• 대한기계학회논문집A
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• 제30권3호
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• pp.302-309
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• 2006

Effective mixing plays a crucial role in microfluidics for biochemical applications. Owing to the small device scale and its entailing the low Reynolds number, the mixing in microchannels proceeds very slowly. In this work, we optimize the configuration of obstacles in the Y-channel mixer in order to attain maximum mixing efficiency. Before the optimum design, mixing characteristics are investigated using unstructured grid CFD method. Then, the analysis method is employed to construct the approximate analysis model to be used in the optimization procedure. The main optimization tool in the present work is sequential quadratic programming method. Using this approximate optimization procedure, we may obtain the optimum layout of obstacles in the Y-channel mixer in an efficient manner, which gives the maximum mixing efficiency.

• 대한기계학회논문집A
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• 제37권8호
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• pp.1059-1067
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• 2013

자동차 연료탱크는 크게 본체와 본체에 조립되는 부품들로 구성되어 있다. 본체에는 차량 주행시에 연료탱크에서 발생되는 증발가스를 배출하고, 연료가 외부로 유출되는 것을 방지하기 위한 여러 밸브들이 조립되어 있다. 하지만 이러한 밸브들은 연료 넘침에 주된 원인으로 알려져 있음에도 불구하고 현재 증발가스의 배출과 기구적인 위치만 고려하여 설계되고 있다. 따라서 본 연구에서는 밸브들의 기존기능을 유지하면서 연료 넘침을 최소화 시키기 위해 근사최적설계를 적용하였고, 다구치 방법을 통해 실제 실험에서 근사최적설계의 유용성을 보였다. 결과적으로 최적화된 밸브 위치를 통해 개발기간과 비용을 절감하였고, 연료 넘침 최소화를 통해 자동차의 신뢰성을 향상시켰다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.1846-1851
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• 2003

Approximate optimization has become popular in engineering field such as MDO and Crash analysis which is time consuming. To accomplish efficient approximate optimization, accuracy of approximate model is very important. As surrogate model, Kriging have been widely used approximating highly nonlinear system . Because Kriging employs interpolation method, it is adequate for deterministic computer simulation. Because there are no random errors and measurement errors in deterministic computer simulation, instead of classical DOE ,space filling experiment design which fills uniformly design space should be applied. In this work, various space filling designs such as maximin distance design, maximum entropy design are reviewed. And new design improving maximum entropy design is suggested and compared.

• 한국산학기술학회논문지
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• 제15권7호
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• pp.4057-4064
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• 2014

본 연구는 본 연구에서 제안하는 근사 최적화 방법(메타모델 기반의 시뮬레이션 최적화)을 사용하여 저렴한 해석 비용으로 펀치 단조품의 예비성형체(preform)를 설계한다. 본 연구에서 사용한 설계목표는 유효변형률의 균일한 분포이고 설계변수는 예비성형체 치수이며, 구속조건으로 최대 미충진 비율을 사용한다. 이를 위해 먼저 예비성형펀치(반재), 마스터펀치(상부다이) 및 하부다이로 구성되는 단조성형 공정을 DEFORM 시뮬레이션에 의해 모사하고, 이 시뮬레이션 결과가 실제 단조 공정을 모사하고 있는지 확인하는 검증 방법에 관해 소개한다. 또한 본 연구에서 수행한 설계 최적화 과정, 즉 (i) 초기 메타모델의 생성, (ii) 메타모델의 최적화 수행, (iii) 메타모델 최적해의 검증, (iv) 메타모델의 개선에 관하여 상세히 기술한다.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 1997년도 추계 학술대회논문집
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• pp.126-130
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• 1997

A new and efficient method is presented for design optimization, which is based on a computational fluid dynamics (CFD). The method is applied to design an airfoil configuration. The Navier-Stokes equations are solved for the viscous analysis of the flow, which provides the object function. The CFD analysis is then coupled with the optimization procedure that used a conjugate gradient method. During the one-dimensional search of the optimization procedure, an approximate flow analysis based on a first-order Taylor series expansion is used to reduce the computational cost, (This study is supported by Korean Ministry of Education through Research Fund)

