• 제목/요약/키워드: Sequential approximate optimization

검색결과 59건 처리시간 0.023초

혼합 개선을 위한 Y-채널 마이크로 믹서의 최적설계 (Optimum Design of a Y-channel Microcmixer for Enhanced Mixing)

  • 신용수;최형일;이동호;이도형
    • 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.

Efficient Approximation Method for Constructing Quadratic Response Surface Model

  • Park, Dong-Hoon;Hong, Kyung-Jin;Kim, Min-Soo
    • Journal of Mechanical Science and Technology
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    • 제15권7호
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    • pp.876-888
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    • 2001
  • For a large scaled optimization based on response surface methods, an efficient quadratic approximation method is presented in the context of the trust region model management strategy. If the number of design variables is η, the proposed method requires only 2η+1 design points for one approximation, which are a center point and tow additional axial points within a systematically adjusted trust region. These design points are used to uniquely determine the main effect terms such as the linear and quadratic regression coefficients. A quasi-Newton formula then uses these linear and quadratic coefficients to progressively update the two-factor interaction effect terms as the sequential approximate optimization progresses. In order to show the numerical performance of the proposed method, a typical unconstrained optimization problem and two dynamic response optimization problems with multiple objective are solved. Finally, their optimization results compared with those of the central composite designs (CCD) or the over-determined D-optimality criterion show that the proposed method gives more efficient results than others.

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민감도법을 이용한 크리깅모델의 순차적 실험계획 (Sensitivity Approach of Sequential Sampling for Kriging Model)

  • 이태희;정재준;황인교;이창섭
    • 대한기계학회논문집A
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    • 제28권11호
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    • pp.1760-1767
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    • 2004
  • Sequential sampling approaches of a metamodel that sampling points are updated sequentially become a significant consideration in metamodeling technique. Sequential sampling design is more effective than classical space filling design of all-at-once sampling because sequential sampling design is to add new sampling points by means of distance between sampling points or precdiction error obtained from metamodel. However, though the extremum points can strongly reflect the behaviors of responses, the existing sequential sampling designs are inefficient to approximate extremum points of original model. In this research, new sequential sampling approach using the sensitivity of Kriging model is proposed, so that new approach reflects the behaviors of response sequentially. Various sequential sampling designs are reviewed and the performances of the proposed approach are compared with those of existing sequential sampling approaches by using mean squared error. The accuracy of the proposed approach is investigated against optimization results of test problems so that superiority of the sensitivity approach is verified.

휴대폰용 카메라 렌즈 시스템의 공차최적설계 (Tolerance Analysis and Optimization for a Lens System of a Mobile Phone Camera)

  • 정상진;최동훈;최병렬;김주호
    • 한국CDE학회논문집
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    • 제16권6호
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    • pp.397-406
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    • 2011
  • Since tolerance allocation in a mobile phone camera manufacturing process greatly affects production cost and reliability of optical performance, a systematic design methodology for allocating optimal tolerances is required. In this study, we proposed the tolerance optimization procedure for determining tolerances that minimize production cost while satisfying the reliability constraints on important optical performance indices. We employed Latin hypercube sampling for evaluating the reliabilities of optical performance and a function-based sequential approximate optimization technique that can reduce computational burden and well handle numerical noise in the tolerance optimization process. Using the suggested tolerance optimization approach, the optimal production cost was decreased by 30.3 % compared to the initial cost while satisfying the two constraints on the reliabilities of optical performance.

마이크로 믹서의 형상 최적화 (Shape Optimization of a Micro-Static Mixer)

  • 한석영;김성훈
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2004년도 춘계학술대회 논문집
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    • pp.166-171
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    • 2004
  • In this study, shape optimization of micro-static mixer with a cantilever beam was accomplished for mixing the mixing efficiency by using successive response surface approximations. Variables were chosen as the length of cantilever beam and the angle between horizontal and the cantilever beam. Sequential approximate optimization method was used to deal with both highly nonlinear and non-smooth characteristics of flow field in a micro-static mixer. Shape optimization problem of a micro-static mixer can be divided into a series of simple subproblems. Approximation to solve the subproblems was performed by response surface approximation, which does not require the sensitivity analysis. To verify the reliability of approximated objective function and the accuracy of it, ANOVA analysis and variables selection method were implemented, respectively. It was verified that successive response surface approximation worked very well and the mixing efficiency was improved very much comparing with the initial shape of a micro-static mixer.

