• International Journal of Aeronautical and Space Sciences
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• v.4 no.1
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• pp.45-52
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• 2003

A three-dimensional aerodynamic shape optimization technique in inviscid compressible flows is developed by using a parallel continuous adjoint formulation on unstructured meshes. A new surface mesh modification method is proposed to overcome difficulties related to patch-level remeshing for unstructured meshes, and the effect of design sections on aerodynamic shape optimization is examined. Applications are made to three-dimensional wave drag minimization problems including an ONERA M6 wing and the EGLIN wing-pylon-store configuration. The results show that the present method is robust and highly efficient for the shape optimization of aerodynamic configurations, independent of the number of design variables used.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.8
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• pp.469-476
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• 2004

In this paper, a 3D shape optimization algorithm which guarantees a smooth optimal shape is presented using parameterized sensitivity analysis. The design surface is parameterized using Bezier spline and B-spline, and the control points of the spline are taken as the design variables. The parameterized sensitivity for the control points are found from that for nodal points. The design sensitivity and adjoint variable formulae are also derived for the 3D non-linear problems. Through an application to the shape optimization of 3D electromagnet to get a uniform magnetic field, the effectiveness of the proposed algorithm is shown.

• Transactions of Materials Processing
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• v.23 no.2
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• pp.103-109
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• 2014

Flexibly-reconfigurable roll forming (FRRF), which is a sheet forming process for multi-curved sheet metal, may solve both the economic and technical problems incurred in using a conventional die forming process. In the FRRF process, the multi-curved sheet metal is formed by different strain distributions on the sheet metal, and the reconfigurable rollers are used as tools during the forming. Therefore, a thorough investigation focused on the reconfigurable rollers is required for the realization of the FRRF process prior to the fabrication of FRRF machine. In the current study, a series of finite element simulations were conducted to study the load distributions experienced by the reconfigurable roller. In order to verify the shape design variables, the effect of the metal thickness on the curvatures of sheet is also presented.

• Journal of Mechanical Science and Technology
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• v.18 no.9
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• pp.1590-1603
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• 2004

In this study the optimization of plate-fin type heat sink with vortex generator for the thermal stability is performed numerically. The optimum solutions in the heat sink are obtained when the temperature rise and the pressure drop are minimized simultaneously. Thermal performance of heat sink is influenced by the heat sink shape such as the base-part fin width, lower-part fin width, and basement thickness. To acquire the optimal design variables automatically, CFD and mathematical optimization are integrated. The flow and thermal fields are predicted using the finite volume method. The optimization is carried out by means of the sequential quadratic programming (SQP) method which is widely used for the constrained nonlinear optimization problem. The results show that the optimal design variables are as follows; B$_1$=2.584 mm, B$_2$=1.741 mm, and t=7.914 mm when the temperature rise is less than 40 K. Comparing with the initial design, the temperature rise is reduced by 4.2 K, while the pressure drop is increased by 9.43 Pa. The relationship between the pressure drop and the temperature rise is also presented to select the heat sink shape for the designers.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.31 no.8
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• pp.663-671
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• 2007

In this work, shape optimization of a wire-wrapped fuel assembly in a liquid metal reactor has been carried out by combining a three-dimensional Reynolds-averaged Navier-Stokes analysis with the radial basis neural network method, a well known surrogate modeling technique for optimization. Sequential Quadratic Programming is used to search the optimal point from the constructed surrogate. Two geometric design variables are selected for the optimization and design space is sampled using Latin Hypercube Sampling. The optimization problem has been defined as a maximization of the objective function, which is as a linear combination of heat transfer and friction loss related terms with a weighing factor. The objective function value is more sensitive to the ratio of the wire spacer diameter to the fuel rod diameter than to the ratio of the wire wrap pitch to the fuel rod diameter. The optimal values of the design variables are obtained by varying the weighting factor.

