Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network - Al-Hemiri, Adel; Akkar, Suhayla (Iraqi Journal of Chemical and Petroleum Engineering, 2007)
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 611measurements 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 thedeveloped ANN correlation noticeably improved prediction of dispersed phase hold up. The developed correlation alsoshows better prediction over a wide range of operation parameters in RDC columns.