Akepati S. Reddy

Electrocoagulation removal of Cr(VI) from simulated wastewater using response surface methodology.

The present study envisages the performance of a laboratory scale electrocoagulation system for the removal of Cr(VI) from 100 mg l(-1) solution using Al-Al electrodes with an effective surface area of 100 cm(2), and placed 15 mm apart. The interaction between voltage x time, and amperage x time best explained the Cr(VI) reduction efficiency with the coefficient of determination (R(2)) being 0.8873 and 0.9270 respectively. Similarly, the square root of energy consumption in Cr(VI) reduction had a linear correlation with voltage x time (R(2)=0.8949), whereas, amperage x time better explained energy consumption (R(2)=0.9400). Response surface methodology was used for the optimization of process variables (pH, voltage and treatment time), response modeling and predictions. Maximum Cr(VI) reduction efficiency of 90.4% was achieved at pH 5, 24 V and 24 min treatment time, and the treatment consumed 137.2 KWh m(-3) of electrical energy. Multiple response optimization for maximizing Cr(VI) reduction efficiency and minimizing energy consumption showed 49.6% Cr(VI) removal at pH 5, 12.8 V and 24 min treatment time. The response models developed explained 95.2% variability for Cr(VI) reduction efficiency and 99.4% variability for energy consumption. Results of the prediction models were validated through laboratory scale batch experiments.

Multivariate analysis for assessing the quality of stormwater from different Urban surfaces of the Patiala city, Punjab (India)

Land use modifications associated with urbanization, such as clearance of vegetation, replacement of previously pervious areas with impervious surfaces and drainage channel modifications, result in increased runoff volumes, which often create flooding hazards and increase pollutant transport. An attempt has been made in the present study to investigate stormwater quality from five different urban sub-watersheds (that differ in land use and development activities) in the city of Patiala, India. The five sub-watersheds have similar geological, topographical and climatic conditions and were chosen to minimize the effect of these characteristics on stormwater quality and quantity. Stormwater samples were collected during six storm events between April 2010 and March 2011 and analyzed for BOD5, COD, TSS, TDS, Oil and Grease, TKN, Total P, Coliforms and Heavy Metals (Zn, Cd, Ni, Pb, Fe and Cu). Results of the investigation indicate a strong correlation between land use and development activities and the resulting stormwater quality. TSS, COD and Oil and Grease were found to be major pollutants in surface runoff generated from commercial and urbanized catchments (all exceeded the surface water quality standards developed by Central Pollution Control Board, India). The water quality of the smaller residential catchment was better as compared to other catchments. Principal component analysis was investigated to identify linkages between stormwater quality and urban surface types. It was also confirmed through regression analysis that both antecedent dry period and rainfall intensity have telling influence on stormwater quality. Results obtained can provide practical information for improved stormwater management.

Development of Multiple Linear Regression Models for Predicting the Stormwater Quality of Urban Sub-Watersheds

Stormwater management at urban sub-watershed level has been envisioned to include stormwater collection, treatment, and disposal of treated stormwater through groundwater recharging. Sizing, operation and control of the stormwater management systems require information on the quantities and characteristics of the stormwater generated. Stormwater characteristics depend upon dry spell between two successive rainfall events, intensity of rainfall and watershed characteristics. However, sampling and analysis of stormwater, spanning only few rainfall events, provides insufficient information on the characteristics. An attempt has been made in the present study to assess the stormwater characteristics through regression modeling. Stormwater of five sub-watersheds of Patiala city were sampled and analyzed. The results obtained were related with the antecedent dry periods and with the intensity of the rainfall event through regression modeling. Obtained regression models were used to assess the stormwater quality for various antecedent dry periods and rainfall event intensities.

RSM and ANN-GA Experimental Design Optimization for Electrocoagulation Removal of Chromium

The present study was aimed at optimizing electrocoagulation removal of hexavalent chromium using iron electrodes. Process variables investigated were chromium concentration, pH, current density (or voltage) and treatment time, and the responses measured were chromium removal efficiency and energy consumption. Using the experimental results, the treatment process was modeled by response surface methodology (RSM) and by artificial neural network-genetic algorithm (ANN-GA). The optimum current density for energy efficient chromium removal was found to be 20–40 A/m2 for treatment time of 10 min. Current density beyond the optimum range had a cascading effect on chromium removal efficiency.

