• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1257-1260
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• 2005

Grinding process has unique characteristics compared with other machining processes. The cutting edges of the grinding wheel don't have uniformity and act differently on the workpiece at each grinding. The response surface analysis is one of various methods for optimizing and evaluating the process parameters to achieve the desired output. In this study, the effect of the grinding parameters on outcomes of the surface grinding was analyzed experimently. To predict the grinding outcomes and to select the grinding conditions before grinding, the second-order response surface models for the grinding force and the surface roughness were developed.

• Nuclear Engineering and Technology
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• v.28 no.6
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• pp.507-521
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• 1996

Quantification of uncertainties in the source term estimations by a large computer code, such as MELCOR and MAAP, is an essential process of the current Probabilistic safety assessment. The main objective of the present study is to investigate the applicability of a combined procedure of the response surface method (RSM) based on input determined from a statistical design and the Latin hypercube sampling (LHS) technique for the uncertainty analysis of CsI release fractions under a Hypothetical severe accident sequence of a station blackout at Younggwang nuclear power plant using MAAP3. OB code as a benchmark problem. On the basis of the results obtained in the present work, the RSM is recommended to be used as a principal tool for an overall uncertainty analysis in source term quantifications, while using the LHS in the calculations of standardized regression coefficients (SRC) and standardized rank regression coefficient (SRRC) to determine the subset of the most important input parameters in the final screening step and to check the cumulative distribution functions obtained by RSM. Verification of the response surface model for its sufficient accuracy is a prerequisite for the reliability of the final results that can be obtained by the combined procedure proposed in the present work.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.5
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• pp.247-255
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• 2018

In this research, the effect of normal load, sliding velocity, and texture density on thefriction coefficient of surfaces micro-textured on AISI 4140 under paraffin oil lubrication were investigated. The predicted tribological behavior by numerical calculation can be serves as guidance for the designer during the machine development stage. Therefore, in this research friction coefficient prediction model based on response surface methodology (RSM), support vector machine (SVM), and artificial neural network (ANN) were developed. The experimental result shows that the variation of load, speed and texture density were influence the friction coefficient. The RSM, ANN and SVM model was successfully developed based on the experimental data. The ANN model can effectively predict the tribological characteristics of micro-textured AISI 4140 in paraffin oil lubrication condition compare to RSM and SVM.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.754_755
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• 2009

This paper deals with the characteristics analysis & optimum design of Synchronous Reluctance Motor (SynRM) with anisotropy rotor using a coupled Finite Element Method (FEM) & Response Surface Methodology (RSM). The focus of this paper is the characteristics analysis & optimum design relative to the output power on the basis of rotor materials of a SynRM. The coupled Finite Elements Analysis (FEA) & Preisach model have been used to evaluate nonlinear solutions. Comparisons are given with characteristics of normal synchronous reluctance motor and those of anisotropy rotor SynRM (ANISO-SynRM), respectively. The feasibility of using RSM with 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 rotor in anisotropy rotor SynRM.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.972-975
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• 2004

In order to reduce the noise of BLDC motor, a systematic optimization procedure for rotor structure is presented. The noise index is defined as the sum of volume velocity of FE-model that are calculated at the dominant frequencies during dehydration process, which is based on the principle of radiation simple volume source. Then, the five design variables are selected to represent the shape and layout or rotor structure. This discrete design optimization problem for minimizing the noise index is solved by 3-level orthogonal array based effect analysis. Finally, the response surface method (RSM) combined optimization approach is employed for more refining the approximate optimum.

• 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.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.4
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• pp.37-43
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• 2008

Working condition is one of the most important factors in precision working. In this study, we optimized the vibration acceleration level(VAL) of Al 2024 alloy to select optimum working condition of side wall end-milling using RSM(Response Surface Methodology). RSM was well adapted to make analytic model for minimizing vibration acceleration, created the objective function and saved a great deal of computational time. Therefore, it is expected that the proposed optimization procedure using RSM can be easily utilized to solve the optimization problem of working condition. The experimental results of the surface roughness and VAL showed the validity of the proposed working condition of side wall end-milling as it can be observed.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.957-960
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• 2006

In order to predict the accumulated damages by cyclic freeze-thaw, a regression analysis by the Response Surface Method (RSM) is used. RSM has merits when the other probabilistic simulation techniques can not guarantee the convergence of probability of occurrence or when the others can not differentiate the derivative terms of limit state functions, which are composed of random design variables in the model of complex system or the system having higher reliability. For composing limit state function, the important parameters for cyclic freeze-thaw-deterioration of concrete structures, such as water to cement ratio, entrained air pores, and the number of cycles of freezing and thawing, are used as input parameters of RSM. The predicted results of relative dynamic modulus and residual strains after 300 cycles of freeze-thaw for specimens show very good agreements with the experimental results. The RSM result can be used to predict the probability of occurrence for designer specified critical values. Therefore, it is possible to evaluate the life cycle management of concrete structures considering the accumulated damages by the cyclic freeze-thaw by the use of proposed prediction method.

• Structural Engineering and Mechanics
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• v.63 no.3
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• pp.303-315
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• 2017

This paper presents a review on getting a Weighted Multi-Objective Optimization (WMO) of Tuned Mass Damper (TMD) parameters based on Response Surface Methodology (RSM) coupled central composite design and Weighted Desirability Function (WDF) to attenuate the earthquake vibration of a jacket supported Offshore Wind Turbine (OWT). To optimize the parameters (stiffness and damping coefficient) of damper, the frequency ratio and damping ratio were considered as a design variable and the top displacement and frequency response were considered as objective functions. The optimization has been carried out under only El Centro earthquake results and after obtained the optimal parameters, more two earthquakes (California and Northridge) has been performed to investigate the performance of optimal damper. The obtained results also compared with the different conventional TMD's designed by Den Hartog's, Sadek et al.'s and Warburton's method. From the results, it was found that the optimal TMD based on RSM shows better response than the conventional damper. It is concluded that the proposed response model offers an efficient approach regarding the TMD optimization.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2384-2389
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• 2007

The 2nd order response surface method (RSM) has been carried out to get optimum thermal design for enhanced heat transfer on square channel with bleed holes. The RSM was used as an optimization technique with Reynolds-averaged navier-stokes equation. Turbulence model for heat transfer analysis used RNG k-epsilon model. The wall function used enhanced wall function. Numerical local heat transfer coefficients were similar to the experimental tendency. Two design variables such as attack angle of rib (${\alpha}$), rib pitch-to-rib height ratio (p/e) were chosen. Operation condition considered bleeding ratio per bleed hole ($BR_{hole}$). A response surface were constructed by the design variables and operation condition. As a result, adjusted $R^2$ was more than 0.9. Optimization results of various objective function were similar to heat transfer in channel with and without bleed flow. But friction factor was lower than channel without bleed flow.