• Journal of Power Electronics
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• v.13 no.4
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• pp.546-551
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• 2013

This paper deals with the optimum design of the stator and rotor shape of the interior permanent magnet synchronous motors (IPMSM) that are used in applications for automobiles. IPMSMs have the following advantages: high power, high torque, high efficiency, etc. However, cogging torque which causes noise and vibrations is generated at the same time. The optimum design of shape of a IPMSM was carried out with the aim of reducing cogging torque. Six variables which affect to the performance of a IPMSM are chosen. The main effect variables were determined and applied to the response surface methodology (RSM). When compared to the initial model using the finite elements method (FEM), the optimum model highly reduces the cogging torque and improves the total harmonics distortion (THD) of the back-electro motive force (EMF). A prototype of the designed model was manufactured and experimented on to verify the feasibility of the IPMSM.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.306-310
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• 2008

Fuzzy regression, a nonparametric method, can be quite useful in estimating the relationships among variables where the available data are very limited and imprecise. It can also serve as a sound methodology that can be applied to a variety of management and engineering problems where variables are interacting in an uncertain, qualitative, and fuzzy way. A close examination of the fuzzy regression algorithm reveals that the resulting possibility distribution of fuzzy parameters, which makes this technique attractive in a fuzzy environment, is dependent upon an h parameter value. The h value, which is between 0 and 1, is referred to as the degree of fit of the estimated fuzzy linear model to the given data, and is subjectively selected by a decision maker (DM) as an input to the model. The selection of a proper value of h is important in fuzzy regression, because it determines the range of the posibility ditributions of the fuzzy parameters. In this paper, we discuss the interdependent relationship among the h value, membership function shape, and the spreads of fuzzy parameters in fuzzy linear regression with fuzzy input-output using shape-preserving operations.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.1
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• pp.11-20
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• 1993

Sensitivity information is required in the optimal design process. In structural optimization, sensitivity calculation is a bottleneck due to its complexities and expensiveness. Various schemes have been proposed for the calculation. Analytic and finite difference methods are the most popular at the present time. However, they have advantages and disadvantages in different ways. Semi-anayltic method has been suggested to overcome the difficulties. In spite of the excellency, the semi-analytic method has been found to possess numerical error quite much with respect to shape variables. In this research, the error from each method is evaluated and compared using a shape variable. A two-dimensional beam is selected for an example since it has mathematical solution. An efficient method is suggested for the structural optimization which utilizes finite element method.

• Journal of the Ergonomics Society of Korea
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• v.17 no.2
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• pp.49-63
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• 1998

The purpose of this study is to study real body size and ideal body shape by considering the degree of satisfaction of body part and understanding body size by the degree of leanness/obesity. The subjects in this study were 420 males from 18 to 25 years old. Body measurements and surveys were taken and analyzed by mean, standard variation, correlation analysis, regression analysis, crosstabulation analysis, cluster analysis, one-way ANOVA, and Duncan's Test. The results of analyses indicate that the subjects tended to be satisfied with thick chest and upper limbs, wide shoulder width, and preferred to be tall and have big hands and feet. By cluster analysis of 19 variables, the subjects were divided into 4 groups, each consisting 41, 138, 134, and 47 males. Because the 19 variables were body measurements transformed to eliminate the body size factor, this classification was considered to express how lean or how obese a human body appears. The results of one way ANOVA and Duncan's Test indicate that, according to the degree of leanness/obesity from Group I (lean tendency) to Group IV(obese tendency), characteristics of the body shape changed as follows; height became lower, limbs became shorter, trunk and limbs became thicker and weight became heavier. Also it showed that Group IV were most satisfied with chest girth, upper limb girth and shoulder width and Group I with height, hip girth and waist girth.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.306-311
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• 2008

Fuzzy regression, a nonparametric method, can be quite useful in estimating the relationships among variables where the available data are very limited and imprecise. It can also serve as a sound methodology that can be applied to a variety of management and engineering problems where variables are interacting in an uncertain, qualitative, and fuzzy way. A close examination of the fuzzy regression algorithm reveals that the resulting possibility distribution of fuzzy parameters, which makes this technique attractive in a fuzzy environment, is dependent upon an h parameter value. The h value, which is between 0 and 1, is referred to as the degree of fit of the estimated fuzzy linear model to the given data, and is subjectively selected by a decision maker (DM) as an input to the model. The selection of a proper value of h is important in fuzzy regression, because it determines the range of the posibility ditributions of the fuzzy parameters. In this paper, we discuss the interdependent relationship among the h value, membership function shape, and the spreads of fuzzy parameters in fuzzy linear regression with fuzzy input-output using shape-preserving operations.