PERFORMANCE STUDY OF FLEXIBLE

PAVEMENTS: A SAMPLE STUDY

Ritesh.P

Department of Civil Engineering

National Institute of Technology Rourkela

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PERFORMANCE STUDY OF FLEXIBLE
PAVEMENTS: A SAMPLE STUDY
Thesis submitted in partial fulfillment of

the requirements of the degree of

Masters of Technology
in

Department of Civil Engineering

by

Ritesh.P
(Roll Number: 711CE3104)

based on research carried out under

the supervision of

Prof. Mahabir Panda

May, 2016

Department of Civil Engineering

National Institute of Technology Rourkela

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 DepartmentofCivilEngineering
NationalInstituteofTechnologyRourkela
May 31, 2016

Certificate of Examination
Roll Number: 711CE3104
Name: Ritesh.P
Title of Dissertation: PERFORMANCE STUDY OF FLEXIBLE PAVEMENTS:A SAMPLE
STUDY

We the below signed, after checking the dissertation mentioned above and the official record
book (s) of the student, hereby state our approval of the dissertation submitted in partial
fulfilment of the requirements of the degree of Doctor of Philosophy in Department of Civil
Engineeringat National Institute of Technology Rourkela. We are satisfied with the volume,
quality, correctness, and originality of the work.

_____________________________
Prof. Mahabir Panda
Principal Supervisor

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 DepartmentofCivilEngineering
NationalInstituteofTechnologyRourkela

Prof. Mahabir Panda

Professor

May 31, 2016

Supervisor’s Certificate

This is to certify that the work presented in the dissertation entitled PERFORMANCE
STUDY OF FLEXIBLE PAVEMENTS: A SAMPLE STUDYsubmitted by Ritesh.P, Roll
Number 711CE3104, is a record of original research carried out by him under my
supervision and guidance in partial fulfilment of the requirements of the degree of Masters
of Technology in Department of Civil Engineering. Neither this thesis nor any part of it has
been submitted earlier for any degree or diploma to any institute or university in India or
abroad.

Prof. Mahabir Panda

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 Dedication
This Thesis is dedicated to my beloved parents

Ritesh.P

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 Declaration of Originality
I, Ritesh.P, Roll Number 711CE3104hereby declare that this dissertation
entitledPERFORMANCE STUDY OF FLEXIBLE PAVEMENTS: A SAMPLE STUDY
presents my original work carried out as a postgraduate student of NIT Rourkela and, to the
best of my knowledge, contains no material previously published or written by another
person, nor any material presented by me for the award of any degree or diploma of NIT
Rourkela or any other institution. Any contribution made to this research by others, with
whom I have worked at NIT Rourkela or elsewhere, is explicitly acknowledged in the
dissertation. Works of other authors cited in this dissertation have been duly acknowledged
under the sections “Reference” or “Bibliography”. I have also submitted my original research
records to the scrutiny committee for evaluation of my dissertation.
I am fully aware that in case of any non-compliance detected in future, the Senate of NIT
Rourkela may withdraw the degree awarded to me on the basis of the present dissertation.

MAY 31, 2016

Ritesh.P NIT
Rourkela

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 Acknowledgments

First of all, I would like to express my sincere gratitude and respect to my project supervisor
Prof. Mahabir Panda, Professor, department of civil engineering for his encouragement,
valuable suggestions and support for successful completion of my project work. This thesis
would not have been possible without his thorough guidance thorough out my study.

I am grateful to Prof. P.K Bhuyan, department of civil engineering and Prof.UjjalChattaraj,

department of civil engineering for providing suggestions and advices throughout my course
work. I am also thankful to Prof. S.K. Sahoo, HOD of civil engineering for providing
necessary facilities required for my project work.

I am also thankful to all of my friends, my well-wishers who helped me to explore myself and
extendedtheirsupport during my course work. I am also grateful to my mentors (Ph. D
scholars) for their suggestions and immense support all along my thesis work.

I am also thankful to my mother and father who have encouraged mefrom time to time in all
aspects of my life.

May 31, 2016 Ritesh.P

NIT Rourkela Roll Number: 711CE3104

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 Abstract
Pavements are major assets of highway infrastructure. In India, mostly the flexible pavements
deteriorate faster than expected design life. Hence, there is a great need for pavement
performance study. In this thesis, an attempt is made to study performance on pavements on
sample basis. Performance indicators considered are International Roughness Index,
Structural Number, traffic in terms of Equivalent single axle loads, Pavement Condition
Index, and Characteristic deflection from Benkelman Beam test. In total, four sections are
chosen to study the pavement performances. At first, merlin equations are calibrated and
validated with respect to auto-level for calculating IRI, and then structural number is obtained
with respect to layer coefficients and corresponding thicknesses of pavement layers.
Rebound deflection is calculated from Benkelman. Traffic is calculated for three days and
based on this; ESAL is obtained at all sections. Visual observations with simple
measurements have been done to study pavement surface conditions to assess Pavement
Condition Indices of corresponding sections at a particular point of time. Finally simple
modelling has been done to relate functional performance with structural performance of
sample pavement sections considered.

Keywords: Performance, International Roughness Index, Structural Number, Pavement

Condition Indices. Characteristic deflection

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 Contents
CERTIFICATE OF EXAMINATION 3
SUPERVISOR’S CERTIFICATE 4
DEDICATION 5
DECLARATION OF ORIGINALITY 6
ACKNOWLEDGMENTS 7
ABSTRACT 8
CHAPTER 1: INTRODUCTION 11
1. 1 GENERAL 11
1. 2NEED FOR THE STUDY 14
1. 3 OBJECTIVES OF THE STUDY 14
1. 4 SCOPE OF THE STUDY 14
CHAPTER 2: LITERATURE REVIEW 16
2. 1 GENERAL 16
2. 2 DETERIORATION MECHANISM OF FLEXIBLE PAVEMENTS 16
2. 3 PERFORMANCE EVALUATION OF PAVEMENTS 17
2. 4 PAVEMENT PERFORMANCE MODELS SCENARIO 18
2.5 CRITICAL REVIEW OF LITERATURE AND MOTIVATION FOR RESEARCH 21
CHAPTER 3: EMPIRICAL OBSERVATIONS: DATA COLLECTION 22
3.1 FIELD DATA COLLECTION AND LABORATORY INVESTIGATIONS 22
3. 1. 1 INVENTORY DETAILS OF STUDY SECTIONS 22
3. 2 ROUGHNESS SURVEY 23
3. 2. 1 ROUGHNESS MEASURING INSTRUMENT 23
3. 2. 2 THE MERLIN 24
3. 2. 3 METHOD OF USE 25
3. 2. 4 CALIBRATION EQUATIONS 25
3.3 AUTO-LEVEL (ROD AND LEVEL SURVEY) 26
3.3.1 GENERAL DESCRIPTION 26
3.3.2 METHOD OF USE 27
3. 4 BENKELMAN BEAM STUDIES 28
3. 4. 1 BENKELMAN BEAM 28
3. 4. 2METHOD OF USE. 29
3. 5 STRUCTURAL NUMBER 32
3. 6 PAVEMENT SURFACE CONDITION 34
3. 6. 1 METHOD OF USE 35
FIGURE 13: DEDUCTION CURVE FOR PATCHING (ASTM, 2008) 37
FIGURE 14: CORRECTED DEDUCT VALUE CURVE.(ASTM, 2008) 37
3. 7 CALIFORNIA BEARING RATIO 37
3. 8 OPTIMUM MOISTURE CONTENT 38
3. 9 LIQUID AND PLASTIC LIMIT TEST 39
CHAPTER 4: ANALYSIS OF DATA, RESULTS AND DISCUSSIONS 40
4. 1 MERLIN 40
4. 2 BENKELMAN BEAM RESULTS 40

