Programme

Discrete Element Methods for image‑based simulation

Most image-based workflows presented at IBSim convert 3D images into finite-element meshes. This training session introduces a complementary route: the Discrete Element Method (DEM), which represents matter as a set of interacting particles rather than a continuous mesh. That makes DEM especially well suited to the phenomena that are hardest to capture with FEM — crack initiation and propagation, fragmentation, granular flow, powder compaction, and diffuse damage inside a real, image-based microstructure. Every example will be built with a friencly python library or with GranOO, a free and open-source (GPLv3) C++/Python discrete element workbench developed by a French academic consortium (I2M / Arts et Métiers, Bordeaux — IRCER / University of Limoges — LAMIH / UPHF).

GranOO is not a black-box software but a modular collection of C++ libraries and Python bindings. Simulations are assembled as ordered plug-ins driven by simple XML input files, so a user can build a bespoke DEM model without rewriting a solver. It is an explicit dynamic DEM code embedding mechanical, thermal and electrical models (multiphysics), with cohesive-beam / lattice-spring formulations that let a discrete domain reproduce a continuous material — the key to bridging real microstructures and mechanical response.

Hands-on programme (4 modules)

1. DEM & GranOO — theory. Foundations of explicit DEM, the cohesive-beam model for continuous media, and how a GranOO simulation is assembled from plug-ins.
2. Powder compaction (friendly python libDEM). Granular packing and densification — directly relevant to additive manufacturing, powder-bed processes and sintering.
3. Image-based simulation at the microstructure scale (friendly python libDEM). The direct bridge to IBSim — turning a segmented µCT / tomographic volume into a DEM domain to simulate cracking, fragmentation and sintering in the actual microstructure.
4. Some Fracture simulations  (GranOO). DEM's flagship strength: multi-cracking and fragmentation (e.g. Brazilian test, impact on brittle media).

DEM complements image-based FEM precisely where meshes struggle: discontinuities. Recent peer-reviewed GranOO work already operates on this exact loop — image → microstructure → DEM — including ML-aided 3D microstructure reconstruction for viscous-flow sintering (Benjira et al., Powder Technology, 2026), 3D DEM of porous-cracked ceramics at the microstructure scale (Longchamp et al., J. Eur. Ceram. Soc., 2023), microstructure-scale dynamic fragmentation of porous-brittle materials (Longchamp et al., C. R. Mécanique, 2025), and powder spreading in additive manufacturing (Marchais et al., Comp. Part. Mech., 2021).