Automated Shape Analysis and DEM Study on Graded Crushed Stone

Graded crushed stone (GCS), as a cheap and essential component, is of great importance in road construction. The irregularity and variability of particle shape is known to affect the packing characteristics of GCS, such as compactness and void ratio. In this study, the realistic particle outline is...

Full description

Saved in:
Bibliographic Details
Main Authors: Hao Bai, Ruidong Li, Xiangyu Hu, Fei Chen, Zhiyong Liao
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Advances in Materials Science and Engineering
Online Access:http://dx.doi.org/10.1155/2021/3463363
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Graded crushed stone (GCS), as a cheap and essential component, is of great importance in road construction. The irregularity and variability of particle shape is known to affect the packing characteristics of GCS, such as compactness and void ratio. In this study, the realistic particle outline is first automatically extracted based on digital image processing and deep learning algorithms. Then, the elongation (EI), roundness (Rd), and roughness (Rg) of GCS are quantified by shape evaluation algorithms. Moreover, based on the establishment of the GCS shape library, the gravity deposition with various elongations is simulated using the discrete element method to study the packing features of GCS. The elongation effects on the macroscopic and microscopic quantities are explored. Finally, the shear behavior of GCS is studied. The results illustrate that elongation has a significant effect on the packing of GCS.
ISSN:1687-8434
1687-8442