EFFECTS OF AIR VOID AND POROSITY ON MOISTURE DAMAGE OF
MALAYSIAN SPECIALTY HMA
HAMED ABDULGADER DOW
A thesis submitted in fulfillment of the
requirements for the award of the degree of
Master of Engineering
(Civil - Transportation and Highway)
Faculty of Civil Engineering
Universiti Teknologi Malaysia
NOVEMBER, 2008
iii
To my beloved mother, father, grandfather (Dow Algassi) whom passed away while
this research is in progress, uncle (Ali Dow) and friend (Ahmed Moftah)
iv
ACKNOWLEDGEMENT
In the name of ALLAH S.W.T, the Most Beneficent and the Merciful, praise
is to ALLAH S.W.T for the incredible gift endowed upon me and for the health and
strength given to me in order to finish the project and to prepare this thesis.
In preparing this thesis, I was in contact with many people, researchers,
academicians, and practitioners. They have contributed towards my understanding
and thoughts. In particular, I wish to express my sincere appreciation to my main
thesis supervisor, Associate Professor Dr. Abdul Aziz Chik, for encouragement,
guidance, critics and friendship. I am also very thankful to my co-supervisors Assoc.
Prof. Dr. Mohd Rosli Hainin for their guidance, advices and motivation. Without
their continued support and interest, this thesis would not have been the same as
presented here.
My fellow postgraduate students should also be recognised for their support.
My sincere appreciation also extends to all my colleagues, technicians and other
friends in Highway Lab who have provided assistance at various occasions. Their
views and tips are useful indeed. Unfortunately, it is not possible to list all of them in
this limited space. I am grateful to all my family members.
v
ABSTRACT
One of the main causes of distress in asphalt pavements is damage due to
water. This causes related to many effects. The study evaluates different type of
asphalt mixtures towards the resistance to moisture damage. The approach is to
investigate the relationship between air void and porosity against the abrasion
resistance and indirect tensile strength. The evaluation of such properties
concentrates on the following three tests; porosity test, indirect tensile test (IDT) and
CANTABRO test (CAT) .Three different wearing courses with modified asphalt
which porous asphalt (PA),stone mastic asphalt (SMA) and gap-graded asphalt (GPA)
that classified by (JKR/SPJ/2007) are studied. These three mixtures were designed
by means of Superpave method to determine OBC. After that Specimens were
prepared by means of Superpave Gyratory Compactor (SGC) and divided in two
different subsets for controlled dry and wet conditioned testing and tested for water
damage. Results provide relationship between porosity and air voids for PA mixture. In
addition, study also able to establish good models for SMA and GPA mixes compared to
other researcher (Walaa,2002). SMA and GPA mixtures (low porosity) showed less
influence to moisture damage probably due to the reduce amount of penetrating
water. The IDT and CAT are able to discriminate between mixtures of different porosity.
vi
ABSTRAK
Salah satu punca utama masalah yang merisaukan dalam laluan pejalan kaki
asphalt ialah kerosakan disebabkan air. Masalah ini berkaitan dengan pelbagai kesan.
Kajian ini mengkaji beberapa jenis campuran asphalt ke arah ketahanan dari
kerosakan yang disebabkan oleh kelembapan. Kaedahnya adalah dengan mengkaji
kaitain antara ruang dan liang udara dengan ketahanan kemelecetan dan kekuatan
ketengan secara tidak langsung. Pengkajian tentang perkara-perkara tersebut
menumpu kepada tiga ujian berikut; ujian liang udara, ujian ketegangan secara tidak
langsung, dan ujian CANTABRO. Tiga laluan berlainan dengan asphalt yang telah
diubah kepada porous asphalt (PA), batu mastic asphalt (SMA), dan gap-graded
asphalt (GPA) yang telah diklasifikasi oleh (JKR/SPJ/2007) telah dikaji. Ketiga-tiga
campuran ini telah direka menggunakan kaedah Superpave untuk menetutkan OBC.
Selepas specimen telah disediakan menggunakan Superpave Gyratory Compactor
(SGC) dan dibahagikan kepada dua subset yang berbeza untuk ujian kekeringan dan
kebasahan terkawal dan diuji untuk kerosakan air. Keputusan menujukan hubungan
antara liang dan ruang udara untuk campuran PA. Tambahan itu, kajian juga telah
berjaya memberikan model yang baik bagi campuran SMA dan GPA dibandingkan
dengan pengkaji yang lain (Walaa,2002). Campuran SMA dan GPA (liang udara
yang rendah) telah menunjukkan pengaruh yang kurang kepada kerosakan yang
disebabkan oleh kelembapan kerana pengurangan jumlah ketembusan air. IDT dan
CAT berupaya membezakan campuran liang udara yang berlainan.
vii
TABLE OF CONTENTS
CHAPTER
TITLE
PAGE
TITLE PAGE
i
DECLARATION
ii
DEDICATION
iii
ACKNOWLEDGEMENT
iv
ABSTRAK
v
ABSTRACT
vi
TABLE OF CONTENTS
vii
LIST OF TABLES
x
LIST OF FIGURES
xi
LIST OF ABBREVIATIONS
xii
LIST OF APPENDICES
xiv
1
2
PROJECT OVERVIEW
1
1.1
Introduction
1
1.2
Problem Statement
2
1.3
Objectives
3
1.4
Scope of Study
3
LITERATURE REVIEW
4
2.1
Overview of Hot Mix Asphalt
4
2.2
Malaysia specialty asphalt mix design
6
2.2.1
7
Porous Asphalt Design (PA)
viii
2.3
Stone Mastic Asphalt Design (SMA)
8
2.2.3
Gap Graded Asphalt Design
9
The Definitions and the Cause of the Moisture Damage of HMA
10
2.3.1
Adhesive Failure
10
2.3.2
Cohesive Failure
13
2.3.3
Factors Influencing Moisture Damage in HMA
14
2.4
The Mechanisms of Moisture Damage in HMA
2.5
Current Test Methods Used to Predict the Moisture Sensitivity of
2.6
3
2.2.2
14
HMA
17
Porosity of HMA
18
METHODOLOGY
20
3.1
Introduction
20
3.2
Material characteristics
20
3.2.1
Aggregates
22
3.2.1.1 Sieve Analysis
22
3.2.1.2 Aggregate specific gravity
24
Asphalt Binders
26
3.2.2
3.3
Aggregate Structure Design
26
3.4
Asphalt Mixture Design
27
3.4.1
Bulk specific gravity (corelok system)
29
3.4.2
Theoretical Maximum Density (TMD) Test
30
3.4.3
Analysis of Volumetric Parameters
30
3.4.3.1 Analysis of Air Void in the Compacted Mix(VIM) 31
3.5
3.4.3.2 Analysis of Void in Mineral Aggregate (VMA)
31
3.4.3.3 Analysis of Void in Mineral Aggregate (VMA)
32
3.4.4
Determination of Optimum Bitumen Content (OBC)
32
3.4.5
Binder Drain-down Test
32
3.4.6
Cantabro Test on Air Cured Samples
33
Experimental Program
3.5.1
34
Determination of sample porosity using the
(Corelok system)
35
ix
4
5
3.5.2
Indirect Tensile Test IDT
38
3.5.3
CANTABRO Test
38
3.5.3.1 Cantabro Test on Air Cured Samples
39
3.5.3.2 Cantabro Test on Water Soaked Samples
39
RESULTS AND DISCUSSIONS
40
4.1
Introduction
40
4.2
Results of Materials Tests
40
4.2.1
Sieve Analyses
41
4.2.2
Determination of Materials Specific Gravity
41
4.2.2.1 Specific Gravity of Coarse Aggregate
41
4.2.2.2 Specific Gravity of Fine Aggregate
42
4.2.2.3 Specific Gravity of Mineral Filler
42
4.2.2.4 Blend Specific Gravity of Aggregate
42
4.2.2.5 Specific Gravity of Bitumen
43
4.3
Aggregate Gradation
43
4.4
Asphalt Mixture Design Results
45
4.5
Relationship between air void and porosity
46
4.6
Retained Strength or Stiffness
48
4.7
CANTABRO Test
54
CONCLUSION AND RECOMMENDATIONS
57
5.1
Conclusions
57
5.2
Recommendations
58
REFERENCES
APPENDIX A - D
59
62 - 82
x
LIST OF TABLES
TABLE NO.
TITLE
PAGE
2.1
Types of Hot Mix Asphalt
4
2.2
Malaysia porous asphalt gradation
7
2.3
Malaysia stone mastic asphalt gradation
8
2.4
Malaysia gap graded asphalt gradation
9
2.5
Summary of factors influencing moisture damage
15
3.1
Summaries of the Total Experimental Program Samples
35
3.2
Corelok TM % Porosity Data Collection Table
37
4.1
Values of bulk specific gravity of aggregate
42
4.2
Percentage aggregate passing on each sieve size for PA Mix design
43
4.3
Percentage aggregate passing on each sieve size for SMA Mix design 44
4.4
Percentage aggregate passing on each sieve size for GPA Mix design 45
4.5
Mix design results
46
4.6
Standard deviation (SD) and coefficient of variation (CV)
48
4.7
Air void, porosity and indirect tensile strength of dry specimens
50
4.8
Air void, porosity and indirect tensile strength of wet specimens
51
4.9
Percentage change of TSR between wet and dry series of the mixes
53
4.10
CANTABRO Test results
55
4.11
Percentage increase of weight loss
56
xi
LIST OF FIGURES
FIGURE NO.
TITLE
PAGE
2.1
Representative aggregate gradations
5
3.1
The laboratory investigation flow chart
21
3.2
Gradation and size analysis equipment
23
3.3
Major CASG equipment
25
3.4
Major equipment used in performing the FASG test
25
3.5
Superpave gyratory compactor
28
3.6
Vacuum-sealing device
29
3.7
Apparatus for TMD test
30
3.8
Drain-down test apparatus
33
4.1
Traffic flow of Larkin interchange
44
4.2
Gradation limit and design curve for SMA
44
4.3
Gradation limit and design curve for GPA
45
4.4
Relationship between porosity and air void
47
4.5
Relationship between porosity and air void content for SMA and GPA 48
4.6
Effect of air voids and porosity for SMA&GPA) on ITS, dry
49
4.7
Effect of air voids and porosity for PA on ITS, dry
49
4.8
Effect of air voids and porosity for (SMA&GPA) on ITS-wet series
52
4.10
Comparing the ITS of wet and dry
53
4.11
Effect of air voids and porosity on the tensile strength ratio
54
4.12
Average weight loss
55
4.13
Rate of weight loss of the mixes for different air voids
56
xii
LIST OF ABBREVIATIONS
AASHTO
-
American Association of State Highway and Transportation
Officials
ASTM
-
American Society for Testing and Materials
HMA
-
Hot Mix Asphalt
JKR
-
Department of Public Works
PA
-
Porous Asphalt
SMA
-
Stone Mastic Asphalt
GPA
-
Gap Graded Asphalt
CAT
-
CANTABRO Test
IDT
-
Indirect Tensile Test
LA
-
Los Angeles Value
PG
-
Performance Grade
P
-
Porosity
NMAS
-
Nominal Maximum Aggregate Size
SSD
-
Saturated
surface
-
dry
TMD
-
Theoretical Maximum Density
VFB
-
Voids Filled with Bitumen
Gmb
-
Bulk specific gravity of compacted mix
Gsb
-
Combined bulk specific gravity of total aggregate
Gmm
-
maximum specific gravity of mix
VIM
-
Voids in Mix
VMA
-
Voids in Mineral Aggregate
OBC
-
Optimum Bitumen Content
ESAL
-
Equivalent Standard Axle Load
SGC
-
Superpave Gyratory Compactor
CASG
-
Coarse Aggregate Specific Gravity
FASG
-
Fine Aggregate Specific Gravity
xiii
ITS
-
Indirect Tensile Strength
OPC
-
Ordinary Portland Cement
Gsb
-
Aggregate Bulk Specific Gravity
GbulkSSD
-
Aggregate Bulk SSD Specific Gravity
Gsa
-
Aggregate Apparent Specific Gravity
TSR
-
Tensile Strength Ratio
xiv
LIST OF APPENDICES
APPENDIX
TITLE
PAGE
A
Aggregate size distribution and Determination of Filler
62
B
Specific gravity of Aggregate
B1
Specific Gravity of Coarse Aggregate
65
B2
Specific Gravity for Fine Aggregate
66
B3
Blend Aggregate Specific Gravity
67
C
Mixture Design
C1
Maximum Specific Gravity of Bituminous Paving Mixture
68
C2
Bulk Specific Gravity Of Bituminous Paving Mixture
71
C3
Volumetric Properties of Mix
74
C4
Detemination of Optiumum Asphalt Content
77
D
Porosity Result
80
CHAPTER 1
PROJECT OVERVIEW
1.1
Introduction
Moisture damage of Hot Mix Asphalt (HMA) mixtures, generally called
stripping, is a major form of distress in asphalt concrete pavement. Water is a primary
cause of stripping of asphalt pavements since it accelerates or causes typical pavement
distresses such as bleeding, rutting, cracking, raveling and localized failures (potholes)
(Hicks,2003). It is characterized by the loss of adhesive bond between the asphalt
binder and the aggregate (a failure of the bonding of the binder to the aggregate) or by a
softening of the cohesive bonds within the asphalt binder (a failure within the binder
itself), both of which are due to the action of loading under traffic in the presence of
moisture.
Water flows through accessible voids or pore spaces in a pavement. Hence, the
rate of flow must be related to the amount of water accessible voids, or porosity, in
some way. Therefore, the porosity or permeability must be a function of air void. The
nature and the growth rate of the traffic effects are associated with static and dynamic
processes. Static processes cause weakening of cohesion and adhesion or structural
destruction after freeze thaw cycles (Little, 2003).
In case of water saturated
pavements, the dynamic processes are directly related to traffic action which generates
tension and water pressure in pores. This process starts when the water is allowed to
circulate freely through the interconnected voids (Kandhal, 2001).
2
The potential for moisture damage in HMA has traditionally been evaluated
through laboratory testing. Factors affecting moisture damage of HMA have been
identified as the type and use of the mix, the characteristics of the asphalt binder and the
aggregate and environmental effects during and after construction, and the use of antistripping additives (Kiggundu,1988), (Stuart,1990) and (Hicks,1991).
Malaysia, like many other countries in the world has relatively high rainfall
ranging from 400 to 450 mm monthly. Rainfall is distributed throughout most of the
year with portions of the months (June and July) being dryer than other months
(monthly weather review 2008). Water penetrated through pores or affected cracks
areas of the pavements, and caused stripping. In general, after being open to traffic for
approximately four years, the pavements experienced minor to medium cracking
problems. The effect of porosity on pavements associated with moisture damage
immediate after being open to traffic is an important, yet often overlooked, issue .Three
different wearing courses modified asphalt mixtures classified by (JKR/PSJ/2007), (PA)
porous asphalt, (SMA) stone mastic asphalt and (GPA) gap graded asphalt were be
evaluated in this study for the moisture damage.
1.2
Problem statement
The environment and traffic effects are associated with static and dynamic
processes. Static processes cause weakening of adhesion between binder and aggregate
or structural destruction after freeze thaw cycles (Little,2003). In case of water-saturated
pavements, the dynamic processes are directly related to traffic action, which generates
tension and water pressure in pores. This process starts when the water is allowed to
circulate freely through the interconnected voids (Kandhal, 2001). Both dynamic and
static processes are related to air voids and porosity content. As water passes through
pores voids, these effects might result in a weak and saturated pavement immediate
after being open to traffic. The action of water in an asphalt mixture is, however, highly
3
complicated. No single theory can well explain the effect of porosity on moisture
damage.
1.3
Objectives
To date, there has not been any guideline to determine the potential of water
damage in asphalt mixtures associated with porosity. The objectives of this study are as
follows:
ƒ
Water flows through accessible voids or pore spaces in a pavement.
