PARTICLES 2023

Advanced Structure Modelling Using the Bonded-Particle Method: Enabling Complex Capabilities for Structures in DEM Simulations

  • Fimbinger, Eric (Montanuniversität Leoben)

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Bonded-particle modelling is a powerful approach for simulating particle-made structures with enhanced abilities, i.e., structures that are able to deform, brake/fracture, and thus interact with other particles of a DEM simulation in an enhanced complex manner. This modelling approach is based on connecting particles with beam elements (commonly termed bondings, with each bonding connecting two particles) to create a bonded-particle model (BPM), typically consisting of a large number of particles and bondings. The behaviour of such a BPM can be adjusted in two categories: via properties related to the particles, e.g. their mass, shape, or frictional characteristics, and via properties related to the bondings, e.g. their Young’s moduli or breakage criteria. This contribution presents developments in complex bonded-particle modelling for achieving flexible/deformable and breakable/fracturable structures and highlights the enhanced capabilities made possible by using this approach. For this purpose, various applications for bonded-particle modelling in DEM simulations are presented, with selected case studies each demonstrating the effectiveness of bonded-particle modelling in solving practical engineering problems, including: - 1D BPMs, e.g., deformable beams or ropes and chains, - 2D BPMs, e.g., membranes, textiles, nets, bags, shell-like parts (e.g. silos), or conveyor belts (with particular reference to dynamic belt simulation), and - 3D BPMs, e.g., complex-breakable structures (e.g. with considering crack formation or dynamic impact handling; e.g. illustrated on filter cake material). Furthermore, possible interaction scenarios, including interactions of BPMs to particles, rigid parts, other BPMs, or even in terms of SPH (Smoothed-Particle Hydrodynamic) or MBD (Multibody Dynamics), are addressed. Finally, current developments and potential future directions in this field are outlined, and potentials for extending this modelling approach to further application areas are discussed.