• 한국공간정보시스템학회:학술대회논문집
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• 2004.05a
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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

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.355.1-355
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• 2002

Topology optimization is widely accepted as a conceptual design tool for the product design. Since the resulted layout of the topology optimization is a kind of digital images represented by the density distribution, the seamless process is required to transform digital images to the CAD model for the practical use. In this paper, the general process to construct a CAD model is developed to apply for topology images based on elements. (omitted)

• Journal of Korean Association for Spatial Structures
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• v.2 no.3 s.5
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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

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.354-359
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• 2007

A new level set based topology optimization employing inner-front creation algorithm is presented. In the conventional level set based topology optimization, the optimum topology strongly depends on the initial level set distribution due to the incapability of inner-front creation during optimization process. In the present work, an inner-front creation algorithm is proposed, in which the sizes, positions, and number of new inner-fronts during the optimization process can be globally and consistently identified. To update the level set function during the optimization process, the least-squares finite element method is employed. As demonstrative examples for the flexibility and usefulness of the proposed method, the level set based topology optimization considering lightweight design of 3D shell structure is carried out.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.11
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• pp.1925-1932
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• 2003

Topology optimization is widely accepted as a conceptual design tool for the product design. Since the resulted layout of the topology optimization is a kind of digital images represented by the density distribution, the seamless process is required to transform digital images to the CAD model for the practical use. In this paper, the general process to construct a CAD model is developed to apply for topology images based on elements. The node density and the morphology technique are adopted to extract boundary contour of the shape and remove the noise of images through erosion and dilation operation. The proposed method automatically generates point data sets of the geometric model. The process is integrated with Pro/Engineer, so that the engineer in practice can directly handle with curves or surfaces form digital images.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.2
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• pp.1-10
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• 2010

Mapping virtual process topology to physical processor topology is one of the most important design issues in parallel programming. However, the mapping problem is complicated due to the topology irregularity and routing complexity. This paper proposes a new process mapping scheme called adjacency-based mapping (AM) for irregular cluster systems assuming that the two-dimensional mesh process topology is specified as an interprocess communication pattern. The cluster systems have been studied and developed for many years since they provide high interconnection flexibility, scalability, and expandability which are not attainable in traditional regular networks. The proposed AM tries to map neighboring processes in virtual process topology to adjacent processors in physical processor topology. Simulation study shows that the proposed AM results in better mapping quality and shorter interprocess latency compared to the conventional approaches.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.157-162
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• 2007

A new level set based topology optimization employing inner-front creation algorithm is presented. In the conventional level set based topology optimization, the optimum topology strongly depends on the initial level set distribution due to the incapability of inner-front creation during optimization process. In the present work, in this regard, an inner-front creation algorithm is proposed. in which the sizes. shapes. positions, and number of new inner-fronts during the optimization process can be globally and consistently identified by considering both the value of a given criterion for inner-front creation and the occupied volume (area) of material domain. To facilitate the inner-front creation process, the inner-front creation map which corresponds to the discrete valued criterion of inner-front creation is applied to the level set function. In order to regularize the design domain during the optimization process, the edge smoothing is carried out by solving the edge smoothing partial differential equation (PDE). Updating the level set function during the optimization process, in the present work, the least-squares finite element method (LSFEM) is employed. As demonstrative examples for the flexibility and usefulness of the proposed method. the level set based topology optimization considering lightweight design of 3D shell structure is carried out.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.4
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• pp.100-106
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• 2022

Topology optimization is applied for the optimal design of various products to ensure weight reduction and productivity improvement. Reducing the weight of the mold while maintaining its rigidity can ensure shortening of the production cycle, stabilization of the mold temperature, and reduction of mold material costs. In this study, a topology optimization technique was applied to the optimal design of the injection mold, and a topology-optimized model of the mold was obtained. First, the injection mold for the square specimens was modeled. Subsequently, a structural analysis was performed by implementing a load condition generated during the injection molding process. Topology optimization was performed based on the structural analysis results, and the models of the initial and topology-optimized designs were manufactured at 1/4 magnification using a 3D printer. Consequently, compared with the existing model, the weight of the topology-optimized model decreased by 9.8%, and the manufacturing time decreased by 7.61%.

• Communications of the Korean Mathematical Society
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• v.12 no.1
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• pp.127-133
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• 1997

In order to study the limits of sequences appearing in, for example, stochastic process, A. V. Skorokhod has defined new function space topologies. We compare these topologies with the topology of compact convergence, the topology of pointwise convergence and others.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.345-350
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• 2000

In this paper, we introduce a new artificial material model for topology optimization. The present material model, named S-shape material model, accelerates topology optimization process especially in mathematical programming. We overcome the instability and the flatness in heuristic optimization process. Numerical examples show the superiority of the proposed material.