重质颗粒流态化研究现状与展望

doi:10.11949/0438-1157.20240783

摘要/Abstract

摘要：

流化床技术在工业中应用广泛，其中天然铀转化、直接还原炼铁、化学链燃烧等工业过程中使用的是颗粒密度在4.0 g/cm³以上的重质颗粒，而传统化工、能源行业广泛使用的则是密度较小的轻质流化床颗粒。综述了重质颗粒流态化技术在工业中的应用情况，梳理了目前重质颗粒流态化基础的研究进展。已有的实验测量和数值模拟研究均表明重质颗粒的流态化行为与低密度颗粒存在显著差异，且针对低密度颗粒的一些研究规律并不能完全适用于重质颗粒流化床。当前，对重质颗粒的流态化基础研究尚不充分，特别是在流域转变、传热传质特性、颗粒混合分级特性、反应过程强化技术等研究方面，与传统低密度颗粒流态化的基础研究相比，存在巨大的基础研究空白。最后结合相关工业过程的需要，重点讨论了近期应重点补充的重质颗粒流态化基础研究的内容。

关键词: 流化床, 天然铀转化, 核化工, 重质颗粒, 流态化, 数值模拟

Abstract:

Fluidized bed technology is widely used in industry. Industrial processes such as natural uranium conversion, direct reduction ironmaking, and chemical chain combustion use heavy particles with a particle density of more than 4.0 g/cm³. However, in traditional chemical and energy industries, lightweight fluidized bed particles with smaller density are widely used. This article reviews the application background of high-density particle fluidization technology in some industries,which particle densities are beyond 4.0 g/cm³, and explores the impact of high-density particle fluidization quality on system performance. Subsequently, the article reviews the research progress in high-density particle fluidization, highlighting that both experimental measurements and numerical simulations indicate significant differences in the fluidization behavior between high-density and low-density particles. However, existing studies on the fluidization characteristics of high-density particles remain insufficient, particularly regarding the flow characteristics and differences compared to low-density particles. Finally, combined with the needs of related industrial processes, this article focuses on the basic research content of heavy particle fluidization that should be supplemented in the near future.

Key words: fluidized bed, natural uranium conversion, nuclear chemical engineering, high-density particles, fluidization, numerical simulation

中图分类号:

TQ 051.1

李舒月, 王欢, 周少强, 毛志宏, 张永民, 王军武, 吴秀花. 重质颗粒流态化研究现状与展望[J]. 化工学报, 2025, 76(2): 466-483.

Shuyue LI, Huan WANG, Shaoqiang ZHOU, Zhihong MAO, Yongmin ZHANG, Junwu WANG, Xiuhua WU. Current status and prospects of research on fluidization characteristics of high-density particles[J]. CIESC Journal, 2025, 76(2): 466-483.

图/表 17

图1 (a)Geldart分类表征[1]；(b)修正的Geldart流态化行为分类[5-14]

Fig.1 (a) Geldart classification of fluidization behavior[1]; (b) Modified Geldart classification of fluidization behavior[5-14]

图2 (a)模拟以及经验相关式得到的Uif、Umf和Uff随颗粒密度的变化；(b)模拟结果与经验公式Umf标准误差

Fig.2 (a) Variation of simulated Uif, Umf and Uff, and Umf predicted by empirical correlations with particle density; (b) Standard error of Umf

图3 流态化技术在天然铀转化工艺中的应用[28]

Fig.3 Application of fluidization technology in the dry natural uranium conversion process[28]

图4 流化床-化学气相沉积技术[30]

Fig.4 Fluidized bed-chemical vapor deposition(FB-CVD)[30]

图5 高温费托合成主要反应器形式[31]

Fig.5 Main reactor types for high-temperature Fischer-Rropsch synthesis[31]

图6 化学链燃烧技术系统示意图[36-37]

Fig.6 Schematic diagram of the chemical looping combustion system[36-37]

图7 Midrex直接还原工艺流化床反应器示意图[43-44]

Fig.7 Schematic diagram of the fluidized bed reactor in the Midrex direct reduction process[43-44]