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 4. 3 TRAFFIC DATA CALCULATION 41
4. 4 STRUCTURAL NUMBER 41
4. 5 PAVEMENT CONDITION INDEX 41
4.6 PAVEMENT PERFORMANCE MODELLING 41
4.6.1 RELATIONSHIP BETWEEN IRI, STRUCTURAL NUMBER AND ESAL. 42
4. 6. 3. RELATIONSHIP BETWEEN DEFLECTION, IRI AND ESAL. 42
CHAPTER 5: SUMMARY AND CONCLUSIONS 43
5.2 FUTURE SCOPE 43
REFERENCES: 44

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Chapter 1: Introduction

1. 1 GENERAL

Road infrastructure is one of the transport infrastructures that play a prominent role in
improving any area accessibility and movement of population as it provides door to door
service. The road network in India accounts world’s second largest which is widely spread
across 30 states of the country. The road network has increased to 4.82 million km
(considering all type of roads) from 2 million km that was in 1990s. It is observed that
annually billions of rupees are lost to economy due to constraints of road quality and its
capacity. Developing countries like India is now facing a challenge of preserving and
enhancing transportation system infrastructure, so there is a need of planning and
maintenance strategies.
In India mostly there are two types of pavement (i) Flexible pavement and (ii) Rigid
pavement. This study limits only to flexible pavements. As, the funding available for
pavement periodic maintenance and its management system is limited, there is great need for
optimum and efficient maintenance and management of road network. Normally, flexible
pavements are designed for 15-20 years but because of increase in traffic intensity, repetition
of load, durability of various pavement conditions, unpredictable environmental factors,
improper construction practices, lack of good quality materials, high tyre pressure, drainage,
increase in axle loads, etc., flexible or bituminous pavements are showing early signs of
distresses. This reduces performance of pavements. Hence there is a need to study the
performance of flexible pavements.
The ability of road to serve traffic demands and change in environment parameters
over its design life is called Performance and premature changes in performance indicators
like distresses, roughness, etc. is called deterioration.
As Pavements deteriorates faster than its design life, there is a need for developing
performance models so as to predict future condition of pavement. This predicted
deterioration models play a major role both in project and network level. The overall facilities
can be planned for estimating budget and materials with the help of these models.
Transportation policies and proper scheduling of traffic, proper economic use of materials
can be developed if there is accurate deterioration model. By performance parameters, we can
interlink a dependency on infrastructure facility and traffic users like for example, we can

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impose a limitation on axle loads which is one of the sole causes of damage to pavement.
These models help the pavement when it should get overlay so that the pavement can be free
from further damage.
Pavement performance indicators considered in this study are International
Roughness Index, Benkelman beam deflection, traffic, different distress studies, Structural
number of pavement. Hence, both structural and functional evaluation of pavements is
considered in this study.
` Roughness is the main parameter considered for functional evaluation of pavements.
It is termed as unevenness of road surface along longitudinal direction or along direction of
traffic. It covers road quality and vehicle operating cost. Its value gives an indication how
much the road has deteriorated with respect to ride comfort. It is measured in terms of IRI
which has SI unit of m/km. The higher the value the more discomfort, the road causes to
passengers. In our study, roughness is calculated by merlin and has been validated with
respect to readings taken from auto-level. Here, merlin equations for IRI based on auto-level
are developed for both D>42 and D<42. Calibration equations are not provided for D less
than 42. Here, in this study, the sections which are chosen to study the pavement
performance, exhibited values of D <42. Attempt was made to obtain equation for lesser
values of D, like choosing such sections at NIT Rourkela where roads have lesser D and
thereafter at these sections, to find IRI, auto-level is used. Finally, calibrating both these
values an equation is developed for D<42.
The main parameter that takes into account for structural strength of pavements is
deflection of pavement which is determined by Benkelman beam in this study. The pavement
which experiences continuously moving traffic will undergo some deformation at each wheel
load application. When load is removed, it exhibits elastic recovery called rebound
deflection. Repeated deflection may cause excessive flexural stresses induced which may
result in permanent plastic deformation thereafter making pavement prone to fatigue or
alligator cracking. Based on this characteristic deflection value, thickness of overlays can be
determined provided there is traffic data. The primary purpose of calculating the deflection
of an existing pavement is to obtain stress-strain properties of a pavement structure. That
means the deflection should have an upper limit so that pavement can perform well. This
deflection value is so important because many pavement design methods are based on
serviceability-deflection criteria. In this study, modelling is done on prediction of pavement
characteristic deflection considering as a function of IRI, traffic, and structural number.
Benkelman beam deflection is calculated using IRC 81-1977.

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 The most important parameter considering pavement performance is pavement
distress. There are different types of distresses like cracking (longitudinal, transverse, fatigue,
edge, reflective, block), deformation (corrugation, rutting, depression, shoving, bumps),
deterioration (delamination, potholes, patching, ravelling, stripping), mat problem
(segregation and bleeding) and problems in seal coats. Based on the amount of severity
present at each distress, ASTM D 6433 considers different graphs for different distresses to
calculate deduct values for obtaining Pavement Condition Index. This ranges from 0 to 100
where 0 represents weakest pavement and 100 as strongest pavement. These amounts of
severities are calculated by field survey. PCI is calculated using ASTM D 6433. In this study,
four sections are chosen to calculate pavement condition index. Effort is made to check how
this value is changing over time. Due to lack of time, in total at a section two readings are
taken by giving a gap of six months.
Structural number indicates strength of the pavement layers and of the total structure
of pavement. This is derived by adding each layer coefficient multiplied by layer thickness.
In order to determine layer coefficients, CBR of different courses of pavement are calculated
so that they can be interpolated by AASHTO method. Drainage coefficients depends on
quality of drainage facility and per cent of time in the year the pavement would normally be
exposed to moisture levels that causes saturation (depends on average rainfall and prevailing
drainage conditions at site) Tables are given to calculate the coefficients. Modified structural
number is calculated using CBR value of subgrade. Structural number helps to determine no
of equivalent single axle loads the pavement can take. Here, in this study modelling is done to
correlate modified structural number as a function of pavement characteristic deflection
obtained by non-destructive method i. e Benkelman-beam method.
Traffic varies from season to season, year to year which in turn finds difficulty in
predicting. Because of in reliability of traffic prediction, the pavement performance goes
down. In this study, traffic is calculated for 3 days at the time of field observations that took
place. It is assumed a growth percentage of 7.5% for all mixed traffic. This traffic is used to
calculate Equivalent single Axle loads. Finally, this value is used in modelling of some
pavement sections.
In-situ tests like sand replacement method, Benkelman beam test are conducted.
Pavement temperature is calculated using glycerol and thermometer. Samples of different
layers are taken from trial pits so as to calculate pavement layer thicknesses and make tests in
the laboratory. Different tests include modified proctor test, California Bearing Ratio test,
liquid limit, plastic limit, grading, etc.

