4.7 Article

Relating gradation parameters to mechanical and drainage performance of unbound granular materials

Journal

TRANSPORTATION GEOTECHNICS
Volume 23, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.trgeo.2019.100315

Keywords

Unbound granular material; Gradation; Resilient modulus; Permeability; Subsurface drainage

Funding

  1. Manitoba Infrastructure
  2. Yukon Department of Highways and Public Works

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The drainage performance of unbound granular material (UGM) is an important consideration in pavement design because premature failures can occur due to the presence of excess moisture in UGM layers. Recently, transportation agencies have been evaluating their granular base and subbase drainage and mechanical performance to ensure sufficient drainage capacity while maintaining adequate structural support to produce more sustainable pavement structures. Relating performance to UGM construction specification requires accurate characterization of physical and gradation parameters and their effects on the mechanical and drainage performance of UGM. These evaluations led to an update of the specification requirements of UGM in many jurisdictions including Manitoba. In this study, resilient modulus and constant head hydraulic conductivity tests were performed to characterize the mechanical and drainage performance of nine UGM samples. The laboratory test results were also used to investigate the reliability of the estimated hydraulic conductivity from the Moulton prediction model, and from the Enhanced Integrated Climatic Model (EICM). Test results showed an improvement in resilient modulus and drainage quality for samples in gradation bands that specify larger maximum aggregate size and limited fines. A statistical analysis of the test results showed that D-10 larger than 0.2 mm and D-60 larger than 8 mm would guarantee higher stiffness and better drainage performance with a time-to drain of less than 5 days for typical pavement cross-sections and a resilient modulus value exceeding 200 MPa. The Moulton prediction model was found to provide a better approximation of hydraulic conductivity of the materials included in this study, while the EICM model was found to significantly overestimate the hydraulic conductivity for most of the samples.

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