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

초록

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 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 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. (C) 2015 American Society of Civil Engineers.

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