图8 AKAFLOW流化床分选装置示意图[47]

Fig.8 Schematic diagram of the AKAFLOW fluidized bed separator[47]

图9 ZrO2颗粒在60°锥形床中U/Ums分别为1.8、2.1、2.4的喷动行为实验[51-53]

Fig.9 Experimental study of spouting behavior of ZrO₂ particles in a 60 ° conical bed at U/Ums ratios of 1.8, 2.1, and 2.4[51-53]

图10 (a)实验测量的最小喷动速度与文献中不同经验关联式预测值的比较；(b)Goldshan等[54]提出的最小喷动速度关联式与实验数据的比较

Fig.10 (a) Comparison of experimental minimum spouting velocity with predicted values from different empirical correlations in the literature; (b) Comparison of experimental data with the minimum spouting velocity correlation proposed by Goldshan et al.[54]

图11 Dogan实验得到气体扩散系数与San José基于低密度颗粒推导的气体扩散系数预测值的对比[55]

Fig.11 Comparison of gas diffusion coefficients obtained from Dogan's experiments with predicted values derived by San José for low-density particles[55]

图12 氧化铪床层中的气孔和气体通道[59]

Fig.12 Pores and gas channels in a hafnia (HfO₂) bed[59]

图13 不同密度颗粒与气泡表面的相互作用[65]

Fig.13 Interaction between particles of different densities and the surface of a bubble[65]

图14 四种不同密度颗粒的实验结果：(a)颗粒流型；(b)与模拟结果相比进气气速与床层压降随颗粒密度的变化关系[92]

Fig.14 Experimental results for four different density particles: (a) Particle flow patterns; (b) Relationship between inlet gas velocity and bed pressure drop as a function of particle density compared with simulation results[92]

图15 (a)低密度FCC颗粒与重质UO2的充分流动状态对比；(b)颗粒密度和气速对床层膨胀率的影响[21-22]

Fig.15 (a) Comparison of the fully fluidized states between low-density FCC particles and high-density UO2 particles; (b) Effect of particle density and gas velocity on bed expansion ratio[21-22]

