• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.301-309
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• 2021

In this study, we tried to improve the performance of the existing U-net-based deep learning rainfall prediction model, which can weaken the meaning of time series order. For this, ConvLSTM2D U-Net structure model considering temporal consistency of data was applied, and we evaluated accuracy of the ConvLSTM2D U-Net model using a RainNet model and an extrapolation-based advection model. In addition, we tried to improve the uncertainty in the model training process by performing learning not only with a single model but also with 10 ensemble models. The trained neural network rainfall prediction model was optimized to generate 10-minute advance prediction data using four consecutive data of the past 30 minutes from the present. The results of deep learning rainfall prediction models are difficult to identify schematically distinct differences, but with ConvLSTM2D U-Net, the magnitude of the prediction error is the smallest and the location of rainfall is relatively accurate. In particular, the ensemble ConvLSTM2D U-Net showed high CSI, low MAE, and a narrow error range, and predicted rainfall more accurately and stable prediction performance than other models. However, the prediction performance for a specific point was very low compared to the prediction performance for the entire area, and the deep learning rainfall prediction model also had limitations. Through this study, it was confirmed that the ConvLSTM2D U-Net neural network structure to account for the change of time could increase the prediction accuracy, but there is still a limitation of the convolution deep neural network model due to spatial smoothing in the strong rainfall region or detailed rainfall prediction.

• Journal of the Korean Applied Science and Technology
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• v.38 no.5
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• pp.1292-1301
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• 2021

The purpose of this study was to investigate the anti-pruritic activities such as cell viability and pruritus-related factor using seomaeyakssuk (Artemisia argyi H.; Seomaeyakssuk) extract on MC/9 (mouse mast cell line). Seomaeyakssuk was extracted from hot distilled water. Cell viability was assessed using MTT assay on MC/9 cells. Anti-pruritic activities were measured through changes in the levels of transcription factor (IL4 and IL31) on MC/9 cells. In addition, the expression of linked proteins and histamine was measured. The results confirmed that significant cytotoxicity does not appear in the concentration range of 25, 50, and 100 ㎍/㎖. The levels of IL4 was reduced to 12% (25 ㎍/㎖), 26% (50 ㎍/㎖) and 61% (100 ㎍/㎖). Also, level of IL31 was decreased 33% (50 ㎍/㎖) and 36% (100 ㎍/㎖). In the case of proteins levels decreased significantly IL-4 34%/69% and IL-31 36%/37% at 50 ㎍/㎖ and 100 ㎍/㎖. Histamine decreased by 22, 58% and 61%, respectively, at concentrations of 25, 50, and 100 ㎍/㎖. This results shows possibility of ADD as raw material in anti-pruritic products.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.558-564
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• 2021

The water purifier market has increased rapidly in recent years. The welding technology of the evaporator is a key component that determines the level of ice production and the cold water performance of an ice purifier. The finger type evaporator of an ice purifier can remove ice and is divided largely into an instant heat method and a hot gas method. In the hot gas type evaporator, particularly during the production process, the pinhole phenomenon inside the copper pipe and clogging problems occur intermittently when welding high-pressure pipes due to the high-temperature oxygen welding. Its use in a water purifier can cause a problem in that ice and cold water do not form, and repairs cannot be made on site. To solve this problem, in this study, a cap jig was applied to improve the welding defect of the hot gas evaporator. In addition, the oxygen welding flame size was adjusted so that the heat source could be well supplied to the cap jig, and the effectiveness was confirmed through a wave pressure test, a test, and a thermal shock test.

• Journal of Life Science
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• v.31 no.3
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• pp.338-345
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• 2021

Zizania latifolia has long been used as a tea for both edible and medicinal purposes. However, research into the use of Z. latifolia as a high value-added edible material is lacking. In a previous study, we confirmed that tricin is the major component in Z. latifolia. In this study, we investigated the protective effect of a Z. latifolia extract (ZLE). Toxicity tests of ZLE or tricin on HepG2 cells revealed no toxicity due to ZLE or tricin at all concentrations used. The reduction in cell viability by tert-butyl hydroperoxide (t-BHP) was suppressed by treatment with ZLE or tricin. In addition, ZLE or tricin effectively inhibited the production of reactive oxygen species (generation of hydrogen peroxide, alkoxy free radicals, and peroxyl free radicals by t-BHP) and oxidative damage. ZLE or tricin treatments also increased the protein expression of superoxide dismutase 1 (SOD1), catalase, heme oxygenase-1 (HO-1), and nuclear factor erythroid-related factor 2 (Nrf2), which are known as antioxidant enzymes, suggesting that the protective effect of ZLE is related to activation of tricin. Taken together, the results indicate that Z. latifolia can be developed as a functional food material for improving liver function.

• Tunnel and Underground Space
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• v.30 no.6
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• pp.573-590
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• 2020

This study presents the current status of DECOVALEX-2023 project Task G and our research results so far. Task G, named 'Safety ImplicAtions of Fluid Flow, Shear, Thermal and Reaction Processes within Crystalline Rock Fracture NETworks (SAFENET)' aims at developing a numerical method to simulate the fracture creation and propagation, and the coupled thermohydro-mechanical processes in fracture in crystalline rocks. The first research step of Task G is a benchmark simulation, which is designed for research teams to make their modelling codes more robust and verify whether the models can represent an analytical solution for displacements of a single rock fracture. We reproduced the mechanical behavior of rock and embedded single fracture using a three-dimensional grain-based distinct element model for the simulations. In this method, the structure of the rock was represented by an assembly of rigid tetrahedral grains moving independently of each other, and the mechanical interactions at the grains and their contacts were calculated using 3DEC. The simulation results revealed that the stresses induced along the embedded fracture in the model were relatively low compared to those calculated by stress analysis due to stress redistribution and constrained fracture displacements. The fracture normal and shear displacements of the numerical model showed good agreement with the analytical solutions. The numerical model will be enhanced by continuing collaboration and interaction with other research teams of DECOVALEX-2023 Task G and validated using various experiments in a further study.

