faculty of engineering 3... · specimens were prepared using the marshal mix design procedure for...
TRANSCRIPT
59
Digitally Signed by: Content manager’s Name
DN : CN = Weabmaster’s name
O= University of Nigeria, Nsukka
OU = Innovation Centre
Nwamarah Uche
Faculty of Engineering
Department of Civil Engineering
DEVELOPMENT OF LAYERED ELASTIC ANALYSIS PROCEDURE FOR PREDICTION OF FATIGUE AND RUTTING STRAINS IN CEMENT -
STABILIZED LATERITIC BASE OF LOW VOLUME ROADS
EKWULO, EMMANUEL OSILEMME PG/Ph.D/10/57787
60
CHAPTER 3
METHODOLOGY
3.1 Layered Elastic Analysis and Design Procedure for Cement Stabilized Low-
Volume Asphalt Pavement
This study is geared towards developing a layered elastic analysis and design
procedure for the prediction of fatigue and rutting strain in cement-stabilized
lateritic base asphalt pavement. This chapter described in detail, the procedure to be
adopted in characterization of LEADflex pavement material, traffic estimation and
summary of the LEADFlex procedure.
The design procedure comprises of two parts, namely; empirical and analytical.
3.2 Empirical
The empirical part involves material characterization, traffic estimation, computation
of pavement layer thicknesses and development of simple empirical relationship
between these parameters.
3.2.1 Pavement Material Characterization
Material characterization involves laboratory test on surface, base and subgrade
materials to determine the elastic modulus of the asphalt concrete, elastic modulus of
the cement-stabilized lateritic material and resilient modulus of the natural
subgrade.
3.2.1.1 Asphalt Concrete Elastic Modulus
The following physical (rheological) property test were carried out on the bitumen
sample:
1. Specific gravity test
2. Consistency test such as;
i. Penetration Test
61
ii. Softening Point Test
iii. Ductility Test
iv. Viscosity Test
3. Gradation Analysis Test
The result of the specific gravity of aggregates and consistency test for binder are
presented in Tables 3.1A and 3.2A of Appendix A.
3.2.1.2 Mix Proportion of Aggregates
In order to meet the specification requirement for aggregate gradation, the
proportion of each aggregate mix was determined. The straight line method of
aggregate combination was used; this method involved plotting on a straight line the
percent passing on each sieve size with the corresponding sieve size for both
aggregates on the same graph as shown in Figure 3.3A of Appendix A. After which a
mix proportion was obtained for each aggregate by locating their point of
intersection on the graph. The Specification limits for aggregate in accordance with
ASTM (1951: C136) and proportion of each aggregate based on aggregate
combination is presented in Table 3.5A of Appendix A. From the aggregate
gradation and combination, the proportion of coarse and fine aggregates were
determined as 58% for gravel and 42% for sand.
3.2.1.3 Specimen Preparation
Specimens were prepared using the Marshal mix design procedure for asphalt
concrete mixes as presented (NAPA, 1982; Roberts et al, 1996; Asphalt Institute,
1997). The procedure involved the preparation of a series of test specimens for a
range of asphalt contents such that the test data curves showed well defined
optimum values. Test were scheduled on the basis of 0.5 percent increment of
asphalt content with at least 3 asphalts contents above and below the optimum
asphalt content. Three specimens were prepared for each asphalt content, each
62
specimen required approximately 1.2kg of the total weight of the mixture and
measures 64mm thick and 100mm diameter.
To prepare the test specimens, aggregates were first heated for about 5 minutes
before bitumen was added to allow for absorption into the aggregates. After which
the mix was poured into a mould and compacted on both faces with 35, 50, 75, 100,
125 and 150 blows using a rammer falling freely at 450mm and having a weight of
6.5kg. The compacted specimens were subjected to the following test and analysis:
i. Bulk specific gravity
ii. Stability and Flow at the pavement temperature
iii. Density and voids
The maximum stability, unit weight and median of air voids were determined as
1700N, 2460kg/m3 and 5% at 4.5%, 4% and 5% binder content respectively. The
optimum binder content was obtained by taking the average of the binder contents
at maximum stability, unit weight, and median of air voids. Optimum binder
content of 4.5% was obtained for the bituminous mixes and was used to for the
preparation of the asphalt concrete mix (Asphalt Institute, 1997).
