DESIGNING BASES AND SUBGRADES FOR BETTER PAVEMENT …

DESIGNING BASES AND SUBGRADES

FOR

BETTER PAVEMENT PERFORMANCE

Robert L. Lytton

Houston Foundation Performance Association

December 13, 2017

Better Models for Base Course and

Subgrade for Pavement Design

and Performance Prediction

NCHRP 1-53 Project

AASHTO Pavement ME Design Product Task Force

Hilton Savannah Desoto Hotel Savannah, Georgia

April 4-5, 2017

3

Introduction and Objectives

Problem: performance of flexible and rigid

pavements shows low sensitivity to

subgrade/unbound layer properties

Objective: propose enhancements needed to

better reflect the influence of subgrade/unbound

layers (properties and thickness)

4

What do we need to emphasize? (1/2)

Unbound layers

Modulus: moisture-sensitive, stress-dependent,

cross-anisotropic

Permanent deformation: moisture-sensitive,

stress-dependent

Shear strength: moisture-sensitive

Erosion

Thickness

5

What do we need to emphasize? (2/2)

Subgrade

Modulus: moisture-sensitive, stress-dependent

Permanent deformation: moisture-sensitive,

stress-dependent

Shear strength: moisture-sensitive

Foundation

6

(-) Suction Ground Surface

Wet Season

Equilibrium

Dry Season

Depth

Water Table

Suction of the

Water

7

Dry Season


Wet Season

Equilibrium

Depth

8

Hierarchical Input Level

Level 1:

Laboratory-measured k1, k2, k3

SWCC

Equilibrium suction and its depth

SWCC in Pavement ME Design

9

A Family of Generated SWCCs

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

0.00 5.00 10.00 15.00 20.00 25.00 30.00

Su

ctio

n (

pF

)

Volumetric Water Content (Ѳw)

E-02 1-3-4 E-02 2-3-2 E-02 3-1-2

E-03 4-3-10 E-03 6-10-1 E-03 6-10-3

E-05 61-12 E-04 1-3 E-04 2-6

E-06 1-13 E-06 2-6 E-06 3-10

E-09 1-14 E-01 1-3-2-3 E-07 68-2-6

E-07 69-1-14 E-09 2-1-6 E-09 235-1-12

14

Dry Season


Wet Season

Equilibrium

Depth

15

Some Characteristic Curves

Soil water characteristic curve

Soil dielectric characteristic curve

Soil conductivity characteristic curve

Soil osmotic suction – evaporable water content

curve

Soil osmotic suction – electrical conductivity

curve

16

Soil Water Characteristics Curve

(SWCC)

17

A Family of Generated SWCCs

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

0.00 5.00 10.00 15.00 20.00 25.00 30.00

Su

ctio

n (

pF

)

Volumetric Water Content (Ѳw)

E-02 1-3-4 E-02 2-3-2 E-02 3-1-2

E-03 4-3-10 E-03 6-10-1 E-03 6-10-3

E-05 61-12 E-04 1-3 E-04 2-6

E-06 1-13 E-06 2-6 E-06 3-10

E-09 1-14 E-01 1-3-2-3 E-07 68-2-6

E-07 69-1-14 E-09 2-1-6 E-09 235-1-12

18

Filter Paper Suction Test Setup

19

Soil Water Characteristics Curve (SWCC)

( )

ln exp(1)

cb

sw C h

h

a

6

ln 1

( ) 110

ln 1

r

r

h

hC h

h

Fredlund and Xing Equation (1994)

Four soil parameters Volumetric

water

content

Saturated volumetric

water content

20

Four Parameters

Correlations for parameters af and bf :

R² = 0.9154

3.4990

3.4995

3.5000

3.5005

3.5010

3.5015

3.5020

0.00 5.00 10.00 15.00 20.00 25.00 30.00

af (p

si)

MBV (mg/g)

R² = 0.7719

1.984

1.988

1.992

1.996

2.000

2.004

2.008

0.00 5.00 10.00 15.00 20.00 25.00 30.00b

f

MBV (mg/g)

0.00023.4994fa MBV 0.0032.0044fb MBV

21

Four Parameters

Correlations for parameters cf and hr:

R² = 0.859

0.070

0.140

0.210

0.280

0.350

0.420

0.00 5.00 10.00 15.00 20.00 25.00 30.00

cf

MBV (mg/g)

