• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.3
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• pp.264-278
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• 2018

The support structure of an optical mirror system is the one of the important design elements because the one affects the optical aberrations of the mirror surface. In this paper, Lagrange equation of the moving body of the fast steering mirror system(FSM) has been formulated to use with optimization design. Major goals for optimization are to assign the reasonably flexible stiffness to the structure and to enhance the first natural frequency of the mirror and support system in aid of more affordable control bandwidth for the FSM. Pursuing these purposes with the proposed method, the finite element analysis(FEA), optimization technique and the Zernike polynomial estimation are used for the design effects. It is concluded that the proposed approach for design well guides toward the desired design goals with regards to both structural and optical performances.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.8
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• pp.1071-1079
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• 2018

In this study, the design methodology as well as network architecture of Support Vector Machine based Polynomial Neural Network, which is a kind of the dynamically generated neural networks, is introduced. The Support Vector Machine based polynomial neural networks is given as a novel network architecture redesigned with the aid of polynomial neural networks and Support Vector Machine. The generic polynomial neural networks, whose nodes are made of polynomials, are dynamically generated in each layer-wise. The individual nodes of the support vector machine based polynomial neural networks is constructed as a support vector machine, and the nodes as well as layers of the support vector machine based polynomial neural networks are dynamically generated as like the generation process of the generic polynomial neural networks. Support vector machine is well known as a sort of robust pattern classifiers. In addition, in order to enhance the structural flexibility as well as the classification performance of the proposed classifier, multi-objective particle swarm optimization is used. In other words, the optimization algorithm leads to sequentially successive generation of each layer of support vector based polynomial neural networks. The bench mark data sets are used to demonstrate the pattern classification performance of the proposed classifiers through the comparison of the generalization ability of the proposed classifier with some already studied classifiers.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.246-249
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• 2005

The TFT-LCD is extensively used from a small watch to a large TV display, and the demand is increasing rapidly. The size of R-LCD glass plate becomes more bigger, and the thickness become more thinner with high demands. As a result natural frequency of the TFT-LCD glass plate becomes more lower. The TFT-LCD glass plate will be moved by robot arm and may receive effect of vibration that occur at transfer. Natural frequency of the TFT-LCD glass plate is increased or decrease according to location that robot arm fixs glass plate. Purpose of a this study is finding support location that optimize the first natural frequency of TFT-LCD glass plate. The size optimization method of ANSYS 8.0 is used as the optimization tool search on the optimal support location of TFT-LCD glass plate. The considered number of support point is from 4 to 9.

• Journal of Ocean Engineering and Technology
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• v.24 no.1
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• pp.153-160
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• 2010

This paper deals with the topology optimized design of the riser support structures for floating production storage and offloading units (FPSOs) under global and local loading conditions. For a preliminary study and validation of the numerical approach, a simplified plate under static loading is first evaluated with the representative topology optimization methods, the Homogenization Design Method (HDM) and Density Method (DM) or Simple Isotropic Material with Penalization (SIMP). In the context of the corresponding riser support structures, the design problem is formulated such that structure shapes based on design domain variables are determined by minimizing the compliance subject to a mass target, considering the stress criterion. An initial design model is generated based on an actual FPSO riser support configuration. The topology optimization results present improved design performances under various loading conditions, while staying within the allowable limit of the offshore area.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.5
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• pp.543-551
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• 2011

The paper deals with the comparative study of design optimization based on various approximation techniques in strength design of riser support structure installed on floating production storage and offloading unit(FPSO) using offshore operation loading conditions. The design optimization problem is formulated such that structural member sizing variables are determined by minimizing the weight of riser support structure subject to the constraints of structural strength in terms of loading conditions. The approximation techniques used in the comparative study are response surface method based sequential approximate optimization(RBSAO), Kriging based sequential approximate optimization(KBSAO), and the enhanced moving least squares method(MLSM) based approximate optimization such as CF(constraint feasible)-MLSM and Post-MLSM. Commercial process integration and design optimization(PIDO) tools are employed for the applications of RBSAO and KBSAO. The enhanced MLSM based approximate optimization techniques are newly developed to ensure the constraint feasibility. In the context of numerical performances such as design solution and computational cost, the solution results from approximate techniques based design optimization are compared to actual non-approximate design optimization.

