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International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 2    
Website: http://www.ijser.org
scirp IJSER >> Volume 3,Issue 2,February 2012
Simulation of methanol synthesis from synthesis gas in fixed bed catalytic reactor using mathematical modeling and neural networks
Full Text(PDF, )  PP.162-168  
Author(s)
Parvaneh Nakhostin Panahi, Seyed Mahdi Mousavi, Aligholi Niaei, Ali Farzi, Dariush Salari
KEYWORDS
methanol synthesis, mathematical modeling, artificial neural network
ABSTRACT
Recently, methanol synthesis with CO2-rich feed has drawn a lot of attention and research is currently aimed at finding a suitable catalyst for such a task. A pseudo-homogeneous model was developed for fixed bed catalytic methanol reactor based on the reaction mechanisms and mass and energy balance equations. The model utilizes the kinetic equation proposed by Vanden Bussche and Froment in 1996. With the proposed mathematical model, the profile of methanol molar flow rate, H2 and CO2 conversion, methanol yield, and temperature were achieved through the length of catalytic bed reactor. Good agreement was found between model results and industrial data. The proposed model used for calculating of reactor output against variation of the inlet molar flow H2/ CO2 in the feed then modeling of the methanol unit by use of artificial neural networks was done with obtained results from mathematical model.
References
[1] ShahrokhiM, BaghmishehG R. " Modeling, simulation and control of a methanol synthesis fixed bed reactor”.Chemical Engineering Science, vol. 60, 4275–4286, 2005.

[2] Løvik I. “Modelling, estimation and optimization of the methanol synthesis with catalyst deactivation”. Doctoral thesis, Norwegian University of Science and Technology. 127p. 2001.

[3] Vanden Bussche1. K. M., Froment. G. F., “A Steady-State Kinetic Model for Methanol Synthesis and the Water Gas Shift Reaction on a Commercial Cu/ZnO/Al2O3 Catalyst”. Journal of Catalysis,vol. 161, pp. 1–10, 1996.

[4] Raudaskoski R., Niemelä M. and Keiski R.L. “The effect of ageing time on co-precipitated Cu/ZnO/ZrO2 catalysts used in methanol synthesis from CO2 and H2”. Topics in Catalysis ,vol. 45, pp. 57-60, 2007.

[5] Yang R., Yu X., Zhang Y., Li W. and Tsubaki N. “A new method of low-temperature methanol synthesis on Cu/ZnO/Al2O3 catalysts from CO/CO2/H2”. Fuel,Vol. 87,pp. 443-450, 2008.

[6] Klier K. “Methanol synthesis”. Advances in Catalysis, Vol. 31, pp. 243- 313, 1982.

[7] Skrzypek J., Lachowska M., Grzesik M., Słoczyński J. and Novak P. “Thermodynamics and kinetics of low pressure methanol synthesis”. TheChemical Engineering Journal,vol. 58, pp. 101-108, 1995.

[8] Sinadinovic-fiser S.V, Jankovic M. R and Radicevic R. Z. “simulation of the fixed - bed reactor for methanol synthesis”. Petroleum and coal, vol. 43, pp. 31-34, 2001.

[9] Fatemi Sh, Hosseini A. “Modeling and simulation of methanol synthesis from synthesis gas based on kinetic model effect of CO2 in fixec bed catalyst Cu/ZnO/Al2O3” The 10th Iranin national chemical engineering congress, November 2005, Zahedan, Iran.

[10] Salari D, Niaei A , Aghazadeh F and Hosseini S.A . “Preparation and characterization of high performance (Co, Cu)/Pt/γ-Al2O3 bimetallic catalysts for oxidation of 2-propanol : Experiments and ANN modelling” The Canadian Journal of Chemical Engineering, Vol. 9999, pp. 1-10, 2011.

[11] Omata K, Nukai N, Yamada M, “Artificial Neural Network Aided Design of a Stable Co−MgO Catalyst of High-Pressure Dry Reforming of Methane”, Ind. Eng. Chem. Res,Vol. 44,pp. 296, 2005.

[12] Kito S, Ishikura T, Niwa M, Murakami Y, Hattori T, “Application of neural network to estimation of catalyst deactivation in methanol conversion”, Catal. Today,vol. 97 ,pp. 41, 2004.

[13] Nabavi R, Niaei A, Salari D, Towfighi J. “Modeling of thermal cracking of LPG: Application of artificial neural”. J. Anal. Appl. Pyrolysis , vol. 80 ,pp. 175–181, 2007.

[14] Mousavi S M, Nakhostin Panahi P, Niaei A, Farzi A, Salari D.”Modeling and Simulation of Styrene Monomer Reactor: Mathematical and Artificial Neural Network Model” International Journal of Scientific & Engineering Research, Vol. 3, Issue 2, 2012.

[15] Papadokonstantakis S, Machefer S, Schnitzleni K, Lygeros A.I, “Variable selection and data pre-processing in NN modelling of complex chemical processes”, Comput.Chem. Eng, vol. 29, pp. 1647, 2005.

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