CFD-DEM simulation of fluidized bed with an immersed tube using a coarse-grain model

2021 ◽  
Vol 231 ◽  
pp. 116290
Author(s):  
Lianyong Zhou ◽  
Yongzhi Zhao
2019 ◽  
Vol 44 (13) ◽  
pp. 6448-6460 ◽  
Author(s):  
Tian Qi ◽  
Tingzhou Lei ◽  
Beibei Yan ◽  
Guanyi Chen ◽  
Zhongshan Li ◽  
...  

2014 ◽  
Vol 244 ◽  
pp. 33-43 ◽  
Author(s):  
Mikio Sakai ◽  
Minami Abe ◽  
Yusuke Shigeto ◽  
Shin Mizutani ◽  
Hiroyuki Takahashi ◽  
...  

2019 ◽  
Vol 196 ◽  
pp. 37-53 ◽  
Author(s):  
Alexander Stroh ◽  
Alexander Daikeler ◽  
Markku Nikku ◽  
Jan May ◽  
Falah Alobaid ◽  
...  

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1098
Author(s):  
Kizuku Kushimoto ◽  
Kaya Suzuki ◽  
Shingo Ishihara ◽  
Rikio Soda ◽  
Kimihiro Ozaki ◽  
...  

A new simpler coarse-grain model (SCG) for analyzing particle behaviors under fluid flow in a dilute system, by using a discrete element method (DEM), was developed to reduce calculation load. In the SCG model, coarse-grained (CG) particles were enlarged from original particles in the same way as the existing coarse-grain model; however, the modeling concept differed from the other models. The SCG model focused on the acceleration by the fluid drag force, and the CG particles’ acceleration coincided with that of the original particles. Consequently, the model imposed only the following simple rule: the product of particle density and squared particle diameter is constant. Thus, the model had features that can be easily implemented in the DEM simulation to comprehend the modeled physical phenomenon. The model was validated by comparing the behaviors of the CG particles with the original particles in the uniform and the vortex flow fields. Moreover, the usability of the SCG model on simulating real dilute systems was confirmed by representing the particle behavior in a classifier. Therefore, the particle behavior in dilute particle-concentration systems would be analyzed more simply with the SCG model.


2014 ◽  
Vol 5 (12) ◽  
pp. 2144-2149 ◽  
Author(s):  
John K. Brennan ◽  
Martin Lísal ◽  
Joshua D. Moore ◽  
Sergei Izvekov ◽  
Igor V. Schweigert ◽  
...  

2017 ◽  
Vol 314 ◽  
pp. 346-354 ◽  
Author(s):  
Chengxiao Song ◽  
Daoyin Liu ◽  
Jiliang Ma ◽  
Xiaoping Chen

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