• 한국군사과학기술학회지
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• 제8권2호
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• pp.22-29
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• 2005

In this study we performed topology optimization and size optimization about support structure of pressure container which is installed in a Common Bed. The optimization study shows that structure weight optimization results can be applied to navy ship. The topology optimization is performed by static load, homogenization and optimality criteria method and size optimization is performed by SOL200 of NASTRAN.

• Structural Engineering and Mechanics
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• 제77권6호
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• pp.779-795
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• 2021

In the recent decades, various optimization algorithms have been considered for the optimization of structures. In this research, a new enhanced algorithm is used for the size and topology optimization of truss structures. This algorithm, which is obtained from the combination of Crow Search Algorithm (CSA) and the Cellular Automata (CA) method, is called CA-CSA method. In the first iteration of the CA-CSA method, some of the best designs of the crow's memory are first selected and then located in the cells of CA. Then, a random cell is selected from CA, and the best design is chosen from the selected cell and its neighborhood; it is considered as a "local superior design" (LSD). In the optimization process, the LSD design is used to modify the CSA method. Numerical examples show that the CA-CSA method is more effective than CSA in the size and topology optimization of the truss structures.

• 한국공간정보시스템학회:학술대회논문집
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• 한국공간정보시스템학회 2004년도 춘계 학술발표회 논문집 제1권1호(통권1호)
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• pp.43-52
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• 2004

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algerian was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithms. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

• 한국공간구조학회논문집
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• 제10권4호
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• pp.59-66
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• 2010

본 연구는 스페이스 트러스 구조물의 초기 형상을 결정하기 위해 밀도법을 이용한 위상최적화 기술을 고려하고자 한다. 대부분의 초기 형상설계는 다양한 최적화 방법을 활용하지 않고 설계자의 경험이나 시행착오적인 방법을 바탕으로 수행되고 있다. 이런 이유로 합리적이고 경제적인 최적화기술이 초기 형상설계에 도입되어야 한다. 따라서 본 연구에서는 스페이스 트러스 구조물을 대상으로 설계영역을 설정하고 위상최적화를 수행하여 최적의 재료분포를 찾은 뒤 크기최적화를 이용하여 최적부재 크기를 찾고자 한다. 이와 같이 밀도법을 이용한 위상 및 크기최적화를 병행하여 수행할 경우 합리적인 스페이스 트러스 구조물의 초기 형상을 도출할 수 있다.

• 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.

• 한국공간구조학회논문집
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• 제2권3호
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• pp.93-102
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• 2002

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithms. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.558-563
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• 2003

The tracked vehicle travel on off rod and on rod. So the tracked vehicle need a sufficient stiffness and a lightweight. In this study we performed FEA for the track vehicle and performed topology optimization based on the results of FEA. The displacements of road wheel are used as displacement constraint for topology optimization. We performed topology optimization with the control of the frame size which is the results of topology optimization and suggested the shaped of the tracked vehicle bottom plate of topology optimization

• Structural Engineering and Mechanics
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• 제53권5호
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• pp.847-865
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• 2015

This paper presents the application of a recently developed meta-heuristic algorithm, called Colliding Bodies Optimization (CBO), for size and topology optimization of steel trusses. This method is based on the one-dimensional collisions between two bodies, where each agent solution is considered as a body. The performance of the proposed algorithm is investigated through four benchmark trusses for minimum weight with static and dynamic constraints. A comparison of the numerical results of the CBO with those of other available algorithms indicates that the proposed technique is capable of locating promising solutions using lesser or identical computational effort, with no need for internal parameter tuning.

• Architectural research
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• 제14권1호
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• pp.19-26
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• 2012

The technique of integrated design optimization is proposed to design spatial structures. Various element technologies such as topology optimization, layout editing and size optimization processes are used in an integrated manner to improve the performance of spatial structures. In order to demonstrate the present technique, a unit spatial structure is optimized and numerical results are described here.

• 한국공간구조학회논문집
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• 제3권3호
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• pp.67-74
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• 2003

The purpose of this study is to improve convergence speed of topology optimization procedure using the existing ESO method and to deal with topology decision of the truss structures according to a boundary condition, such as cantilever type. At the existing ESO topology optimization procedure for the truss structures, the adjustment of member sizes according to target stress has been executed by increasing or reducing a very small value from each member size. In this case, it takes too much iteration till convergence. Accordingly, it is practically hard to obtain optimum topology for a large scale structures. For that reason, it is necessary to improve convergence speed of ESO method more effectively. During the topology decision procedure, member sizes are adjusted by calculating approximate solution for member sizes corresponding to the target stress at every step, the new member sizes are adjusted by such method are applied in FEA procedure of next step.