advances in intelligent compaction for hma

Advances in Intelligent

Compaction for HMA

Victor (Lee) Gallivan, PE

FHWA - Office of Pavement Technology

February 3, 2010

NCAUPG HMA Conference

Overland Park, Ks.

What is Intelligent Compaction

Technology

Office of Pavement Technology

Federal Highway Administration

www.fhwa.dot.gov/pavement/

An Innovation in Compaction

Control and Testing

----Definition----

What is “Intelligence?”

– Oxford Dictionary: “…able to vary behavior in response to varying situations and requirements”

– Ability to:Collect information

Analyze information

Make an appropriate decision

Execute the decision

3000-4000 TIMES A MINUTE

Shortcomings Density Acceptance…

Limited Number of Locations

Benefits of IC for HMA

Improve density….better performance

Improve efficiency….cost savings

Increase information…better QC/QA

GPS Base Station GPS Radio & Receiver GPS Rover

Real Time Kinematic (RTK) GPS Precision

NG

PSPA

NNG

LWD-a

Bomag America

Caterpillar

Ammann/Case Dynapac

Sakai America

Mapping of Roller Passes

Longitudinal Joint

Shoulder (Supported)Paving Direction

Courtesy Sakai America

Correlation w/ In-Situ Testing

Impact ForceFrom Rollers 300 mm

LWD/FWD200 mm

LWD

Nuclear Density Gauge

DynamicCone Penetrometer

2.1 m

2.1 m

0.3 m 0.2 m 0.3 m

1.0 m

X X X X X X X X2.1 m

Distance = Roller travel in 0.5 sec.

In-situ spot test measurements

Influence depths are assumed ~ 1 x B (width)

Area over witch the roller MV’s are averaged

Courtesy of Dr. David White

IC National Efforts

– NCHRP 21-09 “Examining the Benefits and

Adoptability of Intelligent Soil Compaction”

(Completed but not published yet)

– Transportation Pooled Fund #954 – “Accelerated

Implementation of Intelligent Compaction Technology

for Embankment Subgrade Soils, Aggregate Base and

Asphalt Pavement Material”

– The Transtec, Group, Austin, Texas

(George Chang- PI)

– Additional State IC Programs (OK, WI, etc.)

MD

MN

KS

TXMS

IN

NY

PA

VA

ND

GA

TX

WI

Objectives: Based on data obtained from

field studies:

– Accelerated development of QC/QA

specifications for granular and cohesive

subgrade soils, aggregate base and Hot

Mix Asphalt (HMA) pavement materials…

– Short, Long and Future Term Goals

– 3-year IC study for all the above materials

– 12 participating States

– 12+ field demonstration

Objectives

Develop an experienced and

knowledgeable IC expertise base within

Pool Fund participating State DOTs

Identify and prioritize needed

improvements to and/or research of IC

equipment and field QC/QA testing

equipment

Short Term Goals

Improved Density

More Uniform Density

More efficient compaction process

Operator Accountability

Correlate Measurements with Field Densities

Real-time Density Control (QC)

Long Term Goals

Continuous Compaction Control specifications

Real-time Density Acceptance (QA)

Future Goals

Tie to Design Guide (verify design)?

Performance specifications?

MN

KS

TXMS

IN

NY

PA

VA

MD

ND

GA

WI

2008

2009

2010

Route 4, Kandiyohi County, MN

Mapping existing subbase

New HMA construction

MN

KS

TXMS

IN

NY

PA

VA

MD

ND

GA

WI

Sakai double-drum

IC roller

HMA non-wearing course layer mapa = 0.6 mm,

f = 3000 vpm

Class 5 aggregate subbase layer map, a = 0.6 mm,

f = 2500 vpm

Reflection of hard spots onthe HMA layer

Reflection of hard spots onthe HMA layer

Reflection of

soft spots onthe HMA layer

HMA Map Subbase Map

CCVSubbase

(a = 0.6 mm, f = 2500)

0 5 10 15 20 25

CC

VS

ub

ba

se (

a =

0.3

mm

, f

= 3

00

0)

0

5

10

15

20

25

CCVSubbase

(a = 0.6 mm, f = 2500)

0 5 10 15 20 25

CC

VH

MA (

a =

0.6

mm

, f

= 3

00

0)

0

5

10

15

20

25

CCVSubbase

(a = 0.3 mm, f = 3000)

0 5 10 15 20 25

CC

VS

ub

ba

se (

a =

0.3

mm

, f

= 3

00

0)

