Numerical modeling and optimization of wastewater treatment using porous polymeric membranes

A new modeling approach was developed for prediction of ammonia removal from water by means of porous membranes. The model was based on adaptive neuro-fuzzy interface system (ANFIS) to simulate ammonia stripping from water by means of hollow-fiber membrane contactors. The predictions aimed to obtain optimum conditions for ammonia stripping using the Taguchi method. The initial concentrations of ammonia, pH of the ammonia solution, velocity of the feed, and the presence of excess ions in the ammonia feed solution were considered as the input properties. On the other hand, mass transfer coefficient was considered as output. The prediction results revealed that the pH of the ammonia feed has a significant effect on the separation of ammonia from water. The results also showed that the prediction of ANFIS model and experimental data match well and that the model can be used for prediction of porous membranes. Furthermore, simulated annealing was also used to determine controllable conditions to find the highest mass transfer coefficient. POLYM. ENG. SCI., 2013. (c) 2012 Society of Plastics Engineers