Discrete Element Modeling for Sieve Analysis with Image-based Realistic Aggregates
Grain sizes play significant roles in determining internal structure and mechanical behaviors of a granular assembly. The main objectives of this research are to develop a numerical method for sieve analysis through an image-based discrete element modeling and apply the newly-developed method for analyzing aggregate particle sizes. The discrete element software package, PFC5.0 Suite, was employed to establish a virtual sieving testing method to determine aggregates grain size. X-ray Computed Tomography was employed to scan the selected individual aggregate particles. Then, a speciallydesigned discrete element model was created for the virtual sieve tests. Finally, three vibration patterns were considered to investigate their effects on the sieving analysis results. Through this research, the recommendations were made for aggregate sieve analysis.