In particle systems, understanding mechanical interactions between particles is fundamental for accurately predicting material behavior under various conditions, especially when cohesive forces play a critical role. The Discrete Element Method (DEM) is able to model these interactions based on material as well as contact properties. This paper evaluates the accuracy of DEM in predicting material behavior, for which a cost-effective cohesion model is implemented within an in-house DEM code. Simulations of wooden particles in a shear cell, with and without grease coating, are able to replicate the corresponding experimental results. The addition of the cohesion model results in a negligible increase in computational effort, which is of key importance for its application to larger systems. (c) 2025 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creative commons.org/licenses/by/4.0/).
Discrete element modeling of shear cell experiments with cohesive wooden spheres
la Manna, S;Barletta, D;Poletto, M;
2025
Abstract
In particle systems, understanding mechanical interactions between particles is fundamental for accurately predicting material behavior under various conditions, especially when cohesive forces play a critical role. The Discrete Element Method (DEM) is able to model these interactions based on material as well as contact properties. This paper evaluates the accuracy of DEM in predicting material behavior, for which a cost-effective cohesion model is implemented within an in-house DEM code. Simulations of wooden particles in a shear cell, with and without grease coating, are able to replicate the corresponding experimental results. The addition of the cohesion model results in a negligible increase in computational effort, which is of key importance for its application to larger systems. (c) 2025 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creative commons.org/licenses/by/4.0/).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


