• 한국환경보건학회지
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• 제35권6호
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• pp.491-499
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• 2009

The removal of turbidity from $TiO_2$ wastewater by an electrocoagulation/flotation process was studied in a batch reactor. The response surface methodology (RSM) was applied to evaluate the simple and combined effects of the three main independent parameters, current, NaCl dosage and initial pH of the $TiO_2$ solution on the turbidity removal efficiency, and to optimize the operating conditions of the treatment process. The reaction of electrocoagulation/flotation was modeled by use of the Box-Behnken method, which was used for the fitting of a 2nd order response surface model. The application of RSM yielded the following regression equation, which is an empirical relationship between the turbidity removal efficiency of $TiO_2$ wastewater and test variables in uncoded unit: Turbidity removal (%)=69.76+59.76Current+11.98NaCl+4.67pH+5.00Current${\times}$pH-160.11$Current^2-0.34pH^2$. The optimum current, NaCl dosage and pH of the $TiO_2$ solution to reach maximum removal rates were found to be 0.186 A, 0.161 g/l and 7.599, respectively. This study clearly showed that response surface methodology was one of the most suitable method to optimize the operating conditions for maximizing the turbidity removal. Graphical response surface and contour plots were used to locate the optimum point.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제51권2호
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• pp.55-60
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• 2002

This paper presents an optimization procedure by using Response Surface Methodology(RSM) to determine design parameters for reducing cogging torque. RSM is achieved through using the experimental design method in combination with Finite Element Method and adapted to make analytical model for a complex problem considering a lot of interaction of these parameters. Sequential Quadratic Problem (SQP) method is used to solve the relsulting of constrained nonlinear optimization problem.

• 한국안전학회지
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• 제32권1호
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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.

• 지식경영연구
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• 제21권1호
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• pp.27-40
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• 2020

Response surface methodology (RSM) empirically studies the relationship between a response variable and input variables in the product or process development phase. The ultimate goal of RSM is to find an optimal condition of the input variables that optimizes (maximizes or minimizes) the response variable. RSM can be seen as a knowledge management tool in terms of creating and utilizing data, information, and knowledge about a product production and service operations. In the field of product or process development, most real-world problems often involve a simultaneous consideration of multiple response variables. This is called a multiple response surface (MRS) problem. Various approaches have been proposed for MRS optimization, which can be classified into loss function approach, priority-based approach, desirability function approach, process capability approach, and probability-based approach. In particular, the loss function approach is divided into univariate and multivariate approaches at large. This paper focuses on the univariate approach. The univariate approach first obtains the mean square error (MSE) for individual response variables. Then, it aggregates the MSE's into a single objective function. It is common to employ the weighted sum or the Tchebycheff metric for aggregation. Finally, it finds an optimal condition of the input variables that minimizes the objective function. When aggregating, the relative weights on the MSE's should be taken into account. However, there are few studies on how to determine the weights systematically. In this study, we propose an interactive procedure to determine the weights through considering a decision maker's preference. The proposed method is illustrated by the 'colloidal gas aphrons' problem, which is a typical MRS problem. We also discuss the extension of the proposed method to the weighted MSE (WMSE).

• 전기학회논문지
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• 제58권4호
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• pp.735-741
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• 2009

This paper presents an algorithm for the permanent magnet shape optimization of a large scale BLDC(Brushless DC) motor to minimize the cogging torque. A response surface method (RSM) using multiquadric radial basis function is employed to interpolate the objective function in design parameter space. In order to get a reasonable response surface with relatively small number of sampling data points, additional sampling points are added on the basis of design sensitivity analysis computed by using FEM. The algorithm has 2 stages: the first stage is to determine the PM arc angle, and the 2nd stage is to optimize the magnet pole shape. The developed algorithm is applied to a 5MW BLDC motor to get a minimum cogging torque. After 3 iterations with 4 design parameters, the cogging torque is reduced to 13.2% of the initial one.

