• International Journal of CAD/CAM
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• v.7 no.1
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• pp.61-69
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• 2007

The objective of this work is to integrate reliability analysis into topology optimization problems. We introduce the reliability constraint in the topology optimization formulation, and the new model is called Reliability-Based Topology Optimization (RBTO). The application of the RBTO model gives a different topology relative to the classical topology optimization that should be deterministic. When comparing the structures resulting from the deterministic topology optimization and from the RBTO model, the RBTO model yields structures that are more reliable than the deterministic ones (for the same weight). Several applications show the importance of this integration.

• 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 Communications and Networks
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• v.8 no.3
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• pp.339-350
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• 2006

Several novel concepts and tools have revolutionized our understanding of the Internet topology. Most of the existing efforts attempt to develop accurate analytical models. In this paper, our goal is to develop an effective conceptual model: A model that can be easily drawn by hand, while at the same time, it captures significant macroscopic properties. We build the foundation for our model with two thrusts: a) We identify new topological properties and b) we provide metrics to quantify the topological importance of a node. We propose the jellyfish as a model for the inter-domain Internet topology. We show that our model captures and represents the most significant topological properties. Furthermore, we observe that the jellyfish has lasting value: It describes the topology for more than six years.

• 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.

• 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 Power Electronics
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• v.17 no.6
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• pp.1694-1706
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• 2017

Models and experiments for magnetic resonance coupling wireless power transmission (MRC-WPT) topologies such as the chain topology and branch topology are studied in this paper. Coupling mode theory based energy resonance models are built for the two topologies. Complete energy resonance models including input items, loss coefficients, and coupling coefficients are built for the two topologies. The storage and the oscillation model of the resonant energy are built in the time domain. The effect of the excitation item, loss item, and coupling coefficients on MRC systems are provided in detail. By solving the energy oscillation time domain model, distance enhancing models are established for the chain topology, and energy relocating models are established for the branch topology. Under the assumption that there are no couplings between every other coil or between loads, the maximum transmission capacity conditions are found for the chain topology, and energy distribution models are established for the branch topology. A MRC-WPT experiment was carried out for the verification of the above model. The maximum transmission distance enhancement condition for the chain topology, and the energy allocation model for the branch topology were verified by experiments.

• Journal of Information Technology Applications and Management
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• v.11 no.2
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• pp.205-214
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• 2004

Internet evolves into the huge network with new nodes inserted or deleted depending on specific situations. A new model of network topology is needed in order to analyze time-varying Internet more realistically and effectively. In this study the non-monotony models are proposed which can describe topological changes of Internet such as node insertion and deletion, and can be used for predicting its future topology. Simulation is performed to analyze the topology generated by our model. Simulation results show that our proposed model conform the power law of realistic Internet better than conventional ones. The non-monotony model can be utilized for designing Internet protocols and networks with better security.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.523-528
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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. The node density and the morphology technique is 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 surface form digital images.

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.1019-1031
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• 2004

This paper describes a new modeling method for the prediction of transmembrane protein topology. The structural regions of the transmembrane protein have been modeled by means of a multiple state hidden Markov model that has provided for the detailed modeling of the heterogeneous amino acid distributions of each structural region. Grammatical constraints have been incorporated to the prediction method in order to capture the biological order of membrane protein topology. The proposed method correctly predicted 76% of all membrane spanning regions and 92% sidedness of the integration when all membrane spanning regions were found correctly.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.6
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• pp.365-370
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• 2023

This paper presents a particle-structure collision model for topology optimization, which requires sensitivity analysis. Therefore, a new model that incorporates sensitivity analysis is needed. The proposed particle-structure collision model conducts sensitivity analysis for topology optimization. To evaluate the accuracy of the proposed model, it was applied to a simplified one-dimensional collision problem. Optimization of the final positions of particles using topology optimization through this model confirmed the suitability of the proposed approach. These results demonstrate that it is possible to consider particle-structure collision in topology optimization.