3.2.1.4 Determination of Bulk Specific Gravity (Gmb) of Samples
The bulk specific gravity of each specimen was obtained by measuring the weight of
each compacted specimen in air and its weight in water. The bulk specific gravity
was then determined as the ratio of the weight of the specimen in air to the
difference in weight of specimen in air and water as follows:
wa
a
mbWW
WG
−= (3.1)
where, Gmb = bulk specific gravity of compacted specimen
Wa = Weight air
Ww = Weight in water
63
3.2.1.5 Determination of Void of compacted mixture
The Air Voids consist of the small air spaces between the coated aggregate particles.
Voids Analysis involved the determination of both percent air voids and percent
voids in mineral aggregates of each specimen. The results of bulk specific gravity
and maximum specific gravity were used with already existing equations to
determine the percent airs voids and percent voids in mineral aggregates.
At the compactions levels of 35, 50, 75, 100, 125 and 150 blows using a harmer of
weight 6.5kg falling freely at 450mm, the percent air voids “Va” were determined
using equation 3.2
Gmm
GGV mbmm
a
−= x 100% (3.2)
Where, Va = percent air voids content
Gmm = maximum specific gravity of compacted mixture
Gmb = bulk specific gravity of compacted mixture
3.2.1.6 Density of Specimens
The density of the specimens were determined by multiplying the bulk specific
gravity already determined by 1000kg/m3.
3.2.1.7 Stability and Flow of Samples
The Marshall Test Apparatus was used for the stability and flow test. The machine
was used to apply load at a constant rate of deformation of 50mm/minute until
failure occurred (Asphalt Institute, 1997). The point of maximum load was recorded
as the Marshall stability value for the specimen. The flow values in units of 0.25mm
was also obtained simultaneously at maximum load using the flow meter attached to
the machine.
64
3.2.1.8 Determination of Asphalt Concrete Elastic Modulus
The elastic modulus of the asphalt concrete was determined using the modified
Witczak model ((Christensen et al, 2003)) in equation 3.3.
[ ])3.3(
1
00547.0)(000017.0003958.00021.0871977.3
)(802208.0058097.0002841.0)(001767.0029232.0249937.1log
)log393532.07919691.0(
34
2
38384
4
2
200200
η−−
+−+−+
+−−−−+−=
e
PPPP
VV
VVPPPE
abeff
beff
a
Where
E = Elastic Modulus (Psi)
η = Bituminous viscosity, in 106 Poise (at any temperature, degree of aging)
Va = Percent air voids content, by volume
Vbeff = Percent effective bitumen content, by volume
P34 = Percent retained on 3/4 in. sieve, by total aggregate weight(cumulative)
P38 = Percent retained on 3/8 in. sieve, by total aggregate weight(cumulative)
P4 = Percent retained on No. 4 sieve, by total aggregate weight(cumulative)
P200 = Percent retained on No. 200 sieve, by total aggregate weight(cumulative)
Using equation 3.3, the design elastic modulus of asphalt concrete was determined
by developing a regression equation relating the compaction levels and percents air
voids on one hand and the percents air voids and elastic modulus on the other hand.
Table 3.6A of APPENDIX presents the compaction level, percent air voids and elastic
modulus of the asphalt concrete. Figures 3.4A and 3.5A of APPENDIX A shows the
relationship between compaction level and air voids, and air voids and elastic
modulus
From Figures 3.4A and 3.5A of Appendix A, the design elastic modulus of 3450MPa
can be obtained for percentage air voids of 3.04% and compaction level of 90 blows.
