To reliably predict the permanent deformation behaviour of unbound granular materials (UGM) in a pavement structure, the material parameters of the constitutive models used in design should be evaluated using a multi-stage (MS) loading approach. This paper investigated the prediction of the accumulation of permanent strain in UGM using some current models, extended applying the time-hardening approach, based on MS repeated load triaxial tests (RLTTs). The material parameters of these models were optimised for five different UGM used in pavement construction using the MS RLTT data with a specific set of stress levels. With these models, the accumulations of permanent strain in the same materials for MS RLTTs with a different set of stress levels were predicted. Using this approach, three out of the four models performed very well, which may be further developed for field conditions for better prediction of rutting.

A simple model has been proposed to characterise the accumulation of permanent deformation (PD) in unbound granular materials (UGMs) under cyclic loading of variable magnitudes. The model was developed based on multi-stage (MS) repeated-load triaxial (RLT) tests. The material parameters of this model can be evaluated using an MS RLT test. The model was validated by calibrating it for a few UGMs with a range of grain size distributions, moisture contents and degrees of compaction. The calibrated model was further validated by predicting the PD behaviour of some of these UGMs for different stress conditions. Generally, quite satisfactory predictions were obtained with this model with the advantage of reduced effort required for its calibration compared to some existing models. Additionally, the sensitivity of the parameters of this model to moisture, degree of compaction and grain size distribution was investigated with the aim of incorporating them into the model in future.

The influence of moisture on the resilient deformation properties of unbound granular materials was investigated based on repeated load triaxial tests. Results showed that the resilient modulus (M_R) decreased with increasing moisture for a relatively low number of load cycles (N) where the deformation behaviour was mostly resilient with a negligible amount of associated accumulated permanent deformation (PD). Modelling attempts on this behaviour were quite satisfactory. Furthermore, the M_R showed an increasing trend with increasing moisture, up to the optimum, when the N was relatively large with a significant amount of accumulated PD. Above the optimum, the M_R generally decreased. Further investigation suggested that moisture aided the post-compaction (PC) and possible particle rearrangement that resulted in the increased PD and increased M_R. The existing model did not work in this case indicating that the effect of PC on M_R should be considered in modelling.

An existing permanent deformation (PD) model for the unbound granular materials (UGMs) in pavements, developed based on multistage (MS) repeated load triaxial (RLT) tests, was modified to better suit to field conditions and software applications. The model was calibrated for a few UGMs with a series of moisture contents (w) using MS (to include the stress-history effect) RLT tests and was validated by predicting the PD under different sets of stress levels and w’s. Generally, it exhibited improved predictions over the Mechanistic-Empirical Pavement Design Guide (MEPDG) model. The model was further applied for field conditions and was implemented in a pavement design software entitled ERAPave PP, using data from accelerated testing of three structures employing a heavy vehicle simulator (HVS). Based on additional MS RLT tests, a guideline for the ranges of the material parameters for different types of UGMs was presented.

Permanent deformation is one of the failure modes considered in the analysis and design of flexible pavements. ERAPave performance prediction (PP) which is a mechanistic empirical (ME) pavement design tool utilises two distinct models for the prediction of permanent deformation in the bound and unbound granular layers including subgrade. This paper aims to calibrate these models using pavement response and performance data from accelerated pavement testing (APT) structures. Material properties such as layer modulus were established through an optimisation that involves both falling weight deflectometer (FWD) and pavement response measurements. Based on the predicted performance results, a separate set of calibration was performed for permanent deformation development in moist and wet moisture conditions. The calibrated models have resulted in predictions that are in good agreement with observed performances. Furthermore, the model parameters successfully captured the initial densification behaviour and the associated sensitivity with axle load level.