• Journal of Korea Water Resources Association
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• v.47 no.10
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• pp.945-958
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• 2014

Soil temperature is one of the most important environmental factors that govern hydrological and biogeochemical processes related to diffuse pollution. In this study, considering the snowmelting and the soil freezing-thawing processes, a set of computer codes to estimate winter soil temperature has been developed for CAMEL (Chemicals, Agricultural Management and Erosion Losses), a distributed watershed model. The model was calibrated and validated against the field measurements for three months at 4 sites across the study catchment in a rural area of Yeoju, Korea. The degree of agreement between the simulated and the observed soil temperature is good for the soil surface ($R^2$ 0.71~0.95, RMSE $0.89{\sim}1.49^{\circ}C$). As for the subsurface soils, however, the simulation results are not as good as for the soil surface ($R^2$ 0.51~0.97, RMSE $0.51{\sim}5.08^{\circ}C$) which is considered resulting from vertically-homogeneous soil textures assumed in the model. The model well simulates the blanket effect of snowpack and the latent heat flux in the soil freezing-thawing processes. Although there is some discrepancy between the simulated and the observed soil temperature due to limitations of the model structure and the lack of data, the model reasonably well simulates the temporal and spatial distributions of the soil temperature and the snow water equivalent in accordance with the land uses and the topography of the study catchment.

• Journal of the Korea Concrete Institute
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• v.26 no.3
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• pp.315-321
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• 2014

Concrete as a construction material is widely used in nuclear vessel and plant for excellent radiation shielding. However the isolation characteristics in concrete may affect adversely in the case of fire and melt-down in nuclear vessel since temperature cooling down is very difficult from outside. This study is for development of high thermal conductive concrete, and its mechanical and thermal properties are evaluated. Magnetite aggregates with volume ratio of 42.3% (maximum) and steel powder of 1.5% are replaced with normal aggregates and thermal properties are evaluated. Thermal conductivity little increases by 30% addition of magnetite but rapidly increases afterwards. Finally thermal conductivity is magnified to 2.5 times in the case of 42.3% addition of magnetite. Steel powder has a positive effect on high thermal conduction to 106~113%. Several models for thermal conduction like ACI, DEMM, and MEM are compared with test results and they are verified to reasonably predict the thermal conductivity with increasing addition of magnetite aggregates and steel powder.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.57-65
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• 2021

We propose a novel method to detect abnormal data of specific symptoms using deep learning in air pollution measurement system. Existing methods generally detect abnomal data by classifying data showing unusual patterns different from the existing time series data. However, these approaches have limitations in detecting specific symptoms. In this paper, we use DeepLab V3+ model mainly used for foreground segmentation of images, whose structure has been changed to handle one-dimensional data. Instead of images, the model receives time-series data from multiple sensors and can detect data showing specific symptoms. In addition, we improve model's performance by reducing the complexity of noisy form time series data by using 'piecewise aggregation approximation'. Through the experimental results, it can be confirmed that anomaly data detection can be performed successfully.

• Composites Research
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• v.27 no.2
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• pp.66-71
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• 2014

This study carried out finite element vibration analysis of pole structures made of GFRP, which is based on the micro-mechanical approach for different fiber-volume fractions. The finite element (FE) models for composite structures using multi-scale approaches described in this paper is attractive not only because it shows excellent accuracy in analysis but also it shows the effect of the material combination. The FE model is used for studying free vibrations of laminated composite poles for various fiber-volume fractions. In particular, new results reported in this paper are focused on the significant effects of the fiber-volume fraction for various parameters, such as fiber angles, layup sequences, and length-thickness ratios. It may be concluded from this study that the combination effect of fiber and matrix, largely governing the dynamic characteristics of composite structures, should not be neglected and thus the optimal combination could be used to design such civil structures for better dynamic performance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.3
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• pp.223-233
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• 2011

A ceramic monolithic catalyst is a honeycomb structure that consists of two layers. The honeycomb structure is regarded as a continuum in structure and heat-flow analysis. The equivalent mechanical properties of the honeycomb structure were determined by performing finite element analysis (FEA) for a test specimen. Bending strength experiments and FEA of the test specimen used in ASTM C1674-08 standard test were performed individually. The bonding coefficient between the cordierite ceramic layer and the washcoat layer was almost zero. The FEA test specimen was modeled on the basis of the bonding coefficient. The elastic modulus, Poisson's ratio, and the thermal properties of the ceramic monolithic substrate were determined by performing the FEA of the test specimen.

• Journal of the Earthquake Engineering Society of Korea
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• v.3 no.4
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• pp.71-82
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• 1999

An axisymmetric shell element which includes the effects of the meridional and circumferential cable prestresses is developed. The fluid-structure interaction is expressed as added mass effect which is in proportion to the acceleration of the structure in interface surface. The added mass is obtained by using finite element method under the assumption that the fluid is invicid, incompressible and irrotational. It is coded for personal computer by the maximum use of axisymmetic properties and the dynamic analysis are performed under seismic exitations. A ring element makes the characteristics of the axisymmetric shell to be fully utilized. The elgenvalue solutons under the initial prestresses and the internal fluid are well agreed with the exact solutions and references by using under 20 elements. The eigenvalues are decreased along the increasing the height of internal fluid and these effects are dominant under the lower wave numbers. The results of the seismic analysis show that the radial deflection under the meridional prestress is a little larger than that under the circumferential prestress.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.87.3-88
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• 2017

