Abstract
Due to environmental limitations and issues, the main goal of this research is modification of conventional Claus sulfur recovery process to decreases sulfur contaminant emission. In this regard, two environmentally friendly alternatives are proposed based on the isothermal concept in reactors. Since Claus reaction is exothermic and reversible, the adiabatic fixed bed reactors in the catalytic section of Claus process are substituted by the isothermal reactors. The furnace and catalytic reactors are modeled based on the mass and energy conservation laws at steady state condition. To prove accuracy of the developed model, the simulation results of conventional process are compared with the available plant data. Then, the optimal condition of modified processes are calculated considering sulfur recovery as the objective function using the Genetic algorithm as a useful method in global optimization. The attainable decision variables are inlet temperature of furnace and reactors, coolant temperature, feed split fraction and air flow rate in the furnace. The simulation results show that H2S conversion in the proposed cases increases about 1.87 % and 1.78 % compared to the conventional process. Generally, the main advantages of proposed structures are higher sulfur recovery and lower sulfur contaminant emission such as COS and CS2 emission.
References
[1] Cox BG, Clarke PF, Pruden BB. Economics of thermal dissociation of H2S to produce hydrogen. Int J Hydrogen Energy. 1998;23:531–44.10.1016/S0360-3199(97)00111-0Suche in Google Scholar
[2] Goar B. Sulfur recovery technology. New York: American Institute of Chemical Engineers, 1986.Suche in Google Scholar
[3] Clark PD. Sulfur and hydrogen sulfide recovery. Kirk-Othmer encyclopedia of chemical technology. New Jersey: John Wiley & Sons, 2000.Suche in Google Scholar
[4] Pierucci S, Ranzi E, Molinari L. Modeling a claus process reaction furnace via a radical kinetic scheme. Comput Aided Chem Eng. 2004;18:463–68.10.1016/S1570-7946(04)80143-3Suche in Google Scholar
[5] Manenti F, Papasidero D, Bozzano G, Ranzi E. Model-based optimization of sulfur recovery units. Comput Chem Eng. 2014;66:244–51.10.1016/j.compchemeng.2014.01.019Suche in Google Scholar
[6] Zarei S, Ganji H, Sadi M, Rashidzadeh M. Kinetic modeling and optimization of Claus reaction furnace. J Nat Gas Sci Eng. 2016;31:747–57.10.1016/j.jngse.2016.03.086Suche in Google Scholar
[7] Kazempour H, Pourfayaz F, Mehrpooya M. Modeling and multi-optimization of thermal section of Claus process based on kinetic model. J Nat Gas Sci Eng. 2017;38:235–44.10.1016/j.jngse.2016.12.038Suche in Google Scholar
[8] Nabikandi NJ, Fatemi S. Kinetic modelling of a commercial sulfur recovery unit based on Claus straight through process: comparison with equilibrium model. J Ind Eng Chem. 2015;30:50–63.10.1016/j.jiec.2015.05.001Suche in Google Scholar
[9] Puchyr DM, Mehrotra AK, Behie LA, Kalogerakis N. Hydrodynamic and kinetic modelling of circulating fluidized bed reactors applied to a modified Claus plant. Chem Eng Sci. 1996;51:5251–62.10.1016/S0009-2509(96)00364-8Suche in Google Scholar
[10] Elsner MP, Menge M, Müller C, Agar DW. The Claus process: teaching an old dog new tricks. Catal Today. 2003;79:487–94.10.1016/S0920-5861(03)00071-3Suche in Google Scholar
[11] Asadi S, Pakizeh M, Chenar MP. An investigation of reaction furnace temperatures and sulfur recovery. Front Chem Sci Eng. 2011;5:362–71.10.1007/s11705-011-1106-zSuche in Google Scholar
[12] Ghahraloud H, Farsi M, Rahimpour M. Modeling and optimization of an industrial Claus process: thermal and catalytic section. J Taiwan Inst Chem Eng. 2017;76:1–9.10.1016/j.jtice.2017.03.005Suche in Google Scholar
[13] Reverberi AP, Klemeš JJ, Varbanov PS, Fabiano B. A review on hydrogen production from hydrogen sulphide by chemical and photochemical methods. J Clean Prod. 2016;136:72–80.10.1016/j.jclepro.2016.04.139Suche in Google Scholar
