MKAQ 1053 / SKAA 4813€¦ · Reliability • Definitions –Reliability = 1 –P[Failure]...

MKAQ 1053 / SKAA 4813

Pavement Design & Construction/ Advanced Highway Engineering

Dr. Haryati Yaacob

Office Location

• M50- Room 02-34

– 07-5538666/ 019-7341405

• haryatiyaacob@utm.my

• yaacob.h@gmail.com

• Topic 1 – Flexible Pavement Design:

– AASHTO Method,

– Asphalt Institute Method,

– ATJ 5/85 (revised 2013)

• Topic 2 – Rigid Pavement Design

- Concrete pavement in Malaysia

- Concrete pavement elements

- Subgrade and sub-base design

- Shoulder options

- Design of rigid pavement

- AASHTO Method

- PCA Method

- Joints

- Steel design

• Topic 3 – Interlocking Block Pavement

Recommended Text

• Huang, Y.H., Pavement Analysis and Design,

Prentice Hall, 1993.

• Freddy L. Roberts et. Al., Hot Mix Asphalt

Materials, Mixture Design and Construction,

NAPA, 1996.

• Yoder & Witczak, Principles of Pavement

Design, Wiley Publications, 1975.

Flexible Pavement

• Structure

– Surface course

(waterproof, anti-skid)

– Base course

– Subbase course

– Subgrade

Pavement types

Type of Pavement & their Load

Distribution

Pavement Types & How They

Effect the Subgrade

Structural Design of Flexible

Pavements

Subgrade

Granular Subbase Layer

Granular Base Layer

Binder Layer

Surface Layer

Design Procedures

• AASHTO Method

• Asphalt Institute Method

• ATJ 5/85 (2013)

AASHTO METHOD

AASHO Road Test

• 1958 - 1960 near Ottawa, Illinois

• Soil uniform and representative of large

portion of US

• 4 large and 2 smaller loops

• Variables included

– pavement thickness

– load magnitude

– environmental effects

• Introduced concept of serviceability (PSR)

• Forms basis of AASHTO Method

AASHO Road Test

Development of Design• AASHO Road Test

– Basis for most currently acceptable design methods

– Importance of traffic loads and repetition

• Design has been largely an empirical process

– Current AASHTO Procedure

• AASHTO is still a statistically based empirical

design method

– Original models revised and extended to make them

more widely applicable

AASHTO Design Variables

• Time

• Traffic

• Reliability

• Materials

• Environment

• Serviceability

Time

• Performance Period

– Time from initial

construction to first

rehab

– Time between rehabs

• Analysis Period

– Time that any design

must cover

– Often equal to

performance period

Highway Analysis

Period

High Volume Urban 30 - 50

High-Volume Rural 20 - 50

Low-volume paved 15 - 25

Low-volume

aggregate surface

10 - 20

Traffic: Primary Design Input

• Complex Problem

– Traffic is composed of many vehicle types

• “Mixed” traffic

• Variable load magnitude

• Variable tire and axle configurations

• Variable tire inflation pressure

• Variable speeds

– Need to predict future growth, changes

– Estimate where traffic will travel

• Wheel wander

• Lane selection

Load Observations/Assumptions

• Different wheel loads and configurations produce different pavement response

• Larger, more concentrated loads = more stress/strain

• Repeated stress/strain can cause eventual failure

• Fewer applications of heavy loads can cause comparable damage to higher applications of lighter loads

• Load repetitions can be correlated to loss of serviceability

Mixed Traffic –Axle configuration

Truck Wheel Loads

Tractor

Single Axle, Single Tires

Trailer

Single Axle, Dual Tires

Tandem Axle, Dual Tires

• Legal axle weight: 18-20 kip

• Tire pressure: 80 – 120 psi

• More axles can carry more

weight, but spread out the

damaging effect

ESALs

• Equivalent Single Axle Loads

• Used for highway pavements to convert mixed traffic to a number of standard axles for design

• Defined as:– Total # of applications of a standard axle (generally

18,000 lb single) required to produce the same damage or loss of serviceability as a number of applications of one or more different axle loads and/or configurations over life of pavement

21

ESAL Calculation

ESALi = Current Traffic x Growth Factor x 365 x ESAL Factor

m

i

itotal ESALESAL1

Growth Rates• Large errors can result in ESAL calc’s from poor

estimates of future traffic

• Best estimates are obtained by forecasting

vehicle types separately

• Forecasting techniques include

– Historical trends (regression)

– Engineering judgment

– Compound interest equation

– Straight line projections

23

Predict Future

• How fast will traffic grow?

• What is the design level of traffic?

