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 reformi...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Al-Khwarizmi College of Engineering – University of Baghdad
2017-12-01
|
Series: | Al-Khawarizmi Engineering Journal |
Subjects: | |
Online Access: | http://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/190 |
id |
doaj-c4818898be8b45a39ce8ac9d43b10c25 |
---|---|
record_format |
Article |
spelling |
doaj-c4818898be8b45a39ce8ac9d43b10c252020-11-24T23:54:51Zeng Al-Khwarizmi College of Engineering – University of BaghdadAl-Khawarizmi Engineering Journal1818-11712312-07892017-12-01101Prediction of Reaction Kinetic of Al- Doura Heavy Naphtha Reforming Process Using Genetic AlgorithmRamzy H. Saihod0Zaidoon M. Shakoor1Abbas A. Jawad2Department of Petroleum Technology / University of TechnologyDepartment of Chemical Engineering / University of TechnologyAl-Doura Refinery / Middle Refinery Company 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. http://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/190Heavy NaphthaReformingGenetic AlgorithmOptimizationReaction Kinetic |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ramzy H. Saihod Zaidoon M. Shakoor Abbas A. Jawad |
spellingShingle |
Ramzy H. Saihod Zaidoon M. Shakoor Abbas A. Jawad Prediction of Reaction Kinetic of Al- Doura Heavy Naphtha Reforming Process Using Genetic Algorithm Al-Khawarizmi Engineering Journal Heavy Naphtha Reforming Genetic Algorithm Optimization Reaction Kinetic |
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 |
series |
Al-Khawarizmi Engineering Journal |
issn |
1818-1171 2312-0789 |
publishDate |
2017-12-01 |
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.
|
topic |
Heavy Naphtha Reforming Genetic Algorithm Optimization Reaction Kinetic |
url |
http://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/190 |
work_keys_str_mv |
AT ramzyhsaihod predictionofreactionkineticofaldouraheavynaphthareformingprocessusinggeneticalgorithm AT zaidoonmshakoor predictionofreactionkineticofaldouraheavynaphthareformingprocessusinggeneticalgorithm AT abbasajawad predictionofreactionkineticofaldouraheavynaphthareformingprocessusinggeneticalgorithm |
_version_ |
1725464547634970624 |