development of empirical correlations between …

DEVELOPMENT OF EMPIRICAL CORRELATIONS

BETWEEN CALIFORNIA BEARING RATIO (CBR)

AND SOIL INDEX PROPERTIES.

K.V.S.D. Jayamali

(09/8812)

Degree of Master of Engineering

Department of Civil Engineering

University of Moratuwa

Sri Lanka

September 2013

i

DEVELOPMENT OF EMPIRICAL CORRELATIONS

BETWEEN CALIFORNIA BEARING RATIO (CBR)

AND SOIL INDEX PROPERTIES.

Kevitiyagala Vithanage Sanjeewani Disna Jayamali

(09/8812)

Thesis submitted in partial fulfillment of the requirement for the degree

Master of Engineering in Foundation Engineering and Earth Retaining Systems

Department of Civil Engineering

University of Moratuwa

Sri Lanka

September 2013

ii

DECLARATION

I hereby declare that the work presented in this dissertation is my own research except

as cited in the references. I also declare that this report has not been accepted for any

other University or Institute and no part of this project report has been submitted

earlier or concurrently for same or any other Degree or Diploma, to the best of my

knowledge.

……………………….

K.V.S.D. Jayamali

Admission No :

Date :

Certified By

……………………….

Dr. U.P. Nawagamuwa

(Supervisor)

iii

DEDICATION

This dissertation is dedicated to my loving husband and my parents and family, for

their endless love, support and encouragement. I won’t be here without their love,

patience, bear and understanding throughout my life. My wholehearted thanks go to

all of you giving me strength to achieve my dreams and lightened up my spirit to

finish this study and this thesis.

iv

ACKNOWLEDGEMENT

I would like to take this opportunity to express my sincere appreciation to all people

and organization that had contributed towards the successful completion of this

project.

First and foremost, I would like to extend gratitude to my supervisor, Dr. U.P.

Nawagamuwa, Senior Lecturer, Department of Civil Engineering, University of

Moratuwa, Sri Lanka for his guidance and support throughout this study, and

especially for his confidence on me. Once more I thank him for his able supervision

with spending his precious time and valuable advices in completion of this research

successfully.

Secondly, I wish to extend by sincere thanks to Geotech (Pvt) Ltd where I am

employed, for the cooperation by funding me in successful completion of this project.

My special thanks goes to all the staff of Group Engineering Laboratories (Pvt) Ltd

for their assistant to carry out laboratory experiments, and laboratory manager of

Engineering & Laboratories (Pvt) Ltd who provided relevant information and data for

achieving the research requirements while sharing her knowledge with me.

Last but not least, not to forget the full supports that has been given by my family

during my study.

v

ABSTRACT

The California Bearing Ratio is a penetration test for evaluation of the mechanical

strength of road sub-grades and base-courses. This can be used as a mean of designing

the road pavement required for a particular strength of sub-grade by comparing the

strength of different sub-grade materials.

However; civil engineers always encounter difficulties in obtaining representative

CBR value for design of pavement. Over the years, many correlations had been

proposed by various researchers in which the soil index properties were used to

develop these correlations.

A study was carried out to find correlations between CBR value with soil index

properties those best suit the type of soils in Sri Lanka. Analyses were carried out

based on the published correlations and soil data obtained from several Sri Lankan

project sites. Based on the results, it is observed that the current published correlations

are not in good agreement with Sri Lanka soils. In addition, no typical range could be

found based on the soil index properties.

Mechanical Strength of soil depends not only on the soil type but also on the

observable physical characteristics which significantly influence on a soil’s behavior.

Therefore, a method is proposed for correlating soaked CBR value and compaction

parameters with such index properties, for Sri Lankan soils. This research covers the

entire soil types according to Unified Soil Classification System which are generally

used as sub-grades and base-courses.

Among the several soil index properties, Atterberg Limits and grain size distribution

data are used in this regard as these tests are much more economical and rapid than

Compaction and CBR tests. The correlations are established in the form of an

equation as a function of different soil properties by the method of regression

analysis. Finally, results of the laboratory test are used to compare with the results of

regression equation for the compiled data for the validation of the correlation.

