Treatment of oily wastewater using low cost ceramic membrane: Comparative assessment of pore blocking and artificial neural network models

Abstract

This work addresses the performance and modeling of the separation of oil-in-water (o/w) emulsions using low cost ceramic membrane that was prepared from inorganic precursors such as kaolin, quartz, feldspar, sodium carbonate, boric acid and sodium metasilicate. Synthetic o/w emulsions constituting 125 and 250 mg/L oil concentrations were subjected to microfiltration (MF) using this membrane in batch mode of operation with varying trans-membrane pressure differentials (Δ P) ranging from 68.95 to 275.8 kPa. The membrane exhibited 98.8% oil rejection efficiency and 5.36 × 10 −6 m 3/m 2 s permeate flux after 60 min of experimental run at 68.95 kPa trans-membrane pressure and 250 mg/L initial oil concentration. These experimental investigations confirmed the applicability of the prepared membrane in the treatment of o/w emulsions to yield permeate streams that can meet stricter environmental legislations (<10 mg/L). Subsequently, the experimental flux data has been subjected to modeling study using both conventional pore blocking models as well as back propagation-based multi-layer feed forward artificial neural network (ANN) model. Amongst several pore blocking models, the cake filtration model has been evaluated to be the best to represent the fouling phenomena. ANN has been found to perform better than the cake filtration model for the permeate flux prediction with marginally lower error values.