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Construction Quality Control Practices for Evaluation of InSitu Stiffness and Material Variability

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Title: Construction Quality Control Practices for Evaluation of InSitu Stiffness and Material Variability


1
Construction Quality Control Practices for
Evaluation of In-Situ Stiffness and Material
Variability
  • North Central Pavement Research Partnership
  • University of Wisconsin Madison
  • October 8, 2008
  • John Siekmeier, PE

2
Topics
  • Testing for Compaction
  • Changing from Density to Modulus
  • New Field Testing Techniques
  • Intelligent Compaction Equipment
  • Data Management and Geostatistics
  • What Weve Learned

3
Testing for Compaction
  • Uniformity is the Priority
  • Traditional (Empirical Pavement Design, Soil
    Factor)
  • Specify Relative Density (Proctor Test)
  • Specify Moisture Limits (Proctor Test)
  • Observation or Test Rolling
  • Future (Mechanistic Pavement Design, MnPAVE)
  • QC Intelligent Compaction Equipment
  • QC/QA Continue to Specify Moisture
  • QA Specify Modulus and Strength (LWD, DCP)

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Density Testing Issues
  • Proctor had a Different Idea
  • Optimum Moisture for Compaction
  • Strength May Not be Achieved
  • Rutting Due to Moisture and Construction Traffic

9
Proctor Had a Different Idea 1933
  • 12 inch firm blows
  • not
  • 12 inch free fall (drop)

10
Proctor 1948
  • This inadvertent substitution evidently led some
    organizations to assume that instead of striking
    a minimum length blow of 12 inches, the tamper
    should be dropped a distance of 12 inches in free
    fall.

11
Proctor 1948
  • Originally published objective of compaction in
    earth fills was a saturated penetration
    resistance of 300 lb per sq in.
  • Soil would then have twice the penetration
  • resistance required to permit loaded truck
    travel when fully saturated.

12
  • DENSITY
  • 6.5 Increase
  • STRENGTH
  • 8.3 x Increase

13
Changing from Density to Strength
  • We Still Need Moisture Control
  • Density
  • Mass / Volume
  • Proctor Test is NOT the Maximum
  • Strength
  • This is a Performance Related Parameter
  • We Just Need Two of the Three
  • Moisture and Strength

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Why Use Performance Based Tests?
  • Achieve agreement between construction quality
    assurance, pavement design and performance.
  • Quantify alternative materials and construction
    practices.
  • Show economic benefit of improved materials.
  • Reward good construction.
  • This requires new specifications and new tools.
  • Tools must be quantitative, portable, and
    accurate in the field.

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New Field Testing Equipment
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22
Light Weight Deflectometer (LWD)
  • Impulse Device
  • Load measured
  • Velocity measured
  • Deflection calculated
  • Elastic modulus estimated
  • Immediate results
  • Trial Spec developed

23
Buffers
24
Load Cell
25
Geophone
26
Wireless Transmitter
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Intelligent Compaction Definition
  • Intelligent compaction (IC) equipment measures
    and records the quality of compaction during the
    compaction process. The compactors force
    changes in real time to increase compaction where
    needed, while preventing over compaction. The
    equipment uses a global positioning system to
    create a map that shows the quality of compaction
    across the entire surface of each lift.

31
Bomag Soil and Asphalt IC Systems
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Benefits to Mn/DOT
  • Increased Compaction Uniformity
  • Complete Documentation of Every Lift
  • Automation and Better Record Keeping
  • Improved Inspector Safety
  • No More Sand Cone Testing

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QA During Bomag Dam Construction
36
General QC/QA Procedure
  • Quality Control by the Contractor includes
  • Quality Control Plan
  • Moisture testing
  • Roller compaction value
  • Corrective actions to be taken
  • Quality Assurance by Owner includes
  • Review and approval of the Contractors QC plan
  • Analyses of the final recording pass of the IC
    roller
  • QA testing using the light weight deflectometer
    (LWD) dynamic cone penetrometer (DCP) and
    moisture tests
  • Review and approval of the Contractors QC report
  • Archive of electronic QC and QA data

37
IC Roller Specifications
  • Provide real-time correction during compaction
  • Provide current map for visual review on demand
  • Provide paper maps for permanent documentation
  • Provide an electronic data file in specified
    ASCII format
  • Date, time, and location of the proof layer
  • Roller compaction value (RCV) (modulus,
    stiffness, or another index)
  • Resonance meter value (RMV) and roller pass
    number (RPN)
  • Roller direction, speed, horsepower, and total
    mass
  • Drum mass, width, diameter, frequency, amplitude,
    acceleration, force
  • Position data and time stamp for each record
    accurate to the frequency of the drum

