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