Numerical solution of stochastic partial differential difference equation arising in reliability engineering

In this paper, a numerical method is proposed to solve the transient state of Markovian system of equations. Such equations appear in the field of reliability engineering for systems having variable failure and repair rates. Generally, steady state behaviour of the system model is studied due to some constraint on obtaining transient state solution. The proposed method helps to determine the probability values, by utilizing finite difference scheme iteratively in conjunction with the results of integral appearing in stochastic differential difference equation obtained using supplementary variable technique. This method also uses the Lagranges method to interpolate the missing value of repair rates of the system wherever required in computation. Results thus obtained are found to be efficient for studying the transient state behaviour of the system.

Characterization and prediction of stormwater runoff quality in sub-tropical rural catchments

Due to scarcity of local data on stormwater pollution levels and rainfall-runoff generation process, very few attempts have been made towards the management of stormwater in sub-tropical rural catchments. An attempt has been made in the present study to characterize and predict the stormwater runoff characteristics using regression modeling from five rural catchments in north-west India. Stormwater samples and flow data were collected from 75 storm events. Samples were analyzed for pH, total suspended solids (TSS), 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), total kjeldhal nitrogen (TKN), total phosphorous (TP), nitrate-nitrogen (NO3-–N), total coliform count (TC), fecal coliform count (FC), Zn, Cu and Fe. It was found that size of the catchment and the land use practices influenced the stormwater quality even in predominantly rural areas, otherwise thought to be homogeneous. The results obtained were related with the antecedent dry days (ADD) and average rainfall. ADD was found to be positively correlated with pollutant loads whereas average rainfall showed negative correlation. The study highlights the importance of ADD in causing greater mean pollutant concentrations except for TKN, TP and NO3-–N. Regression models were developed for the studied catchments to estimate mean pollutant concentrations as a function of rainfall variables. Results revealed that measured pollutant concentrations demonstrated high variability with ADD and average rainfall in small rural catchments, whereas in large catchments, factors like land use, extent of imperviousness etc. resulted in low predictability of measured parameters.

Textile dyebath wastewater decolorization by electrolytic processes: response surface optimization using IV-optimal design

AbstractThe aim of the present study is to investigate the potential of electrolytic process on textile dyebath dump wastewater (sulfate concentration ~30 g/L) collected from the cotton fabric dyeing process to remove color and COD concentration. Four different electrode combinations were tested i.e. stainless steel–stainless steel, iron–iron, aluminum–aluminum, and iron (anode)–aluminum (cathode) for best removal efficiency and minimum power consumption along with sludge generation rate. The significant process parameters (voltage/current density and treatment time) were optimized for real industrial wastewater using response surface methodology approach. COD removal efficiency and color removal efficiency were taken as two responses. The best electrode combination was Fe–Al to achieve 75% COD removal efficiency and 91% color removal efficiency. The optimized process conditions are 7.6 V (1242 A/m2) and 14 min treatment time consuming 59 kWh/kg of COD removal with sludge generation rate of 24.1 g/L.

Performance of a new ceramic microfiltration membrane based on kaolin in textile industry wastewater treatment

Abstract A ceramic microfiltration membrane with a porosity of 40.2%, mean pore diameter of 0.27 μm, and a flexural strength of 55 MPa was prepared and applied for treatment of two types of textile dye-bath effluents. The ceramic membrane had a water permeability of 1376 L/m2.h.bar and showed excellent corrosion resistance against basic medium. Considerable removal of COD (25%), TDS (31%), BOD (39%), turbidity (21%), sulphates (34%), chlorides (33%), and color (26%) from textile effluents was achieved in the microfiltration treatment along with complete (100%) removal of TSS. This study revealed that filtration of textile effluents using a sub-micron range ceramic membrane (0.27 μm) is more effective than traditional microfiltration membranes (2–10 μm). The flux data fitted well with the standard pore blocking model indicating that the removal of various contaminants is due to adsorption of solutes on the interior surfaces of membrane pores.