TY - JOUR ID - TI - Prediction of Fractional Hold-Up in RDC ColumnUsing Artificial Neural Network AU - Suhayla Akkar سهيلة عكار AU - Adel Al-Hemiri عادل احمد عوض PY - 2007 VL - 8 IS - 4 SP - 31 EP - 37 JO - Iraqi Journal of Chemical and Petroleum Engineering المجلة العراقية للهندسة الكيمياوية وهندسة النفط SN - 19974884 26180707 AB - 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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