• Proceedings of the Korean Society For Composite Materials Conference
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• 2005.04a
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• pp.17-20
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• 2005

In-situ structural health monitoring of filament wound pressure tanks were conducted during water-pressurizing test using embedded fiber Bragg grating (FBG) sensors. We need to monitor inner strains during working in order to verify the health condition of pressure tanks more accurately because finite element analyses on filament wound pressure tanks usually show large differences between inner and outer strains. Fiber optic sensors, especially FBG sensors can be easily embedded into the composite structures contrary to conventional electric strain gages (ESGs). In addition, many FBG sensors can be multiplexed in single optical fiber using wavelength division multiplexing (WDM) techniques. We fabricated a standard testing and evaluation bottle (STEB) with embedded FBG sensors and performed a water-pressurizing test. In order to increase the survivability of embedded FBG sensors, we suggested a revised fabrication process for embedding FBG sensors into a filament wound pressure tank, which includes a new protecting technique of sensor heads, the grating parts. From the experimental results, it was demonstrated that FBG sensors can be successfully adapted to filament wound pressure tanks for their structural health monitoring by embedding.

• Annual Conference on Human and Language Technology
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• 2015.10a
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• pp.124-128
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• 2015

문맥의존 철자오류는 해당 단어만 봤을 때에는 오류가 아니지만 문맥상으로는 오류인 문제를 말한다. 이러한 문제를 해결하기 위해서는 문맥정보를 보아야 하지만, 형태소 분석 단계에서는 자세한 문맥 정보를 보기 어렵다. 본 논문에서는 형태소 분석 정보만을 이용한 철자오류 수정을 위한 문맥으로 사전훈련(pre-training)된 단어 표현(Word Embedding)를 사용하고, 기존의 기계학습 알고리즘보다 좋다고 알려진 딥 러닝(Deep Learning) 기술을 적용한 시스템을 제안한다. 실험결과, 기존의 기계학습 알고리즘인 Structural SVM보다 높은 F1-measure 91.61 ~ 98.05%의 성능을 보였다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1996.04a
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• pp.182-189
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• 1996

The focus of this study is on the problem of the design of structure of undetermined topology. This problem has been regarded as being the most challenging of structural optimization problems, because of the difficulty of allowing topology to change. Conventional approaches break down when element sizes approach to zero, due to stiffness matrix singularity. In this study, a novel nonlinear Programming formulation of the topology Problem is developed and examined. Its main feature is the ability to account for topology variation through zero element sizes. Stiffness matrix singularity is avoided by embedding the equilibrium equations as equality constraints in the optimization problem. Although the formulation is general, two dimensional plane elasticity examples are presented. The design problem is to find minimum weight of a plane structure of fixed geometry but variable topology, subject to constraints on stress and displacement. Variables are thicknesses of finite elements, and are permitted to assume zero sizes. The examples demonstrate that the formulation is effective for finding at least a locally minimal weight.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.335.1-335
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• 2002

Among many structural dynamics modification methods for plate and shell vibration problems, embedding an emboss to the surface is very efficient. But deciding an optimal position and shape using optimization algorithm needs defining geometry and remeshing the model for every iteration step to implement the method, which takes much numerical cost. (omitted)

• Computational Structural Engineering
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• v.8 no.1
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• pp.161-172
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• 1995

An Integrated processing system for finite element structural analysis has been studied. It is designed to control integratedly the preprocessing, the execution and the postprocessing of a finite element structural analysis program on Windows. It becomes a better graphic user interface(GUI) for the concurrent representation of various inputs and outputs through the dialog-type on multi-windows by the multi-tasking and the object linking and embedding(OLE). Data input can be done easily through menus, dialog boxes and automatic stepwise inputs on the multiple windows, and then output results can be seen with input data on the same screen. Efficiency and validity of the system were examined by solving several numerical examples.

• Structural Engineering and Mechanics
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• v.16 no.4
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• pp.391-404
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• 2003

Local reinforcement in dowel type timber joints is essential to improve ductility, to increase load carrying capacity and to reduce the risk of brittle failure, especially in the case of using solid dowel. In many types of reinforcing materials available today, DVW (densified veneer wood) has been demonstrated to be the most advantages in terms of compatibility, embedding performance and ductility. Preliminary studies show that using appropriately sized DVW discs bonded into the timber interfaces may be an effective way to reinforce the connection. In this paper, non-linear 3-dimensional finite element models, incorporating orthotropic and non-linear material behaviour, have been developed to simulate structural performance of the timber joints locally reinforced by DVW discs. Different contact algorithms were applied to simulate contact conditions in the joints. The models were validated by the corresponding structural tests. Correlation between the experimental results and the finite element simulations is reasonably good. Using validated finite element models, parametric studies were undertaken to investigate effects of the DVW disc sizes and the end distances on shear stresses and normal stresses in a possible failure plane in the joint.

