performance based design of flexible pavement for a...

Performance based design of flexible pavement for a DBOT

National highway project

Introduction

• Indian road network of 33 lakh Km is second largest in the

world

• Majority of the pavements are flexible type.

• Design is based upon the IRC 37 -2001

No performance prediction

No alternate design

Design upto 150 msa

• Last five years private sector involved in construction and

funding of public infrastructure work.

• DBOT (Design/Build/Own/Transfer) projects are public

infrastructure projects which employ a particular form of

structured financing.

• Many of the road projects have been awarded as DBOT

projects.

• Need for the design which is capable of

Predicting the performance

Future maintenance requirements

Identifying the cash flow for the project

Best usage locally available materials

Life cycle cost

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Methodology

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Testing and design

Testing • Four representative soil samples collected from Ahmedabad Viramgam

Maliya road project.

• The properties of soil like gradation , plasticity index, maximum dry

density and optimum moisture content ,california bearing ratio,

unconfined compressive strength, sulphate content and Ph were tested.

• The locally available soils are fine grained with medium to high

plasticity with low CBR.

Tests on soils.

1.362.47 1.46

19.31

0

5

10

15

20

25

CBR, %

Sample - 1

Sample - 2

Sample - 3

Sample - 4

1.78 1.871.71

2.19

0.00

0.50

1.00

1.50

2.00

2.50

MDD g /cc

Sample - 1 Sample - 2 Sample - 3 Sample - 4

14.70

12.50

15.20

5.80

0

2

4

6

8

10

12

14

16

18

20

OMC %


68

21

92

6152

19

70

61

82

26

54

77

25

1220 18

0

20

40

60

80

100

LL, % PL, % FSI, % SILT+CLAY, %


Observations

• The soils exhibit high plasticity with more percentage of fines and free swell

index. Three soil samples are highly plastic with plasiticity index more than 30

and fails the criteria of MORTH.

• The free swell index of the same soils are more than 50 and are higher than

allowable limits.

•The california bearing ratio of soil 4 is good and remaining 3 soils are below

3% .

•The soil requires modification and the modifiers are selected from the chart

below.

Guide for selection of binders for various plasticity index values andcontent of fines ( after AUSTROADS 1998)Source :Mix design for stabilised pavement layers AUSTROADS(2002)

Selection of binder

Soil stabilisation• Lime and chemical modifiers are selected for modification.

• Soil is modified with Lime and RBI grade 81 at 2 %, 4% , 6%, 8% to

the weight of soil.

• The unconfined compressive strength of modified soil are tested for 7

days by curing at room temperature and packing the samples with

polythene bags to prevent moisture loss.

• Resilient modulus of the modified soil is tested at the percentage of

modifier at which UCC is high .

Soil stabilisation with lime

0.00

0.20

0.40

0.60

0.80

1.00

1.20

0 2 4 6 8 10

UC

C S

tren

gth,

N/m

m2

Lime, %

UCC StrengthSample 1 Sample 2Sample 3 Sample 4

0.29

0.22

0.18 0.

23

0.53

0.40

0.27

0.70

0.55

0.46

0.23

0.96

0.57

0.66

0.23

1.00

0.52

0.70

0.22

1.14

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1 2 3 4

UC

C M

Pa

Samples

Untretaed 2% 4% 6% 8%

Soil stabilisation with RBI grade 81

0.0

1.0

2.0

3.0

4.0

0 2 4 6 8 10

UC

C M

pa

Lime %

Sample 1 Sample 2 Sample 3 Sample 4

0.29

0.22

0.18 0.23

0.26 0.

46

0.25

1.43

0.40 0.

58

0.35

2.22

0.73 0.

93

0.51

2.67

0.98 1.

22

0.63

3.43

0.0

1.0

2.0

3.0

4.0

1 2 3 4

UC

C M

pa

samples

un treated 2% 4% 6% 8%

Soil stabilisation with lime

586

117

3319

330

500

1000

1500

2000

2500

3000

3500

SO3 mg/l

Sample - 1

Sample - 2

Sample - 3

Sample - 4

8

8.5

9

9.5

10

10.5

11

11.5

0 5 10pH

Lime, %

pH

Sample 1 Sample 2

Sample 3 Sample 4

Comparision of stabilised soil

0

0.5

1

1.5

2

2.5

1 2 3 4

UC

C M

pa

Soil samples

2 %

Lime RBI

0

0.5

1

1.5

2

2.5

1 2 3 4

UC

C M

pa

Soil samples

4 %

lime RBI 81

0

0.5

1

1.5

2

2.5

3

3.5

4

1 2 3 4

UC

C M

pa

Soil samples

6 %

Lime RBI 81

0

0.5

1

1.5

2

2.5

3

3.5

4

1 2 3 4

UC

C M

pa

Soil samples

8%

Lime RBI 81

Observations

• The unconfined compressive strength of soils increased with increase of

lime content except third sample. So the soil sample 3 was tested for Ph at

varying percentages of lime and the soil is not reactive with lime.

