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

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

Youn, Heejung

AbstractFalling weight deflectometer (FWD) testing is commonly used to estimate subgrade resilient modulus (MR) by using back calculation and/or the AASHTO MR equation. Considering the availability of limited information in the pavement management information system (PMIS) database, the AASHTO MR approach is suitable for subgrade assessment at a network level because of its simplicity. An adjustment factor is commonly applied to the AASHTO MR equation because of the difference between laboratory-measured MR and estimated MR. 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 MR. This paper presents a methodology to improve the accuracy of the existing AASHTO MR equation by constructing an MR adjustment factor based on the correlation of back-calculated ER and AASHTO MR. 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 MR 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 MR could reduce variation in the adjustment factor, increasing the R2 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.