Jump to ContentJump to Main Navigation

New Journal at De Gruyter!

International Journal of Chemical Reactor Engineering

Ed. by de Lasa, Hugo / Xu, Charles Chunbao

4 Issues per year


IMPACT FACTOR increased in 2014: 0.592
5-year IMPACT FACTOR: 0.678

SCImago Journal Rank (SJR) 2014: 0.257
Source Normalized Impact per Paper (SNIP) 2014: 0.358
Impact per Publication (IPP) 2014: 0.484

Mathematical Modeling of Gas Oil HDS and Optimization of Operational Conditions in Trickle Bed Reactor by Genetic Algorithm

Reza Abbasi1 / Shohreh Fatemi2

1University of Tehran,

2University of Tehran,

Citation Information: International Journal of Chemical Reactor Engineering. Volume 7, Issue 1, ISSN (Online) 1542-6580, DOI: 10.2202/1542-6580.1864, April 2009

Publication History

Published Online:
2009-04-07

The present work aims to employ genetic algorithm (GA) to optimize a HDS process, which is difficult to optimize by conventional methods. The considered chemical process is the three phase catalytic trickle-bed reactor in which hydrodesulphurization reaction occurs. Non-linear kinetics coupled with the transitional mathematical model of the gas, liquid and solid phases are used to describe the dynamic behavior of the multivariable process. The model, based on a two-film theory, was tested with regards to hydrodesulphurization of vacuum gas oil in a high-pressure pilot plant operated under isothermal conditions. Due to the high dimensionality and non-linearity of the model, a rigorous one, the solution of the optimization problem through conventional algorithms does not always lead to the convergence. This fact justifies the use of an evolutionary method, based on the GAs, to deal with this process. In this way, in order to optimize the process, the GA code is coupled with the rigorous model of the reactor. The aim of the optimization through GAs was to search for the optimal conditions that minimize the gas make and sulfur content of the outlet oil. Many simulations are conducted in order to find the maximization of the objective function without violating the constraints. The results show that the GA is used successfully in the process optimization.

Keywords: mathematical modeling; trickle bed reactor; dynamic simulation; non-linear dynamics; optimization; genetic algorithm

Citing Articles

Here you can find all Crossref-listed publications in which this article is cited. If you would like to receive automatic email messages as soon as this article is cited in other publications, simply activate the “Citation Alert” on the top of this page.

[1]
Abbas Azarpour, Tohid Nejad Ghaffar Borhani, Sharifah Rafidah Wan Alwi, Zainuddin Abdul Manan, and Mazyar Madooli Behbehani
Industrial & Engineering Chemistry Research, 2015, Page 150707111144002
[2]
R. Abbasi, L. Wu, S.E. Wanke, and R.E. Hayes
Chemical Engineering Research and Design, 2012, Volume 90, Number 11, Page 1930

Comments (0)

Please log in or register to comment.