• Journal of Korea Foundry Society
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• v.41 no.3
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• pp.235-240
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• 2021

We present the effect of the critical cooling rate during rapid solidification on the nucleation of precipitates in an Fe₇₅B₁₃P₅Nb₂Hf₁C₄ (at.%) alloy. The thermophysical properties of the rapidly solidified Fe₇₅B₁₃P₅Nb₂Hf₁C₄ liquids, which were obtained at various cooling rates with various sizes of gas-atomized powder during a high-pressure inert gas-atomization process, were evaluated. The cooling rate of the small-particle powder (≤20 ㎛) was 8.4×10⁵ K/s, which was 13.5 times faster than that of the large-particle powder (20 to 45 mm; 6.2×10⁴ K/s) under an atomized temperature. A thermodynamic calculation model used to predict the nucleation of the precipitates was confirmed by the microstructural observation of MC-type carbide in the Fe₇₅B₁₃P₅Nb₂Hf₁C₄ alloy. The primary carbide phase was only formed in the large-particle gas-atomized powder obtained during solidification at a slow cooling rate compared to that of the small-particle powder.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.3
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• pp.159-165
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• 2021

This study introduces a topology optimization method for the simultaneous design of macro-scale structural configuration and unit structure variation to ensure effective heat conduction. Shape changes in the unit structure depending on its location within the macro-scale structure result in micro- as well as macro-scale design and enable better performance than using isotropic unit structures. They result in functionally graded composite structures combining both configurations. The representative volume element (RVE) method is applied to obtain various thermal conductivity properties of the multi-material based unit structure according to its shape change. Based on the RVE analysis results, the material properties of the unit structure having a certain shape can be derived using machine learning. Macro-scale topology optimization is performed using the traditional solid isotropic material with penalization method, while the unit structures composing the macro-structure can have various shapes to improve the heat conduction performance according to the simultaneous optimization process. Numerical examples of the thermal compliance minimization issue are provided to verify the effectiveness of the proposed method.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1407-1419
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• 2020

Long time-series gridded data is crucial for the analyses of Earth environmental changes. Climate reanalysis and satellite images are now used as global-scale periodical and quantitative information for the atmosphere and land surface. This paper examines the feasibility of DCT-PLS (penalized least square regression based on discrete cosine transform) for the spatial gap filling of gridded data through the experiments for multiple variables. Because gap-free data is required for an objective comparison of original with gap-filled data, we used LDAPS (Local Data Assimilation and Prediction System) daily data and MODIS (Moderate Resolution Imaging Spectroradiometer) monthly products. In the experiments for relative humidity, wind speed, LST (land surface temperature), and NDVI (normalized difference vegetation index), we made sure that randomly generated gaps were retrieved very similar to the original data. The correlation coefficients were over 0.95 for the four variables. Because the DCT-PLS method does not require ancillary data and can refer to both spatial and temporal information with a fast computation, it can be applied to operative systems for satellite data processing.

• Tunnel and Underground Space
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• v.31 no.4
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• pp.270-288
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• 2021

We proposed a numerical method to simulate the hydro-mechanical behavior of rock fracture using a grain-based distinct element model (GBDEM) in the paper. As a part of DECOVALEX-2023 Task G, we verified the method via benchmarks with analytical solutions. DECOVALEX-2023 Task G aims to develop a numerical method to estimate the coupled thermo-hydro-mechanical processes within the crystalline rock fracture network. We represented the rock sample as a group of tetrahedral grains and calculated the interaction of the grains and their interfaces using 3DEC. The micro-parameters of the grains and interfaces were determined by a new methodology based on an equivalent continuum approach. In benchmark modeling, a single fracture embedded in the rock was examined for the effects of fracture inclination and roughness, the boundary stress condition and the applied pressure. The simulation results showed that the developed numerical model reasonably reproduced the fracture slip induced by boundary stress condition, the fracture opening induced by fluid injection, the stress distribution variation with fracture inclination, and the fracture roughness effect. In addition, the fracture displacements associated with the opening and slip showed good agreement with the analytical solutions. We expect the numerical model to be enhanced by continuing collaboration and interaction with other research teams of DECOVALEX-2023 Task G and validated in further study experiments.

• Journal of Korea Water Resources Association
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• v.55 no.3
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• pp.205-215
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• 2022

Amidst the global climate crisis, dam operation policies formulated under the stationary climate assumption could lead to unsatisfactory water management. In this work, we assessed status-quo performance of the Yongdam Dam in Korea under various climatic stresses in flood risk reduction and water supply reliability for 2021-2040. To this end, we employed a decision-centric framework equipped with a stochastic weather generator, a conceptual streamflow model, and a machine-learning reservoir operation rule. By imposing 294 climate perturbations to dam release simulations, we found that the current operation rule of the Yongdam dam could redundantly secure water storage, while inefficiently enhancing the supply reliability. On the other hand, flood risks were likely to increase substantially due to rising mean and variability of daily precipitation. Here, we argue that the current operation rules of the Yongdam Dam seem to be overly focused on securing water storage, and thus need to be adjusted to efficiently improve supply reliability and reduce flood risks in downstream areas.