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Prediction of Fractional Hold-Up in RDC ColumnUsing Artificial Neural Network

Authors: Suhayla Akkar سهيلة عكار --- Adel Al-Hemiri عادل احمد عوض
Journal: Iraqi Journal of Chemical and Petroleum Engineering المجلة العراقية للهندسة الكيمياوية وهندسة النفط ISSN: 19974884/E26180707 Year: 2007 Volume: 8 Issue: 4 Pages: 31-37
Publisher: Baghdad University جامعة بغداد


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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