0

5

10

15

20

25y = 2.45 ln(x) + 2.3

R2 = 0.69

y = 0.41x + 2.7

R2 = 0.33

y = 0.27x + 8.0

R2 = 0.30

Sakai double-drum IC roller

Subbase Mapping

HMA Map Subbase

Map

Premature

Failure

Peter’s Road, Springville, NY

Mapping existing subbase


MN

KS

TXMS

IN

NY

PA

VA

MD

ND

GA

WI

Sakai double-drum

IC roller

Subbase Mapping3000 vpm, 0.6mm, 5 tracks, 2mph

2500 vpm, 0.6mm, 3 tracks, 2mph

3000 vpm, 0.6mm, 4 tracks, 3 mph

Day 2 – First Lift of Base Course

Day 3 – 2nd Lift of Base Course

Day 3 – Intermediate Course

s

NG vs NNG 1st lift base

y = 0.0978x + 108.26

R2 = 0.1473

120

121

122

123

124

125

125

127

129

131

133

135

137

139

141

143

145

NG density (pcf)

NN

G d

en

sit

y (

pcf)

NG vs NNG

Linear (NG vs NNG)

Binder base

y = 0.118x + 107.54

R2 = 0.1552

120

121

122

123

124

125

126

127

128

129

130

120

125

130

135

140

145

NG density (pcf)

NN

G d

en

sit

y (

pcf)

NG vs NNG

Linear (NG vs NNG)

NG

NNG (PQI)

US 84, Wayne County, MS

Mapping existing stabilized base

New HMA Construction

MN

KS

TXMS

IN

NY

PA

VA

MD

ND

GA

WI

Sakai double-drum

IC roller

Mapping

Results

TB 2A-2

N

TB 2B-1

TB 2C-1

TB 2A-1TB 2A-3

TB 2A-1

TB 2A-2

TB 2A-3

TB 2B-2

TB 2C-2

TB 2B-1

TB 2C-1

TB 2B-2

TB 2C-2

0

5

10

15

20

25

TB02A (5-day cure) TB02B (6-day cure) TB02C (7-day cure)

CC

Vs

Mapping w/

Sakai double-drum

IC roller

Sakai double-drum

IC roller

0 50 100 150 200 250 300

Lag Distance

0

0.5

1

1.5

2

2.5

Va

rio

gra

m

Direction: 0.0 Tolerance: 90.0Column D

Exponential Model

Nugget=1.68

Sill = 2.2

Range = 30

0 20 40 60 80 100 120 140 160 180 200

Lag Distance

0

0.5

1

1.5

2

2.5

3

3.5

Variogra

m

Direction: 0.0 Tolerance: 90.0Column D

Nugget=1.38

Sill = 2.2

Range = 35

Exponential Model

EB Lane 1 (400 to 582 m)

Semi-variogram of CCV

EB Lane 1 (0 to 300 m)

Sakai CCV

North

Total length of 582 m

US 340EB, Frederick, MD

SMA overlay

Mapping milled HMA surface

MN

KS

TXMS

IN

NY

PA

VA

MD

ND

GA

WI

Sakai

double-drum

IC roller

Bomag

double-drum

IC roller

Mapping

Milled HMA

Test bed 02 Mapping

Bomag Evib Sakai CCV

Bomag Sakai

US 340 EB

Mapping

Milled HMA

Sakai

double-drum

IC roller

TB 03A Mapping on Exiting HMA Pavement

0

10

20

30

40

50

60

70

80

90

0 50 100 150 200 250 300 350 400 450

Lag Distance

0

50

100

150

200

250

300

350

400

450

500

Va

rio

gra

m

Direction: 0.0 Tolerance: 90.0Column L: CCV

Exponential Model

Nugget = 300

Sill = 398

Range = 65

North

Sakai CCV Kridging Map

Semi-variogram for CCV

Lane 1

Shoulder

Bridge

TB 03B SMA overlay (distance 0 to 684 m)

140

160

180

200

220

240

260

280

10

12

14

16

18

20

22

24

26

28

30

32

34

36

38

0 50 100 150 200 250 300 350 400 450

Lag Distance

0

5

10

15

20

25

30

35

Va

riog

ram

Direction: 0.0 Tolerance: 90.0Column L: CCV

Nugget=16.5

Sill=28.5

Range=40

SAKAI CCV Surface Temperature

Semi-variogram - exponential model

PSPA

vs

FWD

200

300

400

500

600

700

800

900

200 300 400 500 600 700 800 900

Back-calculated modulus of existing HMA pavement (ksi)

PS

PA

se

ism

ic m

od

ulu

s o

f e

xis

tin

g H

MA

pa

ve

me

nt

(ks

i)

y = 1.011x + 477.16

R2 = 0.1289

300

350

400

450

500

550

600

650

0.00 20.00 40.00 60.00 80.00 100.00

SAKAI CCV on Existing HMA Pavement

PS

PA

Seis

mic

mo

du

lus o

f exis

tin

g H

MA

layer

(ksi)

Modulus of Existing HMA Layer vs SMA Overlay CCV

Linear (Modulus of Existing HMA Layer vs SMA Overlay CCV)

