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Prediction of Fractional Hold-Up in RDC ColumnUsing Artificial Neural Network | ||
| Iraqi Journal of Chemical and Petroleum Engineering | ||
| Article 1, Volume 8, Issue 4, 2007, Pages 31-37 | ||
| Authors | ||
| Suhayla Akkar; Adel Al-Hemiri | ||
| Abstract | ||
| 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. | ||
| Keywords | ||
| dispersed phase hold up; RDC; artificial neural networks | ||
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