Hence, the rate of flow must be related to the amount of water accessible
voids, or porosity, in some way. Therefore, the porosity or permeability
must be a function of air void.
ƒ
This study is attempted to simulate the water damage on asphalt
pavement by indirect tensile strength and compacted mixtures loses.
1.4
Scope of the Study
This study involves laboratory experiments where this study focus on three
different wearing courses modified asphalt mixtures classified by (JKR/PSJ/2007), (PA)
porous asphalt, (SMA) stone mastic asphalt and (GPA) gap graded asphalt were be
designed and evaluated in this study for the moisture damage. The mixtures design
followed superpave method and their evaluated for moisture damage conducted by
CANTABRO test (CAT) and indirect tensile test (IDT).
CHAPTER 2
LITRATURE REVIEW
This chapter discusses the overview of hot mix asphalt, moisture damage and its
factors as will as HMA porosity.
2.1
Overview of Hot Mix Asphalt
Most HMA is divided into three different types of mix—dense-graded, open-
graded, and gap-graded—primarily according to the gradation of the aggregate used in
the mix as shown in (Table 2.1) and Representative gradations are shown in Figure 2.1
(a),(b) and (c) (USA Army Corps, 2000).
TABLAE 2.1 : Types of Hot Mix Asphalt
5
FIGURE 2.1 Representative aggregate gradations
6
In 2007 year, PWD public work department or JKR launched a new Standard
Specification for Road works Section 4: Flexible Pavement. The new specification
replaces the Standard Road Specification 1988: Chapter 4 and embodies years of
research and experience by PWD on pavement technology. The new specification
incorporates technical procedures on construction of specialty mixes such as Stone
Mastic Asphalt (SMA), Porous Asphalt (PA), Gap Graded Asphalt (GPA),
Microsurfacing, Coloured Surfacing, Cold In place Recycling, Hot in Place Recycling,
Chip Seal and Crack Sealing. It also specify procedures on construction of polymer
modified asphalt, presents new generation Asphaltic concrete, for both wearing and
binder course, and details the use of International Roughness Index (IRI) as a measure
of surfacing quality at the end of a road project. PWD hopes that the new specification
will help improve the overall quality of Malaysian road pavement.
This study focused on three specialties mixes which divided to three mixes
according to types PA,SMA,GPA and further two mixes according to the gradation of
the aggregate i.e. open-graded and gap graded.
2.2
Malaysia specialty asphalt mix design
The design of specialty asphalt mix (JKR.2007) is based on
ƒ
A minimum binder content to ensure resistance against particle loss and
thick film on the aggregate.
ƒ
A maximum binder content to avoid binder runoff and still maintain
permeability in the mix.
Using the cantabro abrasion value, a minimum amount of binder is fixed. The
initial selection of mix type is influence by the aggregate gradation that need to carried.
The propose of using modified binder is to improve the resistance against particle loss
with open and gap mixtures through higher cohesion and to obtain a longer durability
7
through thicker binder films because of higher viscosity. In additional reduce drain
down the final paved layer thickness is typically 5 cm.
2.2.1
Porous Asphalt Design (PA)
The mix design approach followed in Malaysia (JKR.2007) is as following:
ƒ
Two types of porous asphalt mixes are used; one is 10 mm nominal
maximum size and other 14 mm nominal maximum size. The 10 mm is
the more like that of other countries. But the 14 mm mix is considerably
courser. The gradations are shown in Table 2.2.
Table 2.2 : Malaysia porous asphalt gradation
Gradation
% Passing
20 mm
14 mm
10 mm
5 mm
2.36 mm
0.075 mm
14 mm
100
85-100
55-75
10-25
5-10
2-4
10 mm
–
100
95-100
30-50
5-15
2-5
ƒ
The mix design is based on first measuring the voids at various binder
content then the voids, the percentage of wear and drain down estimated
using cantabro and drain down tests. The design binder content is
optimized for air voids, wear and drain down percentages.
ƒ
The aggregate are specified to provide a hard and durable rock. The LA
value must be low, less than 25% according to ASTM C 131.
ƒ
The aggregates must have high polishing resistance, not less than 40
according to MS 30.
ƒ
Maximum flakiness index of 25 is specified to control aggregate shape
degradation
ƒ
The binder is polymer modified, PG 76 is used. Tolerance asphalt
content 4-6% and the air voids tolerance 18-25%.
8
ƒ
Maximum binder drain down not more than 0.3% according to
(JKR,2007)
ƒ
Maximum compacted specimens losses allowed is 15 % according to
(JKR,2007)
ƒ
2.2.2
The specimens are compacted using 50 Marshall Blows.
Stone Mastic Asphalt Design (SMA)
Stone Mastic Asphalt (SMA) is typically gap-graded and content high
percentage of fine aggregate. The mix design approach followed in Malaysia
(JKR.2007) is as following:
There are two gradation of stone mastic asphalt using in Malaysia; one is 12.5
mm nominal maximum size and other 9.5 mm nominal maximum size. Both have large
gap gradation between 9.5 mm and 4.75 sieves. The gradations are shown in Table 2.3.
Table 2.3 : Malaysia stone mastic asphalt gradation
% Passing
Gradation
19
12.5
9.5
4.75
2.36
0.600
0.300
0.075
mm
mm
mm
mm
mm
mm
mm
mm
12.5 mm
100
85-95
65-75
20-28
16-24
12-16
12-15
8-10
9.5 mm
–
100
72-83
25-38
16-24
12-16
12-15
8-10
ƒ
The mix design is based on first measuring the voids at various binder
content then the adequate OBC estimated by using drain down tests. The
design binder content is optimized for air voids and drain down
percentages.
ƒ
The aggregate are specified to provide a hard and durable rock. The LA
value must be low, less than 25% according to ASTM C 131.
9
ƒ
The aggregates must have high polishing resistance, not less than 40
according to MS 30.
ƒ
Maximum flakiness index of 25 is specified to control aggregate shape
degradation
ƒ
The binder is polymer modified, PG 76 is used. Tolerance asphalt
content 5-7% and the air voids tolerance 3-5%.
2.2.3
ƒ
Maximum binder drain down not more than 0.3%
ƒ
The specimens are compacted using 50 Marshall Blows.
Gap Graded Asphalt Design
Gap graded asphalt is typically content less than SMA percentage of fine
aggregate which passing 4 mm sieve. The mix design approach followed in Malaysia
(JKR, 2007) is as following:
ƒ
Two types of porous asphalt mixes are used; one is 10 mm nominal
maximum size and other 14 mm nominal maximum size. The gradations
are shown in Table 2.4.
Table 2.4 : Malaysia gap graded asphalt gradation
% Passing
Gradation
25
mm
20
mm
14
mm
12.5
mm
10
mm
8
mm
4
mm
2
mm
0.600
mm
0.300
mm
0.075
mm
20 mm
100
76100
6489
–
5681
–
4155
1631
12-16
6-10
3-7
12.5 mm
–
–
100
85100
–
6585
4065
2040
–
10-20
3-10
ƒ
A gap grading is to be obtained by omitting 12.5,8 and 10 mm fraction
from the 20 mm and 12 mm mixtures.
ƒ
The mix design is based on voids content at various binder content.
10
ƒ
The aggregate are specified to provide a hard and durable rock. The LA
value must be low, less than 25% according to ASTM C 131.
ƒ
The aggregates must have high polishing resistance, not less than 40
according to MS 30.
ƒ
Maximum flakiness index of 25 is specified to control aggregate shape
degradation
ƒ
The binder is polymer modified, PG 76 is used. Tolerance asphalt
content 5-7% and the air voids tolerance 3-5%.
ƒ
2.3
The specimens are compacted using 50 Marshall Blows.
The Definitions and the Cause of the Moisture Damage of HMA
Since moisture damage in HMA mixtures was first identified as a distress type, a
significant amount of effort has been applied to defining the underlying mechanisms
and to developing tests to predict its occurrence. Moisture damage in HMA may be
generically defined as the separation of the asphalt coating from the aggregate in a
compacted HMA mixture in the presence of water under the action of repeated traffic
loading.
Overall, two areas of focus have been identified: a failure of bonding of the
binder to the aggregate (i.e., a failure of adhesion) and a failure within the binder itself
(i.e., a failure of cohesion). These two areas have, over the years, generated a significant
body of research leading to a number of disparate conclusions.
2.3.1
Adhesive Failure
Most researchers, however, consider that moisture damage in HMA is due more
to the adhesive mode of failure than to the cohesive mode. For example, as
11
(Majidzadeh, 1968) stated, stripping of the binder from aggregate in presence of water
(i.e., moisture damage) results in adhesive failure which is considered as an economic
loss and an engineering failure in the design of a proper mixture.(Kennedy,1982)
explained that stripping was the loss of adhesion between the asphalt binder and the
aggregate due to the action of water, and (Tunicliff, 1982) suggested that stripping was
the displacement of the asphalt binder film from the aggregate surface, which he
explained using the chemical reaction theory of adhesion. Thus, a number of hypotheses
relative to the adhesive bond between asphalt and aggregate have been developed in
order to better understand the phenomenon of stripping under this definition. (Hicks,
1991) provided an overview of previous research on adhesion. He identified four broad
theories that have been developed to explain the adhesion of asphalt binder to
aggregate.
Mechanical adhesion theory (Lee,1954) and (Rice,1958) suggests that the
adhesion of asphalt binder to the aggregate is affected by several aggregate physical
properties, including surface texture, porosity or absorption, surface coatings, surface
area, and particle size. In general, a rough, porous surface had a tendency to provide the
strongest interlock between aggregate and asphalt. However, as (Hicks, 1991) stated,
“…the greater the surface area of the aggregate, the greater the amount of asphalt
cement required for stability. ….Consequently, a mixture with substantial fines tends to
strip more readily because complete particle coating requires more asphalt cement
which is more difficult to achieve without creating a stability problem.”
Chemical reaction between the asphalt binder and the aggregate has been
generally accepted to explain why different types of aggregate demonstrate different
degrees of adhesion between the binder and the aggregate in the presence of water. In
other words, the surface pH values of the aggregate and of the binder affect the quality
of the surface adhesion (Barksdale, 1991). The reason for this has been attributed to the
different polarities of the surface minerals in the aggregate and the asphalt binder. In the
interior of a crystal, forces are in equilibrium. On the surface of a crystal, the bonding
forces of the atoms or molecules may be partially unsatisfied, with excess or “free”
12
charges, so that the surface may exhibit polarity (Rice, 1958). A quartz (SiO2), which is
a primary mineral component of quartzite and other silicious minerals, comprises the
silicon dioxide tetrahedron (SiO4
4-
) as a unit crystal structure. The silicon atom has a
positive valence of 4 and each oxygen atom has a negative valence of 2. The positive
valence of the silicon atom is satisfied by sharing its electron with the electron of each
oxygen atom. However, one unsatisfied negative valence of each oxygen atom results in
a net negative polarity of the quartz crystal structure (Rice, 1958). The surface of calcite
(CaCO3), which is a primary mineral component of limestone, has a non-polar
property. This is also related to the crystal structure of calcite. In this structure, the
positive valences of the carbon and the calcium atoms are satisfied by the covalent bond
with two oxygen atoms and one oxygen atom (e.g., CaCO3 → CaO + CO2). The
satisfied valence of each atom makes the surface of a calcite polyhedron non-polar
(Povarennykh, 1972).
The differential degree of wetting of the aggregate by asphalt and water has
been explained using surface energy theory. (Rice, 1958) suggested that when asphalt
and aggregate were brought together, adhesion tension is established between two
phases. He also reported data which indicated that the adhesion tension for water-toaggregate is higher than that for asphalt-toaggregate. Hicks stated, “… water will tend
to displace asphalt cement at an aggregate–asphalt cement interface where there is
contact between the water, asphalt, and aggregate. (Mark, 1935) indicates that
interfacial tension between the asphalt and aggregate varies with both the type of
aggregate and the type of asphalt cement
Molecular orientation theory affirms that when asphalt binder comes into
contact with an aggregate surface, the molecules in the asphalt align themselves on the
aggregate surface to satisfy the energy demand of the aggregate (Hubbard, 1958). It was
demonstrated that this alignment of asphalt molecules was affected by the orientation of
unsatisfied ions on the surface of aggregate, (Mark, 1935). Hicks stated, “…water
molecules are dipolar. Asphalt molecules are generally non-polar, although they contain
13
some polar components. Consequently, water molecules, being more polar, may more
readily satisfy the energy demands of an aggregate surface.”
2.3.2
Cohesive Failure
Even though cohesive failure of asphalt has been regarded as a less important
factor in the definition of moisture damage of HMA, (Bikerman, 1960) suggested that
the probability of cohesive failure was much greater than of adhesive failure. This was
also demonstrated by work of (Kanitpong,2002), which is supported by the observation
of failure surfaces in asphalt mixtures obtained from the Tensile Strength Ratio (TSR)
test, where the failure was visually observed within the binder coating without evidence
of apparent loss of adhesion to the aggregate particles.
This cohesive failure can be partially explained by emulsification of water in the
asphalt phase, which is different to conventional emulsified asphalts in which the
asphalt is emulsified in a water phase (Fromm, 1974). Fromm’s work (1974) showed
that water could enter into the asphalt film and form a water-in-asphalt emulsion. This
emulsification of water in the asphalt film causes asphalt particles to separate from the
asphalt film (cohesive failure) and ultimately leads to an adhesive failure at a critical
time when this emulsification boundary propagates to the aggregate surface.
However, since the mechanism of cohesive failure leads, ultimately, to an
adhesive failure, most instances of cohesive failure may only be inferred rather than
observed, and the final mechanism (i.e., adhesive) is reported as the cause (Terrel,
1994). Thus, even though the definition of moisture damage in HMA has been regarded
as the failure of adhesive and cohesive bonds between the asphalt and the aggregates in
the presence of water, it has proven difficult to distinguish between the two modes of
failure in predicting failure mode unless the failure surface of HMA is visually
inspected a posteriori (Terrel, 1994).
14
2.3.3
Factors Influencing Moisture Damage in HMA
Several surveys (Kiggundu, 1988), (Stuart, 1990) and (Hicks, 1991) have been
undertaken to better understand which factors should be considered in evaluating moisture
damage in HMA mixtures. Many variables, including the type and use of the mix, asphalt
characteristics, aggregate characteristics, environmental effects during and after
construction, and the use of anti-stripping additives, have been identified. Even though most
responses in these surveys were as expected, some results were contradictory. For example,
gravel is not always associated with stripping. The reason for this was pointed out in the
literature: even though the chemistry of the original gravel deposit made it moisture
susceptible, compounds that could prevent stripping might be adsorbed into the aggregate
surfaces over a period of geologic time so that the same gravel might exhibit good
resistance to stripping, unless it was crushed and thereby exposed “fresh” surfaces to the
asphalt (Tunicliff, 1982). Based on work by Hicks (1991), Table 2.5 summarizes the
factors influencing moisture damage.
2.4
The Mechanisms of Moisture Damage in HMA
Even though many factors have been suggested to influence moisture damage in
HMA mixtures, the essential problem was how water penetrated the asphalt film and/or
interfaces between asphalt and aggregate. Several different mechanisms have been
identified in the literature.
