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Agglomeration of fine solid particles under the excitation of external acoustic field has potential applications in the field of ultra-low emission of combustion pollutants. It is expected that the performance of particle agglomeration can be improved by adding large sized liquid droplets. According to the dynamic process of acoustic agglomeration, including the particle motion, collision, agglomeration and rebound, a model of acoustic agglomeration for gas-liquid-solid three phase system with coexistence of liquid droplets and solid particles in gas phase is developed by using the direct simulation Monte Carlo (DSMC) method. Using this model, numerical simulations are performed to investigate the process and performance of acoustic agglomeration of fine solid particles under the effect of additional droplets. The numerical results are compared with experimental data, and the proposed model is validated. On this basis, the dynamic behaviors of acoustic agglomeration of fine particles in the case with additional droplets are explored. Furthermore, the influences of the diameter and number concentration of additional droplets on the performance of acoustic agglomeration of fine particles are examined. The results show that rapid agglomeration among the solid fine particles and additional droplets can be achieved by adding droplets into the acoustic field, yielding large sized liquid-solid mixed-phase particles. In this process, the agglomeration efficiency of fine particles increases significantly. It is also found that the diameter and number concentration of additional droplets are important factors that affect the acoustic agglomeration of fine particles. The agglomeration efficiency of fine particles rises, while the magnitude of increase tends to decrease with the droplet diameter and number concentration increasing. The research results can provide both theoretical basis for modeling the agglomeration process of complex particle systems and method guidance for achieving the ultra-low emission of fine particles from combustion sources.
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Keywords:
- fine particles /
- acoustic agglomeration /
- additional droplets /
- numerical simulation
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Google Scholar
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图 1 碰撞颗粒对类型 (a) 固体颗粒与固体颗粒; (b) 固体颗粒与液滴; (c) 固体颗粒与混合相颗粒; (d) 液滴与液滴; (e) 液滴与混合相颗粒; (f) 混合相颗粒与混合相颗粒
Figure 1. Types of collision particle pair: (a) Solid particle and solid particle; (b) solid particle and droplet; (c) solid particle and mixed-phase particle; (d) droplet and droplet; (e) droplet and mixed-phase particle; (f) mixed-phase particle and mixed-phase particle.
图 2 数值模拟流程
Figure 2. Flow chart of numerical simulation.
图 4 声凝并动力学行为 (a) 粒径分布; (b) 细颗粒凝并效率; (c) 凝并过程快照 (0 ≤ x ≤ 0.25λ, 液相放大40倍, 固相放大120倍)
Figure 4. Dynamic behavior of acoustic agglomeration: (a) Particle size distribution; (b) agglomeration efficiency of fine particles; (c) snapshots of agglomeration process (0 ≤ x ≤ 0.25λ, liquid phase at 40× magnification and solid phase at 120× magnification).
图 5 外加液滴直径对声凝并效果的影响 (a) 粒径分布; (b) 细颗粒凝并效率
Figure 5. Influence of additional droplet diameter on performance of acoustic agglomeration: (a) Particle size distribution; (b) agglomeration efficiency of fine particles.
图 6 外加液滴数目浓度对声凝并效果的影响 (a) 粒径分布; (b) 细颗粒凝并效率
Figure 6. Influence of additional droplet number concentration on performance of acoustic agglomeration: (a) Particle size distribution; (b) agglomeration efficiency of fine particles.
表 1 模型验证采用的参数
Table 1. Parameters used for model validation.
P/Pa T/K L/dB f/Hz t/s ρs/(kg·m–3) ρl/(kg·m–3) e fp 数值 101325 298.15 144 1400 4 2500 1000 0.6 0.2 
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表 2 数值模拟参数
Table 2. Parameters used in numerical simulation.
P/Pa T/K L/dB f/Hz t/s ρs/(kg·m–3) ρl/(kg·m–3) e fp 数值 101325 298.15 140 2000 4 2500 1000 0.6 0.2
DownLoad: CSV
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[1] Zhou D, Luo Z, Jiang J, Chen H, Lu M, Fang M 2016 Powder Technol. 289 52
Google Scholar
[2] Shang X P, Ng B F, Wan M P, Xiong J W, Arikrishnan S 2018 Aerosol Sci. Technol. 52 872
Google Scholar
[3] Zhang G X, Ma Z F, Shen J, Zhang K, Wang J Q, Chi Z H 2020 J. Hazard. Maters. 382 121089
Google Scholar
[4] 屈广宁, 凡凤仙, 张斯宏, 苏明旭 2020 69 064704
Google Scholar
Qu G N, Fan F X, Zhang S H, Su M X 2020 Acta Phys. Sin. 69 064704
Google Scholar
[5] Wu Z H, Fan F X, Yan J P, Chen H T, Hu X H, Su M X 2022 Chem. Eng. Sci. 249 117298
Google Scholar
[6] Liu J Z, Zhang G X, Zhou J H, Zhao W D, Cen K F 2009 Powder Technol. 193 20
Google Scholar
[7] Fan F X, Zhang M J, Peng Z B, Chen J, Su M X, Moghtaderi B, Doroodchi E 2017 Aerosol Air Qual. Res. 17 1073
Google Scholar
[8] Yan J P, Chen L Q, Li Z 2016 Fuel. 165 316
Google Scholar
[9] Zhang G X, Zhang L L, Wang J, Hu E 2017 Powder Technol. 317 181
Google Scholar
[10] Wang J, Liu J Z, Zhang G X, Zhou J H, Cen K F 2011 Powder Technol. 210 315
Google Scholar
[11] Yang N N, Fan F X, Hu X H, Su M X 2022 J. Aerosol Sci. 165 106018
Google Scholar
[12] Yan J P, Chen L Q, Lin Q 2017 Powder Technol. 315 106
Google Scholar
[13] Chen H, Wang T, Luo Z Y, Zhou D, Lu M S, He M C, Fang M X, Cen K F 2017 Aerosol Air Qual. Res. 17 857
Google Scholar
[14] Yan J P, Lin Q, Zhao S H, Chen L Q 2018 Powder Technol. 340 8
Google Scholar
[15] Zhang G X, Wang J Q, Chi Z H, Hu E 2018 Chem. Eng. Sci. 187 342
Google Scholar
[16] Shang X P, Wan M P, Ng B F, Ding S R 2020 Powder Technol. 362 111
Google Scholar
[17] Crowe C T, Schwarzkopf J D, Scommerfeld M, Tsuij Y 2012 Multiphase Flows with Droplets and Particles (2nd Ed.) (New York: CRC Press) pp119–137
[18] Higashitani K, Makino H, Matsusaka S 2020 Powder Technology Handbook (4th Ed.) (New York: CRC Press) p60
[19] Tsuji Y, Tanaka T, Yonemura S 1998 Powder Technol. 95 254
Google Scholar
[20] Zhang G X, Liu J Z, Wang J, Zhou J H, Cen K F 2012 Chin. Sci. Bull. 57 2404
Google Scholar
[21] Song L 1990 Ph. D. Dissertation (State College: Pennsylvania State University)
[22] Sgrott O L, Sommerfeld M 2019 Can. J. Chem. Eng. 97 511
[23] Ennis B J 1991 Powder Technol. 65 257
Google Scholar
[24] He Y X, Zhao H B 2016 Int. J. Multiphase Flow. 83 12
Google Scholar
[25] Kleinhans U, Wieland C, Frandsen F J, Spliethoff H 2018 Prog. Energy Combust. Sci. 68 65
Google Scholar
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