Sanjeev Adhikari

3D discrete element models of the hollow cylindrical asphalt concrete specimens subject to the internal pressure

The objective of this paper is to use the discrete element model (DEM) to predict the asphalt mixture dynamic modulus in the hollow cylindrical specimen across a range of test temperatures and load frequencies. The microstructure of the asphalt concrete specimen was captured by X-ray tomography techniques. The hollow circular images were produced from the layer of cylindrical X-ray computed tomography (X-ray CT) images. The asphalt concrete images were divided into three phases according to a density index: aggregate, sand mastic and air void phases. The sand mastic phase was composed of fine aggregates (smaller than 2.36 mm) and asphalt binder. The distribution of air void, sand mastic and aggregate were also investigated along with the depth of the hollow cylindrical specimen. In the DEM simulation, the sand mastics dynamic modulus using different loading frequencies and test temperatures was used to predict the asphalt mixtures dynamic modulus. The predicted dynamic modulus was at that same loading frequency and test temperature with sand mastics dynamic modulus. The strain response of the asphalt concrete under a tensile haversine load was calculated at the inner core of the hollow cylindrical specimen to determine the dynamic modulus. The linear contact-stiffness model and Burgers contact model were used to calculate this strain response. This paper has also investigated the difference in the dynamic modulus from the 2D and 3D models by comparing laboratory measurements of the asphalt mixture. When comparing the 2D and 3D DEM, the modulus prediction of the 3D DEM was around 27% higher than that of the 2D model. The difference in modulus between laboratory measurements and 3D DEM predictions was within a 10% range. The linear elastic model and the viscoelastic model were compared with the 2D DEM. When comparing these two models, it was found that the modulus difference was within a 5% range.

Air void effect on an idealised asphalt mixture using two-dimensional and three-dimensional discrete element modelling approach

In this study, an idealised asphalt mixture was modelled with the discrete element method for both two-dimensional (2D) and three-dimensional (3D) cases. The air voids were randomly generated and counted within the models to reach a specific air void level (e.g. 6%). The 2D models were used to compute the strain and stress responses when the specimens were subjected to a compressive load. Then, the moduli of the specimens were computed from the stress–strain curves. The 3D idealised model was generated using a number of layered 2D models. The air void distribution patterns were also studied with 2D and 3D randomly generated models at specific air void levels. The results showed that the modulus deviation increases when the air void level increases. In addition, the modulus deviations of the 3D models were found to be much lower than those of the 2D models. When comparing the modulus predictions from the 2D models with those from the 3D models, the research proved that the 3D models yielded higher moduli than the 2D models. The average of the predicted modulus difference between 2D and 3D models was 26% at 10% air voids, and 7% at 4% air voids. When the air void increased from 0 to 10%, the modulus decreased by 30% in the 3D models, when compared with 48% in the 2D models. The 2D and 3D models predicted the same modulus for 0% of air voids. However, the 2D models under-predicted the mixture modulus, especially when the air void level was higher. In the 2D modelling of the asphalt mixtures, a large number of models were needed to achieve a reasonable prediction due to larger deviation, even at lower air void levels. At higher air void levels, the 3D models yielded a much higher prediction than 2D simulations.

DEM Models of Idealized Asphalt Mixtures

The stiffness behavior of an idealized asphalt mixture at the different air void levels was investigated in this paper. The asphalt mixture was modeled with the discrete element modeling (DEM) approach by randomly generated air voids in two dimensions (2D) and three dimensions (3D). Air voids were calculated within the DEM model to meet the specific air void level (i.e. 4%, and 10%). Sixteen different 2D idealized models were generated with 4% and 10% air void levels. A 3D idealized model was generated using the 16 2D models. Then the 16 replicates of the 3D models were prepared with 4% and 10% air void levels. Both 2D and 3D models were used to compute the stress-strain response under compressive loads. The moduli of specimens were computed from the stress-strain curve. The result showed modulus decreased with air void increased. The 3D model predicted higher modulus than the 2D models. When air voids increased from 0% to 10%, the modulus decreased 30% on the 3D models and 48% on the 2D models. When comparing modulus prediction of 2D and 3D models, it was found that, at 0% air void level, the prediction was the same for both 3D and 2D. However, at 10% air void levels, 3D models yielded 26% higher modulus than the 2D models. It was found that the modulus deviation on the 3D models was much lower than the 2D models.