15
Table 2.5 : Summary of factors influencing moisture damage
Desirable
Characteristics
Factor
Supporting Researchers
1) Aggregate
a) Surface Texture
b) Porosity
c) Mineralogy
Rough
Depends on pore size
Basic (PH=7) Aggregate
are more resistant
d) Dust Coatings
Clean
e) Surface Moisture
f) Surface Chemical
Composition
Dry
Able to share electrons or
form hydrogen bonds
Increase viscosity of
Asphalt
g) Mineral Filler
Hicks (1991), Majidzadeh(1968)
Hicks (1991),Thelen (1958)
Rice (1958), Majidzadeh (1968)
Majidzadeh (1968) ,Tunnicliff
(1982)
Majidzadeh (1968), Kim(1985)
Hicks (1991)
Hicks (1991)
2) Asphalt Cement
a) Viscosity
b) Chemistry
C) Film Thickness
High
Nitrogen and Phenols
Thick
Thelen (1958)
Curtis et al. (1991)
Hicks (1991)
a) Voids
Very low or Very high
b) Gradation
Very dense or Very open
c) Asphalt Content
High
Terrel and Shute (1989)
Brown et al. (1985), Takallou et
al. (1985)
Hicks(1991)
3) Type of Mixture
4) Environmental Effect During Construction
a) Temperature
b) Rainfall
c) Compaction
Warm
None
Sufficient
Hicks (1991), Majidzadeh(1968)
Hicks (1991)
Hicks (1991), Tunnicliff (1982)
5) Environmental Effect after Construction
a) Rainfall
None
b) Freeze–Thaw
None
c) Traffic Loading
Low Traffic
6) Modifiers or
Additives
Use
Hicks (1991)
Lottman (1982), Taylor and
(1983)
Fromm (1974), Gzemski et al.
(1968)
Tunnicliff (1982)
16
Lottman tried more closely to replicate field–related conditions in the
laboratory. To carry out this project (Lottman 1978, May1982), he took notice of the
behavior of water in the pore structure of an HMA mixture loaded by heavy traffic. He
suggested some of the major moisture–damage mechanisms (Lottman, 1982):
ƒ
The development of pore water pressure in the mixture voids due to the
repetition of wheel-loads; thermal expansion and contraction produced
by ice formation, temperature cycling above freezing, freeze-thaw, and
thermal shock; or a combination of these factors (mechanical disruption).
ƒ
Asphalt removal by water in the mixture at moderate to high
temperatures (emulsification).
ƒ
Water–vapor interaction with the asphalt filler mastic and larger
aggregate interfaces (adhesion failure based on surface energy theory).
ƒ
Water interaction with clay minerals in the aggregate fines (adhesion
failure based on chemical reaction).
Based on these hypotheses, he developed a mechanical laboratory test protocol
generally referred to as the Lottman test. The exposed interiors of laboratory tested
specimens were compared to those of field damaged specimens and this was used to
confirm the Lottman test protocol and hypothesis (Lottman, 1978).
Hydraulic scouring has been suggested to explain moisture damage due to the
movement of surface traffic loads on saturated HMA pavement. When a heavy traffic
wheel moves over a saturated pavement surface, water is pressurized within the
pavement void structure in front of the moving load and immediately relieved behind
the load. Thus, sealed surface layers, where the traffic-imposed loads are highest, were
stripped by rapidly reversing high water velocities and pressures within the saturated
pore structure (Taylor, 1983). However, it has been generally observed by inspection of
field specimens of stripped pavements that most stripping begins at the bottom of an
HMA layer and progresses upwards (Kandhal, 1992). (Taylor,1983) suggested that the
reason for this behavior was that the asphalt at the bottom of a pavement layer is usually
in tension under the application of surface applied loads and is often influenced by
17
prolonged exposure to moisture from water trapped within a granular base course above
the subgrade.
2.5
Current Test Methods Used to Predict the Moisture Sensitivity of HMA
The development of tests to predict the potential of moisture sensitivity of HMA
began in the 1930s (Terrel, 1989). Since that time, numerous tests have been developed
to identify moisture sensitivity of HMA mixtures. (Hicks, 1991) stated that failure due
to the moisture damage to HMA occurs in two stages. The first stage is the failure of the
adhesion and cohesion bonds and the second stage is the mechanical failure of the
pavement under traffic action, as a logical continuation of the first stage. Thus, tests
were separated into three categories depending which stage is deemed more critical in
moisture damaged HMA pavement.
ƒ
Visual inspection testing focuses on the first stage failure. The loose
mixture is immersed in water at room temperature or boiling water for a
specific duration. The criteria of failure are decided by visual
identification of stripped (uncoated) aggregate
ƒ
Mechanical laboratory testing considers the second stage failure as more
detrimental in HMA pavements. The compacted mixture is conditioned
in a manner that is intended to simulate the real situation. A comparison
of the physical conditions such as strength or resilient modulus and wear
or loss of the conditioned and unconditioned samples is used to evaluate
the moisture damage potential in HMA pavement.
ƒ
Loaded wheel testing simulates in the laboratory the pavement under
traffic. This testing was originally developed to evaluate rutting in
asphalt mixtures. However, it has been recognized that when these tests
are performed on saturated mixtures, there is a possibility to more
accurately evaluate moisture sensitivity in HMA.
18
2.6
Porosity of HMA
In recent years, design and use of open graded mixes has gained popularity. It is
important to conceder that the use of air voids for design and quality control of these
mixes might be misleading for determination of pavement durability. While % air voids
is a viable design and quality control criteria for fine graded mixes, a more adequate and
meaningful method has to be used for open graded mixtures designed for the highway
system (Corelok Operator’s Guide, 2007).
Air void content is of concern primarily for stability and durability of asphalt
mixture. Air void determination during construction is used to protect against excessive
water permeability that can cause premature failure. For durability, only the air voids
that are accessible to water, the % porosity, is of concern. The concerning fact with the
present method is that two samples with 7% air voids can have completely different
permeability characteristics depending on the void structure within the sample.
However, two samples with the same porosity will have the same permeability. We
believe that for open graded mixtures, determination of % porosity is better design and
pavement quality indicator as compared to the currently determined % air voids
measurement.
Percent porosity is defined as the percentage of water permeable voids in the
compacted mixture. This parameter can be calculated by using a bulk specific gravity
and an apparent maximum gravity of any compacted mixture under test. It does no
require a previously determined Gmm value, which in most cases is not representative
of the gradation of randomly selected coarse graded compacted sample.
Porosity can be used as a direct indicator of mix durability and will have a
strong correlation to mixture permeability and segregation. This test is easy to perform
and can be completed in approximately 7 minutes using the Corelok system. A detailed
procedure for conducting this test is attached in next chapter.
19
Knowing the total porosity of compacted samples is helpful in determining the
performance of pavement with respect to permeability. The present tests for
determination of permeability are time consuming and the measurements are based on
number of assumption that cannot be defended, physically and theoretically.
CHAPTER 3
METHODOLOGY
3.1
Introduction
This chapter provides detailed information on the materials used and their
properties. It also highlights the laboratory procedures for the tests performed. The main
aim of the study is to provide more insight of the contribution the different air voids and
porosity in asphalt specialty mixtures towards resistance to moisture damage. Based on
this aim, the objectives have been achieved by conducting laboratory investigation.
Laboratory investigation is including material characteristics, mix design method and
experimental program. Figure 3.1 shows the laboratory investigation flow chart.
3.2
Material characteristics
Asphalt mixture is a composite material that is largely made of two main
components; aggregate and asphalt cement. This section describes the properties of the
aggregates and the asphalt cement binders used.
21
Material
characteristics
Aggregates
Asphalt Binder
Aggregate Structure Design
Asphalt Mixture Design
Experimental program
Porosity
Relationship
Moisture
Damage Test
ITS & CAT
Analysis
Conclusion
Recommendation
Figure 3.1
The laboratory investigation flow chart
Air void
22
3.2.1
Aggregates
Sources of aggregate were selected to encompass a wide range of aggregates
typically used in the State of Johor.The aggregate type that has been used was granite
obtained from Hanson Quarry Products located at Kulai, Johor. Three aggregate
gradations were used which are as follows:
ƒ
Nominal maximum aggregate size (NMAS) of 10 mm (designated as
PA14).
ƒ
(NMAS) of 12.5 mm (designated as SMA 14).
ƒ
And (NMAS) of 20 mm (designated as GAP 25).
Different stockpiles from each type of aggregates were acquired. Aggregates
were acquired and kept properly sealed from any moisture intrusion. Detailed laboratory
evaluation procedures of individual aggregate gradation were conducted to determine
the basic aggregate properties such as specific gravity, gradation, and other Superpave
consensus properties. The laboratory tests conducted on each aggregate gradation
included
ƒ
Sieve analysis (ASTM C 117) to determine as-received gradation
ƒ
Specific gravity and absorption (AASHTO T 85 for coarse aggregate and
AASHTO T 84 for fine aggregate)
3.2.1.1 Sieve Analysis
The test can be run on either dry or washed aggregate. The washed sieve
analysis takes longer but produces a more accurate gradation, particularly the percent
passing the No. 200 (0.075 mm) sieve since the washing helps remove these small
particles from the larger particles. The dry sieve analysis procedure is often used where
rapid results are required.
The basic sieve analysis consists of weighing an aggregate sample and then
passing it through a nest of sieves. The nest of sieves is made up of a stack of wire-cloth
screens with progressively smaller openings from top to bottom. The material retained
23
on each sieves weighed and compared to the total sample mass. Particle size distribution
is expressed as a percent retained or percent passing by weight on each sieve size.
Figure 3.1 shows the major gradation and size analysis equipment.
Figure 3.2
Gradation and size analysis equipment
The washed procedure takes one to three days from sampling the aggregate to
completion depending on the moisture content of the aggregate when it is sampled. The
dry procedure can take about one to two hours from sampling the aggregate to
completion. The percentages of aggregates passing each sieve and total percentages of
aggregates retained on each sieve size was calculated and recorded to the nearest 0.5%.
Percentage of Mineral Filler, which ordinary Portland cement and dust that can
calculate by following equation
Mineral Filler = [(A – B) / A] x 100. …………………………………Equation 3.1
24
Where:
A= Original dry mass of sample, gram; and
B= Dry mass of sample after washing, gram.
3.2.1.2 Aggregate specific gravity
The aggregate specific gravity test is used to calculate the specific gravity of a
coarse and fine aggregate sample by determining the ratio of the weight of a given
volume of aggregate to the weight of an equal volume of water.
ƒ
Oven-dry (no water in sample).
ƒ
Saturated surface-dry (SSD, water fills the aggregate pores).
ƒ
Submerged in water (underwater).
Using these three weights and their relationships, a sample's apparent specific
gravity, bulk specific gravity, and bulk SSD specific gravity as well as absorption can
be calculated. Also effective specific gravity can be calculated by known theoretical
maximum density of bituminous mixtures. Aggregate specific gravity is needed to
determine weight-to-volume relationships and to calculate various volume-related
quantities such as voids in mineral aggregate (VMA), and voids filled by asphalt
(VFA). Absorption can be used as an indicator of aggregate durability as well as the
volume of asphalt binder it is likely to absorb.
The mass of a coarse aggregate sample is determined in SSD, oven-dry and
submerged states. These values are then used to calculate bulk specific gravity, bulk
SSD specific gravity, apparent specific gravity and absorption. Figure 3.2 shows major
coarse aggregate specific gravity CASG equipment and Figure 3.3 shows the major
equipment used to perform the aggregate fine specific gravity FASG test.
25
Figure 3.3
Figure 3.4
Major CASG equipment
Major equipment used in performing the FASG test
26
3.2.2
Asphalt Binders
One binder type was used in this study. Polymer-modified asphalt binders
meeting Malaysia PG76 specifications (JKR/SPJ/rev2007), for high-volume traffic
mixtures (greater than 30 million equivalent single axle load; EASLs). Based on
viscosity test, 200°C to mixing temperature and 180°C, for short term again.
3.3
Aggregate Structure Design
The main aim of this task was to design the aggregate structures using an
analytical aggregate gradation method that will allow a rational blending of different
sizes of aggregate to achieve a densely packed aggregate skeleton in order to minimize
the binder content and maximize the volume filled by mineral aggregates for stiffness
and bearing capacity purposes.
The 0.45 Power Maximum Density Graph for aggregate gradation evaluation
was utilized for this study. This graph uses Fuller and Thompson's equation with n =
0.45 and is convenient for determining the maximum density line and adjusting
gradation (Roberts et al., 1996). This graph is slightly different than other gradation
graphs because it uses the sieve size raised to the nth power (usually 0.45) as the x-axis
units. Thus, a plot of Fuller and Thompson's maximum density equation with n = 0.45
appears as a straight diagonal line. This straight line goes from zero to the maximum
aggregate size for the gradation being considered. There is some debate as to whether
this line should end at maximum aggregate size or nominal maximum aggregate size or
somewhere in between, however the most commonly accepted practice is to end it at the
maximum aggregate size.
27
3.4
Asphalt Mixture Design
Mixture design was performed on all the aggregate structures that were
formulated using the 0.45 Power Maximum Density Graph for aggregate gradation and
evaluation. The Superpave mixture design method was followed for all the mixtures
designed in phase one except for VMA and VFA requirements, phase two drain down
excepted for PA and SMA and phase three cantabro test excepted for PA . The
Superpave mixture design method specifies the number of gyrations to which a sample
must be compacted with the Superpave Gyratory compactor (SGC) which shown in
Figure 3.4. The number of gyrations specified for mixture design is determined
according to volume of traffic expected on the road. 50 blows of Marshall hammer that
recommended by (JKR/SPJ/2007) was equivalent to 100 gyrations in this study. For
every aggregate structure, trial asphalt content was estimated. The aggregates were then
batched out in the appropriate quantities to produce a final mix specimen of
approximately (PA, 4000g),(SMA,4600g) and (GPA,4700g).
The aggregate batches, asphalt binder and mixing equipment were heated for
four hours at 200°C to achieve appropriate uniform mixing temperature. The binder and
the aggregate were then mixed until a uniform mix is obtained. The resulting mix was
then placed in a flat pan and heated for two hours at the compaction temperature of
180°C for short term aging. This aging represents the aging that occurs in the field
between mixing and placement and allows for absorption of the asphalt binder into the
aggregate pores.
For each trial, two specimens were compacted at the estimated asphalt content to
the target design number of gyrations using the Superpave gyratory compactor. The
bulk specific gravity and density of the compacted specimens using an automatic
vacuum sealing method-(corelok system) were then determined according to ASTM
D6752-02 standard test procedure. Another set of two identical specimens in the loose
condition of the same mix was used for the maximum theoretical density determination
which was done using the Rice method according to AASHTO T 209 standard. The air
28
void was then calculated for that mixture at the estimated asphalt content and specified
number of gyrations. The design asphalt content was determined as the asphalt content
required achieving 4.0% air voids for (SMA, GPA) and 20% air void for (PA) at Ndes.
The mixtures were then further analyzed to determine the rest of volumetric and
physical properties at the design asphalt content.
Finally, for adequate optimum bitumen content that recommended by
(JKR/SPJ/2007) two tested were done .First, drain down test for both PA and SMA and
second, cantabro test just for PA one.
Figure 3.5
Superpave gyratory compactor
29
3.4.1 Bulk specific gravity (corelok system)
This test method covers the determination of the bulk specific gravity of
compacted bituminous mixtures and/or of bituminous cores used for pavement density
determination. This test method should be used with samples that contain open or
interconnecting voids. Mixes such as Stone Matrix Asphalt (SMA), open graded friction
courses (PASB, PASSRC), and Superpave coarse graded mixtures with significant
surface texture should be sealed for accurate bulk specific density results ASTM
D6752-02.
Vacuum-sealing device utilizes an automatic vacuum chamber (shown in Figure
3.5) with a specially designed, puncture resistant plastic bag, which tightly conforms to
the sides of the sample and prevents water from infiltrating into the sample.
Lab compacted specimens or field cores are placed into puncture resistant
polymer bags. The specimen and bag are then placed inside a vacuum chamber, which
is completely evacuated of air before the bag is automatically sealed. The bag tightly
conforms to the specimen’s surface and prevents the infiltration of water into the
specimen. Then the specimen’s density is measured by performing the water
displacement method. Gravity Suite TM software used to calculate input data.
