• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.414.1_415.1
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• 2009

This paper deals with optimum design criteria for maximum torque density & minimum torque ripple of Flux Switching Motor (FSM) using RSM & FEM. The focus of this paper is to find a design solution through the comparison of torque density and torque ripple according to rotor shape variations. And then, a central composite design(CCD) mixed resolution is introduced, and analysis of variance (ANOVA) is conducted to determine the significance of the fitted regression model.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.3
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• pp.232-238
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• 2011

In the present study, Taguchi method is used to determine the rough region first, followed by RSM technique to determine the exact optimum value during milling on a machining center. A region reducing algorithm is applied to narrow down the region of the Taguchi method for RSM. The result from the Taguchi method is fed to train the artificial neural network (ANN), whose optimum value is used to drive the region reducing algorithm. The proposed algorithm is tested under different cutting condition and results show that the introduced algorithm works well during milling process. It is also shown that theoretically obtained optimal cutting condition is very close to experimentally obtained result.

• Journal of the Korean institute of surface engineering
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• v.51 no.5
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• pp.303-308
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• 2018

Currently hydrofluoric acid (HF) based glass etch method is widely used for anti-glare (AG) surface treatment since it can effectively alleviate the specular reflection problem with relatively low processing cost. However, due to the environmental regulation and safety problem, it is essential to develop alternative technology to replace this method. For this, in this paper, we propose sand blasting based AG surface treatment method for display glass. To characterize the sand blasting process, surface roughness, haze, surface durability, and flatness are considered as process outputs and central composite design (CCD) method and response surface model (RSM) method are applied to model each process output. Models for surface roughness and haze showed 96.44% and 97.24% of R-squared values, respectively and they can be applied to optimize AG surface treatment process for various haze level requirements of display industries.

• Journal of Environmental Science International
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• v.23 no.3
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• pp.359-368
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• 2014

The aim of our research was to apply experimental design methodology in the optimization of N, N-Dimethyl-4-nitrosoaniline (RNO, which is indictor of OH radical formation) degradation using gas mixing-circulation plasma process. The reaction was mathematically described as a function of four independent variables [voltage ($X_1$), gas flow rate ($X_2$), liquid flow rate ($X_3$) and time ($X_4$)] being modeled by the use of the central composite design (CCD). RNO removal efficiency was evaluated using a second-order polynomial multiple regression model. Analysis of variance (ANOVA) showed a high coefficient of determination ($R^2$) value of 0.9111, thus ensuring a satisfactory adjustment of the second-order polynomial multiple regression model with the experimental data. The application of response surface methodology (RSM) yielded the following regression equation, which is an empirical relationship between the RNO removal efficiency and independent variables in a coded unit: RNO removal efficiency (%) = $77.71+10.04X_1+10.72X_2+1.78X_3+17.66X_4+5.91X_1X_2+3.64X_2X_3-8.72X_2X_4-7.80X{_1}^2-6.49X{_2}^2-5.67X{_4}^2$. Maximum RNO removal efficiency was predicted and experimentally validated. The optimum voltage, air flow rate, liquid flow rate and time were obtained for the highest desirability at 117.99 V, 4.88 L/min, 6.27 L/min and 24.65 min, respectively. Under optimal value of process parameters, high removal(> 97 %) was obtained for RNO.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.5
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• pp.535-541
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• 2015

In this study, an approximate multi-objective optimization of a wall-mounted monitor bracket arm was performed. The rotation angle of the bracket arm was determined considering the inplane degree of freedom. We then formulated an optimization problem on maximum stress and deflection. Analyses of mean and design parameters were conducted for sensitivity regarding performance with orthogonal array and response surface method (RSM). RSM models of objective and constraint functions were generated using central composite (CCD) and D-optimal design. The accuracy of approximate models was evaluated through $R^2$ value. The obtained optimal solutions by non-dominant sorting genetic algorithm (NSGA-II) were validated through the finite element analysis and we compared the obtained optimal solution by CCD and D-optimal design.

• Advances in environmental research
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• v.9 no.1
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• pp.65-84
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• 2020

The potential use of Sargassum boveanum algae for the removal of uranium from aqueous solution has been studied by varying three independent parameters (pH, initial uranium ion concentration, S. boveanum dosage) using a central composite design (CCD) under response surface methodology (RSM). Batch mode experiments were performed in 20 experimental runs to determine the maximum metal adsorption capacity. In CCD design, the quantitative relationship between different levels of these parameters and heavy metal uptake (q) were used to work out the optimized levels of these parameters. The analysis of variance (ANOVA) of the proposed quadratic model revealed that this model was highly significant (R² = 0.9940). The best set required 2.81 as initial pH(on the base of design of experiments method), 1.01 g/L S. boveanum and 418.92 mg/L uranium ion concentration within 180 min of contact time to show an optimum uranium uptake of 255 mg/g biomass. The biosorption process was also evaluated by Langmuir, Freundlich, Temkin and Dubinin-Radushkevich isotherm models represented that the experimental data fitted to the Langmuir isotherm model of a suitable degree and showed the maximum uptake capacity of 500 mg/g. FTIR and scanning electron microscopy were used to characterize the biosorbent and implied that the functional groups (carboxyl, sulfate, carbonyl and amine) were responsible for the biosorption of uranium from aqueous solution. In conclusion, the present study showed that S. boveanum could be a promising biosorbent for the removal of uranium pollutants from aqueous solutions.