65
3.2.2 Base Material
The base material used in the study is cement-treated laterite of elastic modulus of
329MPa. The elastic modulus was determined by correlation with CBR as presented
in equation 3.4 (Ola, 1980). From equation 3.5, elastic modulus of 329MPa
corresponds with CBR of 79.5% approximately 80% CBR. The study is based on
cement stabilized base of 80% CBR ie elastic modulus of 329MPa.
E(psi) = 250(CBR)1.2 (3.4)
3.2.2.1 Soil Classification Test
The following soil classification tests were carried out on the sample to obtain its
physical properties.
(i) Natural moisture content.
(ii) Atterberg limit (liquid and plastic limit)
(iii) Sieve analysis
(iv) Compaction (Moisture-density) tests.
3.2.2.2 Sieve Analysis
500g of an oven dried sample was used for sieve analysis. Wet sieving was carried
out to determine the accurate amount of silt and clay passing sieve 0.075(No. 200).
The result of the sieve analysis is shown in Table 3.7A of APPENDIX A and the
Particle Size Distribution is shown in Figure 3.6A of APPENDIX A.
Group index value of the sample was also obtained as follows:
Group index GI = 0.2a + 0.005ac + 0.01bd
(3.5)
a = that portion of percentage passing No. 200 sieve greater than 35% and not
exceeding 75%, expressed as a positive whole number (1-40)
66
therefore a = 0; percentage passing No. 200 sieve is 22%, less than 35%
b = that portion of percentage passing No. 200 sieve greater than
15% and not exceeding 55% expressed as a whole number (1-40), therefore
b = 22-15 = 7
c = that portion of numerical liquid limit greater than 40 and not exceeding 60,
expressed as a positive whole number (1-20) therefore c =0; liquid limit = 32%,
less than 40%.
d = that potion of the numerical plasticity, index greater than 10 and not exceeding
30, expressed as a positive whole number (1-20)
Therefore a = 16 – 10 = 6
GI = 0.2 x 0 + 0.005x0x0 + 0.01x 7x 6 = 0.42
3.2.2.3 Compaction Test
Compaction (Moisture-Density) test was carried out on the soil sample to determine
the optimum moisture content (OMC) and the corresponding maximum dry density
(MDD) of the sample. The test was carried out using a proctor mould of 100mm
diameter by 115mm height and a 2.5kg hammer with a drop of 300mm. 3000g of the
oven dried soil was mixed with a specified amount of water and compacted in three
layers in the proctor mould, each layer being compacted with 25 blows of the
hammer falling a distance of 300mm. The result of the compaction test is shown in
the Table 3.8A of Appendix A and the moisture-density relation is shown in Figure
3.7A of APPENDIX A.
3.2.2.4 Soil Classification
From the classification tests, the material was found to posses the following physical
properties.
(i) Well graded
(ii) Natural moisture content = 11.31%
67
(iii) Liquid limit = 32%
(iv) Plasticity index = 15.51%
(v) Proctor maximum dry density = 1960kg/m3
(vi) Proctor optimum moisture content = 10.8%
Base on the AASHO (1993) classification system, the Sieve Analysis and Group
index, the soil was classified as A-2-6 (0.42). That is, the soil is silty or clayed gravely
and sand and it is rated as excellent to good as sub-grade materials
In accordance with Table 3.9A of APPENDIX A, the soil will require about 5 to 9% cement for stabilization
3.2.2.5. California Bearing Ratio (CBR) Test Specimen
To obtain a cement treated laterite of 80% CBR, trial CBR test were carried out at
varying cement contents. The cement treated specimen for the CBR test were
prepared in the CBR mould 152.4mm (6.0in) in diameter and 177.8mm (7.0in) high
with collar and base. The soil- cement mixture was mixed with water at the optimum
moisture content and compacted in three layers with 50 blows per layer in the CBR
mould using the modified AASHTO hammer of 4.5kg falling a distance of 450mm.
A set three specimens were prepared for each fiber content. The compacted
specimen in the mould was kept in an air- tight water proof sack to prevent loss of
moisture for 24 hours and tested using the CBR machine. Table 3.10A of Appendix A
presents the trial CBR tests result while Figure 3.8A of Appendix A shows the
relationship between the cement content and CBR. From Figure 3.8A of APPENDIX
A, 80% CBR was obtained at cement of 5.4%.