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1. 2NEED FOR THE STUDY

The roads of the country are showing early signs of distress after each monsoon. This
is leading to heavy loss on maintenance and also resulting in poor riding quality, prone to
accident, and speed reduction. The factors causing deterioration of roads are so complex to
understand and they vary from one place to another. Hence, there is a need to study the
different pavement performance indicators like roughness, traffic, deflection, etc. mechanism
on a regular basis, say for six months. In this study, readings are taken only two times at a
section.

1. 3 OBJECTIVES OF THE STUDY

The main objectives of this study are the following:

i. To collect data on the performance of roads including the road inventory data.
ii. To conduct traffic volume study and study axle load pattern.
iii. To conduct functional and structural evaluation of the pavement sections in
respect of sustainability of the concerned pavements.
iv. Evaluation of structural number of pavements.
v. To establish relationships of pavement deterioration with traffic growth with due
consideration of independent variables/parameters.

1. 4 SCOPE OF THE STUDY

The scope of works covers the following:

i. Selection of pavement sections under different traffic, different pavement

thickness and pavement crust conditions including up gradation ones.
ii. Collection of road inventory data of selected pavement sections.
iii. Collecting performance data in respect of identified parameters.
iv. Analysis of collected data and development of models to predict the performance
of road pavements to establish sustainability.

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First chapter gives introduction to the current topic i.e. Performance study of flexible
pavements.

Second Chapter gives the previous work done on the empirical studies and literature
review on pavement performance parameters.

Third chapter comprises of several experiments conducted in several locations.

Experiments are done to study the properties of pavement performance indicators.

Fourth chapter gives the results obtained from laboratory studies. These results include
modelling done on different pavement performance parameters.

Fifth Chapter gives the summary and conclusions of the work done.

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Chapter 2: Literature review

2. 1 GENERAL

Pavement performance is change in its state with respect to as it was at the time of
construction. It gives an idea whether the pavement is able to carry traffic and satisfy
according to environmental conditions during its design life. The road network is getting
overstressed as a result of gradual increase in traffic. This results in performance failure. If it
fails to carry the design loads, then it is structural type and it is a functional type if it doesn’t
provide a smooth riding surface. This uneven surface not only cause discomfort to traffic but
also increases operating cost of vehicles. (Thube et al. 2008)

2. 2 DETERIORATION MECHANISM OF FLEXIBLE PAVEMENTS

The repeated effects of vehicular loads, different characteristics of traffic and its
composition with its loading, traffic volume, change in environmental and surrounding
conditions, some maintenance related activities with time changes both structural and
functional capacity of pavement. So, the main cause of pavement failure is combination of
environment with unpredicted value of traffic with unreliability of loading. Accumulation of
cracking or distresses is called deterioration and it is termed as failure when it can’t serve any
further traffic. Deterioration patterns show the same trend irrespective of place. The factors
that cause failure to the pavements include cracking like alligator, longitudinal, transverse,
block; rutting along wheel paths and roughness along longitudinal profile. These are also
termed as distresses of flexible pavements. The amount of distress gives a value or an
indication to the overall pavement condition. Different distress modes occur independently
and so the models which we have to plan should be based on whether it is of load type or
non-load type. (Gedafa D S, 2007)

Many factors that cause pavement deterioration are interlinked to each other. So, the factors
responsible for this deterioration can be shown as follows:

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 Figure 1: Factors influencing Pavement Performance (Gedafa D S, 2007)

2. 3 PERFORMANCE EVALUATION OF PAVEMENTS

It is necessary to find out how pavements and its materials response under repeated axle
loads of traffic in order to have more durable pavements in future. It has been observed that
deterioration of pavements is minimal during initial stage after construction like 2-3 years
and this progress at a larger rate during its late years. For performance evaluation the first
task is to identify different factors that cause damage. The main factors that many researchers
adopted are pavement strength (structural number), traffic loading, environmental conditions,
and subgrade support. Mainly evaluation is carried out using three criteria (i) Roughness of
pavements (ii) Pavement distress or surface condition of pavements (iii) Pavement deflection,
here in our study deflection is carried out by Benkelman beam test. Many researchers termed
different terms to describe pavement condition. (Thube et al.2005)

i. Present Serviceability Index: It is an index where it ranges from 0 to 5, 0 being

the weak pavement and 5 being the strongest. Its value is given by set of panel
members where they consider all the parameters. It can also be calculated using
slope variance and amount of cracking and patching done in pavements.

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 ii. Present Serviceability: This is a term that is used to describe whether pavement is
able to cope with present traffic and environment.
iii. Performance Index: It gives the summary of PSI that changes over a period of
time and so it is represented as area under PSI versus time curve.
iv. Pavement Condition Index: It ranges from 0 to 100. 100 being rhe best and 0
worst. It is calculated using ASTM D 6433. This value is found from deduction
curves which in turn depend on amount of severity of distresses present.(AASHO,
1993)

2. 4 Pavement performance models Scenario

Yoder (1966) stated that pavement deflection which occurs due to many factors; is
one of the main cause which effects pavement performance. He stated permissible deflection
varies with stiffness of pavement and with difference in pavement materials. He has also
calculated pavement stresses and strains under controlled loading conditions by assuming
viscoelastic behaviour of pavements.

Collop and Cebon(1995) reported a whole-life performance model (WLPPM).

Thismodel is capable of making deterministic pavement damage predictions resulting
fromrealistic traffic and environmental loading. Realistic predictions of pavement
degradationwith traffic has been obtained by taking into account most of the primary factors
ofvehicle/pavement interaction. Simulation by WLPPM shows that short- wave
lengthsurface – roughness components can be smoothed out, and traffic loading increases
theamplitude of long wave length components.

Sebaaly et al. (1996) developed a pavement performance model for bituminous

concrete overlays at Nevada. The aim is to predict pavement behaviour under combined
influence of environment and traffic. The performance index taken here is Present
Serviceability Index for long term pavement performance.

Fujiezhouet al. (2002) developed, calibrated, and validated pavement performance

prediction models for the Texas mechanistic-empirical flexible pavement design system. This
report proposed many models for crack initiation and propagation for different distresses.
VESYS rutting model was recommended for predicting flexible pavement layer rutting where
its validation of field data is done by repeated load test. McGhee (2002) developed and

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implemented Pavement Condition Index for Virginia department of transportation. ItIncluded
indices to describe load and non-load related distresses and pavement longitudinal and cross-
slope information including rutting and ride quality. Pavement types to be included in index
development were flexible (asphalt), rigid (concrete), and composite (a combination of
asphalt and concrete).

