• 한국전산유체공학회:학술대회논문집
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• 2000.05a
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• pp.60-65
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• 2000

An aerodynamic design method has been developed by using a three-dimensional unstructured Euler code and an adjoint code with a discrete approach. The resulting adjoint code is applied to a wing design problem of super-sonic transport with a wing-body-nacelle configuration. Hicks-Henne shape functions are adopted far the surface geometry perturbation, and the elliptic equation method is employed fer the interior grid modification during the design process. Interior grid sensitivities are neglected except those for design parameters associated with nacelle translation. The Sequential Quadratic Programming method is used to minimize the drag with constraints on the lift and airfoil thickness. Successful design results confirm validity and efficiency of the present design method.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.822-824
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• 2005

This paper presents a scheme to solve the congestion problem using phase-shifting transformer(PST) in power systems. Available transfer capability(ATC) is an important indicator of the usable amount of transmission capacity accessible by several parties for commercial trading in power transaction activities. This paper deals with an application of optimization technique for ATC calculation. Sequential quadratic programming(SQP) is used to maximize power flow of tie line subject to security constraints such as voltage magnitude and real power flow. The proposed method is applied to 10 machines 39 buses model systems to show its effectiveness.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.931-939
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• 2014

In this paper we propose the iteratively reweighted least squares procedure to solve the quadratic programming problem of support vector expectile regression with an asymmetrically weighted squares loss function. The proposed procedure enables us to select the appropriate hyperparameters easily by using the generalized cross validation function. Through numerical studies on the artificial and the real data sets we show the effectiveness of the proposed method on the estimation performances.

• Journal of Mechanical Science and Technology
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• v.15 no.2
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• pp.192-198
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• 2001

We consider an interpolation problem with nonuniform rational B-spline curves given ordered data points. The existing approaches assume that weight for each point is available. But, it is not the case in practical applications. Schneider suggested a method which interpolates data points by automatically determining the weight of each control point. However, a drawback of Schneiders approach is that there is no guarantee of avoiding undesired poles; avoiding negative weights. Based on a quadratic programming technique, we use the weights of the control points for interpolating additional data. The weights are restricted to appropriate intervals; this guarantees the regularity of the interpolating curve. In a addition, a knot placement is proposed for pleasing interpolation. In comparison with integral B-spline interpolation, the proposed scheme leads to B-spline curves with fewer control points.

• Structural Engineering and Mechanics
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• v.51 no.2
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• pp.229-248
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• 2014

In this paper, the development of a new optimization software for finite element model updating of engineering structures titled as FemUP is described. The program is used for computational FEM model updating of structures depending on modal testing results. This paper deals with the FE model updating procedure carried out in FemUP. The theoretical exposition on FE model updating and optimization techniques is presented. The related issues including the objective function, constraint function, different residuals and possible parameters for FE model updating are investigated. The issues of updating process adopted in FemUP are discussed. The ideas of optimization to be used in FE model updating application are explained. The algorithm of Sequential Quadratic Programming (SQP) is explored which will be used to solve the optimization problem. The possibilities of the program are demonstrated with a three dimensional steel frame model. As a result of this study, it can be said that SQP algorithm is very effective in model updating procedure.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2001.09a
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• pp.339-347
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• 2001

A probabilistic optimum design method of the base isolation system consisting of linear spring, viscous damper and frictional element is presented. For the probabilistic approach, the base excitation is assumed to be a stationary Gaussian filtered random process. For optimum design, the objective function and constraints are derived based on the stochastic responses of the system. As a numerical example, the optimum design problem of a three-story base isolated shear type structure is formulated and solved by the sequential quadratic programming method. As a result, the effects of variation of design variables such as parameters of the base isolation system and the mass of base on the objective function and constraints are investigated and the optimum parameters of the base isolation system under study are derived.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.43-48
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• 2003

In this study the optimization of plate-fin type heat sink for the thermal stability is performed numerically. The optimum design variables are obtained when the temperature rise and the pressure drop are minimized simultaneously. The flow and thermal fields are predicted using the finite volume method and the optimization is carried out by using the sequential quadratic programming (SQP) method which is widely used in the constrained nonlinear optimization problem. The results show that when the temperature rise is less than 34.6 K, the optimal design variables are as follows; $B_{1}$ = 2.468 mm, $B_{2}$ = 1.365 mm, and t = 10.962 mm. The Pareto optimal solutions are also presented for the pressure drop and the temperature rise.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.2
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• pp.70-78
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• 2005

In this paper, a novel rotor flux estimation method of an induction motor using support vector regression(SVR) is presented. Two well-known different flux models with respect to voltage and current are necessary to estimate the rotor flux of an induction motor. Training of SVR which the theory of the SVR algorithm leads to a quadratic programming(QP) problem. The proposed SVR rotor flux estimator guarantees the improvement of performance in the transient and steady state in spite of parameter variation circumstance. The validity and the usefulness of proposed algorithm are throughly verified through numerical simulation.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.35 no.2
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• pp.201-208
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• 1999

To develop a new fish cage which is required for offshore or moving cage culturing system has been gradually increased against being closely dense of fish cage in shallow water. Though submersible fish cage culturing system is essential technology for converting from shallow water into the offshore, it was pointed out the serious problem about stability of which are sinking and floating state. This study is presented conceptual design of submersible fish cage centered with a mooring steel pile to acquire stability and faculty. Design of mooring steel pile for submersible fish cage culturing system needs to carry out optimal design of mooring steel pile for which much efforts are required. Formulation and optimal design process of submersible fish cage are organized into using Sequential Quadratic Programming method of numerical optimization. For submersible fish cage system centered with a mooring steel pile, process of the optimal design is proposed and the optimal solutions are obtained.

• ETRI Journal
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• v.31 no.2
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• pp.121-128
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• 2009

In this paper, we describe a fixed-threshold sequential minimal optimization (FSMO) for structured SVM problems. FSMO is conceptually simple, easy to implement, and faster than the standard support vector machine (SVM) training algorithms for structured SVM problems. Because FSMO uses the fact that the formulation of structured SVM has no bias (that is, the threshold b is fixed at zero), FSMO breaks down the quadratic programming (QP) problems of structured SVM into a series of smallest QP problems, each involving only one variable. By involving only one variable, FSMO is advantageous in that each QP sub-problem does not need subset selection. For the various test sets, FSMO is as accurate as an existing structured SVM implementation (SVM-Struct) but is much faster on large data sets. The training time of FSMO empirically scales between O(n) and O($n^{1.2}$), while SVM-Struct scales between O($n^{1.5}$) and O($n^{1.8}$).