• The Journal of the Acoustical Society of Korea
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• v.37 no.4
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• pp.256-261
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• 2018

There are three types of noise generated inside the vehicle: BSR (Buzz, Squeak, Rattle). In this paper, we propose a classifier that automatically classifies automotive BSR noise by using features extracted from deep convolutional neural networks. In the preprocessing process, the features of above three noises are represented as noise-map using STFT (Short-time Fourier Transform) algorithm. In order to cope with the problem that the position of the actual noise is unknown in the part of the generated noise map, the noise map is divided using the sliding window method. In this paper, internal parameter of the deep convolutional neural networks is visualized using the t-SNE (t-Stochastic Neighbor Embedding) algorithm, and the misclassified data is analyzed in a qualitative way. In order to analyze the classified data, the similarity of the noise type was quantified by SSIM (Structural Similarity Index) value, and it was found that the retractor tremble sound is most similar to the normal travel sound. The classifier of the proposed method compared with other classifiers of machine learning method recorded the highest classification accuracy (99.15 %).

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.6
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• pp.130-137
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• 2018

Many constitutive models for concrete have been developed to predict the nonlinear behavior of concrete members considerably. The constitutive model for reinforcing bar that include the tension stiffening effect due to the bond characteristics between steel bars and concrete is being studied but the bilinear model is generally used. It was found that the buckling of the longitudinal reinforcing bars is controlled the nonlinear behavior of hybrid precast concrete panel, which is being developed for core wall. In this study, the constitutive models that can consider the embedding and buckling effects of reinforcing bar are investigated and a new model combing these constitutive models is proposed. In order to verify the proposed model, the analysis results are compared with experimental results of the concrete wall and hybrid precast concrete panel. The analysis of embedding-effect-only modeling predicted that the deformation increases continually without the decrease in the load carrying capacity. However, the analysis results of proposed model showed good agreement with some experimental results, thus verifying the proposed computational model.

• Advances in Computational Design
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• v.7 no.3
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• pp.173-188
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• 2022

In modern buildings, glass is considered a structurally unsafe material due to its brittleness and unpredictable failure behavior. The possible use of structural glass elements (i.e., floors, beams and columns) is generally prevented by its poor tensile strength and a frequent occurrence of brittle failures. In this study an innovative modelling based on an equivalent thickness concept of laminated glass beam reinforced with FRP (Fiber Reinforced Polymer) composite material and of glass plates punched is presented. In particular, the novel numerical modelling applied to an embedding Carbon FRP-rod in the interlayer of a laminated structural glass beam is considered in order to increase both its failure strength, together with its post-failure strength and ductility. The proposed equivalent modelling of different specimens enables us to carefully evaluate the effects of this reinforcement. Both the responses of the reinforced beam and un-reinforced one are evaluated, and the corresponding results are compared and discussed. A novel equivalent modelling for reinforced glass beams using FRP composites is presented for FEM analyses in modern material components and proved estimations of the expected performance are provided. Moreover, the new suggested numerical analysis is also applied to laminated glass plates with wide holes at both ends for the technological reasons necessary to connect a glass beam to a structure. Obtained results are compared with an integer specimen. Experimental considerations are reported.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.10-13
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• 2009

본 논문에서는 모드해석 기법이 내장된 가속도기반 무선센서노드을 개발하였다. 이를 위해 다음과 같은 연구가 수행되었다. 첫째, 가속도 데이터를 취득하고 분석할 수 있는 가속도기반 무선센서노드를 설계하였다. 둘째, 무선센서노드를 이용한 구조건전성모니터링에 적합한 모드해석 기법으로 주파수영역분해법을 선정하였다. 셋째, 무선센서노드에서 모드해석을 독자적으로 수행하기 위한 분산 무선센서 네트워크기반 모드해석 알고리즘을 설계하고 무선센서노드에 내장하였다. 마지막으로, 개발된 무선센서노드를 PSC 거더모형에 설치하고 기존 구조건전성모니터링 시스템과의 성능비교를 통해 검증하였다.