• Composites Research
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• v.24 no.6
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• pp.25-30
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• 2011

This paper presents an experimental study on the enhancement of electromagnetic shielding (EMI) properties of glass fiber, carbon fiber, and glass-carbon fiber composites by adding layers of multi-walled carbon nanotubes (MWCNTs). In the case of glass-fiber composites, spraying 0.1~0.2 g of MWCNT over a fiber area of $200mm{\times}200mm$ (1.8~3.6 ${\mu}m$ in thickness) resulted in significant improvement in EMI shielding effectiveness (SE). Also, when applying multiple MWCNT layers, it was more effective to place the layers concentrated near the center of the composite rather than spreading them out. On the contrary, inherently conductive carbon fiber and glass-carbon fiber composites did not show appreciable improvement with the addition of MWCNT layers. In order to maximize the effectiveness of carbon nanomaterials as EMI shielding fillers, it is imperative to understand the effect of these materials on various EMI shielding mechanisms and their interactions.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.542-545
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• 2010

재료의 마이크로 스케일 해석에서 결정의 geometrically necessary dislocation (GND) 효과에 의한 소성구배(plastic gradient)를 고려하는 것은 재료의 소성 거동을 분석하는데 영향을 미친다. 본 연구에서는 먼거리(long range)에서 전위(dislocation)의 영향을 고려하는 GND의 효과를 적용하여 소성 구배의 영향을 받는 다결정(polycrystal) 고체의 거동을 유한요소해석을 이용하여 살펴보았다. 재료의 거동을 분석하기 위해 탄성(elastic)과 소성(plastic) 변형에 먼 거리 변형률(long range strain)을 고려한 항(term)이 포함된 변형 구배(deformation gradient)의 multiplicative decomposition 모델을 사용하였다. 먼 거리 변형률에 의한 영향을 고려하기 위해 구배 경화 계수(gradient hardness coefficient)와 먼 거리 변형률 길이에 대한 재료변수(parameter)가 사용되었다. 각각의 계수들이 다결정 고체의 거동에 미치는 영향을 확인하기 위해 두 변수의 적용에 따른 다결정 고체의 거동을 분석하였다. 다결정 재료의 GND 효과에 의한 소성 구배 효과를 고려해서, 고려하지 않은 경우와 비교하여 발생하는 경화(hardening)의 차이를 분석함으로서 GND에 의한 다결정 고체 거동의 영향을 확인하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.663-666
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• 2021

본 논문에서는 바다와 같은 스케일이 큰 장면인 물 시뮬레이션에서 표현되는 거품 효과(Foam effects)를 노이즈 없이 디테일하게 표현할 수 있는 프레임워크를 소개한다. 거품이 생성될 위치와 거품 입자의 이류는 기존의 접근법인 스크린 투영 방법을 통해 계산한다. 이 과정에서 중요한 것이 투영맵이지만 이산화된 스크린 공간에 운동량을 투영하는 과정에서 노이즈가 발생한다. 본 논문에서는 노이즈 제거 신경망(Denoising neural network)을 활용하여 이 문제를 효율적으로 풀어낸다. 투영맵을 통해 거품이 생성될 영역이 선별되면 2D공간을 3D공간으로 역변환(Inverse transformation)하여 거품 입자를 생성한다. 결과적으로 깔끔한 거품 효과뿐만 아니라, 노이즈 제거 과정으로 인해 소실되는 거품 없이 안정적으로 거품 효과를 만들어냈다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6C
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• pp.267-274
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• 2012

The conventional approach to evaluate the contaminant transport in soils adopts the macro-scale implementation while the pore configuration and network is a dominant factor to determine the fate of contaminant. However, the observation of fate and transport at pore scale may not be readily approachable because of the computational expenses to solve Navier-Stokes equation. We herein present the 2D Lattice-Boltzmann method that enables to assess the local fluid velocity and density efficiently for the case of single phase and multi-components. The solute fate spatio-temperal space is explicitly determined by the advection of fluid flow. Two different types of idealized pore space provides the path of fluid. Also, solute transport, the velocity field and average concentration of solute are computed in steady state. Results show that the pore geometry such as tortuosity mainly affect the solute fate. It highlights the significance of the pore configuration and shape in granular soils and rock discontinuity in spite of the equivalent porosity.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.149-153
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• 2006

Precipitation is the most important component and critical to the study of water and energy cycle. This study investigates the propagation of precipitation retrieval uncertainty in the simulation of hydrologic variables for varying spatial resolution on two different vegetation cover. We explore two remotely sensed rain retrievals (space-borne IR-only and radar rainfall) and three spatial grid resolutions. An offline Community Land Model (CLM) was forced with in situ meteorological data In turn, radar rainfall is replaced by the satellite rain estimates at coarser resolution $(0.25^{\circ},\;0.5^{\circ}\;and\;1^{\circ})$ to determine their probable impact on model predictions. Results show how uncertainty of precipitation measurement affects the spatial variability of model output in various modelling scales. The study provides some intuition on the uncertainty of hydrologic prediction via interaction between the land surface and near atmosphere fluxes in the modelling approach.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.7
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• pp.768-774
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• 2010

