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Metali Sarkar,Vikas K. Sangal,Haripada Bhunia 대한환경공학회 2020 Environmental Engineering Research Vol.25 No.3
Hydrodynamic study of Activated Sludge Process (ASP) is important to optimize the reactor performance and detect anomalies in the system. Residence time distribution (RTD) study has been performed using LiCl as tracer on a pilot scale aeration tank (AT) and ASP, treating the pulp and paper mill effluent. The hydraulic performance and treatment efficiency of the AT and ASP at different operating parameters like residence time, recycle rate was investigated. Flow anomalies were identified and based on the experimental data empirical models was suggested to interpret the hydrodynamics of the reactors using compartment modelling technique. The analysis of the RTD curves and the compartment models indicated increase in back-mixing ratio as the mean hydraulic retention time (MHRT) of the tank was increased. Bypassing stream was observed at lower MHRT. The fraction of dead zone in the tank increased by approximate 20-25% with increase in recycle rate. The fraction of the stagnant zone was found well below 5% for all performed experiments, which was under experimental error. The substrate removal of 91% for Chemical oxygen demand and 96% for Biochemical oxygen demand were observed for the ASP working at a hydraulic mean residence time 39 h MRT with a 20% recycling of activated sludge.
Alok Garg,Gaganpreet Kaur,Vikas K. Sangal,Pramod K. Bajpai,Sushant Upadhyay 대한환경공학회 2020 Environmental Engineering Research Vol.25 No.5
The present work deals with the modeling and optimization of photocatalytic degradation (UV/TiO₂) of aqueous solution of Acid Red 114 (AR114) dye using Artificial Neural Networks (ANN) and RSM. Photocatalytic treatment of AR114 has been executed using suspension TiO₂catalyst for commercial applications exposed to ultraviolet irradiation in a shallow pond reactor. ANN optimization has been applied to for predicting the behavior of photocatalysis. The input parameters used for analysis of aqueous dye solution are - TiO₂ dose, pH of the dye solution, initial dye concentration, UV light intensity, time and area/volume, and time whereas the outputs are evaluated in form of degradation and decolorization efficiency of AR114. The outcomes of ANN optimization have been experimentally validated. Results achieved establish ANN modeling as a good predictive model. Parameteric optimization using multi-parameter optimization has been employed with desirability function approach. Results obtained from RSM are in line as per the results of ANN modeling as well as experimental. First order kinetics is use to effectively express degradation and decolorization of AR114 dyes. Total organic carbon (TOC) removal and GC-MS study of the dye shows the total mineralization and formation of non-toxic intermediate products.