The discrete element method (DEM) coupled with computational fluid dynamics (CFD) is a powerful tool for exploring the detailed behaviors of dense particle–fluid interaction problems such as fluidized beds. Coarse-graining models have been proposed to decrease the computational cost by increasing the model particle size. In this study, we examine the influence of the model particle size and the spatial resolution on the average size and number of bubbles in coarse-graining DEM-CFD calculations of bubbling fluidized beds. Calculation results indicate that the bubble size is scaled by the model particle size if parameters are following similarity laws defined in a particle scale, as well as the geometric similarity of the whole system is maintained. The usage of coarse spatial resolution increases the bubble size and decreases the number of bubbles. The countervailing influence of the model particle size and the spatial resolution in a practical coarse-graining scenario results in nearly the same bubble size.

离散元法 (DEM) 与计算流体动力学 (CFD) 相结合，是探索密集颗粒-流体相互作用问题（例如流化床）的详细行为的有力工具。已经提出粗粒度模型以通过增加模型粒度来降低计算成本。在本研究中，我们研究了模型粒度和空间分辨率对鼓泡流化床粗粒 DEM-CFD 计算中气泡平均尺寸和数量的影响。计算结果表明，如果参数遵循粒子尺度中定义的相似性规律，并且保持整个系统的几何相似性，则气泡尺寸由模型粒子尺寸缩放。使用粗空间分辨率会增加气泡大小并减少气泡数量。