3D discrete element models of the hollow cylindrical asphalt concrete specimens subject to the internal pressure
Source abstract
Abstract
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 mastic's dynamic modulus using different loading frequencies and test temperatures was used to predict the asphalt mixture's dynamic modulus. The predicted dynamic modulus was at that same loading frequency and test temperature with sand mastic's 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 Burger's 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.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Asphalt Pavement Performance Evaluation · Rock Mechanics and Modeling · Geotechnical Engineering and Underground Structures
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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