Skip to main content
SpringerLink
Log in

Computational fluid dynamics simulation of gas-liquid two phases flow in 320 m3 air-blowing mechanical flotation cell using different turbulence models

  • Published:
Journal of Central South University Aims and scope Submit manuscript

Abstract

According to the recently developed single-trough floating machine with the world’s largest volume (inflatable mechanical agitation flotation machine with volume of 320 m3) in China, the gas-fluid two-phase flow in flotation cell was simulated using computational fluid dynamics method. It is shown that hexahedral mesh scheme is more suitable for the complex structure of the flotation cell than tetrahedral mesh scheme, and a mesh quality ranging from 0.7 to 1.0 is obtained. Comparative studies of the standard k-ε, k-ω and realizable k-ε turbulence models were carried out. It is indicated that the standard k-ε turbulence model could give a result relatively close to the practice and the liquid phase flow field is well characterized. In addition, two obvious recirculation zones are formed in the mixing zones, and the pressure on the rotor and stator is well characterized. Furthermore, the simulation results using improved standard k-ε turbulence model show that surface tension coefficient of 0.072, drag model of Grace and coefficient of 4, and lift coefficient of 0.001 can be achieved. The research results suggest that gas-fluid two-phase flow in large flotation cell can be well simulated using computational fluid dynamics method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. AHMED N, JAMESON G J. The effect of bubble size on the rate of flotation of fine particles [J]. International Journal of Mineral Processing, 1985, 14(3): 195–215.

    Article  Google Scholar 

  2. GIRGIN E H, DO S, GOMEZ C O, FINCH J A. Bubble size as a function of impeller speed in a self-aeration laboratory flotation cell [J]. Minerals Engineering, 2006, 19(2): 201–203.

    Article  Google Scholar 

  3. KOH P T L, SCHWARZ M P. CFD modeling of bubble–particle collision rates and efficiencies in a flotation cell [J]. Minerals Engineering 2003, 16(11): 1055–1059.

    Article  Google Scholar 

  4. KOH P T L, SCHWARZ M P. CFD modeling of bubble–particle attachments in flotation cells [J]. Minerals Engineering, 2006, 19(6/7/8): 619–626.

    Article  Google Scholar 

  5. RIELLY C D, EVANS G M, DAVIDSON J F, CARPENTER K J. Effect of vessel scaleup on the hydrodynamics of a self-aerating concave blade impeller [J]. Chemical Engineering Science, 1992, 47(13/14): 3395–3402.

    Article  Google Scholar 

  6. KOH P T L, SCHWARZ M P. CFD model of a self-aerating flotation cell [J]. International Journal of Mineral Processing [J]. 2007, 85(1/2/3): 16–24.

    Article  Google Scholar 

  7. WEBER A, MEADOWS D, VILLANUEVA F, PALOMO R, PRADO S. Development of the world’s largest flotation machine [C]//Centenary of Flotation Symposium. Brisbane, 2005: 285–291.

    Google Scholar 

  8. YIANATOS J B, MOYS M H, CONTRERAS F, VILLANUEVA A. Froth recovery of industrial flotation cells [J]. Minerals Engineering, 2008, 21(12/13/14): 817–825.

    Article  Google Scholar 

  9. SHEN Zheng-chang. Research and design of 200 m3 air forced flotation machine [J]. Nonferrous Metals, 2009, 61(2): 100–103. (in Chinese)

    Google Scholar 

  10. SHEN Zheng-chang. Research on the design and processing characteristics of 320 m3 air-forced mechanical flotation cell [C]//Proceedings of 7th Academic Conference of Chemical, Metallurgy and Material Engineering Department. Chinese Academy of Engineering, Beijing, 2009, 10: 788–793. (in Chinese)

    Google Scholar 

  11. YIANATOS J B, BERGH L G, AGUILERA J. Flotation scale up: use of separability curves [J]. Minerals Engineering, 2003, 6(4): 347–352.

