to conditions in Pakistan and its inherent inability to
consider the effects of high traffic loads on. pavement
performance and.recognizing that the development of a pavement
design procedure for Pakistan.is a time dependent process, the
overall objective of this study is to work out ehe_p;eg;e§eg

nd f ti ue life rf nce of he .AASHTO de 1
pavemen; seceiens (using vegieee rug and fetigee performance
megele) . The study consists of two parts, the first part
addresses the sensitivity of the AASHTO design procedure to
the traffic levels and range of material properties being used
in Pakistan. The second part addresses the rut and fatigue
life/performance of the AASHTO designed pavement sections. The
two parts will be executed according to the following steps

(for details see chapter 4):-

1. Establish a series of AC pavement structural design for

traffic levels existent in Pakistan.

Compute the mechanistic responses of each pavement
section and analyze sensitivity to the AASHTO determined
layer thicknesses and subsequently verify SHRP study

results (see section 4.10.2).

Select AASHTO designed pavement sections with constant
variables and estimate the "critical pavement responses"
for 23,000-lb and 28,000-lb single axle loads (120 psi

tire pressure).

Calculate the "fatigue and rut life" for each pavement
section using various fatigue and rut performance

prediction models.

Re-compute the fatigue and rut life of the AASHTO
designed pavement sections by using the alternat ive
materials, and different combinations of layer

thicknesses, and various existing fatigue/rut models.

(XLAPTIJI2

BAIHOGFKNWND

2.1 INTRODUCTION

In the early stages of development, the design and/or
evaluation of a pavement structure consisted of rule-of-thumb
precedures based on judgement and past experience. During the
period 1920 to 1940, engineers made a concerted effort to
evaluate the structural properties of soil. In the 1920‘s, the
U.S. Bureau of Public Road (BPR) developed a soil
classification system based upon the observed field
performance of soils under highway pavements. This system, in
conjunction with the accumulated data, helped the highway
engineer to correlate performance with subgrade types.
Beginning in the late 1940‘s highway engineers were faced.with
the need to predict the performance of pavement structures
subjected to heavier wheel loads and more frequencies than
they had ever experienced before. This need necessitated the
design and execution of several road test experiments
including the maryland Road Test, the WASHO Road Test in
Idaho, and the AASHO Road Test in Illinois. Results of the
road tests have led to the development of empirical design
procedures that were limited to certain soil and material
types for which they were developed. In order to extend the
road test results to other materials and to be able to
calculate the effects of various wheel loads and mixed traffic

on the pavement performance; mechanistic design method were

10

developed which provided the capability of estimating the
stresses and strains induced in the pavement structure due to
various axle load magnitudes. and configurations. The
mechanistic approaches were later augmented with pavement
performance and distress prediction models which were
developed using the results of the various road tests, field

observations, and laboratory test results.

2.2 STRUCTURAL COMPONENTS OF A FLEXIBLE PAVEMENT

The load carrying capacity of a truly flexible pavement
is brought about by the load—distributing characteristics of
the layered system. Classical flexible pavements consist of a
series of layers with the highest-quality materials placed at
or near the surface. Hence, the strength.of a typical flexible
pavement is the result of building up thick layers and,
thereby, distributing the load over the subgrade (5). The
various layers which act as structural components in a
flexible pavement are subbase, base, and.asphalt concrete (2).
The main.objective of a flexible pavement structural design is
to determine the thickness and vertical position of each
paving material. The pavement is designed to provide a
serviceable roadway for the predicted design traffic over the

selected design life.

2.3 PAVEMENT DESIGN CONCEPTS
There are several basic design concepts that form the

nucleus of any rational pavement design procedure. These

11

include the limitation of roadbed stress, surface deflection,

tensile strain at the bottom of the asphalt, and shear stress.

2.3.1 Subgrade Stress.

The subgrade stress can be decreased by increasing the
thicknesses of the asphalt, base, and/or subbase layers. The
literature (5) reveals that another’ efficient method of
reducing the vertical compressive subgrade stress. is to
increase the rigidity (moduli) of the upper pavement layers.
In a layered system, the major influence upon the stress is
usually exerted by the stiffness of the layer directly above
the subgrade. Hence in.a three layer system, the subbase layer
modulus Eh has the more pronounced effect upon stress
reduction, while the base layer modulus E2 controls the
subgrade stress for two layered systems. Therefore, in order
to reduce the subgrade stress to some tolerable design value,
one can either increase the layer thicknesses or use more

rigid material.

2.3.2 Surface Deflection

Depending upon the type of layered pavement structure
considered, the percentage of the total surface deflection
contributed by the subgrade layer varies from about 70 to 95
percent. It can, therefore, be assumed that most of the
deflection is caused by the elastic compression of the
subgrade layer. Deflections are simply the. mathematical

integration of the vertical strain with depth. Since the

L-

12

strain magnitude, for a given material, the strain magnitude
at a given point is a direct function of the stress state, it
can be deduced that the same general factors that tend to
decrease the subgrade vertical compressive stress also tend to
decrease the pavement deflection. It should be noted that a
greater reduction in stress can be accomplished by increasing
the modulus or rigidity' of the pavement layer than by

increasing the layer thicknesses (5).

2.3.3 Tensile Stress

High tensile stress at the bottom of the asphalt layer
causes shorter fatigue life. In. general, increasing the
modulus of the AC layer relative to that of the base
(increasing modulus ratio) or decreasing the thickness of the
AC relative to that of the base (decreasing thickness ratio)
cause higher tensile strain. It should be pointed out that a
maximmnr tensile stress value does occur at some low .AC
thickness value. Further decreases in this parameter causes

bearing capacity failure (5).

2.3.4 Shear Stress

On any given horizontal plane in a layered structure,
the maximum horizontal shear stress (Tn) occurs directly under
the edge of the loaded area. The 1rz value is zero directly
under the center of the loaded area and it decreases as the
radial distance from the edge of the loaded area increases.

Increasing the modulus value of the AC layer causes an

13

increase in the shear stress. It should be noted that the
maximum Tr2 value within the pavement structure occurs about
middepth (neutral axis) in the surface layer. The thickness of
the surface layer also plays a significant role in the
magnitude of shear stress development. For fixed modular ratio
E1 and E2, as the thickness of the surface layer increases, the
magnitude of the shear stress is decreases and the location of
the maximum shear stress shifts upward from about middepth of

the layer to approximately the third point.

2.4 DESIGN CRITERIA

A number of design criteria are used to describe the
terminal or failure conditions (5,6,7,). These include ride
quality, rut and alligator ( fatigue) cracking. These terms

are defined below:-

2.4.1 Ride Quality

The functional performance of a pavement concerns how
well the pavement serves the user. In this context, riding
comfort or ride quality is the dominant characteristics. In
order to quantify riding comfort, the "serviceability-
performance" concept was developed at the AASHO road test in
1957. The serviceability of a pavement is expressed in terms
of the Present Serviceability' Index (PSI). For flexible
pavements, the PSI is obtained from.measurements of roughness

and distress(cracking, patching and rut depth).The PSI scale

14

ranges from 0 (impassible pavement) to 5 (excellent pavement) .
The initial serviceability' index (pg is an engineering
estimate of the PSI value immediately after construction.
Value of (pi) established for AASHO road test conditions was
4.2 for flexible pavements. The terminal serviceability index
(pt) is the lowest acceptable PSI level before resurfacing or
reconstruction becomes necessary for the particular class of
highway. An index of 2.5 or 3.0 is often suggested for use in
the design of major highways, and 2.0 for highways with a
lower classification (6).

The original serviceability equation was developed at the

AASHO Road Test (5) and is presented below.

ps: .. 5.03-1.91 log(1+SV) - 1.38(RD)’ - 0.01(c + p)”
Where

PSI = Present Serviceability Index

log = logarithm (base 10)

Sv = Slope variance

C = Linear Feet of major cracking per 1000
ft2 area

P = Bituminous patching in ft’ per 1000 ft2 area

RD = Rut Depth in inches (both wheel tracks)

measured with a 4-foot straight edge

Since, the effects of the terms C, P, and RD in the
equation on PSI are minor relative to the effect of the slope

variance (SV), many agencies rely only on 8V to estimate ride

15

quality (6).

2.4.2 Rutting

A rut is a surface depression in the wheel paths.
Pavement uplift may occur along the sides of the rut; however,
in many instances, ruts are noticeable only after a rainfall,
when wheel paths are filled with water. Rutting stems from a
permanent deformation in any of the pavement layers or
subgrade, usually caused by consolidation or lateral movement
of the materials due to traffic loads. Rutting may be caused
by plastic movement in the mix in hot weather or inadequate
compaction during construction. Significant rutting can lead
to major structural failure of the pavement and hydroplaning
potential. Wear of the surface in the wheel path from studded

tires can also cause a type of "rutting" (6).

2.4.3 Alligator or Fatigue Cracking.

Alligator or fatigue cracking is a series of
interconnecting‘ cracks caused. by fatigue failure of the
asphalt concrete surface (or stabilized base) under repeated
traffic loading. The cracking initiates at the bottom of the
asphalt surface (or stabilized base) where tensile stress or
strain is highest under a wheel load. The cracks propagate to
the surface initially as one or more longitudinal parallel
cracks. After repeated traffic loading, the cracks connect,
forming many-sided sharp-angled pieces that develop a pattern

resembling chicken wire or the skin of an alligator. The

16

pieces are usually less than 1 foot on the longest side.
Alligator cracking occurs only in areas that are subjected to
repeated traffic loading. Therefore, it would not occur over
an entire area unless the entire area.was subjected to traffic
loading. Alligator cracking is considered a major structural

distress (6).

2 .5 DESIGN APPROACHES

In order to calculate the layer thicknesses of various
given materials to achieve a certain "life" of the pavement,
two basic approaches are being followed, namely, "empirical"

and "mechanistic-empirical".

2.5.1 Empirical Design Approach

Empirical design approach is derived from experience or
observations alone. Empirically derived relationships define
the interaction between performance, load and pavement
thickness for a given geographic location and climatic

conditions. They are easy and simple to use.

2.5.1.1 Empirical Design Concept

Empirical design approach relies largely on engineering
experience and judgement, mathematical performance or distress
models based on measurements of field performance or some
combination thereof, often without consideration of structural
theory. These models are generally used to determine the

required. pavement thickness for' a given. number of load

17

applications and/or the occurrence of distress due to pavement
material properties, subgrade type, climate and traffic
conditions.

Performance models typically takes the following form (4):

Y = A + (B1)(x1)°‘ + (13,) (x,) °’ + ----- (1390:.)

Where
Y = The predicted performance variable, such
as rutting, cracking, serviceability, etc.
x1, x,,...xn = Independent design variables, such
as traffic volume and composition,
climate, material properties, layer
thickness, etc.

A, B's, C's = Constants.

Examples of empirical models might include:-

1. Estimation of predicted loss of serviceability
for a given pavement design, traffic and
climatic conditions over a period of time.

2. Prediction of the rutting that will be found on
a particular pavement given traffic volumes and
compositions, pavement materials properties,
subgrade type, climate, etc.

3. Prediction of the number of 18-kip ESAL'S that
a pavement can withstand before fatigue cracking

reaches an unacceptable level.

18

2.5.1.2 Limitations of Empirical design Procedures
Empirical procedures are accurate only for the exact

conditions and ranges of independent variables (climate,

material properties, traffic etc) under' which they' were

developed and may actually be invalid outside of these ranges.

2.5.2 Mechanistic-Empirical Design Approach

In general, mechanistic-empirical design procedures
consists of two models; theoretical and empirical
(statistical). The theoretical model is mainly used to
calculate the pavement mechanistic responses (i.e., stresses,
strains, and deflections) based on a theoretical model. Some
methods use the linear elastic theory, some others employee
the nonlinear elastic theory, and still others use the
viscoelastic theory. The empirical/statistical model relate
the mechanistic responses to various types of load-related
distress such as rutting and fatigue cracking. Therefore, the
differences between the various mechanistic-empirical design
procedures are mainly related to the theory employed in the
method, the boundary conditions, and.to the statistical models
(pavement performance models) embedded in the method.
Mechanistic design offers the only direct analytical
consideration of the numerous variables that influences
pavement performance in a design procedure. A disadvantage of
such an approach to pavement design is that it typically
requires more comprehensive data than the empirical design

techniques (2).

19

2.5.2.1 Mechanistic-Empirical Design Concept

The basic components of mechanistic-empirical method
consists of a structural analysis of the pavement system and
the incorporation of distress or performance functions into
the method.

Structural analysis refers to the calculation of stress,
strain and deflection.in a pavement that has been subjected to
external loads or the effects of temperature or moisture. Once
these values are determined.at critical locations (see Figures
2.1 and 2.2), comparisons can.be made to the maximum allowable
values obtained from experimental or theoretical studies. The
pavement can be designed by adjusting the different layer
thicknesses so that the calculated stresses, strains and
deflections are a fraction of the maximum allowable values

(2).

2 . 5 . 2 . 2 Advantages of Mechanistic-Empirical Design Procedures .
Important advantages of this design philosophy are:-
1 . Ability to analyze a pavement for several different

failure modes, such as cracking and rutting.

2. Ability to improve the reliability of pavement design.
3 . Ability to more accurately model the behavior of pavement
sections.

2.5.2.3 Commonly used Empirical Statistical Models
1. Fatigue Models. The most commonly used fatigue

prediction models are:-

20

Compressive strain - rutting
Tensile strain - fatigue or alligator cracking
Compressive strain - rutting

Compressive strain - rutting, depressions

WHEEL LOAD

 

 

ASPHALT CONCRETE

 

 

 

 

GRANULAR BASE

 

GRAN ULAR SUBBASE

 

SUBGRADE

Figure 2.1: Typical asphalt pavement with a granular base
showing the critical stress/strain locations

21

l Compressive strain - rutting

2 Tensile strain - transverse reflective cracking or fatigue cracking
3 Compressive strain - rutting

4 Compressive strain - rutting, depressions

WHEEL LOAD

 

ASPHALT CONCRETE

 

 

STABILIZED BASE !
(ASPHALT, CEMENT, .....) g

GRANULAR SUBBASE

 

SUBGRADE

Figure 2.2: Typical asphalt pavement with a stabilized base
showing the critical stress/strain locations

22

Asphalt Institute Fatigue Model. The Asphalt
Institute model uses the following relationship to
determine the permissible strain at the bottom of

the asphalt layer (6).

Permissible strain = 240(N/106)-3.29

Or N, a 10‘ (240/6r)3.29
Monsimith Fatigue Model. Monsimith developed the
following relationship to find the fatigue life of
a pavement structure (5).

FL = K(1/£)°

The approximate values of K and C are

tabulated below:

 

 

AC Modulus C Log10 K
100 2.86 -5.08
250 2.96 -5.95
500 3.53 -8.14
1000 4.06 —10.20

The above values of c and K are to be used in the

following form of the model:

LongL a Logm(K) + c[Logm(1/e)]

23

MICK-PAVE Model. The MICHPAVE program was

developed for the Michigan department of

transportation (12). The program utilizes the

following fatigue model.

Log FL =- -2.25 - 2.8 log(Do) + 2.3(B,) + 0.92 log(E,)
+ 0.15 (The - 0.26 AV + 0.0000 Eu - 1.096
log(TS) + 1.17 log (CS) - 0.001 xv

+ log[(1+F)/32]

Where

1% = peak surface deflection

B1 = function of base and subbase thickness
E8 = modulus of base

TM:= Ac thickness

AV = percent air voids in AC

modulus of roadbed soil

It)
8
u

H
U)
ll

tensile strain at the bottom of the AC
CS = compressive strain at the top of the AC
KV = kinematic viscosity of the asphalt

F = average annual air temperature

NAASRA Model ( Australian Model). N A A S R A
developed the following relationship to predict the

fatigue life (N,) of the pavement structure(7).

N, . 10‘ (225/5,)5

Where 6, = radial strain (microstrain)

24

2. Rut Models. The most common rut prediction models

are:-

a. The Asphalt Institute Rut Model. .Asphalt Institute
developed the following relationship to predict the

number of load repetitions to 13 mm rut depth (7):-

N = 106 (482/ev)"“
Where 6,, = vertical compressive strain

(microstrain)

b. The TRRL Rut Model. The following TRRL rut model
predicts the number of load repetitions to 10 nmi

rut depth (7):-

N'= 10‘ (453/ev)L’5
Where 6,, = vertical compressive strain

(microstrain)

c. The ERES Rut Model. ERES developed following rut
model which limits the vertical strain. on the
roadbed soil to a value that will not overstress
the soil. However the literature is quite on the
maximum allowable rut depth (2):-

N =- 1.365 x 10" (ev * 10“) ""7"
Where Ev = vertical compressive strain

(microstrain)

25

2.6 DESIGN PROCEDURES
Two design procedures can be found: empirical and
mechanistic-empirical.
2.6.1 Empirical Procedures
Two of the more popular empirical design methods are,

the AASHTO and the Asphalt Institute methods:-

2.6.1.1 AASHTO Design Procedure

The AASHTO design procedure was developed as the
result of the AASHO Road Test that was conducted under a
particular set of environment, one roadbed soil, and.a limited
load/traffic conditions. The method has been modified and
revised several times. The most significant revision was made
in 1986. The 1993 revision of the AASHTO design procedure did
not include any further modification of the 1986 version.
However, the design of the asphalt overlay' was totally
revised.

