• Proceedings of the Korea Society for Simulation Conference
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• 2002.11a
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• pp.3-7
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• 2002

컴퓨터 네트워킹 기술의 발달에 힘입어 분산처리를 이용한 기법이 복잡한 구조물의 최적설계에 널리 사용되고 있다. 최적설계시 구조물이 복잡하고 설계 변수가 많아질수록 설계 변수간의 교호작용이 복잡해지고 국부최적해가 많아지는 특성이 있다. 최근의 최적 설계는 이러한 문제점을 해결하고자 다양한 전역 최적화 기법을 도입하여 적용하고 있다. 본 연구에서는 진화이론을 바탕으로 한 유전자 알고리즘과 실험계획법을 바탕으로 한 반응표면법에 분산처리 기법을 도입하여 인공위성 추진 모듈의 최적화에 적용시켰다. 그 결과 유전자 알고리즘이 조금 더 좋은 최적값을 보였으며 해석시간은 반응표면법을 적용 시켰을 경우가 훨씬 짧았다. 병렬처리 기법을 이용한 위성구조체의 최적설계에 있어 유전자 알고리즘은 해의 전역성에서 반응표면법은 시간의 효율성에서 각각 장점을 보였다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.449-450
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• 2009

• Journal of Soil and Groundwater Environment
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• v.12 no.5
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• pp.73-85
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• 2007

In this study, the experiment of solid-phase microextraction (SPME) technique using GC/FID was conducted as a possible alternative to liquid-liquid extraction for the analysis of EGBE, DGBE, DBM and TGME in water, and also, an optimization condition of trace analysis for disel oxygenates including EGBE by the design of experiment (DOE) was described. Experiments used a fractional factorial design method followed by central composite design allowing optimization of a number of factors as well as statistical analysis of the results. The response surface analysis showed that the extraction efficiency could be represented by a second-order polynomial equation in which the salts concentration, extraction temperature, extraction time and sonication time are the major influences. Using DOE method, a new datadependent method was developed to improve the quantity of confidently analyzed disel oxygenates in water samples.

• Journal of the Korean Magnetics Society
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• v.27 no.2
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• pp.54-62
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• 2017

This paper presents a design of the Interior Permanent Magnet Synchronous Motor (IPMSM). an initial design process is accomplished by using the parametric design. In the design process, motor characteristics of parameters is computed by the d-q axis equivalent circuit model. Then, an optimal design process is accomplished by combination the experimental design and the response surface method. Finally, the design and analysis results are verified with experimental results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.700-703
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• 2004

A reliability analysis and design procedure based on the design of experiment (DOE) is combined with the response surface method (RSM) for numerical efficiency. The procedure established is based on a 3$^n$ full factorial DOE for numerical quadrature using explicit formula of optimum levels and weights derived for general distributions. The full factorial moment method (FFMM) shows good performance in terms of accuracy and ability to treat non-normally distributed random variables. But, the FFMM becomes very inefficient because the number of function evaluation required increases exponentially as the number of random variables considered increases. To enhance the efficiency, the response surface moment method (RSMM) is proposed. In RSMM, experiments only with high probability are conducted and the rest of data are complemented by a quadratic response surface approximation without mixed terms. The response surface is updated by conducting experiments one by one until the value of failure probability is converged. It is calculated using the Pearson system and the four statistical moments obtained from the experimental data. A measure for checking the relative importance of an experimental point is proposed and named as influence index. During the update of response surface, mixed terms can be added into the formulation.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.12
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• pp.689-697
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• 2017