Chai (2000) conducted preliminary optimization of HDM-4 at North South

Expressway in Malaysia for studying parameters that effect pavement performance. He found
that the factors which effect the deterioration are roughness, age and environmental data. He
has not chosen material properties of pavement.

Bose et al. (2005) conducted studies on distresses that occur prematurely and also
failure of bituminous pavements. After five case studies which he has taken, it is reported that
cause is due to improper sub surface drainage and aggregate getting stripped. Later Mariaa et
al. (2005) in the same year studied the effect of bond that effect performance of flexible
pavements. It was concludes that life of the pavement gets reduced by 80% if there is a poor
bond between base and binder course. Aggarwal et al. (2005) has given an overall picture of
the problems of road networks in developing countries, which are rapid traffic growth,
inadequate funding for maintenance and upkeep, lack of skilled man power, attitude towards
maintenance etc. Thube et al.(2005) critically reviewed the maintenance management
strategy for low volume roads in India and stressed the need for development of pavement
distress data base, deteriorationmodels, optimal investment and maintenance strategy and
highlighted the need for a suitable national level policy regarding paving of unpaved low
volume roads in India. Reddy et al. (2005) developed flexible pavement preservation
framework for an integrated asset management. In this study methodology integrates
pavement condition data management, pavement performance and its standards to generate
pavement preservation program. Riding Comfort Index (RCI) has been established to
determine the preservation needs. Various maintenance management tools were derived as
part of this study

Masad et al. (2006) reported a study to compare effect of wheel loads to deflection of
pavements that occur at surface. He has done by finite element method considering isotropic
and later it was found that tensile stresses which got induced at lower regions of bituminous
layer are higher than those predicted. So the pavement can’t be treated as isotropic while
doing analysis. Salama et al. (2006) studied relative damaging effect of different type or

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configuration of truck traffic. Studies on different distresses are done like both crack
initiations and propagations. It was shown that multiple axles create more damage compared
to single and tandem axles. Bayomy et al. (2006) analysed long-term pavement performance
for the Idaho general pavement sections and specific pavement sections. The research
investigated into the use of the data to develop models that enable the prediction of the
seasonal variation effects on the pavement materials (soils and asphalt mixes). Models were
developed based on analysis of national data for the subgrade and asphalt concrete moduli.

Mathew et al. (2008) developed deterioration models for ravelling initiation and
progression, pothole progression, roughness progression and edge failure using neural
network and regression techniques. The ANN models were compared and found to be more
suitable to the rural roads as compared with the conventional empirical statistical models.

Gedafa et al. (2010) presented a methodology for the estimation of flexible

pavementsremaining service life by using the surface deflection data. Models were
developed usingnonlinear regression procedure in the Statistical Analysis Software and
Solver inMicrosoft Excel. This study reported a sigmoidal relationship between remaining
servicelife and central deflection. Kumar et al. (2010) developed deterioration prediction
models for deflection androughness of 17 road sections in Uttarakhand, using Artificial
Neural Network (ANN) and linear regression. Pavement Serviceability Rating (PSR) and
Riding Comfort Index (RCI) were worked out based on visual inspections of the test sections.

Sreedevi et al.(2011) conducted Field performance indicators for NRMB in a tropical

setting. Pavement performance indicators for road sections constructed using Natural Rubber
Modified Bitumen and Ordinary bitumen operating under identical conditions has been
derived from periodic field data collection and analysis. Study on decision support system
for performance based maintenance management of highway pavements was done by
Muralikrishna and Veeraragavan (2011). Deterioration models were developed for deflection
progression and roughness progression. One set of data was used for the validation process,
done by chi-square test. Markussvensson et al. (2011) has modelled pavement performance
prediction, based on rutting and cracking data. The aim of this project is to develop prediction
models for flexible pavement structures for initiation and propagation of fatigue cracks in the
bound layers, and rutting for the whole structure. A statistical approach has been used for the
modelling where both cracking and rutting are related to traffic data, climate conditions, the
subgrade characteristics as well as the pavement structure.

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 Subagio et al. (2013) has conducted a case study on structural and functional
performance in Indonesia. The research evaluates the Structural and Functional performance
of National Road (PANTURA) located in the North Java’s Corridor. Two methods were
used in this evaluation, BinaMarga’s (CASE STUDY section of Jalan Kaliurang,
MALANG)method and the AASHTO-93 method. The BinaMarga’s (Pavement condition
value ranges from 0 to 7)method focused on the evaluation of the Functional Performance,
while the AASHTO-93 method was used to analyse the Structural Condition. Some
parameters considered are: IRI, PSI while in the Structural analysis the SN (Structural
Number) was used.
Harold (2014) considered structural factors of flexible pavements for initial evaluation
of the sps-1 experiment. This project relates structural property of pavement with materials
used in pavement construction. Different tests were conducted on subgrade, unbound
granular base, asphalt treated base, asphaltsurface, etc. so as to account for the correct reason
for deterioration of pavement. It also discusses different methodologies to analyse field data.

2.5 CRITICAL REVIEW OF LITERATURE AND MOTIVATION FOR RESEARCH

The factors that are mostly responsible for deterioration of pavements are vehicular
loading, traffic, drainage, environmental factors, adhesive property of bitumen, etc. Different
studies have used different indices to calculate pavement conditions like RCI, PSI, PCI, PSR,
etc. For pavements to perform satisfactorily, it is necessarily important to satisfy functional
and structural conditions. Functional analysis includes IRI whereas structural analysis
includes rebound deflection.

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Chapter 3: Empirical Observations: Data Collection

In this chapter, a detailed explanation of several experiments that are conducted both
on field and laboratory are given. In this study, a total of 4 sections are chosen in such a way
that they differ each from intensity of traffic, pavement material composition, different
terrain, etc. Models are developed based on these sections details and are shown in chapter 4.

3.1 Field Data Collection and Laboratory Investigations

Data collection has ranged from visual observations to the use of 8.16KN axle load
truck to measure surface deflection, unevenness by merlin, field density by sand replacement
method, distress studies, traffic flow with axle load surveys, and laboratory tests like
compaction, CBR, Gradation, etc.

The data include:

i. Inventory of study sections.

ii. Pavement shoulder condition.
iii. Pavement distress studies or surface deflection.
iv. Unevenness of pavement using MERLIN.
v. Characteristic deflection using Benkelman beam as per IRC 81, 1997.
vi. Traffic studies for 3 days.
vii. Pavement layer composition from in-situ trial pits and sample is obtained for
further study of its properties.
viii. In-situ density of sub-base and base course by sand replacement method.
ix. Laboratory investigation on subgrade, sub-base, base properties which mainly
include CBR.