The 1993 AASHTO design procedure for flexible pavements
begin with the determination of the required structural number
(SN) as a function of design reliability and standard
deviation, the number of 18-kip equivalent single axle load
(ESAL), the effective resilient modulus of the roadbed soil
0%) and the total allowable serviceability loss in terms of
PSI. Trial pavement designs are then identified by using
different layer thicknesses that provide the required
structural number, meet minimum layer thickness criteria, and

provide adequate protection for the underlying materials (2).

26

2.6.1.2 Road Note 29

Road Note 29 was first published in 1960 to provide
a guide to the structural design of roads carrying medium to
heavy traffic under British conditions of climate, materials,
traffic loading etc.
This note deals solely with the construction of new roads and

not with the resurfacing and maintenance of existing roads

(8).

2.6.2 Mechanistic-Empirical Design Procedures
Few of the more commonly used design procedure under
this approach are the VESYS, Finite element, and elastic

layered system methods.

2.6.2.1 VESYS (Visco-Elastic System) Method

The VESYS structural subsystem computer program is
designed in a modular form based on the theory of
viscoelasticity. It includes routines for the computations of
the pavement deformation in each of the N layer. The VESYS
computer program consists of four major interactive models as

follows (2):

1. Primary response model in terms of stress, strain and
displacement under static loading. The model produces a
probablistic linear viscoelastic solution for the mean
and variance of the time dependent stress, strain and

deflection at prescribed positions of a layered pavement

27

system.

2. General response model that is defined as that response
of a mathematical model resulting from any type of
loading input.

3. Damage model that consists of three submodels: rut,
cracking and roughness. The outputs of the primary and
the general response models are used for the prediction
of pavement distress.

4. Performance model in terms of present serviceability
index (PSI). In this model, the rut depth and roughness
prediction models are used in conjunction with the AASHO

developed PSI equation.

2.6.2.2 Finite Element Method
The finite element method is used for the structural
analysis of pavements, specially when the nonlinear behavior
of granular and cohesive materials is to be considered in the
mechanistic modeling. In the method it is necessary to impose
side and bottom boundaries at a reasonable distances from the
loaded area. Weak roadbed soils require deep finite element
mesh which increases the computational efforts and in case of
nonlinear problems, requires a mainframe computer (2).
Several finite element (FEM) programs have been
developed, some popular programs are:-
1. ILLI-PAVE, a stress dependent program developed at the
University of Illinois, U.S.A. The ILLI-PAVE computer

program considers the pavement as an axisymmetric solid.

28

The program uses stress-dependent resilient modulus and
failure criteria for granular materials and fine grained
soils. The principle stresses in the granular and
subgrade layers are modified at the end of each
iteration, so that they do not exceed the strength of the
materials as defined by Mohr-Coulomb failure criteria

(9).

The MICK-PAVE is very similar to ILLI-PAVE and uses
similar methods to characterize granular materials and
fine grained soils. A major improvement is the use of’
flexible boundary at a limited depth beneath the surface
of the subgrade, instead of a rigid boundary at a large
depth.below the surface. The subgrade below the flexible
boundary is considered as a homogeneous half -space, whose
stiffness matrix can be determined and superimposed to
the stiffness matrix of the pavement above the flexible
boundary to form.the overall stiffness matrix. The use of
flexible boundary greatly reduces the number of finite
elements required, especially those oblong elements at
the bottom. Consequently' the storage requirement is
significantly reduced and the program can be implemented
on personal computers. The fewer number of simultaneous
equations to be solved and the elimination of those

oblong elements also yield more accurate results (2, 12) .

29

2.6.2.3 Elastic Layered Methods
2.6.2.3.1 Asphalt Institute Method
The Asphalt Institute method for flexible pavement

design can be used to design an asphalt pavement composed of
various combinations of asphalt surface and base. emulsified
asphalt surface and base, and untreated aggregate base and
subbase. The procedure uses multi layer elastic theory for the
determination of the required pavement thickness. In the
development of the design procedure, two critical stress-
strain conditions were examined. The first is the maximum
vertical compressive strain induced at the top of the roadbed
soil (rutting) and the second is the maximum horizontal
tensile strain induced at the bottom of the asphalt concrete
layer (fatigue cracking). For a<given.set of design variables,
the larger of either the rut potential or the fatigue life
governs the thickness requirement (2). The method uses 20 to
25 percent of fatigue crack in the asphalt surface and 0.5
inch of rut as the limiting criteria.

Parameters relevant to design are traffic in terms of 18
kips single axle load, environment (design.charts are prepared

for 45°F, 60°F, 75°F) and material characteristics.

2.6.2.3.2 ELSYMS

ELSYMS is a computer program that models a three
dimensional idealized elastic layered pavement system. The
pavement may be loaded with one or more identical uniform

circular loads normal to the surface of the pavement. The

30

program computes various component, strains and displacements

along locations specified by the user, within the layered

pavement. It is a modification.of the layer 5 program.allowing

consideration of multiple loads as well as the presence of a

rigid base below the subgrade (13).

Development of the ELSYMS Procedure. ELSYMS was
developed by Gale Ahlborn of the Institute of
Transportation and Traffic Engineering (ITTE) at the
University of California, Berkeley. It is based on the
elastic layered system, with the ability to consider
multiple loads as well as the presence of a rigid base
below the subgrade. The coordinate system in ELSYMS is a
three dimensional cartesian system.

The program assumes that each layer is composed of
a weightless, homogeneous, isotropic material. The
material behaves in an ideally elastic manner, according
to Hook’s Law. Each layer is of uniform thickness and
infinite width in all horizontal directions. The bottom
elastic layer'may be semi-infinite in thickness or may'be
given a finite thickness, in which case the program
assumes the bottom elastic layer is supported by a rigid
base. The boundaries between the layers are assumed to
develop full friction, with the exception of the
interface between the bottom layer and the rigid base
where zero friction.can.be specified" The surface is free

of shear and the applied loads are assumed to be

31

identical, vertical, and uniform over circular areas. The
principle of superposition is used to determine the
response at any given point when the multiple loads are
specified. The input data consists of layer property,
load, and.evaluation coordinate data, as shown in Figures
2.3, 2.4 and 2.5. The output of ELSYMS contains a summary
of all the responses calculated at each point. These
include principal stresses and strains as well as the
normal stresses, strains, and displacements. The output
result menu and the output options are presented in

Figures 2.6, 2.7, 2.8 and 2.9.

Data Required by ELSYMS. The input data required for

ELSYMS is divided into the following three categories:-

a. Layer Properties. Each pavement analyzed.by ELSYMS
may be composed of one to five elastic layers. The
three properties required for each layer are the
thickness (in inches), Poisson’s ratio, and modulus
of elasticity. The thickness is set equal to zero
for the bottom elastic layer which is assumed to be
a semi-infinite. If a thickness is given, it is
assumed that the layer is resting on a rigid base
and the user is prompted to determine if the base
is a full friction rigid base or a no friction
base.

b. Load Data. Loading is applied to the pavement by a

series of up to ten uniform circular loads applied

32

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Displacement
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RESULTS MENU FOR ELSYM 5

LAYER = 1 z = 8 00
1. - Stresses Normal & Shear & Principal
2. - Strains Normal & Shear & Principal
3. - Displacements
4. - Return or continue with Next Layer
Selection = = >

Figure 2.8 Terminal Screen : Output Option 3
Displacements

RESULTS MENU FOR ELSYM 5

- Stresses Normal & Shear & Principal
- Strains Normal & Shear & Principal
- Displacements

- Return or continue with Next Layer

DUNH

Selection = = >

Figure 2.9 Terminal Screen : Results Menu

38

normal to the surface of the pavement. The loads
are defined by any two of the following three
properties: load force in pounds, load pressure in
psi, or load radius in inches. ELSYMS calculates
the third property based on the two entered. The
location is defined by X and Y coordinates along
the surface of the top layer of the pavement. All
load values must be positive, but the coordinates
may be positive or negative distances.

Evaluation Coordinate. ELSYMS evaluates stresses,
strains and displacements at locations determined
by the user. These locations are entered as a
series of XYZ coordinates. All combinations of KY

and Z coordinates can be evaluated.

Program Limitations. There are several limitations

imposed on the ELSYMS procedure. The first two are based

on the analysis procedure itself and the remaining are

based on array size limits in the coding. The limitations

are as follows:-

Poisson’s ratio for any layer must not have a value
of one. In addition, Poisson’s ratio for a bottom
layer on a rigid base must not equal to 0.75 and
therefore, should not be in range of 0.748 to
0.752. These values lead to impossible results or

run time errors because of the equations used in

39

the analyses.

The program uses a truncated series for the
integration. process that leads to some
approximation of the results at and near the
surface and. at jpoints located. at some distance
from the load.

The number of different pavement systems for
solution is limited only by the size of the data
file on the diskette. Each pavement is analyzed
individually' and. thus there is no program
limitation.

The number of elastic layers in the pavement
cannot exceed five.

The number of identical uniform circular loads
applied to the pavement cannot exceed ten.

The number of evaluation coordinates where results
are desired is limited to a maximum of ten XY
coordinates pairs and ten Z coordinates, for a
combined maximum of 100 points. The minimum number
would be one XY pair and one Z for a total of one
point.

For“ pavements with. a rigid. base specified, the

maximum value for coordinate Z cannot exceed the

 

4O

depth to the rigid base.
h. All values except for the XY coordinates must be

positive.

(JLAPTE1I3

IKESEAEKHHIHJUN

RESEARCH OBJECTIVES

As stated in chapter 1, the research objectives are:-

Establish a series of AC pavement structural design by
using the AASHTO procedure (DNPS-86) for various
combinations of roadbed soil modulus, structural layer
material properties and traffic levels existent in

Pakistan (see Table 3.1).

Compute the mechanistic responses of each pavement
section using ELSYMS for a standard 18,000-lb single axle
load (80 psi tire pressure) and analyze their sensitivity
to the assigned range of variables (roadbed and layer
moduli and traffic levels) and subsequently verify SHRP
study results (see section 4.10.2) for ranges of

variables in Pakistan.

Select AASHTO designed pavement sections from Table 3.1
with the constant variables as given below and then
calculate "critical pavement responses" using ELSYMS for
23,000-lb and 28,000-lb single axle load (120 psi tire

pressure).

- AC layer coefficient, a1 = 0.44

41

Table 3.1: Study Variables

 

42

J"

for Sensitivity Analyses

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Test Test Level
Variable

I II III
AC Modulus 150 300 450
(ksi)
Base Modulus 20 30 40
(ksi)
Subbase 10 15 20
Modulus
(ksi)
Roadbed Soil 7.5 10 20
Modulus
(ksi) H
18,000-lb 25 50 75
ESAL's
(million)

43

- Base layer coefficient, a.2 = 0.14

1.00

- Base drainage coefficient, m2

- Subbase layer coefficient, a3 0.11

Subbase drainage coefficient, ab = 1.00

- Design reliability, R = 95%

- Overall standard. deviation, 80 == 0.45 (Traffic
errors included)

- Performance period = 10 years

- Loss in serviceability = 1.9

Calculate the "fatigue and rut life" for each pavement
section (for loading conditions of 18,000 lb, 23,000 lb
and 28,000 lb) using various fatigue and rut performance

prediction models.

Re-compute adopting combinations of strategies mentioned

below, the fatigue and rut life of the AASHTO designed

pavement sections after changing the material properties

and using different combinations of layer thicknesses and

check them against various other existent fatigue and rut

criterion.

a. Use asphalt stabilized base with layer moduli
values ranging between 250,000 and 450,000 psi.

b. Eliminate subbase layer and use asphalt treated
base (elastic modulus value up to 200,000 psi).

c. Use granular base and subbase but with increased

layer moduli (increase in layer moduli to be

44

achieved through compaction and.better gradation of

the materials).

To accomplish the above objectives a 3-part research plan

was formulated. These parts are presented in the next section.

3.2 RESEARCH PLAN AND METHODOLOGY

As stated early, a 3-parts research plan was formulated and

executed as presented below:-

3.2.1 PART I -Sensitivity Analysis of outputs from AASHTO
design procedure (DNPS-86 computer program) and verification
of SHRP study results (11) for ranges of variables in

Pakistan. This part consists of two phases as follows:-

PHASE I - In this phase a series of AC pavement structures
was designed by using the AASHTO design guide (the
AASHTO DNPS-86 computer program was used). In the
design, a range of variables (roadbed and layer
moduli and traffic levels) similar to that existing
in Pakistan was used. Table 3.2 and Figure 3.1
provide a list of the values of these variables. As
it can be seen from Figure 3.1, the design matrix
consists of 243 cells. Each cell representing a
pavement section. Table 3.3 provides a list of the
constant values of the other design input required

by the AASHTO. These constant values have no impact

 

45

Table 3.2: Sensitivity analysis - Study variables.

 

Ranges of values

 

Design Variables

Nominal

 

Low High
Traffic in terms of 18-kips 25 50 75
ESALs (millions)
Asphalt concrete resilient 150 300 450
modulus (ksi)
Base resilient modulus (ksi) 20 30 40
Subbase resilient modulus (ksi) 10 15 20
Roadbed resilient modulus (ksi) 7.5 10 20

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47

Table 3.3: Sensitivity analysis - Constant design variables

 

 

Design Variables value
Design and analysis period (years) 10
Loss in serviceability 1.9
Reliability 95%
Standard deviation 0.45
Drainage coefficient (all layers) 1.0
Wheel load (lbs) 9000
Tire pressure (psi) 80

Poisson's ratio

AC 0.40
Base 0.35
Subbase 0.35

Roadbed 0.45

48

on this study. The sensitivity of the AASHTO
outputs (layer thicknesses) to the assigned range

of variables was then determined.

PHASE II- In this phase the mechanistic responses of each
pavement section of Figure 3.1 to 18,000 lb axle
load (80 psi tire pressure) were determined using
the ELSYMS computer program. The mechanistic
responses were then analyzed to verify the accuracy
and applicability of SHRP results (11) to
conditions in Pakistan. Initially it was planned to
verify the results of the study using field data.
Unfortunately such data was not available and

consequently this alternate plan was formulated.

3.2.2 PART II - In this part the performance of some of
the pavement sections of Figure 3.1 was compared relative to
the roughness, rut and fatigue cracking. In the comparison
several existing rut and fatigue performance models and the
AASHTO roughness models were used and relative performance of
9 pavement sections (9 cells) of Figure 3.1 was predicted.
These 9 pavement sections were chosen because the material
properties (layer coefficient and moduli) are equivalent to
those used in Pakistan for the design of pavement structures.
During the analysis 3 additional pavement sections with.15 ksi
roadbed modulus were also designed by using the AASHTO design

guide and their relative performance were predicted. The

49

reason for addition of these three cells is to narrow the gap
in the values of the roadbed modulus. Figure 3.2 shows the
original 9 cells of Figure 3.1 and the 3 new cells alongwith
the material properties used in the design. The analysis in

this part consists of the following 3 steps.

STEP 1- The ELSYMS computer program was used to calculate
the radial tensile strain at the bottom of the AC
layer and the vertical compressive strain at the
top of the roadbed soil for the pavement sections
of Figure 3.2. The following combinations of axle

loads and tire pressures were used in the

analysis:-
Axle Load(lbs) Tire Pre ure si
18000 80
23000 120
28000 120
STEP 2- The fatigue life of each of the 12 pavement

sections of Figure 3.2 was then estimated by using

the following models:-

a) Asphalt Institute Fatigue Model

b) Monismith Fatigue Model

c) MICE-PAVE Fatigue Model. The parameters used
in the MICH-PAVE model are:

Percent air voids in Asphalt mix = 6.5%, the

50

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STEP 3

51

average value used by the National Highway

Authority (NHA).

The kinematic viscosity of the asphalt binder
of 270.00 centistoke.

An average annual temperature of 88°F (This is
the average annual temperature observed in
Risalpur area for the year 1993).

d) NAASRA Fatigue Model

The number of load repetitions to cause a specific
rut depth for the 12 cells of Figure 3.2 was
calculated by using the following three rut models
(It is to be noted that each model was caliberated

for different rut depth as mentioned in chapter 2):

a) Asphalt Institute Rut Model
b) TRRL Rut Model

c) ERES Rut Model

PART III - ENHANCEMENT OF THE PERFORMANCE OF THE

AASHTO DESIGNED PAVEMENT SECTIONS

In this part, the performance of each of the 12 pavement

sections of Figure 3.2 was reassessed by using the following

alternatives:-

1. Alternative 1. Replace the granular base layer with

52

asphalt stabilized layer with a range of elastic moduli

from 250 to 450 ksi.

2. Alternative 2. Eliminate the subbase layer and use

asphalt treated base with a modulus value of 200 ksi.

3. Alternative 3. Increase the layer moduli of the granular
base and subbase layer. The modulus of the base layer
will be increased to a maximum value of 75 ksi and the
modulus of the subbase layer to a maximum value of 40

ksi.

The 3 alternatives provide the means to the highway engineer
to optimize the material selection process relative to

pavement performance and cost.

(HLAPTTHK4

IUMEHTT)FLEXIBLEHHNVENHEWTIHflflKHWPTKNCEDIHUE

4.1 INTRODUCTION

The design procedure recommended by the American
Association of State Highway and Transportation Officials
(AASHTO) is based on the results of the extensive AASHO Road
Test conducted in Ottawa, Illinois, in the late 19509 and
early 19608. The AASHO Committee on Design first published an
interim design procedure in 1961. It was revised in 1972 and
1981. In 1984-85, the subcommittee on Pavement Design and a
teanlof consultants revised.and expanded the interimgprocedure
under NCHRP Project 20-7/24 and issued the 1986 Design.Guide.

