• Journal of the Korean Chemical Society
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• v.57 no.6
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• pp.769-777
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• 2013

The effect of operating conditions (temperature and the partial pressures of H2 and CO) on the reaction rate of Fischer-Tropsch synthesis (FTS) were investigated by carrying out experiments according to a Box-Behnken design (BBD), and were mathematically modeled by using response surface methodology (RSM). The catalyst used was a nano-structured cobalt/manganese oxide catalyst, which was prepared by thermal decomposition. The rate of synthesis was measured in a fixed-bed micro reactor with $H_2/CO$ molar feed ratio of 0.32-3.11 and reactor pressure in the range of 3-9.33 bar at space velocity of $3600h^{-1}$ and a temperature range of 463.15-503.15 K, under differential conditions (CO conversion below 2%). The results indicated that in the present experimental setup, the temperature and the partial pressure of CO were the most significant variables affecting reaction rate. Based on statistical analysis the quadratic model of reaction rate of FTS was highly significant as p-value 0.0002.

• Environmental Engineering Research
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• v.24 no.1
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• pp.24-30
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• 2019

The present study explores the applicability of response surface methodology (RSM) in conjunction with central composite design (CCD) matrix to statistically optimize ettringite crystallization process for the removal of sulphate from landfill leachate. A three factor-five coded level CCD with 20 runs, was performed to estimate the best fitted model. The RSM results indicated that the fitted quadratic regression model could be appropriate to predict sulfate removal efficiency. The pH was identified as the most dominant parameter affecting sulphate removal. 61.6% of maximum sulphate removal efficiency was obtained at pH of 11.06 for a 1.87 of $Ca/SO_4$ and 0.51 of $Al/SO_4$ molar ratios. The operating cost for ettringite crystallization at optimized conditions was calculated to be 0.52 $/$m^3$. The significance of independent variables and their interactions were tested by analysis of variance. Scanning electron microscope (SEM) and SEM coupled with energy dispersive X-Ray spectroscopy results confirmed the formation of ettringite crystal and were used to describe its morphology features.

• Transactions of the Korean hydrogen and new energy society
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• v.31 no.6
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• pp.546-552
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• 2020

In this study, optimization research was conducted through statistical analysis with the aim of maximizing the efficiency of organic matter reduction and hydrogen production by applying electrolysis process at sewage treatment plant. Statistical analysis and optimal operating conditions of organic matter removal efficiency and H2 generation, which varied with various conditions in the electrolysis process, were derived using response surface methodology. As a result, 1,268 μS/cm of conductivity, 350 A current, and pH 3.2 was found to be the optimum condition to reach the desired value as 38% of organic matter reduction and 2.58 L/min of H2 production. The experiment also determined that the optimization study was reliable. Base on this study, it was confirmed that the removal of organic matter and hydrogen production could be stably by applying the electrolysis process in the sewage treatment plant.

• 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.

• Journal of the Korean Chemical Society
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• v.58 no.2
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• pp.198-204
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• 2014

In this present study, bagasse based pulp and paper industry wastewater was treated under different operating conditions such as initial pH (6-8), temperature ($25-35^{\circ}C$) and contact time (3-7 days) by using Bacillus subtilis. Response surface methodology (RSM) coupled with Box-Behnken response surface design (BBD) was employed to investigate the effect of process variables on the responses such as turbidity, biological oxygen demand (BOD) and chemical oxygen demand (COD) removal. The experimental data were analyzed by Pareto analysis of variance (ANOVA) and the second order polynomial models were developed. Interactive effects of the process variables on the responses were studied using plotting 3D response surface contour graph and the optimum process conditions were found to be: initial pH of 7, temperature of $30^{\circ}C$ and contact time of 5 days. Under these conditions, removal efficiencies of turbidity, BOD and COD were found to be 85%, 93% and 80% respectively which are close agreement with real experiments. These results indicate that the treatment of bagasse based pulp and paper industry wastewater using Bacillus subtilis is an effective and novel technique.

