Simulation of an Industrial Wastewater Treatment Plant by Up-flow Anaerobic Fixed Bed Bioreactor Based on an Artificial Neural Network

Abstract

Given the variable nature of industrial wastewaters, the appropriate operation of an industrial wastewater treatment plant (WWTP) is a prerequisite for keeping process stability at ideal conditions. In this respect, an artificial neural network (ANN) can be a powerful device for the prediction of treatment performance. This study assessed some qualitative parameters of industrial wastewater (Amol Industrial Estate) during a one-year operating period. The wastewater treatment process consisted of an equalization tank, up-flow anaerobic fixed bed (UAFB) bioreactor, activated sludge tank, sedimentation tank, and chlorination basin. The ANN was utilized to estimate the system efficiency of the UAFB process. The outcomes demonstrated an extraordinary arrangement between the real and simulated data (R2 > 0.8). This model supplied a proper device for forecasting the implementation of WWTPs. Continuous checking elements could be used for the simulation of wastewater specifications.