coarse-grained CFD-DEM方法在不同流态流化床中的模拟验证

doi:10.11949/j.issn.0438-1157.20180962

摘要/Abstract

摘要：

传统CFD-DEM方法的计算量随着系统内颗粒数目的增加而显著增加，coarse-grained CFD-DEM（粗颗粒）方法将若干个真实颗粒打包成虚拟颗粒从而显著减小系统计算量。在coarse-grained CFD-DEM方法进行应用之前，对其进行广泛的验证是有必要的。采用coarse-grained CFD-DEM方法模拟得到不同流态流化床的气固流动特征（固含率、压降、颗粒速度等），与传统CFD-DEM和实验测量吻合较好。另外，系统的计算效率随着粗颗粒放大系数的增加显著提升。研究表明，粗颗粒方法能够以较小的计算精度损失而使计算速度大幅提升，能够适用于大尺度稠密气固流动系统的模拟。

关键词: coarse-grained方法, 离散单元法, 计算流体力学, 流化床, 气固两相流, 计算效率

Abstract:

The computation load for traditional computational fluid dynamics-discrete element method (CFD-DEM) simulations tremendously increases when the number of particles augments in the system. The coarse-grained CFD-DEM method, in which a number of real particles are lumped into a numerical parcel, can remarkably reduce the computation load. It is necessary to extensively verify the coarse-grained CFD-DEM method before it is applied. Therefore, in the current work, the coarse-grained CFD-DEM method is validated in fluidized beds with various fluidization regimes. On one hand, it is found that gas and solid features (i.e., void fraction, pressure signals, and particle velocity) obtained from this method match well with the experiment measurements. On the other hand, as the coarse-grained ratios increase, the calculation time for a specific case is significantly reduced. In summary, the coarse-grained CFD-DEM contributes a great improvement of calculation efficiency while a little loss of numerical accuracy, which is expected to be a powerful tool to simulate gas-solid flow dynamics in large-scale dense particulate systems.

Key words: coarse-grained method, DEM, CFD, fluidized bed, gas-solid flow, computational efficiency

中图分类号:

TQ 018

林俊杰, 罗坤, 王帅, 胡陈枢, 樊建人. coarse-grained CFD-DEM方法在不同流态流化床中的模拟验证[J]. 化工学报, 2019, 70(5): 1702-1712.

Junjie LIN, Kun LUO, Shuai WANG, Chenshu HU, Jianren FAN. Verification of coarse-grained CFD-DEM method in multiple flow regimes[J]. CIESC Journal, 2019, 70(5): 1702-1712.

图/表 15

图1 鼓泡床模拟装置

Fig.1 Experimental setup of bubbling fluidized bed adopted in simulation

表1 物性参数（鼓泡流化床）

Table 1 Physical properties and parameters(bubbling fluidized bed)

Parameter	Value
particle diameter/mm	3.256
particle density/(kg?m^-3)	1131
original number of particles	95000
restitution coefficient	0.97
friction coefficient	0.35
collision spring constant/(N?m^-1)	800
parcel diameter of CGP-k1.5/mm	4.884
parcel number of CGP-k1.5	28148
parcel diameter of CGP-k2/mm	6.512
parcel number of CGP-k2	11875
fluid density/(kg?m^-3)	1.205
dynamic viscosity/(Pa·s)	1.8 × 10^-5
superficial velocity/(m?s^-1)	2.1

图2 传统CFD-DEM与coarse-grained CFD-DEM模拟所得鼓泡床中颗粒速度瞬态分布（t = 30 s）

Fig.2 Transient distribution of particle velocity in bubbling fluidized bed simulated by traditional and coarse-grained CFD-DEM

图3 鼓泡床时均分布

Fig.3 Time-averaged distribution of bubbling fluidized bed

图4 鼓泡床中压降对比及压力频谱特性对比

Fig.4 Comparison of pressure drop and frequency spectrum in bubbling fluidized bed

图5 鼓泡床中不同模拟方法耗时对比

Fig.5 Comparison of calculation time with different methods in bubbling fluidized bed

图6 三维喷动床几何体示意图

Fig.6 Schematic diagram of spouting fluidized bed used in present simulation

表2 物性参数(喷动床流化床)

Table 2 Physical properties and parameters(spouting fluidized bed)

Parameter	Value
particle diameter/mm	4.04
particle density/(kg?m^-3)	2526
original number of particles	44800
restitution coefficient	0.97
friction coefficient	0.33
collision spring constant/(N?m^-1)	800
parcel diameter of CGP-k1.5/mm	6.06
parcel number of CGP-k1.5	13274
parcel diameter of CGP-k2/mm	8.08
parcel number of CGP-k2	5600
fluid density/(kg?m^-3)	1.205
dynamic viscosity/(Pa·s)	1.8 × 10^-5
spouting velocity/(m?s^-1)	65
background velocity/(m?s^-1)	3.5

图7 传统CFD-DEM与coarse-grained CFD-DEM模拟所得喷动床中颗粒速度瞬态分布（t = 30 s）

Fig.7 Transient distribution of particle velocity in spouting fluidized bed simulated by traditional and coarse-grained CFD-DEM

图8 喷动床气固流动特性

Fig.8 Time-averaged gas-solid properties in spouting fluidized bed

图9 喷动床中颗粒垂直速度时均分布

Fig.9 Particle vertical velocity in spouting fluidized bed measured with different methods

图10 喷动床中不同模拟方法耗时对比

Fig.10 Comparison of calculation time with different methods in spouting fluidized bed

图11 循环流化床3-D几何结构及计算域网格划分

Fig.11 Sketch of 3-D circulating fluidized bed and grid of calculation domain

图12 提升管不同高度处x = 0和y = 0截面固含率分布

Fig.12 Distributions of time-averaged solid holdup at different height of slices x = 0 and y = 0 of riser

图13 循环流化床整床压降时均分布

Fig.13 Full-loop distribution of pressure in CFB with time-averaged properties

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