TY - JOUR AU - Ayad Faisal AU - Laith Naji PY - 2019/03/31 Y2 - 2024/03/29 TI - Simulation of Ammonia Nitrogen Removal from Simulated Wastewater by Sorption onto Waste Foundry Sand Using Artificial Neural Network JF - Association of Arab Universities Journal of Engineering Sciences JA - ASSOC ARA UNIV J ENG SCI VL - 26 IS - 1 SE - Articles DO - 10.33261/jaaru.2019.26.1.004 UR - https://jaaru.org/index.php/auisseng/article/view/262 AB - 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%. ER -