• Title/Summary/Keyword: Optimal Design

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Optimal Design for Locally Weighted Quasi-Likelihood Response Curve Estimator

  • Park, Dongryeon
    • Communications for Statistical Applications and Methods
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    • v.9 no.3
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    • pp.743-752
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    • 2002
  • The estimation of the response curve is the important problem in the quantal bioassay. When we estimate the response curve, we determine the design points in advance of the experiment. Then naturally we have a question of which design would be optimal. As a response curve estimator, locally weighted quasi-likelihood estimator has several more appealing features than the traditional nonparametric estimators. The optimal design density for the locally weighted quasi-likelihood estimator is derived and its ability both in theoretical and in empirical point of view are investigated.

Optimal Design and Development of Electromagnetic Linear Actuator for Mass Flow Controller

  • Chung, Myung-Jin;Gweon, Dae-Gab
    • Journal of Mechanical Science and Technology
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    • v.17 no.1
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    • pp.40-47
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    • 2003
  • In this paper, we constructed the analytic model of control valve as a function of electric and geometric parameters, and analyzed the influence of the design parameters on the dynamic characteristics. For improving the dynamic characteristics, optimal design is conducted by applying sequential quadratic programming method to the analytic model. This optimal design aims to minimize the response time and maximize force efficiency. By this procedure, control valve can be designed to have fast response in motion.

Kinematic Optimal Design of a Stewart Platform based on Dexterity (조작성에 근거한 스튜엇트 플렛폼의 기구학적 최적설계)

  • 김한성;최용제
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.04a
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    • pp.771-777
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    • 1996
  • In this paper, an optimal design technique for a Stewart platform has been presented considering workspace and dexterity. In the definition of a design objective function, previously suggested dexterity index was used to be maximized. In this optimal design process, the workspace can be used as design constraint when necessary. An algorithm for workspace computation has been briefly described. Finally, optimal desigm results for some example cases have been presented.

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Multi-Optimal Designs for Second-Order Response Surface Models

  • Park, You-Jin
    • Communications for Statistical Applications and Methods
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    • v.16 no.1
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    • pp.195-208
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    • 2009
  • A conventional single design optimality criterion has been used to select an efficient experimental design. But, since an experimental design is constructed with respect to an optimality criterion pre specified by investigators, an experimental design obtained from one optimality criterion which is superior to other designs may perform poorly when the design is evaluated by another optimality criterion. In other words, none of these is entirely satisfactory and even there is no guarantee that a design which is constructed from using a certain design optimality criterion is also optimal to the other design optimality criteria. Thus, it is necessary to develop certain special types of experimental designs that satisfy multiple design optimality criteria simultaneously because these multi-optimal designs (MODs) reflect the needs of the experimenters more adequately. In this article, we present a heuristic approach to construct second-order response surface designs which are more flexible and potentially very useful than the designs generated from a single design optimality criterion in many real experimental situations when several competing design optimality criteria are of interest. In this paper, over cuboidal design region for $3\;{\leq}\;k\;{\leq}\;5$ variables, we construct multi-optimal designs (MODs) that might moderately satisfy two famous alphabetic design optimality criteria, G- and IV-optimality criteria using a GA which considers a certain amount of randomness. The minimum, average and maximum scaled prediction variances for the generated response surface designs are provided. Based on the average and maximum scaled prediction variances for k = 3, 4 and 5 design variables, the MODs from a genetic algorithm (GA) have better statistical property than does the theoretically optimal designs and the MODs are more flexible and useful than single-criterion optimal designs.

Gradient Index Based Robust Optimal Design Method for MEMS Structures (구배 지수에 근거한 MEMS 구조물의 강건 최적 설계 기법)

  • Han, Jeung-Sam;Kwak, Byung-Man
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.7
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    • pp.1234-1242
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    • 2003
  • In this paper we present a simple and efficient robust optimal design formulation for MEMS structures and its application to a resonant-type micro probe. The basic idea is to use the gradient index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-effective and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation. This method, although shown for MEMS structures, may as well be easily applied to conventional mechanical structures where information on uncertainties is lacking but robustness is highly important.

