Prediction of resilient modulus from soil index properties
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Prediction of resilient modulus from soil index properties

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English
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  • Alternative Title:
    Resilient modulus prediction employing soil index properties
  • Creators:
    George, K.P.
  • Corporate Creators:
  • Subject/TRT Terms:
  • Publication/ Report Number:
  • Resource Type:
    Tech Report
  • Geographical Coverage:
    Mississippi
  • TRIS Online Accession Number:
    987786
  • OCLC Number:
    61363334
  • Corporate Publisher:
    Mississippi. Dept. of Transportation
  • NTL Classification:
    NTL-HIGHWAY/ROAD TRANSPORTATION-Construction and Maintenance;NTL-HIGHWAY/ROAD TRANSPORTATION-Soils and Geology;
  • Abstract:
    Subgrade soil characterization in terms of Resilient Modulus (MR) has become crucial for pavement design. For a new design, MR values are generally obtained by conducting repeated load triaxial tests on reconstituted/undisturbed cylindrical specimens. Because the test is complex and time-consuming, in-situ tests would be desirable if reliable correlation equations could be established. Alternately, MR can be obtained from correlation equations involving stress state and soil physical properties. Several empirical equations have been suggested to estimate the resilient modulus. The main focus of this study is to substantiate the predictability of the existing equations and evaluate the feasibility of using one or more of those equations in predicting resilient modulus of Mississippi soils. This study also documents different soil index properties that influence resilient modulus.

    Correlation equations developed by the Long Term Pavement Performance (LTPP), Minnesota Road Research Project, Georgia DOT, Carmichael and Stuart Drumm et al., Wyoming DOT, and Mississippi DOT are studied/analyzed in detail. Eight road (subgrade) sections from different districts are selected and soils tested (TP 46 Protocol) for MR in the laboratory. Other routine laboratory tests are conducted to determine physical properties of the soil. Validity of the correlation equations are addressed by comparing measured MR to predicted MR. In addition, variations expected in the predicted MR due to inherent variability in soil properties is studied by the method of point estimates. The results suggest that LTPP equations are suited for purposes of predicting resilient modulus of Mississippi subgrade soils. For fine-grain soils, even better predictions are realized with the Mississippi equation.

    A sensitivity study of those equations suggests that the top five soil index properties influencing MR include moisture content, degree of saturation, material passing #200 sieve, plasticity index and density.

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