As a fundamental study to apply the new flocculation method using ballast in water treatment process, the optimal conditions for general and ballast coagulant dosage, and pH, which are known to have a significant influence, were derived by response surface methodology. Poly aluminum chloride (PAC) and magnetite ballast were used as a general coagulant and ballast, respectively. Coagulation experiments were performed by jar-tester using the kaolin based synthetic water. The effects of three independent variables (pH, PAC, and ballast) on response variables (turbidity removal rate and average settling velocity of flocs) and the optimum condition of independent variables to induce the optimum flocculation were obtained by 17 experimental conditions designed by Box-Behnken procedure. After performing experiments, the quadratic regression model was derived for each of response variables, and the response surface analysis was conducted to explore the correlation between independent variables and response variables. The $R^2$ values for the turbidity removal rate and the average settling velocity were 0.9909 and 0.8295, respectively. The optimal conditions of independent variables were 7.4 of pH, 38 mg/L of PAC and 1,000 mg/L of ballast. Under these conditions, the turbidity removal rate was more than 97% and the average settling velocity exceeded 35 m/h.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.3
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• pp.258-266
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• 2008

The conventional approximate optimization method, which uses the statistical design of experiments(DOE) and response surface method(RSM), can derive an approximated optimum results through the iterative process by a trial and error. The quality of results depends seriously on the factors and levels assigned by a designer. The purpose of this study is to propose a new technique, which is called a sequential design of experiments(SDOE), to reduce a trial and error procedure and to find an appropriate condition for using artificial neural network(ANN) systematically. An appropriate condition is determined from the iterative process based on the analysis of means. With this new technique and ANN, it is possible to find an optimum design accurately and efficiently. The suggested algorithm has been applied to various mathematical examples and a structural problem.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2006.10a
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• pp.2-3
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• 2006

본 논문에서는 신경망 모델링을 통하여 HDP-CVD를 이용한 실리콘 산화막 형성에 영향을 주는 다섯 가지 공정 장비 변수와 그에 따른 두 가지 출력 파라미터 Deposition rate과 Uniformity와의 관계를 동시에 고려한 특성결과를 분석하고， 최적의 recipe를 Genetic Algorithm을 통해 제시하였다. 실험계획법을 사용하여， 필요한 실험의 횟수를 최소화 하였으며 그 실험결과를 신경망 모델링을 통하여 입력변수와 출력파라미터의 관계를 3차원의 반응표면 곡선으로 분석하였다. 이 과정을 통해 Deposition rate과 Uniformity을 동시에 고려한 두 출력파라미터를 만족하는 최적의 입력변수 값들을 제시하였다.

• Applied Chemistry for Engineering
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• v.28 no.5
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• pp.559-564
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• 2017

In this study, the optimization process was carried out by using the central composite model of the response surface methodology in waste cooking oil based biodiesel production process. The acid value, reaction time, reaction temperature, methanol/oil molar ratio, and catalyst amount were selected process variables. The response was evaluated by measuring the FAME content (more than 96.5%) and kinematic viscosity (1.9~5.5 cSt). Through basic experiments, the range of optimum operation variables for the central composite model, such as reaction time, reaction temperature and methanol/oil molar ratio, were set as between 45 and 60 min, between 50 and $60^{\circ}C$, and between 8 and 12, respectively. The optimum operation variables, such as biodiesel production reaction time, temperature, and methanol/oil molar ratio deduced from the central composite model were 55.2 min, $57.5^{\circ}C$, and 10, respectively. With those conditions the results deduced from modeling were as followings: the predicted FAME content of the biodiesel and the kinematic viscosity of 97.5% and 2.40 cSt, respectively. We obtained experimental results with deduced operating variables mentioned above as followings: the FAME content and kinematic viscosity of 97.7% and 2.41 cSt, respectively. Error rates for the FAME content and kinematic viscosity were 0.23 and 0.29%, respectively. Therefore, the low error rate could be obtained when the central composite model among surface reaction methods was applied to the optimized production process of waste cooking oil raw material biodiesel.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.1
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• pp.21-28
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• 2008

The final polishing process is based on slurry, pad, conditioner, equipment. Therefore, the concept of wafer final polishing is also necessary for repeatability of results between polished wafers. In this study, the machining conditions have a pressure, table speed, machining time and slurry ratio. This research investigated the surface characteristics that apply variable machining conditions and response surface methodology was used to obtain more flexible and optimumal condition base on Taguchi method. On the base of estimated response surface curvature from the equation and results of Taguchi method, combined design of experiment was considered to lead to optimumal condition. Finally, polished wafer was obtained mirror like surface.