表1 重质颗粒流态化研究总结

Table 1 The summary of research on fluidization of high-density particles

作者（年份）	颗粒性质	主要结论
Saxena et al.^[85-87](1999)	Fe: $d_{p} =$ 1416 μm，ρ=7.831 g/cm³ Cu: $d_{p} =$ 935 μm，ρ=8.92 g/cm³	施加外磁场可强化重质颗粒的流动性
Zhou et al.^[51-53](2005,2008,2012)	ZrO₂: $d_{p} =$ 300、400、500、650 μm；ρ=6.0 g/cm³	传统的经验公式无法准确预测ZrO₂颗粒的最小喷动速度。本工作基于ZrO₂实验数据建立了新的最小喷动速度关联式，并在关联式中包含了锥角、静床高度和颗粒粒径的影响
Cooper et al.^[79](2005) Leaper^[81](2015)	焦炭: $d_{p} =$ 355 μm，ρ=1.8 g/cm³ 金红石（Ti）: $d_{p} =$ 69.5 μm，ρ=4.8 g/cm³ 玻璃球: $d_{p} =$ 124 μm，ρ=2.5 g/cm³ WC: $d_{p} =$ 179 μm，ρ=4.5 g/cm³	与颗粒粒度差异相比，密度差异更能促使多组分颗粒在流化过程中分层
Luckos et al.^[68-69](2005,2007)	硅石（SiO₂）: $d_{p} =$ 190 μm，ρ=2.66 g/cm³ 金红石（TiO₂）: $d_{p} =$ 115 μm，ρ=4.085 g/cm³ 钛铁矿: $d_{p} =$ 80 μm，ρ=4.71 g/cm³ 矿渣: $d_{p} =$ 155 μm，ρ=4 g/cm³	Ergun方程分别为钛铁矿和矿渣颗粒拟合了最小流化速度的相关性。这两个相关性都倾向于低估颗粒的最小流化速度
Pannala et al.^[94](2007) Setarehshenas et al.^[95](2016)	ZrO₂: $d_{p} =$ 500 μm，ρ=6.0 g/cm³	重质颗粒在喷动床床层中存在独有的不连贯喷动现象
Formisani et al.^[82-83](2008)	玻璃球: $d_{p} =$ 223、661 μm，ρ=2.48 g/cm³ 钢丸: $d_{p} =$ 243 μm，ρ=7.6 g/cm³ 陶瓷球: $d_{p} =$ 701 μm，ρ=3.76 g/cm³	密度不同的二元混合物的流化速度区间宽度与组分间的密度差距有关，同时还与初始体积分数和初始混合状态有关
de Vos et al.^[32](2009)	雾化硅铁: $d_{p} =$ 38 μm，ρ=6.7 g/cm³ 研磨硅铁: $d_{p} =$ 50 μm，ρ=6.6 g/cm³	A类颗粒团聚临界粒径的经典概念不能充分描述重质的A类颗粒的夹带行为
Chao et al.^[99](2012)	钢珠: $d_{p} =$ 243 μm，ρ=7.6 g/cm³ 玻璃珠: $d_{p} =$ 223 μm，ρ=2.46 g/cm³	密度主导的二元颗粒离析行为和颗粒的速度分布都依赖于表观气体速度
Alekhine et al.^[75](2012)	重质青铜: $d_{p} =$ 43.1 μm，ρ=8.79 g/cm³	观察到重质青铜颗粒在循环流化床中的“噎塞”极限
Rodrigues et al.^[60-61](2013,2011)	W颗粒: $d_{p} =$ 75 μm，ρ=19.3 g/cm³	重质的钨颗粒完全流化的床层膨胀率只有10%
Saayman et al.^[65](2013)	FeSi: $d_{p} =$ 41、59 μm，ρ=6.69 g/cm³	向FeSi床层中添加细粉颗粒反而降低了鼓泡状态下密相床层的空隙率，使得反应器性能下降，这与以往低密度颗粒床层中的研究规律相反
刘坤等^[59](2015)	HfO₂: $d_{p} =$ 74~100 μm，ρ=9.68 g/cm³	氧化铪床层开始流化时并没有像低密度颗粒床层一样出现均匀膨胀，而是局部首先出现气流通道