The empirical performance equations obtained from the
AASHO Road Test are still being used as the basic models in
the current guide but were modified and extended to make them
applicable to other regions in U.S.A. It should be kept in
mind that the original equations were developed under a given
climatic setting with a specific set of pavement materials and
subgrade soils. The climate at the test site is temperate with
an average annual precipitation of about 34 in. The subgrade
soils consisted of A-6 and A-7-6 that are poorly drained, with

CBR values ranging from 2 to 4.

4.2 CHANGES IN THE 1986 AASHTO Design Guide

The 1986 AASHTO Design Guide presents major changes in

several areas including (6):-

53

54

Reliability. A reliability factor based on variations in
the input variables was introduced into the 1986 AASHTO
guide.

Soil Support Value. The soil support value has been
replaced with the effective resilient modulus of the
roadbed soil.

Layer coefficients. The 1986 AASHTO Guide suggests the
use of the resilient moduli of the layers to assigned
layer coefficients to both stabilized and unstabilized
materials.

Regional factor. The subjective regional factor was
replaced by a rational approach to account for the
effects of environmental factors such as moisture,
temperature, and freeze-thaw cycles on pavement design.
Traffic and Load Equivalency Values. Extensive
information concerning methods for calculating equivalent
single axle loads are provided. Load equivalency values
have been extended to include heavier loads, more axles,
and terminal serviceability levels of up to 3.0.
Mechanistic-Empirical Design Procedure. A state of
knowledge concerning mechanistic-empirical design

concepts is provided in the guide.

4.3 OVERVIEW OF THE AASHO ROAD TEST

The AASHO Road Test was conducted near Ottawa, Illinois,

U.S.A, located about 80 miles southwest of Chicago. The site

was chosen because the soil within the area was uniform and

55

representative of the country. The climate was typical of that
found in the northern United States.

The Test facilities consisted of six two lane test loops,
constructed as shown in Figure 4.1. The north tangent of each
loop was constructed of flexible pavement sections and the
south tangent was constructed of rigid pavement sections. Most
of the 234 flexible pavement structural design sections (468
test sections each 160 feet in length) comprised a complete
replicated factorial experiment to investigate the effects of
varying the thicknesses of surface, base and subbase layers.
Several additional studies were conducted to evaluate surface
treatments, shoulders, and. four' different types of base
layers: crushed stone,gravel, cement-treated. gravel, and
bituminous-treated gravel.

All vehicles assigned to any one traffic lane in loops 2
through 6 (no traffic operated over lane 1) had the same axle
arrangement and axle load combinations, as described in Table
4.1. The tire pressure and steering axle loads were
representative of normal practice at that time. The test was
conducted over a two year period which was sufficient to allow
the application of 1,114,000 load applications to each loop
(2).

Several measurements were taken at regular intervals to
assess pavement performance. These include transverse pavement
profile to determine rutting, cracking, patching, deflections,
strains, layer thickness, and temperature. This information

was used directly in the development of the performance models

S6

  
 
 
   
 
    

PRESTRESSED

' Test Tangent—-——-1 / caucus":

iFtexible

 

 

   

   
   
 

R Id
L——Test Tangent

LOOP 5

 

STEEL I’BEAH

 
 
    
   
 

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CONCRETE

 

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leXIbleZ

 
  
 

RI Id
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LOOP 6

STEEL l-BEAN

Figure 4.1 Layout of the ASSHO road test

Table 4.1

57

 

Axle weights and distributions used on various
loops of the AASHO road test
LOOP LANE WEIGHT IN KIPS

 

 

 

 

FRONT LOAD GROSS
AXLE AXLE WEIGHT
2 2 4
2 6 8
4 12 28
6 24 54
6 18 42
9 32 73
6 22.4 51
9 4O 89
9 3O 69
12 48 108

 

 

 

 

58

that eventually became the basis for the current AASHTO Design

Guide.

4.4 DESIGN VARIABLES
The general design variables considered in the design and

construction of any pavement structure are presented below

(6).

1. Time constraints. Time constraints permit the designer
to select from strategies ranging from ‘the initial
structure lasting" the entire analysis jperiod (i.e.,
performance period equals the analysis period) to stage
construction with an initial structure and planned
overlays (6). To achieve the best use of available funds,
the AASHTO Design Guide encourages the use of a longer
analysis period (for high-volume facilities), that
include at least one rehabilitation period. Thus, the
analysis period should be equal to or greater than the
performance period (9).

a. Performance Period. This refers to the period of
time that an initial pavement structure will last
before it needs rehabilitation. It also refers to
the performance time between rehabilitation
operations. In the AASHTO design guide, the
performance period is equal to the time elapsed as
the new, reconstructed, or rehabilitated pavement

deteriorates from its initial serviceability to its

59

terminal serviceability. For the performance
period, the designer must select minimum and
maximum bounds that are established by the agency
experience (6). The selection of performance period
can be affected by such factors as the functional
classification of the pavement, the type and level
of maintenance applied, the available funds for
initial construction, life cycle cost, and other
engineering considerations (9).

b. Analysis Period. This refers to the period of
time for which the analysis is to be conducted,
i.e., the length of time that any design strategy
must cover. Because of the consideration of the
maximum performance period, it may be necessary to
consider and plan for stage construction (i.e., an
initial pavement structure followed by one or more
rehabilitation operations) to achieve the desired
analysis period. In the past, pavements were
typically designed and analyzed for a 20-year

performance period (6).

Traffic. The design procedures for both highways and low
volume roads are all based on cumulative expected 18-kip
equivalent single axle loads (ESAL) during the
performance and analysis periods (6). If a pavement is
designed for the analysis period without any

rehabilitation or surfacing, all that is required is the

60

total ESAL over the analysis period. However, if stage
construction is considered and rehabilitation or
resurfacing is anticipated, a graph or equation of
cumulative ESAL versus time is needed so that the ESAL
traffic during any given stage can.be obtained. Hence, an
accurate traffic forecasting model is crucial in the
pavement design process.

Reliability. The reliability of a pavement design-
performance process is the probability that a pavement
will perform. satisfactorily' during' its design life.
Basically, it is a means of incorporating some degree of
certainty into the design process to ensure that the
various design alternatives will last the analysis
period. The reliability design factor accounts for
variations in both traffic prediction, performance
prediction, material, and construction.

Table 4 .2 presents recommended levels of reliability
for various pavement functional classifications.
Application of reliability concept requires the selection
of a standard deviation that is representative of local
conditions. Table 4.3 presents the recommended values of
standard deviation. Values of So deve10ped at the AASHO
Road Test did not include traffic error. However, the
performance prediction error developed at the Road Test
was 0.25 for rigid and 0.35 for flexible pavements. This
corresponds to a total standard deviation of 0.35 and

0.45 for rigid and flexible pavements, respectively (6).

61

Table 4.2: Recommended level of reliability for various

pavement functional classifications.

 

Reliability (%)

 

 

Functional classification Urban Rural
Interstate and Other Freeways 85-99.9 80-99.9
Principal Arterials 80-99 75-95
Collectors 80-95 75-95

Local 50-80 50-80

 

62

Table 4.3: Recommended values of standard deviation.

 

Standard Deviation

Design Condition

 

 

Flexible Rigid
Variation in pavement performance 0.35 0.25
prediction without traffic error
Total variation in pavement 0.45 0.35

performance prediction and

in traffic estimation

 

63

When. stage construction. is considered" the
reliability of each stage must be compounded to achieve
the overall reliability:

R =(R

) Ila
overall

stage

in which n is the number of stages being considered. For
example, if two stages are contemplated and the desired
level of overall reliability is 95 percent, the
reliability of each stage must be (0.95)1’2, or 97.5

percent (9).

Environmental Effects. The environment can affect
pavement performance in several ways. Temperature and
moisture changes can have an effect on the strength,
durability and load carrying capacity of the pavement and
roadbed materials. Another major environmental impact is
the direct effect of roadbed swelling, frost heave, etc.
on loss of ride quality and serviceability. Additional
effects such as aging, hardening and overall material
deterioration due to weathering, have been considered in
the AASHTO Design Guide only in terms of their inherent

influence on the pavement performance prediction models

(6).

Serviceability. The AASHTO Design Guide defines
serviceability of a pavement as its ability to serve the
traffic during its design life. The primary measure of

serviceability is the Present Serviceability Index (PSI) ,

64

which ranges from 0 (impassible road) to 5 (perfect
road). The basic design philosophy of this guide is the
serviceability-performance concept, which. provides a
means of designing a pavement based on a specific total
traffic volume and a minimum level of serviceability
desired at the end of the performance period (6).
Initial and terminal serviceability indexes must be
established to compute the changes in serviceability,
APSI, to be used in the design equation. The initial
serviceability is a function of pavement type and
construction quality. Typical values from the AASHO Road
Test are 4.2 for flexible pavements and 4.5 for rigid
pavements. The terminal serviceability' index: is the
lowest index that will be accepted.before rehabilitation
or reconstruction become necessary. An index of 2.5 or
higher is suggested for design of major highways and 2.0

for highways with lower traffic (9).

4.5 MATERIAL PROPERTIES FOR STRUCTURAL DESIGN
4.5.1. Effective Roadbed Soil Resilient Modulus

The basis for material characterization in AASHTO Design
Guide is its elastic or resilient modulus. For roadbed
materials, laboratory resilient modulus test (AASHTO 1274)
should be performed on representative samples in stress and
moisture conditions simulating those of the primary moisture
seasons. Alternatively, the seasonal resilient modulus values

may be determined by correlations with soil properties i.e.,

65

clay content, moisture, PI, etc. The purpose of identifying
seasonal moduli is to quantify the relative damage a pavement
is subjected.to during each season.of the year and treat it as
a part of the overall design. An effective roadbed soil
resilient modulus is then established which is equivalent to
the combined effect of all the seasonal modulus values. (The
development of the procedure for generating roadbed soil
resilient modulus is presented in Appendix HH of volume 2 of
the 1986 AASHTO Design Guide).

Two different procedures for determining the seasonal
variation.of the modulus are offered.aslguidelines. One method
is to obtain a laboratory relationship between resilient
modulus and moisture content. With an estimate of the in situ
moisture content of the soil beneath the pavement, the
resilient modulus for each.of the seasons may be estimated. An
alternate procedure is to backcalculate the resilient modulus
for different seasons using nondestructive deflection test
data conducted on in- service pavements. These may be used as
adjustment factors to correct the resilient modulus for a

reference condition (6).

4.5.2. Pavement Layer Materials Characterization

The 1986 AASHTO Design Guide relies more heavily on the
determination of material properties for the estimation of
appropriate layer coefficient values. Although there are many
types of material properties and laboratory test procedures

for assessing the strength of the pavement materials, the

66

AASHTO Guide recommends that for a relatively low stiffness
material, the AASHTO T274 standard test procedure be used to
determine its resilient modulus. For stiff materials the
AASHTO Guide recommends the use of the repeated load indirect
tensile test (ASTM D4123).

Because of the small displacements and brittle nature of
the highly stiff materials (e.g¢, portland cement concrete and
those materials stabilized with a high cement content) The
Guide recommends that the elastic modulus of such. high
stiffness materials be determined according to the procedure

described in ASTM C469 (6).

4.6 LAYER COEFFICIENTS

The AASHTO flexible pavement layer coefficient (a1) is a
measure of the relative ability'of a unit thickness of algiven
material to function as a structural component of the pavement
(2). A value of this coefficient is assigned to each layer in
the pavement structure in order to convert the actual layer
thicknesses into a structural number (SN). This layer
coefficient expresses the empirical relationship between SN
and thickness. The following general equation relates the
structural number (SN), layer coefficients (a.), thicknesses

UL), and drainage coefficients (an):

SN=Ea1D1m1

Although. the elastic or resilient modulus has been

67

adopted as the standard material quality measure, it is still

necessary to identify layer coefficients because of their

roles in.the structural number'design.approachn The discussion

of how these coefficients are estimated is presented below in

five categories, depending on the type and function of the

layer material (6).

1.

Asphalt Concrete Surface Course. Figure 4.2 provides a
chart that may be used to estimate the structural layer
coefficient of a dense-graded asphalt concrete surface
course based on its elastic (resilient) modulus (Ex; at
68° F. Caution is recommended for modulus values above
450,000 psi.

Granular Base Layer. Figure 4.3 provides a chart that
may be used to estimate the layer coefficient of a
granular base layer(aq). The following relationship may
also be used to estimate the layer coefficient provided

that the elastic/resilient modulus (EMS is known:

a, = 0.249 (10910 a”) - 0.977

Granular Subbase Layers. Figure 4.4 provides a chart
that may'be used.to estimate the layer coefficient of the
subbase layer (as). The following relationship may also
be used to estimate the layer coefficient provided that

the elastic/resilient modulus (Efl) is known:

a3 = 0.227 (logm E”) - 0.839

Structrual Layer
Coefficient al

05

Q4

Q3

02

DJ

00

68

 

 

 

 

 

 

 

 

 

 

 

 

 

101m” ZDKDO 3GNND IwQDG) guano

Elastic Modulus of Asphalt Concrete (psi)

Figure 4.2 Chart for estimating structural layer
coefficient of dense-graded asphalt
concrete based on the elastic
(resilient)modulus

69

 

 

 

 

 

 

0.20 a
018 2
40 ‘
0.16 -«
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‘° 70 j 80 - a
' 60
.92 50 " : Q 8 '-
0 ~— ~' .
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g a
t: 20 -l m
U) ... 15 'l
0.06 "“- ———————————— SO—fi ——————— — —————-I
4.0 .4
0.04 H I.
0.02 "

ll) Scale derived by averaging correlations obtained from Illinois.

(2) Scale derived by averaging correlations obtained from California. New Mexico and Wyoming.
(3) Scale derived by averaging correlations obtained from Texas.

(4) Scale derived on NCHRP project

Figure 4.3: Variation in granular base layer coefficient

(a,) with various base strength parameters.

0.20 -

0.14 -.

0.10 ....

0.06 -.

70

 

 

Figure 4.4

------------ 100 f--—---------90 -
70 -€ 80 -
“7' 40 70-
i=3
"" Of.
0
"' m _
% ..l U 60
8 _____________________________
E 20
a 50 -
U
E
m 10 —
40-
............................. 30 _
5 _ ‘i
25 -
I..— ..J— _

_____________ 2
is
3.—
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r
l- 0: —————————————
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5—

12-4

10—

 

 

(1) Scale derived from correlation from Illinois.
(2) Scale derived from correlations obtained from the Asphalt Institute, California,

New Mexico and Wyoming
(3) Scale derived from correlations obtained fromTexas
(4) Scale derived on NCHRP project (3)

14.1 .

i (4)

Modulus - 1000 psi

 

Variation in granular subbase layer coefficient
(a3) with various subbase strength parameters

71

4. Cement Treated Bases. Figure 4.5 provides a chart that
may be used to estimate the structural layer coefficient

of cement treated bases.

5. Bituminous Treated Bases. Figure 4.6 presents a chart
that may' be used to estimate the structural layer
coefficient of bituminous treated bases. The elastic
modulus or the Marshal Stability can be used as a input

to the chart.

4.7 PAVEMENT STRUCTURAL NUMBER

The treatment for the expected level of drainage for a
flexible pavement is through the use of modified layer
coefficients (e.gx, a higher effective layer coefficient would
be used for improved drainage conditions). The factor for
modifying the each layer coefficient is referred to the
drainage coefficient (an) which has been integrated into the
structural number (SN) equation along with layer coefficients

(a1) and layer thicknesses (In); thus:

SN=a1D1+a2D2m2+a3D3m3 ...... Eq4.1

Table 4.4 presents recommended In,L values as a function
of the quality of the drainage and the percent of time during
the year the pavement structure would normally be exposed to
moisture levels approaching saturation. As a bases for

comparison, the an, value for conditions at the AASHO Road

0.28

0.22

0.16

0.10

72

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=
O
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C
D

 

 

 

(1) Scale derived by averaging correlations from Illinois, Louisiana and Texas
(2) Scale derived on NCHRP project (3)

Figure 4.5 Variation in aszr cement—treated base with

base strength parameters

73

 

1800 — 40 4
0.30 --:------------------------------;. ------------------------------- ---
1600
3.0 -
2.5 d
l200 - A
f“ N
..‘3 V
2.0. -
0.20 Hf. ---------------------------- 4- ---------------------------- we
5 600 £ 15 a.
cg _ ' . _ E
8: 3. ""
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(U
a :- é’
(U
E 200 _. '5': 1.0 - 2
m S
2
0.10 .. --------------------------------------------------------------- ~--
0 ..

 

 

(1) Scale derived by averaging correlation obtained from Illinois.
(2) Scale derived on NCHRP project (3)

Figure 4.6 Variationina2 for bituminous-treated base

with base strength parameters

74

Table 4.4: Recommended m1 values for modifying structural
layer coefficients of untreated base and subbase

materials in flexible pavements.

