• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.880-880
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• 2012

수위-유량자료는 수문모형의 적용 등과 같은 다양한 수자원분야에서 기초적인 관측자료로서 이용되고 있다. 하지만 겨울철 결빙에 따른 수위계의 오작동과 제한된 실측 수위자료에 따른 수위 자료의 보정과 획득에 어려움을 겪고 있다. 본 연구에서는 수자원 분야에서 다양하게 적용된 바 있는 인공신경망 기법과 누적결빙온도일 (AFDD; Accumulated Freezing Degree Days) 개념을 이용하여 오산천 유역의 탑동수위관측점의 결빙기 수위자료를 보정하였다. 연구결과 보정된 수위자료는 강우량과 방류량 등의 영향을 비교적 잘 반영하는 것으로 나타났으며 향후 지속적인 연구를 통해 인공신경망을 이용한 수위 보정 결과를 검정할 수 있어야 할 것이다.

• 한국도로학회:학술대회논문집
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• 2009.11a
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• pp.221-226
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• 2009

• 한국도로학회:학술대회논문집
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• 2010.03a
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• pp.255-260
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• 2010

• Proceedings of the Korea Concrete Institute Conference
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• 1997.10a
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• pp.755-760
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• 1997

The comprehensive performance of the water-proofing materials which are sealer, liquid and preformed membranes were investigated as basic experimental data for guide line of field workers. The water-proofing performance, shear strength and bond strength were tested under the ambient temperature of $20^{\cire}C$ and after 60 cycles of freezing and thawing ($-17.8^{\cire}C$~$4^{\cire}C$, 6cycle/day). The performance includes workability, permeability, cost and the influence of water-proofing materials to environment.

• Journal of the Korean Geosynthetics Society
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• v.12 no.3
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• pp.23-29
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• 2013

The mechanical behavior of frozen soils is different from that of unfrozen soils due to the phase change between water and ice. The strength characteristics of frozen soils are governed by the intrinsic material properties such as grain size, ice and water content, air bubbles, and by externally imposed testing conditions such as temperature, freezing time, and strain rate. Especially, the strength of the frozen soils is generally higher than that of unfrozen soils due to ice binding capacity with soil particles, and is strongly affected by a highly complex interaction between the solid soil skeleton and the pore matrix, composed of ice and unfrozen water. In this study, the direct shear test and unconfined compression test are carried out inside of a large-scaled freezing chamber, and the relationships between cohesion and unconfined compression strength under various freezing temperature conditions are discussed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.6
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• pp.143-151
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• 2007

This study presents the experimental results of frost durability including resistance to freezing-thawing and surface scaling of concrete. Mixing design was proportioned with the various water-binder ratio between 0.37 and 0.47 and three different binder compositions corresponding to Type I cement without any supplementary cementitious materials(OPC), Type II cement with 50% blast-furnace slag replacement(BFS50), and ternary cement with Type III cement, 15% fly ash, and 35% slag replacement (BFS35%+FA15%). Test results showed that the mixing design with BFS50% and BFS35%+FA15% exhibited higher durability factor than that made with OPC only. Finally, the use of blend cement containing slag can be used effectively in terms of frost durability of the concrete exposed to severe condition under coastal environment like as flying salt, sea water spray, etc.

• Korean Journal of Construction Engineering and Management
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• v.24 no.3
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• pp.42-51
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• 2023

Freeze and burst water meter in winter causes many social costs, such as meter replacement cost, inability of water use, and secondary damage by freezing water. The government is making efforts to modernize local waterworks, and in particular, is promoting SWM(Smart Water Management) project nationwide. In this study suggests a new freeze risk notification information service based on the temperature by IoT sensor inside the water meter box rather than outside temperature. In addition, in order to overcome the quantitative and regional limitation of IoT temperature sensors installed nationwide, and AI based temperature prediction model was developed that predicts the temperature inside water meter boxes based on data acquired from IoT temperature sensors and other information. Through the prediction model optimization process, a nationwide water meter freezing risk information service was convinced.

• Current Research on Agriculture and Life Sciences
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• v.6
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• pp.163-169
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• 1988

This study was conducted to predict the density changes according to concentration and temperature changes under freezing point. This information is needed for the design of freezing equipment and for the efficient utilization of refrigerating system. Orange juice, Apple juice, Grape juice and Sucrose solution were used for the measurement of density in this study at the temperature range from $-5^{\circ}C$ to $-40^{\circ}C$ and at the concentration range from 10 to 40%. The unfrozen water fraction of samples was determined by Heldman's method. The density values were determined by measuring the weight of a frozen solution at each temperature with a known volume. Solutions were placed in the thick-walled aluminum tubes. When the solution was frozen the excess ice was removed with a razor until the surface of the ice was flush with the top of the aluminum tube. The tube and ice were weighted immediately. Knowing the volume, tare weight, and final weight, the density could be determined. With this procedure, the data of density and unfrozen water fraction for fruit juices and sucrose solution were collected. The density prediction models of fruit juices and sucrose solution under freezing point were established by the optimization computer program with measured experimental data.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.443-452
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• 1993

Direct freezing tests of soybean seed by liquid nitrogen were carried out at various moisture contents and the following important conclusions were drawn from the results of temperature measurements of soybean seed and photographs of bubbles generated on its surface : 1) Assuming that the temperature gradient in a soybean seed is negligible because of its small seed size and the freezing ratio is followed the Heiss's formula, and a differential equation based on the heat energy balance was introduced . The equation was easily solved by the Runge-Kutta-Gill method and the predicted values of the temperature were in good agreement with the observed data. 2) The photographs of bubble generation during freezing showed the boiling mode was nucleate, and then the most suitable formula on the nucleate boiling heat transfer was introduced from many formulate proposed up to now by fitting the calculated values based on the formula to the observed data. The formula used for the predict on of the seed temperature was as follows: $\frac{{\partial}T_s}{\partial\theta}\;=\;-\frac{{\alpha}(T_s\;-\;T_L)^{3.3}}{W(C_s\;-\;\frac{{\delta}m(CT_s\;+\;{\sigma})}{T_s^2})}$ where C = difference of the specific heat between pure ice and water m=moisture content of soybean seed $T_s$ = seed temperature $T_L$ = Temperature of liquid nitrogen W = mass of soybean seed $\alpha$ = proportional constant $\delta$ = constant depends on variety or the type of seed $\theta$ = time $\sigma$ = latent heat of melting of pure ice This study will give important information in the hydro-freezing technique by liquid nitrogen, available as a new technique of processing agricultural products in the near future.

• 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.