Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However, these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611 measurements collected from the open literature, a correlation for hold u...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Baghdad/College of Engineering
2007-12-01
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| Series: | Iraqi Journal of Chemical and Petroleum Engineering |
| Subjects: | |
| Online Access: | http://ijcpe.uobaghdad.edu.iq/index.php/ijcpe/article/view/494 |
| Summary: | In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably improved prediction of dispersed phase hold up. The developed correlation also
shows better prediction over a wide range of operation parameters in RDC columns. |
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| ISSN: | 1997-4884 2618-0707 |