Figure 3.6
Vacuum-sealing device
30
3.4.2
Theoretical Maximum Density (TMD) Test
The theoretical maximum density of bituminous mixtures is intrinsic properties
which is the values are influenced by the composition of the mixtures in term of types
and amounts of aggregates and bituminous materials. The test was conducted for
determining the density and maximum theoretical specific gravity of loose bituminous
mixture using the Rice method. The test apparatus as illustrated in Figure 3.6 and
procedure was carried out in accordance to AASHTO T 209.
Figure 3.7
Apparatus for TMD test
3.4.3 Analysis of Volumetric Parameters
When all Superpave testing were completed, each parameter needs to be
analyzed to determine the optimum bitumen content. The specimens were tested to
determine their volumetric composition. Plots were prepared, for percentage of bitumen
content versus:
i.
Air Voids in the Compacted Mix (VIM).
ii.
Voids in Mineral Aggregate (VMA).
iii.
And Void Filled with Bitumen (VFB).
31
3.4.3.1 Analysis of Air Void in the Compacted Mix (VIM)
Void in Mix or Air Voids is the total volume of the small pockets of air between
the coated aggregate particles throughout a compacted paving mixture, expressed as a
percent of the compacted mixture. To find the VIM percentage, the following equation
can be used:
VIM or Va, % = 100 x [1 – (Gmb/Gmm)] …………………………………Equation 3.2
Where:
Gmb = bulk specific gravity of compacted mixture; and
Gmm = theoretical maximum specific gravity.
Noted, when conducted bulk specific gravity compacted bituminous mixtures
test in this study air void of compacted mixtures resulted automatically by input the
maximum specific gravity (Gmm) in the Gravity Suite TM software.
3.4.3.2 Analysis of Void in Mineral Aggregate (VMA)
Void in Mineral Aggregate may be defined as the volume of inter-granular void
space between the aggregate particles of a compacted paving mixture that include air
voids and the effective bitumen content (volume of bitumen not absorbed into the
aggregate). This value can be obtained using the following formula:
VMA, % = 100 – [Gmb x Ps / Gsb] …………………………………Equation 3.3
Where:
Gmb = bulk specific gravity of compacted mixture;
Gsb = combined bulk specific gravity of the total aggregate and
Ps = percent of aggregate in the mixture.
32
3.4.3.3 Void Filled with Bitumen (VFB)
Void Filled with Bitumen (VFB) is the percent of the volume of the VMA that
filled with bitumen. The following formula was used to calculate the VFB:
VFB= (VMA-Va)/VMA×100…………………………………Equation 3.4
3.4.4
Determination of Optimum Bitumen Content (OBC)
The optimum bitumen content was the value that gives the required air voids or
VIM, the minimum VMA requirement and meets the VFB range. The optimum bitumen
content was determined from the plotted smooth curve when the percent of air voids
were 4.0% for SMA & GPA mixtures and 20% for PA mixture.
3.4.5
Binder Drain-down Test
Binder drain-down test is recommended by JKR 2007 for SMA and PA
mixtures. The test developed for this purpose by AASHTO T 305 is anticipated to
simulate conditions that the mixture is likely to encounter as it is produced, stored,
transported, and placed. Drain-down is considered to be that portion of the mixture
(fines and bitumen) that separates itself from the sample as a whole and flows
downward through the mixture.
Binder drain-down test was conducted on three loose mixtures at the mean of
optimum binder content to ensure that the binder draining property of the mixtures was
within acceptable levels. It was also provides an evaluation of the mixture draindown
potential produced in the field. The important aspects of the test were to place the
33
samples of the SMA loose mixtures in a wire basket fabricated using standard 6.3mm
sieve cloth (Figure 3.7).
Figure 3.8
Drain-down test apparatus
The basket was positioned on a pre-weighted plate or pan which was placed in
an oven for three hours at an anticipated mix production temperature. At the end of
three hours, the basket containing the sample was removed from the oven along with
the pan and the pan was weighted. The mass of any binder that drain-down from the
bitumen to the pan was measured. This mass was then expressed as a percentage by
weight of the total mixture and should meet the criterion in JKR 2007.
3.4.6 Cantabro Test on Air Cured Samples
Cantabro test is recommended by JKR 2007 for PA mixture. This test generally
considered as good indicator for the bonding properties between binder and aggregates.
Cantabro Test on air-cured samples was used to measure the resistance of the mixes to
raveling.
34
Three superpave specimens were prepared and compacted with SGC to obtain
specimens with diameter of 100 mm and height of 60±5 mm. The specimens were
conducted at the optimum binder content to ensure that the percentage abrasion loss of
the mixtures was within acceptable levels. Each test specimen was weighed to the
nearest 0.1 g (P1) then placed in a Los Angeles Machine (ASTM Method C131)
without the steel balls. The total number of rotations considered in this research was
three hundred accordant to (JKR, 2007). After three hundred rotations, the weight of the
sample was recorded to the nearest 0.1 g (P2). Test performed at temperature of
25Cºand speed of 30 to 33 rpm. The percentage abrasion loss (P) was calculated
according to the following Equation:
P=
P1 − P2
*100 …………………………………equation 3.5
P1
Where:
P1=initial weight to the nearest 0.1g, and
P2=final weight to the nearest 0.1g.
3.5
Experimental Program
After the determination of optimum asphalt content, sets of 108 specimens of
100mm diameter were prepared and compacted with the SGC to different air void. All
samples were tested to determine porosity and air void content using the CORELOK
machine. After porosity test the samples were divided into two sets. One set of 54
specimens were used to determine the indirect tensile strength (ITS). The other set of 54
specimens were used to identify the abrasion resistance of the mixtures. The summaries
of the total experimental program design for this study are shown in Table 3.1. The
relative performance of the mixtures with different air void content was then evaluated
35
Table 3.1 : Summaries of the Total Experimental Program Samples
ITS
&CAT
TEST
PA
SMA
GPA
Nominal
air void
(%)
19
20
21
3
4
5
3
4
5
Condition
Dry/
wet
Dry/
wet
Dry/
wet
Dry/
wet
Dry/
wet
Dry/
wet
Dry/
wet
Dry/
wet
Dry/
wet
Repetition
3
3
3
3
3
3
3
3
3
Total
18
Total All
Specimens
18
18
3×18×2=108
3.5.1 Determination of sample porosity using the (Corelok system)
The approach in this technique is to determine a fundamental parameter that is
not based on any assumptions. In this method a sample is vacuum-sealed inside a bag
and a sealed density, P1 is calculated. The same sample, while under water, is opened
and a second density, P2 is determined. Since the sample is under complete vacuum
prior to opening the bag, P2 will yield an apparent density of the compacted sample.
The density P2 includes the volume due to inaccessible air voids (Corelok Operator’s
Guide, 2007). In this method, a standard equation can be used for calculation of %
porosity,
⎛ P 2 − P1 ⎞
% Porosity = ⎜
⎟ × 100 …………………………………Equation 3.6 ⎝ P2 ⎠
Where:
P1= the Corelok vacuum sealed density of compacted sample
P2 = density of the vacuum sealed sample after opening under water
ƒ
Definitions:
i.
% porosity defines as the % air void in the compacted sample that
is accessible to water and that are interconnected.
36
ƒ
Indications:
i.
It is expected that the %P will increase in air void content as
determined by the ratio of Corelok machine bulk density (Gmb)
and maximum density (Gmm).
ii.
It is expected that increase in %P will indicate higher potential of
mix permeability. Studies have shown that mixture with %P
larger then 7 % are highly permeable.
iii.
Since the Corelok method is fast, %P can be a quick indicator of
field permeability.
iv.
This method can also be used during design to determine the
permea-bility potential of mixes.
ƒ
Procedure:
i.
Set Corelok to program # 2 using the up and down arrows on the
front
ii.
panel.
Inspect an appropriate size bag for holes or stress point. Do not
use the bag if it is damaged.
iii.
Obtain an empty bag weight, record in column A of the porosity
data sheet as shown in table 3.5.
iv.
Weight in appropriate size compacted and dry asphalt sample.
v.
Record the dry sample weight in column B.
vi.
Seal the sample inside the bag using the procedure outlined in the
corelok manual.
vii.
Submerge the sealed sample and wait until the scale stabilizes.
viii.
Record the weight in column C.
ix.
While the sample is still submerged under water, cut the bag open
with scissors.
x.
Allow water to inter the gag.
xi.
Leave the sample under the water for 4 minutes. Make sure the
bag is not floating out of the water and it is not touching the sides
of o the bottom of the tank.
xii.
Record the weight in column D.
37
Table 3.2 : Corelok TM % Porosity Data Collection Table
Sample ID
ƒ
A
B
C
D
Bag Weight
Dry Sample
Sealed Sample
Sample weight
(g)
Weight before
Weight in
after Cutting
sealing (g)
Water (g)
the bag (g)
Calculations:
The calculation performed by using the porosity program in the provided
Gravity Suite TM software. Just input the weight in the columns
provided and the program will automatically calculate % porosity. Also,
input the maximum specific gravity (Gmm) in the program, % air void
calculated for purpose of this study.
Alternatively, can be use the standard equations given in ASTM D6752
to calculate the bulk sealed density of the sample, P1, and PS 132-01 to
calculate the maximum (or apparent) density, P2, of the compacted
sample. Use the equation given above to calculate % porosity.
38
3.5.2
Indirect Tensile Test IDT
The indirect tensile test (IDT) was used to determine the effect of water on the
indirect tensile strength (ITS) of asphalt mixtures according ASTM standard D 4867
and to compare compacted specimens with different porosity and air void content.
After the porosity test, the same specimens were divided into 2 subsets, dry and
wet as shown in previous Table 3.1. The dry subset was stored at 25oC for 5 days. The
wet subset was tested after conditioning in water. It was partially saturated applying a
partial vacuum of 370 to 410 mbar for 5 minutes using a vacuum chamber shown in
previous Figure 3.6 without any freeze/thaw cycle, because the temperature in Malaysia
never falls below the freezing point. Afterwards the wet subset was immersed in a water
bath for 24 hours at 60oC for 2 hours at 25oC according to the procedure ASTM
designation D 4867/D 4867 M – 96. Based on the maximum load Fmax determined
with the IDT, the indirect tensile strength (ITS) for a cylindrical specimen of diameter
‘d’ and the height ‘h’ was estimated by using the following equation:
ITS =
2 * Fmax
…………………………………Equation 3.7
π*h *d
Where:
h = height of the sample, and
d = diameter of the sample
3.5.3
CANTABRO Test
The CANTABRO test was used to evaluate the effect of water on the abrasion
resistance of a paving mixture. CANTABRO test is generally considered as good
indicator for the bonding properties between binder and aggregates. Again, after
porosity test the same specimens were divided in 2 subsets, dry and wet ones as shown
in previous Table 3.1. The samples were stored at 25oC for 5 days to dry before tested.
39
3.5.3.1 Cantabro Test on Air Cured Samples
Cantabro Test on air-cured samples was used to measure the resistance of the
mixes to raveling.
The initial weight of the specimen was recorded. Specimen was placed in a Los
Angeles Machine (ASTM Method C131) without the steel balls. The total number of
rotations considered in this research was three hundred according (JKR, 2007). After
three hundred rotations, the weight of the sample was recorded. Test performed at
temperature of 25 C° and speed of 30 to 33 rpm.
3.5.3.2 Cantabro Test on Water Soaked Samples
Cantabro Test was performed on water soaked samples to evaluate the resistance
to stripping of the mix.
In this test the initial weight of the specimen was recorded. The subset was
partially saturated applying a partial vacuum of 370 to 410 mbar for 5 minutes using a
vacuum chamber. The samples were then placed in a water bath at 60 C° for 24 hours.
On the next day the samples were taken out of the bath and allowed to drain for 18
hours. Using Los Angeles Machine (ASTM Method C131) the testing procedure
conducted was similar to the Cantabro test on air cured samples. The percentage
abrasion loss (P) for both conditions dry and wet was calculated according to following
equation:
P=
P1 − P2
*100 …………………………………equation 3.8
P1
Where:
P1=initial weight to the nearest 0.1g, and
P2=final weight to the nearest 0.1g.
CHAPTER 4
RESULTS AND DISCUSSIONS
4.1
Introduction
This chapter includes a summary of the data generated from the lab testing of
mixtures selected for this project. Several tests were conducted to determine the optimum
bitumen content, porosity, air void, indirect tensile strength and abrasion resistance of
specialty hot mix asphalt. These data were analyzed to get the relationship between
porosity and air void content and their related with indirect tensile strength and abrasion
resistance to evaluated the moisture damage of mixtures selected in this project. The results
of each laboratory tests were shown in Appendices and then were further analyzed in
detail in this chapter.
4.2
Results of Materials Tests
The constituents of a hot mix asphalt are aggregate (both coarse and fine),
mineral filler, and bitumen. All these materials were tested for their specific gravity and
aggregate gradation. Besides that, the aggregates obtained from the Hanson Quarry
were also tested for the total amount of coated dust.
41
4.2.1
Sieve Analyses
Two types of sieve analysis were performed on the aggregates, one being the dry
sieve and the other being the wash sieve analysis. The dry sieve analysis was performed
to separate the aggregates according to the sieve sizes used in the gradation so as to
make it easier to batch the mixes. The gradation of each mix will be further discussed in
Section 4.3.
Wash sieve analysis were conducted to determine the total amount of dust
coated on the aggregates. This is so to calculate the amount of filler and/or dust that
might need to be added to the mix. Therefore, the wash sieve analysis was conducted
for every mix and the result can be viewed in Appendix A.
4.2.2
Determination of Materials Specific Gravity
The specific gravity test has been carried out for all the materials used in the
study, including aggregates, mineral filler, and bitumen. The aggregates were divided
into coarse and fine with the earlier defined as aggregates larger than 4.75mm and the
latter being defined as aggregates smaller than 4.75mm until 0.075mm. This
categorization is in accordance with AASHTO standard. In this study, the specific
gravity for the aggregates has been determined based on the gradation of each mix
selected.
4.2.2.1 Specific Gravity of Coarse Aggregate
As the samples for testing specific gravity of aggregate is based on each mix
selected in this study, the coarse sizes are in the range of 5-10mm for PA, 4.75-9.50mm
SMA and 4-20mm for GPA. The full results of the test conducted are shown in
Appendix B-1.
42
4.2.2.2 Specific Gravity of Fine Aggregate
The specific gravity testing for fine aggregate also utilizes the gradation of each
mix selected. The sizes of aggregates tested range from 0.075- 3.36mm for PA, SMA
and 0.075-2mm for GPA. The full results of the test conducted are shown in Appendix
B-2.
4.2.2.3 Specific Gravity of Mineral Filler
Functioning as an anti stripping agent, the mineral filler chosen for this study
was Ordinary Portland Cement (OPC) accordant to JKR 2007. The previous Studies
conducted at the Transportation and Highway Laboratory of Universiti Teknologi
Malaysia has found that the specific gravity for OPC is 2.980. This value was used in
determining the blend specific gravity of aggregate.
4.2.2.4 Blend Specific Gravity of Aggregate
Based on the mix, the percentage of coarse aggregate, fine aggregate and
mineral filler varies accordingly. The determination of SG
blend
was done for each mix.
Table 4.1 shows the values of percentage and blend specific gravity of aggregate and
calculated these values’ are shown in Appendix B-3.
Table 4.1 : Values of bulk specific gravity of aggregate
Mix
Type
PA
SMA
GPA
Coarse
%
60
68.5
52
Fine
%
38
29.5
46
OPC
%
2
2
2
Gsb
GbulkSSD
Gsa
2.625
2.633
2.658
2.655
2.658
2.683
2.705
2.701
2.724
Absorption
%
1.175
0.996
0.944
43
4.2.2.5 Specific Gravity of Bitumen
The bitumen provides the cohesive forces that hold the aggregate particles
together. The cohesive forces grow with increasing bitumen viscosity. In this study,
bitumen of PG 76 has been used. Based on previous studies conducted at Transportation
and Highway Laboratory of Universiti Teknologi Malaysia, the specific gravity of
bitumen is taken as 1.03. This value was used in the determination of effective specific
gravity of aggregate.
