Permanent Strain Modeling of Recycled Concrete Aggregate for Unbound Pavement Construction

This paper presents the development towards a constitutive relationship for permanent strain using repeated load triaxial testing (or RLTT) data under various stress regimes for three granular materials prepared to a single level of compaction and at different levels of moisture content. For each sample investigated, initial permanent strain models were developed. A predictive model (${\epsilon }_p$ model) with seven parameters was then suggested for each material following the general power law based on the permanent strain testing data. The model is capable of estimating the accumulated permanent strain at any number of cycles as a function of number of repetitions, considering the ratio of the mean normal stress to atmospheric pressure, $p_a$, the maximum shear stress ratio, moisture content and maximum dry density corresponded to the optimum, and weighted plasticity index. The ${\epsilon }_p$ model was applied on data from multistage permanent strain testing over many cycles to validate the model’s performance in predicting permanent strain. The permanent strain model was found to have a good to excellent statistical prediction accuracy for the three investigated materials.