• Examine historical trends

– Develop best estimate of future growth

rate

• Apply growth factor to current volume

g

gFactorGrowth

n 1)1(

Lane and Directional Distributions

• Typical Assumptions

– Directional distribution = 50%

– Lane Distribution-Typically design for

‘heaviest’ loaded lane

# Lanes/Direction %Traffic In Design Lane

1 100

2 80-100

3 60-80

4 or more 50-75

Conversion of mix traffic to ESALs

Reliability• Definitions

– Reliability = 1 – P[Failure]

– “The reliability of a pavement design-performance process is the probability that a pavement section designed using the process will perform satisfactorily over the traffic and environmental conditions for the design period.”

• 1993 AASHTO Guide

Reliability

Recommended Reliability

Functional Class Urban Rural

Interstate/Freeway 85-99.9 80-99.9

Principle Arterials 80-99 75-95

Collectors 80-95 75-95

Local 50-80 50-80

Variability

• Need design standard deviation

– Account for variability of all input variables

• Recommended values

– S0 = 0.45 (flexible)

– S0 = 0.35 (rigid)

Serviceability – ability of a pavement to

serve the type of traffic

PSI

• 0 – 5

• 0 = Impassible

• 5 = Perfect

PCRDSVPSI 01.0)(38.1)1log(91.103.5 2

(Flexible Pavement)

(Rigid Pavement)

PCSVPSI 09.0)1log(80.141.5

Materials

• Need to characterize stiffness

– E, Mr

• Account for seasonal variability

• Determine structural coefficients

Environment

• Need to consider freeze/thaw and swelling

of soils

– AASHTO has an established procedure

– We will not go through the procedure

Seasonal Effects on Unbound Layers

10

100

10001

-Feb

3-M

ar

2-A

pr

2-M

ay

1-J

un

1-J

ul

31

-Ju

l

30

-Au

g

29

-Sep

29

-Oct

28

-No

v

28

-Dec

Date

Ela

stic

Mo

dulu

s, M

Pa

Seasonal Effects on HMAC

Cell 1 - Mn/ROAD (1993-1996)

100

1000

10000

100000

0 30 60 90 120 150 180 210 240 270 300 330 360

Day of Year

Mo

du

lus,

MP

a

AASHTO Design Values

• Select average values for everything but

not subgrade

• Compute relative stiffness of subgrade for

design

Effective Subgrade Modulus/ Effective

Roadbed Soil Resilient Modulus, Mreff

Definition: an equivalent modulus that would result in the same damage if

seasonal modulus values were actually used

Finding Mreff

• Find seasonal modulus every month

– Non destructive deflection testing

Finding Mreff

• Find relative damage, uf for each season

Uses AASHTO Damage Equation

mf = 1.18x108MR-2.32

• Determine weighted average uf

• Find Mreff corresponding to uf

Structural Number

SN = a1D1 + a2m2D2 + … + anmnDn

Structural Coefficients

• ai = measure of relative ability of a unit

thickness of a given material to function as

a structural component of the pavement

Asphalt Concrete Structural Coefficient , a1

Granular Base Layer Coefficient (untreated) , a2

a2= 0.249 (log E2) -0.977

Granular Subbase Layer Coefficient , a3

a3-= 0.227 ( log E3)- 0.839

Drainage Coefficient, mi

• Depends on quality of drainage and

availability of moisture

Quality Water < 1% 1 -5 % 5 - 25% > 25%

Removed

Excellent 2 hours 1.40 - 1.35 1.35 - 1.30 1.30 - 1.20 1.20

Good 1 day 1.35 - 1.25 1.25 - 1.15 1.15 - 1.00 1.00

Fair 1 week 1.25 - 1.15 1.15 - 1.05 1.05 - 0.80 0.80

Poor 1 month 1.15 - 1.05 1.05 - 0.80 0.80 - 0.60 0.60

Very Poor Never Drain 1.05 - 0.95 0.95 - 0.75 0.75 - 0.40 0.40

mi Values for Modifying Structural Layer Coefficients

(Untreated Base and Subbase Materials)

% Time pavement structure is exposed to

moisture levels approaching saturation95%

Design Equation

• Based on road test

• Determines number of ESALs before DPSI

is reached

07.8log32.2

1

10944.0

5.12.4log

20.01log36.9log

19.5

018

D

RR M

SN

PSI

SNSZW

Design Procedure

• Determine SN required above each layer

• Find thickness to satisfy SN above each

layer

AASHTO Layer Thickness Determination

Subbase E3 a3 m3

Base E2 a2 m2

Surface E1 a1

SN3 SN2 SN1

D1

D2D3

Roadbed Soil

SN= a1D1 + a2D2m2 + a3D3m3

D1≥ SN1/a1

D2 ≥( SN2- a1D1)/ a2m2

D3 ≥ (SN3- a1D1-a2D2m2)/a3m3

Minimum Thickness - AASHTO

ESAL, 1000 AC Base

< 50 1 4

50 – 150 2 4

150-500 2.5 4

500 – 2,000 3 6

2,000 – 7,000 3.5 6

> 7,000 4 6

Design example

• Calculate D1, D2 and D3. Given:

