Funding organisation: DFG
Contact Person: Kostas Giannis
Summary of the overall project:
Our project focuses on refining an elastic-plastic multi-contact model for Discrete Element Method (DEM) simulations, particularly for particle assemblies such as pharmaceutical powders. By validating and improving this model, our aim is to enhance predictions of both micro and macro behavior, especially during compression to form tablets under high loads.
Incorporating machine learning techniques enables us to generate 3D particles, moving beyond the assumption of perfectly spherical particles. This approach enhances the realism of our simulations, providing a more accurate representation of particle behavior under compression.
In addition, we will compare DEM against detailed Finite Element Method (FEM) simulations to validate its accuracy and effectiveness.
Our goal is to establish DEM as a standard tool for analyzing compaction processes across various industries. This advancement will lead to more efficient industrial practices and reduced reliance on empirical-based design approaches, marking a new era of precision in powder processing.
Fig.: Schematic representation of the project plan