Search

The compaction of asphalt mixture is crucial to the performance of the pavement. However, the mix design (i.e., porosity, aggregate size distribution, binder content), which is based on compaction results, remains largely empirical. It is difficult to relate the aggregate size distribution and the asphalt binder properties to the compaction curve in both the field and laboratory compaction of asphalt mixtures. In this paper, the author proposes a simple mathematical model from the perspective of granular physics to predict the compaction of asphalt mixtures. In this model, the compaction process is divided into two mechanisms: (i) viscoplastic deformation of an ordered granular-fluid assembly, and (ii) the transition from an ordered system to a disordered system due to particle rearrangement. This model could take into account both the viscous properties of the asphalt binder and the grain size distributions of the aggregates, where the viscous deformation is calculated with a proposed governing equation and the particle rearrangement effect is solved using simple DEM simulations. This model is calibrated based on the Superpave gyratory compaction tests in the pavement lab, and the R-squares of model predictions are all above 0.95. The model results are compared with experimental data to show that it can provide good predictions for the experiments, suggesting its potential for enhancing the design of asphalt mixtures.

Suffusion constitutes a major threat to the foundation of a dam, and the likelihood of suffusion is always determined by the internal stability of soils. It has been verified that internal stability is closely related to the grain size distribution (GSD) of soils. In this study, a numerical model is developed to simulate the suffusion process. The model takes the combined effects of GSD and porosity (n) into account, as well as Wilcock and Crowe’s theory, which is also adopted to quantify the inception and transport of soils. This proposed model is validated with the experimental data and shows satisfactory performance in simulating the process of suffusion. By analyzing the simulation results of the model, the mechanism is disclosed on how soils with specific GSD behaving internally unstable. Moreover, the internal stability of soils can be evaluated through the model. Results show that it is able to distinguish the internal stability of 30 runs out of 36, indicating a 83.33% of accuracy, which is higher than the traditional GSD-based approaches.