– E1= 400,000psi; E2= 30, 000psi; E3= 11,000

– a1= 0.42; a2=0.14; a3= 0.08

– m2=m3=1.2

– Mreff = 5,700 psi

– w18= 18.6 x 106

– R = 95%

– So= 0.35

– ΔPSI = 2.1

Asphalt Institute Method

Mechanistic-Empirical Design

Design Criteria

• Mechanics of materials coupled with

observed performance

Number of Loads Until Failure

Str

ess o

r S

train

Performance Equations

• Fatigue

– 11% AC

– VTM 5%

– 20% Cracking at AASHO Road Test

• Rutting

– ½” Rut

– Need to have good materials, compaction

854.0

291.3

*1

0796.0

EN

t

f

477.4

9 110365.1

v

rN

Traffic Analysis

• Use ESALs for detailed analysis

• Same process as AASHTO

– SN = 5

– pt = 2.5

Simplified procedure for

determining Design ESAL

Materials

• Resilient modulus and Poisson’s ratio

• Poisson’s Ratio

– Soils = 0.45

– Other materials = 0.35

Soils modulus determination

***Discussion based on handouts given.

• Determine the design level from modulus

measurements

– Charts account for seasonal changes

• Design level function of traffic

– Build in reliability safety factor

ESAL Design Value %

<10,000 60

10,000 – 1,000,000 75

>1,000,000 87.5

Quality requirements for untreated

Aggregate Base and Subbase

• Should meet requirements below

Test Subbase Base

CBR, min 20 80

R-Value, min 55 78

LL, max 25 25

PI, max 6 NP

Sand Eq., min 25 35

P200 12 7

Design charts

• Design charts were developed based

• Temperature

– 3 Regions

• New York: 45˚F

• North Carolina: 60˚F

• Arizona: 75˚F

• Pavement Type– Full depth HMA

– HMA over Emulsified Asphalt Bases- Three types

• I: dense graded aggregate, similar to HMA

• II: semiprocessed aggregate

• III: mixes with sands or silty sands

– HMA over untreated aggregate Base

– HMA and emulsified Asphalt over Untreated Aggregate Base

AI – Design Procedure

• Select pavement type

• Select region

• Determine traffic

• Determine MR

• Use design charts to find thickness

AI Minimum Thicknesses

ESALs Min HMA over Type I Min HMA over Type II

& Type III

104 1 2

105 1.5 2

106 2 3

107 2 4

>107 2 5

Combine thickness of HMA surface course and emulsified asphalt base

course.

I – mixes with processes dense graded agg which should be mixed in a plant and have

properties similar to HMA

II- mixes with semiprocessed, crusher run, pit run or bank run agg

III – mixes with sands or silty sand

Total HMA thickness, including both surface and base course

Design example

• MR = 10, 000 psi , ESAL = 106, Determine

thickness :

– Full depth HMA

– HMA surface over type II emulsified asphalt

base

– HMA over 6” untreated aggregate base

– HMA and emulsified asphalt mix over 6”

untreated aggregate base

ATJ 5/85 Design Method

(2013 revision)

• New flexible and semi flexible pavements

containing one or more bound layers

• New flexible for low volume roads,

consisting of unbound or new cement

stabilized granular materials

• New flexible and semi-flexible heavy duty

pavements for severe loading conditions

Data required:

• Type and volume of commercial vehicles

• Design life

• Sub-grade type and strength

• Type and properties of paving materials

• Environment which pavement will be

exposed to

Criteria

Traffic

• Data

– Number of commercial vehicles during Year 1

of Design Period, which is the expected year

of completion of construction.

– Vehicle class and axle load distribution.

– Directional and lane distribution factors.

– Traffic growth factors.

Design Procedure1. From traffic count , determine:

– ADT (3 days, 24 hours per day. If traffic count covers

time period of 0600 to 2200 hours, multiply the count

with 1.2)

– % PCV with un-laden weight > 1.5 tons (PCV) and

break down into vehicle categories.