 

Percent of Time Pavement structure is Exposed

to Moisture Levels Approaching Saturation

 

 

Quality of

Drainage Less than 1-51; 5-25% Greater than 25%
1%

Excellent 1.40 - 1.35 1.35 - 1.30 1.30 - 1.20 1.20

Good 1.35 - 1.25 1.25 - 1.15 1.15 - 1.00 1.00

Fair 1.25 - 1.15 1.15 - 1.05 1.00 - 0.80 0.80

Poor 1.15 - 1.05 1.05 - 0.80 0.80 - 0.60 0.60

Very Poor 1.05 - 0.95 0.95 - 0.75 0.75 - 0.40 0.40

 

 

75

Test is 1.0. Finally it is also important to note that these
values apply to the effects of drainage on untreated base and
subbase layers. Although improved drainage is certainly
beneficial to stabilized or treated materials, the effects on
performance of flexible pavements are not as profound as those

quantified in Table 4.4 (6)

4.8 COMPUTATION OF REQUIRED PAVEMENT THICKNESS

For both the asphalt concrete pavements (AC) and surface
treatments surface types, the design is based on identifying
a flexible pavement structural number (SN) to withstand the

projected level of axle load (6).

4.8.1. Determination of the Required Structural NUmber.
Figure 4.7 presents a nomograph for determining the
design structural number (SN) required for specific

conditions. The nomograph solves the following equation:-

log" (Wu) = ZR S0 + 9.36 * log1° (SN + 1) - 0.20 +

log1° [ aPSI/4.2-1.5 ]
------------------------ + 2.32 * log10 (MR) - 8.07

The required data to be substituted into this equation

76

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77

is:-
a. The estimated future traffic, W18, for the
performance period.

b. The reliabilityy R, ‘which. assumes that average
values are used for all inputs. For hand
calculation, 22 can be obtained from Table 3.2.

c. The overall standard deviation, So.

d. The effective resilient modulus of roadbed material,
M.

e. The design serviceability loss, APSI = p°-;x.

4.8.2. Selection of Trial Pavement Thickness Design.

Once the design structural number' of an. initial
pavement has been determined, the designer must identify a Set
of pavement layer thicknesses that will provide the required
structural number (2).

4.8.3. Layered Design Analysis.

Flexible pavement structures are layered system and
should be designed accordingly. Each unbound or aggregate
layer must be protected from excessive vertical stresses,
which could result in permanent deformation. This requires
that.a minimum layer thickness value be established. Table 4.5
(6) provides a list of suggested minimum thicknesses for
surface and base layers for various traffic conditions. The
minimum thickness values should be modified for local
conditions.

The AASHTO design nomograph presented in Figure 4.7 can

78

Table 4.5: Minimum Layer Thickness

 

Minimum Thinkness (inches)

 

 

Traffic Asphalt Concrete Aggregate
(ESAL) Surface Base
Less than 50,000 1.0(or surface 4
treatment)
50,000 - 150,000 2.0 4
150,000 - 500,000 2.5 4
500,000 - 2,000,000 3.0 6
2,000,000 - 7,000,000 3.5 6
Greater than 7,000,000 4.0 6

 

1 inch = 2.54 cm

79

be used to determine the design structural number required for
the protection of any unbound layer by substituting the
resilient modulus of that layer for the roadbed resilient
modulus in the nomograph. Hence, the nomograph can be used to
determine the thickness of the AC layer that is required to
protect the base course. It can also be used to determine the
required thicknesses of the AC and base layers to protect the
subbase layer. Such use is termed as layer design analysis.
This procedure, however, should not be applied to
determine the required layer thickness above materials having
a modulus higher than 40,000 psi. Layer thickness above such
materials should be established on the bases of cost-

effectiveness and minimum practical thickness considerations .

4.9 LIMITATIONS OF THE AASHTO FLEXIBLE PAVEMENT DESIGN

PROCEDURE

The AASHTO design procedure is being used by many highway
agencies of the world for the design of flexible and rigid
pavements. Roads designed by using the AASHTO Guide have
exhibited premature failure in many parts of the world,
especially in Pakistan. In the light of the advancements in
the pavement design procedures, the researchers have carried
out analytical studies of the AASHTO Design Procedure and
pointed out certain limitations/ inadequacies in the Procedure,

which are summarized below:-

1. Materials. The AASHO Road Test used a specific set of

80

pavement materials and one roadbed soil. The
extrapolation of the performance of these materials to
general applications is a questionable proposition
because the materials and soils available in.Pakistan.are
not identical to those used at the road test site and
therefore should perform differently. The pavement design
agencies in Pakistan do not seem to recognize this as is
evidenced by the widespread use of a1 = 0.44, a2 = 0.14,
and a3 = 0.11. These structural layer coefficients
values represent the relative strength. of the
construction.materials used.at the.AASHO road test and do
not represent the strength properties of the materials
available locally (10).

Traffic. The AASHO Road Test sections were subjected to
1.1 million applications of axle loads ranging from 2000
lbs to 30,000 lbs on single axles and 24,000 lbs to
48,000 lbs on tandem axles. No tridem axle were included

in the Road Test experiment. Each test section was

'exposed to axle loads of only one particular magnitude

and configuration, as opposed to mixed traffic. Tire
pressures were representative of normal practice at the
time i.e., 80 psi.

In Pakistan, like in many other developing countries
of the world, the economics of truck transportation have
contributed.to an increase in.the average gross weight of
trucks such that the majority of the trucks are operating

well above the legal axle load limits. A recent axle load

81

survey carried out by the Military College of Engineering
(4) indicates gross overloading as may be seen from the
truck factor ranges presented in Table 4.6. Table 4.7
presents a comparison of traffic loading conditions of
the AASHO Road Test and Pakistan. As axle loads have
increased, the use of higher tire pressure has become

more popular in the trucking industry.

Climate. AC pavements constructed in hot climatic zones
like Pakistan undergo greater permanent deformation due
to softening of the bitumen. The AASHTO empirical model
was developed in a temperate climate where the mean
monthly air temperature varies between -4°C during
january to 24°C during july. Thus, the AASHTO empirical
model is not applicable to the hot climatic conditions of
Pakistan.

Moreover, the use of the AASHTO empirical model for
climatic conditions in Pakistan has resulted in
inaccurate predictions of environmental deterioration
over time i.e., aging or weathering of the AC. These
processes result in the loss of volatile material in the
bitumen and are primarily a function of temperature.
Therefore a greater loss of serviceability (ride quality)
in AC pavements in Pakistan would be expected due to
rapid aging of the AC than accounted for by the AASHTO

empirical model.

82

Table 4.6: Truck Factors at Texila on N-S (Loaded Vehicles)

 

 

 

E

Vehicle Axle Configuration Truck Truck Factors
Type Factor Range in USA

2 Axle Both single axles 4.757 0.15 - 0.21

3 Axle One single & one tandem 11.850 0.29 - 1.59
4 Axle All single axles 6.996 0.43 - 1.32
5 Axle One single & two tandem 4.380 0.43 - 1.32
6 Axle One single, one tandem & 14.730 0.71 — 1.39

one tridem 15.820 0.71 — 1.39
.__________J_

 

 

 

 

 

 

83

 

 

Table 4.7: Traffic Loading Comparison AASHO Road Test and

PAKISTAN
Maximum Maximum Maximum Maximum Maximum
Tandem Tandem Tridem Truck Tire
Axle Axle Axle Load Pressure
Load Load Load (lbs) (lbs)
(lbs) (lbs) (lbs)

AASHO 30,000 48,000 None 108,000 70

PAKISTAN' 47,000 95,000 110,000 174,000 145

 

 

 

 

 

 

 

 

 

84

4. Quality control. The AASHTO Road Test sections were
short in length (160 ft) and an extraordinary effort was
put forth to ensure uniformity of all pavement
components. Thus construction quality control was
extremely high. Typical highway projects are normally
several miles long, contain much greater construction and
material variability. In Pakistan, the variability is
even more due to poor quality control and construction
practices (10). Since the AASHTO model is based on the
performance of the AASHTO test sections with very little
variability, therefore AC pavements in Pakistan designed
using this model would tend to show not only overall
rapid deterioration but also more variability in
performance along the project in the form of localized

failures.

4.10 Mechanistic Evaluation/Calibration

Baladi and Mckelvey (11) conducted mechanistic evaluation
and calibration of the AASHTO flexible design equations by
using artificial pavement sections with various layer
properties, roadbed soil modulus, and traffic volumes.
Throughout the analysis it was assumed that the mechanistic
responses (stresses, strains, and deflections) of the pavement
sections due to an applied 18000-lb single axle load are
indicative of the level of damage delivered to these sections.

The work plan consisted of five phases as follows:-

PHASE-1.

PHASE-2.

PHASE-3.

PHASE-4.

PHASE-5.

85

Establish a full factorial experiment design matrix
that consists of 243 cells (each cell represents a
pavement section). Design each pavement section by
using the 1986 AASHTO design procedure and
establish the layer thicknesses. The full factorial
experiment design matrix is shown in Figure 4.8.
Conduct mechanistic analysis of each pavement
section of step 1 by using MICHPAVE computer
program and determine its mechanistic responses due
to an 18-kip single axle load.

Compare the resulting mechanistic responses to
determine whether or not the outputs of the AASHTO
design procedure are reasonable.

Select pavement sections from Figure 4.8. Redesign
(by using the AASHTO design procedure) the layer
thicknesses based on four additional values of the
drainage coefficients of the base layer and two
values of the drainage coefficients of the subbase
layer. Conduct mechanistic analysis of each
redesigned section and then mechanistically
evaluate the concept of drainage coefficients.
Select pavement sections from Figure 4.8. Redesign
(by using the AASHTO design procedure) the layer
thicknesses based on two additional values of loss
of serviceability due to environmental factors.
Conduct mechanistic analysis of each redesigned

section and then mechanistically evaluate the

86

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87

concept of loss of serviceability.
Each of the five phases were accomplished in several
steps. Details for each phase and the corresponding steps are
presented else where (11). Important conclusions/concepts

brought out by the study are presented below.

4.10.1 Observations of the AASHTO Outputs

For a given value of the resilient modulus of the
roadbed soil, a constant traffic volume, a constant design
reliability level, and a constant overall standard deviation,
the AASHTO design procedure produces:-

1. Pavement sections with a constant SN which presumably
provides an equal level of protection against traffic
loading to all pavement layers regardless of the type and
quality of the AC, base, and subbase layer.

2. An AC layer thickness that is independent of the
properties (modulus or layer coefficient) of the subbase
material and roadbed soil. It depends on the layer
coefficients of the AC and base materials.

3. A. base layer thickness that is independent of the
resilient modulus of the AC layer and roadbed soil. It
depends on the layer coefficient of the base and subbase
materials.

4. A.subbase thickness that is independent of the resilient
modulus of the AC and base layers. It depends on the
layer coefficient of the subbase material and the modulus

of the roadbed soil.

88

4.10.2 Mechanistic Evaluation of the AASHTO Design Equation
The 243 pavement sections were analyzed by using the
linear option of the MICHPAVE computer program. The
mechanistic responses of' the 243 pavement sections are

provided in the matrices given elsewhere (11).

Table 4.8 summarizes the AASHTO and mechanistic response

outputs of the seven pavement sections from the above
study. Based on the data presented in the table and the range
of the material properties used in this study, the following
conclusions were drawn:-

1. Based on the pavement surface peak deflection data listed
in Table 4.8 and shown in Figure 4.9 and on the
assumption that the peak surface deflection can be used
as a measure of the level of damage delivered to a
pavement section (higher deflection causes higher
compression and higher rut and/or fatigue cracking

potential), one can conclude that:-

For a constant traffic level and one type of roadbed
soil, the AASHTO design procedure produces pavement
sections (layer thicknesses) such that the peak surface
deflection is constant. Hence, the amount of overall
damage delivered.to the pavement section (or the overall
protection level) is constant and independent of the

layer properties.

2. Based on the amount of vertical compression (the

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Figure 4.9 Peak pavement surface deflections of

the seven indicated pavement sections

92
difference between the peak deflections at the top of any
two consecutive layers) experienced by each pavement
layer (see Figures 4.10, 4.11, 4.12, and 4.13, and the
resulting vertical strains at the top and bottom of each
pavement layer (see Figures 4.14, and 4.15), the

following conclusion was drawn:-

For a constant traffic level and one type of roadbed
soil, the AASHTO design procedure produces pavement
sections (layer thicknesses) such that the amount of
compression and the resulting compressive strain
experienced by any one layer vary from one section to
another. Hence, the amount of damage delivered to each
layer of the pavement sections (or the level of
protection) varies. This implies that while the AASHTO
design procedure insures that the overall damage of the
pavement sections is the same, the relative damage

delivered to each layer is not.

Based on the magnitude of the tensile stress induced at
the bottom of the AC layer (of seven pavement sections)
due to an 18-kips ESAL and the ratio of that tensile
stress to the value of the AC modulus (see Table 4.8 and
Figure 4.16, and 4.17), the following conclusion was

drawn:-

For a constant traffic level and one type of roadbed

93

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

   

   

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'87'114 141'
Pavement section number

The amount of compression in the AC layer
of the seven indicated pavement sections

Figure 4.10

94

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Figure 4.11 The amount of compression in the base layer
of the seven indicated pavement sections

60 14122 ' 87 '114'141' '141‘150'159

 

Compression in the subbase layer (mill)

Figure 4.12

 

60 141222 87 114141 141 150159
Pavement section number

The amount of compression in the subbase layer
of the seven indicated pavement sections

161

 

Figure 4.

96

 

 

 

Compression in the roadbed soil (mills)
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Pavement section number

 

 

 

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Figure 4.14 The vertical strains induced at the top of
each pavement layer for the indicated
pavement sections

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Figure 4.15

each pavement layer for the indicated

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99

 

 

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of the seven indicated pavement sections

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igure 4.17 The ratio of the tensile stress at the bottom

of the AC layer to its resilient modulus for

the seven indicated pavement sections

101
soil, the AASHTO design procedure produces pavement
sections (layer thicknesses) such that the tensile stress
induced at the bottom of the AC layer vary from one
section to another. Hence, the amount of damage delivered
to the AC layer of the pavement sections (or the level of
protection) varies. This implies that while the AASHTO
design procedure insures that the overall damage of the
pavement sections is the same, the relative damage

delivered to each layer is not.

It should be noted that the three conclusions stated
above are strictly based on the outputs (layer thicknesses) of
the AASHTO flexible pavement design procedure and the outputs
of the mechanistic analysis of the AASHTO designed pavement

sections.

4.10.3 Conclusions
Relative to the AASHTO Design Procedure and the above
general observations and in the range of material properties

used in the SHRP study, the following conclusions were drawn:-

1. Results of the mechanistic evaluation support the first

observation (see page 90) of the AASHTO Design Procedure.

2. Results of the mechanistic evaluation do not support
observations "2, 3 and 4" (see page 90,) of the AASHTO

Design Procedure.

102
4.10.4 Important Concepts Relative to the calibration of
the AASHTO Flexible Design Equations:-

Several important concepts related to the calibration of
the AASHTO flexible design equations can be inferred from the
mechanistic analysis of those equations. These concepts can.be
divided (according to the type of the AASHTO equation) into
two categories: the concepts of the structural number and the
concept of the resilient modulus of the roadbed soil in the
AASHTO main design equation (11). These two categories are

presented below:—

1. The Concept of the AASHTO Structural Number
The AASHTO equation (note that drainage coefficient is

not included yet) can be written as follows:

SN = a1D1 + a,,D2 + a3D3 which can also be written

38:

SN = SN1 + SN2 + SN,

That is the structural number of a pavement section
is the linear sum of the structural numbers of its
layers. The following conclusions were made relative to

this AASHTO concept.

STRUCTURAL NUMBER AASHTO CONCEPT - 1
The total structural number of any flexible pavement

section is the sum of the structural numbers of its

103

layers. The findings of the mechanistic analysis support

this AASHTO concept .

STRUCTURAL NUMBER - AASHTO CONCEPT - 2
The structural number of any flexible pavement layer is
the product of its thicknesses and its layer coefficient.
For any layer, its coefficient can be obtained from the
appropriate equation or chart based on the modulus values
of that layer. The results of the mechanistic analysis do

not support this AASHTO concept.

The Concept of the AASHTO Main Design Equation

The number of lB-kips ESAL (W18) is a function of the
design reliability (2,.) , the overall standard deviation
(So) of the materials and traffic data, the structural
number (SN) of the pavement section, the resilient
modulus (M) of the roadbed soil, and the serviceability
loss (APSI) expected during the performance period. In
practice, however, the number of 18 kips ESAL is used as
an input to the equation and the required structural

number is obtained.

Log (Wu) -- Z, (80) + 9.36[Log(SN + 1)] - 0.20 +

LOQ[(APSI)/(4.2 - 1.5)
-------------------------- + 2.32[Log(M,)] - 8.07
[0.4 + 1094/(SN + l)"”]

3 .

4.11

104

THE CONCEPT OF THE AASHTO MAIN DESIGN EQUATION

The structural number of a pavement section is a function
of only one material property, the resilient modulus of
the roadbed soil. Pavement sections‘with.different types
of roadbed soil will have different structural numbers
such that each section will receive the same amount of
damage. The results of the mechanistic analysis do not

support this AASHTO concept.

Results of the mechanistic evaluation do not support the

role of the roadbed soil resilient modulus in the AASHTO
main design/ performance equation (the equation does not
properly account for the effects of the resilient modulus
of the roadbed soil on the structural capacity of the

pavement).

AASHTO Layer Coefficients

Considerable disagreement is apparent about both the

definition and the recommended method of measurement of layer

coefficients (15). For example, the following statements are

from the 1986 AASHTO Design Guide (6):

"The structural number is an abstract number....
converted to actual thickness of surfacing, base and
subbase, by means of appropriate layer coefficients
representing the relative strength of the construction

materials"

105
2. "In effect, the layer coefficients are based on the
elastic moduli Ma and have been determined based on
stress and strain calculations in a multilayered pavement

system" (section 1.2 AASHTO Design Guide 1986).

