• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.7
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• pp.601-608
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• 2015

The static aeroelastic analysis and optimization of flexible wings are conducted for steady state conditions while both aerodynamic and structural parameters can be used as optimization variables. The system of multidisciplinary design optimization as a robust methodology to couple commercial codes for a static aeroelastic optimization purpose to yield a convenient adaptation to engineering applications is developed. Aspect ratio, taper ratio, sweepback angle are chosen as optimization variables and the skin thickness of the wing. The real-coded adaptive range multi-objective genetic algorithm code, which represents the global multi-objective optimization algorithm, was used to control the optimization process. The support vector regression(SVR) is applied for optimization, in order to reduce the time of computation. For this multi-objective design optimization problem, numerical results show that several useful Pareto optimal designs exist for the flexible wing.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.1
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• pp.1-8
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• 2014

Using the level set and the meshfree methods, we develop a topological shape optimization method applied to linear elasticity problems. Design gradients are computed using an efficient adjoint design sensitivity analysis(DSA) method. The boundaries are represented by an implicit moving boundary(IMB) embedded in the level set function obtainable from the "Hamilton-Jacobi type" equation with the "Up-wind scheme". Then, using the implicit function, explicit boundaries are generated to obtain the response and sensitivity of the structures. Global nodal shape function derived on a basis of the reproducing kernel(RK) method is employed to discretize the displacement field in the governing continuum equation. Thus, the material points can be located everywhere in the continuum domain, which enables to generate the explicit boundaries and leads to a precise design result. The developed method defines a Lagrangian functional for the constrained optimization. It minimizes the compliance, satisfying the constraint of allowable volume through the variations of boundary. During the optimization, the velocity to integrate the Hamilton-Jacobi equation is obtained from the optimality condition for the Lagrangian functional. Compared with the conventional shape optimization method, the developed one can easily represent the topological shape variations.

• Computational Structural Engineering
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• v.9 no.1
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• pp.141-149
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• 1996

Efficient approximate reanalysis techniques based on substructuring are presented. In most optimal design problems, the analysis precedure must be repeated many times. In particular, one of the main obstacles in the structural optimization systems is high computational cost and time required for the repeated analysis of large-scale structural systems. The purpose of this paper is to show how to evaluate efficiently the sturctural behavior of new designs using information from the previous ones, instead of the multiple repeated analysis of basic equations for successive modification in the optimal design. The proposed reanalysis method is a combined Taylor series expansion and reduced basis method based on substructuring. Several numerical examples illustrate the effectiveness of the method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.1 s.71
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• pp.27-37
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• 2006

A Metropolis genetic algorithm (MGA) is developed and applied for the structural design optimization. In MGA, favorable features of Metropolis criterion of simulated annealing (SA) are incorporated in the reproduction operations of simple genetic algorithm (SGA). This way, the MGA maintains the wide varieties of individuals and preserves the potential genetic information of early generations. Consequently, the proposed MGA alleviates the disadvantages of premature convergence to a local optimum in SGA and time consuming computation for the precise global optimum in SA. Performances and applicability of MGA are compared with those of conventional algorithms such as Holland's SGA, Krishnakumar's micro GA, and Kirkpatrick's SA. Typical numerical examples are used to evaluate the computational performances, the favorable features and applicability of MGA. The effects of population sizes and maximum generations are also evaluated for the performance reliability and robustness of MGA. From the theoretical evaluation and numerical experience, it is concluded that the proposed MGA Is a reliable and efficient tool for structural design optimization.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2639-2641
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• 2000

계수적 구간 불확실 플랜트를 안정화하는 강인 제어기의 설계의 방법으로서 고정차수 극 배치(FOPA : Fixed Order Pole Assighnment) 알고리즘을 이용할 수 있다. FOPA 알고리즘에 의해서 강인제어기 계수의 집합은 선형제약조건으로 표현되고, 이 조건을 만족하는 임의의 한점은 주어진 불확실 시스템을 안정화한다. 본 논문에서는 선형제약조건으로 주어진 제어기 계수의 집합에서 외란의 에너지를 최소화하는 제어기를 구하는 알고리즘을 제안한다. 일반적으로 전역 최적해을 구하는 문제는 BMI(bilinear matrix inequalities)로 표현되지만 제어기의 계수를 고정했을 때는 LMI(lineal matrix inequalities)로 간략화되기 때문에 제어기계수에 대한 최소화와 성능지수에 대한 최소화를 반복함으로써 국부 최적해를 구할 수 있다. 제안한 알고리즘의 효용성을 보이기 위해 제어기 설계 예를 보이고, 그 성능을 비교 분석한다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.6
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• pp.40-50
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• 2002