4.3
Aggregate Gradation
Aggregate gradation influences such key HMA parameters as stiffness, stability,
durability, permeability, workability, fatigue resistance, frictional resistance and
resistance to moisture damage (Roberts et al., 1996). Additionally, the maximum
aggregate size can be influential in compaction and lift. A good gradation will lead to
the durability and strength of a pavement. For all the three mixes, the gradation limits
was in accordance with JKR 2007 Standard Specification as described in Section 2.2.
The aggregate gradation was designed based on the mean of gradation limit. The mean
values for each mix design was selected and plotted in the graph of percentage
aggregate passing versus sieve size to the power of 0.45. Table Figure 4.2 to 4.4
illustrated the graph for each mix type while Figure 4.1 to 4.3 tabulated the percentage
of aggregate passing on each sieve size.
Table 4.2 : Percentage aggregate passing on each sieve size for PA Mix design
SIEVE SIZE
(mm)
14
10
5
2.36
0.075
GRADATION
^0.45
3.28
2.82
2.06
1.47
0.31
LIMIT
LOWER
UPPER
100
100
95
100
30
50
5
15
2
5
%
PASSING
100
97.5
40
10
3.5
44
Figure 4.1
Traffic flow of Larkin interchange
Table 4.3 : Percentage aggregate passing on each sieve size for SMA Mix design
SIEVE SIZE
(mm)
12.5
9.5
4.75
2.36
0.6
0.3
0.075
GRADATION
^0.45
3.12
2.75
2.02
1.47
0.79
0.58
0.31
Figure 4.2
LIMIT
LOWER
UPPER
100
100
72
83
25
38
16
24
12
16
12
15
8
10
%
PASSING
100
77.5
31.5
20
14
13.5
9
Gradation limit and design curve for SMA
45
Table 4.4 : Percentage aggregate passing on each sieve size for GPA Mix design
SIEVE SIZE
(mm)
25
20
14
10
4
2
0.6
0.3
0.075
GRADATION
^0.45
4.26
3.85
3.28
2.82
1.87
1.37
0.79
0.58
0.31
Figure 4.3
4.4
LIMIT
LOWER UPPER
100
100
76
100
64
89
56
81
41
55
16
31
12
16
6
10
3
7
%
PASSING
100
88
76.5
68.5
48
23.5
14
8
5
Gradation limit and design curve for GPA
Asphalt Mixture Design Results
All the Superpave compacted specimens were prepared according to AASHTO
T 312 standard method. ASTM D6752-02 standard test procedure for Determination of
Bulk Specific Gravity and air void of Compacted Sample. For theoretical maximum
46
density test, procedure was carried out in accordance to AASHTO T 209. After
conducted the tests, all the results were tabulated in Appendix C.
The analysis was carried out to obtain the parameter values which were density,
air voids, and voids in mineral aggregate and void filled with bitumen. The plotted
graphs for air voids versus bitumen content that have been drawn were attached also in
Appendix C. The adequate OBC tests which drain-down and cantabro recommended by
JKR-2007 done in this study. The results of all parameter values at desired air voids of
4±1% for (SMA & GPA) and 20±1% for PA mixtures were summarized in Table 4.5
below.
Table 4.5 : Mix design results
Properties
PA
SMA
GPA
4.5
6.7
6.2
Gmb
1.985
2.610
2.282
_
Gmm
2272
2.369
2.361
_
20
4
4
(3-7%) for (SMA&GPA) and
OBC (%)
VIM (%)
JKR 2007 Specification
(4-7%) for (SMA&GPA) and
(4- 6%) for (PA)
(18- 25&) for (PA)
4.5
VMA (%)
27.8
19.4
19.5
Min 17 %
VFA (%)
28.6
79.30
81.1
Max 17 %
Draindown (%)
0.08
0.12
_
Max 0.3%
Cantabro (%)
9.9
_
_
Loss Max 15%
Relationship between air void and porosity
The porosity was measured on samples of various void contents prepared from
three different mixtures, i.e., SMA, PA, and GPA. That the air void contents of asphalt
47
mixtures were changed by altering compaction efforts (75, 100 and 125Gyr).details’ of
results as shown in Appendix D.
The porosity of these samples fitted linear relationships to the air void content,
as shown in Figure 4.4. The GPA and SMA have similar porosity between 3.8% and 4%
air void. SMA porosity trend line increase more than GPA after 4% air void and start to
porosity content (%)
decrease before 3.8% air void as shown in Figure 4.5.
y = 0.0278x2 - 0.2134x + 12.154
R2 = 0.9588 PA
25
20
y = -0.0849x2 + 1.6639x - 2.6004
R2 = 0.9133 G PA
15
10
y = -0.1716x2 + 2.5765x - 4.7934
R2 = 0.9011 SM A
5
0
0
5
10
15
20
25
air void conte nt (%)
Figure 4.4
Relationship between porosity and air void
The results of average standard deviation (SD) and coefficient of variation (CV)
are presented in Table 4.6. There is a relationship which can define porosity to air voids
and PA mixture. Also it shows that good models for SMA and GPA mixes. This table is
useful to specify the maximum mixes air voids for a specific mix.
48
y = -0.1716x2 + 2.5765x - 4.7934
R 2 = 0.9011 SM A
y = -0.0849x2 + 1.6639x - 2.6004
R 2 = 0.9133 GP A
Porosity content (%)
5
4
3
2
1
0
0
1
2
3
4
5
6
7
Air void content (% )
Figure 4.5
Relationship between porosity and air void content for SMA and GPA
Table 4.6: Standard deviation (SD) and coefficient of variation (CV)
Mix
Type
PA
SMA
GPA
4.6
Target
VTM
%
20%
21%
22%
3%
4%
5%
3%
4%
5%
Total
Sample
in
series
12
12
12
12
12
12
12
12
12
VTM
mean
%
VTM VTM
SD CV %
20.35
21.40
22.56
3.28
4.69
5.77
3.21
4.66
5.74
0.31
0.27
0.39
0.54
0.36
0.30
0.49
0.33
0.49
1.51
1.28
1.72
16.49
7.77
5.14
15.40
7.10
8.50
Porosity
mean %
Porosity
SD
Porosity
CV %
19.33
20.31
21.47
1.74
3.53
4.33
1.84
3.28
4.16
0.37
0.38
0.40
0.90
0.55
0.35
0.66
0.33
0.48
1.91
1.88
1.88
51.81
15.69
7.99
35.88
10.04
11.57
Retained Strength or Stiffness
The air void, porosity content and the ITS for dry specimens are given in Table
4.7. Figures 4.6 and 4.7 showed the influence of air void and porosity content on ITS in
the dry test. It can be seen that the indirect tensile strength decreases with increasing air
49
void and porosity content which is similar to previous researches (Gulber et al.2005;
Jian et al.2004; Walaa et al.2002). Moreover, the SMA trend line is higher as compared
with other mixes, which could be due to less fine aggregate and high OBC. Note that
the value of the SMA and GPA graded mixture with 6% nominal air void and 4%
porosity content is slightly equal to the value of the PA graded with nominal 20% air
void and 18 % porosity content.
y = -166.26x + 1757.2
R 2 = 0.8936
indirect tensile strenght (kpa)
1500
1300
y = -66.693x + 1253.1
R 2 = 0.5393
1100
900
700
y = -102.34x + 1404.2
R 2 = 0.9303
500
y = -118.85x + 1321.4
R 2 = 0.9307
300
100
0
1
2
3
4
5
6
7
8
air void & porosity content (%)
Linear (SMA Air void)
Linear (SMA Porosity )
Effect of air voids and porosity for SMA&GPA) on ITS, dry
indirect tensile strenght (kpa)
Figure 4.6
Linear (GPA Air void)
Linear (GPA Porosity)
y = 26.469x2 - 1149.1x + 12720
R 2 = 0.9652 P A P o ro sity
800
y = 31.592x2 - 1418.9x + 16186
R 2 = 0.863 P A VTM
700
600
500
400
300
200
100
18
19
20
21
22
23
24
air void & porosity content (%)
Linear (PA Air void)
Figure 4.7
Linear (PA Porosity)
Effect of air voids and porosity for PA on ITS, dry
50
Table 4.7: Air void, porosity and indirect tensile strength of dry specimens
Sample
ID
Target
VTM
VTM
(%)
Porosity
(%)
ITS (kpa)
ITS average
(kpa)
Standard
deviation
Porous Asphalt (PA)
PA-2
PA-4
PA-13
PA-22
PA-17
PA-19
PA-16
PA-30
PA-29
20 %
21 %
22 %
19.90
20.43
20.72
18.83
19.48
19.78
619.57
518.52
498.52
21.18
21.47
21.56
19.77
20.45
20.45
521.27
474.82
474.29
490.13
26.97
21.87
22.74
23.06
20.80
21.59
21.78
339.17
409.13
402.09
383.47
38.52
1227.99
40.53
972.31
163.79
783.55
33.80
1068.45
70.63
935.44
29.96
816.19
110.79
545.54
64.89
Stone Mastic Asphalt (SMA)
SMA-32
SMA-25
SMA-23
SMA-22
SMA-16
SMA-12
SMA-15
SMA-11
SMA-4
3%
4%
5%
2.39
3.39
4.07
0.51
1.63
3.89
1272.52
1218.18
1193.27
4.15
4.86
5.07
3.76
3.41
4.04
1152.35
932.45
832.12
5.38
5.96
6.01
4.1
4.54
4.42
814.95
787.92
747.78
Gap Graded Asphalt (GPA)
GPA-1
GPA-22
GPA-7
GPA-4
GPA-30
GPA-16
GPA-29
GPA-21
GPA-31
3%
4%
5%
2.59
3.41
3.56
1.59
2.22
2.32
1137.64
1071.26
996.46
4.10
4.96
4.98
2.85
3.41
3.78
970.04
918.19
918.10
5.20
5.59
6.43
3.83
4.00
4.88
879.10
881.20
688.27
The air void porosity content and the indirect tensile strength for the wet
specimens are given in Table 4.7. Figures 4.8 and 4.9 showed the influence of air void
content on ITS in the wet test. It can be seen that the wet series also influence by the
increase in air voids, seen by the reduction of the indirect tensile strength. The SMA
trend line is still above the other mixes. This confirms the previous note on the effect of
fine aggregate and the binder.
51
Table 4.8 : Air void, porosity and indirect tensile strength of wet specimens
Sample ID
Target
VTM
VTM (%)
Porosity
(%)
ITS (kpa)
ITS average
(kpa)
Standard
deviation
387.02
99.03
307.38
13.98
260.96
7.45
Porous Asphalt (PA)
PA-10
PA-1
PA-9
PA-6
PA-24
PA-14
PA-36
PA-33
PA-32
SMA-31
SMA-28
SMA-34
SMA-13
SMA-14
SMA-21
SMA-1
SMA-5
SMA-20
20 %
21 %
22 %
3%
4%
5%
19.90
18.71
501.32
20.41
19.79
332.85
20.75
19.77
326.90
21.00
19.97
323.48
21.51
20.31
298.36
21.69
20.59
300.29
21.87
21.21
268.16
22.74
21.32
261.46
23.06
22.44
253.27
Stone Mastic Asphalt (SMA)
2.67
3.36
3.80
0.78
1.61
2.18
1195.07
990.64
1037.20
1074.31
107.15
4.37
4.78
4.89
3.12
3.04
3.18
914.67
746.33
700.62
787.21
112.73
5.41
5.94
5.96
3.80
4.62
4.42
656.21
605.31
597.57
619.70
31.86
Gap Graded Asphalt (GPA)
GPA-6
GPA-9
GPA-2
GPA-23
GPA-20
GPA-26
GPA-15
GPA-32
GPA-34
3%
4%
5%
2.17
3.54
3.93
0.62
1.38
2.8
719.08
676.19
643.88
679.72
37.72
4.17
4.74
5.05
2.75
3.23
3.82
670.14
612.30
537.92
606.79
66.28
5.18
5.72
6.32
3.82
4.31
3.68
547.55
532.01
520.02
533.19
13.81
Comparing the regression curves in Figure 4.8 of SMA and PA mixes of the dry
and wet test, it can be seen that the slopes for both gradation are similar. This means
that the ITS of the wet and dry series decreases almost equally fast with air void and
porosity content. Although the porosity of SMA and GPA similar, it can be noted that
the regression curves of GPA increase slowly than the SMA. In this case this regression
curves may be attributed to the influence of water, high permeability, the fewer points
of contact and interlocking in the aggregate skeleton (Gubler,2005).
52
y = -183.28x + 1665.7
R 2 = 0.9475
indirect tensile strenght (kpa)
1500
1300
y = -159.78x + 1302
R 2 = 0.8928
1100
900
700
500
y = -56.164x + 861.3
R 2 = 0.8843
300
y = -55.647x + 769.86
R 2 = 0.8354
100
0
1
2
3
4
5
6
7
8
air void & porosity content (%)
Linear (SMA Air void)
Linear (SMA Porosity )
Effect of air voids and porosity for (SMA&GPA) on ITS-wet series
indirect tensile strenght (kpa)
Figure 4.8
Linear (GPA Air void)
Linear (GPA Porosity)
800
700
y = 26.469x2 - 1149.1x + 12720
R 2 = 0.9652 P A P o ro sity
600
500
400
300
200
100
18
19
20
21
22
23
24
air void & porosity content (%)
Linear (PA Air void)
Figure 4.9
y = 31.592x2 - 1418.9x + 16186
R 2 = 0.863 P A VTM
Linear (PA Porosity)
Effect of air voids and porosity for( PA) on ITS –wet series
The tensile strength ratio (TSR) was obtained by comparing the ITS of wet
specimens with that of the corresponding dry specimens. The TSR, air void and
porosity for each series is summarized in Table 4.8.
53
1400
y = 0.9871x - 154.74
1200
R 2 = 0.9484
PA
ITS wet
1000
800
SMA
y = 0.8001x - 60.007
R2 = 0.7703
600
GPA
400
y = 0.5045x + 132.28
R 2 = 0.7592
200
0
0
200
400
600
800
1000
1200
1400
ITS dry
Figure 4.10
Comparing the ITS of wet and dry
Table 4.9 : Percentage change of TSR between wet and dry series of the mixes
Mix Type
PA
SMA
GPA
Air void average
%
20.35
21.4
22.56
3.28
4.69
5.78
3.20
4.67
5.74
Porosity average
%
19.36
20.22
21.39
1.77
3.43
4.32
1.82
3.31
4.09
TSR %
70.23
62.73
68.65
87.39
81.2
79.09
63.56
64.79
66.07
From Figure 4.9 it can be note that TSR for the SMA graded mixtures decreases
with increasing air void content. This could mean that a SMA graded mixture with
higher air void content becomes more water susceptible. However, in the case of GPA
graded mixtures, the TSR is slightly increasing with increasing air void content. PA
mixtures are demonstrated as a curve-up trend. In general there are not TSR
discriminate between different mixes, air void and porosity content. Note that SMA
graded mixtures show better TSR values.
54
y = -3.3154x + 93.068
R 2 = 0.9891
Tensile strength ratio (%)
100
y = 5.5413x2 - 238.49x + 2628.8
R2 = 1
y = -3.3754x + 98.023
R 2 = 0.9592
90
80
70
y = 0.9793x + 60.365
R 2 = 0.9899
60
y = 1.0713x + 61.516
R 2 = 0.9646
50
y = 6.7886x2 - 277.41x + 2896.5
R2 = 1
40
30
0
2
4
6
8
10
12 14 16 18
20 22 24
Air void & porosity content (%)
Linear (SMA air void)
Linear (GPA air void)
Linear (SMA porosity)
Linear (GPA porosity)
Poly. (PA air void)
Poly. (PA porosity)
Figure 4.11
4.7
Effect of air voids and porosity on the tensile strength ratio
CANTABRO Test
The results of CANTABRO test are shown in Table 4.9. Note that the
percentage of air void and porosity were taken as average of both series, dry and wet
condition.
