Heat and Mass Transfer

, Volume 55, Issue 8, pp 2341–2354 | Cite as

Experimental and numerical study of Stairmand cyclone separators: a comparison of the results of small-scale and large-scale cyclones

  • Halil I. Erol
  • Oguz TurgutEmail author
  • Rahmi Unal


Gas cyclone separators are employed to separate particles from gas. In this study, the effect of the vortex finder diameter, inlet velocity and particle size on the flow field and the performance of a large industrial Stairmand cyclone has been studied both experimentally and numerically. The vortex finder diameters used are 0.40, 0.45, 0.50 and 0.55 times the cyclone diameter. Cyclones with body diameters of 700 mm and 254 mm are used. Cyclone inlet velocity is changed from 11.5 m∙s−1 to 19 m∙s−1. Particle size is varied between 1 and 13 μm. Whether the correlations obtained for small-scale cyclones are valid for large-scale cyclones has been investigated. The three-dimensional numerical study is carried out by using ANSYS Fluent 17.0 software package for incompressible turbulent flow condition. Reynolds stress model is chosen as the turbulence model. Sawdust ash is used as particles. The results of numerical study are compared with the results of experimental study and literature. Results are found to be consistent with each other. It is seen that cyclone collection efficiency and pressure drop increase when both vortex finder diameter decreases and inlet velocity increases, but 50% cut-off diameter decreases. Results show that the correlations obtained for small sampling cyclones may not be appropriate for large-scale cyclones.


Cyclone separators Reynolds stress model CFD Experimental study Vortex finder 



cyclone inlet height, m.


cyclone inlet width, m.


cone-tip diameter, m.


length of inlet section, m.


the drag coefficient, −.


cyclone body diameter, m.


core diameter of cyclone, m.


vortex finder diameter, m.


hydraulic diameter, m.


particle diameter, m.


particle cut-off diameter, m.


gravitational acceleration in i-direction, m∙s−2.


height of cyclone cylinder part, m.


vortex finder length outside the cyclone, m.


dimensionless parameter, −.


cyclone height, m.


turbulent intensity level, −.


fluctuating kinetic energy, m2∙s−2.


pressure drop, Pa.

\( \overline{\mathrm{P}} \)

mean pressure, Pa.


fluctuating kinetic energy production, m2∙s−3.


turbulence production term, m2∙s−3.


volume flow rate, m3∙s−1.


radius of cyclone, m.


core diameter, m.


Reynolds number, −.


particle relative Reynolds number, −.


Reynolds stress tensor, m2∙s−2.


extension vortex finder inside the cyclone, m.


time, s.


average velocity, m∙s−1.

\( \overline{{\mathrm{u}}_{\mathrm{i}}} \)

mean velocity in the i-direction, m∙s−1.


i-component fluid velocity, m∙s−1.


inlet velocity, m∙s−1.


ith fluctuating velocity component, m∙s−1.


particle velocity in i-direction, m∙s−1.


maximum tangential velocity, m∙s−1.


coordinate system, m.

Greek symbols


Kronecker delta, −.


turbulence dissipation rate, m2∙s−3.


dynamic viscosity, kg∙m−1·s−1.


gas density, kg∙m−3.


particle density, kg∙m−3.


kinematic viscosity, m2∙s−1.


turbulent (eddy) kinematic viscosity, m2∙s−1.



Analyzing of particle size using Malvern Mastersizer E instrument was carried out by third author. The remaining parts of the present study were performed by first and second authors.

Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.