R² = 0.796

19.9998

20.0000

20.0001

20.0003

20.0004

20.0006

0.00 5.00 10.00 15.00 20.00 25.00 30.00h

r

MBV (mg/g)

0.4150.4956fc MBV 9.5 0620.00 E

rh xMBV

22

Soil Dielectric Characteristics Curve

(SDCC)

23

Soil Dielectric Characteristics Curve

(SDCC)

Dielectric

constant

Saturated dielectric

constant min 51.45 10

1

sat

r

m

h

x h

h

h h

Minimum dielectric

constant

Suction

Curve fitting parameters

Maximum

Suction

24

A Standard Percometer Device with

Surface Probe

PER-CO-METER

PERMITTIVITY-

CONDUCTIVITY-

METER

25

Dielectric Constant Measurements

Process with a Percometer

MaterialDielectric

Constant

Air 1.0

Water 81.0

Asphalt 4.0-6.0

Concrete 8.0-12.0

Clay 4.0-40.0

26

A Family of Generated SDCCs

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

1.00 6.00 11.00 16.00 21.00 26.00 31.00 36.00 41.00

Suct

ion

(pF)

Dielectric Constant (er)

E-01 1-3-2-3 E-02 1-3-4

E-02 3-1-2 E-03 4-3-10

E-03 6-10-1 E-03 6-10-3

E-04 2-6 E-05 61-12

E-06 3-10 E-06 2-6

E-06 1-13 E-07 68-2-6

E-07 69-1-14 E-08 235-1-12

E-08 2-1-6 E-09 1-14

27

Minimum Dielectric Value

Correlation for minimum dielectric vs MBV

R² = 0.7642

0.90

1.00

1.10

1.20

1.30

1.40

1.50

1.60

0.00 5.00 10.00 15.00 20.00 25.00 30.00

Min

imum

Die

lect

ric

Cons

tatn

(em

in)

Methylene Blue Value (MBV)

Minimun dielectricconstant points

min 0.1243log 1.0668MBV

28

Saturated Dielectric Value

Correlation for saturated dielectric vs MBV

R² = 0.9311

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

0.0 5.0 10.0 15.0 20.0 25.0 30.0

Satu

rate

d D

iele

ctri

c Co

nsta

tn (e

sat)

Methylene Blue Value (MBV)

Saturated dielectricconstant points

2

sat 0.0334 0.1086 12.569MBV MBV

29

Base Course Aggregate

AASHTO T 330-07 Methylene Blue Scale

30

Methylene Blue Equipment

Weig

ht

Bala

nce

Hach

DR

Colo

rim

ete

r

Tim

er

Pla

stic

Tube

Mic

rop

ipe

tte

Sm

all

tub

e

Syrin

ge

Syringe

filt

er

Eyedro

pper

Me

thyle

ne

Blu

e

Solu

tion

31

Grace Methylene Blue Test

Weigh 20g of sample***and 30g MB. Mix them

and shake for 5 min.

Take solution into syringe that has 2 micrometer

filter.

Dilute the 130 mL aliquot with distilled water

to accurately total 45 g.

Fill the glass tube with the diluted solution

and place in the colorimeter.

Place cover over the glass tube and take a

reading. MB Reading will display in couple

seconds.

Replace the plunger and push solution to filter

into a 1 mL plastic tube.

Determine the percent clay based on MB from the

chart.

32

HORIBA Particle Size Distribution Analyzer

• Particle size distribution curve

of passing No 200 sieve

• Total measurement time is

less than 10 min

• Typical test result of a

soil sample

• Determine size of 2 μm

particle

33

What is pfc?

Percent Fines Content

2100

#200

mpfc

Percent passing

No.200 sieve

Percent passing

2 micrometer

percent

fines

content

34

The Relationship Between MBV and pfc

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00

Met

hy

len

e B

lue

Va

lue

(mg

/g)

Percent Fines Content (%)