• The unconfined compressive strength of soil is increasing with increasing

percentage of RBI grade 81. Even soil sample 3 reacted well with RBI

grade 81.

• The resilient modulus of stabilised soil are tested at 6 % of lime and RBI

grade 81

Resilient Modulus• The Resilient Modulus (MR) is a subgrade material stiffness test.

• A material's resilient modulus is actually an estimate of its modulus of

elasticity (E).

• While the modulus of elasticity is stress divided by strain for a slowly

applied load, resilient modulus is stress divided by strain for rapidly

applied loads – like those experienced by pavements.

Resilient modulus

0

50

100

150

200

0 5 10 15 20

Mr i

n M

pa

Cycles

Mr Soil 3

soil rbi

0

50

100

150

200

250

300

0 5 10 15 20

Mr i

n M

pa

Cycles

Mr Soil 2

soil lime rbi

0

50

100

150

200

0 5 10 15 20

Mr i

n M

pa

Cycles

Mr Soil 1

soil lime rbi

0

100

200

300

400

0 5 10 15 20

Mr i

n M

pa

cycles

Mr Soil 4

soil lime rbi

Design resilient modulus• The resilient modulus values are varying in each cycle and the

designed value is difficult to calculate as the modulus varying much.

• Mr value determined at a deviatoric stress of 6Psi is adequate for

design purposes (after Little,2000).

• Out of 4 soils , soil3 was not reactive with lime and it has high

sulphate contents.

• Soil 3 is not considered for design

Design resilient modulus

• The cost of RBI81 is many times the cost of Lime and the design

modulus were more or less equal. So the design was carried out with

lime stabilised soil only.

105

160

255

115

180195

0

50

100

150

200

250

300

1 2 3

Mr i

n M

pa

samples

Design resilient modulus

lime rbi

Pavement design• Pavement design involves calculating the thickness of pavement

layers. For some set of inputs like traffic loading , environmental

conditions and material properties.

• The design of the pavement is done in both empirical and Mechanistic

empirical method in the present study.

• Design as per IRC 37 2001( empirical design) is considered as basic

design.

• Mechanistic empirical design is used to develop alternate designs.

Design as per IRC 37 2001• Design inputs

– Design CBR = 5– Rolling terrain/ plain – Design traffic 150 msa– Annual traffic growth 7.5

Mechanistic Empirical Design• The mechanistic part of ME design is directed to calculating one or more

responses in the pavement structure as a function of material properties

,layer thickness and loading conditions.

• These responses must then be related to observed performance

(smoothness, deterioration, fatigue cracking etc.,).

• The tensile strain value at the bottom of bituminous layer and compressive

strain at the top of subgrade are critical strains used in these models.

• Circly software is used to calculate the critical strains in the pavement.

• Prediction models for distress to predict the performance

• The resilient modulus (Mr) for all layers except subgrade are calculated as

per IRC 37 (2001)

Design frame workENVIRONMENTAL

CONDITIONSTRAFFIC

CONDITIONSMATERIAL

PROPERTIES LAYER THICKNESS

MECHANISTIC PAVEMENT MODEL

PAVEMENT RESPONSE

PERFORMANCE PREDICTION

Damage factors

D<critical value

FINAL DESIGN

NO

YES

Inputs for M-E designTYPE OF MIX RESILIENT MODULUS

(Mpa)

POISON’S RATIO

Bituminous concrete 60/70 1270 0.35

Dense bituminous macadam

80/100

797 0.35

Wet mix macadam 250 0.40

Granular sub base 170 0.40

Stabilised subgrade type1 100 0.40



• The design is done by keeping the modulus of the layers as constant

and changing the thickness. The critical strains for each input variables

are calculated.

• The fatigue life and rutting life of the pavement are predicted from

models.

• The design developed as per IS 37 (2001) has critical strains below

the trigger value and so the both fatigue and rutting life are found to be

more than 150 msa. This critical strains are considered as bench mark.

• For the same values of critical strains the various design thicknesses

are developed by introducing the stabilized layers with resilient

modulus 100 Mpa , 150 Mpa and 250 Mpa respectively.

Stabilised vs Unstabilsed

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Circly software interface

Output from Circly

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PREDICTION MODELS FOR DISTRESS•

Fatigue cracking prediction model:

Nf = 2.21*10-4 *(1/et)3.89 * (1/E)0.854

Where

Nf = Number of cumulative standard axles to produce 20 percent cracked

surface area

et = Tensile strain at the bottom of bituminous layer.