[14] Adewale R, Salem DJ, Berrouk AS, Dara S. Simulation of hydrogen production from thermal decomposition of hydrogen sulfide in sulfur recovery units. J Clean Prod. 2016;112:4815–25.10.1016/j.jclepro.2015.08.021Suche in Google Scholar
[15] Bassani A, Pirola C, Maggio E, Pettinau A, Frau C, Bozzano G, et al. Acid Gas to Syngas (AG2S™) technology applied to solid fuel gasification: cutting H2S and CO2 emissions by improving syngas production. Appl Energy. 2016;184:1284–91.10.1016/j.apenergy.2016.06.040Suche in Google Scholar
[16] Bassani A, Bozzano G, Pirola C, Ranzi E, Pierucci S, Manenti F. Low impact methanol production from sulfur rich coal gasification. Energy Procedia. 2017;105:4519–24.10.1016/j.egypro.2017.03.970Suche in Google Scholar
[17] Eow JS. Recovery of sulfur from sour acid gas: a review of the technology. Environ Prog. 2002;21:143–62.10.1002/ep.670210312Suche in Google Scholar
[18] Dowling NI, Clark PD. Kinetic modeling of the reaction between hydrogen and sulfur and opposing H2S decomposition at high temperatures. Ind Eng Chem Res. 1999;38:1369–75.10.1021/ie980293tSuche in Google Scholar
[19] Hawboldt KA. Kinetic modelling of key reactions in the modified Claus plant front end furnace. University of Calgary, 1998.Suche in Google Scholar
[20] Monnery W, Hawboldt K, Pollock A, Svrcek W. New experimental data and kinetic rate expression for the Claus reaction. Chem Eng Sci. 2000;55:5141–48.10.1016/S0009-2509(00)00146-9Suche in Google Scholar
[21] Dryer F, Glassman I, editors. High-temperature oxidation of CO and CH4. Symposium (International) on combustion. Elsevier, 1973.10.1016/S0082-0784(73)80090-6Suche in Google Scholar
[22] Westbrook CK, Dryer FL. Simplified reaction mechanisms for the oxidation of hydrocarbon fuels in flames. Combust Sci Technol. 1981;27:31–43.10.1080/00102208108946970Suche in Google Scholar
[23] Karan K, Mehrotra AK, Behie LA. COS-forming reaction between CO and sulfur: A high-temperature intrinsic kinetics study. Ind Eng Chem Res. 1998;37:4609–16.10.1021/ie9802966Suche in Google Scholar
[24] Karan K, Mehrotra AK, Behie LA. A high-temperature experimental and modeling study of homogeneous gas-phase COS reactions applied to Claus plants. Chem Eng Sci. 1999;54:2999–3006.10.1016/S0009-2509(98)00475-8Suche in Google Scholar
[25] Monnery W, Hawboldt K, Pollock A, Svrcek W. Ammonia pyrolysis and oxidation in the Claus furnace. Ind Eng Chem Res. 2001;40:144–51.10.1021/ie990764rSuche in Google Scholar
[26] Karan K, Behie LA. CS2 formation in the Claus reaction furnace: A kinetic study of methane-sulfur and methane-hydrogen sulfide reactions. Ind Eng Chem Res. 2004;43:3304–13.10.1021/ie030515+Suche in Google Scholar
[27] Birkholz RK, Behie LA, Lana IG. Kinetic modelling of a fluidized bed Claus plant. Can J Chem Eng. 1987;65:778–84.10.1002/cjce.5450650511Suche in Google Scholar
[28] Tong S, Dalla Lana I, Chuang K. Kinetic modelling of the hydrolysis of carbonyl sulfide catalyzed by either titania or alumina. Can J Chem Eng. 1993;71:392–400.10.1002/cjce.5450710308Suche in Google Scholar
[29] Tong S, Dalla Lana I, Chuang K. Kinetic modeling of the hydrolysis of carbon disulfide catalyzed by either titania or alumina. Can J Chem Eng. 1995;73:220–27.10.1002/cjce.5450730208Suche in Google Scholar
[30] Holman J. Heat transfer, 9th ed. Boston : McGraw-Hill, 2002.Suche in Google Scholar
[31] Fogler HS. Elements of chemical reaction engineering. Estados Unidos: Prentice Hall, 1999.Suche in Google Scholar
[32] Cussler EL. Diffusion: mass transfer in fluid systems. Cambridge: Cambridge University Press, 2009.10.1017/CBO9780511805134Suche in Google Scholar
[33] Smith JM. Chemical engineering kinetics. Singapore: McGraw-Hill, 1981.Suche in Google Scholar
[34] Wilke C. Estimation of liquid diffusion coefficients. Chem Eng Prog. 1949;45:218–24.Suche in Google Scholar
[35] Reid RC, Prausnitz JM, Poling BE. The properties of gases and liquids. New York: McGraw-Hill, 1987.Suche in Google Scholar
[36] Edgar TF, Himmelblau DM, Lasdon LS. Optimization of chemical processes. New York: McGraw-Hill, 2001Suche in Google Scholar
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