• Journal of the Korean Society of Safety
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• v.32 no.1
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• pp.27-32
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• 2017

The experimental design methodology was applied in the real scale coal-fired boiler to predict the various combustion properties according to the operating conditions and to assess the coal plant safety. Response surface method (RSM) was introduced as a design of experiment, and the database for RSM was provided with the numerical simulation of the coal-fired boiler. The three independent variables, high heating value of coal (HHV), overall stoichiometry excess air ratio (OST), and burner-side stoichiometry excess air ratio (BST), were set to characterize the cross section averaged NOx concentration and temperature distribution. The maximum NOx concentration was predicted accurately and mainly controlled by BST in the boiler. The parabola function was assumed for the zone averaged peak temperature distribution, and the prediction was in a fairly good agreement with the experiments except downstream. Also, the location of the peak temperature was compared with that of maximum NOx, which implies that thermal NOx formation is the main mechanism in the coal-fired boiler. These results promise the wide use of statistical models for the fast prediction and safety assessment.

• Nuclear Engineering and Technology
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• v.18 no.1
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• pp.38-47
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• 1986

A statistical procedure, which uses response surface method and Monte Carlo simulation technique, is proposed for analyzing the thermal margin of light water reactor core. The statistical thermal margin analysis method performs the best.estimate thermal margin evaluation by the probabilistic treatment of uncertainties of input parameters. This methodology is applied to KNU-1 core thermal margin analysis under the steady state nominal operating condition. Also discussed are the comparisons with conventional deterministic method and Improved Thermal Design Procedure of Westinghouse. It is deduced from this study that the response surface method is useful for performing the statistical thermal margin analysis and that thermal margin improvement is assured through this procedure.

• Nuclear Engineering and Technology
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• v.42 no.2
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• pp.219-230
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• 2010

In nuclear power plants (NPPs), periodic sensor calibrations are required to assure that sensors are operating correctly. By checking the sensor's operating status at every fuel outage, faulty sensors may remain undetected for periods of up to 24 months. Moreover, typically, only a few faulty sensors are found to be calibrated. For the safe operation of NPP and the reduction of unnecessary calibration, on-line instrument calibration monitoring is needed. In this study, principal component-based auto-associative support vector regression (PCSVR) using response surface methodology (RSM) is proposed for the sensor signal validation of NPPs. This paper describes the design of a PCSVR-based sensor validation system for a power generation system. RSM is employed to determine the optimal values of SVR hyperparameters and is compared to the genetic algorithm (GA). The proposed PCSVR model is confirmed with the actual plant data of Kori Nuclear Power Plant Unit 3 and is compared with the Auto-Associative support vector regression (AASVR) and the auto-associative neural network (AANN) model. The auto-sensitivity of AASVR is improved by around six times by using a PCA, resulting in good detection of sensor drift. Compared to AANN, accuracy and cross-sensitivity are better while the auto-sensitivity is almost the same. Meanwhile, the proposed RSM for the optimization of the PCSVR algorithm performs even better in terms of accuracy, auto-sensitivity, and averaged maximum error, except in averaged RMS error, and this method is much more time efficient compared to the conventional GA method.

• Journal of the Korean Chemical Society
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• v.57 no.6
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• pp.761-768
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• 2013

Removal of COD and TSS from rice mill wastewater was investigated using continuous electrocoagulation method (CEC). The electrical energy consumption (EEC) of the process was also examined in order to evaluate the economic viability. The Box-Behnken statistical experiment design (BBD) and response surface methodology (RSM) were used to investigate the effects of major operating variables. Initial pH, current density, electrode distance and flow rate were selected as independent variables in BBD while COD removal, TSS removal and EEC were considered as the response functions. The predicted values of responses obtained using the response function was in good agreement with the experimental data. Optimum operating conditions were found to be pH of 7, current density of 15 mA $cm^{-2}$, electrode distance of 5 cm and flow rate of 70 ml/min. Under these conditions, greater than 89% removal of COD and TSS were obtained with EEC value of 7 KWh.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.2
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• pp.141-147
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• 2015

This paper deals with thermal characteristic analysis of induction motors for machine tool spindle for motion error prediction. Firstly, the inverse design of general induction motors for machine tool spindle has been performed by design principles. Characteristics considering VVVF inverter of induction motors were analyzed. Secondary, power loss and thermal characteristics of induction motors analyzed by equivalent thermal resistance model from Motor-CAD S/W. To develop a second-order fitted power-loss distribution model for the constant-torque operating range of the induction motor, we employed the design of experiment and response surface methodology techniques. Finally, the analysis results were experimentally verified, and the validity of the proposed analysis method was confirmed.