Issue
Korean Journal of Chemical Engineering,
Vol.29, No.11, 1531-1540, 2012
Computational fluid dynamics modeling of hydrogen production in an autothermal reactor: Effect of different thermal conditions
A numerical model was developed and validated to simulate and improve the reforming efficiency of methane to syngas (CO+H2) in an autothermal reactor. This work was undertaken in a 0.8 cm diameter and 30 cm length quartz tubular reactor. The exhaust gas from combustion at the bottom of reactor was passed over a Ru/γ-Al2O3 catalyst bed. The Eddy Dissipation Concept (EDC) model for turbulence-chemistry interaction in combination with a modified standard k-ε model for turbulence and a reaction mechanism with 23 species and 39 elementary reactions were considered in the combustion model. The pre-exponential factors and activation energy values for the catalyst (Ru) were obtained by using the experimental results. The percentage of difference between the predicted and measured mole fractions of the major species in the exhaust gas from combustion and catalyst bed zones was less than 5.02% and 7.73%, respectively. In addition, the results showed that the reforming efficiency, based on hydrogen yield, was increased with increase in catalyst bed’s thermal conductivity. Moreover, an enhancement of 4.34% in the reforming efficiency was obtained with increase in the catalyst bed wall heat flux from 0.5 to 2.0 kW/m2.
[References]
  1. Gosiewski K, Chem. Eng. Process., 39(5), 459, 2000
  2. Christensen TS, Primdahl II, Hydrocarb. Process., 73(3), 39, 1994
  3. Ko KD, Lee JK, Park D, Shin SH, Korean J. Chem. Eng., 12(4), 478, 1995
  4. Kim KH, Lee SY, Nam SW, Lim TH, Hong SA, Yoon KJ, Korean J. Chem. Eng., 23(1), 17, 2006
  5. Lim MS, Hong MS, Chun YN, Korean J. Chem. Eng., 26(4), 1022, 2009
  6. Koo K, Yoon J, Lee C, Joo H, Korean J. Chem. Eng., 25(5), 1054, 2008
  7. Aasberg-Petersen K, Christensen TS, Nielsen CS, Dybkjaer I, Fuel Process. Technol., 83, 253
  8. Simeone M, Salemme L, Scognamiglio D, Allouis C, Volpicelli G, Int. J. Hydrog. Energy., 33, 1252, 2008
  9. Rabe S, Truong TB, Vogel F, Appl. Catal. A: Gen., 292, 177, 2005
  10. Dantas SC, Escritori JC, Soares RR, Hori CE, Chem. Eng. J., 156(2), 380, 2010
  11. Dias JAC, Assaf JM, J. Power Sources, 130(1-2), 106, 2004
  12. Park SH, Chun BH, Kim SH, Korean J. Chem. Eng., 28(2), 402, 2011
  13. Lee HJ, Lim YS, Park NC, Kim YC, Chem. Eng. J., 146(2), 295, 2009
  14. Ma L, Trimm DL, Jiang C, Appl. Catal. A: Gen., 138(2), 275, 1996
  15. Biesheuvel PM, Kramer GJ, AIChE J., 49(7), 1827, 2003
  16. Chan SH, Hoang DL, Ding OL, Int. J. Heat Mass Transf., 48(19-20), 4205, 2005
  17. Lin ST, Chen YH, Yu CC, Liu YC, Lee CH, J. Power Sources, 148, 43, 2005
  18. Avci AK, Trimm DL, Onsan ZI, Chem. Eng. Sci., 56(2), 641, 2001
  19. Cipiti F, Pino L, Vita A, Lagana M, Recupero V, Int. J. Hydrog.Energy., 33, 3197, 2008
  20. Behroozsarand A, Ebrahimi H, Zamaniyan A, Ind. Eng. Chem. Res., 48(16), 7529, 2009
  21. Shi L, Bayless DJ, Prudich ME, Int. J. Hydrog. Energy., 34, 7666, 2009
  22. Zhou XW, Chen CX, Wang FC, Chem. Eng. Process., 49(1), 59, 2010
  23. Yu YH, Chem. Eng. Technol., 25(3), 307, 2002
  24. Zahedinezhad M, Rowshanzamir S, Eikani MH, Int. J. Hydrog.Energy., 34, 1292, 2009
  25. KARIM GA, HANAFI AS, ZHOU G, J. Energy Resour. Technol.-Trans. ASME, 115(4), 301, 1993
  26. Xu J, Froment G, AIChE J., 35, 88, 1989
  27. Amirshaghaghi H, Zamaniyan A, Ebrahimi H, Zarkesh M, Appl. Math. Model., 34, 2312, 2010
  28. Fluent 6.2.16: Fluent Inc., Lebanon, 2001
  29. Dally BB, Fletcher DF, Masri AR, Combust. Theory Model., 2, 193, 1998
  30. Glarborg P, Miller JA, Kee RJ, Combust. Flame., 65, 177, 1986
  31. Bilger RW, Stamer SH, Kee RJ, Combust. Flame., 80, 135, 1990
  32. Chen GB, Chen CP, Wu CY, Chao YC, Appl. Catal. A: Gen., 332(1), 89, 2007