Liu et al.^[92-93](2015,2024)	ZrO₂: $d_{p} =$ 2000 μm，ρ=5.6 g/cm³ Fe: $d_{p} =$ 2000 μm，ρ=7.8 g/cm³ UO₂: $d_{p} =$ 2000 μm，ρ=10.8 g/cm³ 玻璃珠: $d_{p} =$ 2000 μm，ρ=2.6 g/cm³	颗粒的密度与所需流化气速及床层压力之间存在着明显的正相关关系。当颗粒密度增加时，颗粒稳定喷动气速范围随密度增加而扩大，同时重质颗粒的不连贯喷动存在低密度颗粒不易存在的双频现象，说明重质颗粒在喷动床中存在独特的喷动现象
Vanni et al.^[62-64](2015)	W颗粒: $d_{p} =$ 70、75 μm，ρ=19.3 g/cm³	重质颗粒的临界床径比常见的Geldart A类和B类颗粒的临界直径要大
Bournival et al.^[66](2016)	PMMA: $d_{p} =$ 40 μm，ρ=1.2 g/cm³ 玻璃珠: $d_{p} =$ 40 μm，ρ=2.5 g/cm³ TiO₂: $d_{p} =$ 40 μm，ρ=3.6 g/cm³	重质颗粒在与气泡接触时因具有较大的惯性，容易从气泡表面掉落，而密度小的颗粒则更容易附着在气泡表面，阻碍气泡的凝聚
He et al.^[70](2017) Zou et al.^[71](2024)	精铁矿石: $d_{p} =$ 86.9 μm，ρ=4.9 g/cm³	锥形流化床可强化重质铁矿石颗粒的流化
Goldshan et al.^[54](2018)	ZrO₂: $d_{p} =$ 100 μm，ρ=6.0 g/cm³ 增韧Al₂O₃: $d_{p} =$ 1000、2000、2400 μm，ρ=3.7 g/cm³ 玻璃珠: $d_{p} =$ 1000、2000 μm，ρ=2.46 g/cm³	随着颗粒密度的增加，最大压降、稳定喷动压降以及最小喷动速度都会增加。随着密度的增加，功率谱密度函数显示出略低的振幅。以上现象认为是由于重质颗粒惯性力的增加造成的
Kraft et al.^[102](2018)	青铜: $d_{p} =$ 118 μm，ρ=8.73 g/cm³	研究的曳力模型不能很好地预测重质床料循环速率以及系统的压力分布
Shao et al.^[96-97](2019,2020)	煤: $d_{p} =$ 2440 μm，ρ=1.3 g/cm³ 砂: $d_{p} =$ 570、730、890、1950 μm，ρ=2.59 g/cm³ Al₂O₃: $d_{p} =$ 2440 μm，ρ=3.97 g/cm³ NiO: $d_{p} =$ 570、730、890、1950 μm，ρ=5.242 g/cm³ Fe₂O₃: $d_{p} =$ 1880 μm，ρ=6.67 g/cm³	随着颗粒密度的减小，最小流化速度降低
McIntyre et al.^[67](2020)	钛铁矿石: $d_{p} =$ 95、107、109、236、321 μm，ρ=4.7 g/cm³	通过实验测定的最小流化速度与常用的经验关联式存在较大误差
Tsurμmaki et al.^[98](2022)	玻璃球: $d_{p} =$ 300、600 μm，ρ=2.5 g/cm³ 铁-锰氧化物: $d_{p} =$ 300、600 μm，ρ=5.08 g/cm³ 尖晶石: $d_{p} =$ 300、600 μm，ρ=5.5 g/cm³	低密度材料的流化速度快于重质材料
Guo et al.^[55](2023) Dogan et al.^[56](2023)	ZrO₂: $d_{p} =$ 300、400、500、650 μm，ρ=6.0g/cm³ 锆钙化Al₂O₃: $d_{p} =$ 500 μm，ρ=3.2 g/cm³ Cu: $d_{p} =$ 500 μm，ρ=8.92 g/cm³	重质颗粒要求更高的操作气体速度；重质颗粒与低密度颗粒在喷动床中存在不同的轴向气体混合行为
Hessels et al.^[74](2023)	氧化铁: $d_{p} =$ 56.63 μm，ρ=4.6 g/cm³	氢气还原实验中，得到远低于期望的1%的转化率
Mollick et al.^[58](2024)	玻璃球: $d_{p} =$ 2440 μm，ρ=2.5 g/cm³ ZrO₂: $d_{p} =$ 570、730、890、1950 μm，ρ= 6.2 g/cm³ WC: $d_{p} =$ 1880 μm，ρ=16 g/cm³	不同密度的颗粒最小喷动速度与床高的关系呈现出不同的指数关系，说明轻质颗粒与重质颗粒的喷动行为也遵循不同的规律

