Falling weight deflectometer (FWD) testing is commonly used to estimate subgrade resilient modulus ( M R ) by using back calculation and/or the AASHTO M R equation. Considering the availability of limited information in the pavement management information system (PMIS) database, the AASHTO M R approach is suitable for subgrade assessment at a network level because of its simplicity. An adjustment factor is commonly applied to the AASHTO M R equation because of the difference between laboratory-measured M R and estimated M R . However, large variations in the adjustment factor have been observed with different geographical locations and climate conditions. Thus, using a fixed value of the adjustment factor has led to inaccurate assessment of subgrade soil M R . This paper presents a methodology to improve the accuracy of the existing AASHTO M R equation by constructing an M R adjustment factor based on the correlation of back-calculated E R and AASHTO M R . This study also investigated the effects of subgrade soil stiffness, bedrock depth, highway classification, and environmental condition on the correlation. Additionally, the uncertainty of the AASHTO subgrade M R equation because of the variation in the adjustment factor was quantified. As an example analysis, the methodology was applied to five districts in the state of Texas. The newly constructed M R could reduce variation in the adjustment factor, increasing the R 2 value from 0.524 to 0.894 in the correlation. The developed methodology can be applied to a smaller set of FWD data such as each road and county, which can reduce an uncertainty in the adjustment factor.


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    Title :

    Methodology to Improve the AASHTO Subgrade Resilient Modulus Equation for Network-Level Use


    Contributors:


    Publication date :

    2015-07-23




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown





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