3. 1. 1 Inventory details of Study Sections

i. Four sections were chosen from sites close to Rourkela. Length of each section is
chosen as 500m.
Details of sections are not presented here for publication purposes.

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 Figure 2: Trial pit and Sand replacement method in progress.
ii. Rainfall data: Average rainfall data in these sections from previous year studies
have rainfall less than 1300mm. This information will be helpful both for surface
drainage characteristics and also for finding characteristic deflection.
iii. Temperature: Field temperature is calculated using glycerol and thermometer.
iv. Shoulder condition is checked whether it is good or not.

Details of traffic data are not presented here for publication purposes.

3. 2 Roughness Survey

Roughness gives an idea about functional performance of pavement. Roughness is

expressed in terms of convenient index that gives comfort to traffic user while accessing
roads of any given profile while travelling. Both surface distresses and profile have influence
on ride comfort. There are many indices to measure roughness like Bump Integrator value,
MERLIN index, Unevenness Index, International Roughness Index. The standard index
followed across world for determining roughness is IRI. This IRI can be calibrated for
different instruments. (IRC, SP 16)

3. 2. 1 Roughness Measuring Instrument

There are different experimental setups to use roughness. They include Rod and level
Survey, Dipstick Profiler, Profilo-graphs, Response type road roughness meters, MERLIN,
fifth wheel Bump indicator (Indian practice), Profiling devices, etc. (Internet Source)

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Here, in this study roughness is measured by both merlin and auto-level (rod and level
survey).

3. 2. 2 THE MERLIN

It is an instrument that is developed to measure longitudinal road profile. The readings

are taken graphically. With less estimation in error, merlin roughness index can be converted
into IRI. It is widely used because of its simplicity, easy to work and handle. It is not suitable
for calculating roughness at long stretches as it is slow and manually done.

The device is called MERLIN-Machine for Evaluating Roughness using Low-cost

instrumentation. (TRL Report 229, 1996)

Figure 3: The MERLIN (Kumar et al. 2008)

Merlin consists of front and rear legs where it can rest on pavement surface along with probe
at half the midway. The device is 1.8m separated. With reference to imaginary line between
front and rear foot, the position of probe which can be above or below the line and this gives
mid-chord deviation. The probe goes up or down relative to the imaginary line joining front
and rear foot. The probe moves because of counter weight located at same side and at the end
of probe there is a hinge where it connects with moving arm. A moving arm has a pointer that
is attached to chart. For each position, we have to mark a cross in chart provides where the
arm points. The pointer movement depends on mid chord deviation exhibited by probe.(TRL
Report 229, 1996)

24
 Figure 4: MERLIN Readings at site

3. 2. 3 Method of use

Initially, before starting the experiment all the front feet, rear feet and probe is
levelled to same level. The level of probe is adjusted using turnscrew. Place Merlin chart at
plank available at top and mark the mid position of chart. Now the pointer of moving arm
should point the midpoint of chart. As, the circumference of front wheel is 2.25m so readings
are taken at every multiple intervals of 2. 25m. In total, 200 readings are to be taken so as to
cover 450m. At each point, the position of pointer with a cross in a suitable section is carried
out by administrator. For further system of estimations, the merlin’s handle is rolled forward
and heading towards and rehashed. To have a note on number of cross done till yet, there is a
tally box provided at extreme left corner. The chart is removed after 200 observations. The
distribution of marks or cross on chart gives roughness on road. Depending on movement of
pints, the graph is scattered. We now consider 90% of the points in the chart that means
eliminating 5% points on both top and bottom side

3. 2. 4 CALIBRATION EQUATIONS

The IRI scale and the Merlin scale are related by the following equation for all type of
pavement surface:

IRI (in m/km) =0. 593+0. 0471D, 42 > D > 312 (2. 4> IRI > 15. 9)

25
D=roughness in Merlin scale measured in mm(TRL Report 229, 1996)

3.3 AUTO-LEVEL (ROD AND LEVEL SURVEY)

Roughness measured by this method is very accurate. This method is generally

preferred when survey stretch is small. Auto-level is an automatic operated optical instrument
that helps in establishing or checking any point in horizontal planes. It is used as it involves
only two people, one to focus the auto-level and other to hold the staff. These levels set up
quickly as so it become easy to operate. (FHWA, 2008)

Figure 5: Auto- level.(Punmia, 2012)

3.3.1 General Description

It consists of tripod, auto level and staff to take readings. After setting up the
instrument, the height of any station is found after knowing the height of collimation or
instrument height by measuring the plane with the help of staff. Height of instrument is
obtained by choosing a reference point called bench mark. The levelling head consists of 3
parts (i) A tribach or top plate that carries spirit level, (ii) Foot screws, (iii) Trivet or foot
plate that is attached with tripod head. (Punmia, 2012)

The steps followed before starting the experiment are as given below:

i. Attaching the instrument or auto-level to tripod.

ii. Adjusting the levelling head with the help of foot screws.

26
3.3.2 Method of use

(i) At start of the project, choose a datum/benchmark.

(ii) To get accurate results fix a scale of 1m to the staff so that readings can be taken
in millimetres.
(iii) The length of the road section to be surveyed is measured.
(iv) The auto level is set up at location in such a way that benchmark is visible. Affix
the auto-level and level it by adjusting it with levelling screws such that the
bubble comes to middle called level circle.
(v) The elevation of bench mark on its horizontal plane is determined with the help of
eyepiece. Further readings at a regular interval of 2. 25m distance should be
determined.
(vi) Level difference is calculated from previous to present point.
(vii) Slope can be calculated for each interval by slope=level difference/interval
distance.
(viii) Average slope is calculated by modulus of summation of all slopes divided by
total no. of sections. (FHWA, 2008)

The IRI (International Roughness Index) is finally determined by IRI=avg. slope*1000

(ix) If auto-level readings are taken along any gradient roads, then slope is calculated
as ( (present reading –previous reading) - (difference in level as per gradient) )
/interval length(Sayers 1996)

Figure 6: Auto-level readings at site.

27
 Here in this study, Roughness is found from MERLIN for those four sections. Later it
was found that some merlin roughness index value has a value less than 42. So, some
sections where D<42, in NIT Rourkela are chosen. At those sections both merlin and
auto-level tests are conducted. Now having D value and IRI value from auto-level, value
of IRI for D<42 are calibrated.