PSPA

Vs

IC

Existing pavements

New SMA constrcution

IC RMV vs

NGy = 0.2858x + 149.28

R2 = 0.2031

140

145

150

155

160

165

0 5 10 15 20 25 30 35 40

SAKAI CCV

Den

sit

y

Density vs CCV

Linear (Density vs CCV)

Sakai

Double-drum

IC roller

NG

Park&Ride, Clayton County, GA

Mapping subbase


MN

KS

TXMS

IN

NY

PA

VA

MD

ND

GA

WI

Sakai

double-drum

IC roller

Mapping

GAB

Sakai

CCV

Sakai

Double-drum

IC roller

Park & Ride

TB 01A Intermediate HMA Layer

Sakai CCV

Surface

temperature (oC)

Roller pass

Sakai

Double-drum

IC roller

TB 01A

Sakai

Double-drum

IC roller

TB 05A

TB 05A Intermediate HMA Layer

Roller passes

Sakai CCV

Outer loop

Inner loop

Nor

th

NG

US 52, West Lafayette, IN

Mapping milled HMA surface

New HMA overlay

MN

KS

TXMS

IN

NY

PA

VA

MD

ND

GA

WI

Sakai

Bomag

Before

After

TB 03 HMA intermediate layer

TB04

TB 03 HMA intermediate layer

TB04

Sakai

Double-drum

IC roller

TB 04

Future Initiatives:

– Regional Conferences – that target practitioners

– Establishment of Optimum Measurement Values

– Guidance Manual/Best Practices for both Soils and

Hot Mix Asphalt Materials

– Mini-IC Demo’s: Limited support for field trials with

Non-TPF States

– Web-Page Continuation

– 2010 Schedule

May Wisconsin HMA- Full

May/June Texas HMA-Mini

June Virginia HMA-Full

June/July North Dakota Soils-Full

June/July Pennsylvania HMA-Mini Soils-Full

June/July Indiana Soils-Full

June/July Tennessee HMA-Mini

July/Aug California HMA-Mini

August BIA HMA-Mini

www.intelligentcompaction.com

http://www.intelligentcompaction.com/

Benefits of IC

Improve density…better performance

Improve efficiency…cost savings

Increase information…better QC/QA

Ultimate Goals of TPF IC

Gain the knowledge needed to develop

credible and productive IC specifications

for future projects

Future IC Spec

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120

Experimental Variogram

Exponential Variogram

Nugget = 0Sill = 70Range = 15Distance to Asymptotic "Sill" = 100

Station 275+00 to 277+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 275+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 271+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 271+00 to 269+00

< 1%< 29<70%

<1%29 - 3470-80%

3%34 - 3880-90%

52%38 - 5590-130%

45%55>130%

IC DataCCV% Target

Window Variograms!!!

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 275+00 to 277+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 275+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 271+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 271+00 to 269+00

< 1%< 29<70%

<1%29 - 3470-80%

3%34 - 3880-90%

52%38 - 5590-130%

45%55>130%

IC DataCCV% Target


Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 275+00 to 277+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 275+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 271+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 271+00 to 269+00

< 1%< 29<70%

4%29 - 3470-80%

6%34 - 3880-90%

59%38 - 5590-130%

31%55>130%

IC DataCCV% Target


Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 275+00 to 277+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 275+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 271+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 271+00 to 269+00

< 1%< 29<70%

4%29 - 3470-80%

6%34 - 3880-90%

59%38 - 5590-130%

31%55>130%

IC DataCCV% Target

Window Variograms!!!Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 275+00 to 277+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 275+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 271+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 271+00 to 269+00

0%< 29<70%

<1%29 - 3470-80%

4%34 - 3880-90%

79%38 - 5590-130%

17%55>130%

IC DataCCV% Target


0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 275+00 to 277+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 275+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 271+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 271+00 to 269+00

0%< 29<70%

<1%29 - 3470-80%

4%34 - 3880-90%

79%38 - 5590-130%

17%55>130%

IC DataCCV% Target


0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 275+00 to 277+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 275+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 271+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 271+00 to 269+00

< 1%< 29<70%

1%29 - 3470-80%

4%34 - 3880-90%

83%38 - 5590-130%

10%55>130%

IC DataCCV% Target


0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 275+00 to 277+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 275+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 273+00 to 271+00

Lag Distance (h)

0 50 100 150 200

Sem

i-Var

ianc

e g (

h)

0

20

40

60

80

100

120




Station 271+00 to 269+00

< 1%< 29<70%

1%29 - 3470-80%

4%34 - 3880-90%

83%38 - 5590-130%

10%55>130%

IC DataCCV% Target


Courtesy of Dr. David White

Indianapolis - Colts

Superbowl XLIV

Champions - 02/07/2010

?????

Thank you

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