3. " ..... it is not essential that elastic moduli of these
materials are characterized. In general, layer
coefficients derived from test roads or satellite
sections are preferred" (section 2.3.3 AASHTO Design
Guide 1986).

At the international conference on the Structural Design
of Asphalt Pavements, Shook and Finn (20) stated the
following:

"It is believed that the coefficients a1 , a2, a3 are
functions of the strengths of the various layers involved. At
the present time (1962), however, no entirely satisfactory
techniques are available for defining or measuring these
strength factors." Persual.of existing and.current literature
reveals (19) that two predominant methods have been adopted

for estimating the layer coefficients of bituminous

materials:-
a. A power law relating the layer coefficients to the
resilient modulus (MR) (e.g., see Figure 2.5 in the
AASHTO Guide).
b. Based.on.0demark's equivalent stiffness hypothesis,

an analogous relationship is used, wherein the one—

third power of the ratio of the material modulus to

106
that of a reference material (whose layer
coefficient is presumed to be known) gives the
ratio of the unknown layer coefficient to that of

the reference material.
The Assumption of a relationship between strength and
layer coefficients is an extrapolation, since no measure of
structural strength or adequacy was included in the data used

to calibrate the AASHO model (19).

(HIAPTIHIS

SHIHNYIUEHMURSSEIEHITVIFYAUIALJEHS

5.1 SENSITIVITY OF THE AASHTO EQUATION TO THE DESIGN
VARIABLES

A review of the AASHTO design procedure (DNPS 86 Computer

Program) results listed in Table 5.1 and presented in Figure

5.1 through 5.5, illustrate the effect of various variables as

follows:-

1. For the traffic input values considered a three fold
increase in the initial traffic (25 million to 75
million ESALs) causes an 18 percent increase in the AC
thickness, 10.66 percent increase in the base thickness,
10 percent increase in the subbase thickness and 13.76
percent increase in the overall thickness. The effect
of traffic on thickness is more pronounced for lower

values of traffic.

2. A three fold increase in the AC modulus (150 to 450 ksi)
yields in about 43 percent decrease in the AC thickness.
The overall pavement thickness decreases by about 23
percent. The thicknesses of the base and sub-base layers

are not affected by the changes in the AC modulus.

3. For two fold increase in the base modulus (20 ksi to 40

ksi) the AC thickness decreases by about 21 percent and

107

 

108

Table 5.1: Effect on thickness of variation in traffic and

layer material properties.

Effect of ESALs

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ESALS (millions) 25 50 75
Layer Type Thickness (inches)

AC 9.76 10.86 11.54
Base 7.03 7.50 7.78
Subbase 5.88 6.25 6.47
Total Thickness 22.67 24.61 25.79
Effect of AC Modulus

AC Modulus (ksi) 150 300 450
Layer Type Thickness (inches)

AC 16.07 10.86 9.13
Base 7.50 7.50 7.50
subbase 6.25 6.25 6.25
Total Thickness 29.82 24.61 22.88
Effect of Base Modulus

Base Modulus (ksi) 20 30 40
Layer Type Thickness (inches)

AC 12.47 10.86 9.80.
Base 5.05 7.50 8.48
Subbase 6.25 6.25 6.25
Total Thickness 23.77 24.61 24.53
Effect of Subbase Modulus

Subbase Modulus (ksi) 10 15 20
Layer Type Thickness (inches)

AC 10.86 10.86 10.86
Base 12.41 7.50 4.26
Subbase 0.00 6.25 8.15
Total Thickness 23.27 24.61 23.27
Effect of Roadbed Modulus

Roadbed Modulus (ksi) 7.5 10.00 20.00
Layer Type Thickness (inches)

AC 10.86 10.86 10.86
Base 7.50 7.50 7.50
Subbase 11.00 6.25 0.00

 

Total Thickness 29.36 24.61 18.36

 

30

25

20

15

10,

109

Thickness (inches)

 

 

 

 

 

 

 

 

 

%K )6
x7
5— -«
0 l
25 so 75

ESAL’S (millions)

+AC +Base X‘Subbase UTotaL

Figure 5.1: Effect of variation in traffic on pavement layer thicknesses

110

Thickness (inches)

35

 

 

 

ate
xi.
>I<

 

 

 

 

5 r—
0 J
150 300 450

AC modulus (ksi)

+AC +Base X'Subbase GTotaL

Figure 5.2: Effect of variation in AC modulus on pavement layer thicknesses.

111

Thickness (inches)

30

 

Sn/

 

 

0 1 1 1 1 4 1 1 1
20 22 24 26 28 30 32 34 36 38 40

 

Base modulus (ksi)
*‘AC +Base *Subbase DTotaL

Figure 5.3: Effect of variation in base modulus on pavement layer thicknesses.

 

112

Thickness (inches)

14

 

 

10—

 

 

0 l
10 15 20

 

Subbase modulus(ksi)

*AC +Base *Subbase

Figure 5.4: Effect of variation in subbase modulus on pavement layer thicknesses.

113

Thickness (inches)

 

3S

 

 

 

 

l I
7.5 10 12.5 15 17.5 20

Roadbed modulus (ksi)

 

*AC +Base *Subbasc GTotaL

Figure 5.5: Effect of variation in roadbed modulus on pavement layer thicknesses.

 

114
the base thickness increases by about 68 percent. The
overall pavement thickness is increased by only 3
percent. The Subbase thickness is not affected by the

change in the base modulus.

An increase in the subbase modulus causes the base
thickness to decrease and. the subbase thickness to
increase. The AC layer thickness is not effected by the

changes in the sub-base modulus.

Softer road bed soils require more thickness of the
subbase and correspondingly greater over all thickness.
The AC and the base thicknesses are not affected by the

changes in the road-bed soil modulus.

MECHANISTIC EVALUATION OF AASHTO FLEXIBLE PAVEMENT DESIGN
PROCEflURE - VERIFICATION OF SHRP STUDY (11) FOR HIGHER

LEVELS OF TRAFFIC

5.2.1. Outputs from.AASHTO Design Procedure

Figure 5.6 shows the structural number for each of the

243 pavement sections of Figure 3.1. These structural numbers

are obtained when a subbase material softer than the roadbed

soil is omitted from the analysis. Figure 5.7 also presents

the structural numbers of pavement sections of Figure 3.1.

These structural numbers are obtained when a subbase material

softer than the roadbed soil is included in the analysis.

115

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117
Figures 5.8 through 5.11 depicts the thicknesses of the AC,
base and subbase layers and the total thickness for all 243
pavement sections, respectively. These thicknesses corresponds

to the structural numbers listed in Figure 5.7.

5.2.2 Mechanistic Analysis

After obtaining the layer thicknesses from the AASHTO
design procedure using the DNP886 computer program for all 243
pavement sections of Figure 3.1, a mechanistic analysis was
conducted for each section by using ELSYMS computer program.
It should. be noted that the mechanistic responses were
obtained only for critical locations in the pavement
structure. The values of Poisson's ratio, Axle load, and Tire

pressure used in the study are listed below.

a) Poisson's Ratio Values

Layer Type Pgisson's Ratio
AC 0.40
Base 0.35
Subbase 0.35
Roadbed 0.45

b) An axle Load of 18000-lbs and the single tire
option in ELSYMS computer program were used.
Hence the load on one tire was considered to
be 9000-lbs.

c) A typical tire pressure of 80 psi was used.

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Please note that this is the tire pressure
used at the AASHO Road Test sections.
Results of the mechanistic analysis
(mechanistic Responses) are provided in

Figures 5.12 through 5.21.

5.2.3. Verification of SHRP Study Results

To verify the results of the SHRP study at higher
levels of traffic, a traffic level of 75,000,000 ESAL's
and roadbed ‘with resilient modulus of 10 ksi is
considered. This gives a matrix of 27 cells with
variables as shown in Figure 5.22. The cells have been
numbered as they appear in the main matrix of Figure 3 .1.
Table 5.2 shows the outputs (layer thicknesses) of the
AASHTO design procedure for the 27 cells of Figure 5.22.
Mechanistic responses of these 27 pavement sections are
presented in Table 5.3.

According to the Amsnwo Design Procedure, the 27
pavement sections are suppose to have the same
serviceability loss over the 10-year performance period,
they are supported on the same roadbed soil, and they
carry the same amount of traffic of 75,000,000 ESAL’s
over the same performance period. Hence, the amount of
damage delivered to each pavement section during the
performance period is the same. This implies that the 27
pavement sections receive the same level of protection

against damage.

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ON 0H 0.3 om 0H CH ON 03” OH ON 03” OH ON 03” OH on 0H CH cm 0.3 OH ON 00 OH ON 03 0.3

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Examination of the mechanistic responses of the 27

pavement sections of Figure 5.22 indicates that:-

The peak surface deflections listed in Table 5.4 and
shown in Figure 5.23 are almost constant for all
sections, (the peak pavement surface deflection varies in
the range of 1 mill which is negligible). Assuming that
the peak surface deflection can be used as a measure of
the level of damage delivered to a pavement section
(higher deflection causes higher compression and higher
rut/or fatigue cracking potential), the following

conclusion was made.

For a constant traffic level and one type of roadbed
soil, the AASHTO design procedure produces pavement
sections (layer thicknesses) such that the peak pavement
surface deflection is constant. Hence the amount of
overall damage delivered to the pavement section (or the
overall protection level) is constant and.independent of

the material properties.

Based on the amount of vertical compressive stress at the
tOp of the pavement layers and vertical strains at the
top of the pavement layers as given in Table 5.5 and
shown in Figure 5.24 and 5.25 respectively, the following
conclusion from the SHRP study is also verified to the

range of conditions found in Pakistan:

139

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 5.4: The pavement surface deflections for 27 pavement
sections of Figure 5.22.
Cell Deflections at top of layer (Mills) “
Number
AC Base Roadbed I
(Peak pavement deflection)
6 13.50 9.88 8.07
15 13.70 10.10 8.28
24 13.70 NA/13.70 8.80
33 13.90 10.50 8.65
42 14.20 10.80 8.48 J
51 14.20 10.80 8.74
60 14.00 10.90 9.09
69 14.40 11.10 8.64
78 14.50 11.20 8.84
87 12.80 11.40 9.07 I
96 13.10 11.60 9.35
105 13.10 NA/11.70 10.00 |
114 13.30 12.00 9.70
123 13.70 12.40 9.50
132 13.80 12.50 9.83
141 13.50 12.30 9.97
150 14.00 12.80 9.63
159 14.10 12.90 9.88 J
168 12.60 12.80 9.38 n
177 12.90 12.10 9.67 4|
186 12.90 NA/12.10 10.40
195 13.20 12.40 10.00
204 13.60 12.80 9.84
213 13.70 12.90 10.20 |
222 13.40 12.70 10.30 II
231 13.90 13.20 9.95 “
240 14.10 13.40 10.20 H

140

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141

Table 5.5: The vertical compressive stress and vertical
strains at the top of layer for 27 sections of

Figure 5.22.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Cell Vert compressive Vert strains (Microstrains)
Number Stress (psi)
Base Roadbed AC Base Roadbed

6 3.64 1.41 89.00 125 107

15 3.40 1.49 86.60 128 129

24 NA/3.39 1.73 86.30 128 133

33 5.67 1.67 80.60 144 112 H
42 5.33 1.58 76.80 147 140 H
51 5.19 1.69 75.70 149 132 H
60 9.15 2.01 76.60 143 109

69 7.40 1.65 71.70 159 148

78 7.16 1.74 69.60 161 138

87 5.09 1.80 12.20 149 134 H
96 4.71 1.91 15.30 152 162 u
105 NA/4.70 2.24 15.50 152 167

114 7.89 2.12 55.20 169 140 H
123 7.43 1.99 29.60 173 174 H
132 7.21 2.14 31.00 175 165 H
141 10.90 2.28 32.60 181 140 fl
150 10.40 2.07 38.30 182 183

159 10.00 2.18 40.60 188 171 H
168 5.33 1.91 42.80 145 141 H
177 4.99 2.03 45.70 148 170 H
186 4.99 2.39 46.00 148 174 H
195 8.37 2.26 57.50 164 147 I
204 7.88 2.12 61.70 168 184

213 7.65 2.29 63.00 170 174

222 11.60 2.43 66.10 175 148

231 11.00 2.20 71.60 180 194

240 10.60 2.32 73.90 182 180

 

 

 

 

 

 

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Figure 5.25: The vertical strains at top of pavement layers for Indicated pavement sections.

144
The induced stresses and strains experienced by any one
pavement layer vary from one pavement section to another.
This implies that the AASHTO design method produces
inconsistent results relative to these mechanistic
responses. Hence the results of mechanistic analysis do
not support the AASHTO concept that the Structural Number
(SN) of any one flexible pavement layer is the product of

its thickness and its layer coefficient.

Based on the magnitude of the tensile stress induced at
the bottom of the AC layer of the 27 pavement sections of
Figure 5.22 due to an 18-kip ESAL and the ratio of that
tensile stress to the value of the AC modulus as given in
Table 5.6 and shown in Figures 5.26 and 5.27, the
following finding from the SHRP study is verified

relative to the conditions in Pakistan.

For a constant traffic level and one type of roadbed
soil, the AASHTO design procedure produces pavement
sections (layer thicknesses) such that the tensile stress
induced at the bottom of the AC layer vary from one
section to another. This implies that the AASHTO design
procedure produces inconsistent pavement sections
relative to fatigue damage. Once again, the results of
the mechanistic analysis do not support the AASHTO
concept that the structural number of any flexible

pavement layer is the product of its thickness and its

145
Table 5.6: The tensile stress at the bottom of the AC layer
and the ratio of the tensile stress to the AC

modulus for 27 pavement sections of Figure 5.22.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Cell Tensile stress at Ratio of the tensile 1
Number bottom of the AC layer stress to AC modulus ‘
(p81) !
6 85.40 0.569 !
15 88.00 0.587 fl
24 88.10 0.587
33 94.60 0.631 j
42 97.80 0.652
51 99.50 0.663 +|
60 86.20 0.57
69 102 0.680
78 104 0.693
87 106 0.353
96 108 0.360
105 109 0.363
114 118 0.393
123 121 0.403
132 123 0.410
141 123 0.410
150 127 0.423
159 129 0.430
168 104 0.231
177 107 0.238
186 107 0.238
195 117 0.260
204 120 0.267
213 121 0.269
222 122 0.271
231 126 0.280
240 128 0.284

 

146

 

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148

layer coefficient.

Sections 156, 159 and 162 (see Figure 3.1) were designed
using AASHTO design procedure. The material properties of
the AC, base and subbase layers for all three sections
are the same. All sections were designed. to carry
75, 000, 000 18-kip ESAL’s. The only difference between the
three sections is the resilient modulus of the roadbed
soil. It varies from 7.5 ksi to 10 ksi and 20 ksi for
sections 156, 159 and 162 respectively. The outputs
(layer thicknesses) obtained from the AASHTO design
procedure are listed. in 'Table 5.7. The mechanistic
responses are summarized.in‘Table 5.8. Examination.of the
mechanistic responses for sections 156, 159 and 162
indicate that:

The peak.pavement surface deflection varies from 16.0
mills for pavement section 156 to 11.8 mills for pavement
section 162. Figure 5.28 shows the peak deflection at the
top of each pavement layer. It can be seen that the peak
pavement deflection at top of each layer varies from one
section to another which.indicates that the amount of the
overall damage received by one pavement section is

different than that received by the other section.

It is to be noted that for the same traffic level
and pavement layer properties, the AASHTO produced

structural numbers for various types of roadbed soils do

149

 

 

 

 

 

 

 

 

 

 

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152
not provide the same level of protection to that soil.
Since for these three pavement sections, the only factor
affecting the calculation of the required structural
number is the resilient modulus of the roadbed soil, then
the following finding of the SHRP study is verified to

the conditions in Pakistan:-

The AASHTO main design equation for flexible pavements
does not properly account for the effects of the
resilient modulus of the roadbed soil on the structural

capacity of the pavement.

5.2.4. Mechanistic Evaluation of the AASHTO Drainage
Coefficients

To verify the results of the SHRP study relative to
drainage coefficients at higher levels of traffic, mechanistic
evaluation of the AASHTO drainage coefficients was conducted
by using the data of pavement section 240 from Figure 3.1.
Five values of the drainage coefficients were used (0.5, 0.7,
1.0, 1.3, and 1.5). For each design, the same value of the
drainage coefficient was used for both base and subbase
materials. Two evaluation methods were used: The layer
thickness modification method, and the layer coefficient
modification method. In the layer thickness modification
'method, the layer coefficients of the base and subbase
materials are not modified but the thickness of the

appropriate layer is either reduced or increased depending on

153
the value of the drainage coefficient. In the layer
coefficient modification method, the values of the layer
coefficient of the base and subbase are modified by
multiplying the actual layer coefficient by the drainage
coefficient. The modified layer coefficient values are then
used to estimate the modified layer moduli (using the
appropriate AASHTO layer coefficient equation) which.was then
used as an input to the AASHTO design method. For further
details on these two methods the reader is referred to
reference (11). The results of both methods are presented in

the subsequent subsections.