The averages of weight loss for each series are plotted in Figure 4.10.
Comparing the values of the both SMA and GPA graded dry series, it can be noted that
the percentage of weight loss is not significantly different from a statistic point of view.
Therefore no high difference is observed between the SMA series with 3.22% and
5.77% air void content, also between GPA series with 3.22%and 5.75 %. Considering
the both graded wet series, the SMA weight loss is slightly increased. However both
series show lower percentage of weight loss in wet condition; thus water not influences
the abrasion resistance.
55
Table 4.10 : CANTABRO Test results Mixture type
Average of air
void %
Average of
porosity %
Average of
mass loss %
Standard
deviation
20.35
21.40
22.57
3.27
4.64
5.77
3.22
4.67
5.75
19.26
20.37
21.38
1.72
3.63
4.13
1.86
3.27
4.24
14.31
17.7
19.61
4.01
5.67
5.74
2.65
3.07
4.1
2.49
1.35
1.52
0.33
0.88
0.66
0.51
0.22
0.55
20.35
21.40
22.57
3.27
4.64
5.77
3.22
4.67
5.75
19.26
20.37
21.38
1.72
3.63
4.13
1.86
3.27
4.24
28.56
34.78
37.36
4.46
8.69
11.28
6.13
6.58
7.16
7.20
1.77
5.12
0.30
4.20
2.29
0.86
2.01
0.62
Dry series
Porous
Asphalt
(PA)
Stone mastic
asphalt
(SMA)
Gapgraded
asphalt
(GPA)
Wet series
Porous
Asphalt
(PA)
Stone mastic
asphalt
(SMA)
Gapgraded
asphalt
(GPA)
28.50
34.78
37.36
Cantabro loss value
40
6.58
7.16
4.46
8.69
11.28
6.36
5
4.1
10
5.74
2.65
3.07
15
4.01
5.67
20
19.61
30
25
14.31
17.7
Mass loss (%)
35
0
Dry
Wet
Condition
Figure 4.12
Average weight loss
PA 20.35
AV&19.26 P
PA 21.40
AV&20.37 P
PA 22.57
AV&21.38 P
SMA 3.27
AV&1.72 P
SMA 4.64
AV&3.63 P
SMA 5.77
AV&4.13 P
GPA 3.22
AV&1.86 P
GPA 4.67
AV&3.27 P
GPA 5.75
AV&4.24 P
56
Comparison increase weight loss between dry and wet test for different mixtures
as shown in Table 4.10. Figure 4.11 indicates that water leads to a higher abrasion with
increasing air void content for SMA, similar with PA and decrease with GPA graded.
Note The GPA graded demonstrated with rate weight loss similar with TSR, both value
decreases with increase air void. Interestingly, the series with PA graded mixtures
(20.35 %VTM & 19.26 porosity) it can acceptable by JKR specification.
Table 4.11 : Percentage increase of weight loss
Mixture type
Porous
Asphalt
(PA)
Stone mastic
asphalt
(SMA)
Gapgraded
asphalt
(GPA)
Average of air
void %
20.35
21.4
22.56
3.27
4.7
5.77
3.21
4.65
5.76
Average of
porosity %
19.31
20.33
21.22
1.67
3.81
4.47
1.93
3.28
4.51
increase of
weight loss %
49.79
49.11
47.51
10.09
34.75
49.11
58.33
53.34
42.74
Rate weight loss (%)
Rate of weight loss
70
60
50
PA
40
30
SMA
GPA
20
10
0
20.35-3.27-3.21 21.4-4.70-4.65 22.56-5.77-5.76
Air void content (%)
Figure 4.13
Rate of weight loss of the mixes for different air voids
CHAPTER 5
CONCLUSION AND RECOMMENDATIONS
5.1
Conclusions
This limited study was carried out to evaluate the effect of different Air void and
porosity on moisture damage of Malaysian specialty HMA. Based on the analyses
presented in Chapter 4, the following conclusions can be drawn:
ƒ
Results provide relationship between porosity and air voids for PA
mixture. In addition, study also able to establish good models for SMA
and GPA mixes compared to other researcher (Walaa,2002).
ƒ
The IDT is able to discriminate between wet conditioned and dry control
for SMA and PA graded.
ƒ
The IDT is able to discriminate between mixtures of different porosity.
ƒ
The Indirect Tensile Strength for PA and SMA (ITS) decreases as air
void condition increases for both dry and wet condition, however its
increase for GPA mixture.
ƒ
The Tensile Strength Ratio TSR shows only slight dependence on air
void content.
ƒ
The PA mixture with higher porosity appeared to have the similar TSR
compare with GPA.
ƒ
The CANTABRO test shows increasing percentage of weight loss with
increasing air void content for all mixes.
58
ƒ
The CANTABRO test shows significant difference between the behavior
of wet and dry condition specimens. The percentage of weight loss
increased for wet series.
5.2
Recommendations
Based on the conclusions above, several recommendations for future research
can be drawn in this chapter.
ƒ
Comparing the Superpave design result in this study with Marshall
method that recommended by JKR 2007.
ƒ
Propose laboratory testing uses the repeated loads to simulate traffic
movement on pavement for dry and wet conditions.
ƒ
Compacted samples at discriminate air voids.
59
REFRENCES
1. Hicks, R.G., Santucci, L. and Aschenbrener, T., 'Introduction and seminar
objectives', TRB (2003).
2. Little, D.N. and Jones IV, D.R., 'Chemical and mechanical process of moisture
damage in hot-mix asphalt pavements', TRB (2003).
3. Kandhal, P.S. and Rickards, I.J., 'Premature failure of asphalt overlays from
stripping: case histories', NCAT Report No 01- 01, (2001).
4. Hicks, R.G. “Moisture Damage in Asphalt Concrete.” NCHRP Synthesis of
Highway Practice, Vol.175, Transportation Research Board, October 1991.
5. Kiggundu, B.M. and Roberts, F.L. Stripping in HMA Mixtures: State of The Art
and Critical Review of Test Methods. NCAT Report 88-2, National Center for
Asphalt Technology, September 1988.
6. Stuart, K.D. Moisture Damage in Asphalt Mixtures – A State of the Art Report.
FHWA-RD-90-019, Federal Highway Administration, August 1990.
7. http://www.kjc.gov.my/english/service/climate/climate_upd.html
8. “A guide to the visual assessment of flexible pavement surface conditions”.
Jabatan Kerja Malaysia; 2005.
9. “A guide to the visual assessment of flexible pavement surface conditions”.
Jabatan Kerja Malaysia; 2007.
10. Majidzadeh, K. and Brovold, F, N. Effect of Water on Bitumen – Aggregate
Mixtures – State of the Art. Special HRB Report, No. 98, Highway Research
Board, 1968
11. Kennedy, T.W., Roberts, F.L., and LEE, K.W. “Evaluation of Moisture
Susceptibility of Asphalt Mixtures Using the Texas Freeze-Thaw Pedestal Test.”
Proceedings of the Association of Asphalt Paving Technologists, Vol. 53, 1982.
12. Tunnicliff, D.G. and Root, R.E. “Antistripping Additives in Asphalt Concrete –
State of the Art 1981.” Proceedings of the Association of Asphalt Paving
Technologists, Vol. 53, 1982.
60
13. Lee, A.R. and Nicholas, J.W. “Adhesion in Construction and Maintenance of
Roads.” Adhesion and Adhesives, Fundamentals and Practice, Society of
Chemical Industry, London, 1954.
14. Rice, J.M. “Relationship of Aggregate Characteristics to the Effect of Water on
Bituminous Paving Mixtures.” ASTM STP 240, American Society for Testing
and Materials, 1958.
15. Barksdale, R.D. The Aggregate Handbook. National Stone Association,
Washington, D.C., 1991.
16. Povarennykh, A.S. Crystal Chemical Classification of Mineral. Plenum Press,
New York –London, 1972.
17. Mark, C. “Physic-Chemical Aspects of Asphalt Pavements: Energy Relations at
Interface between Asphalt and Mineral Aggregate and Their Measurement.”
Industrial and Engineering Chemistry, 1935.
18. Hubbard, P. “Adhesion in Bituminous Road Materials: A Survey of Present
Knowledge.” Journal of the Institute of Petroleum, Vol. 44, No. 420, pp.423432, 1958.
19. Bikerman, J.J. “The Rheology of Adhesion.” Rheology, Theory and Application,
Vol.3, 1960.
20. Kanitpong, K. and Bahia, H, U. “Role of Adhesion and Thin Film Tackiness of
Asphalt Binders in Moisture Damage of HMA.” Proceedings of the Association
of Asphalt Paving Technologists, Vol. 72, 2002.
21. Fromm, J.H. “The Mechanisms of Asphalt Stripping From Aggregate Surfaces.”
Proceedings of the Association of Asphalt Paving Technologists, Vol. 43, 1974.
22. Terrel, R.L. and Al-Swailmi, S. Water Sensitivity of Asphalt – Aggregate Mixes:
Test Selection. Report SHRP-A-403, Strategic Highway Research Program,
National Research Council, Washington, D.C., 1994.
23. Kiggundu, B.M. and Roberts, F.L. Stripping in HMA Mixtures: State of The Art
and Critical Review of Test Methods. NCAT Report 88-2, National Center for
Asphalt Technology, September 1988.
24. Thelen, E. “Surface Energy and Adhesion Properties in Asphalt-Aggregate
System.” Proceeding of the Highway Research Board, Bulletin 192,1958.
61
25. Kim, Ok-Kee., Bell, C.A. and Hicks, R.G. “The Effect of Moisture on the
Performance of Asphalt Mixtures.” ASTM STP 899, American Society for
Testing and Materials, 1985.
26. Curtis, C.W., Terrel, R.L., Perry, L.M., AL-Swailm, S., and Braanan, C.J.
“Importance of Asphalt –Aggregate Interactions in Adhesion.” Proceedings of
the Association of Asphalt Paving Technologists, Vol. 60, 1991
27. Terrel, R.L., and Shute, J.W. Summary Report on Water Sensitivity. SHRPA/IR-89-003, Strategic Highway Research Program, National Research Council,
1989.
28. Brown, A.B., Sparks, W.J., and Marsh, E.G., “ Objective Appraisal of Stripping
of Asphalt from Aggregate.” ASTM STP 240, American Society for Testing and
Materials, 1985.
29. Takallou, H.T., Hicks, R.G., and Wilson, J.L., “Evaluation of Stripping
Problems in Oregon.” ASTM STP 899, American Society for Testing and
Materials, 1985
30. Lottman, P. R. “Laboratory Test Method for Predicting Moisture – Induce
Damage to Asphalt Concrete.” Transportation Research Record, No.843, 1982.
31. Taylor, A.Mark. and Khosla, N.Paul. “Stripping of Asphalt Pavements: State of
The art.” Transportation Research Record, No.911, 1983.
32. Gzemski, G.F., McGlashan, W.D., and Dolch, L.W. “ Thermodynamic Aspects
of the Stripping Problem.” Highway Research Circular, No. 78, 1968.
33. R.P.Lottman. Predicting Moisture-Induced Damage to Asphalt Concrete.
NCHRP Report 192, Transportation Research Board, October 1978.
34. R.P.Lottman. Predicting Moisture-Induced Damage to Asphalt Concrete – Field
Evaluation. NCHRP Report 246, Transportation Research Board, May 1982.
35. Kandhal, P.S. Moisture Susceptibility of HMA Mixes: Identification of Problem
and Recommended Solutions. NCAT Report 92-1, National Center for Asphalt
Technology, May 1992.
