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Mathematical and Artificial Neural Network Modeling and Simulation of Catalytic Fixed Bed Reactor for Producing Ethyl Benzene from Ethanol

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Year: 2019
COI code: ICCO02_034
Paper Language: English

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Authors Mathematical and Artificial Neural Network Modeling and Simulation of Catalytic Fixed Bed Reactor for Producing Ethyl Benzene from Ethanol

  Atiyeh Aghaei Sarvari - M. Sc. Student, Faculty of Chemical and Petroleum Engineering, University of Tabriz, Tabriz, Iran
  Ali Farzi - Assistant Professor, Faculty of Chemical and Petroleum Engineering, University of Tabriz, Tabriz, Iran

Abstract:

Ethyl benzene is the raw material of producing styrene monomer and is produced via benzene alkylation in presence of ethanol and ethylene. Benzene alkylation process for production of ethylbenzene consists of three steps: alkylation step for the reaction of benzene with ethylene. Transition step inwhich polyethyl-benzenes (mostly diethyl benzene and triethyl benzene) are converted to ethylbenzene in reverse-alkylation process in presence ofbenzene. Separation step where non-reacted, polyethyl-benzenes and other compounds are separated and ethylbenzene with high purity is obtained. Theamount of ethylbenzene in crude oil is very low and it is also used for production of diethyl benzene, cellulose acetate, etc. as well as production ofstyrene. In this study, benzene alkylation in presence of ethanol in a catalytic fixed bed reactor in steady-state, unsteady-state, adiabatic and nonadiabaticconditions was modeled using fundamental laws and artificial neural network assuming one dimensional pseudo-homogeneous system. Basedon the results of this study, at steady-state condition, percent conversion of benzene to ethylbenzene was reduced by increasing the amount of feed flow.In both steady-state and unsteady-state conditions, concentrations of products increased, as inlet temperature increased. Modeling of the system byartificial neural network showed that the best network with 7 neurons in hidden layer, estimated the output results of fundamental modeling withminimum error value of about 0.001.

Keywords:

Ethyl benzene, Process modeling, Steady-state, Unsteady-state, Artificial neural network

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COI code: ICCO02_034

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Aghaei Sarvari, Atiyeh & Ali Farzi, 2019, Mathematical and Artificial Neural Network Modeling and Simulation of Catalytic Fixed Bed Reactor for Producing Ethyl Benzene from Ethanol, 2nd Iranian Catalyst Conference, تهران- دانشگاه خوارزمي- دانشكده شيمي, دانشگاه خوارزمي, https://www.civilica.com/Paper-ICCO02-ICCO02_034.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
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Type: state university
Paper No.: 17376
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