5.2.4.1 Layer Thickness Modification Method

Pavement section number 240 was designed using the 1986
AASHTO design. procedure (DNPS 86 Computer jprogram). The
pavement section was designed once for each of the following
values of the drainage coefficients (0.5, 0.7, 1.0, 1.3, and
1.5). The outputs (layer thicknesses, and structural numbers)
are listed in Table 5.9. Mechanistic analysis of the AASHTO
designed sections was then conducted by using the ELSYMS
computer'progrann The mechanistic responses are also listed in
Table 5.9 and shown in Figures 5.29 through 5.32 as a function
of the drainage coefficient. It should be noted that the five
pavement sections are supported on the same roadbed soil (MR
= 10 ksi), were designed to carry the same traffic volume

(75, 000,000, 18-kip ESALs) and to have the same serviceability

154
Table 5.9: Layer thicknesses, moduli, and mechanistic

responses for five values of drainage coefficients

for section 159 (thickness modification method).

 

 

 

 

 

 

 

 

 

 

Drainage coefficient
Results of Analysis (pavement section 159 of Figure 5.1)
0.50 0.70 1.00 1.30 1.50
Layer Thicknesses(inches)
AC 8.77 8.77 8.77 8.77 8.77
Base 12.08 8.63 6.04 4.65 4.03
Subbase 16.88 12.06 8.44 6.49 5.63
Structural Number 6.07 6.07 6.07 6.07 6.07
Layer Modu1i(ksi)
AC 450 450 450 450 450
Base 18.41 25.21 40.00 64.75 88.67
Subbase 10.10 13.42 20.00 31.46 41.79
Roadbed 10.00 10.00 10.00 10.00 10.00
Deflection at top of
layer (mills)
AC 15.40 14.70 14.10 13.50 13.30
Base 14.70 14.00 13.40 12.90 12.60
Subbase 11.40 11.70 12.00 12.00 11.90
Roadbed 8.03 9.17 10.20 10.70 10.90
Vertical stress at top of
layer (psi)
Base 7.79 8.91 10.60 12.50 13.80
Subbase 2.81 3.63 4.61 5.49 5.99
Roadbed 1.36 1.81 2.32 2.63 2.75
Tensile Stress at the 108 100 89.10 76.60 68.20
bottom of AC (psi)
Vertical strain at top of
layer (microstrain)
AC 92.70 84.20 73.90 63.40 57.10
Base 209 198 182 164 152
Subbase 207 209 198 176 162
Roadbed 143 171 180 177 172

 

 

 

 

 

 

 

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159

loss (1.9) during a performance period of 10 years.

Examination of the mechanistic responses indicate that:

1. The peak deflection at the top of each pavement layer is
a function of the drainage quality as shown in Figure
5.29. For example, the peak pavement deflection
(deflection at the top of the AC) increases as the

quality of the drainage material deteriorates.

2. The amount of compression experienced by each pavement
layer is a function of the drainage quality (Figure
5.30) . Hence the damage delivered to each layer is

affected by the quality of the drainage.

3. The vertical strains (Figure 5.31) at the top of the base
and subbase layers increase as the quality of drainage
deteriorate. This shows that a higher level of damage is

delivered to the layers with poor drainage quality.

4. The tensile stress induced at the bottom of the AC layer
(Figure 5.32) due to an 18-kip ESAL increases from 68.2
psi to 108 psi, (an increase of about 60%) as the
drainage coefficient decreases from 1.5 to 0.5. This
shows that the pavement sections constructed with.poorly
drainable material will have shorter fatigue life as
compared to the sections constructed.with good drainable

material. The SHRP study (11) showed.an.increase of about

160
70% in the radial tensile stress as the drainage

coefficient decreased from 1.4 to 0.6.

5.2.4.2 Layer coefficient Modification Method

In this method, the layer coefficients of the base and
subbase were modified by multiplying them by the value of the
drainage coefficients (a1 *mi) . The modified layer coefficients
were then used to estimate the modified layer moduli. Pavement
section 204 was then redesigned using the AASHTO design
procedure (DNPSBG computer program) and the five modified
values of the layer coefficient and moduli. The outputs (layer
thicknesses, and structural numbers) of DNPS 86 computer
program are listed in Table 5.10. The mechanistic analysis of
the AASHTO designed sections was then conducted by using
ELSYMS computer program. The mechanistic responses are also
listed.in Table 5.10 and shown in Figures 5.33 through 5.36 as
a function of the drainage coefficient. As before, the five
pavement sections are supported on the same roadbed (MR = 10
ksi), and were designed to carry the same traffic volume
(75,000,000, 18-kip ESALs) and.to have the same serviceability'
loss (1.9) during performance period of 10 years. Examination

of the mechanistic responses indicate that:-

1. The peak deflections at the top of each pavement layer as
function of the drainage coefficient (Figure 5.33) vary
with the variation in the drainage quality. It is to be

noted that the peak pavement deflection (the deflection

Table 5.10:

161

Layer thicknesses, moduli,

and mechanistic

responsses for five values of the drainage

coefficient of section 159 (Layer coefficient

modification method)

 

Results of Analysis

Drainage coefficient

(pavement section 159 of Figure 5.1)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

0.50 0.70 1.00 1.30 1.50
Layer Thicknesses (inches)
AC 11.41 10.29 8.77 7.37 6.56
Base 25.78 12.14 6.04 3.34 2.43
Subbase 0.53 7.46 8.44 7.99 7.20
Structural Number 6.06 6 06 6.06 6 06 6.06
Layer Moduli(ksi)
AC 450 450 450 450 450
Base 18.41 25.21 40.00 64.75 88.67
Subbase 10.10 13.42 20.00 31.46 41.80
Roadbed 10.00 10.00 10.00 10.00 10.00
Deflection at top of
layer (mils)
AC 11.90 12.80 14.10 15.30 16.20
Base 11.10 12.00 13.40 14.80 15.70
Subbase 7.43 9.78 12.00 13.90 15.10
Roadbed 7.37 8.57 10.20 11.90 13.20
Vertical stress at top of
layer (psi)
Base 5.21 6.99 10.60 15.90 20.20
Subbase 1.15 2.30 4.61 8.61 12.10
Roadbed 1.13 1.57 2.32 3.25 3.99
Tensile Stress at the 70.40 78.50 89.10 95.60 95.80
bottom of AC (psi)
Vertical strain at top of
layer (microstrain)
AC 20.60 50.20 73.90 100 118
Base 137 155 182 205 215
Subbase 87.60 140 198 245 266
Roadbed 118 143 180 217 246

 

 

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166
at the top of the AC layer) decreases with the quality of
the drainage which is opposite to the finding of the
layer thickness modification method (see page 162 and

Figure 5.29).

The amount of compression experienced by each pavement
layer is a function of the drainage quality (Figure 5.34)
is different. Higher drainage coefficient causes lower
degree of compression in the AC and base layers and

higher compression in the subbase layer.

It can.be seen that the vertical strains (Figure 5.35) at
top of the base and subbase layers decrease as the
quality of drainage deteriorate. This shows that the
higher level of damage is being delivered to the layers
with poor drainage quality. This observation is opposite
to what was observed in the layer thickness modification

method (see page 162).

The tensile stress induced at the bottom of the AC layer
(Figure 5.36) due to an 18-kip ESAL is depicted.by Figure
5.36.It can be seen that the maximum variation in the
magnitude of the tensile stress from one section to
another is about 27 percent. For the thickness
modification method this variation was about 60 percent
(see Figure 5.32). This shows that the layer coefficient

modification method tends to produce better thickness

167
design than the thickness modification method.
The results of the ‘mechanistic responses from. both
methods i.e. the layer thickness modification method and the
layer coefficient modification method verify the fellowing

finding of SHRP (11) study:

For pavement sections‘with the same layer properties but
different drainage coefficients that have been designed by
using AASHTO procedure to be supported on the same roadbed
soil, to carry the same traffic volume and to have the same
serviceability loss during an equal performance period, the
results of the mechanistic analysis indicate that the
magnitudes of the deflections, stresses and strains induced in
the various pavement layers vary from.one pavement section to
another. That is the AASHTO design method does not produce
consistent results of the mechanistic responses. Hence the
results of the mechanistic analysis do not support the role of
the drainage coefficient (in adjusting the layer thicknesses

and layer coefficients) in the AASHTO design procedure.

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6.1 OUTPUTS FROM THE AASHTO DESIGN PROCEDURE
Table 6.1 summarizes the outputs from the AASHTO design
procedure for the selected pavement sections explained in

section 3.2.2 and Figure 3.2 of chapter 3 (pagesn)

6.2 MECI-IANISTIC RESPONSES FROM ELSYMS

The mechanistic responses (radial tensile strain at the
bottom of the AC layer and the vertical compressive strain at
the top of the roadbed soil) are listed in Table 6.2. Figure
6.1 presents the variation in radial tensile strain at the
bottom of the AC layer due to variation in axle load and
Figure 6.2 depicts the variation in the radial tensile strain
at the bottom of the AC layer due to variation in the
stiffness of the roadbed soil and the design 18-kip ESAL for
the pavement sections of Figure 3.2. Examination of the

mechanistic responses indicates that:

1. The radial tensile strain at the bottom of the AC layer
increases with the increase in axle load (see Figure
6.1). It can be seen from the figure that, in general,
the rate of increase in tensile strain decreases as the
axle load increases. This however should not be

interpreted as the rate of damage (e.g. fatigue life)

168

169

Table 6.1: Outputs from AASHTO DNPSBG computer program for the

Cell

 

pavement sections of Figure 3.2.

AASHTO Designed Thicknesses .

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

18-Kip IRoadbed ’
No. ESALS Modulus (inches) Q
ksi

( ) AC Base Subbase Total ‘

\

)

| I

)

!

199 25 7.5 8.21 7.03 10.35 25.59 '

202 25 10 8.21 7.03 5.88 21.12 t

i

205a 25 15 8.21 7.03 0.00 15.24 [

|l205 25 20 8.21 7.03 0.00 15.24 !

|

I

200 50 7.5 9.13 7.50 11.00 27.63 .
203 50 10 9.13 7.50 6.25 22.88
206a 50 15 9.13 7.50 0.00 16.63

H

II206 50 20 9.13 7.50 0.00 16.63

201 75 7.5 9.70 7.78 11.41 28.89 i
204 75 10 9.70 7.78 6.47 23.95
207a 75 15 9.70 7.78 0.00 17.48
207 75 20 9.70 7.78 0.00 17.48

 

 

 

 

 

 

 

 

 

170
Table 6.2: Mechanistic responses from ELSYMS for pavement

sections of Figure 3.2 for different axle loads and

tire pressure.

AASHTO Cell Radial Tensile Strain Vertical Compressive

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

‘

Design No. (u strain) at Bottom of Strain (u strain) at Top \

ESALS*10‘ AC Layer for Axle Load/ of Roadbed soil for Axle 1

Tire pressure of Load/Tire pressure of i

I

18-kip/ 23-kip/ 28-kip/ 18-kip/ 23-kip/ 28-kip/ }

80 psi 120 psi 120 psi 120 psi 120 psi 120 psi l

25 199 152 204 234 202 257 314 i
25 202 152 203 233 246 314 382
25 205a 147 198 227 244 315 378
25 205 142 191 218 236 306 366
50 200 132 175 203 168 214 262

50 203 131 174 202 205 261 319 n
50 206a 127 170 196 204 263 317
50 206 123 164 189 198 256 307
75 201 120 160 186 152 193 236

75 204 120 159 285 184 235 287 u

75 207a 117 155 280 184 237 286 “

 

 

 

 

 

 

 

 

 

 

171

RADIAL STRAIN (micro strain)

 

240 ’

220

200 *

180

 

100

 

 

 

 

18 23

AXLE LOAD(K|PS)

 

 

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fisoction 208 X'scmlon 208. .soction 201 'section 204 *soction 207 8section 2070

 

 

Flgure 6.1: Effect of axle load on radial rensile strain at bottom
of AC layer for the indicated pavement sections

28

172
decreases with increasing axle load. The reason is that
the fatigue life in terms of tensile strain follows a
power function. Hence a full analysis of the fatigue life
must be conducted before a proper conclusion regarding
the rate of damage can be made. Nevertheless, the above
observation implies, as it was expected, that increasing

axle load causes higher fatigue damage.

The radial tensile strain at the bottom of the AC layer
decreases with.the increase in.the stiffness (modulus) of
the roadbed soil (see Figure 6.2). This implies that
stiffer roadbed soils cause a decrease in the tensile
strain (though. minimal) in. the asphalt layer. This
finding negates the AASHTO concept that a variation in
the roadbed soil strength affects only the layer

immediately above it.

The vertical compressive strain at the top‘of the roadbed
soil increases almost linearly'with.increase:in.axle load
(see Figure 6.3). The reason for this is that the ELSYMS
computer program uses the layer elastic theory which
produces linear responses. If nonlinear material models
are available, one can then use the nonlinear option of
the MICHPAVE program to assess the nonlinear effects of

the load on the compressive strain.

ii.
L

 

173

RADIAL STRAIN (micro strain)
160

 

14o , 25-8 10‘6 ESAL

I

so x we ESAL ’

120x -i

 

75 X 10‘6 ESAL

100'

80’

60’

40'

 

 

 

7.5 10 15 20

ROADBED MODULUS (ksi)

Figure 6.2: Effect of roadbed soil on radial tensile strain at bottom
of AC layerfor different levels of18 kip ESAL.

174

VERTICAL STRAIN (micro strain)

 

400

 

 

 

 

 

 

100
18 23 28

AXLE LOAD(K|PS)

 

*Soctton 199 +Soctton 202 *uctton 205 'uotlon 20!. 9(section 200 *uotlon 203
Answer! zoo X'mnum zoo. .uctton 201 'am:::: 204 *ucaon 207 Emama 207-

 

 

 

Figure 6.3: Effect of axle load on vertical compressive strain at
top of roadbed for the indicated pavement sections

175

6 .3 PREDICT- FATIGUE AND RUT PERFORMANCE OF THE AASHTO

DESIGNED PAVEMENT SECTIONS

The fatigue and rut lives of each of the AASTHO designed
pavement sections with respect to various fatigue and rut
models are listed in.Table 6.3 through 6.5 and 6.6 through 6.8
respectively. Tables 6.9 and 6.10 present a summary of the
fatigue and rut lives respectively. Figures 6.4 through 6.12
present the pavement lives relative to roughness, fatigue and
rut for pavement sections 199, 200 and 201. Examination.of the

figures indicate that:-

1. The fatigue lives of the AASHTO designed pavement
sections predicted by the various fatigue models are
shorter than the AASHTO design life except for sections
206 and 207, for which the fatigue life predicted by the
MICH-PAVE model is greater than the AASHTO design life
(see Tables 6.9 and 6.10 and Figures 6.4 through 6.6).
This implies that the fatigue life should control the
design of these pavements rather than the roughness as

predicted by the AASHTO model.

2. The fatigue and rut lives of the.AASHTO(designed.pavement
sections decrease with increases in axle load and tire
pressure (see Tables 6.9 and 6.10 and Figures 6.7 through
6.12) . The implication of this is that the design of
pavements that expected to carry high axle loads (as in

Pakistan) must be based on fatigue and rut models rather

Table 6.3:

designed pavement

The fatigue life

176

(Million repetitions) of AASHTO

sections of Figure 3.2

Axle load a 18-Kip, Tire pressure . 80 psi.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

= #
AASHTO Cell Radial Asphalt Monsmith Michpave NAASRA
Design No . Tensile Institute model Model Model
ESALs Strain, Model
*106 bottom of . . . .
Fatigue iFatigue Fatigue Fatigue
AC La er
y Life Life Life Life
(pstrain)
199 152 4.49 0.23 4.09 7 11 II
202 152 4.49 0.23 5.87 7.11
25 205a 147 5.01 0.26 11.09 8.40
205 142 5.62 0.29 24.6 9.99
200 132 7.15 0.37 8.61 14.39
203 131 7.33 0.38 12.62 14.95
50 206a 127 8.12 0.42 23.79 17.45
206 123 9.02 0.47 52.36 20.48
H
201 120 9.78 0.51 13.74 23.17
204 120 9.78 0.51 20.28 23.17
75 207a 117 10.63 0.56 38.47 26.30
207 113 11.92 0.63 84.36 31.30

 

177

 

 

 

 

 

 

 

 

 

 

 

 

Table 6u4: The fatigue life (Million repetitions) of AASHTO
designed pavement sections of Figure 3.2
Axle load a 23-kip, Tire pressure - 120 psi.
AASHTO Cell Radial Asphalt Monismith Michpave
Design No. Tensile Institute model Model
ESALs Strain, Model
*106 bottom of , , ,
Fatigue Fatigue Fatigue
AC La er
y life Life Life
(u strain)
199 204 1.71 0.083 2.21
202 203 1.74 0.085 3.24
25 205a 198 1.88 0.092 6.18
205 191 2.12 0.104 13.62
200 175 2.83 0.141 4.60
203 174 2.88 0.144 6.88
50 206a 170 3.11 0.156 13.18
206 164 3.50 0.176 28.90 4.86
01 160 3.80 0.191 7.28 5.50
204 159 3.88 0.196 10.97 5.67
75 207a 155 4.21 0.213 21.16 6.44

 

 

 

 

 

 

 

 

 

 

 

 

 

178

Table 6.5: The fatigue life (Million ESALs) of AASHTO
designed pavement sections of Figure 3.2

Axle load a 28-kip, Tire pressure - 120 psi.