3.2.3 Subgrade Material
The resilient modulus of subgrade was determined in accordance the AASHTO
Guide (AASHTO, 1993) in order to reflect actual field conditions. It is recommended
that subgrade samples be collected for a period of twelve (12) months in order to
68
accommodate the effect of seasonal subgrade variation on resilient modulus of
subgrades. In this study, samples were collected from January 2011 – December,
2011 (four samples per month). Average subgrade CBR for each month was
determined as presented in Table 3.11A of Appendix A. The resilient modulus (Mr)
was determined using correlation with CBR as shown equation (3.6) (HeuKelom and
Klomp, 1962). The CBR of subgrade material was determined using the procedure as
earlier described in section 3.2.2.4.
Mr (psi) = 1500 CBR
(3.6)
In accordance with AASHTO Guide (AASHTO, 1993), the relative damage per
month were determined using equation 3.7.
fu = (1.18 x 108)32.2−
RM
(3.7)
From equations 3.6 and 3.7
fu = (1.18 x 108)x(32.2
)1500 −CBR
(3.8)
Where,
fu = relative damage factor
CBR = California Bearing Ratio (%)
Therefore, over an entire year, the average relative damage was determined using
equation 3.9 as follows:
:
n
uuuu
fnff
f
+++=
...21 Where, n = 12.
(3.9)
69
=fu 0.53
Hence from equation 3.8, the average CBR is given by
CBR = 1500
)10847.0( 431.08 −−xux f
(3.10)
= 2.64%
The study approximates CBR of subgrade to the nearest whole number, hence the
CBR of the subgrade is taken as 3%. However, for worse conditions a CBR of 2%
may be assumed.
3.2.4 Poison’s Ratio
In mechanistic-empirical design, the Poisson’s ratios of pavement materials are in
most cases assumed rather than determined (NCHRP, 2004). In this study, the
Poisson’s ratios of the materials were selected from typical values used by various
pavement agencies as presented in Literature (NCHRP, 2004; WSDOT, 2005).
3.2.5 Traffic and Wheel load Evaluation
The study considered traffic in terms of Equivalent Single Axle Load (ESAL)
repetitions for a design period of 20years (NCHRP, 2004). Traffic estimation is in
accordance with the procedure contained in the Nigerian Highway Manual part 1
(1973). For the purpose of this study, three traffic categories; Light, medium and
Heavy traffic were considered in design as presented in Table 3.1.
Table 3.1: Traffic Categories (NCHRP, 2004)
Traffic Category
Expected 20 yr Design ESAL
A.C. Surface Thickness
(mm)
Stabilized Base Thickness
(mm)
Light 1 x 104 – 5 x 104 50 ≥ 50
Medium 5 x 104 – 2.5 x 105 75 ≥ 75
Heavy 2.5 x 105 – 7.5 x 105 100 ≥ 100
70
Light Traffic
50,000 ESAL maximum – typical of local streets or low volume country roads with
very few trucks, approximately 4-5 per day, first year.
Medium Traffic
250,000 ESAL maximum – typical of collectors with fewer trucks and buses,
approximately 23 per day, first year.
Heavy Traffic
750,000 ESAL maximum – typical of collectors with significant trucks and buses,
approximately 70 per day first year.
3.2.6 Loading Conditions
The study considered a three layer pavement model. The static load(P) applied on
the pavement surface, the geometry of the load (usually specified as a circle of a
given radius), and the load on the pavement surface in form of Equivalent Single
Axle load (ESAL) was considered. The loading condition on pavement was obtained
by determining the critical load configuration. The critical load configuration was
determined by investigating the effect of single and multiple wheel loads on the
tensile strain below asphalt concrete layer and compressive strain at the top the
subgrade. To investigate this, the pavement system was subjected to three different
loading cases as shown in Figure 3.1. The first one will be single axle with single
wheel (I), the second one will be single axle with dual wheels (four wheels; II), and
the last one will be tandem axle with dual wheels (eight wheels; II + III). Each axle
will be 80kN as assumed in design. The pavement analysis was carried out using
EVERSTRESS program (Sivaneswaran et al, 2001) developed by the Washington
State Department of Transportation (WSDOT). Result of the analysis is shown in
71
Table 3.3 while details of the layered elastic analysis are presented in Tables 3.12A,
3.13A and 3.14A of Appendix A.
