Jump to ContentJump to Main Navigation
Show Summary Details
More options …

International Journal of Chemical Reactor Engineering

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

12 Issues per year


IMPACT FACTOR 2016: 0.623
5-year IMPACT FACTOR: 0.761

CiteScore 2016: 0.58

SCImago Journal Rank (SJR) 2016: 0.224
Source Normalized Impact per Paper (SNIP) 2016: 0.297

Online
ISSN
1542-6580
See all formats and pricing
More options …

A Neural Network Approach for Prediction of the CuO-ZnO-Al2O3 Catalyst Deactivation

Gholamreza Zahedi / Abdolhossein Jahanmiri / M. R. Rahimpor
Published Online: 2005-06-09 | DOI: https://doi.org/10.2202/1542-6580.1187

In this work an Artificial Neural Networks (ANN) approach for estimation of catalyst deactivation during methanol synthesis has been proposed. The approach predicts deactivation of the catalyst at different operating conditions as a function of time. Experimental data of a typical differential reactor were pre-scaled and used for training. Among the various training algorithms, Exact Radial Basis (RBE) method had the best prediction performance and was used for simulation of the reactor. The proposed approach interprets deactivation data, while there are not enough data versus time at different inlet conditions. By using the model, sufficient data were generated which vary with time and agree very well with experimental data. Capability of the model in generating deactivation data at different temperatures, pressures and feed compositions was excellent. The proposed method has great potential as a means to compensate for lack of the phenomenological kinetic modeling techniques.

Keywords: Methanol Synthesis; Catalyst Deactivation; Kinetic Modeling; Neural Network.

About the article

Published Online: 2005-06-09


Citation Information: International Journal of Chemical Reactor Engineering, Volume 3, Issue 1, ISSN (Online) 1542-6580, DOI: https://doi.org/10.2202/1542-6580.1187.

Export Citation

©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston. Copyright Clearance Center

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]
Yazdan Shirvany, Gholamreza Zahedi, and Mohsen Bashiri
Journal of Petroleum Science and Engineering, 2010, Volume 73, Number 1-2, Page 156
[2]
Gholamreza Zahedi, Zohre Karami, and Hamed Yaghoobi
Energy Conversion and Management, 2009, Volume 50, Number 8, Page 2052
[3]
Gholamreza Zahedi and Abbas Azarpour
The Journal of Supercritical Fluids, 2011, Volume 58, Number 1, Page 40

Comments (0)

Please log in or register to comment.
Log in