Reconstruction of implicit surfaces from scattered point data sets have been developed in various engineering and scientific studies. In this paper, we represent a method to construct functions of 2D point data using multi-scale kernels and show it can be applied to graphics applications needed to access data in real-time. Our approach is similar to previous work in that a set of coefficients of the functions are calculated and stored in the preprocessing stage and function values at arbitrary positions are evaluated for real-time applications, however, it is different from others in that users can choose detail levels freely in real-time processing stage. The reason why the functions implicitly supports multi-resolution results from the mathematical properties of multi-scale kernels, and proposed method can be expanded to represent multi-resolution functions of n-dimensional data.

• Phonetics and Speech Sciences
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• v.11 no.4
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• pp.89-96
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• 2019

In this paper, we propose a deep learning architecture that can effectively detect speech segmentation in broadcast contents. We also propose a multi-scale time-dilated layer for learning the temporal changes of feature vectors. We implement several comparison models to verify the performance of proposed model and calculated the frame-by-frame F-score, precision, and recall. Both the proposed model and the comparison model are trained with the same training data, and we train the model using 32 hours of Korean broadcast data which is composed of various genres (drama, news, documentary, and so on). Our proposed model shows the best performance with F-score 91.7% in Korean broadcast data. The British and Spanish broadcast data also show the highest performance with F-score 87.9% and 92.6%. As a result, our proposed model can contribute to the improvement of performance of speech detection by learning the temporal changes of the feature vectors.

• Composites Research
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• v.23 no.3
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• pp.7-12
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• 2010

In order to increase the electrical conductivity and the mechanical properties of carbon fabric composites, multi-walled carbon nanotubes (MWCNTs) and carbon nanofibers (CNFs) were deposited on carbon fabrics by anodic and cathodic electrophoretic deposition (EPD) processes. In the cathodic EPD, carbon nano-particles and nano-sized Cu particles were simultaneously deposited on the carbon fabric, which gave a synergetic effect on the enhancement of properties as well as the degree of deposition. The hybridization of carbon nano-particles and micron-sized carbon fiber significantly improved the through-the-thickness electrical conductivity. In addition, both MWCNTs and CNFs were deposited onto the carbon fabric for multi-scale hybrid composites. Multi-scale deposition improved the through-the-thickness electrical conductivity, compared to the deposition of either MWCNTs or CNFs.

• Journal of Hydrogen and New Energy
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• v.20 no.6
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• pp.455-463
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• 2009

코발트 보호막 코팅이 적용된 페라이트계 스테인리스 스틸인 STS 430과 STS 444 소재에 대해 고체산화물 연료전지용 금속연결재로서의 고온 산화 특성에 대해 살펴보았다. 코발트 코팅층은 $800^{\circ}C$ 고온 산화 후 코발트 산화물 및 $Co_2CrO_4$, $CoCr_2O_4$, $CoCrFeO_4$ 등과 같은 코발트가 함유된 스피넬 상을 형성하였다. 또한 페라이트계 스테인리스 스틸과 코발트 코팅의 계면에서 크롬과 철이 함유된 치밀한 산화층을 형성하여 금속연결재 표면의 스케일 성장속도를 감소시키고 금속연결재 내에 함유된 크롬의 외부 확산을 효과적으로 억제하였다. 한편 STS 430은 고온 산화 후 표면에 형성된 스케일 하부에 $SiO_2$와 같은 내부 산화물이 형성된 반면 STS 444는 표면 스케일 이외에 다른 내부 산화물은 확인되지 않았으며 고온에서의 면저항 측정 결과, 코발트가 코팅된 STS 444의 전기 전도성이 STS 430 보다 우수한 것으로 나타났다.

• Journal of the Korean Geographical Society
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• v.46 no.2
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• pp.197-211
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• 2011

Due to the complexity of spatial interaction and the necessity of spatial representation and modeling, aggregation of spatial interaction data is indispensible. Given this, the purpose of this paper is to evaluate the effects of modifiable areal unit problem (MAUP) on a spatial interaction model. Four aggregation schemes are utilized at eight different scales: 1) randomly select seeds of district and then allocate basic spatial units to them, 2) minimize the sum of population weighted distance within a district, 3) maximize the proportion of flow within a district, and 4) minimize the proportion of flow within a district. A simple Poisson regression model with origin and destination constraints is utilized. Analysis results demonstrate that spatial characteristics of residuals, parameter values, and goodness-of-fit of the model were influenced by aggregation scale and schemes. Overall, the model responded more sensitively to aggregation scale than aggregation schemes and the scale effect on the model was varied according to aggregation schemes.