Key Words : California Bearing ratio, Compaction Parameters, Index Properties,

Regression Analysis

vi

TABLE OF CONTENTS

PAGE

DECLARATION II

DEDICATION III

ACKNOWLEDGEMENTS IV

ABSTRACT V

TABLE OF CONTENTS VI

LIST OF TABLES IX

LIST OF FIGURES X

LIST OF APPENDICES XIII

LIST OF SYMBOLS XIV

CHAPTER 1 : INTRODUCTION

1.1 Background 1

1.2 Problem Statement 3

1.3 Aim and Objectives of Study 3

1.4 Scope of Study 4

1.5 Significance of the Study 4

CHAPTER 2 : LITERATURE REVIEW

2.1 Introduction 5

2.2 Index Properties of Soils 5

2.2.1 Particle Size Distribution 5

2.2.2 Atterberg Limits 7

2.3 Soil Classification 9

2.4 Soil Compaction 14

2.5 California Bearing Ratio 15

2.5.1

2.5.2

2.5.3

Applications of California Bearing Ratio

Advantages and Disadvantaged of CBR Test

Alternative to CBR & its Limitations

17

18

19

vii

2.6 Existing Correlations between CBR and Index Tests 20

2.6.1

2.6.2

2.6.3

2.6.4

2.6.5

2.6.6

2.6.7

2.6.8

2.6.9

2.6.10

2.6.11

Black (1962)

de Graft – Johnson and Bhatia (1969)

Agarwal and Ghanekar (1970)

The Highway Agency (1994)

National Cooperative Highway Research Program (2001)

Kin (2006)

Vinod and Cletus (2008)

Roy et al (2009)

Ayodele et al (2009)

Patel and Desai ( 2010)

Breytenbach (2009)

20

22

23

24

25

26

27

28

28

28

28

2.6.12

2.6.13

Singh et al (2011)

Agarawal et al (2011)

33

34

CHAPTER 3 : METHODOLOGY

3.1 Introduction 36

3.2 Data Collection 38

3.2.1 Data Selection and Grouping 38

3.3 Laboratory Test Methods 40

3.4 Data Analysis 41

3.4.1 Regression Analysis 41

CHAPTER 4 : RESULTS AND DISCUSSION

4.1

4.2

4.3

4.4

Introduction

Data Categorization

Data Filtration

Data Analysis

43

43

44

51

4.4.1

4.4.2

Individual Parameter Analysis by Graphical Representations

Evaluation and Modification of Published Correlations

51

62

4.4.3 Development of New Empirical Correlations 92

4.4.4 General Discussion 107

4.4.5 Validation of developed correlations 109

viii

CHAPTER 5 : CONCLUSIONS AND RECOMMENDATIONS

5.1 Conclusion 111

5.2 Recommendations for Future Study 112

REFERENCES 114

ix

LIST OF TABLES TABLE

NO. TITLE PAGE

Table 2.1 :

Table 2.2(a):

Table 2.2(b):

Table 2.3 :

Table 2.4 :

Table 2.5 :

Table 2.6 :

Table 2.7 :

Table 2.8 :

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 4.9 :

Different methods of Proctor Compaction Test

Typical Values of CBR by Unified Soil Classification System (Semen,2006)

Typical Values of CBR by Unified Soil Classification System(Semen,2006)

Subgrade CBR estimation of British soils compacted at natural moisture

content (The Highway Agency, 1994)

Statistics of Data Used by International Journal of Computer Applications

Correlation Equations Obtained by SRA

Statistical Results of SRA.

Correlation Equations Obtained By MRA

Statistical Results of MRA

Data Filtration

Statistics of fine grained plastic soil data compacted to 100% MDD and

OMC in standard manner

Statistics of coarse grained plastic soil data compacted to 100% MDD and

OMC in standard manner

Statistics of coarse grained non-plastic soil data compacted to 100% MDD

and OMC in standard manner

Statistics of coarse grained plastic soil data compacted to 95% MDD and

OMC in modified manner

Statistics of coarse grained non-plastic soil data compacted to 95% MDD

and OMC in modified manner

Individual relationship between CBR and index properties of fine grained

soils compacted to 100% MDD & OMC in Standard manner

Individual relationship between CBR and index properties of coarse grained

soils compacted to 100% MDD & OMC in Standard manner

Individual relationship between CBR and index properties of coarse grained

soils compacted to 95% MDD & OMC in Modified manner

14

16

17

24

34

35

35

35

35

44

46

47

47

48

48

53

57

61

x

LIST OF FIGURES

FIG NO. TITLE PAGE

Fig.2.1 : Soil Grading Curve 6

Fig 2.2 : Soil Plasticity Stages 7

Fig 2.3: Unified Soil Classification of fine grained soils 11

Fig 2.4: Unified Soil Classification of Coarse grained soils 12

Fig 2.5: Plasticity Chart 13

Fig 2.6: Relationship between CBR and plasticity index at various liquidity index

values (Black ,1962)

21

Fig 2.7: Correction of CBR values for partial saturation (Black ,1962) 21

Fig 2.8( a): Relationship between suitability index and soaked CBR values for Ghanaian

Lateritic Soils (de Graft – Johnson et al ,1969)

22

Fig 2.8(b): Relationship between suitability index and soaked CBR values for Ghanaian

