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Lagrangian Simulation of a Fluid with Solid Particle Loading Performed on Supercomputers

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Abstract

The simulation of a fluid with particle loading is a challenging task. In this contribution two Lagrangian simulation methods are coupled to handle the challenges when simulating such scenarios. The Smoothed Particle Hydrodynamics method is used for modeling the fluid. The particles within the fluid are simulated with the Discrete Element Method, which is also applied for the boundary geometry. These methods are coupled to model a fluid and solid particles in one common simulation. In this work Lagrangian methods are employed because the natural handling of the solid-fluid interface.The simulation of a fluid with particle loading requires a large numbers of particles. With an increasing number of particles the computational effort rises. In the presented examples, the number of particles is up to 50 million. Therefore, the calculation is done on supercomputers.First, in this work the simulation framework for complex fluid particles simulation is presented. Then, the employed simulation methods are introduced and some simulations for verifying the framework are discussed. Afterwards simulations of a fluid with particles as loading and complex boundaries and the results are presented.

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Acknowledgements

The research leading to the presented results has received funding from the German Research Foundation (DFG) under the program SFB 716 “A5 Dynamic simulation of systems with large particle numbers”, subproject “Simulation of abrasive damage processes using hybrid smoothed particle hydrodynamics”. Also, the support of the colleagues within the SFB 716, especially of D2, M.Sc. Amer Wafai and Dr.-Ing. Rainer Keller has been very helpful. This financial support by the DFG is highly appreciated.

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Correspondence to Florian Beck .

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Beck, F., Fleissner, F., Eberhard, P. (2013). Lagrangian Simulation of a Fluid with Solid Particle Loading Performed on Supercomputers. In: Nagel, W., Kröner, D., Resch, M. (eds) High Performance Computing in Science and Engineering ‘13. Springer, Cham. https://doi.org/10.1007/978-3-319-02165-2_28

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