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Visualization study on the coarse graining DEM for large-scale gas–solid flow systems
Particuology ( IF 3.5 ) Pub Date : 2020-07-31 , DOI: 10.1016/j.partic.2020.07.001
Yuki Mori , Mikio Sakai

Gas–solid flows are ubiquitous in industrial systems. The coupled model of the discrete element method (DEM) and computational fluid dynamics (CFD) is one of the techniques for the simulation of the gas–solid flows. To enhance the applicability of the DEM-CFD method, the coarse graining DEM has been developed to simulate large-scale powder systems. The coarse graining DEM is a scaling law model and hence can simulate large-scale systems using a smaller number of particles than the actual one. Although the coarse graining DEM enables to effectively simulate large-scale powder systems on a single PC, visualized image is lack of reality due to reduced spatial resolution. Here a novel visualization method is developed to produce realistic images. In the proposed technique, the virtual particles are located by considering the motion and location of the coarse grain particles. To show the adequacy of the proposed method, two types of visualization based on the computational results are made: a blow-up of powder due to injected gas flow and a spouted bed. In these systems, the visualized images are shown to be improved by the proposed visualization technique. The effectiveness of the proposed method is proved by the agreement of the images based on the calculation results between the standard DEM-CFD method and coarse graining DEM.



中文翻译:

大型气固两相流系统粗粒度DEM的可视化研究

气固两相流在工业系统中无处不在。离散元方法(DEM)和计算流体动力学(CFD)的耦合模型是气固流模拟的技术之一。为了增强DEM-CFD方法的适用性,已经开发了粗粒度DEM来模拟大规模粉末系统。粗粒度DEM是一个比例定律模型,因此可以使用比实际数量少的粒子来模拟大规模系统。尽管粗粒度DEM可以在单个PC上有效地模拟大规模粉末系统,但由于空间分辨率降低,可视化图像仍然不现实。在这里,开发了一种新颖的可视化方法来产生逼真的图像。在提出的技术中,通过考虑粗粒粒子的运动和位置来定位虚拟粒子。为了显示所提出方法的适当性,基于计算结果进行了两种可视化处理:由于注入的气流造成的粉末吹扫和喷射床。在这些系统中,显示的可视化图像显示通过建议的可视化技术得到了改善。根据标准DEM-CFD方法和粗粒度DEM之间的计算结果,通过图像的一致性证明了该方法的有效性。显示的可视化图像通过提出的可视化技术得到了改善。根据标准DEM-CFD方法和粗粒度DEM之间的计算结果,通过图像的一致性证明了该方法的有效性。显示的可视化图像通过提出的可视化技术得到了改善。根据标准DEM-CFD方法和粗粒度DEM之间的计算结果,通过图像的一致性证明了该方法的有效性。

更新日期:2020-07-31
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