表1 重质颗粒流态化研究总结

Table 1 The summary of research on fluidization of high-density particles

作者（年份）	颗粒性质	主要结论
Saxena et al.^[85-87](1999)	Fe: $d_{p} =$ 1416 μm，ρ=7.831 g/cm³ Cu: $d_{p} =$ 935 μm，ρ=8.92 g/cm³	施加外磁场可强化重质颗粒的流动性
Zhou et al.^[51-53](2005,2008,2012)	ZrO₂: $d_{p} =$ 300、400、500、650 μm；ρ=6.0 g/cm³	传统的经验公式无法准确预测ZrO₂颗粒的最小喷动速度。本工作基于ZrO₂实验数据建立了新的最小喷动速度关联式，并在关联式中包含了锥角、静床高度和颗粒粒径的影响
Cooper et al.^[79](2005) Leaper^[81](2015)	焦炭: $d_{p} =$ 355 μm，ρ=1.8 g/cm³ 金红石（Ti）: $d_{p} =$ 69.5 μm，ρ=4.8 g/cm³ 玻璃球: $d_{p} =$ 124 μm，ρ=2.5 g/cm³ WC: $d_{p} =$ 179 μm，ρ=4.5 g/cm³	与颗粒粒度差异相比，密度差异更能促使多组分颗粒在流化过程中分层
Luckos et al.^[68-69](2005,2007)	硅石（SiO₂）: $d_{p} =$ 190 μm，ρ=2.66 g/cm³ 金红石（TiO₂）: $d_{p} =$ 115 μm，ρ=4.085 g/cm³ 钛铁矿: $d_{p} =$ 80 μm，ρ=4.71 g/cm³ 矿渣: $d_{p} =$ 155 μm，ρ=4 g/cm³	Ergun方程分别为钛铁矿和矿渣颗粒拟合了最小流化速度的相关性。这两个相关性都倾向于低估颗粒的最小流化速度
Pannala et al.^[94](2007) Setarehshenas et al.^[95](2016)	ZrO₂: $d_{p} =$ 500 μm，ρ=6.0 g/cm³	重质颗粒在喷动床床层中存在独有的不连贯喷动现象
Formisani et al.^[82-83](2008)	玻璃球: $d_{p} =$ 223、661 μm，ρ=2.48 g/cm³ 钢丸: $d_{p} =$ 243 μm，ρ=7.6 g/cm³ 陶瓷球: $d_{p} =$ 701 μm，ρ=3.76 g/cm³	密度不同的二元混合物的流化速度区间宽度与组分间的密度差距有关，同时还与初始体积分数和初始混合状态有关
de Vos et al.^[32](2009)	雾化硅铁: $d_{p} =$ 38 μm，ρ=6.7 g/cm³ 研磨硅铁: $d_{p} =$ 50 μm，ρ=6.6 g/cm³	A类颗粒团聚临界粒径的经典概念不能充分描述重质的A类颗粒的夹带行为
Chao et al.^[99](2012)	钢珠: $d_{p} =$ 243 μm，ρ=7.6 g/cm³ 玻璃珠: $d_{p} =$ 223 μm，ρ=2.46 g/cm³	密度主导的二元颗粒离析行为和颗粒的速度分布都依赖于表观气体速度
Alekhine et al.^[75](2012)	重质青铜: $d_{p} =$ 43.1 μm，ρ=8.79 g/cm³	观察到重质青铜颗粒在循环流化床中的“噎塞”极限
Rodrigues et al.^[60-61](2013,2011)	W颗粒: $d_{p} =$ 75 μm，ρ=19.3 g/cm³	重质的钨颗粒完全流化的床层膨胀率只有10%
Saayman et al.^[65](2013)	FeSi: $d_{p} =$ 41、59 μm，ρ=6.69 g/cm³	向FeSi床层中添加细粉颗粒反而降低了鼓泡状态下密相床层的空隙率，使得反应器性能下降，这与以往低密度颗粒床层中的研究规律相反
刘坤等^[59](2015)	HfO₂: $d_{p} =$ 74~100 μm，ρ=9.68 g/cm³	氧化铪床层开始流化时并没有像低密度颗粒床层一样出现均匀膨胀，而是局部首先出现气流通道
Liu et al.^[92-93](2015,2024)	ZrO₂: $d_{p} =$ 2000 μm，ρ=5.6 g/cm³ Fe: $d_{p} =$ 2000 μm，ρ=7.8 g/cm³ UO₂: $d_{p} =$ 2000 μm，ρ=10.8 g/cm³ 玻璃珠: $d_{p} =$ 2000 μm，ρ=2.6 g/cm³	颗粒的密度与所需流化气速及床层压力之间存在着明显的正相关关系。当颗粒密度增加时，颗粒稳定喷动气速范围随密度增加而扩大，同时重质颗粒的不连贯喷动存在低密度颗粒不易存在的双频现象，说明重质颗粒在喷动床中存在独特的喷动现象
