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A GPU-based coupled SPH-DEM method for particle-fluid flow with free surfaces

机译:一种基于GPU的耦合SPH-DEM,用于自由表面的颗粒流体流动

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Particle-fluid flows with free-surfaces are commonly encountered in many industrial processes, such as wet ball milling, slurry transport and mixing. Accurate prediction of particle behaviors in these systems is critical to establish fundamental understandings of the processes, however the presence of the free-surface makes modelling them a challenge for most traditional, continuum, multi-phase methodologies. Coupling of smoothed particle hydrodynamics and discrete element method (SPH-DEM) has the potential to be an effective numerical method to achieve this goal. However, practical application of this method remains challenging due to high computational demands. In this work, a general purposed SPH-DEM model that runs entirely on a Graphic Processing Unit (GPU) is developed to accelerate the simulation. Fluid-solid coupling is based on local averaging techniques and, to accelerate neighbor searching, a dual-grid searching approach is adapted to a GPU architecture to tackle the size difference in the searching area between SPH and DEM. Simulation results compare well with experimental results on dam-breaking of a free-surface flow and particle-fluid flow both qualitatively and quantitatively, confirming the validity of the developed model. More than 10 million fluid particles can be simulated on a single GPU using double-precision floating point operations. A linear scalability of calculation time with the number of particles is obtained for both single-phase and two-phase flows. Practical application of the developed model is demonstrated by simulations of an agitated tubular reactor and a rotating drum, showing its capability in handling complex engineering problems involving both free-surfaces and particle-fluid interactions. (C) 2018 The Authors. Published by Elsevier B.V.
机译:具有自由表面的颗粒流体通常在许多工业过程中遇到,例如湿球磨,浆料输送和混合。这些系统中的粒子行为的准确预测对于建立对过程的基本理解至关重要,但是自由表面的存在使它们对最传统的连续性多相方法进行建模。平滑颗粒流体动力学和离散元素法(SPH-DEM)的耦合有可能成为实现这一目标的有效数值方法。然而,由于高计算需求,这种方法的实际应用仍然具有挑战性。在这项工作中,开发了一种完全在图形处理单元(GPU)上运行的一般所用的SPH-DEM模型以加速模拟。流体固耦合基于本地平均技术,并且为了加速邻居搜索,双电网搜索方法适用于GPU架构,以解决SPH和DEM之间的搜索区域中的尺寸差异。仿真结果与实验结果相比,实验结果对定性和定量的自由表面流动和颗粒流体流动的实验结果,确认了开发模型的有效性。可以使用双精度浮点操作在单个GPU上模拟超过1000万颗粒。为单相和两相流量获得具有粒子数量的计算时间的线性可扩展性。通过搅拌的管状反应器和旋转鼓的模拟证明了开发模型的实际应用,示出了其在处理涉及自由表面和颗粒流体相互作用的复杂工程问题方面的能力。 (c)2018作者。 elsevier b.v出版。

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