Measured Data Points pfc Modeled Plot MBV=7.0 Critical Point Line

Zone II

Zone I

R2=0.79

35

“C” Shaped Curve Equation

n

apfc b MBV

MBV

Coefficient parameters

depend on soil type

Methylene Blue

Value

Percent fines

content

a 28.014

b 0.8131

n 0.6288

Typical Values

36

A Good Quality Base Course

37

A Poor Quality Base Course

38

Base Course Aggregate

Grace Methylene Blue Value Scale

39

Matric Suction and Water Content

Measurements

40

3

211

3( )

k

km octy a

a a

I fhE k P

P P

Resilient Modulus

1 2 3k ,k ,k Coefficients of resilient

modulus model

M a t r i c

S u c t i o n

O c t a h e d r a l s h e a r

s t r e s s

A t m o s p h e r i c

p r e s s u r e

11 f

S a t u r a t i o n f a c t o r

F i r s t i n v a r i a n t o f

t h e s t r e s s t e n s o r

Vo l u m e t r i c w a t e r

c o n t e n t

41

Aggregate Properties and k Values

42

Aggregate Properties and k Values

Aggregate Property k Values

k1 k2

k3

γd (Dry Density)

ω (Water Content)

MBV

pfc

Gradation aG

λG

Angularity aA

λA

Shape aS

λS

Texture aT

λT

43

Compaction Curve Equation

Three fitting parameters change with soil type

csch csch

dn

d w sat w satd d

w s sat w s sat w

a bG G

Unit weight of

water

Dry unit weight

Specific

gravity

Volumetric

water

content

Saturated

volumetric water

content

44

Saturated Volumetric Water Content Predicted and calculated saturated volumetric

water contents

R² = 0.9916

0.100

0.120

0.140

0.160

0.180

0.200

0.220

0.240

0.260

0.280

0.300

0.100 0.150 0.200 0.250 0.300

Cal

cula

ted

Ѳsa

t

Predicted Ѳsat

Saturated volumetricwater content datapoints

sat sat sat

sat sat sat

sat 1 2 3

1 2 3

= 0.214926485H + 0.27640261H - 0.12511932H + 0.30045553

H ,H ,and H ( and )f MBV pfc

45

Typical Compaction Curve as Tested in

the Laboratory and as Modeled

Optimum Moisture Content

46

Optimum Moisture Content

2 11 11 1

2 11 11 1

2 21ln 1 1 4

2

2 21ln 1 1 4

2

d d d

d d

n nn nd d

s sat

d d d d

opt

n nn nd d

sat s

d d d d

b bG

a n a n

b bG

a n a n

Optimum Moisture

Content

47

A Family of Compaction Curves

Generated compaction density curves

115

120

125

130

135

140

145

150

155

160

0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0% 18.0%

Dry

Un

it W

eig

ht

(p

si)

Gravimetric Water Content

E-01 E-02 E-03

E-04 E-05 E-06

E-07 E-08 E-09

S=10% S=20% S=30% S=40% S=50% S=60% S=70% S=80% S=90% S=100%

48

Stress-Dependent Mechanistic-Empirical

Permanent Deformation Model

Proposed model (Gu, Zhang, et al. 2015)

Model components

Laboratory test design

Laboratory verification

Numerical verification

Hierarchical input level

0 2 1

m nN

p e J I K

2sin

3 3 sin

6cos

3 3 sin

cK

49

Repeated Load Permanent Deformation Test

Test Equipment

Test Protocol

50

Proposed AASHTO Standard for Permanent

Deformation Test

51

Repeated Load Permanent Deformation

Test Results

Proposed model is

sensitive to cohesion.

Moisture change results in

change of cohesion.

Korkiala-Tanttu (K-T) model (Korkiala-Tanttu 2009)

UIUC model (Chow et al. 2014)

PME

PME

52

Role of Shear Strength Model

53

Hamburg Wheel-Tracking Device (HWTD) to

Measure erodibility

54

HWTD Test Results

-4.0

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0 1000 2000 3000 4000 5000

Def

lect

ion

(mm

)

Number of Passes

Dry Test

#2_SP-SM #4_SM #5_s(CL) #8_CH

-8

-7

-6

-5

-4

-3

-2

-1

0

0 1000 2000 3000 4000 5000

Def

lect

ion

(mm

)

Number of Passes

Wet Test

#2_SP-SM #4_SM #5_s(CL) #8_CH

Unbound

Stabilized Unbound Stabilized

55

Critical Erosion Depth Model

Erosion depth curve: e

e

eDN N e

Critical erosion depth: 1

1

ee

ce e

e

D

Number of load cycles at the point of inflection:

