Methodology to Improve the AASHTO Subgrade Resilient Modulus Equation for Network-Level Use: Fid-Bau Portal

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

Nam, Boo Hyun / Kee, Seong-Hoon / Youn, Heejung / Kim, Dae Young

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.