3. 4 Benkelman beam Studies

A. C Benkelman devised this simple deflection beam for measuring deflection at

pavement surface. This test is done by ‘IRC: 81-1997’ which has title ‘Guidelines for
Strengthening of Flexible Road Pavements using Benkelman Beam Deflection Technique’.
This study governs structural performance of pavements. Structural capacity is the amount of
traffic or equivalent axle loads the pavement before it reaches its terminal serviceability
value. It is widely used in India because of its simplicity, reliability and as it is a Non-
Destructive test. But for more accurate results, destructive tests like falling weight
deflectometer are used. (IRC, 1997)

Flexible pavements performance is more or less related to recovery or elastic

deformation that occurs under wheel loads. More the recovery, more the performance. The
elastic deflection depends upon many factors like pavement temperature at surface, quality
and thickness of different pavement courses, subgrade soil and its type, amount of
compactive effort used, drainage conditions, etc. (Yoder, 1966)

3. 4. 1 Benkelman Beam

Benkelman Beam consists of a beam that is slender in nature which is 3.66m long. It
is pivoted at a distance of 2.44m from the tip or probe. So, the beam is divided into two parts
in the ratio 2: 1. Dial gauge is attached at rear end to measure deflection under wheel load.
The whole beam should be able to enclose in a casing (or locking device) so as to secure
beam while it is shifted to new site. It consists of an adjusted supported leg at the pivot so as
to rest in the ground. The beam is levelled by using turn screws and mercury level placed at
rear part of the beam. To conduct this test a truck with suitable tyre pressure and tyre load,
glycerol and thermometer, information regarding annual rainfall, etc. is required. (IRC, 1997)

28
 Figure 7: Benkelman Beam apparatus. (NPTEL, 2013)

3. 4. 2Method of use.

i. Before starting the experiment, standard truck must have a rear axle load of
8170kg and is equally distributed on two dual tyre wheels. The tyre is inflated to a
pressure of 5. 60kg/cm2. A tolerance of +/-1% and +/-5% can be allowed for load
and pressure.
ii. The Benkelman Beam is calibrated to check whether both beam and dial gauge
are properly working or not.
iii. Initially, points are marked where readings are to be taken. In this study which
covers 500m stretch, 20 points (both left and right wheel path) are chosen having
Chainage 0, 50, 100, ………450, 475, 425, ………75, 25m respectively.
iv. The distance of measurement points in the transverse direction should be as
follow:

Table1: Distance from pavement edge where Benkelman readings should be taken.

Lane width Distance from edge of pavement

<3. 5m 0. 6m
>3. 5 m 0. 9m
For divided four lane highway 1. 5m

29
v. The truck is slowly made to move and made to stop at left wheel path initially and
it is centrally placed at first point (Chainage: 0m) so as to measure deflection.
vi. The beams is levelled using mercury level and turn screws.
vii. The tip or probe is inserted between the gaps provided by dual wheels. The tip
must touch the surface where deflection is to be measured.
viii. Reading is noted from dial gauge and this is termed as initial dial gauge reading
denoted by Do.
ix. The truck is moved slowly to a further distance of 2. 7m from that point and made
to stop. The reading which is termed as intermediate dial gauge reading (Di) is
noted through dial gauge.
x. The truck is further moved at a distance of 9m from the study point and final dial
gauge reading (Df) is noted.
xi. These three set of readings correspond to one deflection point or study point.
Further, the truck is moved to another study point (Chainage: 50m) and readings
are taken with the procedure discussed above.
xii. The temperature of the pavement is noted with the use of glycerol and
thermometer.

Figure 8: BBD survey in progress and probe location

30
 Rebound deflection (D) at any point is given by:
 If Di-Df<= 0. 025mm, D is given as 2 (Do-Df)
 Di-Df>=2. 5 divisions of dial gauge or 0. 025mm, then D is given as:
D=2 (Do-Df) + (2*k* (Di-Df)) where value of K=2. 91
xiii. Correction for pavement temperature: Correction must be made if the
pavement temperature differs from 350c. Correction is given by 0. 01 (35-T).
So, correction is positive if temperature is less than 350c and negative if
temperature is greater than 350c.
xiv. Correction for Seasonal variations: Correction for seasonal variation depends
on subgrade soil type, moisture content at field of subgrade, average rainfall in the
area. The moisture correction factors were obtained from charts provided from
IRC: 81-1997.

Figure 9: Moisture correction factors for annual rainfall<1300mm and PI<15 for
Clayey soils (IRC, 1997)

xv. Limits of deflection values are shown in table below and are as per IRC code.

Table2: limits of Benkelman Beam deflection values (IRC, 1997)

Rebound Deflection(mm) Strength of Pavement

0.5-1 Reasonably strong
1-2 Moderate
2-3 Weak
>3 Very Weak(permanent deformation)

31
 xvi. Characteristic deflection is calculated as follows:
 Mean of rebound deflections at every study point is calculated
 Standard deviation of rebound deflection is calculated.
Finally, characteristic deflection is given as,
D’= (mean + D + temp correction+2*deviation) *seasonal correction factor.

3. 5 Structural Number

Structural number which was once called “Thickness Index” was developed by
American Association of State Highway Officials (AASHO) road tests. It indicates strength
of the pavement. It is calculated as per AASHTO guide for design of pavement structures.
When strength of subgrade is also taken into account then it is termed as Modified Structural
Number (MSN). MSN depends on CBR value of subgrade as AASHO has conducted tests on
uniform subgrade soils. (AASHTO, 1993)

Pavement structural number gives an indication of layer thickness and layer materials and is
given by, SN=a1D1+a2D2m2+a3D3m3+…. (AASHTO, 1993)

Where,

a1, a2, a3. . are layer coefficients of surface, base and sub-base course

D1, D2, D3. . are respective thickness of pavement layers

m2, m3, … are drainage coefficient of drainage layers.

Determination of Layer Coefficients: This layer coefficient depends on how individual

layer contributes towards performance of pavement. So, this value is different for different
pavement materials used. AASHO has developed graphs to directly calculate layer
coefficients values provided if we know any of the following (i) CBR (ii) Resilient Modulus
(3) Reliability value of the pavement. There are different graphs for different conditions like
for cement treated bases, bituminous treated bases, unbound bases, unbound sub-bases, etc.
In this study the coefficient is found from CBR value (un-soaked) and all the sections are
unbound bases and sub-bases. Below is a sample graph that is used to find layer coefficient.
(AASHTO, 1993)

32
 Figure 10: Variation of Granular Sub-base layer coefficient(AASHTO, 1993)

Determination of drainage coefficient:

This depends on quality of drainage facility and per-cent of time in a year the pavement will
experience moisture saturation level. AASHTO guide has developed table to find this value
and is presented below:

Table 3: Recommended drainage coefficients for base and sub-base courses (AASHTO,
1993)

Percent of time pavement is approaching

Saturation
Drainage Quality <1% 1-5% 5-25% >25%
Excellent 1.4-1.35 1.35-1.3 1.2-1.2 1.2
Good 1.35-1.25 1.25-1.15 1.15-1 1
Fair 1.25-1.15 1.15-1.05 1-0.8 0.8
Poor 1.15-1.05 1.05-0.8 0.8-0.6 0.6
Very poor 1.05-0.95 0.95-0.75 0.75-0.4 0.4

33
In sections that we have taken under study, we assume drainage coefficients as 1 as it can be
assumed 5-25% time the pavement has approached saturation and good drainage quality.