한국천문연구원은 차세대소형위성 1호의 근적외선 영상분광기 NISS (Near-infrared Imaging Spectrometer for Star formation history) 탑재체를 개발하여 2017년 6월 30일에 최종 비행모델을 납품하였고, 이 발표는 탑재체 NISS 구조체의 비행모델 개발 결과를 보고한다. NISS는 0.9 - 2.5um (R~20) 근적외선 파장에서 관측을 해야 하기 때문에, 구조체의 배경잡음을 없애기 위해서 200K까지 passive cooling으로 냉각되며, H2RG 검출기는 소형 냉동기에 의해 약 88K에서 운영된다. NISS 구조체의 passive cooling을 효율적으로 수행하기 위해서 방열판, Kevlar 지지대, MLI, 표면제어용 필름 등을 조립하였고, 실제 지상 시험을 통해서 그 성능을 확인하였다. NISS 구조체는 최종 시스템 조립 과정에서 전자부 하네스 조립을 함께 수행했으며, 온도 모니터링 센서를 부착하고 소형 냉동기 피드백 온도를 반복 시험을 통해서 결정하였다. NISS 구조체는 미러 및 렌즈를 지지하는 광기계부를 함께 포함하기 때문에 발사 및 우주환경에서 광학 성능을 유지하기 위한 설계를 거쳐서 제작 되었으며, 최종 시스템 검교정 시험, 진동 및 열진공 시험을 통해서 그 성능을 확인하였다. NISS를 탑재한 차세대소형위성 1호는 2018년 상반기에 미국의 Falcon 9 발사체에 실려서 발사될 예정이다.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.4
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• pp.55-61
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• 2024

Recently, the number of aging concrete structures is steadily increasing. This is because many of these structures are reaching their expected lifespan. Such structures require accurate inspections and persistent maintenance. Otherwise, their original functions and performance may degrade, potentially leading to safety accidents. Therefore, research on objective inspection technologies using deep learning and computer vision is actively being conducted. High-resolution images can accurately observe not only micro cracks but also spalling and exposed rebar, and deep learning enables automated detection. High detection performance in deep learning is only guaranteed with diverse and numerous training datasets. However, surface damage to concrete is not commonly captured in images, resulting in a lack of training data. To overcome this limitation, this study proposed a method for generating concrete surface damage images, including cracks, spalling, and exposed rebar, using stable diffusion. This method synthesizes new damage images by paired text and image data. For this purpose, a training dataset of 678 images was secured, and fine-tuning was performed through low-rank adaptation. The quality of the generated images was compared according to three base models of stable diffusion. As a result, a method to synthesize the most diverse and high-quality concrete damage images was developed. This research is expected to address the issue of data scarcity and contribute to improving the accuracy of deep learning-based damage detection algorithms in the future.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.5
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• pp.112-120
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• 2012

A numerical model considering the internal vaporization and the creep effect, in the form of a analytical program, for tracing the behavior of high strength concrete(HSC) members exposed to fire is presented. The two stages, i.e., spalling procedure and fire resistance time, associated with the thermal, moisture flow, creep and structural analysis, for the prediction of fire resistance behavior are explained. The use of the analytical program for tracing the response of HSC member from the initial pre-loading stage to collapse, due to fire, is demonstrated. Moisture evaporates, when concrete is exposed to fire, not only at concrete surface but also at inside the concrete to adjust the equilibrium and transfer properties of moisture. Finite element method is employed to facilitate the moisture diffusion analysis for any position of member, so that the prediction method of the moisture distribution inside the concrete members at fire is developed. The validity of the numerical model used in this program is established by comparing the predictions from this program with results from others fire resistance tests. The analytical program can be used to predict the fire resistance of HSC members for any value of the significant parameters, such as load, sectional dimensions, member length, and concrete strength.

• Journal of Bio-Environment Control
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• v.28 no.3
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• pp.225-233
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• 2019

In the summer season, natural ventilation is commonly used to reduce the inside air temperature of greenhouse when it rises above the optimal level. The greenhouse shape, vent design, and position play a critical role in the effectiveness of natural ventilation. In this study, computational fluid dynamics (CFD) was employed to investigate the effect of different roof vent designs along with side vents on the buoyancy-driven natural ventilation. The boussinesq hypothesis was used to simulate the buoyancy effect to the whole computational domain. RNG K-epsilon turbulence model was utilized, and a discrete originates (DO) radiation model was used with solar ray tracing to simulate the effect of solar radiation. The CFD model was validated using the experimentally obtained greenhouse internal temperature, and the experimental and computed results agreed well. Furthermore, this model was adopted to compare the internal greenhouse air temperature and ventilation rate for seven different roof vent designs. The results revealed that the inside-to-outside air temperature differences of the greenhouse varied from 3.2 to $9.6^{\circ}C$ depending on the different studied roof vent types. Moreover, the ventilation rate was within the range from 0.33 to $0.49min^{-1}$. Our findings show that the conical type roof ventilation has minimum inside-to-outside air temperature difference of $3.2^{\circ}C$ and a maximum ventilation rate of $0.49min^{-1}$.