D. Krishna

Removal of Chromium from Aqueous Solution by Custard Apple (Annona Squamosa) Peel Powder as Adsorbent

Chromium has been widely used in various industries like textile, leather, chemical manufacture, metal finishing, paint industry and many other industries. Since hexavalent chromium is a priority toxic, mutagenic and carcinogenic chemical when present in excess, it is very much required to remove chromium from effluents before allowing it to enter any water system or on to land. In the present study, the removal of hexavalent chromium by adsorption on the Custard apple peel powder as adsorbent has been investigated in the batch experiments. The agitation time, the adsorbent size, adsorbent dosage, initial chromium concentration, temperature and the effect of solution pH are studied. The Freundlich model for Cr (VI) adsorption onto Custard apple peel powder is proved to be the best fit followed by Langmuir model and Tempkin model based on high regression coefficient R^2 value. The adsorption behavior is described by a pseudo second order kinetics. The maximum metal uptake is found to be 7.874 mg/g. The morphology on the surface of adsorbents and also the confirmation of chromium binding on adsorbent surface at different stages were obtained by scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) analysis. The results obtained in this study illustrate that Custard apple peel powder is expected to be an effective and economically viable adsorbent for hexavalent chromium removal from industrial waste water.

Response Surface Modeling and Optimization of Chromium (Vi) Removal From Aqueous Solution Using Borasus Flabellifer Coir Powder

The potential use of Borasus flabellifer coir powder for the removal of chromium (VI) from aqueous solution has been investigated in batch mode experiments. Percentage removal of chromium (VI) is found to be 97.6% at pH 2, amount of adsorbent dosage of 0.5 g in 50 mL solution and temperature of 303 K. Influences of parameters like initial chromium (VI) concentration (5-30 mg/L), pH (1-3), and biomass dosage (10-14 g/L) on chromium (VI) adsorption were examined using response surface methodology. The Box-Behnken experimental design in response surface methodology was used for designing the experiments as well as for full response surface estimation and 15 trials as per the model were run. The optimum conditions for maximum removal of chromium (VI) from an aqueous solution of 20 mg/L were as follows: adsorbent dosage (10.1869 g/L), pH 1.9 and initial chromium (VI) concentration (6.3244 mg/L). The high correlation coefficient (R^2 =0.989) between the model and the experimental data showed that the model was able to predict the removal of chromium (VI) from aqueous solution using B. flabellifer coir powder efficiently.

Tuning of PID Controllers for Unstable Continuous Stirred Tank Reactors

Tuning Proportional Integral and Derivative (PID) controllers for unstable Second Order Plus Time Delay systems with a Zero (SOPTDZ), based on internal model control (IMC) and stability analysis (SA) principles is proposed. The controllers designed by the proposed methods are used to control unstable jacketed Continuous Stirred Tank Reactors (CSTR), carrying out irreversible first order reaction. The performance of proposed controllers is compared with the synthesis method. Simulation results on nonlinear unstable continuous stirred tank reactors and transfer function models are presented to the show the efficiency of the proposed controllers.

Artificial Neural Network and Response Surface Methodology Approach for Modeling and Optimization of Chromium (VI) Adsorption from Waste Water using Ragi Husk Powder

Abstract An artificial neural network (ANN) and response surface methodology models were developed to predict the removal efficiency of chromium (VI) from waste water using Ragi husk powder as adsorbent. Both of the models were used to study the effect of operational parameters such as pH, adsorbent dosage and initial chromium (VI) concentration and to optimize the conditions for the maximum chromium (VI) adsorption. The ANN model for the adsorption of chromium (VI) was developed by a single-layer feed-forward back-propagation network with 14 neurons in the hidden layer to obtain minimum mean squared error. A tansigmoid was used as transfer function for input and purelin for output layers. The response surface methodology model was developed using Box–Behnken design technique. The high correlation coefficient (R2 = 0.996 in ANN and 0.993 in response surface methodology models) between the predicted data and the experimental data showed that both of the models were capable of envisaging the chromium (VI) removal. The pattern search method in a genetic algorithm was applied to obtain optimum values of input parameters for the maximum removal of chromium (VI) for the ANN model. A comparison of the models for the optimization of input parameters is also discussed.

Artificial Neural Network (ANN) Approach for Modeling Chromium (VI) Adsorption From Aqueous Solution Using a Borasus Flabellifer Coir Powder

An artificial neural network (ANN) model was developed to predict the removal efficiency of chromium (VI) from aqueous solution using a Borasus flabellifer coir powder as adsorbent. The effect of operational parameters such as pH, adsorbent dosage, and initial chromium (VI) concentration are studied to optimize the conditions for the maximum removal of chromium (VI) ions. The ANN model was developed using 54 experimental data points for training and 16 data points for testing by a single layer feed forward back propagation network with 18 neurons to obtain minimum mean squared error (MSE). A tansigmoid was used as transfer function for input and purelin for output layers. The high correlation coefficient (R^2_(average-ANN)=0.992) between the model and the experimental data showed that the model was able to predict the removal of chromium (VI) from aqueous solution using Borasus flabellifer coir powder efficiently. Pattern search method in genetic algorithm was applied to get optimum values of input parameters for the maximum removal of chromium (VI).

Response Surface Modeling and Optimization of Cu (II) Removal from Waste Water Using Borasus Flabellifer Coir Powder

In the present work, Cu (II) removal from waste water was investigated using ＂Borasus flabellifer＂ coir powder as adsorbents in batch mode experiments. The effect of such parameters as initial Cu (II) concentration (20-60mg/L), pH (5-7), and biomass dosage (10-14g/l) on Cu (II) removal have been investigated using response surface methodology. The Box-Behnken experimental design in response surface methodology was used for designing the experiments as well as for full response surface estimation and 15 trials as per the model were run. The optimum input parameters for maximum removal of Cu (II) from an aqueous solution of 20 mg/L were as follows: biomass dosage (12.3646g/L), pH (6.30642) and initial Cu (II) concentration (25.0414mg/L). The high correlation coefficient (R^2=0.977) between the model and the experimental data showed that the model was able to predict the removal of Cu (II) from waste water using ＂Borasus flabellifer＂ coir powder efficiently.

Tuning of PID Controllers for Continuous Stirred Tank Reactors

Abstract Tuning of proportional integral and derivative (PID) controllers for stable SOPTDZ (second order plus time delay with a zero) systems is proposed. The PID controller was designed based on internal model control and stability analysis principles. The proposed controllers were applied to the various stable transfer function models of jacketed CSTR, isothermal CSTR carrying out Van de Vusse reaction and a bioreactor. Simulation results on various transfer function models and on non-linear model equations of jacketed CSTR carrying first-order exothermic reaction, isothermal constant volume CSTR carrying out Van de Vusse reaction and a bioreactor are given to show the effectiveness of the proposed PID controllers. The performance under model uncertainty is also studied considering perturbation in one parameter at a time. The performance of the proposed controllers is compared with the controller designed by direct synthesis method.