Two Dimensional and Three Dimensional Discrete Element Models for HMA

Hot Mix Asphalt (HMA) is a composite material that consists of mineral aggregates, asphalt binders and air voids. A Discrete Element Model (DEM) of the HMA microstructure was developed to study the stiffness behavior in both two dimensions (2D) and three dimensions (3D). Image analysis techniques were used to capture the HMA microstructure. The HMA microstructure was divided into two phases: aggregates phase (i.e., aggregates larger than 1.18mm sieve) and mastic phase (i.e., with binder and aggregates smaller than 1.18 mm). Air voids were modeled within the DEM to meet a specific air void level (i.e. 0%, 4%, and 7%) by using a random algorithm. The 3D microstructure of the asphalt mixture was obtained by using a number of parallel 2D images. The input data on the models included not only the aggregate and mastic properties, but also the microstructure of the aggregate skeleton and mastic distribution. Both 2D and 3D models were used to compute the stress-strain response under compressive loads. The moduli of the specimens were computed from the stress-strain curve in the DEM simulation. The moduli of the 2D and 3D models were then compared with the experimental measurements. It was found that the 3D discrete element models were able to predict the mixture dynamic modulus across a range of temperatures and loading frequencies. The 3D model predictions were much better than that of the 2D model. In addition, the effect of different air void percentages was discussed in this paper. As air void increased, the predicted modulus decreased.

Prediction of Dynamic Modulus of Asphalt Concrete using Two-Dimensional and Three-Dimensional Discrete Element Modeling Approach

The objective of this study is to predict the asphalt mixture dynamic modulus using both two-dimensional (2D) and three-dimensional (3D) discrete element models (DEM) generated using the X-ray computed tomography images. An experimental program was developed with a uniaxial compression test to measure the dynamic modulus of asphalt mastic and asphalt mixtures at different temperatures and loading frequencies. In the DEM simulation, the mastic properties and aggregate elastic modulus were used as input parameters. The strain response of the asphalt mastic and mixture models under a compressive load was monitored, and the dynamic modulus was computed. The mixture properties were obtained using images of aggregate, mastic, and air voids from the X-ray CT. The experimental measurements of dynamic modulus were employed to compare with the 2D and 3D predictions. It was found that the 3D discrete element models were able to predict the mixture modulus across a range of temperatures and loading frequencies. The 3D DEM models prediction is much better than that of the 2D DEM models.

Dynamic Moduli for M-E Design for Asphalt Pavements

In the USA, many highway agencies have successfully implemented the Superpave volumetric mixture design procedure. Yet, a number of studies have shown that the Superpave volumetric mixture design method alone is insufficient to ensure reliable mixture performance over a wide range of traffic and climatic conditions. As highway agencies begin the implementation of the AASHTO Mechanistic-Empirical Design Guide (MEPDG), they will be tasked with the development of local calibration factors specific to the materials, construction practices, loading regimes and environment of their region. The local calibration factors specific to the materials include the test of the dynamic modulus of asphalt mixtures. In fact, the dynamic modulus of asphalt mixtures is an important input parameter for pavement thickness design. Therefore, the objectives of this paper are to: 1) review the current status of Superpave simple performance tests for asphalt mixes; 2) measure the dynamic modulus of Superpave asphalt mixes, and; 3) compare with the predictive equations for the dynamic modulus to establish a correlation. The dynamic modulus data will be used in the MEPDG design procedure for asphalt pavements.