Modeling of high-temperature reforming reactor based on interactive thermal control with a tail gas combustor

Abstract

This paper proposes a method to model hydrocarbon reforming by coupling detailed chemical kinetics with complex computational fluid dynamics. The entire chemistry of catalyzed reactions was confined within the geometrically simple channels and modeled using the low-dimensional plug model, into which the interactive thermal control of the multi-channel reforming reactor has been implemented with a tail-gas combustor around the external surface of these catalytic channels. The geometrically complex flow in the tail gas combustor was simulated using FLUENT without involving any chemical reactions. The influences of the conditions at the reactor inlet such as the inlet gas velocity, the inlet gas composition and the variety of hydrocarbons of each channel on gas conversions were investigated numerically. The impact of the tail gas combustor setup on the efficiency of the reforming reactor was also analyzed. Methane catalytic partial oxidation (CPO _x) and propane steam reforming (SR) were used to illustrate the approach reported in the present work.

Keywords

Computational fluid dynamics / Reaction kinetics / Catalytic partial oxidation / Steam reforming

References

[1] Silva AL, Mueller IL (2011) Hydrogen production by sorption enhanced steam reforming of oxygenated hydrocarbons (ethanol, glycerol, n-butanol and methanol): thermodynamic modelling. Int J Hydrogen Energy 36:2057–2075

[2] Thormann J, Pfeifer P, Kunz U. Dynamic performance of hexadecane steam reforming in a microstructured reactor. Chem Eng J, 2012, 191: 410-415.

[3] Maier L, Hartmann M, Tischer S, et al. Interaction of heterogeneous and homogeneous kinetics with mass and heat transfer in catalytic reforming of logistic fuels. Combust Flame, 2011, 158: 796-808.

[4] Yua M, Zhua K, Liu Z, et al. Carbon dioxide reforming of methane over promoted Ni _xMg_1−xO(1 1 1) platelet catalyst derived from solvothermal synthesis. Appl Catal B, 2014, 148–149: 177-190.

[5] Moon DJ, Ryu JW. Partial oxidation reforming catalyst for fuel cell-powered vehicles applications. Catal Lett, 2003, 89: 3-4.

[6] Schädel BT, Deutschmann O (2007) Studies in surface science and catalysis. In: Noronha FB, Sousa-Aguiar EF, Schmal M (eds). Natural gas conversion VIII, Elsevier, pp 207–212

[7] Holladay JD, Hu J, King DL, et al. An overview of hydrogen production technologies. Catal Today, 2009, 139: 244-260.

[8] Hartmanna M, Maier L, Deutschmann O. Hydrogen production by catalytic partial oxidation of iso-octane at varying flow rate and fuel/oxygen ratio: from detailed kinetics to reactor behavior. Appl Catal A, 2011, 391: 144-152.

[9] Bičáková O, Straka P. Production of hydrogen from renewable resources and its effectiveness. Int J Hydrogen Energy, 2012, 37: 11563-11578.

[10] Waller MG, Walluk MR, Trabold TA. Operating envelope of a short contact time fuel reformer for propane catalytic partial oxidation. J Power Sources, 2015, 274: 149-155.

[11] Ghouse JH, Adams TA. A multi-scale dynamic two-dimensional heterogeneous model for catalytic steam methane reforming reactors. Int J Hydrogen Energy, 2013, 38: 9984-9999.

[12] Iranshahi D, Bahmanpour AM, Paymooni K, et al. Simultaneous hydrogen and aromatics enhancement by obtaining optimum temperature profile and hydrogen removal in naphtha reforming process: a novel theoretical study. Int J Hydrogen Energy, 2011, 36: 8316-8326.

[13] Deutschmann O, Schmidt LD. Modeling the partial oxidation of methane in a short-contact-time reactor. AIChE J, 1998, 44: 2465-2477.

[14] Schädel BT, Duisberg M, Deutschmann O. Steam reforming of methane, ethane, propane, butane, and natural gas over a rhodium-based catalyst. Catal Today, 2009, 142: 42-51.

[15] Deutschmann O (2008) Computational fluid dynamics simulation of catalytic reactors. In: Ertl G, Knözinger H, Schüth F et al (eds.) Handbook of heterogeneous catalysis, 2nd edn. Wiley, p 1811–1828

[16] Deutschmann O, Tischer S, Kleditzsch S et al (2007) DETCHEM software package, 2.1 edition. http://www.detchem.com/

[17] Goldin GM, Ren Z, Zahirovic S. A cell agglomeration algorithm for accelerating detailed chemistry in CFD. Combust Theor Model, 2009, 13: 721-739.