| Issue |
EPJ Web Conf.
Volume 340, 2025
Powders & Grains 2025 – 10th International Conference on Micromechanics on Granular Media
|
|
|---|---|---|
| Article Number | 05007 | |
| Number of page(s) | 4 | |
| Section | Polydispersity, Segregation, and Pattern Formation | |
| DOI | https://doi.org/10.1051/epjconf/202534005007 | |
| Published online | 01 December 2025 | |
https://doi.org/10.1051/epjconf/202534005007
Flow behaviour of granular materials: Modelling wall adhesion and its impact on grain segregation
School of Chemical and Process Engineering, University of Leeds, LS2 9JT, UK
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 1 December 2025
Abstract
Granular assemblies, composed of large collections of discrete, macroscopic particles, exhibit complex and often unpredictable behaviours during flow. For instance, discharge of granular materials from a hopper can result in particles segregating by size, and the role of wall adhesion in this process remains underexplored. This study uses Discrete Element Modelling (DEM) to examine how wall adhesion affects particle segregation and mound formation on discharge. A bin-based method from [4] is employed to assess segregation under gravity in mass flow and funnel flow geometries. Segregation in both geometries is primarily driven by percolation during loading. In mass flow, wall adhesion primarily affects finer particles at lower regions, influencing their initial flow patterns, while its impact on larger particles increases with height. In funnel flow, adhesion influences larger particles throughout the system, with strong adhesion values (>0.025 J/m2) impeding finer particle flow at higher levels, ultimately reversing initial segregation trends. This results in layered segregation across different flow phases, producing distinct stratified layers in the discharge mound.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