• 한국기계가공학회지
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• 제15권3호
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• pp.8-14
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• 2016

Medical bed head consoles (BHC) are generally used to increase the efficiency of medical equipment and speed the medical treatment response time. The BHC design has been consistently improved including a movable shelf unit that is embedded to mount stably medical instruments on the lower part of the main console. The cost of a BHC can be reduced through design optimization to limit the overall weight. However, as the size of a head console might decrease due to design optimization, the BHC deflection could be increased. In this study, multi-objective optimal design was adopted to consider this BHC design problem. In order to reduce the cost of optimization planning, an approximate model was applied for the design optimization. In the context of approximate optimization, we used the response surface method and non-dominant sorting genetic algorithm developed from various fields. Multi-objective optimal solutions were also compared with a single objective optimal design.

• 대한기계학회논문집A
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• 제39권5호
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• pp.535-541
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• 2015

본 연구에서는 벽걸이 모니터 브라켓 암의 다중목적 근사최적설계를 수행하였다. 이를 위해 브라켓 암의 자유도를 고려하여 평면내의 회전 각도를 선정해 응력과 처짐량이 크게 발생하는 경우에 대한 최적화 문제를 정식화 하였다. 직교배열표와 반응표면법을 사용하여 평균 및 파라미터 분석을 통해 성능지수에 대한 설계변수 민감도를 확인하였으며, 중심합성계획법과 D-최적 계획법을 사용하여 목적함수와 제한조건함수에 대하여 반응표면 근사모델을 생성하고 $R^2$ 값을 통해 정확도를 평가하였다. 이를 비지배 분류 유전알고리즘에 적용하여 최적화를 수행하고 유한요소해석을 통해 검증하였다. 또한, 중심합성 계획법과 D-최적 계획법을 이용한 최적해를 비교 분석하였다.

• 한국시뮬레이션학회논문지
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• 제3권2호
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• pp.57-67
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• 1994

For many practical and industrial optimization problems where some or all of the system components are stochastic, the objective functions cannot be represented analytically. Therefore, modeling by computer simulation is one of the most effective means of studying such complex systems. In this paper, with discussion of simulation optimization techniques, a case study in machining process for application of simulation optimization is presented. Most of optimization techniques can be classified as single-or multiple-response techniques. The optimization of single-response category, these strategies are gradient based search methods, stochastic approximate method, response surface method, and heuristic search methods. In the multiple-response category, there are basically five distinct strategies for treating the responses and finding the optimum solution. These strategies are graphical method, direct search method, constrained optimization, unconstrained optimization, and goal programming methods. The choice of the procedure to employ in simulation optimization depends on the analyst and the problem to be solved.

• 전자공학회논문지B
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• 제31B권4호
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• pp.145-154
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• 1994

This paper proposes an efficient method for improving the training performance of the neural network by using a hybrid of a stochastic approximation and a backpropagation algorithm. The proposed method improves the performance of the training by appliying a global optimization method which is a hybrid of a stochastic approximation and a backpropagation algorithm. The approximate initial point for a stochastic approximation and a backpropagation algorihtm. The approximate initial point for fast global optimization is estimated first by applying the stochastic approximation, and then the backpropagation algorithm, which is the fast gradient descent method, is applied for a high speed global optimization. And further speed-up of training is made possible by adjusting the training parameters of each of the output and the hidden layer adaptively to the standard deviation of the neuron output of each layer. The proposed method has been applied to the parity checking and the pattern classification, and the simulation results show that the performance of the proposed method is superior to that of the backpropagation, the Baba's MROM, and the Sun's method with randomized initial point settings. The results of adaptive adjusting of the training parameters show that the proposed method further improves the convergence speed about 20% in training.

• Journal of applied mathematics & informatics
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• 제7권2호
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• pp.453-465
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• 2000

In this paper, a new method for finding the approximate solution of a second order nonlinear partial differential equation is introduced. In this method the problem is transformed to an equivalent optimization problem. them , by considering it as a distributed parameter control system the theory of measure is used for obtaining the approximate solution of the original problem.