Prediction of Reaction Kinetic of Al- Doura Heavy Naphtha Reforming Process Using Genetic Algorithm

In this study, genetic algorithm was used to predict the reaction kinetics of Iraqi heavy naphtha catalytic reforming process located in Al-Doura refinery in Baghdad. One-dimensional steady state model was derived to describe commercial catalytic reforming unit consisting of four catalytic reforming...

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Autores principales:	Ramzy H. Saihod, Zaidoon M. Shakoor, Abbas A. Jawad
Formato:	article
Lenguaje:	EN
Publicado:	Al-Khwarizmi College of Engineering – University of Baghdad 2015
Materias:	Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/0d460cc2b42e444b82901d5fd8bcab26
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spelling	oai:doaj.org-article:0d460cc2b42e444b82901d5fd8bcab262021-12-02T09:48:44ZPrediction of Reaction Kinetic of Al- Doura Heavy Naphtha Reforming Process Using Genetic Algorithm 1818-1171https://doaj.org/article/0d460cc2b42e444b82901d5fd8bcab262015-07-01T00:00:00Zhttp://www.iasj.net/iasj?func=fulltext&aId=87763https://doaj.org/toc/1818-1171In this study, genetic algorithm was used to predict the reaction kinetics of Iraqi heavy naphtha catalytic reforming process located in Al-Doura refinery in Baghdad. One-dimensional steady state model was derived to describe commercial catalytic reforming unit consisting of four catalytic reforming reactors in series process. The experimental information (Reformate composition and output temperature) for each four reactors collected at different operating conditions was used to predict the parameters of the proposed kinetic model. The kinetic model involving 24 components, 1 to 11 carbon atoms for paraffins and 6 to 11 carbon atom for naphthenes and aromatics with 71 reactions. The pre-exponential Arrhenius constants and activation energies were determined after fine tuning of the model results with experimental data. The input to the optimization is the compositions for 21 components and the temperature for the effluent stream for each one of the four reactors within the reforming process while the output of optimization is 142 predicted kinetic parameters for 71 reactions within reforming process. The differential optimization technique using genetic algorithm to predict the parameters of the kinetic model. To validate the kinetic model, the simulation results of the model based on proposed kinetic model was compared with the experimental results. The comparison between the predicted and commercially results shows a good agreement, while the percentage of absolute error for aromatics compositions are (7.5, 2, 8.3, and 6.1%) and the temperature absolute percentage error are (0.49, 0.5, 0.01, and 0.3%) for four reactors respectively. Ramzy H. SaihodZaidoon M. Shakoor Abbas A. JawadAl-Khwarizmi College of Engineering – University of BaghdadarticleChemical engineeringTP155-156Engineering (General). Civil engineering (General)TA1-2040ENAl-Khawarizmi Engineering Journal, Vol 10, Iss 1, Pp 47-61 (2015)
institution	DOAJ
collection	DOAJ
language	EN
topic	Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040 Ramzy H. Saihod Zaidoon M. Shakoor Abbas A. Jawad Prediction of Reaction Kinetic of Al- Doura Heavy Naphtha Reforming Process Using Genetic Algorithm
description	In this study, genetic algorithm was used to predict the reaction kinetics of Iraqi heavy naphtha catalytic reforming process located in Al-Doura refinery in Baghdad. One-dimensional steady state model was derived to describe commercial catalytic reforming unit consisting of four catalytic reforming reactors in series process. The experimental information (Reformate composition and output temperature) for each four reactors collected at different operating conditions was used to predict the parameters of the proposed kinetic model. The kinetic model involving 24 components, 1 to 11 carbon atoms for paraffins and 6 to 11 carbon atom for naphthenes and aromatics with 71 reactions. The pre-exponential Arrhenius constants and activation energies were determined after fine tuning of the model results with experimental data. The input to the optimization is the compositions for 21 components and the temperature for the effluent stream for each one of the four reactors within the reforming process while the output of optimization is 142 predicted kinetic parameters for 71 reactions within reforming process. The differential optimization technique using genetic algorithm to predict the parameters of the kinetic model. To validate the kinetic model, the simulation results of the model based on proposed kinetic model was compared with the experimental results. The comparison between the predicted and commercially results shows a good agreement, while the percentage of absolute error for aromatics compositions are (7.5, 2, 8.3, and 6.1%) and the temperature absolute percentage error are (0.49, 0.5, 0.01, and 0.3%) for four reactors respectively.
format	article
author	Ramzy H. Saihod Zaidoon M. Shakoor Abbas A. Jawad
author_facet	Ramzy H. Saihod Zaidoon M. Shakoor Abbas A. Jawad
author_sort	Ramzy H. Saihod
title	Prediction of Reaction Kinetic of Al- Doura Heavy Naphtha Reforming Process Using Genetic Algorithm
title_short	Prediction of Reaction Kinetic of Al- Doura Heavy Naphtha Reforming Process Using Genetic Algorithm
title_full	Prediction of Reaction Kinetic of Al- Doura Heavy Naphtha Reforming Process Using Genetic Algorithm
title_fullStr	Prediction of Reaction Kinetic of Al- Doura Heavy Naphtha Reforming Process Using Genetic Algorithm
title_full_unstemmed	Prediction of Reaction Kinetic of Al- Doura Heavy Naphtha Reforming Process Using Genetic Algorithm
title_sort	prediction of reaction kinetic of al- doura heavy naphtha reforming process using genetic algorithm
publisher	Al-Khwarizmi College of Engineering – University of Baghdad
publishDate	2015
url	https://doaj.org/article/0d460cc2b42e444b82901d5fd8bcab26
work_keys_str_mv	AT ramzyhsaihod predictionofreactionkineticofaldouraheavynaphthareformingprocessusinggeneticalgorithm AT zaidoonmshakoor predictionofreactionkineticofaldouraheavynaphthareformingprocessusinggeneticalgorithm AT abbasajawad predictionofreactionkineticofaldouraheavynaphthareformingprocessusinggeneticalgorithm
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Prediction of Reaction Kinetic of Al- Doura Heavy Naphtha Reforming Process Using Genetic Algorithm

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