DQDaniel Queteschiner

Daniel Queteschiner

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

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Daniel Queteschiner has a total of 5 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Coupling resolved and coarse-grain DEM models

    by Daniel Queteschiner, Thomas Lichtenegger, Simon Schneiderbauer, Stefan Pirker

    The discrete element method (DEM) is a well-established approach to study granular flows in numerous fields of application; however, the DEM is a computationally demanding method. Thus, simulations of industrial scale systems are hardly feasible on today’s hardware. This situation is typically resolved by limiting the simulation domain or introducing a coarse-grain model. While the former approach does not provide information of the full system, the latter is especially problematic in systems, where geometric restrictions are in the range of particle size, so both are insufficient to adequately describe large-scale processes. To overcome this problem, we propose a novel technique that efficiently combines resolved and coarse-grain DEM models. The method is designed to capture the details of the granular system in spatially confined regions of interest while retaining the benefits of the coarse-grain model where a lower resolution is sufficient. To this end, our method establishes two-way coupling between resolved and coarse-grain parts by volumetric passing of boundary conditions.


  • Open Access

    Adaptive coarse-graining for large-scale DEM simulations

    by Daniel Queteschiner, Thomas Lichtenegger, Simon Schneiderbauer, Stefan Pirker

    The large time and length scales and, not least, the vast number of particles involved in industrial-scale simulations inflate the computational costs of the Discrete Element Method (DEM) excessively. Coarse grain models can help to lower the computational demands significantly. However, for effects that intrinsically depend on particle size, coarse grain models fail to correctly predict the behaviour of the granular system. To solve this problem we have developed a new technique based on the efficient combination of fine-scale and coarse grain DEM models. The method is designed to capture the details of the granular system in spatially confined sub-regions while keeping the computational benefits of the coarse grain model where a lower resolution is sufficient. To this end, our method establishes two-way coupling between resolved and coarse grain parts of the system by volumetric passing of boundary conditions. Even more, multiple levels of coarse-graining may be combined to achieve an optimal balance between accuracy and speedup. This approach enables us to reach large time and length scales while retaining specifics of crucial regions. Furthermore, the presented model can be extended to coupled CFD-DEM simulations, where the resolution of the CFD mesh may be changed adaptively as well.