• Journal of Korean Society of Environmental Engineers
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• v.33 no.3
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• pp.149-156
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• 2011

This experimental design and response surface methodology (RSM) have been applied to the investigation of the electro-UV-ultrasonic complex process for the disinfection of E. coli in the water. The disinfection reactions of electro-UV-ultrasonic process were mathematically described as a function of parameters power of electrolysis ($X_1$), UV ($X_2$), and ultrasonic process ($X_3$) being modeled by use of the Box-Behnken technique, which was used for fitting 2nd order response surface model. The application of RSM yielded the following regression equation, which is empirical relationship between the residual E. coli number (Ln CFU) in water and test variables in coded unit: residual E. coli number (Ln CFU) = 23.69 - 3.75 Electrolysis - 0.67 UV - 0.26 Ultrasonic - 0.16 Electrolysis UV + 0.05 Electrolysis Ultrasonic + 0.27 $Electrolysis^2$ + 0.14 $UV^2$ - 0.01 $Ultrasonic^2$). The model predictions agreed well with the experimentally observed result ($R^2$ = 0.983). Graphical 2D contour and 3D response surface plots were used to locate the optimum range. The estimated ridge of maximum response and optimal conditions for residual E. coli number (Ln CFU) using 'numerical optimization' of Design-Expert software were 1.47 Ln CFU/L and 6.94 W of electrolysis, 6.72 W of UV and 14.23 W of ultrasonic process. This study clearly showed that response surface methodology was one of the suitable methods to optimize the operating conditions and minimize the residual E. coli number of the complex disinfection.

• Korean Chemical Engineering Research
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• v.54 no.1
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• pp.44-51
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• 2016

The powder core, conventionally fabricated from iron particles coated with insulator, showed large eddy current loss under high frequency, because of small specific resistance. To overcome the eddy current loss, the increase in the specific resistance of powder cores was needed. In this study, copper oxide coating onto electrically conductive iron particles was performed using a planetary ball mill to increase the specific resistance. Coating factors were optimized by the Response surface methodology. The independent variables were the CuO mass fraction, mill revolution number, coating time, ball size, ball mass and sample mass. The response variable was the specific resistance. The optimization of six factors by the fractional factorial design indicated that CuO mass fraction, mill revolution number, and coating time were the key factors. The levels of these three factors were selected by the three-factors full factorial design and steepest ascent method. The steepest ascent method was used to approach the optimum range for maximum specific resistance. The Box-Behnken design was finally used to analyze the response surfaces of the screened factors for further optimization. The results of the Box-Behnken design showed that the CuO mass fraction and mill revolution number were the main factors affecting the efficiency of coating process. As the CuO mass fraction increased, the specific resistance increased. In contrast, the specific resistance increased with decreasing mill revolution number. The process optimization results revealed a high agreement between the experimental and the predicted data ($Adj-R^2=0.944$). The optimized CuO mass fraction, mill revolution number, and coating time were 0.4, 200 rpm, and 15 min, respectively. The measured value of the specific resistance of the coated pellet under the optimized conditions of the maximum specific resistance was $530k{\Omega}{\cdot}cm$.