– Traffic Growth factor (r) for CV

2. From geometric design – number of lanes and terrain

condition

Number of lanes (in ONE

direction)

Lane distribution factor, L

One 1.0

Two 0.9

Three or more 0.7

Type of Terrain Terrain factor, T

Flat 1.0

Rolling 1.1

Mountainous/steep 1.3

3. Design period

• 10 years for low volume and rural road.

• 20 years for high volume and urban road

4. Design traffic (1st year of design period)

ESALY1 = ADT x 365 x PCV x LEF (3.7) x L x T

ESALY1 = number of ESALs for base year (design lane)

ADT = Average Daily Traffic

PCV = Percentage of CV (un-laden weight > 1.5 tons)

VLF = Vehicle Load Equivalent Factor (including Tire Factor)

L = Lane Distribution Factor

T = Terrain Factor

If traffic distribution by vehicle type is available:

ESALY1 = [ADTcv1 x LEFcv1 + ADTcv2 x LEFcv2 +…+

ADTcv3 x LEFcv3] x 365 x L x T

5. Design Traffic (Number of ESALs) for the Design Period

ESALDES = ESALY1 x [(1 + r)n – 1)]/r

ESALDES = design traffic for the design lane in one direction

r = annual traffic growth rate factor for design period

n = number of years in design period

OR

Design Traffic ESALDES = ESALY1 x TGF

Total Growth Factor (TGF)

6. Decide traffic category

Normal distribution with single tailed analysis, the following normal

deviate values shall apply:

• 60% Probablility: Mean – 0.253 x STD

•70% Probablility: Mean – 0.525 x STD

• 85% Probablility: Mean – 1.000 x STD

•statistical analysis shall be used to evaluate laboratory or field test

results for use as input for pavement design (sub-grade, sub-base,

road base and bituminous courses)

7. SG categories

• Min 5% CBR for T1- T3

• If not, at least 0.3 meter of SG shall be

replaced or stabilized to ensure the minimum

value is met.

• Large volume traffic T4 and T5, min CBR 12%

8. Get T and S, choose from catalogue

• Mechanistic Design using Elastic Layer Programs

• Asphalt Institute SW-1 (based on Manuals MS-1; MS-11;

MS-17; MS-23)

• Pavement Design: A Guide to the Structural Design of Road

Pavements, STANDARDS AUSTRALIA and AUSTROADS,

2004, in conjunction with CIRCLY Version 5.0

• SHELL SPDM Version 3.0

• Pavement Design and Analysis by Yang H. Huang, Second

Edition, 2003 in conjunction with KENLAYER

• Layer Elastic Theory using RUBICON TOOLBOX Version

2.9.8.

• 3 types of pavement : – Conventional flexible pavement with granular base.

– Deep-strength flexible (composite) pavement with

bituminous surface course(s) and a base stabilized

with Portland cement, bituminous emulsion, or a

combination of both.

– Full-depth asphalt pavement with bituminous base

course

T1 : < 1 million ESALs

T2 : 1- 2 million ESALs

T3: 2 -10 million ESALs

T4 : 10 – 30 million ESALs

T5 : > 30 million ESALs

T5 : > 30 million ESALs

( Polymer Modified Asphalt)

Conceptual outline of Pavement Structure

Properties of Paving Materials• Bituminous Wearing and Binder Courses

• Bituminous Road base

– similar to binder and wearing course except a lower

temperature used for this layer

• Crushed Aggregate and Wet Mix Road Base

– Performance -> shear strength, stiffness and by

material breakdown that may occur during

construction and heavy traffic

– similar composition but construction practices are

different

– Min CBR 80%, elastic modulus 350±100 Mpa

• Stabilized Road base

– In situ or Plant

– 2 types:

• STB 1 . Aggregates stabilised primarily with

cement or lime . 3% to 5% Portland cement.

E = 1800 MPa; v = 0.40

• STB 2. Aggregates stabilised primarily with a

bituminous emulsion/foamed bitumen +

cementitious. Bituminous emulsion or foamed

bitumen and a maximum of 2% Portland cement.

E= 1200 MPa; v 0.35

Other options for Low Volume Roads

Example 1

• Traffic count data: ADT 2700 vehicles

both directions (24 hour period)

• PCV: 16% ( no detailed break down by

vehicle type)

• Terain : rolling

• Design life: 20 years

• Annual traffic growth: 4%

• CBR mean =18.5% , standard deviation=

4.4%, 85% probability

Example 2

• Design a road pavement for a 4-lane freeway (concession toll-road)

with an average daily traffic of 7286 vehicles, of which 20% are

commercial vehicles with an un-laden weight > 1.5 tons

CV 1 = 624

CV 2 = 456

CV 3 = 316

CV 4 = 102