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Chun Ming Chew,M.K. Aroua,M.A. Hussain 한국공업화학회 2017 Journal of Industrial and Engineering Chemistry Vol.45 No.-
In this work, a novel approach combining first principle equation of Darcy’s law on cake filtration andartificial neural network (ANN) predictivemodels were utilized to represent the dead-end ultrafiltration(UF) process. Common on-line data available in most industrial-scale UF membrane water treatmentplant such as feed water turbidity, filtration time and transmembrane pressure were used as inputsparameters. An UF pilot plant was set up to carry out these experiments. This hybridmodelling approachconsisting of cake filtration and ANN models have shown promising results to predict the specific cakeresistance and total suspended solids of the feed water with good accuracy. These two filtrationparameters are often considered as indicators for membrane fouling propensity. Sensitivity analysis hasindicated strong linear correlation between feed water turbidity and specific cake resistance in the UFprocess. The hybrid model provides an alternative method to estimate these parameters besides theconventional laboratory analysis. This practical modelling approach will be beneficial to industrial-scaleUF membrane water treatment plant operations to predict the fouling propensity of the UF process basedon commonly available on-line data and simple laboratory analysis.