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수치적 노이즈가 존재하는 사출 성형품 휨의 최적설계 (Design Optimization for Minimizing Warpage in Injection Molding Parts with Numerical Noise)

  • 박창현;김성룡;최동훈;표병기
    • 대한기계학회논문집A
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    • 제29권11호
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    • pp.1445-1454
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    • 2005
  • In order to minimize warping deformation which is an essential factor in the failure of injection molding parts, this study proposes an optimization design method fer determining design variables of injection molding parts. First, using a commercial package program for injection molding analysis, namely, Computer Aided Plastics Application(CAPA), we investigate the effects of parameters of injection molding process. Next, an optimum design process is established by interfacing CAPA to PQRSM embedded in EMD10S, a design framework developed by the conte. of innovative Design Optimization Technology(iDOT). PQRSM is a very efficient sequential approximate optimization algorithm. Optimum design results demonstrate the effectiveness of the design method suggested in this study by showing that the results of the optimum design is better than those of the initial design. It is believed that the proposed methodology can be applied to other injection molding design applications.

A Robust Optimization Using the Statistics Based on Kriging Metamodel

  • Lee Kwon-Hee;Kang Dong-Heon
    • Journal of Mechanical Science and Technology
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    • 제20권8호
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    • pp.1169-1182
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    • 2006
  • Robust design technology has been applied to versatile engineering problems to ensure consistency in product performance. Since 1980s, the concept of robust design has been introduced to numerical optimization field, which is called the robust optimization. The robustness in the robust optimization is determined by a measure of insensitiveness with respect to the variation of a response. However, there are significant difficulties associated with the calculation of variations represented as its mean and variance. To overcome the current limitation, this research presents an implementation of the approximate statistical moment method based on kriging metamodel. Two sampling methods are simultaneously utilized to obtain the sequential surrogate model of a response. The statistics such as mean and variance are obtained based on the reliable kriging model and the second-order statistical approximation method. Then, the simulated annealing algorithm of global optimization methods is adopted to find the global robust optimum. The mathematical problem and the two-bar design problem are investigated to show the validity of the proposed method.

다분야 최적화에서의 근사모델 관리기법의 활용 (Managing Approximation Models in Multidisciplinary Optimization)

  • 양영순;정현승;연윤석
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2000년도 가을 학술발표회논문집
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    • pp.141-148
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    • 2000
  • In system design, it is not always possible that all decision makers can cooperate fully and thus avoid conflict. They each control a specified subset of design variables and seek to minimize their own cost functions subject to their individual constraints. However, a system management team makes every effort to coordinate multiple disciplines and overcome such noncooperative environment. Although full cooperation is difficult to achieve, noncooperation also should be avoided as possible. Our approach is to predict the results of their cooperation and generate approximate Pareto set for their multiple objectives. The Pareto set can be obtained according to the degree of one's conceding coupling variables in the other's favor. We employ approximation concept for modelling this coordination and the mutiobjective genetic algorithm for exploring the coupling variable space for obtaining an approximate Pareto set. The approximation management concept is also used for improving the accuracy of the Pareto set. The exploration for the coupling variable space is more efficient because of its smaller dimension than the design variable space. Also, our approach doesn't force the disciplines to change their own way of running analysis and synthesis tools. Since the decision making process is not sequential, the required time can be reduced comparing to the existing multidisciplinary optimization techniques. This approach is applied to some mathematical examples and structural optimization problems.

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휴대폰용 카메라 모듈의 렌즈 시스템에 대한 공차 해석 및 설계 개선에 관한 연구 (Tolerance Analysis and Design Improvement of a Lens System for Mobile Phone Camera)

  • 정상진;최병렬;최동훈;김주호
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2008년도 추계학술대회A
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    • pp.1063-1068
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    • 2008
  • A lens system of a camera module for mobile phones is comprised of the composition and design of various shapes of lens. To improve responses such as the modular transfer function (MTF), a lens system should always be constructed by considering uncertainty that can be caused by manufacturing and assembly error. In this study, tolerance optimization using the Latin Hypercube Sampling (LHS) technique is performed. In order to reduce the computational burden of the tolerance optimization process and decrease the influence from numerical noise effectively, we use the Progressive Quadratic Response Surface Modeling (PQRSM), which is one of Sequential Approximate Optimization (SAO) techniques. Using this method, we achieved optimal tolerance for each lens and obtained reliability for satisfying user‘s requirements. In addition, through the design process the manufacturing and assembly cost of a lens system was reduced.

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