   

 

 

 

 

 

 

 

 

 

 

 

 

 

a:
Radial Asphalt Monsmith Michpave NAASRA
Tensile Institute model. Model Model
Strain, Model
*106 bottom of , , , ,
Fatigue Fatigue Fatigue Fatigue"
AC La er
y Life Life Life Life
(ustrain)
199 234 1.09 0.052 1.20 0.82 Ii
202 233 1.10 0.052 1.73 0.84 H
25 205 227 1.20 0.057 3.26 0.95 P
205a 218 1.37 0.066 7.25 1.17
200 203 1.73 0.084 2.56 1.67
203 202 1.76 0.086 3.73 1.71
50 206 196 1.95 0.095 7.02 1.99
206a 189 2.19 0.11 15.46 2.39
201 186 2.31 0.11 4.10 2.59
204 185 2.35 0.12 6.01 2.66
75 207 180 2 58 0.13 11 36 3 05

 

 

 

 

 

 

 

 

 

 

179

Table 6.6: Rut life (Million repetitions) of AASHTO designed
pavement sections of Figure 3.2

Axle Load a 18-kip, Tire Pressure - 80 psi.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

.=_========.=_=====-======:=——.--—.
” AASHTO Cell Vertical Asphalt TRRL ERES
Design. NO. compressive Institute Model Model
ESALs strain, Model
*106 top Of Rut Life Rut Life Rut LifeII
roadbed
(pstrain)
199 202 49.21 24.29 47.43
202 246 20.35 11.15 19.62
25 205a 244 21.11 11.51 20.36
205 236 24.51 13.14 23.64
200 168 112.37 50.30 110.00
203 205 46.06 22.92 44.40
50 206a 204 47.08 23.36 45.38
206 198 53.82 26.29 51.87
201 152 175.95 74.70 170.00
204 184 74.76 35.12 72.03
207a 184 74.76 35.12 72.03 H
I
I
I

 

 

 

180
Table 6.7: Rut life (Million repetitions) of AASHTO designed

pavement sections of Figure 3.2

Axle load a 23-kips, Tire pressure = 120 psi.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

AASHTO Cell Vertical .Asphalt TRRL ERES
Design 1%). compressive Institute Model Model
ESALs strain, Model
*106 top of . . . '
Rut Life Rut Life Rut Life
roadbed
(ustrain)
199 257 16.73 9.38 16.14 H
202 314 6.82 4.25 6.58 I
25 205a 315 6.72 4.20 6.49 I
205 306 _ 7.65 4.71 7.39
200 214 38.00 19.33 36.63
203 261 15.61 8.83 15.06
50 206a 263 15.09 8.56 14.55
206 ‘256 17.03 9.53 16.42 f
201 193 60.36 29.08 58.17
204 235 24.98 13.36 24.09
75 207a 237 24.05 12.92 23.19 i
207 231 26.98 14.30 26.02 “

 

 

181

Table 6.8: Rut life (Million ESALs) of AASHTO designed
pavement sections of Figure 3.2

Axle load = 28-kip, Tire pressure a 120 psi.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

=g - - - - — ”7 ___-_, ~ .
AASHTO Cell Vertical Asphalt TRRL ERES
Design. No. compressive Institute Model Model
ESALs strain, Model

*106 to of
p Rut Life Rut Life Rut Life
roadbed
(pstrain)
199 314 6.82 4.25 6.58 n
202 382 2.83 1.96 2.74
25 205a 378 2.97 2.04 2.87
205 366 3.43 2.32 3.31 n
200 262 15.35 8.70 14.80
203 319 6.35 4.00 6.13
50 206a 317 6.54 4.10 6.31
206 307 7.55 4.65 7.28
201 236 24.51 13.14 23.63
204 287 10.20 6.07 9.84
75 207a 286 10.36 6.15 10.00
207 278 11.77 6.88 11.35
1=====m==s=—=__====A

 

 

 

 

 

 

 

 

Table 6.9:

 

pavement

sections

182

of Figure 3.2

Summary of fatigue lives (Million repetitions) of

 
   
   

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

====—-
Asphalt Monismith Model-
Institute Model-Fatigue Life for
ESALs Fatigue Life forAxle Load of Axle Load of
*10‘ Axle Load of
18- 23- 28- 18- 23- 28- 18- 3- 28- 18- 23- 28-
kip kip kip kip ip kip kip ip kip Ikip litip Ikip
199 4.49 1.70 1.09 0.23 0.083 0.052 4.09 2.21 1.20 7.11 1.63 0.82
202 4.49 1.73 1.10 0.23 0.085 0.0525.87 3.24 1.73 7.11 1.67 0.84
25 205a5.01 1.88 1.20 0.26 0.092 0.05711.09I6.18 3.26 8.40 1.90 0.95
205 5.62 2.12 1.37 0.29 0.104 0.06624.6013.627.25 9.99 2.27 1.17
200 7.15 2.83 1.73 0.37 0.141 0.0848.61 4.60 2.56 14.39 3.51 1.67
203 7.33 2.88 1.76 0.38 0.144 0.08612.626.88 3.73 14.95 3.61 1.71
0 206a8.12 3.11 1.95 0.42 0.156 0.09523.7913.187.02 17.45 4.06 1.99
5
206 9.02 3.50 2.19 0.47 0.176 0.110 52.36 28.9015.46 20.48 4.86 2.39
201 9.78 3.80 2.31 0.51 0.191 0.11013.747.28 4.10 23.17 5.50 2.59
204 9.78 3.88 2.35 0.51 0.196 0.120 20.28 10.976.01 23.17 5.67 2.66
5 207a10.63 4.21 2.58 0.56 0.213 0.130 38.47 21.1611.36 26.30 6.44 3.05
7
207 11.92 4.69 2.88 0.56 0.239 0.140 84.36 )IG.3‘724.93 31.30 7.59 3.61
fig

 

 

 

 

183

Summary of rut lives (Million repetitions) of the

Table 5.10:
pavement sections of Figure 3.2

3 I
ERES Model Rut Life

 

AASHIT) Cell Asphalt Institute TRRL Model Rut Life
Model Rut Life for for Axle Load of for Axle Load of

Design No.

Axle Load of

 

 

 

 

 

 

 

 

 

ESALs
.10.
18- 23- 25- 18- 23- 25- 18- 23- 28-
kip kip kip kip kip kip kip kip kip
199 49.21 15.73 6.82 24.29 9.38 4.25 47.43 15.14 5.53
202 20.35 6.82 2.83 11.15 4.25 1.95 19.52 6.58 2.74
205a 21.11 6.72 2.97 11.51 4.20 2.04 20.36 6 49 2.87
25
205 24.51 7.55 3.43 13.14 4.71 2.32 23.54 7.39 3.31
200 112.37 33.00 15.35 50.30 19.33 5.70 110.00 35.53 14.50
203 45.05 15.51 5.35 22.92 8.83 4.00 44.40 15.05 5.13
206a 47.08 15.09 5.54 23.35 8.56 4.10 45.38 14.55 5.31
50
7.55 25.29 9.53 4.55 51.87 15.42 7.28

206 53.82 17.03
170.00 58.17 23.63

 

201 175.95 60.36 24.51 74.70 29.08 13.14

72.03 24.09 9.84

 

204 74.76 24.98 10.20 35.12 13.36 6.07

72.03 23.19 10.00

 

207a 74.76 24.05 10.36 35.12 12.92 6.15

75
39.16 14.30 6.88 81.49 26.02

11.35

 

 

 

 

26.98 11.77

 

 

207 84.58

 

 

 

 

 

 

 

 

 

Predicted performance (Million Repetitions)

184

 

20)—

 

ERES

NAASRA

A) MICH PAV-
1 1 1 1

Roughness Fatigue

 

 

 

 

Performance Models

Figure 6.4: Comparison of predicted performances of
pavement section 199 (18 - kip ESAL)

250

's‘ '5’

Predicted performance (Million Repetitions)
8

185

 

 

 

AASHTO

Roughness

Figure 6.5: Comparison of predicted performances of

ERES

AASRA

N
Al MICH PAVj
l L 1

Fatigue

 

Performance Models

pavement section 200 (18 - kip ESAL)

 

Predicted performance (Million Repetifions)

400

§

'5’

100

186

 

 

 

 

 

ERES
— AASHHD
J AI MICH PAViNMSRA
Roughness l 1 Fatigue 1 1
Performance Models
Figure 6.6: Comparison of predicted performances of

pavement section 201(18 - kip ESAL)

 

Predicted performance (Million Repetitions)

187

Al Fatigue Model performance

 

 

 

   

Axle load (Kips)

Figure 6.7: Effect of axle load on predicted fatigue
performance of pavement section 199

 

Predicted performance (Million Repetitions)

188

MICHPAVE Model Performance

 

 

 

   

Axle Load (kips)

Figure 6-8: Effect of axle load on predicted fatigue
performance of pavement section 199

 

 

189

NAASRA Fatigue Model Performance

 

Predcted perfonnanoe (Mllion Repetitions)
.5

 

 

Figure 6.9:

   

Axle load (Kips)

Effect of axle load on predicted fatigue
performance of pavement section 199

 

 

Predicted performance (Million Repetitions)

20

190

Al Rut Model performance

 

 

     

Axle Load (Kips)

Figure 6.10: Effect of axle load on predicted rut
performance of pavement section 199

 

Predicted performance (Million Repetitions)

20

191

TRRL Rut Model performance

 

 

 

   

Axle load (Kips)

Figure 6.11: Effect of axle load on predicted rut
performance of pavement section 199

 

Predcted performance (Million Repetitions)

8

(A
O

B

..a
O

192

ERES Rut Model performance

 

 

 

Figure 6.12:

   

Axle load (Kips)

Effect of axle load on predicted rut
performance of pavement section 199

 

193

than on roughness. Hence the AASHTO design procedure
(which is roughness based model) is not applicable in

Pakistan.

The different fatigue and rut performance models used in
the study show large differences in.the predicted.fatigue
and rut performance for any one pavement section (see
Tables 6.9 and 6.10 and Figures 6.4 through 6.6). Given
that those models were developed for pavements in
different environmental regions and different pavement
designs and construction practices, one can conclude that
Pakistan must develop rut and fatigue models that are
applicable to the axle loads found in Pakistan and to the

environmental conditions.

,An.’

CILKPTERUI
SJIHNYIUflflfiUTS-lflflflAfiKflflMmmflf(”fFAJIGKflURlflFPERTIHMMMflflflE

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7.1 GENERAL

It was stated in Chapter 6 that for the pavement sections
of Figure 3.2 and in the range of material properties used,
the predicted fatigue life (in terms of 18-kip ESAL) using
various fatigue models, is much shorter than the Design ESALs
used.in AASHTijrocedure. Since the AASHTO design.procedure is
based on pavement roughness, one can conclude that for the
pavement sections of Figure 3.2, the fatigue life not
roughness should control the pavement design process. Given
the above scenario, the question becomes what material types
should be used so that the fatigue life of the pavement is
equal to or longer than the AASHTO Design ESALs, input in the
procedure?

To answer the question, three trial designs were
conducted. In the first trial, the granular base layer was
simply replaced by an AC stabilized base material. The second
trial consisted of eliminating the subbase layer and replacing
the granular base layer by an asphalt treated layer. In the
third trial, the values of the modulus of the base and subbase
layer were increased (to be achieved through compaction). In
these trials, the thicknesses obtained from the AASHTO Design
Procedure, listed in Table 6.1 (without changing the
base/subbase modulus) were used. The results of the analysis

are discussed/presented below.

194

195

7.2 TRIAL 1, REPLACING GRANULAR BASE WITH AN AC STABILIZED
BASE (layer modulus equal to or greater than 250 ksi)
In this trial, the granular base layer (Layer modulus 30
ksi) of each pavement section of Figure 3.2 was replaced.by an
AC stabilized base layer while keeping the same thicknesses.
Mechanistic analysis was then conducted, and the fatigue life
(in terms of 18-kip ESAL) and the number of ESALs to 0.5 inch
rut were then computed using various prediction models. Table
7.1, Table 7.3 and Table 7.5 present the original and.enhanced
fatigue lives while the original and enhanced rut lives are
listed in Table 7.2, Table 7.4 and Table 7.6. Figure 7.1,
Figure 7.3 and Figure 7.5 present the comparison of the
original and.enhanced fatigue lives whereas Figure 7.2, Figure
7.4 and Figure 7.6 depict the comparison of the original and
enhanced rut lives for pavement section 199 (Monismith model
exhibits very low original and enhanced fatigue performance
therefore it has not been discussed and shown in the Figures).
From the examination of the results in this trial following is

observed:

1. For the combination of 18 kip axle load and 80 psi
tire pressure, to exhibit fatigue performance equal
to or greater than the AASHTO input ESALs following

is seen:

a. The elastic modulus of the AC stabilized base

(for the pavement sections considered in this

196

study) needs to be enhanced in the range of
250 ksi to 300 ksi. This range of base modulus
satisfies all the fatigue criterion except
Monismith criterion (see Table 7.1).

The magnitude of the enhancement varies with
the type of fatigue/rut prediction model. In
the range of AC stabilized base modulus (250
ksi to 300 ksi) used for this trial, Asphalt
Institute model exhibit fatigue life which is
almost equal to AASHTO input ESALs whereas
MICHPAVE and NAASRA fatigue models exhibit
fatigue life ‘much. greater than. the .AASHTO
input ESALs (see Table 7.1). Figure 7.1
present the comparison of the enhanced fatigue
lives predicted by various fatigue models for
pavement section 199.

The results of enhanced fatigue lives
exhibited (hue to ‘various fatigue criterion
indicate that the sections where there is no
subbase used, require relatively less increase
in the base modulus to achieve fatigue life
equal to or greater than the sections where
some subbase thickness is used. This reduction
in base modulus is partly attributable to the
increased roadbed modulus (see Tables 7.1 and
Tables 7.2).

The rut life exhibited by all the rut

 

 

197

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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performance criterion used in this study
namely Asphalt Institute, TRRL and ERES is
much greater than the AASHTO input ESALs (see
Table 7.2). Figure 7.2 present the comparison
of the enhanced rut lives predicted by various

rut models for pavement section 199.

For combination. of 23 kip axle load and tire
pressure of 120 psi to exhibit the fatigue
performance equal to or greater than the AASHTO

input ESALs following is seen:

a. A higher increase in the elastic moudli of the
AC stabilize base layer is required. The
increase required in the elastic moudli of the
base is in the range of 335 ksi to 450 ksi
(see Table 7.3).

b. Within this range of elastic moudli i.e., 335
ksi to 450 ksi, the magnitude of enhancement
varies with the type of fatigue prediction
model. .Asphalt Institute: model exhibit the
fatigue life almost equal to or greater than
the AASHTO input ESALs whereas MICHPAVE and
NAASRA fatigue models exhibit fatigue life
much greater than the AASHTO input ESALs (see
Table 7.3). Figure 7.3 present the comparison

of the enhanced fatigue life predicted. by

200

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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204
various fatigue models for pavement section
199.

c. For this combination of load and tire
pressure, the rut life exhibited by all the
rut criterion used in this study namely
Asphalt Institute, TRRL and ERES is much
greater than the AASHTO input ESALs (see Table
7.4). Figure 7.4 presents the comparison of
the enhanced rut lives predicted by various

rut models for pavement section 199.

Combination of 28 kip axle load and 120 psi tire
pressure requires further increase in the moduli of
the AC stabilized base layer. For this combination
of axle load and tire pressure, the elastic moduli
of the base was increased to maximum limit of 450
ksi (Please remember this is the elastic moduli
used for the AC layer in this study). For this

limit of elastic moduli following is seen:

a. Asphalt Institute model exhibits the magnitude
of enhanced fatigue life shorter (39% to 54%
shorter) than AASHTO input ESALs whereas the
MICHPAVE and.NAASRA fatigue criterion exhibits
the magnitude of fatigue life almost double
than the AASHTO input ESALs (see Table 7.5).

Figure 7.5 present the comparison of the

205

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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206

 

 

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CON

209

enhanced fatigue lives predicted by various
fatigue models for pavement section 199.

b. The magnitude of enhanced rut life exhibited
by all the rut criterion used in this study
namely Asphalt Institute, TRRL and ERES is
much greater than the AASHTO design life (see
Table 7.6). Figure 7.6 present the comparison
of the enhanced rut lives predicted by various

rut models for pavement section 199.

For any' axle load, the chances of failure of
pavement sections (considered in this study) in
fatigue are relatively more as compared to its
failure in rut. For example, for combination of 28
kip axle load and 120 psi tire pressure for section
199, the fatigue life predicted by Asphalt
Institute, MICHPAVE and NAASRA models is 15.18
112.10, 45.18 million repetitions reSpectively (see
Figure 7.5) whereas the rut life predicted by AI,
TRRL and ERES models is 246.35, 492.69 and 240
million repetitions respectively (see Figure 7.6).
This shows that chances of section 199 failing in
fatigue are more as compared to its failing in rut.
This phenomena also applies to the other pavement

sections considered in this study.

210

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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211

 

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212

7.3 TRIAL 2, ELIMINATING SUBBASE AND REPLACING GRANULAR BASE
WITH ASPHALT TREATED BASE (Layer Mbdulus Less than or
equal to 200 Ksi).

