- 期刊
Statistical Models for Determination of the Resilient Modulus of Subgrade Soils
並列摘要
A combined laboratory and modeling study was undertaken to develop a database for subgrade soils in Oklahoma and to develop relationships or models that could be used to estimate resilient modulus (MR) from commonly used subgrade soil properties in Oklahoma. Sixty-three soil samples from 14 different sites throughout Oklahoma were collected and tested for the development of the database and the statistical models. Additionally, thirty-four soil samples from 3 different sites, located in Rogers and Woodward counties, were collected and tested to evaluate the developed models. The routine material parameters selected in the development of the models included moisture content (w), dry density (γd), plasticity index (PI), percent passing No. 200 sieve (P200) , and unconfined compressive strength (Uc) ' Bulk stress (θ) and deviatoric stress (σd) were used to identify the state of stress. Several statistical models were developed in this study. These models include: stress-based, multiple regression, polynomial, and factorial. Each model was ranked based on its R2 (goodness of fit) and F values (significance of the model) for the development dataset. Based on the R^2 and F values, the second order polynomial and factorial models were further considered for the evaluation dataset. An evaluation of the two models indicated that for the combined development and evaluation datasets, a second order polynomial model is a good statistical model for evaluating MR from the selected routinely determined properties. The models developed in this study are expected to be useful in the Level 2 and Level 3 designs of pavements in Oklahoma.