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

Project Details







Jia Li, David J White, Pavana K R Vennapusa


Iowa State University, National Concrete Pavement Technology Center


Concrete pavements, Design, Field tests, Foundations, Highways, Pavement layers, Pavements, Quality assurance (QA), Quality control (QC), Service life, Spatial analysis, Subgrade (Pavements)

Project description

Nonuniform 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. Comparisons of directional semivariogram models from dense and sparse datasets from the same project are also provided in this report.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.