Vanni et al.^[62-64](2015)	W颗粒: $d_{p} =$ 70、75 μm，ρ=19.3 g/cm³	重质颗粒的临界床径比常见的Geldart A类和B类颗粒的临界直径要大
Bournival et al.^[66](2016)	PMMA: $d_{p} =$ 40 μm，ρ=1.2 g/cm³ 玻璃珠: $d_{p} =$ 40 μm，ρ=2.5 g/cm³ TiO₂: $d_{p} =$ 40 μm，ρ=3.6 g/cm³	重质颗粒在与气泡接触时因具有较大的惯性，容易从气泡表面掉落，而密度小的颗粒则更容易附着在气泡表面，阻碍气泡的凝聚
He et al.^[70](2017) Zou et al.^[71](2024)	精铁矿石: $d_{p} =$ 86.9 μm，ρ=4.9 g/cm³	锥形流化床可强化重质铁矿石颗粒的流化
Goldshan et al.^[54](2018)	ZrO₂: $d_{p} =$ 100 μm，ρ=6.0 g/cm³ 增韧Al₂O₃: $d_{p} =$ 1000、2000、2400 μm，ρ=3.7 g/cm³ 玻璃珠: $d_{p} =$ 1000、2000 μm，ρ=2.46 g/cm³	随着颗粒密度的增加，最大压降、稳定喷动压降以及最小喷动速度都会增加。随着密度的增加，功率谱密度函数显示出略低的振幅。以上现象认为是由于重质颗粒惯性力的增加造成的
Kraft et al.^[102](2018)	青铜: $d_{p} =$ 118 μm，ρ=8.73 g/cm³	研究的曳力模型不能很好地预测重质床料循环速率以及系统的压力分布
Shao et al.^[96-97](2019,2020)	煤: $d_{p} =$ 2440 μm，ρ=1.3 g/cm³ 砂: $d_{p} =$ 570、730、890、1950 μm，ρ=2.59 g/cm³ Al₂O₃: $d_{p} =$ 2440 μm，ρ=3.97 g/cm³ NiO: $d_{p} =$ 570、730、890、1950 μm，ρ=5.242 g/cm³ Fe₂O₃: $d_{p} =$ 1880 μm，ρ=6.67 g/cm³	随着颗粒密度的减小，最小流化速度降低
McIntyre et al.^[67](2020)	钛铁矿石: $d_{p} =$ 95、107、109、236、321 μm，ρ=4.7 g/cm³	通过实验测定的最小流化速度与常用的经验关联式存在较大误差
Tsurμmaki et al.^[98](2022)	玻璃球: $d_{p} =$ 300、600 μm，ρ=2.5 g/cm³ 铁-锰氧化物: $d_{p} =$ 300、600 μm，ρ=5.08 g/cm³ 尖晶石: $d_{p} =$ 300、600 μm，ρ=5.5 g/cm³	低密度材料的流化速度快于重质材料
Guo et al.^[55](2023) Dogan et al.^[56](2023)	ZrO₂: $d_{p} =$ 300、400、500、650 μm，ρ=6.0g/cm³ 锆钙化Al₂O₃: $d_{p} =$ 500 μm，ρ=3.2 g/cm³ Cu: $d_{p} =$ 500 μm，ρ=8.92 g/cm³	重质颗粒要求更高的操作气体速度；重质颗粒与低密度颗粒在喷动床中存在不同的轴向气体混合行为
Hessels et al.^[74](2023)	氧化铁: $d_{p} =$ 56.63 μm，ρ=4.6 g/cm³	氢气还原实验中，得到远低于期望的1%的转化率
Mollick et al.^[58](2024)	玻璃球: $d_{p} =$ 2440 μm，ρ=2.5 g/cm³ ZrO₂: $d_{p} =$ 570、730、890、1950 μm，ρ= 6.2 g/cm³ WC: $d_{p} =$ 1880 μm，ρ=16 g/cm³	不同密度的颗粒最小喷动速度与床高的关系呈现出不同的指数关系，说明轻质颗粒与重质颗粒的喷动行为也遵循不同的规律

图16 本文讨论的重质颗粒性质的分布范围

Fig.16 Distribution range of particle properties in the works cited in this paper

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