The Experimental studies of sugar effluent by electrochemical – oxidation in Batch reactor using Artificial Neural Network and Response Surface Methods” elucidates the reduction of organics in sugar effluents through electrochemical oxidation technique. Effect of parameters such as current density and mediator concentration on % COD reduction and power consumption for batch reactor without recirculation and the influence of current density, volume and flow rate on % COD reduction, power consumption, mass flux and rate constant for batch reactor with recirculation has been studied and analyzed.
It was found out that, the % COD removal efficiency can be improved by the addition of mediator (NaCl). The maximum % COD reduction of 80.74 % was achieved at current density of 5 A/dm2 and 5 gpl of mediator concentration for Batch reactor. A maximum % COD reduction of 64.28 was achieved at flow rate 20 lph, current density 3 A/dm2, Volume 5 litre for batch reactor with recirculation. Artificial neural network has been used to simulate the batch reactor without recirculation results and the predicted values are then compared with the experimental values. Response surface methodology has been used to study the effects of various parameters on % COD reduction, power consumption and mass flux for batch reactor with recirculation and quadratic models have been generated.