Lateritie-Quartz Gravel (de Graft – Johnson et al ,1979)

23

Fig 2.9: Correlation of CBR, Maximum Dry Density and Optimum Moisture Content

(Kin, 2006)

27

Fig 2.10 : CBR estimation proposed by Stephenson et al (1967) 31

Fig 3.1 : Flow Chart on Overall Research Methodology 37

Fig 3.2 : Hierarchical Chart of Data Grouping 39

Fig 4.1 : Variation of CBR Values compacted to 100% MDD and OMC in a Standard

Manner

45

Fig 4.2 : Variation of CBR Values compacted to 95% MDD and OMC in a Modified

Manner

45

Fig 4.3 : Gradation curve for the sieve analysis 49

Fig 4.4 : Graph for determination of liquid limit test 49

Fig 4.5 : Compaction curve for determination of MDD and OMC 50

Fig 4.6 : Graph showing load vs. penetration for determination of CBR value 50

Fig. 4.7(a): Scattered plots of individual soils parameters Vs. CBR for fine grained plastic

soils compacted to 100% MDD and OMC in standard manner (i)

51

Fig. 4.7(b):

Scattered plots of individual soils parameters Vs. CBR for fine grained plastic

soils compacted to 100% MDD and OMC in standard manner (ii)

52

Fig. 4.8(a): Scattered plots of compaction parameters Vs. CBR for coarse grained soils

compacted to 100% MDD and OMC in standard manner

54

Fig. 4.8(b):

Scattered plots of grading parameters Vs. CBR for coarse grained soils


55

xi

Fig. 4.8(c): Scattered plots of key particle sizes Vs. CBR for coarse grained soils


56

Fig. 4.8(d) Scattered plots of Atterberg Limits parameters Vs. CBR for coarse grained

soils compacted to 100% MDD and OMC in standard manner

56

Fig. 4.9(a)

Scattered plots of compaction parameters Vs. CBR for coarse grained soils

compacted to 95% MDD and OMC in modified manner

58

Fig. 4.9(b): Scattered plots of grading parameters Vs. CBR for coarse grained soils


59

Fig. 4.9(c): Scattered plots of key particle sizes Vs. CBR for coarse grained soils


60

Fig. 4.9(d): Scattered plots of Atterberg Limits parameters Vs. CBR for coarse grained

soils compacted to 95% MDD and OMC in modified manner

60

Fig 4.10(a): Comparison of de Graft – Johnson and Bhatia (1969) with Sri Lankan data 63

Fig 4.10(b): Relationship between SI & CBR for local soils 63

Fig 4.10(c): Relationship between MDD/PI & CBR for local sandy soils 64

Fig 4.11(a): Comparison of Agarwal and Ghanekar (1970) with Sri Lankan data 65

Fig 4.11(b): Comparison of Modified Correlation to Agarwal and Ghanekar (1970) 66

Fig 4.12(a): Comparison of NCHRP (2001) with local soil data 67

Fig 4.12(b): Relationship between wPI & CBR for local soils 68

Fig 4.12(c): Comparison of modified relationships between PI, P075 & CBR for local soils 69

Fig 4.13(a): Comparison of Kin(2006) with local soil data 70

Fig 4.13(b): Power relationship between the ratio of CBR/OMC vs. MDD for local soils 70

Fig 4.13(c): Linear relationship between the ratio of CBR/OMC vs. MDD for local soils 71

Fig 4.14(a): Comparison Graph of Vinod and Cletus (2008) with local plastic soils 72

Fig 4.14(b): Relationship between WLM and CBR for local plastic soils 72

Fig 4.14(c): Modified Relationship between WLM and CBR for plastic soils compacted to

95% MDD & OMC in Modified Manner

73

Fig 4.15: Comparison of Roy et el (2009) with local soil data 74

Fig 4.16(a): Comparison of Ayodele et al (2009) for soils compacted to 100% MDD &

OMC in a Standard Manner

76

Fig 4.16(b):

Comparison of Ayodele et al (2009) for soils compacted to 95% MDD &

OMC in a Modified Manner with Sri Lankan data

76

Fig 4.17(a): Comparison of Patel and Desai ( 2010) for local plastic soils 77

Fig 4.17(b): Comparison of modified Patel and Desai (2010) for local plastic soils 78

xii

Fig 4.18(a): Comparison of South African Railways (1970) with Sri Lankan data 79

Fig 4.18(b): Relationship between If and CBR for coarse grained soils compacted to 95%

MDD and OMC using Mod. Effort

80

Fig 4.18(c): Comparison of new regression correlation between CBR and LL, PL and P075 80

Fig 4.19(a): Comparison of Sood et al. (1978) and Dhir et al(1987) with Sri Lankan data 81