In this paper, we present a GA(Genetic Algorithm) approach to select weighting matrices of an optimal LQ(Linear Quadratic) controller for SVC(Static VAR Compensator). A SVC, one of the FACTS(Flexible AC Transmission System), constructed by a FC(Fixed Capacitor) and a TCR(Thyristor Controlled Reactor), was designed and implemented to improve the damping of a synchronous generator, as well as to control the system voltage Also, a design of LQ controller depends on choosing weighting matrices. The selection of weighting matrices which is not a trivial solution is usually carried out by trial and error. We proposed an efficient method using GA of finding weighting matrices for optimal control law. Thus, we proved the usefulness of proposed method to improve the stability of single machine-infinite bus with SVC system by eigenvalues analysis and simulation.

• Journal of the Korea Society for Simulation
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• v.25 no.1
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• pp.1-9
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• 2016

This study focuses on the air to air missile control fin planform optimization for the minimizing hinge moment with the considering phenomena of fluid and structure simultaneously. The fluid-structure interaction method is applied for the fluid and structure phenomena simulation of the control fins. A transient-loosely coupled method is used for the fluid-structure interaction simulation because it is suited for using each fluid and structure dedicated simulation software. Searching global optimization point is required many re-calculation therefore in this study, a mathematical model is applied for rapidly calculation. The face centered central composite method is used for generating design points and the 2nd polynomial response surface is sued for generating mathematical model. Global optimization is performed by using the generic algorithm. An objective function is the minimizing travel distance of the center of pressure between Mach 0.7 and 2.0 condition. Finally, the objective function of optimized planform is reduced 7.5% than the baseline planform with satisfying constrained conditions.

• The Journal of Information Technology
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• v.5 no.4
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• pp.73-79
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• 2002

In this paper, I will propose the Niche-Meta Genetic Algorithm that has a multi-mutation operator for design of fuzzy controller. The gene in the proposed algorithm is formed by several parameters that represent the crossover rate, mutation rate and input-output membership functions. The optimization of fuzzy membership function is performed with local search on sub-population and the optimal structure is constructed with global search on total-population. The multi-mutation is selected under basis of the result of local evolution. A simulation for 2 D.O.F wheeled-mobile robot is showed to prove the efficiency of the proposed algorithm

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.191-194
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• 2001

멀티미디어 응용의 확산에 따라 MOD와 같은 서비스와 이를 뒷받침하기 위해 네트웍 환경이 급증하고 있다. 이러한 서비스는 네트웍을 이용하므로 실시간성과 최적의 스케줄링 알고리즘이 필요하다. 본 논문에서는 가변적인 네트웍 상황을 고려한 전역시간 동기화 방법을 제안한다. 제안한 알고리즘은 UDP환경 하에서의 설계 및 구현하였다. 성능 측정은 여러 가지 네트웍 환경에서 측정하였다. 제안한 알고리즘을 통해 측정된 데이터분석에 의해 서버 시간에 근접한 시간동기화를 얻을 수 있으므로 클라이언트의 QoS를 높일 수 있다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.6
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• pp.367-374
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• 2022

This papter presents the use of the automatic differential method based on the backpropagation method to obtain the design sensitivity and its application to topology optimization considering the stress constraints. Solving topology optimization problems with stress constraints is difficult owing to singularities, the local nature of stress constraints, and nonlinearity with respect to design variables. To solve the singularity problem, the stress relaxation technique is used, and p-norm for stress constraints is applied instead of local stresses for global stress measures. To overcome the nonlinearity of the design variables in stress constraint problems, it is important to analytically obtain the exact design sensitivity. In conventional topology optimization, design sensitivity is obtained efficiently and accurately using the adjoint variable method; however, obtaining the design sensitivity analytically and additionally solving the adjoint equation is difficult. To address this problem, the design sensitivity is obtained using a backpropagation technique that is used to determine optimal weights and biases in the artificial neural network, and it is applied to the topology optimization with the stress constraints. The backpropagation technique is used in automatic differentiation and can simplify the calculation of the design sensitivity for the objectives or constraint functions without complicated analytical derivations. In addition, the backpropagation process is more computationally efficient than solving adjoint equations in sensitivity calculations.