Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
2 results
Search Results
Item Prediction of water quality indices by regression analysis and artificial neural networks(2008) Rene, E.R.; Saidutta, M.B.The quality of wastewater generated in any process industry is generally indicated by performance indices namely BOD, COD and TOC, expressed in mg/L. The use of TOC as an analytical parameter has become more cornmon in recent years especially for the treatment of industrial wastewater. In this study, several empirical relationships were established between BOD and COD with TOC using regression analysis, so that TOC can be used to estimate the accompanying BOD or COD. A new, the use of Artificial Neural Networks has been explored in this study to predict the concentrations of BOD and COD, well in advance using some easily measurable water quality indices. The total data points obtained from a refinery wastewater (143) were divided into a training set consisting of 103 data points, while the remaining 40 were used as the test data. A total of 12 different models (Al-A12) were tested using different combinations of network architecture. These models were evaluated using the % Average Relative Error values of the test set. It was observed that three models gave accurate and reliable results, indicating the versatility of the developed models.Item Solar assisted photocatalytic degradation of organic pollutants in the presence of biogenic fluorescent ZnS nanocolloids(Elsevier Ltd, 2019) Uddandarao, P.; Hingnekar, T.A.; Mohan Balakrishnan, R.M.; Rene, E.R.The main aim of this study was to ascertain the photocatalytic degradation of organic pollutants present in aqueous phase using fluorescent biogenic ZnS nanocolloids produced from an endophytic fungus Aspergillus flavus. The degradation studies were carried out using different organic pollutants such as methyl violet (MV), 2,4-dichlorophenoxyacetic acid (2,4-D) and paracetamol (PARA) for 120 min, 270 min and 240 min, respectively, at pH varying from 3.0 to 11.0. The results from this study indicate that the degradation efficiency of ZnS nanocolloids for MV, 2,4-D and PARA were 87%, 33% and 51%, respectively, at the optimum concentration of 100 mg/L of the tested organic pollutants. At different time intervals, the samples were analyzed for their chemical oxygen demand (COD) and total organic carbon (TOC) contents. The reduction of COD and TOC were 78% and 74% for MV at 120 min; 55.5% and 57.2% for 2,4-D at 270 min and 47.6% and 44.5% for PARA at 240 min, respectively. The degradation pathway was determined based on the mass spectrum and the intermediates formed; in addition, the interaction between organic pollutants and nanocolloids was also elucidated based on atomic force microscopy (AFM) and fluorescence spectrum. © 2019 Elsevier Ltd