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A novel CFD-DEM coarse-graining method based on the Voronoi tessellation

机译:一种基于Voronoi曲面细分的新型CFD-DEM粗磨法

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摘要

In unresolved flow CFD-DEM simulations, the porosity values for each CFD cell are determined using a coarse graining algorithm. While this approach enables coupled simulations of representative numbers of particles, the influence of the porosity local to the particles on the fluid-particle interaction force is not captured. This contribution considers a two-grid coarse-graining method that determines a local porosity for each particle using a radical Voronoi tessellation of the system. A relatively fine, regular point cloud is used to map these local porosity data to the CFD cells. The method is evaluated using two different cases considering both disperse and tightly packed particles. The data show that the method conserves porosity data, is reasonably grid-independent and can generate a relatively smooth porosity field. The new method can more accurately predict the fluid-particle interactive force for polydisperse particle system than alternative methods that have been implemented in unresolved CFD-DEM codes.
机译:在未解析流CFD-DEM模拟中,每个CFD单元的孔隙度值使用粗粒化算法确定。虽然这种方法能够对代表性数量的颗粒进行耦合模拟,但无法捕捉颗粒局部孔隙率对流体-颗粒相互作用力的影响。本文考虑了一种双网格粗粒化方法,该方法使用系统的径向Voronoi细分确定每个粒子的局部孔隙度。使用相对精细、规则的点云将这些局部孔隙度数据映射到CFD单元。使用两种不同的情况对该方法进行了评估,同时考虑了分散和紧密堆积的颗粒。数据表明,该方法保存了孔隙度数据,具有合理的网格无关性,可以生成相对平滑的孔隙度场。与未解析的CFD-DEM程序中的替代方法相比,新方法可以更准确地预测多分散颗粒系统的流体-颗粒相互作用力。

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