Modeling and optimization of Fischer-Tropsch synthesis in the presence of Co ((III)/Al2O3 catalyst using artificial neural networks and genetic algorithm

被引：50

作者：

Adib, Hooman ^{[1
]}

Haghbakhsh, Reza ^{[1
]}

Saidi, Majid ^{[1
]}

Takassi, Mohammad Ali ^{[2
]}

Sharifi, Fatemeh ^{[3
]}

Koolivand, Mehdi ^{[4
]}

Rahimpour, Mohammad Reza ^{[1
,5
]}

Keshtkari, Simin ^{[1
]}

机构：

[1] Shiraz Univ, Dept Chem Engn, Sch Chem & Petr Engn, Shiraz 71345, Iran

[2] Petr Univ Technol, Dept Petr Engn, Ahvaz, Iran

[3] Isfahan Univ Technol, Dept Comp Engn, Esfahan, Iran

[4] Natl Iranian South Oil Field Co, Dept Petr, Ahvaz, Iran

[5] Shiraz Univ, Gas Ctr Excellence, Shiraz 71345, Iran

来源：

JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING | 2013年 / 10卷

关键词：

Artificial neural network; Genetic algorithm; Fischer-Tropsch synthesis; Catalyst; DESIGN; PERMEABILITY; COLUMN; WEAR;

D O I：

10.1016/j.jngse.2012.09.001

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Fischer-Tropsch synthesis is a collection of chemical reactions that converts a mixture of carbon monoxide and hydrogen into hydrocarbons. In this study, application of FTS is studied in a wide range of synthesis gas conversions. Artificial neural networks (ANN) were used to predict the molar percentage of CH4, CO2 and CO in the Fischer-Tropsch process of natural gas and also genetic algorithm (GA) was applied to obtain the optimum values of operational parameters. The input parameters consist of a 3-dimensions vector which includes the reaction time, operating pressure and temperature and also the output was molar percentage of CH4, CO2 and CO. Topology and decision parameters have been calculated by trial and error and acceptable correlation coefficients (R-2 = 0.94 for CH4, R-2 = 0.93 for CO2 and R-2 = 0.96 for CO) were obtained. Also the results obtained by sensitivity analysis represent that operation time has significant influence on molar percentage of CH4 as desired product with respect to other operational parameters. Finally the results justify that GA-ANN could be effectively used for FTS as a powerful estimation technique. (C) 2012 Elsevier B.V. All rights reserved.

引用

页码：14 / 24

页数：11

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