1e

e

PIN N e

56

Validation of Erosion Model

Model prediction vs. lab

measurements from HWTD

Model prediction vs. observed

performance from 17 LTPP sections

57

LTPP Pavement Sections with

Faulting Data

Unbound Base Course 351

Stabilized Base Course 359

Total 710

58

A Case Study: Verification GPR and FWD

59

Test Location

Delta county in

Texas

Total length 4.5

miles (~24000 ft)

Martin Marietta

Material in

Oklahoma

60

Ground Penetrating Radar Van

Vehicle-Mounted Four-Antenna Configuration for

Highway Speed Data Acquisition

61

Return Reflection at Interfaces

62

Radar Hyper Optics Animation

63

Falling Weight Deflectometer (FWD)

64

Information from GRP

0

2

4

6

8

10

12

0 4000 8000 12000 16000 20000 24000

GP

R d

iele

ctr

ic

feet

0

5

10

15

20

25

0 4000 8000 12000 16000 20000 24000

Ba

se

th

ickn

ess (

in)

feet

Dielectric constant

Base course thickness

65

Information from GRP Matric Suction

Volumetric Water Content

0.0

1.0

2.0

3.0

4.0

5.0

0 4000 8000 12000 16000 20000 24000

Ma

tric

Su

ctio

n (

pF

)

feet

0

0.05

0.1

0.15

0.2

0.25

0 4000 8000 12000 16000 20000 24000

Vo

lum

etr

ic W

C

feet

66

Information from GRP Dry Density

Resilient Modulus

120

125

130

135

140

145

0 4000 8000 12000 16000 20000 24000Dry

Unit W

eig

ht (lb/f

t3)

Distance (ft)

05

10152025303540

0 475 950 1425 1900 2375 2850 3325 3800

Mo

du

lus (

ksi)

Station

Predicted Resilient

Modulus

FWD Back-calculated

Resilient Modulus

67

Location of Identified Pavement Sections

68

Relationship between MBV and pfc

Hunter Material Canyon

Material

Knife River

69

Identified Pavement Sections from SH 21

70

Model-Predicted Mr Vs. FWD-Calculated Mr

0

20

40

60

80

100

0 400 800 1200 1600 2000

Re

sil

ien

t M

od

ulu

s o

f In

-sit

u B

as

e

Co

urs

e (

ks

i)

Station (ft)

Hunter Section Backcalculated Knife River Section Backcalculated

Hunter Section Model-Predicted Knife River Section Model-Predicted

71

Location of Identified Pavement Sections

72

Water Content Determination from

Conductivity

0

1

2

3

4

5

6

7

8

0510152025

Mat

ric

suct

ion

(p

F)

Electrical Conductivity (μs/cm)

Neat US 259 US 259 + 2% cement

US 259 + 4% cement US 259 + 6% cement

0

1

2

3

4

5

6

7

8

0 0.05 0.1 0.15 0.2

Mat

ric

suct

ion

(p

F)

Evaporable Volumetric water content

Neat US 259 US 259 + 2% cement

US 259 + 4% cement US 259 + 6% cement

73

Osmotic Suction vs Water Content

2

2.5

3

3.5

4

4.5

0 0.05 0.1 0.15 0.2

Osm

oti

c Su

ctio

n (

pF)


US 259

US 259 + 2% cement

74

Osmotic Suction vs Conductivity

3

3.5

4

4.5

0 10 20 30 40 50

Osm

oti

c Su

ctio

n (

pF)

Electrical Conductivity (μs/cm)

US 259

US 259 + 2% cement

US 259 + 4% cement

US 259 + 6% cement

75

Conductivity vs Water Content

0

10

20

30

40

50

0 0.05 0.1 0.15 0.2

Ele

ctri

cal C

on

du

ctiv

ity

(μs/

cm)


US 259

US 259 + 2% cement

US 259 + 4% cement

US 259 + 6% cement

76

Some Characteristic Curves

Soil water characteristic curve

Soil dielectric characteristic curve

Soil conductivity characteristic curve

Soil osmotic suction – evaporable water content

curve

Soil osmotic suction – electrical conductivity

curve

DESIGNING BASES AND

SUBGRADES FOR BETTER

PAVEMENT PERFORMANCE

Robert L. Lytton

Houston Foundation Performance Association

December 13, 2017

Documents

DESIGNING BASES AND SUBGRADES FOR BETTER PAVEMENT …