Fig 4.19(b): Comparison of modified correlation to Sood et al. (1978) and Dhir et al(1987) 82

Fig 4.20(a):

Comparison of Haupt(1980) for plastic soils compacted to 100% MDD &

OMC in a Standard Manner

83

Fig 4.20(b):

Comparison of Haupt (1980) for plastic soils compacted to 95% MDD &

OMC in a Modified Manner

84

Fig 4.21(a): Comparison of Agarawal et al (2011) Eq. 2.28 with local plastic soils 87

Fig 4.21(b): Comparison of Agarawal et al (2011) Eq. 2.29 with local plastic soils 87

Fig 4.21(c): Comparison of Agarawal et al (2011) Eq. 2.30 with local plastic soils 87

Fig 4.21(d): Comparison of Agarawal et al (2011) Eq. 2.31 with local plastic soils 88

Fig 4.21(e): Comparison of Agarawal et al (2011) Eq. 2.32 with local plastic soils 88

Fig 4.22(a): Comparison of Agarawal et al (2011) Eq.2.33 with local plastic soils 89

Fig 4.22(b): Comparison of Agarawal et al (2011) Eq.2.34 with local plastic soils 89

Fig 4.22(c): Comparison of Agarawal et al (2011) Eq.2.35 with local plastic soils 89

Fig 4.22(d): Comparison of Agarawal et al (2011) Eq.2.36 with local plastic soils 90

Fig 4.22(e): Comparison of Agarawal et al (2011) Eq.2.37 with local plastic soils 90

Fig 4.22(f):

Comparison of modified Agarawal et al (2011) Eq.2.35 for plastic soils

compacted to 95% MDD and OMC in a modified manner

92

Fig 4.23 :

Comparison of developed empirical correlation for non-plastic coarse grained

soils compacted to 100% MDD and OMC in a standard manner

95

Fig 4.24 :

Comparison of developed empirical correlation for non-plastic coarse grained

soils compacted to 95% MDD and OMC in a modified manner

97

Fig 4.25 :

Comparison of developed empirical correlation for plastic fine grained soils

compacted to 100% MDD and OMC in a standard manner

98

Fig 4.26 : Comparison of developed empirical correlation for plastic fine grained soils of

CBR below 20% compacted to 100% MDD and OMC in a standard manner

99

Fig 4.27 : Comparison of developed empirical correlation for plastic coarse grained soils

compacted to 100% MDD and OMC in a standard manner

100

Fig 4.28(a): Comparison of developed empirical correlation for SC soils compacted to

100% MDD and OMC in a standard manner

103

xiii

Fig 4.28(b): Comparison of developed empirical correlation for SC soils with CBR below

25% compacted to 100% MDD and OMC in a standard manner

104

Fig 4.29 : Comparison of developed empirical correlation for plastic coarse grained soils


105

Fig 4.30: Comparison of developed empirical correlation for ‘SC’ and ‘SM-SC’ soils


107

Fig 4.31 : Verification of developed new correlation - Eq.4.39 109

Fig 4.32 : Verification of developed new correlation - Eq.4.47 110

Fig 4.33 : Verification of developed new correlation -Eq.4.46 110

LIST OF APPENDICES

Appendix 1 - Summary of Compiled Data for Model Derivation

Appendix 2 - Summary of Tests Performed for Model Verification

xiv

LIST OF ABBREVIATIONS AND SYMBOLS

CBR - California Bearing Ratio

CBRTOP

- CBR value at top face of soil sample

CBRBOTTOM

- CBR value at bottom face of soil sample

DCP - Dynamic Cone Penetrometer

D60

- Diameter at 60% passing from grain size distribution (mm)

D50


D30


D10


LL - Liquid Limit

PL - Plastic Limit

PI - Plasticity Index

MDD - Maximum Dry Density

OMC - Optimum Moisture Content

SI - Suitability Index

γd max - Maximum Dry Density

γw - Density of Water

f - Fines Content (%)

MC - Moisture Content

SRA - Simple Regression Analysis

MRA - Multiple Regression Analysis

C - Fraction coarser than 0.425 mm sieve

WLM - Modified Liquid Limit, equal to LL(1 - C/100)

A - % retain on 2.4mm sieve

USCS - Unified Soil Classification System

Cu - Coefficient of Uniformity

Cc - Coefficient of Curvature

P 425 - % Passing 0.425mm sieve

R 425 - % retain on 0.425mm BS sieve

P2360 - % Passing 2.4mm sieve

R2360 - % retain on 2.36mm sieve

P075 - % Passing 0.075 mm sieve

ASTM - American Society for Testing and Materials

BS - British Standards

AASHTO - American Association of State Highway and Transportation Officials

ANOVA - Analysis of Variance

development of empirical correlations between …

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