Determination of Modified Structural Number:

Structural number doesn’t include strength of subgrade. In order to include subgrade strength
of various subgrade soils, a contribution in terms of CBR value of subgrade is used and so
modified structural number is given as: (AASHTO, 1993)

MSN=SN+3.51*log10 (CBRs) -0. 85*(log10CBRs)2-1. 43

Where, CBRs= California Bearing Ratio of the Subgrade.

3. 6 Pavement Surface Condition

Study of pavement surfaces helps in developing Pavement Condition Index. In this

study, for evaluation of PCI, ASTM D 6433 method is followed. PCI is an indicator of
present condition of pavement which is directly related to pavement surface operational
condition. PCI ranges from 0 to 100, 100 representing very good condition and 0 representing
worst condition. PCI value gives an idea to public work officials about current condition of
pavement and rate of deterioration of road network. Deduct value method is used to find
value of PCI.

Table4 : Maintenance intervention based on PCI(Handbook of Highway Engineers, 2001)

PCI Rating Type of Maintenance

80-100 Very Good Preventive
60-80 Good Resurfacing
40-60 Fair Overlay
20-40 Poor Strengthening
<20 Very Poor Rehabilitation

34
3. 6. 1 Method of Use

i. The pavement section under study is divided into sample units of 25m length.
ii. Surface inventory is done on each sample unit. Inventory includes noting down
severity levels (low, medium, high) of different distresses present.
iii. The density is computed after finding severity levels.
iv. As per ASTM D 6433, for each distress type and for each severity level deduction
curves are present from where deduct value is obtained. Distress density is the
amount of distress present divided by sample unit area taken for bituminous
pavement. Deduct values have a range from 0 to 100.
v. The individual deduct values are added to get Total deduct value.
vi. Correction curves are used to determine the Corrected deduct value from total
deduct value. The correction curves used vary by q (no. Of deduct value>5)
values.
vii. After finding corrected deduct value, PCI is evaluated as PCI=100-CDV.
viii. Similarly PCI for all other sample units is calculated and final PCI is computed by
taking average of all PCI values.

Severity values of different distresses are presented below:

35
 Table 5: Severity values of each distress (ASTM, 2008)

Unit of Severity
Sl. No Distress type
measurement
Low (exp) Med (exp) High (exp)
Alligator
1 Sq. metre <6mm 6-19mm >19mm
Cracking

Longitudinal
2 Metres <10mm 10-75mm >75mm
Cracking
Transverse
3 Metres <10mm 10-75mm >75mm
cracking
4 Patch millimetres <6mm 6-12mm >12mm
4 Rutting Millimetre 6-13mm 13-25mm >25mm

5 Block cracking Sq. metre <6mm 6-19mm >19mm

6 Ravelling Sq. metre Loss of <10% >10%

7 Edge cracking Metres <6mm 6-19mm >19mm

8 Depression Millimetre 13-25mm 25-50mm >50mm

9 Bleeding Sq. metre As per D 6433

10 Bumps and sags Millimetre 13-25mm 25-50mm >50

Lane shoulder drop

11 Sq. metre 25-50 mm 50-100mm >100mm
off

Some sample deduction curves are given below:

Figure 11: Deduction curve for rutting Figure 12 :Deduction curve for Alligator
(ASTM, 2008) Cracking (ASTM, 2008)

36
 Figure 14: Corrected Deduct value
Figure 13: Deduction curve for patching curve.(ASTM, 2008)
(ASTM, 2008)

3. 7 California Bearing Ratio

This test is performed as per IS 2720 (part 16) -1987. It is the ratio of force per cross
sectional area of specimen that is required so as to penetrate a soil mass with standard circular
plunger of diameter 50mm at the rate of 1.25mm/min to that required for the corresponding
penetration of a standard material. Tests are conducted on both disturbed and remoulded
soils. In this study, CBR (both soaked and unsoaked) is found for disturbed subgrade, sub-
base and base. The steps involved for this test are given below: (IS 2720, 1987)

i. The material passing 19mm IS sieve should be used in remoulded specimen.

Balancing the material for larger material is done by equal amount of material that
passes 19mm IS Sieve and retained on 4.75mm IS Sieve.
ii. The soil is mixed with water (optimum moisture content) which is determined
from Modified proctor test as per IS 2720 (part 8) -1983. Normally the sample
mass weigh 4.5 kg for fine grained soils and 5.5kg for coarse grained soils.
iii. The empty mould is weighed and is filled with soil in 5 layers with 25 tamping for
each layer.
iv. The mould is placed in water bath for four days in soaking tank (if test conducted
for unsoaked samples, ignore this step).

37
 v. The specimen is placed under the loading machine which has capacity of at least
5000kg and is equipped with movable head or base. A surcharge weight is placed
on top of it. Before loading the specimen, it is ensured that the dial gauge tip
should be in contact with the specimen. Readings are noted from proving ring.
Different proving rings have different calibration equations.
vi. The load is applied and penetration values are noted.
vii. Finally, CBR is found for both 2. 5mm and 5mm penetrations. If CBR 2. 5<CBR5
then test is repeated.
viii. Normally CBR value is determined at 2. 5mm penetration. CBR is given by
(Load required for sample to penetrate 2. 5mm) / (standard load required for
same penetration) *100.

Calibration equation used here is shown below: (Proving Ring Specification)

Load (in KN) = (0. 1089*proving ring reading) +0. 3575 (for 100KN-12267)

Load (in KN) = (0. 0678*proving ring reading) +0. 0015 (for 50KN-02396)

Standard load for 2.5mm penetration is 1370kg and for 5mm penetration is 2055kg.

3. 8 Optimum Moisture Content

This test is done as per IS 2720 (part 8) -1983. Steps involved to carry this test are:

i. 5kg sample of air dried soil passing 19mm IS Sieve is taken and then it is mixed
with some amount of water. The mould with a baseplate attached is weighed.
ii. In our study for GSB and WMM Modified Proctor, it is compacted in 5 layers
with each of 55 blows. Compaction is done by 4. 5kg rammer with 31cm fall.
iii. After compaction total sample is weighed.
iv. This test is repeated till total sample weight decreases from previous value.
v. Some amount of soil mass is takenand is placed in oven for 24 hours to
determine water content.

38
 vi. A graph is plotted between dry density vs water content. Peak value of density gives
maximum dry density and corresponding value for water is optimum moisture content.

Figure 15: Mould and Rammer(IS 2720, 1983)

3. 9 Liquid and Plastic limit test

The liquid and plastic limit test is determined as per IS 2720 (Part 5) -1985. Soil
conducted for these tests must pass 425 micron sieve. Liquid limit test is conducted by
Cassagandre apparatus and plastic limit test by rolling a thread of diameter 3mm. These
values (plasticity index) are required to calculate seasonal correction factor which is used to
calculate characteristic deflection by Benkelman-beam method.

39
Chapter 4: Analysis of Data, Results and Discussions

In this chapter, analysis of data is done. The results that are observed are international
roughness index (by both merlin and auto-level) , traffic studies, Benkelman-beam deflection,
structural number, California bearing ratio, optimum moisture content, liquid and plastic limit
of subgrade. Later, modelling is done on these performance indicators.