In this trial, the subbase was eliminated and granular
base layer of each.pavement section.of Figure 3.2 was replaced
by an Asphalt Treated base (while keeping the same
thicknesses). Mechanistic analysiS‘was than.conducted, and the
fatigue life (in terms of 18 Kip ESAL) and the number of ESALs
to 0.5 inch rut were then computed using various prediction
models. Table 7.7, Table 7.9 and Table 7.11 present the
original and enhanced fatigue lives and Table 7.8, Table 7.10
and Table 7.12 present the original and enhanced rut lives.
Figure 7.7, Figure 7.9 and Figure 7.11 present the comparison
of the original and enhanced fatigues lives whereas Figure
7.8, Figure 7.10 and Figure 7.12 present the comparison of the
original and enhanced rut lives for pavement section 199
(Monismith model exhibits very low original and enhanced
fatigue performance therefore it has not been discussed and
shown in Figures). From the examination of the results in this

trial following is observed:—

1. For the combination of 18-kip axle load and 80 psi
tire pressure, elimination of the subbase layer and
enhancement of granular base to asphalt treated
base, following is seen:

a. To exhibit fatigue life equal to or greater

than the AASHTO input ESALs the layer moduli

213

of the asphalt treated base needs to be
increased in the range of 110 ksi to 160 ksi
(see Table 7.7).

The magnitude of enhancement varies with the
type of fatigue/rut prediction models. This
result is similar to what was predicted in
Trial 1. Asphalt Institute model exhibits the
magnitude of enhanced fatigue life almost
equal to or slightly greater than the AASHTO
input ESALs whereas the MICHPAVE and NAASRA
fatigue models exhibit the magnitude of
fatigue lives much greater than the AASHTO
input ESALs except for section 199 in which
the fatigue life predicted by MICHPAVE model
is slightly' shorter ‘than. the .AASHTO input
ESALs (see Table 7.7). Figure 7.7 presents the
comparison of the enhanced fatigue lives
predicted by various fatigue models for
pavement section 199.

At this load and tire pressure, the magnitude
of enhanced rut life exhibited by all the rut
criterion namely Asphalt Institute, TRRL and
ERES is much greater than the AASHTO design
life (see Table 7.8). Figure 7.8 present the
comparison of the enhanced rut lives predicted
by various rut models for pavement section

199 .

214

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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218

For combination of 23 kip axle load and 120 psi

tire pressure after elimination of subbase, the

asphalt treated base modulus was increased to a

maximum value of 200 ksi. From the examination of

the results, it is observed that:

a.

The elimination of subbase and replacement of
granular base with asphalt treated base
enhances the magnitude of the fatigue life of
the pavement sections considered in this study
but it remains less than the AASHTO input
ESALs with some of the fatigue criterion. For
example, the enhanced fatigue life of all the
pavement sections of this study with MICH-PAVE
fatigue criterion is greater than the AASHTO
input ESALs and this is true for some of the
pavement sections with NAASRA fatigue
criterion whereas the magnitude of the
enhanced fatigue life with Asphalt Institute
fatigue Icriterion. remains shorter" than. the
AASHTO input ESALs by 50% to 82% (see Table
7.9). Figure 7.9 present the comparison of the
enhanced fatigue lives predicted by various
fatigue models for pavement section 199.

For this load and tire pressure, the magnitude
of enhanced rut life exhibited by all the rut
criterion namely Asphalt Institute, TRRL and

ERES is much greater than the AASHTO input

219

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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ESALs (see Table 7 . 10) . Figure 7 . 10 present
the comparison of the enhanced rut lives
predicted by various rut models for pavement

section 199.

For combination of 28 kip axle load and 120 psi
tire pressure, the elimination of subbase and use
of the highest value of the asphalt treated base
modulus i.e., 200 ksi (please remember this is the

highest value of asphalt treated base used for this

study), the examination of the results indicates
that:
a. For the combination of 28-kip axle load and

120 psi tire pressure, the magnitude of the
enhanced fatigue life is greater than the
AASHTO input ESALs only with MICH-PAVE
criterion except for pavement sections 199,
200, and 201 for which the fatigue life is
less than the AASHTO input ESALs by about 40%
(see Table 7.11). The magnitude of enhanced
fatigue life exhibited by the other fatigue
criterion namely Asphalt Institute and NAASRA
is less than the AASHTO input EASLs by about
72% to 89% and 37% to 84% respectively. Figure
7.11 present the comparison of the enhanced
fatigue lives predicted by various fatigue

models for pavement section 199.

 

222

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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b. For this load and tire pressure, the magnitude
of enhanced rut life exhibited by all the rut
criterion namely Asphalt Institute, TRRL and
ERES is much greater than the AASHTO input
ESALs (see Table 7.12). Figure 7.12 present
the comparison of the enhanced rut lives
predicted by various rut models for pavement

section 199.

For the combination of standard axle load of 18 Kip
and 80 Psi tire pressure, the results (presented
for fatigue life in Table 7.1 and Table 7.7 and for
rut life in Table 7.2 and Table 7.8) indicate that
the replacement of granular base with asphalt
stabilized base (Wk base equal to or greater than
250 ksi) and the elimination of subbase and
replacement of granular base with asphalt treated
base 0%, base less than. or equal to 200 Ksi)
exhibits the magnitude of enhanced fatigue/rut life
equal to or greater than the AASHTO input ESALs in
both cases. This mean that for a standard axle load
of 18 kip and tire pressure of 80 psi, the use of
asphalt treated base when no subbase is used may
give economical pavement sections for obvious

reasons .

227

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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229
7.4 TRIAL 3, INCREASING LAYER MODULI (through compaction) OF
THE GRANULAR BASE AND SUBBASE LAYER
In this trial the layer moduli of granular base and
subbase layer of each pavement section of Figure 3.2 was
increased upto a value of 75 Ksi and 40 Ksi respectively,
mechanistic analysis was then conducted, the fatigue life (in
terms of 18 Kip ESAL) and the number of ESAL to 0.5 inch rut
were then computed using various prediction models as was done
in Trial 1 and Trial 2 of the study. The original and enhanced
fatigue lives are listed in Table 7.13, Table 7.15 and Table
7.17. The original and enhanced rut lives are listed in Table
7.14, Table 7.16 and Table 7.18. Figure 7.13, Figure 7.15 and
Figure 7.17 present the comparison of original and enhanced
fatigue lives. Figure 7.14, Figure 7.16 and. Figure 7.18
present the comparison of original and enhanced rut lives for
pavement section 199 (Monismith model exhibit very low
original and enhanced fatigue performances, therefore it has
not been discussed and shown in the Figures). Examination of
the results in this trial indicate that
1. For the combination of 18-kip axle load and 80 psi
tire pressure, by increasing the layer moduli
(through compaction) of the granular base and
subbase layer following is seen:
a. The magnitude of the fatigue and rut lives of
pavement sections is enhanced. The enhancement
varies with the type of fatigue and rut

prediction model. This result is similar to

 

230

the results observed in Trial 1 and Trial 2.
The Enhanced fatigue life exhibited by
MICHPAVE and NAASRA fatigue models is equal to
or greater than the AASHTO input ESALs whereas
Asphalt Institute model exhibit enhanced
fatigue life which is almost half of the
AASHTO input ESALs (see Table 7.13). Figure
7.13 present the comparison of the enhanced
fatigue lives predicted by various fatigue
models for pavement section 199.

The magnitude of enhanced rut life exhibited
by all the rut criterion used in this study
namely Asphalt Institute, TRRL and ERES is
much higher than the AASHTO input ESALs (see
Table 7.14). Figure 7.14 present the
comparison of the enhanced rut lives predicted
by various rut models for pavement section

199.

For the combination of 23-kip axle load and 120 psi

tire pressure, by increasing the layer moduli

(through compaction) of the granular base and

subbase layer following is seen:

The magnitude of enhanced fatigue life
exhibited by MICHPAVE fatigue criterion is
equal to or greater than the AASHTO input

ESALs for only half of the pavement sections

231

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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235

(i.e, pavement section numbers 205, 205a,
206, 206a, 207, and 207a). Please note that
these are those pavement sections in which no
subbase has been used. The magnitude of
enhanced fatigue life exhibited by other
fatigue criterion for all pavement sections
considered in this study remains less than the
AASHTO input ESALs. In Asphalt Institute model
the magnitude: of enhanced fatigue life is
shorter than the AASHTO input ESALs by about
80% to 82%. In NAASRA fatigue model the
magnitude of enhanced fatigue life is shorter
than the AASHTO input ESALs by about 68% to
70% (see Table 7.15). Figure 7.15 present the
comparison of the enhanced fatigue lives
predicted by various fatigue models for
pavement section 199.

b. The magnitude of enhanced rut life exhibited
by all the rut criterion (considered in this
study) is equal to or greater than the AASHTO
input ESALs (see Table 7.16). Figure 7.16
present the comparison of the enhanced rut
lives predicted by various rut models for

pavement section 199.

For the combination of 28—kip axle load and tire

pressure of 120 psi, by increasing the layer moduli

236

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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(through compaction) of the granular base and

subbase layer following is seen:

a.

The magnitude of enhanced fatigue life
exhibited by MICHPAVE fatigue criterion is
equal to or greater than the AASHTO input

ESALs only for three of the pavement sections

considered in this study (i.e, pavement
section number 205a, 206a, 207a) (see Table
7.17). Please note that these are those

pavement sections which has stronger roadbed
soils (MR 20 Ksi). The magnitude of enhanced
fatigue life exhibited by all other fatigue
criterion for all the pavement sections of
this study remains much shorter than the
AASHTO input ESALs. Figure 7.17 presents the
comparison of the enhanced fatigue lives for
pavement section 199.

The magnitude of enhanced rut life exhibited
by Asphalt Institute and ERES rut criterion is
higher than the AASHTO input ESALs only for
half of the pavement sections (i.e, pavement
section 199, 200, 201, 202,203 and 204)(See
Table 7.18). Please remember that these are
those pavement sections in which some
thickness of subbase has been used. The
magnitude of enhanced rut life exhibited by

TRRL rut criterion is equal to or higher than

 

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243
the AASHTO input ESALs except for three
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and 206a and 207a for which it is slightly
lower than the AASHTO input ESALs. Figure 7.18
presents the comparison of the enhanced

fatigue lives for pavement section 199.

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and tire pressure of 80 psi (i.e 23 Kip axle load,
28 Kip axle load and 120 psi tire pressure) the
enhancement in the magnitude of predicted fatigue
life is shorter than the AASHTO input ESALs (see
Table 7.15 and Table 7.17). Therefore for higher
loads and tire pressures, the pavements designed by
merely increasing the layer moduli (through
compaction) of the granular base and subbase may
not exhibit the performance equal to the AASHTO

input ESALs and may fail in fatigue prematurely.

244

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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8.1 CONCLUSIONS

Based on the analysis of this study results, following

conclusions are drawn:

1. Results of the SHRP study stand verified relative to the
conditions in Pakistan except for the case of roadbed
soil stiffer than the subbase/base. For this particular
case the DNPSB6 computer program does not produce same
structural number for same traffic level and one type of
roadbed soil (see Figure 5.7). However if the
subbase/base softer than the roadbed is omitted from the
program then it produces the same structural number for
same traffic level and one type of roadbed soil (see

Figure 5.6).

2 ._ The AASHTO 86 design procedure produces underdesigned
pavement sections for loading conditions in Pakistan with-
respect to various fatigue and rut models (see Table 6.9
and Table 6 . 10) . Hence the AASHTO design procedure (which
is roughness based model) is not applicable in Pakistan.
Therefore, the design of pavements that are expected to
carry high axle loads (as in Pakistan) must be based on

fatigue and rut models rather than on roughness.

246

 

247

Pavement structures placed on stiffer roadbed soil are
likely to experience less fatigue damage. This finding
negates the observation from AASHTO design procedure that '
the variation in the roadbed soil strength affects only
the subbase layer (see Figure 6.2).

The fatigue and rut performance decreases with increase
of axle loads and tire pressure which is a normal

phenomenon in Pakistan.

The Different fatigue and rut models used in the study
show a very large difference in the fatigue and rut
performance for any one pavement section. Similarly the
enhanced predicted rut and fatigue performance for any
one of the pavement sections also varies with the type of

the fatigue/rut prediction model.

The results of the study indicate that for any axle load,
the chances of failure of pavement sections (Considered
in this study) in fatigue are relatively'more as compared

to its failure in rut.

Basing on the trials conducted in this study, it is
concluded that to the conditions in Pakistan pavement
bases need to be treated/stabilized and the fatigue life
not the roughness should control the design process. For
combination of higher axle loads and tire pressures (i.e

23 kip, 28 kip axle load and 120 psi tire pressure), the

 

248
pavements designed by merely increasing the layer moduli
(through compaction) of the granular base and subbase may
not exhibit the performance equal to the AASHTO input

ESALs and may fail in fatigue prematurely.

For the combination of standard axle load of 18 Kip and
80 Psi tire pressure, the examination of results of Trial
1 (the replacement of granular base with asphalt
stabilized base, MR base > 250 Ksi) and Trial 2
(elimination of subbase and replacement of granular base
with asphalt treated base, MR base < 200 Ksi) indicate
that the magnitude of enhanced fatigue/ rut life exhibited
(due to various fatigue/rut models used in this study) in
both the trials is equal to or greater than the AASHTO
input ESALs. This mean that for the combination of
standard axle load of 18 Kip and tire pressure of 80 Psi,
the use of asphalt treated base (MR < 200 Ksi) alongwith
elimination of subbase may be economical in Pakistan as
compared to the use of asphalt stabilized base (MR > 250

Ksi) along with some thickness of subbase.

RECOMMENDATIONS

The study indicates that the AASHTO design procedure
cannot be adopted for conditions other than it was
developed . Hence , it is recommended that the AASHTO

design procedure should not be used as the only procedure

249
for design of pavements in Pakistan. The pavement designs

be examined mechanistically for loading conditions of

Pakistan.

None of the existing pavement performance models can be
used for the existing environmental and material
conditions in Pakistan. It is strongly recommended that
fatigue and rut data be collected and the models be
calibrated for conditions in Pakistan or local models be

developed.

It is highly recommended that to control the heavy axle
load conditions observed in Pakistan, the National
Highway .Authority in Pakistan should install weigh
stations all along its road.network.and.enforce the legal

load limits.

REFERENCES

The Study on National Transport Plan in the Islamic
Republic of Pakistan, Final Report, Volume II, Feburary

1995, JICA.

Training Block. Flexible Pavement Design. University of

Michigan, U.S.A.

Thawat Watanatada, Clell G. Harral, William D. o.
Paterson, Ashok M. Dhareshwar, Anil Bhandari,and Koji
Tsunokania. The Highway Design and Maintenance Standards
Model. Volume 1, Description of the HDM-iii Model. A

World Bank Publication.

Zafar Iqbal Faruqi, "Axle Load Survey to Establish Latest
Truck [Factors for Pavement Design Between Taxila and
Lahore on National Highway (N-S) . A Thesis Work for M.sc.
(Civil Engineering) in Military College of Engineering

Risalpur, 1993.
E.J. Yoder and M. W. Witzak. Principles of Pavement
Design. Second Edition. New York, Jhon Willey $Sons,

1975.72.

American Association of State Highway and Transportation

officials. AASHTO Guide for Design of Pavement

250

 

10.

11.

12.

251
structures. Washington D.C., 1986.
Per Ullidtz. Pavement Analysis. Elservier Science

Publishers B.V. , Amsterdam- Oxford- New york- Tokyo, 1987.

Road Note 29, A guide to the Structural Design of
Pavements for New Roads. Third Edition, Road Research
Laboratory , Department of Environment , Department of

Transportation, London, 1977.

Yang H. Huang University of Kentucky. Pavement Analysis
and Design. Published by Prentice - Hall, Inc. U.S.A.

1993 .

Zafar Iqbal Raja. Pavement Design procedure for pakistan,
an Article Published in Corps of Engineers Journal 1993,

Published by Military College of Engineering Risalpur.

Gilbert Y. Baladi, and Francis X. Mckelvey Professors of
Civil and Environmental Engineering, Michigan State
University. Mechanistic Evaluation and Calibration of the
AASHTO Design Equations and Mechanistic Analysis of the

SHRP Asphalt Surfaced pavement Sections .Unpublished Data .

Ronald S. Harichandran, Ming-Shan Yeh, and Gilbert Y.
Baladi. "MICHPAVE: A Nonlinear finite Element Program for
Analysis of Flexible Pavements". Transportation Research

Record no. 1286, Washington, D.C. 1990.

13.

14.

15.

16.

17.

18.

19.

252

ELSYMS INTERACTIVE MICROCOMPUTER VERSION, User’s Manual
for IBM-PC and Compatible Microcomputer, Report no. FHWA-
TS-87-206, Final report december 1986, US Department of

Transportation USA.

Summary of Traffic Data for National Highways (1994).
National Transport Research Centre Ministry of

Communication Islamabad.

Report.5, Highway Research.Board Special Report 61E, "The

ASSHO Road Test," 1962.

Bonquist, R., R., "Effects of tire pressure on flexible
pavement response and performance, " Draft Report, Federal

Highway Administration, Washington, D. C., 1989.

Majeedq Abdul “Axle ‘Load. Survey" National 'Transport
Research Centre, Planning Commission, Islamabad (NTRC-

65), October 1982.

Majeed, Abdul "Multi Axle Vehicle Survey" National
Transport Research Center, Planning Commission, Islamabad

(NTRC-63), October, 1982.

B.J Coree and T.D. White. "AASHTO Flexible Pavement
Design Method: Fact or Fiction. Transportation Research
Record 1286, National Research Council Washington,

D.C.1990.

 

253
20. J.F. Shook and F.N. Finn. Thickness Design Relationships
for“ .Asphalt Pavements. Proc., 1st International
Conference on the structural design of Asphalt Pavements,

Ann Arbor, Mich., 1962.

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