Effects of turbulence on radial gas diffusion in binary particle fluidized bed

doi:10.11949/0438-1157.20241497

Abstract

Abstract:

In this work, the constants of the standard k-ε turbulence model were optimized to reduce numerical diffusion during simulations of gas diffusion in a binary fluidized bed. The research results show that when the Launder turbulence model constants are used, the turbulence intensity of the flow field in the fluidized bed is too large, resulting in a large difference between the simulation results and the experimental data. By adjusting the turbulence model constants, the calculation accuracy can be significantly improved, and the simulation results are more consistent with the experimental data. When the gas velocity is low, turbulence has little effect on the radial diffusion of gas. But when the gas velocity is high, the consistency between the simulation results and the experimental data using the new model constants is significantly improved. As the concentration of heavy particles in the fluidized bed increased, the tracer concentration in the central region initially decreased, and then increased. The introduction of the second component affected the turbulence intensity in the fluidized bed in a more complex manner.

Key words: fluidized bed, turbulent model constants, gas diffusion, two phase flow, CFD

摘要：

针对模拟研究双组分流化床内气体扩散过程中出现的计算偏差，提出通过优化标准k-ε湍流模型常数提高计算精度，从而消除计算偏差。研究结果表明：采用Launder湍流模型常数时，计算获得流化床内流场湍流强度偏大，导致模拟结果与实验数据相差较大；通过调整湍流模型常数可以明显提高计算精度，模拟结果与实验数据更为一致。在气速较低时，湍流对气体径向扩散影响不大；但在气速较高时，采用新模型常数模拟结果与实验数据的吻合度明显提高。随着重组分颗粒的增加，流化床中心区示踪气体浓度呈现先降低后升高的变化趋势。第二组分颗粒的添加对流化床内湍流强度影响较为复杂。

关键词: 流化床, 湍流模型常数, 气体扩散, 两相流, 计算流体力学

CLC Number:

TQ 021.1

Yiyun ZHANG, Hengzhi CHEN, Yang LI, Chang'an MU, Quanhai WANG. Effects of turbulence on radial gas diffusion in binary particle fluidized bed[J]. CIESC Journal, 2025, 76(6): 2559-2568.

张亿韵, 陈恒志, 李洋, 慕长安, 王泉海. 湍流对双组分颗粒流化床气体径向扩散的影响[J]. 化工学报, 2025, 76(6): 2559-2568.

Figures/Tables 15

Fig.1 Schematic diagram of experimental setup

Table 1 Physical properties of particles used in this work

硅胶

玻璃珠

750

2500

425~880

652

0.22

0.41

Table 2 Modeling parameters in bubbling fluidized bed

Flow field	Unsteady
Pressure-velocity coupling	Phase Couple SIMPLE
Discretization	Second-order upwind
Solid pressure	Lun et al
Radial distribution	Lun et al
Granular temperature	Algebraic
Granular viscosity	Gidaspow
Granular bulk visosity	Lun et al
Frictional viscosity	Schaeffer
Frictional pressure	Based-KTGF
Angle of internal friction	30.0°
Time step size	5×10^-4 s
Mesh size	2 mm×5 mm

Fig.2 Effect of Cμ on turbulence intensity in fluidized bed

Table 3 Constants of standard k-ε turbulence model

Case	C_μ	C₁	C₂
1	0.03	1.84	1.42
2	0.05	1.64	1.62
3	0.09	1.44	1.92
4	0.12	1.2	2.2

Fig.3 Comparison of turbulence intensity in fluidized bed predicted with four groups of model constants

Fig.4 Comparison of tracer gas concentration calculated by different model constants with experimental data (Ug= 0.995 m/s, XJ= 37.5%)

Fig.5 Comparison of lateral gas velocity calculated with different model constants(Ug= 0.995 m/s, XJ= 37.5%)

Fig.6 Contour of distribution of molar ratio of CO2(Ug= 0.66 m/s, XJ= 37.5%)

Fig.7 Contour of the distribution of turbulence intensity(Ug= 0.66 m/s, XJ= 37.5%) in fluidized bed

Fig.8 Comparison of tracer gas concentration calculated by different model constants with experimental data at various gas velocities(XJ= 37.5%, H= 0.15 m)

Fig.9 Effect of gas velocity on radial gas diffusion(XJ= 37.5%)

Fig.10 Comparison of predicted tracer concentration with experimental data at different particle composition(Ug= 0.995 m/s, H=0.15 m)

Fig.11 Effect of ratio of heavy component on radial gas diffusion(Ug= 0.995 m/s)

Fig.12 Effect of ratio of heavy component on turbulence intensity(Ug= 0.995 m/s)

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