E = Elastic modulus of bituminous layer.

Source IRC 37(2001)

Rutting prediction model:

Nr = 4.1656*10-8*(1/ez)4.5337

Where

Nr= Number of cumulative standard axles to produce rutting of 20mm

ez = vertical subgrade strain

Source IRC 37(2001)

Roughness prediction model

IRI = 60.301* e0.096*Age

Where

IRI = International roughness index (inch/mile)

Age in years

Source : zero maintenance performance models using LTTP data

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•The construction cost for a typical four lane for 1 Km is calculated.

•The rates are taken as per the BOQ ( bill of quantities) of the GSRDC

road packages.

• The cost calculated includes only the pavement layers cost other costs

like kerb , earthen shoulder etc., are not considered.

•The cost of the pavement designed as per IS 37 (2001) is considered as

datum and the savings of alternate designs are calculated comparing with

that design cost.

Sl.no BC (mm) DBM (mm)

WMM (mm)

GSB (mm) SUBGRADE (mm)

MODULUS SUBGRADE (Mpa)

COST FOR Ikm croresrs

SAVINGS in rs

1 50 170 250 300 500 50 3.00 ----------

2 50 170 240 270 200 100 2.99 165495

3 50 170 240 250 200 150 2.97 361495

4 50 170 240 240 200 200 2.96 459495

5 50 170 225 240 200 250 2.93 716737.5

0

200000

400000

600000

800000

1000000

100150

200250

Savi

ngs

in R

s

Stabilised subgrade Modulus

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In the present study no structural maintenance is required as the pavement

is safe structural.

Functional maintenance is required to maintain pavement in good

condition.

Various maintenance strategies are developed which includes timing and

treatments.

The trigger value of UI is 2000 mm/ Km.

Six strategies are considered and in which four maintenance treatments are

used. The performance jump of each treatment are given below.

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TREATMENT PERFORMANCE JUMP

IRI inch/ Mile UI mm/Km

Thin overlay 71 1121

Micro surfacing 21 331

Surface dressing 11 174

Crack sealing 3 47

Source :

Maintenance strategy

no

Thin overlay Micro surfacing Surface dressing Crack sealing

1 FA 12 years FA 7years FA 9 years FA 4 years

2 FA 6 years

NA 6 years

------------- FA 3 years

NA 3 years

FA 2 years

NA 2 years after Thin

overlay.

3 FA 6 years

NA 6 years

------------- FA 3 years

NA 3 years after thin

HMA

Every year except at

times of other

treatments

4 ------------- FA 3 years

NA 8 years

NA 3years

FA 2 years

NA 13 years

Every year except at

times of other

treatments

5 ------------ FA 3 years

Every 3 years

13 year 14 year

6 ------------ FA 5 years

NA 5 years

NA 4 years

FA 3 years

Every 3 years

------------

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The zero maintenance model for roughness progression is used to calculate

the roughness of pavement with age.

The preventive maintenance strategies as stated above are compared with

the zero maintenance to find their effectiveness.

Effectiveness of each strategy is graphically represented.

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0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 2 4 6 8 10 12 14

UI m

m/K

m

age in years

Maintenance strategy 1

maintenance 1 zero maintenance THRESHOLDVALUE

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0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 2 4 6 8 10 12 14

UI m

m/K

m

age in years


maintenance 2 zero maintenance THRESHOLDVALUE

0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 2 4 6 8 10 12 14

UI m

m/k

m

age in years


maintenance 3 zero maintenance THRESHOLD…

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0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 2 4 6 8 10 12 14

UI m

m/K

m

age in years



0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 2 4 6 8 10 12 14

UI m

m/K

m

age in years



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0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 2 4 6 8 10 12 14

UI m

m/K

m

age in years



0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 2 4 6 8 10 12 14 16

UI m

m/K

m

age in years

Maintenance strategies

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• Preventive maintenance strategies are of bituminous mixes , future

prediction of the price of bitumen is a problem.

• The rise in bitumen price is not in the range of variation of consumer price

index.

• In order to predict the rise in bitumen price , analysis of the bitumen price

for past 5 year is done.

• It is found that the rise in bitumen cost is in the range of 12 to 15%.

• In the present study the future cost of the treatments are found at a rise of

12 %.

•

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• After calculating the future rate of all treatments, then they were converted

to present worth by using discounted rate of interest as 10%.

• The treatment cost is calculated for one kilometre length of a typical four

lane highway.

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0.00

0.50

1.00

1.50

2.00

12

34

56

Net

pre

sent

wor

th in

rs

cror

es

Maintenance strategies

Net present worth of maintenance strategies

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• Even though the net present worth of maintenance strategy 1 is less than

all other strategies.

• The best strategy is found by using benefit – cost analysis.