• Geomechanics and Engineering
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• v.9 no.6
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• pp.709-727
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• 2015

The main aim of this study is to introduce optimal design of homogeneous earth dams with oblique and horizontal drains based on particle swarm optimization (PSO) incorporating weighted least squares support vector machine (WLS-SVM). To achieve this purpose, the upstream and downstream slopes of earth dam, the length of oblique and horizontal drains and angle among the drains are considered as the design variables in the optimization problem of homogeneous earth dams. Furthermore, the seepage through dam body and the weight of dam as objective functions are minimized in the optimization process simultaneously. In the optimization procedure, the stability coefficient of the upstream and downstream slopes and the seepage through dam body as the hydraulic responses of homogeneous earth dam are required. Hence, the hydraulic responses are predicted using WLS-SVM approach. The optimal results of illustrative examples demonstrate the efficiency and computational advantages of PSO with WLS-SVM in the optimal design of homogeneous earth dams with drains.

• Journal of KSNVE
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• v.10 no.4
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• pp.648-654
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• 2000

A procedure to determine the realizable optimal positions of rigid supports is suggested to get a maximum fundamental natural frequency. a measured frequency response function based substructure-coupling technique is used to model the supported structure. The optimization procedure carries out the eigenvalue sensitivity analysis with respect to the stiffness of supports. As a result of such stiffness optimization, the optimal rigid-support positions are shown to be determined by choosing the position of the largest stiffness. The optimally determined support conditions are verified to satisfy the eigenvalue limit theorem. To demonstrate the effectiveness of the proposed method, the optimal support positions of a plate model are investigated. Experimental results indicate that the proposed method can effectively find out the optimal support conditions of the structure just based on the measured frequency response functions without any use of numerical model of the structure.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.5
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• pp.411-416
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• 2014

In this research we present design optimization methods for a vehicle-mounted satellite antenna positioner. Our initial antenna positioner was conservatively designed to satisfy a worst case scenario where wind blew across the positioner at the speed of 120 km/h. Investigating stresses and safety based on Finite Element Methods (FEM), we find reflector support frames can be optimized to significantly reduce the weight of the positioner system. Thus, we optimize the reflector support frame from the given initial design while considering weight, maximum stress, maximum allowable deflection, cross section, and thickness. As a result, Shape C and the thickness of 2 mm are determined for the cross section of the reflector support frame. Applying this result, the weight of the new antenna positioner is 57.343 kg, which is decreased by 10.74% compared to the initial conservative design.

• East Asian mathematical journal
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• v.31 no.3
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• pp.371-377
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• 2015

We consider a nondifferentiable robust optimization problem, which has a maximum function of continuously differentiable functions and support functions as its objective function, continuously differentiable functions as its constraint functions. We prove optimality conditions for the nondifferentiable robust optimization problem. We formulate a Wolfe type dual problem for the nondifferentiable robust optimization problem and prove duality theorems.

• Korean Chemical Engineering Research
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• v.52 no.5
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• pp.564-573
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• 2014

Economic optimization of cumene manufacturing process to produce cumene from benzene and propylene was studied. The chosen objective function was the operational profit per year that subtracted capital cost, utility cost, and reactants cost from product revenue and other benefit. The number of design variables of the optimization are 6. Matlab connected to and controlled Unisim Design to calculate operational profit with the given design variables. As the first step of the optimization, design variable points was sampled and operational profit was calculated by using Unisim Design. By using the sampled data, the estimation model to calculate the operational profit was constructed, and the optimization was performed on the estimation model. This study compared second order polynomial and support vector regression as the estimation method. As the sampling method, central composite design was compared with Hammersley sequence sampling. The optimization results showed that support vector regression and Hammersley sequence sampling were superior than second order polynomial and central composite design, respectively. The optimized operational profit was 17.96 MM$ per year, which was 12% higher than 16.04 MM$ of base case.