• Advances in Energy Research
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• v.4 no.3
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• pp.189-202
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• 2016

This work emphasized optimum production of biodiesel using non-edible Prunus armeniaca (Bitter Apricot) oil via transesterification collected from the high altitude areas of Himachal Pradesh, India. In this study the author produced biodiesel through the process of transesterification by using an alkali catalyst with alcohol (methanol and ethanol), under the varying molar ratio (1:6, 1:9, 1:12), variable catalyst percentage (1% and 2%) and temperature ($70^{\circ}C$, $75^{\circ}C$, $80^{\circ}C$, $85^{\circ}C$). Furthermore, a few strong base catalysts were used that includes sodium hydroxide, potassium hydroxide, sodium metal and freshly prepared sodium methoxide. After screening the catalyst, response surface methodology (RSM) in connection with the central composite design (CCD) was used to statistically evaluate and optimize the biodiesel production operation using NaOH as catalyst. It was found that the production of biodiesel achieved an optimum level biodiesel yield with 97.30% FAME conversion under the following reaction conditions: 1) Methanol/oil molar ratio: 1:6, 2) Reaction time: 3h, 3) Catalyst amount: NaOH 2 wt. %, and 4) Reaction temperature: $85^{\circ}C$. The experimental results showed that the optimum production and conversion of biodiesel through the process of transesterification could be achieved under an optimal set of reaction conditions. The biodiesel obtained showed appropriate fuel properties as specified in ASTM, BIS and En- standards.

• Environmental Engineering Research
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• v.25 no.1
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• pp.114-122
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• 2020

This study was aimed at using the Central Composite Design (CCD) and Box-Behnken Design (BBD) to compare the efficiency and to elucidate the main interacting parameters in the upflow anaerobic sludge blanket (UASB) reactor, namely: Organic Loading Rate (OLR), Hydraulic Retention Times (HRT) and pH at a constant temperature of 35℃. Optimum HRT (15 h), OLR (3.5 kg.m^-3.d^-1) and pH (7) resulted in biogas production of 5,800 mL/d and COD removal of 80.8%. BBD produced a higher desirability efficiency of 94% as compared to the CCD which was 92%. The regression quadratic models developed with high R² values of 0.961 and 0.978 for both CCD and BBD, respectively, demonstrated that the interaction models could be used to pilot the design space. BBD model developed was more reliable with a higher prediction of biogas production (5,955.4 ± 225.3 mL/d) and COD removal (81.5 ± 1.014%), much close to the experimental results at a 95% confidence level. CCD model predictions was greater in terms of COD removal (82.6 ± 1.06% > 80.8%) and biogas production (4,636.31 mL/d ± 439.81 < 5,800 mL/d) which was less than the experimental results. Therefore, RSM can be adapted for optimizing various wastewater treatment processes.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.6
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• pp.113-125
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• 2017

In spite of bulk literature about the tuning of TMD, the effectiveness of TMD in reducing the seismic response of engineering structures is still in a row. This paper deals with the optimum tuning parameters of a passive TMD and simulated on MATLAB with a ten-story numerical shear building. A weighted multi-objective optimization method based on computer experiment consisting of coupled with central composite design(CCD) central composite design and response surface methodology(RSM) was applied to find out the optimum tuning parameters of TMD. After the optimization, the so-conceived TMD turns out to be optimal with respect to the specific seismic event, hence allowing for an optimum reduction in seismic response. The method was employed on above structure by assuming first the El Centro seismic input as a sort of benchmark excitation, and then additional recent strong-motion earthquakes. It is found that the RSM based weighted multi-objective optimized damper improves frequency responses and root mean square displacements of the structure without TMD by 31.6% and 82.3% under El Centro earthquake, respectively, and has an equal or higher performance than the conventionally designed dampers with respect to frequency responses and root mean square displacements and when applied to earthquakes.

• Journal of the Korean Society of Food Culture
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• v.27 no.2
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• pp.202-210
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• 2012

The purpose of this study was to bake sweet rice muffins with oak mushroom ($Lentinus$ $edodes$) powder. The process included substituting sweet rice flour for cake flour and adding oak mushroom powder. This study determined the optimal mixing conditions of oak mushroom muffins by adjusting the amounts of oak mushroom powder, whole eggs, and soybean oil. The mixing conditions for the oak mushroom muffins included 3 categories: oak mushroom powder (X1), whole eggs (X2), and soybean oil (X3) by Central Composite Design (CCD) which was optimized by Response Surface Methodology (RSM). Oak mushroom muffin formulation was optimized using rheology. Yellowness (p<0.001) and redness (p<0.05) displayed a linear model pattern, whereas lightness (p<0.05) was represented by a quadratic model. Among the sensory properties, variables that appeared to show significant values such as appearance (p<0.5), texture (p<0.5), and overall quality (p<0.5) were used to identify optimums. The result of mechanical properties showed significant values in gumminess (p<0.5) and chewiness (p<0.5). The numerical and graphical methods used in this study determined that the optimum formulation for oak mushroom powder sweet rice muffins was 8.75 g of oak mushroom powder, 235.95 g of whole eggs, and 19.93 g of soybean oil.