Advances in Intelligent Compaction for HMA NCAUPG HMA Conference - - PowerPoint PPT Presentation

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 Force From Rollers 300 mm ฀ LWD/FWD 200 mm ฀ LWD Nuclear Density Gauge Dynamic Cone 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 X

2.1 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 TX MS 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 TX MS IN NY PA VA MD ND GA WI

2008 2009 2010

Route 4, Kandiyohi County, MN Mapping existing subbase New HMA construction

MN KS TX MS IN NY PA VA MD ND GA WI

Sakai double-drum IC roller

HMA non-wearing course layer map a = 0.6 mm, f = 3000 vpm Class 5 aggregate subbase layer map, a = 0.6 mm, f = 2500 vpm

Reflection of hard spots on the HMA layer Reflection of hard spots on the HMA layer Reflection of soft spots on the HMA layer

HMA Map Subbase Map

CCVSubbase (a = 0.6 mm, f = 2500) 5 10 15 20 25 CCVHMA (a = 0.6 mm, f = 3000) 5 10 15 20 25

y = 2.45 ln(x) + 2.3 R2 = 0.69

Sakai double-drum IC roller

Subbase Mapping

HMA Map Subbase Map

Premature Failure

Peter’s Road, Springville, NY Mapping existing subbase New HMA construction

MN KS TX MS IN NY PA VA MD ND GA WI

Sakai double-drum IC roller

Subbase Mapping

3000 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) NNG density (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) NNG density (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 TX MS 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-1 TB 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

5 10 15 20 25 TB02A (5-day cure) TB02B (6-day cure) TB02C (7-day cure) CCVs

Mapping w/ Sakai double-drum IC roller

Sakai double-drum IC roller

Direction: 0.0 Tolerance: 90.0 Column D

Exponential Model Nugget=1.68 Sill = 2.2 Range = 30

Direction: 0.0 Tolerance: 90.0 Column 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 TX MS 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

10 20 30 40 50 60 70 80 90

Direction: 0.0 Tolerance: 90.0 Column 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

50 100 150 200 250 300 350 400 450 Lag Distance 5 10 15 20 25 30 35 Variogram

Direction: 0.0 Tolerance: 90.0 Column 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) PSPA seismic modulus of existing HMA pavement (ksi)

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 PSPA Seismic modulus of existing HMA 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 NG

y = 0.2858x + 149.28 R2 = 0.2031 140 145 150 155 160 165 5 10 15 20 25 30 35 40 SAKAI CCV Density Density vs CCV Linear (Density vs CCV)

Sakai Double-drum IC roller NG

Park&Ride, Clayton County, GA Mapping subbase New HMA construction

MN KS TX MS 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 N

• r

t h

NG

US 52, West Lafayette, IN Mapping milled HMA surface New HMA overlay

MN KS TX MS 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

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)

50 100 150 200

Semi-Variance g (h)

20 40 60 80 100 120 Experimental Variogram Exponential Variogram Nugget = 0 Sill = 70 Range = 15 Distance to Asymptotic "Sill" = 100

Station 275+00 to 277+00 g < 1% < 29 <70% <1% 29 - 34 70-80% 3% 34 - 38 80-90% 52% 38 - 55 90-130% 45% 55 >130% IC Data CCV % Target Lag Distance (h)

50 100 150 200

Semi-Variance g (h)

20 40 60 80 100 120 Experimental Variogram Exponential Variogram Nugget = 0 Sill = 70 Range = 15 Distance to Asymptotic "Sill" = 100

Station 275+00 to 277+00 g < 1% < 29 <70% <1% 29 - 34 70-80% 3% 34 - 38 80-90% 52% 38 - 55 90-130% 45% 55 >130% IC Data CCV % Target Lag Distance (h)

50 100 150 200

Semi-Variance g (h)

20 40 60 80 100 120 Experimental Variogram Exponential Variogram Nugget = 0 Sill = 73 Range = 23 Distance to Asymptotic "Sill" = 150

Station 273+00 to 275+00 < 1% < 29 <70% 4% 29 - 34 70-80% 6% 34 - 38 80-90% 59% 38 - 55 90-130% 31% 55 >130% IC Data CCV % Target Lag Distance (h)

50 100 150 200

Semi-Variance g (h)

20 40 60 80 100 120 Experimental Variogram Exponential Variogram Nugget = 0 Sill = 73 Range = 23 Distance to Asymptotic "Sill" = 150

Station 273+00 to 275+00 < 1% < 29 <70% 4% 29 - 34 70-80% 6% 34 - 38 80-90% 59% 38 - 55 90-130% 31% 55 >130% IC Data CCV % Target Lag Distance (h)

50 100 150 200

Semi-Variance g (h)

20 40 60 80 100 120 Experimental Variogram Exponential Variogram Nugget = 0 Sill = 43 Range = 12 Distance to Asymptotic "Sill" = 74

Station 273+00 to 271+00 0% < 29 <70% <1% 29 - 34 70-80% 4% 34 - 38 80-90% 79% 38 - 55 90-130% 17% 55 >130% IC Data CCV % Target Lag Distance (h)

50 100 150 200

Semi-Variance g (h)

20 40 60 80 100 120 Experimental Variogram Exponential Variogram Nugget = 0 Sill = 43 Range = 12 Distance to Asymptotic "Sill" = 74

Station 273+00 to 271+00 0% < 29 <70% <1% 29 - 34 70-80% 4% 34 - 38 80-90% 79% 38 - 55 90-130% 17% 55 >130% IC Data CCV % Target Lag Distance (h)

50 100 150 200

Semi-Variance g (h)

20 40 60 80 100 120 Experimental Variogram Exponential Variogram Nugget = 0 Sill = 35 Range = 8 Distance to Asymptotic "Sill" = 48

Station 271+00 to 269+00 < 1% < 29 <70% 1% 29 - 34 70-80% 4% 34 - 38 80-90% 83% 38 - 55 90-130% 10% 55 >130% IC Data CCV % Target Lag Distance (h)

50 100 150 200

Semi-Variance g (h)

20 40 60 80 100 120 Experimental Variogram Exponential Variogram Nugget = 0 Sill = 35 Range = 8 Distance to Asymptotic "Sill" = 48

Station 271+00 to 269+00 < 1% < 29 <70% 1% 29 - 34 70-80% 4% 34 - 38 80-90% 83% 38 - 55 90-130% 10% 55 >130% IC Data CCV % Target

Courtesy of Dr. David White

Indianapolis - Colts

Superbowl XLIV Champions - 02/07/2010 ?????

Thank you