Improving the Foundation Layers for Concrete Pavements: Field Assessment of Variability in Pavement Foundation Properties

Non-uniform support conditions under pavements can have detrimental effects on the service life of pavements. Generally, pavement design considers the foundation as a layered medium with spatially uniform material properties and support conditions. But, soil engineering parameters generally show significant spatial variation. In this report, field testing was conducted at several pavement foundation construction sites in a dense grid pattern with relatively close spacing (i.e., < 1 m) over a small area (< 10 m x 10 m) and in a sparse sampling pattern (> 5 m apart) over a large area (> 100 m) to characterize spatial variability. Results from selected field studies were analyzed for a more in-depth analysis of spatial variability and assessment of anisotropy. The measurement parameter values assessed include elastic modulus determined from the light weight deflectometer (LWD) test, penetration index of subbase and subgrade layers using dynamic cone penetrometer (DCP) test, and dry unit weight and moisture content determined from the nuclear gauge (NG) test method. Spatial variability analysis on dense gridded test sections showed that different anisotropic major directions could be expected in different test areas. Results showed that the correlation lengths are about 2 m to 3 m in the minor direction, and the correlation length in the major direction is about 3 to 4 times large than the minor direction, which indicates more uniformity in the major direction than in the minor direction. Comparisons of directional semivariogram models from dense and sparse datasets from the same project are also provided in this report. Results showed range values between 2 m and 11 m for dense gridded datasets taken over a relatively small area versus range values between 15 m to 45 m for sparse datasets taken over large areas. Longer ranges represent more spatially continuous data with longer correlation lengths than shorter ranges. The longer ranges in the sparse dataset compared to shorter ranges calculated using the dense grid dataset suggests that there is a nested structure in the data with both short and long range spatial continuity of the measured properties. In summary, the data and analysis demonstrate that spatial variability in pavement foundation layers can be quantified using semivariogram modeling, but is anisotropic and depends on test spacing.

• Record URL:
  http://www.intrans.iastate.edu/research/documents/research-reports/improving_foundation_layers_field_assessment_of_variability_w_cvr.pdf
• 
• Summary URL:
  https://intrans.iastate.edu/research/completed/improving-the-foundation-layers-for-concrete-pavements/
• Corporate Authors:

  Iowa State University, Ames

  National Concrete Pavement Technology Center
  2711 S Loop Drive
  Ames, IA  United States  50010

  Iowa State University, Ames

  Center for Earthworks Engineering Research
  2711 South Loop Drive, Suite 4600
  Ames, IA  United States  50010

  Federal Highway Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Li, Jia
  • White, David J
  • Vennapusa, Pavana K R
• Publication Date: 2018-4

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Technical Report
• Features: Figures; References; Tables;
• Pagination: 70p

Subject/Index Terms

• TRT Terms: Concrete pavements; Field tests; Foundations; Pavement layers; Quality assurance; Quality control; Service life; Spatial analysis; Subgrade (Pavements)
• Subject Areas: Design; Highways; Pavements;

Filing Info

• Accession Number: 01670498
• Record Type: Publication
• Report/Paper Numbers: DTFH 61-06-H-00011 Work Plan 18, InTrans Project 09-352
• Files: TRIS, ATRI, STATEDOT
• Created Date: May 29 2018 10:24AM