• 한국CDE학회논문집
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• 제9권2호
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• pp.122-132
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• 2004

Progressive mesh representation and generation have become one of the most important issues in network-based computer graphics. However, current researches are mostly focused on triangular mesh models. On the other hand, solid models are widely used in industry and are applied to advanced applications such as product design and virtual assembly. Moreover, as the demand to share and transmit these solid models over the network is emerging, the generation and the transmission of progressive solid models depending on specific engineering needs and purpose are essential. In this paper, we present a Cellular Topology-based approach to generating and transmitting progressive solid models from a feature-based solid model for internet-based design and collaboration. The proposed approach introduces a new scheme for storing and transmitting solid models over the network. The Cellular Topology (CT) approach makes it possible to effectively generate progressive solid models and to efficiently transmit the models over the network with compact model size. Thus, an arbitrary solid model SM designed by a set of design features is stored as a much coarser solid model SM/sup 0/ together with a sequence of n detail records that indicate how to incrementally refine SM/sup 0/ exactly back into the original solid model SM = SM/sup 0/.

• ETRI Journal
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• 제41권5호
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• pp.648-657
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• 2019

A cluster topology was proposed with the assumption of zero noise to improve the performance of wireless body area networks (WBANs). However, in WBANs, the transmission power should be reduced as low as possible to avoid the effect of electromagnetic waves on the human body and to extend the lifetime of a battery. Therefore, in this work, we consider a bit error rate for a cluster-based WBAN and analyze the performance of the system while the transmission of sensors and cluster headers (CHs) is controlled. Moreover, a hierarchical topology is proposed for the cluster-based WBAN to further improve the throughput of the system; this proposed system is called as the hierarchical cluster WBAN. The hierarchical cluster WBAN is combined with a transmission control scheme, that is, complete control, spatial reuse superframe, to increase the throughput. The proposed system is analyzed and evaluated based on several factors of the system model, such as signal-to-noise ratio, number of clusters, and number of sensors. The calculation result indicates that the proposed hierarchical cluster WBAN outperforms the cluster-based WBAN in all analyzed scenarios.

• 한국생산제조학회지
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• 제19권2호
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• pp.224-229
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• 2010

This paper presents a reliability-based topology optimization (RBTO) using bi-directional evolutionary structural optimization (BESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. Deterministic topology optimization (DTO) is obtained without considering of uncertainties related to the uncertainty parameters. However, the RBTO can consider the uncertainty variables because it has the probabilistic constraints. In this paper, the reliability index approach (RIA) is adopted to evaluate the probabilistic constraint. RBTO based on BESO starting from various design domains produces a similar optimal topology each other. Numerical examples are presented to compare the DTO with the RBTO.

• Journal of Power Electronics
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• 제17권5호
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• pp.1195-1202
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• 2017

This paper presents a novel topology named a modified capacitor-assisted Z-source inverter (MCA-ZSI) based on the traditional ZSI. The impedance network of the proposed MCA-ZSI consists of two symmetrical cells coupled with two capacitors with an X-shape structure, and each cell has two inductors, two capacitors, and one diode. Compared with other topologies based on switched ZSI with the same number of components used at impedance network, the proposed topology provides higher boost ability, lower voltage stress across inverter switching devices, and lower capacitor voltage stress. The improved performances of the proposed topology are demonstrated in the simulation and experimental results.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2007년도 하계학술대회 논문집
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• pp.286-288
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• 2007

The proposed method offers an improved control method for high power density AC/DC adapter by using more energy efficient electrical equipments. Power factor corrector (PFC) topology is based on boost topology with boundary conduction mode (BCM). DC/DC topology is based on half-bridge topology with newly introduced off-time control method, which helps to reduce size of the semiconductor and the magnetic devices. Test results with 85W AC/DC adapter (18.5V/4.6A) design shows that the measured efficiency is 90% with power density of $36W/in^3$. It also show low no load power consumption of about 0.5W.

• 대한임베디드공학회논문지
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• 제14권4호
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• pp.219-226
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• 2019

One of the most widely studied protocols for tactical ad-hoc networks is Optimized Link State Routing Protocol (OLSR). As for OLSR research, most research work focus on reducing control traffic overhead and choosing relay point. In addition, because OLSR is mostly dependent on link detection and propagation, dynamic Hello timer become research challenges. However, different timer interval causes imbalance of link validity time by affecting link lifetime. To solve this problem, we propose a weighted topology graph model for constructing a robust network topology based on the link validity time. In order to calculate the link validity time, we use control message timer, which is set for each node. The simulation results show that the proposed mechanism is able to achieve high end-to-end reliability and low end-to-end delay in small networks.

• 한국공간구조학회논문집
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• 제21권4호
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• pp.39-48
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• 2021

In this paper, a GAN-based data augmentation method is proposed for topology optimization. In machine learning techniques, a total amount of dataset determines the accuracy and robustness of the trained neural network architectures, especially, supervised learning networks. Because the insufficient data tends to lead to overfitting or underfitting of the architectures, a data augmentation method is need to increase the amount of data for reducing overfitting when training a machine learning model. In this study, the Ganerative Adversarial Network (GAN) is used to augment the topology optimization dataset. The produced dataset has been compared with the original dataset.

• Steel and Composite Structures
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• 제48권1호
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• pp.73-88
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• 2023

This paper presents a novel implicit level set method for topology optimization of functionally graded (FG) structures with pre-existing discontinuities (pre-cracks) using radial basis functions (RBF). The mathematical formulation of the optimization problem is developed by incorporating RBF-based nodal densities as design variables and minimizing compliance as the objective function. To accurately capture crack-tip behavior, crack-tip enrichment functions are introduced, and an eXtended Finite Element Method (X-FEM) is employed for analyzing the mechanical response of FG structures with strong discontinuities. The enforcement of boundary conditions is achieved using the Hamilton-Jacobi method. The study provides detailed mathematical expressions for topology optimization of systems with defects using FG materials. Numerical examples are presented to demonstrate the efficiency and reliability of the proposed methodology.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2007년도 추계학술대회 논문집
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• pp.555-556
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• 2007

• 대한기계학회:학술대회논문집
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• 대한기계학회 2005년도 창립60주년 기념 추계 학술대회
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• pp.158.1-158.1
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• 2005