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

Advances in Intelligent Compaction for HMA NCAUPG HMA Conference Overland Park, Ks. Victor (Lee) Gallivan, PE FHWA - Office of Pavement Technology February 3, 2010

What is Intelligent Compaction Technology An Innovation in Compaction Control and Testing Office of Pavement Technology Federal Highway Administration www.fhwa.dot.gov/pavement/

----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

LWD-a NG NNG PSPA

Dynapac Ammann/Case Caterpillar Bomag America Sakai America

Mapping of Roller Passes Paving Direction Shoulder (Supported) Longitudinal Joint Courtesy Sakai America

Correlation w/ In-Situ Testing Area over witch the In-situ spot test measurements roller MV’s are averaged X 2.1 m X X X X X X X Distance = Roller travel in 0.5 sec. Impact Force 300 mm ฀ 200 mm ฀ From Rollers LWD/FWD LWD Dynamic Nuclear Cone Penetrometer Density Gauge 0.2 m 0.3 m 2.1 m 0.3 m 1.0 m 2.1 m Influence depths are assumed ~ 1 x B (width) 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.)

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

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?

ND MN NY WI PA MD IN VA KS GA MS TX 2008 2009 2010

ND MN NY WI PA MD IN Route 4, Kandiyohi County, MN VA KS GA MS TX Mapping existing subbase New HMA construction Sakai double-drum IC roller

Subbase Mapping 25 Reflection of CCV HMA ( a = 0.6 mm, f = 3000) y = 2.45 ln(x) + 2.3 hard spots on R 2 = 0.69 the HMA layer 20 HMA Map Subbase Map 15 10 5 HMA non-wearing Class 5 aggregate 0 course layer map subbase layer map, 0 5 10 15 20 25 a = 0.6 mm , a = 0.6 mm , CCV Subbase ( a = 0.6 mm, f = 2500) f = 3000 vpm f = 2500 vpm Reflection of hard spots on the HMA layer Reflection of soft spots on the HMA layer Sakai double-drum IC roller

Premature Failure HMA Map Subbase Map

ND MN NY WI PA MD Peter’s Road, Springville, NY IN VA KS GA MS TX Mapping existing subbase New HMA construction 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 s Day 3 – Intermediate Course

NG vs NNG NG 1st lift base 125 NG vs NNG Linear (NG vs NNG) 124 y = 0.0978x + 108.26 NNG density (pcf) R 2 = 0.1473 123 122 121 120 125 127 129 131 133 135 137 139 141 143 145 NG density (pcf) NNG (PQI) Binder base 130 NG vs NNG 129 Linear (NG vs NNG) 128 NNG density (pcf) 127 y = 0.118x + 107.54 126 R 2 = 0.1552 125 124 123 122 121 120 120 125 130 135 140 145 NG density (pcf)

ND MN NY WI PA MD IN US 84, Wayne County, MS VA KS GA MS TX Mapping existing stabilized base New HMA Construction Sakai double-drum IC roller

TB 2B-2 TB 2B-1 TB 2A-3 TB 2A-2 TB 2A-1 Mapping TB 2C-2 TB 2C-1 N Results TB 2A-1 TB 2A-2 Mapping w/ Sakai double-drum TB 2A-3 IC roller TB 2B-1 TB 2C-1 25 20 15 CCVs TB 2B-2 10 TB 2C-2 5 0 TB02A (5-day cure) TB02B (6-day cure) TB02C (7-day cure)

Sakai CCV Semi-variogram of CCV Column D Direction: 0.0 Tolerance: 90.0 3.5 Exponential Model 3 2.5 Variogram 2 1.5 Nugget=1.38 North 1 Sill = 2.2 Range = 35 0.5 0 0 20 40 60 80 100 120 140 160 180 200 Lag Distance EB Lane 1 (400 to 582 m) Column D Direction: 0.0 Tolerance: 90.0 2.5 2 Exponential Model 1.5 Variogram Sakai double-drum Nugget=1.68 1 Sill = 2.2 IC roller Range = 30 0.5 0 0 50 100 150 200 250 300 Lag Distance EB Lane 1 (0 to 300 m) Total length of 582 m

ND MN NY WI PA MD IN US 340EB, Frederick, MD VA KS GA MS TX SMA overlay Mapping milled HMA surface Bomag double-drum IC roller Sakai double-drum IC roller

Test bed 02 Mapping Bomag Sakai Bomag Evib Sakai CCV Mapping Milled HMA US 340 EB

TB 03A Mapping on Exiting HMA Pavement Sakai CCV Kridging Map North 90 80 70 Mapping 60 50 Lane 1 Milled HMA 40 Shoulder 30 20 10 Semi-variogram for CCV 0 Column L: CCV Direction: 0.0 Tolerance: 90.0 Bridge 500 450 400 350 Sakai 300 Variogram 250 Exponential Model double-drum Nugget = 300 200 Sill = 398 Range = 65 IC roller 150 100 50 0 0 50 100 150 200 250 300 350 400 450 Lag Distance

TB 03B SMA overlay (distance 0 to 684 m) SAKAI CCV Surface Temperature 38 280 36 34 260 32 30 240 28 26 220 24 22 200 20 180 18 16 160 14 12 140 10 Semi-variogram - exponential model Column L: CCV Direction: 0.0 Tolerance: 90.0 35 30 25 20 Variogram 15 Nugget=16.5 10 Sill=28.5 Range=40 5 0 0 50 100 150 200 250 300 350 400 450 Lag Distance

Existing pavements 900 PSPA seismic modulus of existing HMA 800 700 PSPA pavement (ksi) 600 500 vs 400 300 FWD 200 200 300 400 500 600 700 800 900 Back-calculated modulus of existing HMA pavement (ksi) New SMA constrcution 650 PSPA Seismic modulus of existing HMA layer 600 550 PSPA 500 (ksi) y = 1.011x + 477.16 450 R 2 = 0.1289 Vs 400 Modulus of Existing HMA Layer vs SMA Overlay CCV 350 Linear (Modulus of Existing HMA Layer vs SMA Overlay CCV) IC 300 0.00 20.00 40.00 60.00 80.00 100.00 SAKAI CCV on Existing HMA Pavement

165 160 155 Density IC RMV vs 150 y = 0.2858x + 149.28 NG R 2 = 0.2031 145 Density vs CCV Linear (Density vs CCV) 140 0 5 10 15 20 25 30 35 40 SAKAI CCV NG Sakai Double-drum IC roller

ND MN NY WI PA MD IN Park&Ride, Clayton County, GA VA KS GA MS TX Mapping subbase New HMA construction Sakai double-drum IC roller

Sakai Mapping CCV GAB Park & Ride Sakai Double-drum IC roller

TB 01A Intermediate HMA Layer Roller pass Sakai CCV TB 01A Surface temperature ( o C) Sakai Double-drum IC roller

TB 05A Intermediate HMA Layer Outer loop Roller passes Inner loop h t r o N TB 05A Sakai CCV Sakai Double-drum IC roller NG

ND MN NY WI PA MD IN US 52, West Lafayette, IN VA KS GA MS TX Mapping milled HMA surface New HMA overlay Sakai Bomag

Before After TB 04 Sakai TB04 TB04 Double-drum IC roller TB 03 HMA intermediate layer TB 03 HMA intermediate layer

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 North Dakota June/July Soils-Full Pennsylvania HMA-Mini June/July 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