Computational fluid dynamics simulation of methanol to olefins in stage circulating fluidized bed riser: Effect of reactor stage parameters on product yields


The risers of a conventional fluidized bed reactor and a stage fluidized bed reactor for the convention of methanol to olefins (MTO) were simulated using computational fluid dynamics. The reaction rates of the MTO reaction were validated to successfully match with the literature experiment. Then, the reactor stage parameters were examined by using the 2k design of the experiment method, including the number of reactor stages, the thickness of the reactor stage, and the wall temperature of the reactor stage. The stage circulating fluidized bed riser decreased the yield of ethene but increased the yield of propene and light olefins. From the obtained solid volume fraction profile, the stage circulating fluidized bed riser could reduce the back-mixing and increase the system turbulence, which promotes the light olefins of the MTO reaction yield. The wall temperature of the reactor stage did not significantly affect the chemical reaction in the circulating fluidized bed riser.

This is a preview of subscription content, access via your institution.



number of reactor stage [-]


thickness of reactor stage [-]


wall temperature of reactor stage [-]

C :

initial coke content of catalyst [%mol]

CA0 :

initial concentration of methanol [mol/L]

C D0 :

drag coefficient [-]


diffusivity [m2/s]

dp :

solid particle diameter [m]


restitution coefficient [-]


gravity force [m/s2]

g0 :

radial distribution function [-]


enthalpy [J/kg]


unit tensor [-]


diffusive flux [kg/m s]

ki :

rate constant of reaction [mol/(gcatalyst Pa s)]


pressure [Pa]

PA :

initial partial pressure of methanol gas [Pa]


gas constant [J/mol K]


Reynolds number [-]

Ri :

reaction rate [kmol/m3 s]


time [s]


temperature [K]


velocity [m/s]

X oxygenate :

percent conversion of oxygen compound [%]


mass fraction [-]

Y oxygenate :

mole ratio of oxygen compound [-]

α s :

volume ratio of catalyst [-]

β :

interphase exchange or drag coefficient model [kg/m3 s]

ε :

volume fraction [-]

ε s, max :

solid volume fraction at maximum packing [-]

γ s :

collisional dissipation of solid particle fluctuating energy [J/m s3]

κ s :

conductivity of solid particle fluctuating energy [kg/m s]

μ :

viscosity [kg/m s]

θ :

granular temperature [m2/s2]

ρ :

density [kg/m3]

ξ :

bulk viscosity [kg/m s]


catalyst deactivation factors [-]


drag correlation function [-]


gas phase






solid phase


  1. 1.

    B. Chalermsinsuwan, T. Samruamphianskun and P. Piumsomboon, Chem. Eng. Res. Des., 92, 2479 (2014).

    CAS  Google Scholar 

  2. 2.

    Y. Shi, X. Du, L. Yang, Y. Sun and Y. Yang, Int. J. Hydrogen Energy, 38, 13974 (2013).

    CAS  Google Scholar 

  3. 3.

    F. Ren, H. Li, D. Wang and J. Wang, Prepr. Pap.-Am. Chem. Soc., Div. Fuel Chem., 48, 921 (2003).

    CAS  Google Scholar 

  4. 4.

    L. Zhu, N. Xie, P. Jiang, L. Li and H. Chen, Chem. Eng. Res. Des., 114, 247 (2016).

    CAS  Google Scholar 

  5. 5.

    Z. Sun, W. Xiang and S. Chen, Int. J. Hydrogen Energy, 41, 17323 (2016).

    CAS  Google Scholar 

  6. 6.

    S. Ge, Z. Lou, Y. Yang, Z. Huang, J. Sun, J. Wang and Y. Yang, AIChE J., 66, 1 (2020).

    Google Scholar 

  7. 7.

    P. Tian, Y. Wei, M. Ye and Z. Liu, ACS Catal., 5, 1922 (2015).

    CAS  Google Scholar 

  8. 8.

    M. Stöcker, Micropor. Mesopor. Mater., 29, 3 (1999).

    Google Scholar 

  9. 9.

    T. Álvaro-Muñoz, C. Márquez-Álvarez and E. Sastre, Appl. Catal. A: Gen., 472, 72 (2014).

    Google Scholar 

  10. 10.