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Import Alignment from CAD
40
Import Aerial Photography
41
Import IC Roller Data
42
Apply Quantitative Statistics to IC Data
43
GIS Data Management System
44
Characterizing Uniformity
70
60
Worse (Short Range, High Sill)
50
40
Semi-Variance
30
Better (Short Range, Low Sill)
20
Best (Long Range, Low Sill)
10
20
30
40
10
50
60
70
80
Separation Distance (ft)
Relative Rating ONLY
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46
Research and Implementation Roadmap
  • Mechanistic Empirical Design Framework 2000
  • LWD Enhancement and Verification 2003
  • Modulus of Select Granular 2004
  • Moisture Effects on DCP and LWD 2006
  • Modulus of Base Course w/ RAP (LRRB 812) 2006
  • Validation of DCP/LWD Granular (LRRB 829) 2006
  • Unsaturated Soil Pavement Design 2007
  • Implementation of LWD and IC (FHWA) 2007
  • MnPAVE for Local Roads (LRRB 828) 2007
  • Compaction Specs for DCP/LWD (LRRB 860) 2008
  • Best Value Granular for Road Foundations 2008

47
Intelligent Compaction Projects
  • 2004
  • District 3, MnROAD
  • 2005
  • District 1, US 53, Duluth
  • District 7, US 14, Janesville
  • District 8, US 12, Atwater
  • 2006
  • District 2, TH 64, Bemidji
  • District 3, MnROAD
  • Metro District, I-494 Valley Creek Road, Saint
    Paul
  • 2007
  • District 3, US 10, Staples
  • District 4, US 10, Detroit Lakes
  • District 7, TH 60, Worthington
  • Metro District, TH 36, Saint Paul
  • 2008
  • Kandiyohi County, CSAH 4
  • Olmsted County, CSAH 2
  • District 3, MnROAD

48
Kandiyohi County, CSAH 4
  • FHWA/TPF Research Project
  • Accelerated Implementation of IC Technology for
    Embankment Subgrade Soils, Aggregate Base
    Asphalt
  • June 15 17, 2008
  • Site Details
  • 3.2 miles
  • 3 to 10 Compacted Subgrade
  • 6 Class 5 Aggregate
  • 4 HMA

49
Subbase Layer Mapping Operation(Photo Courtesy
of Sakai)
50
HMA Base Course Layer Compaction(Wearing Course
was also mapped)
51
Aithon Software Output Passes
52
Aithon Software Output CCV
53
Aithon Software Output Temperature
54
Premature Failure Base Course
55
Olmsted County, CSAH 2
  • LWD and Intelligent Compaction
  • 0.8 miles
  • 12 inches Select Granular
  • 6-9 inches Aggregate Base
  • 8 inches Concrete Surfacing

56
AccuGrade Compaction
Radio
GPS Receiver
Display
Controller
Slope Sensor
Accelerometer
57
Olmsted County, CSAH 2 CCV
58
AccuGrade Compaction
59
Olmsted County Zorn LWD

60
LWD Target Values LRRB Inv 860
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62
Whats Next ?
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64
Whats Next in Minnesota
  • Intelligent Compaction Specified in More
    Contracts
  • Purchase Specialized IC Validation Test Equipment
  • Industry/Agency Inspector Training Workshop
  • Educate Designers, Opportunity to Refine/Validate
    Design
  • Eliminate Control Strips
  • Specification Includes Design-Based Minimum
    Targets
  • Specification Includes Design-Based Uniformity
    Targets
  • Continued Participation with National Projects
  • NCHRP 21-09 Intelligent Compaction Specifications
  • FHWA-led Intelligent Compaction Pooled Fund

65
Conclusions
  • Construction equipment and field tests are now
    available that can measure the mechanistic
    properties used to design pavements and predict
    performance.
  • IC rollers are well made and easy to operate.
  • Operators learn how to make better decisions.
  • Problem areas are identified early and corrected.
  • IC rollers can measure the stiffness of the
    ground and produce surface covering
    documentation.
  • Data transfer was functional, but must be
    improved.

66
Acknowledgements
  • Special thanks to the following organizations
  • Ammann, Bomag, Caterpillar, and Sakai
  • CNA Consulting Engineers
  • Colorado School of Mines
  • Federal Highway Administration
  • Iowa State University
  • Loughborough University
  • Minnesota Department of Transportation
  • Minnesota Local Road Research Board
  • University of Illinois
  • University of Minnesota
  • University of Wisconsin

67
Thank You.
  • Questions?
  • www.dot.state.mn.us/materials/researchic.html
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