DEVELOPING CORRELATION FOR PREDICTION OF GAS HOLDUP USING GENETIC ALGORITHM

Abstract

This paper deals with the prediction of the overall gas holdup g in slurry bubble column depending on wide range of databank of around 69 measurements collected from the open literature. Correlation for gas holdup was derived using combination of dimensionless analysis and Genetic Algorithm. The correlation takes in consideration the physical properties of liquid and gas that effect on gas holdup and therefore effect on the design of slurry bubble column. Also a comparison between the correlation driven from Genetic Algorithm and a new correlation driven using Quasi-Newton method was made and found that the Average Absolute Relative Error (AARE) was 10.8 % and 16.1%, respectively. This shows that the use of Genetic Algorithm is improve the prediction of gas holdup in slurry bubble column.