Estimation of a Resilient Modulus Model for Cohesive Soils Using Joint Estimation and Mixed Effects

This paper presents the specification and estimation of a model based on the mechanistic empirical Pavement Design Guide (PDG) for estimating resilient modulus of fine-grained soils by using common soil parameters and by combining two different data sources: a database developed with Hawaiian fine-grained soils and data extracted from the Long Team Pavement Performance database for fine -grained subgrade soils. Two statistical techniques are combined to estimate the model parameters: joint estimation and mixed effects. Joint estimation considers multiple databases and allows identification of influential parameters that may be present only in some but not all databases whereas the mixed-effects statistical estimation approach is used to account for the within-group correlation between observations. The general structure of the PDG model is found acceptable if an allowance is made for the compaction level in addition to the saturation level in the PDG sigmoidal function. The resulting model contains parameters that are statistically significant and is more robust in that it can be used under a wider range of conditions than would have been possible if only one data source was available.