Accompanying dataset for the paper "A Level Set Discrete Element Model (LS-DEM) for sintering with an optimization-based contact detection"

Contributions Brayan Paredes-Goyes did contribute to conceive the study, to develop the methodology, to implement the code, to perform numerical simulations and to draft the manuscript. David Jauffres did contribute to conceive the study, to develop the methodology, to co-supervise the project and to critically review the manuscript. Christophe L. Martin did contribute to conceive the study, to perform numerical simulations, helped with implementation and numerical issues, to coordinate the project and to critically review the manuscript. Funding sources This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement MATHEGRAM No 813202. Data structure and information data/Figure11a : Densification kinetics of two prolate ellipsoids and comparison with two spheres and with Eq.(16). data/Figure11b : Consolidation kinetics of two prolate ellipsoids and comparison with two spheres and with Eq.(16). data/Figure12 : Sintering of packings of ellipsoids with different aspect ratios. data/Figure13 : Distribution of the equivalent radius for spheres and ellipsoids after sintering. data/Figure2 : Contact detection accuracy of the original LS-DEM method for a packing of spherical particles. data/Figure7c : Relative error of the approximate solution of the level-set values for an elongated prolate ellipsoid data/Figure8 : Comaprison of the resulting normalized elastic force in LS-DEM with DEM superquadrics and FEM . data/Figure9a : Coordination number during jamming of spheres. data/Figure9b : Mean indentation of ellipsoids as a function of relative density during jamming. data/Figure9c : Initial and final microstructures obtained during jamming. data/Figure10a : Evolution of the mean normalized indentation during sintering of spheres with standard DEM and LS-DEM. data/Figure10b : Evolution of the average coordination number during sintering of spheres with standard DEM and LS-DEM. input/gas_of_spherical_particles : Simulation input files to create a simple gas of spherical particles and to pack them. input/gas_to_pack_0.6_LS : Simulation input files to pack ellipsoids. input/sintering_LS : Simulation input files to sinter ellipsoids. workflows/reproduce_figures.py: script to re-generate all figures workflows/reproduce.sh: script to re-generate all results (follows description in the input/README.md) Paper Description Sintering is a high temperature process for the consolidation of ceramic, metal and polymer powders. The Discrete Element Method (DEM) has been effectively used to model the sintering process at the particle scale considering spherical particles. However, standard manufacturing processes rarely deal with spherical particles. As sintering is a curvature-controlled process, it is important to take into account the deviation from sphericity. This study presents a DEM sintering model for non-spherical particles. The description and dynamic evolution of arbitrary shape particles is achieved by using the Level Set discrete element method (LS-DEM). The original LS-DEM approach uses boundary nodes on the particles to detect contacts. We employ an optimization-based contact detection approach. This improves the capture of small contacts, which is important for a correct description of sintering evolution with reasonable CPU-time consumption. A Newton-Raphson scheme is employed for the optimization algorithm. The normal force and neck size evolution expressions of spherical particles are adapted for arbitrary shape particles by using the local curvature at the contact. The developed model is validated for elastic contacts on superquadric ellipsoids. It is compared with standard DEM on spheres for sintering. The model is applied to investigate the consolidation kinetics of a packing of ellipsoidal particles. It is shown, that a deviation from sphericity is beneficial for both prolate and oblate ellipsoids. An optimum aspect ratio is evaluated, demonstrating that particles that are too elongated slow down densification kinetics.