• 대한기계학회논문집A
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• 제29권8호
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• pp.1061-1069
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• 2005

In part I of this papter Nonlinear Response Optimization using Equivalent Static Loads (NROESL) method/algorithm is developed to conduct optimization for nonlinear behavior structures. The method/algorithm is also verified to show its convergency and optimality. In this present paper, the NROESL algorithm is applied to several structural problems with geometric and/or material nonlinearity. Conventional optimization with sensitivity analysis using the finite difference method is also applied to the same examples. The results of the optimizations are compared. The proposed method is very efficient and derives good solutions.

• 대한의용생체공학회:의공학회지
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• 제26권6호
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• pp.365-372
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• 2005

Topology optimization method has a great advantage and capability over a conventional shape optimization technique because it optimizes a topology as well as a shape and size of structure. The purpose of the present study, using topology optimization method with an objective function of minimum compliance as a mechanism of bone remodeling, is to examine which shape factors of femur is strongly related with the curvature of femoral shaft. As is expected, the optimized curvature increased definitely with neck angle among the shape factors and showed a similar trend with the measured curvature to neck angle. Therefore, the topology optimization method can be successfully applied in the analysis of bone remodeling phenomenon in the subsequent studies.

• Structural Engineering and Mechanics
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• 제38권4호
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• pp.517-527
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• 2011

A topology optimization and shape optimization method are widely used in the design area of engineering field. In this paper, a unified procedure to combine both topology and shape optimization method is used. A material distribution method is used first to extract necessary design parameters of the structure and a shape optimization scheme using genetic algorithm and satisfying all the condition follows. As an example, a GFRP bridge deck is designed and compared with other commercial products. The performance of the designed deck shows that the used design procedure is very efficient and safe. This procedure can be generalized for using in other areas of engineering.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.2097-2098
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• 2006

In this study, we introduce the hybrid optimization of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA). HFCGA is a kind of multi-populations of Parallel Genetic Algorithms(PGA), and it is used for structure optimization and parameter identification of fuzzy set model. It concerns the fuzzy model-related parameters as the number of input variables, a collection of specific subset of input variables, the number of membership functions, and the apexes of the membership function. In the hybrid optimization process, two general optimization mechanisms are explored. The structural optimization is realized via HFCGA method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집A
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• pp.367-371
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• 2001

In the shape optimization based on the finite element method, the accuracy of finite element analysis of a given structure is important to determine the final shape. In case of a bending dominant problem, finite element solutions by the full integration scheme are not reliable because of the locking phenomenon. Furthermore, in the process of shape optimization, the mesh distortion is large due to the change of the structure outline: therefore, we cannot guarantee the accurate result unless the finite element itself is accurate. We approach to more accurate shape optimization to diminish these inaccuracies by improving the existing finite element. The shape optimization using the modified finite element is applied to a two-dimensional simple beam. Results show that the modified finite element have improved the optimization results.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2006년도 정기 학술대회 논문집
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• pp.541-548
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• 2006

This study presents a structural cost optimization method for building frame system using high-strength steel members. In, this optimization method, the material cost of steel member is involved in objective function to find the optimal cost of building frame systems. Genetic Algorithm is adopted to optimizer to find structural cost optimization. The proposed adapted to structural design of 3.5 stories example buildings with buildings frame systems. As a result, The proposed optimization method can be effectively adapted to cost optimization of building frame systems using high-strength steel members.

• 전기학회논문지
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• 제57권5호
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• pp.748-754
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• 2008

The general capacitor placement problem is a combinatorial optimization problem having an objective function composed of power losses and capacitor installation costs subject to bus voltage constraints. In this paper, a global optimization technique, which employing the chaos search algorithm, is applied to solve optimal capacitor placement problem with reducing computational effort and enhancing global optimality of the solution. Chaos method in optimization problem searches the global optimal solution on the regularity of chaotic motions and easily escapes from local or near optimal solution than stochastic optimization algorithms. The chaos optimization method is tested on 9 buses and 69 buses system to illustrate the effectiveness of the proposed method.

• Structural Engineering and Mechanics
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• 제55권5호
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• pp.901-911
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• 2015

The goal of this study is to investigate computational convergence of optimal solutions, with respect to optimality criteria (OC) method and methods of moving asymptotes (MMA) as optimization model for non-linear programming of material topology optimization using an acceleration method that makes design variables rapidly move toward almost 0 and 1 values. 99 line topology optimization MATLAB code uses loop vectorization and memory pre-allocation as properly exploiting the strengths of MATLAB and moves portions of code out of the optimization loop so that they are only executed once as restructuring the program. Numerical examples of a simple beam under a lateral load and a given material density limitation provide merits and demerits of the present OC and MMA for 99 line topology optimization code of continuous material topology optimization design.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제54권4호
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• pp.163-173
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• 2005

The conventional optimization study for electromagnetic systems has been mostly on the shape or size optimization. The goal for these optimization methods is to improve performance of electromagnetic systems by optimizing the interface shape of two different materials while their given layout or initial topology are held. The feasible topology can be diverse and an appropriate topology will give much better design results. In this paper we propose a theory and an algorithm for topology optimization of electromagnetic systems, which are based on the finite element method. The topology optimization technique employes a direct searching method of sensitivity analysis in which the information of material sensitivity is used. Two numerical examples of a switched reluctance motor and an electrostatic actuator of MEMS are tested and their design results show that the optimization method is valid and useful for the topology and basic layout design of electromagnetic systems.

• Journal of Magnetics
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• 제18권3호
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• pp.283-288
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• 2013

This paper presents structural topology optimization that is being applied for the design of electromagnetic vibration energy harvester. The design goal is to maximize the root-mean-square value of output voltage generated by external vibration leading structures. To calculate the output voltage, the magnetic field analysis is performed by using the finite element method, and the obtained magnetic flux linkage is interpolated by using Lagrange polynomials. To achieve the design goal, permanent magnet is designed by using topology optimization. The analytical design sensitivity is derived from the adjoint variable method, and the formulated optimization problem is solved through the method of moving asymptotes (MMA). As optimization results, the optimal location and shape of the permanent magnet are provided when the magnetization direction is fixed. In addition, the optimization results including the design of magnetization direction are provided.