    F. Yaripour, Z. Shariatinia, S. Sahebdelfar and A. Irandoukht, Micropor. Mesopor. Mater., 203, 41 (2015).

    CAS  Google Scholar 

  11. 11.

    F. L. Bleken, S. Chavan, U. Olsbye, M. Boltz, F. Ocampo and B. Louis, Appl. Catal. A: Gen., 447–448, 178 (2012).

    Google Scholar 

  12. 12.

    S. Ivanova, C. Lebrun, E. Vanhaecke, C. Pham-Huu and B. Louis, J. Catal., 265, 1 (2009).

    CAS  Google Scholar 

  13. 13.

    Q. Wang, L. Wang, H. Wang, Z. Li, H. Wu, G. Li, X. Zhang and S. Zhang, Asia-Pacific J. Chem. Eng., 6, 596 (2011).

    CAS  Google Scholar 

  14. 14.

    Q. Yu, X. Meng, J. Liu, C. Li and Q. Cui, Micropor. Mesopor. Mater., 181, 192 (2013).

    CAS  Google Scholar 

  15. 15.

    S. M. Sadrameli, Fuel, 140, 102 (2015).

    CAS  Google Scholar 

  16. 16.

    S. M. Sadrameli, Fuel, 173, 285 (2016).

    CAS  Google Scholar 

  17. 17.

    O. Awayssa, N. Al-Yassir, A. Aitani and S. Al-Khattaf, Appl. Catal. A: Gen., 477, 172 (2014).

    CAS  Google Scholar 

  18. 18.

    J. Freiding and B. Kraushaar-Czarnetzki, Appl. Catal. A: Gen., 391, 254 (2011).

    CAS  Google Scholar 

  19. 19.

    A. Izadbakhsh and F. Khorasheh, Chem. Eng. Sci., 66, 6199 (2011).

    CAS  Google Scholar 

  20. 20.

    X. Huang, H. Li, H. Li and W.-D. Xiao, Fuel Process. Technol., 150, 104 (2016).

    CAS  Google Scholar 

  21. 21.

    Y.-Q. Zhuang, X.-M. Chen, Z.-H. Luo and J. Xiao, Comput. Chem. Eng., 60, 1 (2014).

    CAS  Google Scholar 

  22. 22.

    L. Bona, L. Hao, L. Hua, W. Wei, Y. Mao, L. Zhongmin and L. Jinghai, Chem. Eng. Sci., 143, 341 (2016).

    Google Scholar 

  23. 23.

    H. Schoenfelder, J. Hinderer, J. Werther and F. J. Heil, Chem. Eng. Sci., 49, 5377 (1994).

    CAS  Google Scholar 

  24. 24.

    S. Soundararajan, A. K. Dalai and F. Berruti, Fuel, 80, 1187 (2001).

    CAS  Google Scholar 

  25. 25.

    R. Gupta, V. Kumar and V. K. Srivastava, Rev. Chem. Eng., 21(2), 95 (2005).

    CAS  Google Scholar 

  26. 26.

    R. Aramesh, V. Akbari, A. Shamiri, M. A. Hussain and N. Aghamohammadi, Measurement, 83, 106 (2016).

    Google Scholar 

  27. 27.

    B. Chalermsinsuwan, P. Kuchonthara and P. Piumsomboon, Chem. Eng. Process.: Process Intensification, 49, 1144 (2010).

    CAS  Google Scholar 

  28. 28.

    Y.-P. Zhu, F.-Z. Xiao and Z.-H. Luo, Asia-Pacific J. Chem. Eng., 9, 280 (2014).

    CAS  Google Scholar 

  29. 29.

    S. Yang, L. Peng, W. Liu, H. Zhao, X. Lv, H. Li and Q. Zhu, Powder Technol., 296, 37 (2016).

    CAS  Google Scholar 

  30. 30.

    Z. Yongmin, J. R. Grace, B. Xiaotao, L. Chunxi and S. Mingxian, Chem. Eng. Sci., 64, 3270 (2009).

    Google Scholar 

  31. 31.

    T. Samruamphianskun, P. Piumsomboon and B. Chalermsinsuwan, Chem. Eng. J., 210, 237 (2012).

    CAS  Google Scholar 

  32. 32.