    Article  Google Scholar 

  12. ARBITER N. Development and scale-up of large flotation cells [J]. Minerals Engineering, 2000, 52(3): 28–33.

    Google Scholar 

  13. YIANATOS J B, HENRIQUEZ F H, OROZ A G. Characterization of large size flotation cells [J], Minerals Engineering, 2006, 19(6/7/8): 531–538.

    Article  Google Scholar 

  14. XIA J L, RINNE A, GRÖNSTRAND S. Effect of turbulence models on prediction of fluid flow in an Outotec flotation cell [J]. Minerals Engineering, 2009, 22(11): 880–885.

    Article  Google Scholar 

  15. CHU K W, WANG B, YU A B, VINCE A, BARNETT G D, BARNETT P J. CFD–DEM study of the effect of particle density distribution on the multiphase flow and performance of dense medium cyclone [J]. Minerals Engineering, 2009, 22(11): 893–909.

    Article  Google Scholar 

  16. JAVASUNDARA C T, YANG R Y, GUO B Y, YU A B, RUBENSTEIN J. Effect of slurry properties on particle motion in IsaMills [J]. Minerals Engineering, 2009, 22(11): 886–892.

    Article  Google Scholar 

  17. CHU K W, YU A B. Numerical simulation of complex particle–fluid flows [J]. Powder Technology, 2008, 179(3):104–114.

    Article  Google Scholar 

  18. KARAGOZ I, KAVA F. CFD investigation of the flow and heat transfer characteristics in a tangential inlet cyclone [J]. International Communications in Heat and Mass Transfer, 2007, 34(9/10): 1119–1126.

    Article  Google Scholar 

  19. RAOUFI A, SHAMS M, KANANI H. CFD analysis of flow field in square cyclones [J]. Powder Technology, 2009, 191(3): 349–357.

    Article  Google Scholar 

  20. SHUKLA K S, SHUKLA P, GHOSH P. The effect of modeling of velocity fluctuations on prediction of collection efficiency of cyclone separators [J]. Applied Mathematical Modeling, 2013, 37(8): 5774–5789.

    Article  Google Scholar 

  21. KIM D, STOESSER T, KIM J H. Modeling aspects of flow and solute transport simulations in water disinfection tanks [J]. Applied Mathematical Modeling, 2013, 37(16/17): 8039–8050.

    Article  MathSciNet  Google Scholar 

  22. WANG Shuai, LU Huang, GAO Jian-min, LU Hui-lin, LIU Guo-dong, XU Peng-fei, HE Yu-rong. CFD simulation of gas–solid flow with a cluster structure-dependent drag coefficient model in circulating fluidized beds [J]. Applied Mathematical Modeling, 2013, 37(16/17): 8179–8202.

    MathSciNet  Google Scholar 

  23. TOMINAGA Y, STATHOPOULOS T. CFD simulation of near-field pollutant dispersion in the urban environment: A review of current modeling techniques [J]. Atmospheric Environment, 2013, 79: 716–730.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Machinery Research Institute, Beijing General Research Institute of Mining & Metallurgy, Beijing, 100070, China

    Zheng-chang Shen  (沈政昌)

  2. College of Resources and Metallurgy, Guangxi University, Nanning, 530004, China

    Jian-hua Chen  (陈建华), Chen-hu Zhang  (张谌虎), Xing-jin Liao  (廖幸锦) & Yu-qiong Li  (李玉琼)

Authors
  1. Zheng-chang Shen  (沈政昌)
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jian-hua Chen  (陈建华)
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chen-hu Zhang  (张谌虎)
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xing-jin Liao  (廖幸锦)
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yu-qiong Li  (李玉琼)
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jian-hua Chen  (陈建华).

Additional information

Foundation item: Project(51074027) supported by the National Natural Science Foundation of China

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shen, Zc., Chen, Jh., Zhang, Ch. et al. Computational fluid dynamics simulation of gas-liquid two phases flow in 320 m3 air-blowing mechanical flotation cell using different turbulence models. J. Cent. South Univ. 22, 2385–2392 (2015). https://doi.org/10.1007/s11771-015-2764-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11771-015-2764-7

Key words

Search

Navigation