  1. 1.
    Lim KS, Kwon SB, Lee KW (2003) Characteristics of the collection efficiency for a double inlet cyclone with clean air. J Aerosol Sci 34:1085–1095CrossRefGoogle Scholar
  2. 2.
    Lim KS, Kim HS, Lee KW (2004) Characteristics of the collection efficiency for a cyclone with different vortex finder shapes. J Aerosol Sci 35:743–754CrossRefGoogle Scholar
  3. 3.
    Wang LK, Pereira NC, Hung YT (2004) Air pollution control engineering. Handbook of environmental engineering. Springer Science+Business Media, New YorkGoogle Scholar
  4. 4.
    Elsayed K, Lacor C (2010) The effect of vortex finder diameter on cyclone separator performance and flow field. In: V European conference on computational fluid dynamics, pp 1–14Google Scholar
  5. 5.
    Elsayed K (2015) Design of a novel gas cyclone vortex finder using the adjoint method. Sep Purif Technol 142:274–286CrossRefGoogle Scholar
  6. 6.
    Elsayed K (2015) Optimization of the cyclone separator geometry for minimum pressure drop using co-kriging. Powder Technol 269:409–424CrossRefGoogle Scholar
  7. 7.
    Zhu Y, Lee KW (1999) Experimental study on small cyclones operating at high flowrates. J Aerosol Sci 30:1303–1315CrossRefGoogle Scholar
  8. 8.
    Kim JC, Lee KW (1990) Experimental study of particle collection by small cyclones. Aerosol Sci Technol 12:1003–1015CrossRefGoogle Scholar
  9. 9.
    Elsayed K, Lacor C (2013) The effect of cyclone vortex finder dimensions on the flow pattern and performance using LES. Comput Fluids 71:224–239MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Saltzman BE, Hochstrasser JM (1983) Design and performance of miniature cyclones for respirable aerosol sampling. Environ Sci Technol 17:418–424CrossRefGoogle Scholar
  11. 11.
    Iozia DL, Leith D (1989) Effect of cyclone dimensions on gas flow pattern and collection efficiency. Aerosol Sci Technol 10:491–500CrossRefGoogle Scholar
  12. 12.
    Moore ME, McFarland AR (1993) Performance modeling of single-inlet aerosol sampling cyclones. Environ Sci Technol 27:1842–1848CrossRefGoogle Scholar
  13. 13.
    Halasz MRT, Massarani G (2000) Performance analysis and design of small diameter cyclones. Brazilian J Chem Eng 17:451–458CrossRefGoogle Scholar
  14. 14.
    Hoekstra AJ (2000) Gas flow filed and collection efficiency of cyclone separators. PhD Thesis Technical University DelftGoogle Scholar
  15. 15.
    Raoufi A, Shams M, Farzaneh M, Ebrahimi R (2008) Numerical simulation and optimization of fluid flow in cyclone vortex finder. Chem Eng Process 47:128–137CrossRefGoogle Scholar
  16. 16.
    Swamee PK, Aggarwal N, Bhobhiya K (2009) Optimum design of cyclone separator. AICHE J 55:2279–2283CrossRefGoogle Scholar
  17. 17.
    Elsayed K, Lacor C (2010) Optimization of the cyclone separator geometry for minimum pressure drop using mathematical models and CFD simulations. Chem Engineer Sci 65:6048–6058CrossRefGoogle Scholar
  18. 18.
    Ficici F, Ari V, Kapsiz M (2010) The effects of vortex finder on the pressure drop in cyclone separators. Int J Phys Sci 5:804–813Google Scholar
  19. 19.
    Khalkhali A, Safikhani H (2012) Pareto based multi-objective optimization of a cyclone vortex finder using CFD, GMDH type neural networks and genetic algorithms. Eng Optimiz 44:105–118CrossRefGoogle Scholar
  20. 20.
    El-Batsh HM (2013) Improving cyclone performance by proper selection of the exit pipe. Appl Math Model 37:5286–5303CrossRefzbMATHGoogle Scholar
  21. 21.
    Demir S (2014) A practical model for estimating pressure drop in cyclone separators: an experimental study. Powder Technol 268:329–338CrossRefGoogle Scholar
  22. 22.
    Brar LS, Sharma RP, Dwivedi R (2015) Effect of vortex finder diameter on flow field and collection efficiency of cyclone separators. Particul Sci Technol 33:34–40CrossRefGoogle Scholar
  23. 23.
    Khazaee I (2017) Numerical investigation of the effect of number and shape of inlet of cyclone and particle size on particle separation. Heat Mass Transf 53:2009–2016CrossRefGoogle Scholar
  24. 24.
    Stairmand CJ (1951) The design and performance of cyclone separators. Ind Eng Chem 29:356–383Google Scholar
  25. 25.
    Holman JP (2012) Experimental methods for engineers. McGraw-Hill, New YorkGoogle Scholar
  26. 26.
    Slack MD, Prasad RO, Bakker A, Boysan F (2000) Advances in cyclone modeling using unstructured grids. Chem Eng Res Des 78:1098–1104CrossRefGoogle Scholar
  27. 27.
    Xiang RB, Lee KW (2005) Numerical simulation of flow patterns in cyclones of different cone diameters. Part Part Syst Charact 22:212–218CrossRefGoogle Scholar
  28. 28.
    Chuah TG, Gimbun J, Choong TSY (2006) A CFD study of the effect of cone dimensions on sampling aerocyclones performance and hydrodynamics. Powder Technol 162:126–132CrossRefGoogle Scholar
  29. 29.
    Kaya F, Karagöz I (2008) Performance analysis of numerical schemes in highly swirling turbulent flows in cyclones. Curr Sci 94:1273–1278Google Scholar
  30. 30.
    Elsayed K, Lacor C (2011) The effect of cyclone inlet dimensions on the flow pattern and performance. Appl Math Model 35:1952–1968CrossRefGoogle Scholar
  31. 31.
    ANSYS Fluent 17.0 (2016) Theory Guide. ANSYS IncGoogle Scholar
  32. 32.
    Stendal EAR (2013) Multiphase flows in Cyclone Separators. MSc Thesis Chalmers University of TechnologyGoogle Scholar
  33. 33.
    ANSYS Fluent 17.0 (2016) Tutorial Guide. ANSYS IncGoogle Scholar
  34. 34.
    Fathizadeh N, Mohebbi A, Soltaninejad S, Iranmanesh M (2015) Design and simulation of high pressure cyclones for a gas city gate station using semi-empirical models, genetic algorithm and computational fluid dynamics. J Nat Gas Sci Eng 26:313–329CrossRefGoogle Scholar
  35. 35.
    Elsayed K, Lacor L (2013) CFD modeling and multi-objective optimization of cyclone geometry using desirability function, artificial neural networks and genetic algorithms. Appl Math Model 37:5680–5704CrossRefGoogle Scholar
  36. 36.
    Morsi AS, Alexander AJ (1972) An investigation of particle trajectories in two-phase flow systems. J Fluid Mech 55:193–208Google Scholar
  37. 37.
    Boysan F, Ewan BCR, Swithenbank J, Ayers WH (1983) Experimental and theoretical studies of cyclone separator aerodynamics. Int Chem Eng Symposium Series 99:305–320Google Scholar
  38. 38.
    Ramachandran G, Leith D, Dirgo J, Feldman H (1991) Cyclone optimization based on a new empirical model for pressure drop. Aerosol Sci Technol 15:135–148CrossRefGoogle Scholar
  39. 39.
    Demir S (2014) A practical model for estimating pressure drop in cyclone separators: an experimental study. Powder Technol 268:329–338CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Engineering Faculty, Department of Mechanical Engineering & Clean Energy Research and Application Center (TEMENAR)Gazi UniversityAnkaraTurkey

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