4. 1 MERLIN

By the use of MERLIN, an attempt was made to determine IRI at four sections (1A,
2A, 3A, 4A) which were stated above. It is calculated for both left and wheel paths.

The MERLIN Roughness Index is as follows:

Details of test results are not presented here for publication purposes.

Clearly, most of the values are having MERLIN Roughness Index (D) < 42. Merlin
calibration equations are valid only for D >42.

In order to find correlation between D and IRI by auto-level, some sections are chosen at NIT
Rourkela. Some sections are found to have D>42 and some D<42.

Details of auto level and merlin data for IRI are not presented here for publication
purposes.

4. 2 BENKELMAN BEAM RESULTS

By use of Benkelman-beam, characteristic deflection is obtained for all

sections that arechosen.

For calculating characteristic deflection, plastic and liquid limit of soil is required.

Plastic and liquid limit of soil subgrade is as follows:

Details of test results are not presented here for publication purposes.

40
4. 3 Traffic Data Calculation

As present data of traffic is available (shown above), we can estimate number of

equivalent standard axle loads the pavement has experienced till yet. Assumption is done on
traffic growth rate. It is taken as 7. 5%. One of the readings how ESAL is estimated is given
below. A per IRC 37, 2012 for the pavement which experiences commercial vehicles
between (500-1500, vehicle damage factor is taken as 3.5 provided the section is plain.

Details of test results are not presented here for publication purposes.

4. 4 Structural Number

Layer coefficients of pavement courses are obtained by Soaked CBR values as per
AASHTO that is discussed above. Surface and binder course are assumed to have layer
coefficient of 0. 39.

Details of test results are not presented here for publication purposes.

4. 5 Pavement Condition Index

For calculating pavement condition Index, we should first calculate the amount and
type of severity present in each type of distress. PCI values are shown below. The severities
like low, medium and high should be calculated on percentage of pavement section.

Details of test results are not presented here for publication purposes.

4.6 Pavement Performance Modelling

Factors considered in pavement performance modelling are structural number, traffic

in ESAL (in msa), IRI and characteristic deflection obtained from Benkelman-beam test.
Linear and non-linear regression analysis is done on observed values. Here, in our study the
reliability of regression model is measured by its goodness of fit, which is represented in
terms of coefficient of correlation (R2 value).

41
4.6.1 Relationship between IRI, Structural Number and ESAL.

Details of test results are not presented here for publication purposes.

4. 6. 3. Relationship between Deflection, IRI and ESAL.

Details of test results are not presented here for publication purposes.

42
Chapter 5: Summary and Conclusions

In this study, experiments are conducted in four sections close to Rourkela.to study
the pavement performance of flexible pavements. It includes study of variation of
International roughness Index, Benkelman beam deflection, Pavement distress study, etc.
with time. The experimental setup for the selected sections is discussed in above chapter.
It is seen that MERLIN equations are calibrated and validated for D>42 and D<42.
The results of the experiments on road roughness in terms of IRI using these two (auto level
and merlin) have been compared and it is observed that auto level has small error when
compared with values obtained by merlin. International Roughness Index values at all these
sections are low even after 3-5 years of construction. This means pavement is functionally
performing well.
Modelling is done on pavement performance indicators. IRI is modelled as a function
of ESAL and structural number. Characteristic deflection is modelled as a function of SN and
ESAL. Coefficient of correlation (R2 value) is within permissible limits.

5.2 FUTURE SCOPE

i. A good number of experiments can be conducted to calculate IRI by both auto

level and MERLIN and can be compared.
ii. Pavement Condition should be monitored every six months so as to understand
factors effecting pavement performance.
iii. Crack initiation and propagation models can be developed after having pavement
distress data which is taken every six months.
iv. A number of sections with different material properties should be considered for
predicting Pavement performance.

43
REFERENCES:

[1] AASHTO (1993), 'AASHTO Guide for design of pavement structures',

AmericanAssociation of State Highway & Transportation Officials, Washington, D C.

[2] Aggarwal S, Jain S S and Parida M (2002), 'A critical Appraisal of pavementmanagement
system', Journal of the Indian Roads Congress, Volume 63-2, 327 –403.

[3] Cundill, M.A. (1996). “The Merlin Road Roughness Machine: User Guide”,
ResearchReport 229, Transport Research Laboratory (TRL), Berkshire, United Kingdom.

[4] E. Spangler and W. Kelly, "GMR Road Profilometer - A Method for Measuring Road
Profile." Highway Research Record 121, Highway Research Board, 1966.

[5] Bose S, Sridhar R, Kamaraj C, Sharma G and Kumar G (2005), ‘Investigation ofmoisture
damage to bituminous pavement and effect on field performance – casestudies', Journal of
Indian Road Congress, 66 (3), Paper No. 517, 438 – 449

[6] Gedafa D S (2007), 'Performance prediction and maintenance of flexible pavement', Proc.
Mid-continent transportation research symposium, Ames, Iowa
[7] Gedafa D S, Hossain M and Miller R (2010), 'Estimation of remaining service life
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[8] Gupta A, Kumar P and Rastogi R (2011), 'Pavement deterioration and maintenancemodel
for low volume roads', International Journal of Pavement Research andTechnology, Volume
4, 195-202.
[9] ASTM D 6433 (2007) ‘Standard Practice forRoads and Parking Lots Pavement Condition
Index’.
[10] IRC 81 (1997), ‘Guidelines for strengthening of Flexible pavements using Benkelman
Beam Deflection Technique’, Indian Roads Congress
[11] IS 2720 part 16 (1987), ‘Indian Standard methods of test for soil’, Laboratory
determination of California Bearing Ratio.
[12] IS 2720 part 8 (1987), ‘Indian Standard methods of test for soil’, Determination of water
content-dry density relation using heavy compaction.
[13] IRC 37 (2011), 'Guidelines for the design of Flexible pavements', Indian
RoadsCongress’.

44
[14]Kumar P, Chandra S and Said M D S (2010), 'Performance Study of PMGSY
Roads',Indian Highways, 47-57.
[15] MORT&H (2004), ‘Guidelines for maintenance management of primary, secondaryand
urban roads’, Indian Roads Congress.
[16] B.C.Punmia (2012), ‘Principles of Surveying’.
[17] Nagakumar and Veeraragavan A (2000), ‘Effect of climatic and traffic factors onflexible
pavement response, an overview,’ Journal of Indian Roads Congress, 112-141.
[18] Long Term Pavement Management, Informational Management SystemsDatabase,
Federal Highway Administration
[19] Salt G and Stevens D (2004), 'Pavement Performance Prediction- Determination
andCalibration of Structural Capacity (SNP)', Report.
[20] Turki I, Obedat S and Homoud A S (1996), Development of Models of
PavementCharacteristics on Pavement Condition’, Journal of Indian Roads Congress,
Volume57-1, 201-219.140. Udayakumar L, Robert
[21] Al-Omari and M.I. Darter. Effects of Pavement Deterioration Types on IRIand
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