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The present study investigated the removal efficiency of ammonia nitrogen from simulated wastewater by waste foundry sand based on 120 batch experiments which were modeled by three-layer artificial neural network technique. Contact time (5-120 min), pH of the aqueous solution (3-10), concentration (400-600 mg/L), sorbent dosage (20-120 g/100 mL) and agitation speed (50-250 rpm) were studied. Results showed that the best values of the above parameters were time of  90 min, pH= 10, 400 mg/L, dosage of 90g/100 mL and 200 rpm respectively with removal efficiency equals to 95%. The sorption process was described in a good manner using ANN model which consisted of the tangent sigmoid and linear transfer functions at hidden and output layers respectively with 8 neurons and the maximum sorption capacity was 0.9 mg/g. The sensitivity analysis signified that the relative importance of contact time equal to 36.9% and it is the influential parameter in the sorption of ammonia nitrogen. However, the relative importance of other parameters was agitation speed of 27.43%, WFS dosage of 17.32%, pH of 9.86% and initial concentration of 9.39%.

Simulation of Ammonia Nitrogen Removal from Simulated Wastewater by Sorption onto Waste Foundry Sand Using Artificial Neural Network