The LEADFlex pavement material parameters are as presented in Table 3.2. The
pavement was loaded as described in section 3.2.6 and the effect of single and
multiple wheel load configurations are as presented in Table 3.3. From Table 3.3, the
critical loading condition was determined to be the single, axle, single wheel since it
recorded the highest maximum stresses, strains and deflections.
Figure 3.1: Typical Single Wheel and Dual-wheel Tandem Axle
200mm 200mm
1800mm
I
200mm 200mm 200mm 200mm
13
00
mm
1800mm
305m305m
305m305m
II
III
x
y
72
Table 3.2: Load and materials parameter for determination of critical wheel load
Wheel
Load
(kN)
Tire
Pressure
(kPa)
Pavement Layer
Thickness
(mm)
Pavement Material Moduli
(MPa)
Poison’s Ratio
A.C. Surface
T1
Base
layer
T2
A.C
Surface
E1
Base
E2
Subgrade
E3
A.C
Surface
Base Subgrade
40 690 100 300 3450 329 52 0.35 0.40 0.45
20 690 100 300 3450 329 52 0.35 0.40 0.45
20 690 100 300 3450 329 52 0.35 0.40 0.45
Table 3.3: Critical Loading Configuration Determination
Load Configuration Axle Load
Pavement Response
Maximum Strain (10-6)
Maximum Stress (kPa)
Max. Deflection (10-6mm)
Below Asphalt Layer
On Top Subgrade Layer
Below Asphalt Layer
On Top Subgrade Layer
Below Asphalt Layer
On Top Subgrade Layer
Single Axle, Single wheel
(I)
40kN 285.25 872.52 1372.89 48.85 699.903 587.450
Single Axle, Dual Wheel
(II)
20kN 247.61 652.76 1110.83 38.48 617.261 536.478
Tandem Axle, Dual
Wheel
(II + III)
20kN 241.61 643.86 1090.00 39.47 779.429 699.840
3.2.7 LEADFlex Pavement Model
The LEADFlex pavement is a 3-layer pavement model (surface, base and subgrade)
as shown in Figure 3.2. The load and material parameters are as presented in Table
3.4, Single Axle with single wheel load configuration was assumed. The study
considered application of 40kN load on a single tire having tire pressure of 690 kPa
(AASHTO, 1993).
73
Table 3.4: LEADFlex Pavement Load and materials parameter
Wheel Load (kN)
Tire Pressure
(kPa)
Pavement Layer Thickness
(mm)
Pavement Material Moduli (MPa)
Poison’s Ratio
A.C. Surface
T1
Base layer
T2
A.C Surface
E1
Base
E2
Subgrade
E3
A.C Surface
Base Subgrade
40 690 50 ≥ 50 3450 329 10-103 0.35 0.40 0.45
40 690 75 ≥ 75 3450 329 10-103 0.35 0.40 0.45
40 690 100 ≥100 3450 329 10-103 0.35 0.40 0.45
3.2.8 Environmental Condition
The two environmental parameters that influence pavement performance are
temperature and moisture. Temperature conditions for the particular site have to be
known to properly design an asphalt pavement, hence the test temperature should
be selected so that the asphalt concrete modulus in the test matches with that in the
field (Brown, 1997). In this study, the influence of temperature was accounted for by
characterization of asphalt concrete at the pavement temperature. In the Asphalt
Institute design method, pavement temperature can be correlated with air
temperature (Witczak, 1972) as follows:
Figure 3.2: Typical LEADFlex Pavement Section Showing Location of Strains
µ3 = 0.45, E3 = 10 – 103MPa
εr1
P
µ1 = 0.35 E1 = 3450MPa
µ2 = 0.40 E1 =329MPa
a
εz2
h1≥50mm
h2 >50mm
74
MMPT = MMAT( ) ( )
+
+−
++ 6
4
34
4
11
zz
(3.11)
Where,
MMPT = mean monthly pavement temperature
MMAT = mean monthly air temperature
Z = depth below pavement surface (inches)
The effect of moisture (seasonal variation) was accounted for by calculating a
weighted average subgrade resilient modulus based on the relative pavement
damage over a one year period as described in section 3.2.3.
