Faculty Publications
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Item Artificial intelligence models for predicting the performance of biological wastewater treatment plant in the removal of Kjeldahl Nitrogen from wastewater(Springer Verlag, 2017) Manu, D.S.; Thalla, A.K.The current work demonstrates the support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) modeling to assess the removal efficiency of Kjeldahl Nitrogen of a full-scale aerobic biological wastewater treatment plant. The influent variables such as pH, chemical oxygen demand, total solids (TS), free ammonia, ammonia nitrogen and Kjeldahl Nitrogen are used as input variables during modeling. Model development focused on postulating an adaptive, functional, real-time and alternative approach for modeling the removal efficiency of Kjeldahl Nitrogen. The input variables used for modeling were daily time series data recorded at wastewater treatment plant (WWTP) located in Mangalore during the period June 2014–September 2014. The performance of ANFIS model developed using Gbell and trapezoidal membership functions (MFs) and SVM are assessed using different statistical indices like root mean square error, correlation coefficients (CC) and Nash Sutcliff error (NSE). The errors related to the prediction of effluent Kjeldahl Nitrogen concentration by the SVM modeling appeared to be reasonable when compared to that of ANFIS models with Gbell and trapezoidal MF. From the performance evaluation of the developed SVM model, it is observed that the approach is capable to define the inter-relationship between various wastewater quality variables and thus SVM can be potentially applied for evaluating the efficiency of aerobic biological processes in WWTP. © 2017, The Author(s).Item The combined effects of carbon/nitrogen ratio, suspended biomass, hydraulic retention time and dissolved oxygen on nutrient removal in a laboratory-scale anaerobic–anoxic–oxic activated sludge biofilm reactor(IWA Publishing, 2018) Manu, D.S.; Thalla, A.K.The current trend in sustainable development deals mainly with environmental management. There is a need for economically affordable, advanced treatment methods for the proper treatment and management of domestic wastewater containing excess nutrients (such as nitrogen and phosphorus) which can cause eutrophication. The reduction of the excess nutrient content of wastewater by appropriate technology is of much concern to the environmentalist. In the current study, a novel integrated anaerobic–anoxic–oxic activated sludge biofilm (A2O-AS-biofilm) reactor was designed and operated to improve the biological nutrient removal by varying reactor operating conditions such as carbon to nitrogen (C/N) ratio, suspended biomass, hydraulic retention time (HRT) and dissolved oxygen (DO). Based on various trials, it was seen that the A2O-AS-biofilm reactor achieved good removal efficiencies with regard to chemical oxygen demand (95.5%), total phosphorus (93.1%), ammonia nitrogen concentration (NH4þ-N) (98%) and total nitrogen (80%) when the reactor was maintained at C/N ratio of 4, suspended biomass of 3 to 3.5 g/L, HRT of 10 h, and DO of 1.5 to 2.5 mg/L. Scanning electron microscopy (SEM) of suspended and attached biofilm showed a dense structure of coccus and bacillus bacteria with the diameter ranging from 0.3 to 1.2 ?m. The Fourier transform infrared (FTIR) spectroscopy results indicated phosphorylated macromolecules and carbohydrates mix or bind with extracellular proteins in exopolysaccharides. © IWA Publishing 2018.