• 한국분말재료학회지
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• 제30권3호
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• pp.203-209
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• 2023

Aluminum alloy-based additive manufacturing (AM) has emerged as a popular manufacturing process for the fabrication of complex parts in the automotive and aerospace industries. The addition of an inoculant to aluminum alloy powder has been demonstrated to effectively reduce cracking by promoting the formation of equiaxed grains. However, the optimization of the AM process parameters remains challenging owing to their variability. In this study, the response surface methodology (RSM) was used to predict the crack density of AM-processed Al alloy samples. RSM was performed by setting the process parameters and equiaxed grain ratio, which influence crack propagation, as independent variables and designating crack density as a response variable. The RSM-based quadratic polynomial models for crack-density prediction were found to be highly accurate. The relationship among the process parameters, crack density, and equiaxed grain fraction was also investigated using RSM. The findings of this study highlight the efficacy of RSM as a reliable approach for optimizing the properties of AM-processed parts with limited experimental data. These results can contribute to the development of robust AM processing strategies for the fabrication of high-quality Al alloy components for various applications.

• 전기학회논문지
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• 제57권10호
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• pp.1777-1781
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• 2008

This paper deals with optimum design criteria for maximum torque density & minimum torque ripple of Synchronous Reluctance Motor (SynRM) according to the rated wattage using response surface methodology (RSM). The RSM has been achieved to use the experimental design method in combination with Finite Element Method and well adapted to make analytical model for a complex problem considering of a number of interaction of design variables. The proposed procedure allows the definition of the rotor shape according to flux barrier number, starting from an existing motor or a preliminary design.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제55권12호
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• pp.623-627
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• 2006

This paper deals with the optimum rotor design solution on torque ripple reduction for a SynRM with concentrated winding using response surface methodology (RSM). The RSM has been achieved to use the experimental design method in combination with finite element method (FEM)and well adapted to make analytical model for a complex problem considering a lot of interaction of design variables. Comparisons are given with characteristics of a SynRM according to flux barrier number, flux barrier width variation, respectively.

• 전기학회논문지
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• 제56권12호
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• pp.2145-2149
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• 2007

This paper deals with optimum design criteria to minimize the torque ripple of a concentrated winding Synchronous Reluctance Motor (SynRM) using Response Surface Methodology (RSM). The feasibility of using RSM with the finite element method (FEM) in practical engineering problem is investigated with computational examples and comparison between the fitted response and the results obtained from an analytical solution according to the design variables of stator and rotor in concentrated winding SynRM (6slot).

• 셀메드
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• 제11권3호
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• pp.15.1-15.9
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• 2021

The chemical constitution of a drug has been accepted as an important basis for pharmacological action in Unani medicine. Various dosage forms have been developed on this concept, such as decoctions (Joshanda), infusions (Khesanda), extract (Rub / Usara), and syrup. Zarawand Mudaharaj (ZM.) / Aristolochia rotunda L. root was subjected to extraction process using Soxhlet's apparatus by using Response Surface Methodology (RSM) to design the number of random runs of the extracts with variation in the factors of temperature, the concentration of ethanol in water, time for extraction, for optimizing and maximizing the yield concentration. The data obtained, was analyzed with regression equation and ANOVA two-way summary to interpret the interaction of the factors for yield maximization. Minitab version 18 was used to design and analyze data. Validation of the optimum conditions for maximum yield of the whole extract of ZM. Root was carried out by re-run of the extract using the optimized conditions. The maximum yield percentage thus obtained using RSM was 20.87% whereas using these optimum conditions 21.35 % yield was obtained thereby validating the method. The association between the response functions and the process variables was identified by a three-factor recorded Box-Behnken design. In the present study RSM is used because itis a cheap and affordable method to optimize maximum yield percentage which may be reliably used by researchers. The study set in the surface conditions for ZM. root extraction by the Soxhlet apparatus for maximizing the yield percentage.