3.2.9 Pavement Layer Thickness
Mechanistic-Empirical design combines the elements of mechanical modeling and
performance observations in determining the required pavement thickness for a set
of design conditions. The thicknesses of the asphalt layer for the various traffic
categories are as presented in Table 3.1. The minimum thicknesses of cement-
stabilized base layer were determined based on pavement response using the asphalt
institute response model (Asphalt Institute, 1982). The required minimum base
thickness was determined as that expected traffic and base thickness that resulted in
a maximum compressive strain and allowable repetitions to failure (Nr) such that the
damage factor D is equal to unity.
3.2.10 Traffic Repetition Evaluation
The study considered evaluation of future traffic and determination of axle load
repetition in the form of 80kN equivalent single axle load (ESAL). Vehicle
classification was in accordance with the procedure proposed for the new Nigerian
Highway Manual (1973) where vehicles are classified into 8 different classes as
shown in Table 3.5. Standard operational factors for single and tandem axles based
on the AASHTO road test were used (Nanda, 1981).
75
Table 3.5: Vehicle Classification (Source: Oguara, 2005)
Class Description (Nanda, 1981)
Typical ESALs per Vehicle
1 Passenger cars, taxis, landrovers, pickups, and
mini-buses.
Negligible
2 Buses 0.333
3 2-axle lorries, tippers and mammy wagons 0.746
4 3-axle lorries, tippers and tankers 1.001
5 3-axle tractor-trailer units (single driven axle,
tandem rear axles)
3.48
6 4-axle tractor units (tandem driven axle, tandem
rear axles)
7.89
7 5-axle tractor-trailer units(tandem driven axle,
tandem rear axles)
4.42
8 2-axle lorries with two towed trailers 2.60
3.2.10 Determination of Design ESAL
The expected traffic was determined in accordance with the procedure outlined in
the Nigerian Highway Manual part 1 (1973). A typical example of the procedure for
computation of expected traffic repetitions is as presented in Table 3.6.
Highway Facility: 6-lane (3 lane in each direction)
Traffic Growth rate: 4%
Design Period: 20 year
Traffic Category
- Passenger cars, taxis, landrovers, pickups, and mini-buses: 1321veh/day
- Buses: 520 veh/day
- 2-axle lorries, tippers and mammy wagons: 5 veh/day
- 3-axle lorries, tippers and tankers: 3 veh/day
- 3-axle tractor-trailer units (single driven axle, tandem rear axles): 2 veh/day
- 4-axle tractor units (tandem driven axle, tandem rear axles): 3 veh/day
- 5-axle tractor-trailer units(tandem driven axle, tandem rear axles): 1 veh/day
- 2-axle lorries with two towed trailers: 1 veh/day
76
Procedure
Step 1: Enter vehicle class, equivalent operational factor and number of vehicles in
24 hours (as determined from traffic studies) in columns 1, 2 and 3
respectively.
Step 2: Determine total ESAL per day in column 4 by multiplying columns 2 and 3.
Step 3: Determine total ESAL per year in column 5 by multiplying column 4 by
number of days in a year
Step 4: Determined the ESAL per year for all the axle categories as shown in
column 5 (FHWA, 2001). The design ESALs is obtained in column 7 for a
given growth rate by multiplying columns 5 with the multiplier in column
6.