APPENDIX A
AGGREGATE SIZE DISTRIBUTION AND DETERMINATION OF FILLER
PA
Sieve
Size
mm
Gradation
0.45
power
14
3.279122
10
2.818383
5
2.063177
2.36
1.47167
0.075 0.311729
Pan (grm)
Gradation limit
Lower Upper
Limit
Limit
Percentage
Passing Retaining
%
%
100
95
30
5
2
100
97.5
40
10
3.5
100
100
50
15
5
0
2.5
57.5
30
6.5
Superpave D 150 mm
Mass
Mass
Mass
Passing Retained Retained
(g)
(g)
on each
Sieve (g)
4000
0
0
3900
100
100
1600
2400
2300
400
3600
1200
140
3860
260
140
Mass
Passing
(g)
900
877.5
360
90
31.5
Superpve D 100
Mass
Mass
Retained Retained
(g)
on each
Sieve (g)
0
0
22.5
30
540
690
810
360
868.5
78
31.5
Mass
passing
(g)
1500
1462.5
600
150
525
TMD
Mass
Retained
(g)
0
37.5
900
1350
1447.5
52.5
Washed-sieve analysis
1.Mass of blend aggregate (gram):
a) before
b) After
Aggregate Dust (gram):
3860
3831.2
28.8
868.5
861.3
7.2
1447.5
1435.4
12.1
2.Mass of blend aggregate (gram):
a)before
b)after
Aggregate Dust (gram):
3860
3828.2
31.8
868.5
860.6
7.9
1447.5
1436
11.5
Average Aggregate Dust (gram):
30.3
7.55
11.8
Average Filler Content (gram)=Pan-Average Aggregate Dust
OPC(2%by total weight of aggregate)
Weight of pan used (gram)=Average filler content-OPC
109.7
80
29.7
23.95
18
5.95
40.7
30
10.7
Total Aggregate Weight(gram)=Filler +Total Agg. Retained
3969.7
892.45
1488.2
62 Mass
Retained
on each
Sieve (g)
0
37.5
862.5
450
97.5
SMA
Sieve
Size
mm
12.5
9.5
4.75
2.36
0.6
0.3
0.075
Pan (grm)
Gradation
0.45
power
3.116087
2.754074
2.0161
1.47167
0.794636
0.581707
0.311729
Gradation limit
Lower Upper
Limit
Limit
100
72
25
16
12
12
8
100
83
38
24
16
15
10
Percentage
Passing Retain
%
g
%
100
77.5
31.5
20
14
13.5
9
0
22.5
46
11.5
66
0.5
4.5
Superpave D 150 mm
Mass
Mass
Mass
Passing Retained
Retained
(g)
(g)
on each
Sieve (g)
4600
0
0
3565
1035
1035
1449
3151
2116
920
3680
529
644
3956
276
621
3979
23
414
4186
207
414
Superpve D 100
Mass
Mass
Mass
Passing Retained Retained
(g)
(g)
on Each
Sieve (g)
1200
0
0
930
270
270
378
822
552
240
960
138
168
1032
72
162
1038
6
108
1092
54
108
Mass
passing
(g)
1500
1162.5
472.5
300
210
202.5
135
TMD
Mass
Retained
(g)
0
337.5
1027.5
1200
1290
1297.5
1365
135
Washed-sieve analysis
1.Mass of blend aggregate (gram):
a) before
b) After
Aggregate Dust (gram):
4186
4141.7
44.3
1092
1072
20
1365
28.6
1365
2.Mass of blend aggregate (gram):
a)before
b)after
Aggregate Dust (gram):
4186
4139.1
46.9
1092
1072
18
1365
1339.4
25.6
Average Aggregate Dust (gram):
45.6
19
27.1
Average Filler Content (gram)=Pan-Average Aggregate Dust
OPC(2%by total weight of aggregate)
Weight of pan used (gram)=Average filler content-OPC
368.4
92
276.4
89
24
65
107.9
30
77.9
Total Aggregate Weight(gram)=Filler +Total Agg .Retained
4554.4
1181
1472.9
63 Mass
Retained
on each
Sieve (g)
0
337.5
690
172.5
90
7.5
67.5
GPA
Sieve
Size
mm
Gradation
0.45
power
25
34.2567
20
3.850052
14
3.279122
10
2.818383
4
1.866066
2
1.36604
0.6
0.794636
0.3
0.581707
0.075
0.311729
Pan (grm)
Gradation limit
Lower Upper
Limit
Limit
100
76
64
56
41
16
12
6
3
100
100
89
81
55
31
16
10
7
Percentage
Passin
Retained
g
%
%
100
88
76.5
68.5
48
23.5
14
8
5
0
12
11.5
8
20.5
24.5
9.5
6
3
Superpave D 150 mm
Mass
Mass
Mass
Passin Retained
Retained
g
(g)
on each
(g)
Sieve (g)
4700
0
0
4136 564
564
3595
1104.5
540.5
3219
1480.5
376
2256
2444
963.5
1104.5
3595.5
1151.5
658
4042
446.5
376
4324
282
235
4465
141
235
Superpve D 100
Mass
Mass
Mass
Passing Retained Retained
(g)
(g)
on Each
Sieve (g)
1200
0
0
1056
144
144
918
282
138
822
378
96
576
624
246
282
918
294
168
1032
114
96
1104
72
60
1140
36
60
Mass
passing
(g)
2000
1760
1530
1370
960
470
280
160
100
TMD
Mass
Retained
(g)
0
240
470
630
1040
1530
1720
1840
1900
100
Washed-sieve analysis
1.Mass of blend aggregate (gram):
a) before
b) After
Aggregate Dust (gram):
4465
4418.2
46.8
1140
1121.6
18.4
1900
1867.3
32.7
2.Mass of blend aggregate (gram):
a)before
b)after
Aggregate Dust (gram):
4465
4416.6
48.4
1140
1120.8
19.2
1900
1864.5
35.5
Average Aggregate Dust (gram):
47.6
18.8
34.1
Average Filler Content (gram)=Pan-Average Aggregate Dust
OPC(2%by total weight of aggregate)
Weight of pan used (gram)=Average filler content-OPC
187.4
94
93.4
41.2
24
17.2
65.9
40
25.9
Total Aggregate Weight (gram) =Filler Total Agg. Retained
46524.4
1181.2
1965.9
64 Mass
Retained
on each
Sieve (g)
0
240
230
160
410
490
190
120
60
APPENDIX B
SPECIFIC GRAVITY OF AGGREGATE
APPENDIX B1 SPECIFIC GRAVITY OF COARSE AGGREGATE
COARSE AGGREGATE SPECIFIC GRAVITY INTERACTIVE EQUATION
1.INPUT
Mass of oven dry sample in air, A (g):
Mass of SSD sample in air , B (g):
Mass of SSD sample in water , C (g)
2.CALCULATE
sample 1
993.7
1005.2
618.8
PA14
sample 2
994.3
1006.1
620.4
average
994
1005.65
619.6
sample 1
995.4
1005.3
621.9
SMA14
sample 2
995.9
1005
620.8
average
995.65
1005.15
621.35
3.OUTPUT
Bulk specific gravity ,Gsb:
Bulk SSD specific gravity,Gbulk SSD:
Apparent specific gravity, Gsa:
Absorption (%):
PA14
2.575
2.605
2.655
1.172
SMA14
2.594
2.619
2.660
0.954
sample 1
995.6
1005.2
621.6
GPA20
sample 2
995.3
1005.5
621.9
average
995.45
1005.35
621.75
% GPA25
2.595
2.621
2.664
0.995
AGGREGATE GRADATION FOR COARSE AGGREGATE
Coarse(g)
1000
Total
PA14
10
5
Sieve Size(mm)
SMA14
GPA20
9.5
20
4.75
14
10
4
Percent Retained (%)
PA14
SMA14
GPA20
2.5
22.5
12
57.5
46
11.5
8
20.5
60
68.5
52
Mass Retained(g)
SMA14
GPA20
328.5
230.8
671.5
221.2
153.8
394.2
1000
1000
1000
PA14
41.7
958.3
65 APPENDIX B2 SPECIFIC GRAVITY FOR FINE AGGREGATE
FINE AGGREGATE SPECIFIC GRAVITY INTERACTIVE EQUATION
PA14
sample 1
494.7
877.3
1193.4
500.4
1.INPUT
Mass of oven dry sample in air, A (g):
Mass of pychnometer filled with water, B (g):
Mass of pychnometer. With SSD sample & air, C (g):
Mass of SSD sample, S (g):
2.CALCULATE
sample 2
495.1
877.2
1194.1
500.5
average
494.9
877.25
1193.75
500.45
SMA14
sample 1
495.2
877.2
1194.7
500.4
sample 2
495.5
877.4
1194.6
500.5
sample 2
496.1
877.3
1195.4
500.3
average
495.95
877.25
1195.15
500.2
% PA14
SMA14
GPA20
2.690
2.721
2.774
1.121
2.705
2.733
2.783
1.030
2.721
2.744
2.785
0.857
3.OUTPUT
Bulk specific gravity ,Gsb:
Bulk SSD specific gravity,Gbulk SSD:
Apparent specific gravity, Gsa:
Absorption (%):
GPA20
sample 1
495.8
877.2
1194.9
500.1
average
495.35
877.3
1194.65
500.45
AGGREGATE GRADATION FOR FINE AGGREGATE
Coarse(g)
700
Total
Sieve Size(mm)
PA14
2.36
0.075
–
–
–
SMA14
2.36
0.6
0.3
0.075
–
Percent Retained (%)
GPA20
2
0.6
0.3
0.075
–
PA14
30
6.5
–
–
36.5
SMA14
11.5
6
0.5
4.5
22.5
GPA20
24.5
9.5
6
3
43
Mass Retained(g)
PA14
575.3
124.7
–
–
700
SMA14
357.8
186.7
15.6
140.0
700
GPA20
398.8
154.7
97.7
48.8
700
66 APPENDIX B3 BLEND AGGREGATE SPECIFIC GRAVITY
BLEND AGGREGATE SPECIFIC GRAVITY
1.INPUT
Bulk specific gravity ,Gsb:
Bulk SSD specific gravity,Gbulk SSD:
Apparent specific gravity, Gsa:
Absorption (%):
Percentage , P:
2.CALCULATE
Coarse
2.575
2.605
2.655
1.172
60
PA14
Fine
2.690
2.721
2.774
1.121
38
OPC
2.980
2.980
2.980
Combined G
3.OUTPUT
2
Coarse
2.594
2.619
2.66
0.954
68.5
SMA14
Fine
2.705
2.733
2.783
1.031
29.5
OPC
2.980
2.980
2.980
2
Coarse
2.595
2.621
2.664
0.995
52
GPA25
Fine
2.721
2.744
2.785
0.857
46
OPC
2.98
2.980
2.98
2
100
P1 P2 Pn
G1 G2 Gn
PA14
SMA14
GPA25
Combined Bulk specific Gravity ,Gsb:
2.625
2.633
2.658
Combined Bulk SSD specific Gravity ,Gbulk SSD:
2.655
2.658
2.683
Combined Apparent specific Gravity ,Gsa:
2.705
2.701
2.724
Combined Absorption (%):
1.175
0.996
0.944
67 APPENDIX C
MIXTURE DESIGN
APPENDIX C1 MAXIMUM SPECIFIC GRAVITY OF BITUMINOUS PAVING MIXTURE
MAXIMUM SPECIFIC GRAVITY OF BITUMINOUS PAVING MIXTURE- PA
TMD TEST (1500 gram)
AGGREGATE+PAN (g) =1488.2
BITUMEN (5%) =198.5(g)
NUM.OF SAMPLE=2
CONTROL MIX
Weight of Bowl in Air (gm)
Weight of Bowl in Water (gm)
Weight of Bowl and Sample in Air
(gm)
Weight of Sample (gm)
Weight of Bowl and Sample in
Water (gm)
Asphalt Content of Mix (%)
SG of Asphalt, Gb
=
=
A
B
Sample 1
2205.5
1390.1
Sample 2
2205.7
1390.1
(F) Max SG of Mix, Gmm
=
=
=
C
D = (C - A)
3740.2
1534.7
3744.6
1538.9
=
=
=
E
G
H
2302.1
5
1.03
2301.3
5
1.03
2.46
2.45
2.458
2.660
2.644
2.652
Effective SG of Aggregate, Gse
=
Gmm at specified of % AC's
=
4.5
5
5.5
6
100
100/
%
/
100
100
/
%
/
Average
2.476
2.458
2.440
2.423
68 MAXIMUM SPECIFIC GRAVITY OF BITUMINOUS PAVING MIXTURE- SMA
TMD TEST (1500 gram)
AGGREGATE+PAN (g) =1484.6
BITUMEN (6%) =94.8(g)
NUM.OF SAMPLE=2
CONTROL MIX
Weight of Bowl in Air (gm)
Weight of Bowl in Water (gm)
Weight of Bowl and Sample in Air
(gm)
Weight of Sample (gm)
Weight of Bowl and Sample in
Water (gm)
Asphalt Content of Mix (%)
SG of Asphalt, Gb
=
=
A
B
Sample 1
2205.5
1390.1
Sample 2
2205.6
1390.1
(F) Max SG of Mix, Gmm
=
Effective SG of Aggregate, Gse
=
=
=
C
D = (C - A)
3747.3
1541.8
3742.7
1537.1
=
=
=
E
G
H
2280.8
6
1.03
2291.2
6
1.03
2.37
2.42
2.392
2.582
2.644
2.613
Gmm at specified of % AC's
=
100
100/
%
5.5
6
6.5
7
/
100
100
/
%
Average
/
2.409
2.392
2.376
2.359
69 MAXIMUM SPECIFIC GRAVITY OF BITUMINOUS PAVING MIXTURE - GPA
TMD TEST (2000gram)
AGGREGATE+PAN (g) =1965.9
BITUMEN (6%) =118.0(g)
NUM.OF SAMPLE=2
=
=
CONTROL MIX
Weight of Bowl in Air (gm)
Weight of Bowl in Water (gm)
Weight of Bowl and Sample in
Air (gm)
Weight of Sample (gm)
Weight of Bowl and Sample in
Water (gm)
Asphalt Content of Mix (%)
SG of Asphalt, Gb
(F) Max SG of Mix, Gmm
=
A
B
Sample 1
2205.4
1390.1
Sample 2
2205.7
1390.1
=
=
C
D = (C - A)
4265.6
2060.2
4273.2
2067.5
=
=
=
E
G
H
2585.4
6
1.03
2579.1
6
1.03
2.38
2.35
2.368
2.600
2.564
2.582
Effective SG of Aggregate, Gse
=
Gmm at specified of % AC's
5.5
6
6.5
7
=
100
100/
%
/
100
100
/
%
Average
/
2.384
2.368
2.351
2.335
70 APPENDIX C2 BULK SPECIFIC GRAVITY OF BITUMINOUS PAVING MIXTURE
Core Gravity(TM)
PA-MIX
Sample ID
Bag
Weight
(g)
Sample
Weight
before
Sealing (g)
Sealed
Sample
Weight in
Water (g)
Sample
Weight after
Water
Submersion
(g)
Density of
Water
(g/cm3) for
temperature
correction
Maximum
Specific
Gravity
BC 4.5% NO.1
BC 4.5% NO.2
BC 5.0% NO.1
BC 5.0% NO.2
BC 5.5% NO.1
BC 5.5% NO.2
BC 6.0% NO.1
BC 6.0% NO.2
49.4
49
49.1
48.1
49.5
49.1
48.3
49.2
4007.4
4006.8
4080.3
3969
3939.1
3967.3
3957.2
3971
1967.4
1971.6
2050.3
1957.7
1963
1957.8
1947.2
1965.6
4007.4
4006.8
4080.3
3969
3939.1
3967.3
3957.2
3971
1
1
1
1
1
1
1
1
2.476
2.476
2.456
2.456
2.44
2.44
2.423
2.423
Bulk
Specific
Gravity
(g/cm3)
1.983
1.987
2.029
1.992
2.012
1.993
1.987
1.999
% Air Voids
19.9
19.7
17.4
18.9
17.5
18.3
18.0
17.5
71 Core Gravity(TM)
SMA-MIX
Sample ID
BC 5.5% NO.2
BC 5.5% NO.2
BC 6.0% NO.1
BC 6.0% NO.2
BC 6.5% NO.1
BC 6.5% NO.2
BC 7.0% N0.1
BC 7.0% NO.2
Bag
Weight
(g)
49.4
49.3
49.3
49
49.2
49.1
48.2
49.2
Sample
Weight
before
Sealing (g)
Sealed
Sample
Weight in
Water (g)
Sample
Weight after
Water
Submersion
(g)
Density of
Water
(g/cm3) for
temperature
correction
Maximum
Specific
Gravity
Bulk
Specific
Gravity
(g/cm3)
% Air Voids
4736.4
2614
4736.4
1
2.409
2.254
6.4
4835.1
4597.2
4560.2
4576.6
4668
4827.2
4706.5
2647.1
2558.2
2505.3
2533.6
2587.5
2699.6
2621.7
4835.1
4597.2
4560.2
4576.6
4668
4827.2
4706.5
1
1
1
1
1
1
1
2.409
2.392
2.392
2.376
2.376
2.359
2.359
2.232
2.278
2.242
2.263
2.266
2.292
2.281
7.4
4.8
6.3
4.8
4.6
2.8
3.3
72 Core Gravity(TM)
GAP-MIX
Sample ID
Bag
Weight
(g)
Sample
Weight
before
Sealing (g)
Sealed
Sample
Weight in
Water (g)
Sample
Weight after
Water
Submersion
(g)
Density of
Water
(g/cm3) for
temperature
correction
Maximum
Specific
Gravity
BC 5.5% NO.1
BC 5.5% NO.2
BC 6.0% NO.1
BC 6.0% NO.2
BC 6.5% NO.1
BC 6.5% NO.2
BC 7.0% N0.1
BC 7.0% NO.2
49.2
49.4
49.6
49.5
49.2
49.1
49.2
49.2
4677.6
4772.6
4723.7
4665.7
4642.2
4715.5
4666.8
4611
2551.2
2604.9
2651.2
2578.8
2590.1
2638.3
2616.4
2587.9
4677.6
4772.6
4723.7
4665.7
4642.2
4715.5
4666.8
4611
1
1
1
1
1
1
1
1
2.384
2.384
2.368
2.368
2.351
2.351
2.335
2.335
Bulk
Specific
Gravity
(g/cm3)
2.222
2.223
2.303
2.258
2.285
2.293
2.299
2.303
% Air Voids
6.8
6.7
2.8
4.6
2.8
2.5
1.5
1.4
73 APPENDIX C3 VOLIMTRIC PROPERTIES OF MIX
PA-MIX
% BIT.
SPEC.
NO.
% Bit.
by wt.
of mix.Pb
4.5
4.5
AVG
5
5
AVG
5.5
5.5
AVG
6
6
AVG
SPEC. GRAV.
Gmb
1.983
1.987
1.985
2.029
1.992
2.0105
2.012
1.993
2.0025
1.987
1.999
1.993
VOIDS (%)
Gmm
2.476
2.476
2.476
2.456
2.456
2.456
2.44
2.44
2.44
2.423
2.423
2.423
VIM
19.9
19.7
19.8
17.4
18.9
18.2
17.5
18.3
17.9
18.0
17.5
17.8
VMA
VFA
[1- Gmb(1- Pa)]×100
Gsb
(VMA -VIA) ×100
VMA
28.8
28.7
28.8
27.2
28.5
27.8
27.8
28.5
28.1
28.7
28.3
28.5
31.0
31.3
31.1
36.0
33.7
34.8
37.0
35.7
36.4
37.3
38.1
37.7
74 SMA-MIX
% BIT.
SPEC. GRAV.
VOIDS (%)
SPEC.
NO.
Gmb
Gmm
VIM
% Bit.
by wt.