Robust Optimization of a Resonant-type Micro-probe Using Gradient Index Based Robust Optimal Design Method (구배 지수에 근거한 강건 최적 설계 기법을 이용한 공진형 미소탐침의 강건 최적화)

  • Han, Jeong-Sam;Kwak, Byung-Man
    • Proceedings of the KSME Conference
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    • 2003.04a
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    • pp.1254-1261
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    • 2003
  • In this paper we present a simple and efficient robust optimal design formulation and its application to a resonant-type micro probe. The basic idea is to use the Gradient Index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-efficient and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation.

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Optimal Design Variables of a Parallel-Flow Heat Exchanger by Using a Desirability Function Approach (만족도 함수를 이용한 평행류 열교환기 설계인자 최적화)

  • Oh Seok-Jin
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.17 no.6
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    • pp.587-595
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    • 2005
  • The heat and flow characteristics in a parallel-flow heat exchanger were examined numerically to obtain its optimal design variables. A desirability function approach was introduced to optimize its performance with respect to the design parameters over the design domain. By varying the importance of heat transfer and pressure drop which are out put variables, the optimal values of the design parameters are examined. As a result, the us-age of the desirability function is very effective for the optimization of the design variables in a heat exchanger since the changes of optimal values are physically appropriate by varying the importance of each output variable.

Shape Optimal Design to Minimize Stress Concentration in the Journal of the Heating Drum for a Hot-Rolling Press (열간압연 프레스용 가열드럼 저어널부의 응력집중 최소화를 위한 형상 최적설계)

  • Kim Won-Jin;Lee Boo-Youn
    • Journal of the Korean Society for Precision Engineering
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    • v.22 no.3 s.168
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    • pp.137-145
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    • 2005
  • The present research deals with structural analysis and optimal design of the heating drum of a hot-rolling press for medium density fiberboard. Stress concentration in the journal of the heating drum is analyzed by the submodel technique of the finite element method. The fatigue life under operating conditions is analyzed and evaluated by the stress-life theory. Shape optimal design problems, to minimize the maximum stress occurring in the journal, are formulated and shape parameters of the corner fillets of the journal are defined as the design variables. The problems are solved by the numerical optimization method and optimal shapes are found. The optimal designs are shown to be reliable in terms of the maximum stress and the fatigue life.

Optimal model of transportation for people with disabilities: Conceptual proposal designed in CAD

  • Vergunova, Nataliia;Vergunov, Sergey
    • Advances in Computational Design
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    • v.5 no.4
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    • pp.381-396
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    • 2020
  • This study aimed to develop an optimal model of transportation for people with disabilities. To achieve this goal, powers of research and design should be involved, including CAD software. This paper investigates both: the concept of optimal model of transportation for people with disabilities (functional, ergonomic, constructive, technological and aesthetic solutions included); and its implementation as a fully-fledged 3D-model designed in SolidWorks environment. The optimal model of transportation is complex and consists of two objects. The first object is for indoors that is a wheelchair, the second one is for street driving that is an individual vehicle. The optimal model of transportation is universal and multifunctional, which have become possible with parametric feature-based approach utilized in SolidWorks.

Design optimization of reinforced concrete structures

  • Guerra, Andres;Kiousis, Panos D.
    • Computers and Concrete
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    • v.3 no.5
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    • pp.313-334
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    • 2006
  • A novel formulation aiming to achieve optimal design of reinforced concrete (RC) structures is presented here. Optimal sizing and reinforcing for beam and column members in multi-bay and multistory RC structures incorporates optimal stiffness correlation among all structural members and results in cost savings over typical-practice design solutions. A Nonlinear Programming algorithm searches for a minimum cost solution that satisfies ACI 2005 code requirements for axial and flexural loads. Material and labor costs for forming and placing concrete and steel are incorporated as a function of member size using RS Means 2005 cost data. Successful implementation demonstrates the abilities and performance of MATLAB's (The Mathworks, Inc.) Sequential Quadratic Programming algorithm for the design optimization of RC structures. A number of examples are presented that demonstrate the ability of this formulation to achieve optimal designs.