• 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

• 한국전산구조공학회논문집
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• 제20권1호
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• pp.19-28
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• 2007

이산화 된 구조물의 위상최적화 과정은 균일하게 분포된 재료 밀도의 위상으로 표현되는 초기 설계영역을 시발점으로 한다. 최적화 과정 동안 구조물의 위상은 고정된 설계영역 내에 주어진 최적화 문제를 만족시키는 방향으로 변화하면서, 최종적으로 최적 위상의 재료 밀도 분포를 생산한다. Eschenauer et al.에 의해 제안되었던 설계영역 안에 구멍을 도입하는 개념은 원래 경계면의 최적화 문제에 대해 설계변수의 유한적인 변화를 촉진시켜 최적화의 수렴성 개선을 도모하기 위함이었으나, 위상최적화의 관점에서는 초기 위상의 정의에 따라 다양한 최적 위상이 생산되는 것을 의미한다. 본 연구에서는 초기 설계영역 안에 국소적인 솔리드 상을 도입해 초기 위상에 변화를 주었을 때, 한정된 재료 하에 구조물에 배치 가능한 다양한 최적 위상을 산출할 수 있음을 검증하였다. 수치 예제로서 초기 설계영역 내에 다양한 치수를 가지는 국부적인 원형 솔리드의 고정된 개수를 투입하여 간단한 MBB-보의 위상최적 설계를 수행하였다.

• 정보저장시스템학회논문집
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• 제3권4호
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• pp.178-182
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• 2007

Topology optimization methods are classified into two methods such as the density method and the homogenization method. Those methods need to consider relationships between the material property and the density of each element in a design domain, the relaxation of the design space, etc. However, it is hard to apply on some cases due to the complexity to compose the design objective and its sensitivity analysis. In this paper, a modified topology optimization is proposed to assist designers who do not have mathematical or theoretical background of the topology optimization. In this study, optimal topology of structures can be achieved by the sequential design of experiment (DOE) and the sensitivity analysis. We conducted the DOE with an orthogonal array and the sensitivity analysis of design variables to determine sensitive variables used for connectivity between elements. The modified topology optimization method has advantages such as freedom from penalizing intermediate values and easy application with basic DOE concept.

• 한국자동차공학회논문집
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• 제7권8호
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• pp.224-232
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• 1999

Topology optimization has evolved into a very efficient concept design tool and has been incorporated into design engineering processes in many industrial sectors. In recent years, topology optimization has become the focus of structural design community and has been researched and applied widely both in academia and industry. There are mainly tow approaches for topology optimization of continuum structures ; homogenization and density methods. The homogenization method is to compute is to compute an optimal distribution of microstructures in a given design domain. The sizes of the micro-calvities are treated as design variables for the topology optimization problem. the density method is to compute an optimal distribution of an isotropic material, where the material densities are treated as design variables. In this paper, the density method is used to formulate the topology optimization problem. This optimization problem is solved by using an optimality criteria method. Several example problems are solved to show the usefulness of the present approach.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제3B권2호
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• pp.79-83
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• 2003

The topology optimization for the magnet design is studied. The magnet design in the C-core actuator is investigated by using the derived topology optimization algorithm and finite element method. The design sensitivity equation for the topology optimization is derived using the adjoint variable method and the continuum approach.

• 한국CDE학회논문집
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• 제14권4호
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• pp.281-289
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• 2009

Topology optimization has been widely used for the optimal structure design for weight reduction and high performance. Since the result of three-dimensional topology optimization is represented by the discrete material distribution in finite elements, it is hard to interpret from a design point of view. In this paper, the method for interpreting three-dimensional topology optimization resuIt into a series of cross-sectional curve representation is proposed and interfaced with the existing CAD system for the practical use. The concept of node density and virtual grid is introduced to transform element density values into grid density and material boundaries in each cross section are identified based on the element volume rate to satisfy the amount of material specified in the original design intent. Design exampIes show that three-dimensional topology result can be converted into a form of curve CAD model and the seamless interface with CAD software can be achieved.

• 전기학회논문지
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• 제58권10호
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• pp.1936-1941
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• 2009

This paper deals with a new methodology for topology optimization in which the topology of the design domain may change during the shape optimization process. To achieve this, the concept of the topological gradient is introduced to compute the sensitivity of an objective function when a small hole is drilled in the domain. Based on shape and topological sensitivity values, the shape and topology of the design domain may be simultaneously changed during design iterations if necessary. To verify the advantages and also to facilitate understanding of the method itself, two electrostatic design problems have been tested by using 2D finite element analysis: the first is the inverse problem of a simple dielectric model and the second is the rotor design of a MEMS actuator.

• Structural Engineering and Mechanics
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• 제51권1호
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• pp.67-88
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• 2014

It is shown that topology optimization is a valuable tool for the design of bridge girders. This paper is a follow-up to (Kuty${\l}$owski and Rasiak 2014) and it includes an analysis of truss members' outer dimensions dictated by the standards. Moreover, a frame bridge girder mapped from a selected topology is compared with a typical frame girder on the basis of (Kuty${\l}$owski and Rasiak 2014). The analysis shows that topology optimization by means of the proposed algorithm yields a topology from which one can map a frame bridge girder requiring less material for its construction than the typical frame girder currently used in bridge construction.

• Structural Engineering and Mechanics
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• 제51권1호
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• pp.39-66
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• 2014

This study deals with the design of bridge girder structures and consists of two parts. In the first part an optimal bridge girder topology is determined using a software based on structure compliance minimization with constraints imposed on the body mass, developed by the authors. In the second part, an original way in which the topology is mapped into a bridge girder structure is shown. Additionally, a method of converting the thickness of the bars obtained using the topology optimization procedure into cross sections is introduced. Moreover, stresses and material consumption for a girder design obtained through topology optimization and a typical truss girder are compared. Concluding, this paper shows that topology optimization is a good tool for obtaining optimal bridge girder designs.

• 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