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The benefit area is calculated for each strategy and the ratio of benefit

area to net present worth is calculated.

The strategy which has greater value is the best.

Benefit area for each maintenance strategy is the area between the

threshold curve, maintenance performance curve and zero maintenance

curve.

The benefit area indicates the decrease in roughness and increase in life of

the pavement.

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BENEFIT

AREA

From the above analysis it is clear that the maintenance strategy 2 has more

benefit. So it is considered as best

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0

2000

4000

6000

8000

12

34

56

bene

fit a

rea

strategy

Benefit cost analysis

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In the present study only initial construction cost and maintenance costs are

considered.

As the resilient modulus of the subgrade is increasing the life cycle cost is

decreasing.

Stabilisation is not only for poor soils but also for good soils to yield

economic designs.

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sl.no Design type

Construction cost in crores Rs

Maintenance costs in crores Rs

Life cycle cost in

crores Rs

1 without SSG

3.00 1.34 4.34

2 100 Mpa SSG

2.99 1.34 4.32

3 150 Mpa SSG

2.97 1.34 4.30

4 250 Mpa SSG

2.93 1.34 4.27

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The performance of the pavement is dependent on responses ( strains).

The critical pavement responses

– Tensile strain at bottom of bituminous layer.

– Compressive strain on top of subgrade.

The thickness design procedure is based on limiting the critical pavement

responses in pavement layers.

Sensitivity analysis for pavement responses is carried out .

The input variables mostly affecting the fatigue cracking and rutting are

determined.

In the analysis each layer thickness and modulus are varied one at a time

and keeping other values to their corresponding base values.

The change in the predicted critical pavement response due to a change in a

given parameter is evaluated using the CIRCLY finite element program.

A data of 400 designs are generated to establish synthetic data base.

Pavement structure for synthetic data base generation

Input parameter Minimum Maximum Increments Base value

H1 50 mm 100 mm 10 mm 50 mm

H2 50 mm 475 mm 25 mm 170 mm

H3 50 mm 500 mm 50 mm 250 mm

H4 50 mm 500 mm 50 mm 300 mm

H5 100 mm 500 mm 100 mm 400 mm

E1 1000 Mpa 3500 Mpa 500 Mpa 1270 Mpa

E2 1000 Mpa 3000 Mpa 500 Mpa 797 Mpa

E3 100 Mpa 700 Mpa 50 Mpa 250 Mpa

E4 50 Mpa 500 Mpa 50 Mpa 170 Mpa

E5 50 Mpa 800 Mpa 50 Mpa 100 Mpa

A regression approach is adopted to develop the pavement response model

using input variables and critical responses in pavement layers.

Tensile strain modelεt = 0.00051-6.4e-7H1-1.78e-8E1-5e-7H2-3.3e-8E2-8.4e-8H3-2.8e-7E4-1.9e-

8H4-2.3e-7E4+3.64e-10H5-1.8e-8E5 ( R2 = 0.792)

Compressive strain model:

εc = 10-8(2.85e4-66H1-0.51E1-25H2-E2-16H3-5.4E3-2.6H4+10.5E4-

1.8H5-9.2E5)

Predicted Vs Actual tensile strain Predicted Vs Actual compressive strain

A visual basic program is developed by using strain models.

The program calculates the fatigue life of the pavement, construction cost

and year of treatment required.

The inputs required are layer thicknesses , resilient modulus and traffic

data.

The program gives an idea about the performance of the pavement, cost

etc., without using the CIRCLY software.

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Stabilising the subgrade soil has great impact on the pavement

construction cost. From the present study

It is better to stabilise the good soil also because higher the modulus

lower the crust thickness. In the present study soil 4 is modified even it is

good.

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0

500000

1000000

100150

200250

Savi

ngs

in R

s

Stabilised subgrade Modulus

The thickness of the bituminous layers can be decreased by inducing higher

modulus base , sub base and stabilised subgrade courses.

Type of maintenance and timing of maintenance is more important. In the

present study the strategy 2 has right type of maintenance and timing , so it

has more benefit than other strategies.

Existing natural soil can be stabilised instead of transporting the soil from

borrow areas. Soil samples 1 and 2 are existing soils in the present study.

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As the soil properties varies greatly in a stretch , a common design for a

total stretch may not be economical. Develop alternate designs based upon

the properties of materials available in stretch.

Even though the initial construction cost of the pavement by stabilising soil

it will give more long term benefits.

Best utilisation locally available materials can be done by stabilisation

process.

Proper inspection should be ensured while stabilising is done like mixing of

additive, addition of water etc.,

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Selection of additive plays a key role in stabilisation process. Proper

preliminary investigation should be done before selecting additive.Adequate curing and proper handling of test samples like Unconfined

compressive strength , Resilient modulus is important. It will affect the test

results.

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