    C.-W. Jiang, Z.-W. Zheng, Y.-P. Zhu and Z.-H. Luo, Chem. Eng. Res. Des., 90, 915 (2012).

    CAS  Google Scholar 

  33. 33.

    G. Wu, Y. He and W. Chen, Chem. Eng. J., 351, 1104 (2018).

    CAS  Google Scholar 

  34. 34.

    J. Chang, K. Zhang, H. Chen, Y. Yang and L. Zhang, Chem. Eng. Res. Des., 91, 2355 (2013).

    CAS  Google Scholar 

  35. 35.

    Z. Jingyuan, L. Bona, C. Feiguo, L. Hua, Y. Mao and W. Wei, Chem. Eng. Sci., 189, 212 (2018).

    Google Scholar 

  36. 36.

    B. Chalermsinsuwan and P. Piumsomboon, Chem. Eng. Sci., 66, 5602 (2011).

    CAS  Google Scholar 

  37. 37.

    S. Cloete, S. Amini and S. T. Johansen, Powder Technol., 205, 103 (2011).

    CAS  Google Scholar 

  38. 38.

    S. Cloete, S. T. Johansen and S. Amini, Powder Technol., 239, 21 (2013).

    CAS  Google Scholar 

  39. 39.

    X. Lv, H. Li and Q. Zhu, Chem. Eng. J., 236, 149 (2014).

    CAS  Google Scholar 

  40. 40.

    Y. Zhang, Q. Ma, X. Xu, Y. Xiao and F. Lei, Chem. Eng. Process.: Process Intensification, 98, 71 (2015).

    CAS  Google Scholar 

  41. 41.

    J. Phupanit, C. Soanuch, K. Korkerd, P. Piumsomboon and B. Chalermsinsuwan, Asia-Pacific J. Chem. Eng., 14, 1 (2018).

    Google Scholar 

  42. 42.

    S. Aghamohammadi, M. Haghighi and M. Charghand, Mater. Res. Bull., 50, 462 (2014).

    CAS  Google Scholar 

  43. 43.

    D. C. Montgomery, Design and analysis of experiments, Wiley and Sons, New York (2001).

    Google Scholar 

  44. 44.

    S. Karimipour, R. Gerspacher, R. Gupta and R. J. Spiteri, Fuel, 103, 308 (2013).

    CAS  Google Scholar 

  45. 45.

    J.-H. Kim and J.-H. Rho, Proc. IMechE, Part E: Process. Mech. Eng., 231, 914 (2016).

    Google Scholar 

  46. 46.

    T. Yurata, P. Piumsomboon and B. Chalermsinsuwan, Chem. Eng. Res. Des., 153, 401 (2020).

    CAS  Google Scholar 

  47. 47.

    A. N. R. Bosand P. J. J. Tromp, Ind. Eng. Chem. Res., 34, 3808 (1995).

    Google Scholar 

  48. 48.

    M. Ye, H. Li, Y. Zhao, T. Zhang and Z. Liu, Adv. Chem. Eng., 47, 279 (2015).

    CAS  Google Scholar 

  49. 49.

    R. B. Rostami, M. Ghavipour, Z. Di, Y. Wang and R. M. Behbahani, RSC Adv., 5, 81965 (2015).

    CAS  Google Scholar 

  50. 50.

    M. Sedighi, H. Bahrami and J. Towfighi, J. Ind. Eng. Chem., 20, 3108 (2014).

    CAS  Google Scholar 

Download references


The authors thank the Thailand Research Fund and National Research Council of Thailand for providing a Royal Golden Jubilee Ph.D. Program Grant, No. PHD/0011/2561. The authors also thank the National Research Council of Thailand and Chulalongkorn University for providing the Mid-Career Research Grant (NRCT5-RSA63001-24).

Author information



Corresponding author

Correspondence to Benjapon Chalermsinsuwan.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Soanuch, C., Korkerd, K., Phupanit, J. et al. Computational fluid dynamics simulation of methanol to olefins in stage circulating fluidized bed riser: Effect of reactor stage parameters on product yields. Korean J. Chem. Eng. 38, 540–551 (2021).

Download citation


  • Circulating Fluidized Bed Riser
  • Computational Fluid Dynamics
  • Methanol to Olefins
  • Stage
  • Simulation