Open AccessAutomated Shape Analysis and DEM Study on Graded Crushed Stone
Author(s) -
Hao Bai,
Ruidong Li,
Xiangyu Hu,
Fei Chen,
Zhiyong Liao
Publication year - 2021
Publication title -
advances in materials science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.356
H-Index - 42
eISSN - 1687-8442
pISSN - 1687-8434
DOI - 10.1155/2021/3463363
Subject(s) - roundness (object) , materials science , elongation , discrete element method , void (composites) , particle (ecology) , surface finish , shape factor , void ratio , biological system , composite material , artificial intelligence , mechanics , computer science , geometry , ultimate tensile strength , mathematics , physics , oceanography , biology , geology
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.
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