The expected traffic repetition is therefore determined using equation 3.12.
Ni = ( )
g
gxxFxAADT
n11
365−+
(3.12)
Where,
Ni = Expected traffic repetition (ESAL)
F = Equivalent operational factor
g = growth rate in %
n = design period (20yrs)
Where growth rate data is not available, 4% growth rate is recommended for 20 year
design period for flexible (AASHTO, 1972).
From Table 3.6, ESAL = 2.55 x 105
77
Table 3.6: Vehicle Classification
Vehicle Class
Equivalent Operational
Factor
Number of
Vehicles in 24 hours
Total ESAL
per day
(2) x (3)
Total ESAL per Year
(4) x 365 days
Multiplier
( )g
gn
11 −+
Total ESAL in 20 years
(1) (2) (3) (4) (5) (6) (7)
1 negligible 1321 - - - -
2 0.333 5 1.665 607.725 29.78 18098.05
3 0.746 3 2.238 816.87 29.78 24326.39
4 1.001 2 2.002 730.730 29.78 21761.14
5 3.48 3 10.44 3,810.6 29.78 113479.70
6 7.89 - - - - -
7 4.42 1 4.42 1,613 29.78 48044.07
8 2.60 1 2.60 949 29.78 28261.22
Total ESAL in 20 years 254666.5
3.3 Analytical
The analytical part involved the analysis and the design of the 3-layer pavement
system, evaluation and prediction of maximum horizontal tensile strain at the
bottom of the asphalt layer and maximum vertical compressive strain at the top of
the subgrade using the Layered Elastic Analysis (LEA) procedure. Pavement
analysis was carried out using the EVERSTRESS (Sivaneswaran et al, 2001) program
developed by the Washington State Department of Transportation.
3.4 Summary of the LEADFlex Procedure
The summary of LEADFlex Procedure is itemized below;
1. Material characterization of the asphalt concrete, cement stabilized lateritic
base and subgrade were carried out to determine the design elastic modulus
and resilient modulus of the layers.
78
2. The minimum pavement base thicknesses required to withstand the expected
traffic repetitions were determined using the layered elastic analysis program
EVERSTRESS (Sivaneswaran et al, 2001). The minimum pavement thickness is
referred to as the LEADFlex pavement section.
3. Having determined the required minimum pavement thickness, layered
elastic analysis of the LEADFlex pavement was carried out to compute
pavement response in terms of horizontal tensile strain at the bottom of the
asphalt layer and vertical compressive strain on top the subgrade.
4. Using regression analysis, simple regression equation were developed to
establish the relationship between traffic repetitions and pavement thickness,
pavement thickness and horizontal tensile strain, pavement thickness and
vertical compressive strain.
5. The Asphalt Institute response model (Asphalt Institute, 1982) was adopted to
compute the allowable tensile and horizontal strains, and number of
repetitions to failure in terms of fatigue and rutting criteria.
6. Damage factors D was computed for both fatigue and rutting criteria such that
D ≤ 1.
7. The Procedure was validated using result of layered elastic analysis and
measured strain data from the Kansas Accelerated Testing Laboratory (K-
ATL).
8. Algorithm were written using the developed regression equations and visual
basic codes were used to develop the LEADFlex Program for the design and
analysis of cement-stabilized lateritic base low volume asphalt pavements.
The flow diagram for the LEADFlex Procedure is as shown in Figure 3.1.
79
Figure 3.3: Flow Diagram for LEADFlex Procedure
Material
Inputs
Traffic
Inputs
Pavement Layer
Thickness
Yes
YES
NO NO
Final Design
D>1?
D<<1?
LEADFlex Model
No
Allowable Load
Repetitions
Nf, Nr Expected Load
Repetitions
Ni
Is Horizontal
Tensile Strain at the Bottom of
Asphalt Layer > Allowable?
Is Vertical
Compressive Strain at the Top of Subgrade > Allowable?
Pavement Response
εt, εc
Compute Damage D
Ni/Nf, Ni/Nr
YES
Increase
Pavement
Thickness