VMA
VFA
[1- Gmb(1- Pa)]×100
(VMA -VIA) ×100
Gsb
VMA
of mix.Pb
5.5
2.254
2.409
6.4
19.1
66.5
5.5
2.232
2.409
7.4
19.9
62.8
6
2.243
2.278
2.409
2.392
6.9
4.8
19.5
18.7
64.6
74.3
6
2.242
2.392
6.3
20.0
68.4
2.260
2.392
5.6
19.3
71.3
6.5
2.263
2.375
4.8
19.6
75.6
6.5
2.266
2.375
4.6
19.5
76.4
7
2.265
2.292
2.375
2.359
4.7
2.8
19.6
19.0
76.0
85.3
7
2.281
2.359
3.3
19.4
83.0
2.287
2.359
3.1
19.2
84.1
AVG
AVG
AVG
AVG
75 GPA-MIX
% BIT.
SPEC. GRAV.
VOIDS (%)
SPEC.
NO.
Gmb
Gmm
VIM
VMA
VFA
% Bit.
[1- Gmb(1- Pa)]×100
(VMA -VIA) ×100
by wt.
Gsb
VMA
of mix.Pb
5.5
2.222
2.384
6.8
21.0
67.6
5.5
2.223
2.384
6.7
21.0
68.0
2.223
2.384
6.8
21.0
67.8
6
2.303
2.368
2.8
18.6
84.9
6
2.258
2.368
4.6
20.1
77.2
2.281
2.368
3.7
19.4
81.0
6.5
2.285
2.251
2.8
19.6
85.7
6.5
2.293
2.251
2.5
19.3
87.1
2.289
2.251
2.7
19.5
86.4
7
2.299
2.335
1.5
19.6
92.3
7
2.303
2.335
1.4
19.4
92.8
2.301
2.335
1.5
19.5
92.6
AVG
AVG
AVG
AVG
76 APPENDIX C4 DETEMINATION OF OPTIUMUM ASPHALT CONTENT
PA-MIX
AIR VOID vs BITUMEN CONTENT
VMA vs BITUMEN CONTENT
30
40.0
y = 1.6x2 - 18.04x + 68.51
R² = 0.9632
30.0
20
VMA(%)
VA(%)
25
y = 1.2698x2 - 12.692x + 59.135
R² = 0.9332
35.0
15
10
25.0
20.0
15.0
5
10.0
4
4.5
5
5.5
Bitumen Content
6
6.5
4
4.5
5
5.5
Bitumen Content
6
6.5
VFA vs BITUMEN CONTENT
50.0
y = -2.5579x2 + 32.963x - 67.798
R² = 0.9942
45.0
VFA(%)
40.0
35.0
30.0
25.0
20.0
4
4.5
5
5.5
Bitumen Content
6
6.5
77 SMA-MIX
VA vs BITUMEN CONTENT
8
VMA vs BITUMEN CONTENT
y = -0.2x2 + 0.06x + 12.55
R² = 0.987
7
6
VMA(%)
VA(%)
5
4
3
2
1
y = -0.2496x2 + 2.9636x + 10.696
R² = 0.435
19.7
19.6
19.6
19.5
19.5
19.4
19.4
19.3
19.3
19.2
19.2
19.1
0
4
4
4.5
5
5.5
6
6.5
Bitumen Content
7
4.5
5
7.5
5.5
6
6.5
7
7.5
Bitumen Content
VMA vs BITUMEN CONTENT
100.0
y = 1.0309x2 - 0.4334x + 36.146
R² = 0.9925
VMA(%)
90.0
80.0
70.0
60.0
50.0
4
4.5
5
5.5
6
6.5
7
7.5
Bitumen Content
78 GAP-MIX
AV vs BITUMEN CONTENT
8
21.5
7
21.0
y = 2x2 - 28.4x + 102.4
R² = 0.9872
6
y = 1.6506x2 - 21.505x + 89.236
R² = 0.9052
20.5
5
VMA (%)
AV (%)
VMA vs BITUMEN CONTENT
4
3
20.0
19.5
19.0
2
18.5
1
18.0
0
4.5
5
5.5
6
6.5
7
4.5
7.5
5
5.5
6
6.5
7
7.5
Bitumen Content (%)
Bitumen Content (%)
VFA vs BITUMEN CONTENT
y = -7.4x2 + 108.46x - 304.55
R² = 0.989
100.0
VFA (%)
90.0
80.0
70.0
60.0
50.0
40.0
4.5
5
5.5
6
6.5
7
7.5
Bitumen Content (%)
79 80 APPENDIX
D
POROSITY RESULT
PA-Porosity
Max Gravity (Gmm): 2.476
Sample ID
PA-125 Gyr
PA-1
PA-2
PA-3
PA-4
PA-5
PA-6
PA-7
PA-8
PA-9
PA-10
PA-11
PA-12
PA-100 Gyr
PA-13
PA-14
PA-15
PA-16
PA-17
PA-18
PA-19
PA-20
PA-21
PA-22
PA-23
PA-24
PA-75 Gyr
PA-25
PA-26
PA-27
PA-28
PA-29
PA-30
PA-31
PA-32
PA-33
PA-34
PA-35
PA-36
Bag
Weight
(g)
Inputs
Dry
Sample
Wt. (g)
26.4
26.7
26.5
26.7
26.3
26.5
26.5
26.5
26.6
26.7
26.4
26.4
Double Bag Limit: 75
Bulk
Specific
Gravity
(g/cm3)
Results
Sample
Percent
Maximum Porosity
Gravity
(%)
(g/cm3)
Sealed
Wt. In
Water
(g)
Sample
Wt. After
Cutting
the Bag
(g)
Percent
Air
Voids
(%)
1190.8
1231.1
1198
1202.9
1209.4
1195.7
1207.9
1196.6
1186.3
1196.3
1209.1
1189.5
579.4
603.1
572.2
585.1
585.8
577.2
588.9
585.1
574.5
585.9
590.2
578.3
703.3
724.4
705.3
708.4
710.2
703.6
711.9
704.6
698.4
703.1
710.8
699.9
1.971
1.983
1.937
1.970
1.962
1.956
1.974
1.980
1.962
1.983
1.977
1.969
2.457
2.443
2.446
2.447
2.436
2.444
2.449
2.446
2.446
2.440
2.440
2.444
19.79
18.83
20.81
19.48
19.48
19.97
19.39
19.06
19.77
18.71
19.00
19.41
20.41
19.90
21.78
20.43
20.76
21.00
20.26
20.03
20.75
19.90
20.17
20.47
26.6
26.5
26.5
26.7
26.7
26.3
26.3
26.4
26.5
26.6
26.7
26.6
1212.3
1201.9
1178.5
1170.8
1190.7
1188.6
1178.5
1240.1
1223
1241.8
1220
1229.9
587.5
574.8
565.5
558.4
571.1
578.3
564.6
599.3
588.3
598.2
588
589.8
714
706.8
694.9
688.6
700.7
698.4
693
728.8
719.7
728.4
717
722.7
1.963
1.939
1.945
1.935
1.944
1.971
1.942
1.957
1.949
1.951
1.953
1.943
2.447
2.442
2.451
2.443
2.444
2.439
2.442
2.439
2.444
2.432
2.439
2.439
19.78
20.59
20.64
20.80
20.45
19.20
20.45
19.75
20.24
19.77
19.95
20.31
20.72
21.69
21.43
21.87
21.47
20.41
21.56
20.95
21.28
21.18
21.13
21.51
26.8
26.4
26.6
26.6
26.5
26.6
26.6
26.5
26.5
26.4
26.6
26.7
1223.5
1224.9
1221.8
1230.2
1225.6
1219.5
1234.1
1223.1
1228.7
1232.1
1233.8
1211.6
579.9
577.7
576
580.8
575
574.8
589.4
575.7
580.6
584
582.4
574.9
719.4
720
718.4
722.9
719.5
716.8
723.7
723.7
721.6
723.6
725.5
712.8
1.923
1.914
1.913
1.916
1.905
1.913
1.936
1.911
1.917
1.922
1.915
1.925
2.441
2.440
2.441
2.439
2.435
2.440
2.432
2.463
2.437
2.437
2.441
2.443
21.23
21.55
21.61
21.45
21.78
21.59
20.38
22.44
21.32
21.10
21.53
21.21
22.34
22.70
22.72
22.63
23.06
22.74
21.81
22.84
22.57
22.36
22.64
22.26
81 SMA- Porosity
Max Gravity (Gmm): 2.369
Sample ID
SMA-Gyr125
SMA-25
SMA-26
SMA-27
SMA-28
SMA-29
SMA-30
SMA-31
SMA32
SMA-33
SMA-34
SMA-35
SMA36
SMA-Gyr100
SMA-13
SMA-14
SMA-15
SMA-16
SMA-17
SMA-18
SMA-19
SMA-20
SMA-21
SMA-22
SMA-23
SMA-24
SMA-Gyr75
SMA-1
SMA-2
SMA-3
SMA-4
SMA-5
SMA-6
SMA-7
SMA-8
SMA-9
SMA10
SMA-11
SMA12
Bag
Weight
(g)
Inputs
Dry
Sample
Wt. (g)
Double Bag Limit: 75
Sealed
Wt. In
Water
(g)
Sample
Wt.
After
Cutting
the Bag
(g)
Bulk
Specific
Gravity
(g/cm3)
Results
Sample
Percent
Maximum Porosity
Gravity
(%)
(g/cm3)
Percent
Air
Voids
(%)
26.5
26.5
26.5
26.6
26.6
26.6
26.5
26.8
26.6
26.5
26.4
26.4
1290.4
1288.8
1295.1
1288.3
1278.3
1300.7
1296.8
1310.3
1290.7
1281.6
1285.2
1296.6
719.3
715
721.8
718.3
711.2
720.5
727.1
736.3
723.1
712
718.2
726.2
732.9
734.4
736.9
731.8
726.8
739.8
735.9
743.7
734
728.7
731
737
2.289
2.275
2.288
2.289
2.283
2.270
2.306
2.312
2.304
2.279
2.296
2.302
2.326
2.337
2.332
2.327
2.330
2.331
2.324
2.324
2.330
2.330
2.331
2.329
1.63
2.64
1.88
1.61
1.99
2.59
0.78
0.51
1.15
2.18
1.50
1.13
3.39
3.97
3.42
3.36
3.61
4.16
2.67
2.39
2.76
3.80
3.08
2.81
26.3
26.4
26.7
26.6
26.6
26.9
26.6
26.6
26.6
26.6
26.4
26.5
1209
1221.3
1204.1
1216.1
1232
1301.2
1202.6
1197
1274.4
1300.8
1290.3
1275.3
668.2
672.7
659.7
669.3
678.8
718.6
663.8
652.5
701.5
720.6
715.3
698.9
689.2
693.5
686.1
692.1
708.6
746.6
686
680.6
723.9
746.6
741.8
726.4
2.266
2.256
2.242
2.254
2.257
2.262
2.262
2.228
2.253
2.271
2.273
2.241
2.339
2.326
2.337
2.334
2.367
2.358
2.341
2.331
2.327
2.359
2.365
2.335
3.12
3.04
4.10
3.41
4.65
4.09
3.36
4.42
3.18
3.76
3.89
4.06
4.37
4.78
5.38
4.86
4.74
4.51
4.50
5.96
4.89
4.15
4.07
5.41
26.5
26.4
26.6
26.6
26.5
26.6
26.7
26.7
26.6
26.5
26.5
26.5
1212.3
1209.7
1212.8
1224.5
1207.5
1195.1
1215.8
1243.2
1226.4
1220.8
1212.8
1193.7
664.1
662.6
662.9
667.3
658.4
651.9
662.5
676.4
672.1
671.9
661.2
655.7
689
688.5
688.3
696
687.8
681.4
692.4
707.5
696.6
694.8
690.3
681.5
2.241
2.241
2.235
2.227
2.228
2.230
2.227
2.222
2.242
2.254
2.228
2.249
2.329
2.334
2.325
2.330
2.336
2.339
2.336
2.333
2.327
2.334
2.334
2.344
3.80
3.99
3.87
4.42
4.62
4.69
4.67
4.77
3.68
3.42
4.54
4.04
5.41
5.42
5.66
6.01
5.94
5.88
6.01
6.21
5.37
4.87
5.96
5.07
82 GAP- Porosity
Max Gravity (Gmm): 2.361
Double Bag Limit: 75 Inputs
Sample ID
GPA-125
GYR
GPA1
GPA-2
GPA-3
GPA-4
GPA-5
GPA-6
GPA-7
GPA-8
GPA-9
GPA-10
GPA-11
GPA-12
GPA-100
GPA-13
GPA-14
GPA-15
GPA-16
GPA-17
GPA-18
GPA-19
GPA-20
GPA-21
GPA-22
GPA-23
GPA-24
GPA-75
GYR
GPA-25
GPA-26
GPA-27
GPA-28
GPA-29
GPA-30
GPA-31
GPA-32
GPA-33
GPA-34
GPA-35
GPA-36
Results
Bag
Weight
(g)
Dry
Sample
Wt. (g)
Sealed
Wt. In
Water
(g)
Sample
Wt.
After
Cutting
the Bag
(g)
Bulk
Specific
Gravity
(g/cm3)
Sample
Maximum
Gravity
(g/cm3)
Percent
Porosity
(%)
Percent
Air
Voids
(%)
26.6
26.4
26.8
26.5
26.6
26.6
26.6
26.5
26.3
26.5
26.6
26.7
1306.5
1210.6
1191.1
1203.4
1205.5
1229.1
1201.5
1174.6
1184
1172.2
1208.1
1238.8
731.1
669.7
660.6
664.7
669.3
689.7
666.6
653.9
657
654.3
671.8
690.4
744.6
689
678.1
684.2
686.3
697.4
683.2
665
668.5
663.9
685.8
706
2.300
2.268
2.276
2.264
2.279
2.310
2.277
2.287
2.278
2.295
2.283
2.289
2.337
2.334
2.335
2.331
2.335
2.324
2.331
2.318
2.309
2.319
2.326
2.338
1.59
2.80
2.51
2.85
2.39
0.62
2.32
1.32
1.38
1.03
1.82
2.07
2.59
3.93
3.58
4.10
3.48
2.17
3.56
3.12
3.54
2.79
3.29
3.04
26.6
26.6
26.5
26.4
26.5
26.7
27
26.8
27
27.1
26.8
26.8
1230.1
1203
1210.2
1231.4
1208.7
1213.4
1152.7
1237
1207.3
1211.1
1203.7
1196.1
677.8
660.5
662.4
675.3
657.8
665.3
634.8
679.7
658.34
672.7
664.4
658.1
700
683
687.4
700.4
686.9
688
654.2
701.9
684.4
688.9
683.4
679.3
2.257
2.247
2.239
2.243
2.223
2.244
2.257
2.249
2.229
2.281
2.262
2.254
2.333
2.326
2.328
2.331
2.329
2.322
2.326
2.324
2.322
2.332
2.326
2.327
3.27
3.39
3.82
3.78
4.55
3.39
2.94
3.23
4.00
2.22
2.75
3.17
4.41
4.81
5.18
4.98
5.84
4.98
4.39
4.74
5.59
3.41
4.17
4.55
26.7
26.6
26.6
26.6
26.6
26.5
26.4
26.6
26.6
26.5
26.6
26.4
1216.7
1210.7
1200
1227.9
1204.6
1226
1211.1
1213.8
1240.2
1089.8
1228.8
1187.2
661
663.4
655.5
672.3
659.2
672.4
655.7
661.3
681
590
670.6
642.2
693
688.4
681.1
698.6
684.2
695.4
686.8
689.2
704.2
612.4
694.1
670.4
2.218
2.242
2.233
2.239
2.238
2.244
2.209
2.226
2.247
2.212
2.230
2.207
2.336
2.331
2.325
2.332
2.328
2.323
2.322
2.326
2.326
2.296
2.310
2.310
5.03
3.82
3.95
4.00
3.83
3.41
4.88
4.31
3.41
3.68
3.47
4.44
6.04
5.05
5.40
5.16
5.20
4.96
6.43
5.72
4.83
6.32
5.54
6.51