Record Details

Prediction of bubble size in Bubble columns using Artificial Neural Network

Iraqi Journal of Chemical and Petroleum Engineering

View Archive Info
 
 
Field Value
 
Title Prediction of bubble size in Bubble columns using Artificial Neural Network
 
Creator Sadoon Ahmed zeki, Nada
 
Description In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A comparison with selected correlations in the literature showed that the developed ANN correlation noticeably improved the prediction of bubble sizes. The developed correlation also shows better prediction over a wide range of operation parameters in bubble columns.
 
Publisher University of Baghdad/ College of Engineering
 
Date 2009-03-30
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier http://ijcpe.uobaghdad.edu.iq/index.php/ijcpe/article/view/391
 
Source Iraqi Journal of Chemical and Petroleum Engineering; Vol 10 No 1 (2009): Iraqi Journal of Chemical and Petroleum Engineering; 1-8
المجلة العراقية للهندسة الكيمياوية وهندسة النفط; مجلد 10 عدد 1 (2009): Iraqi Journal of Chemical and Petroleum Engineering; 1-8
2618-0707
1997-4884
 
Language eng
 
Relation http://ijcpe.uobaghdad.edu.iq/index.php/ijcpe/article/view/391/388