Prediction of fractional hold-up in RDC column using artificial neural network

Abstract EN

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.