• Journal of the Earthquake Engineering Society of Korea
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• v.16 no.1
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• pp.37-45
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• 2012

In an effort to further exploit the peak ground-motion acceleration (PGA) information per second available in real time by the enacted law, bracketed summations of the PGA per second ($BSPGA_k$) for 30 seconds based on the records with a rate of 100 samples were compared with the cumulative absolute velocity (CAV) and earthquake intensities based on a worldwide database of records from small-to-large earthquakes. The CAV, currently in use as an earthquake damage indicator for nuclear power plants due to its strong correlation with the earthquake intensity, has the disadvantage of requiring a massive amount of digital data with a rate of more than 100 samples per second. The comparative study shows that the $BSPGA_k$ is well correlated with the CAV over the wide range of strong ground-motion levels, which suggests that the $BSPGA_k$ is one of the new promising ground-motion parameters especially useful for rapid earthquake alert notifications through an earthquake monitoring network. Based on the domestic database of records from small-to-moderate earthquakes with felt reports, it is also observed that the $BSPGA_k$ is comparable to the CAV and better than the PGA in predicting the intensity by using the correlation relation.

• The Journal of Engineering Geology
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• v.26 no.2
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• pp.235-250
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• 2016

In Korea, 70% of the annual rainfall falls in summer, and the number of days of extreme rainfall (over 200 mm) is increasing over time. Because rainfall is the most important trigger of landslides, it is necessary to decide a rainfall threshold for landslide warning and to develop a landslide warning model. This study selected 12 study areas that contained landslides with exactly known triggering times and locations, and also rainfall data. The feasibility of applying a Rainfall Triggering Index (RTI) to Korea is analyzed, and three RTI models that consider different time units for rainfall intensity are compared. The analyses show that the 60-minute RTI model failed to predict landslides in three of the study areas, while both the 30- and 10-minute RTI models gave successful predictions for all of the study areas. Each RTI model showed different mean response times to landslide warning: 4.04 hours in the 60-minute RTI model, 6.08 hours in the 30-minute RTI model, and 9.15 hours in the 10-minute RTI model. Longer response times to landslides were possible using models that considered rainfall intensity for shorter periods of time. Considering the large variations in rainfall intensity that may occur within short periods in Korea, it is possible to increase the accuracy of prediction, and thereby improve the early warning of landslides, using a RTI model that considers rainfall intensity for periods of less than 1 hour.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.1
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• pp.35-42
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• 2008

In the nuclear power plant, early detection of fatigue crack by non-destructive test (NDT) equipment due to the thermal cyclic load is very important in terms of strict safety regulation. To this end, many efforts are exerted to the fabrication of artificial cracked specimen for practicing engineers in the NDT company. The crack of this kind, however, cannot be made by conventional machining, but should be made under thermal cyclic load that is close to the in-situ condition, which takes tremendous time due to the repetition. In this study, thermal loading condition is investigated to minimize the time for fabricating the cracked specimen using simulation technique which predicts the crack initiation and propagation behavior. Simulation and experiment are conducted under an initial assumed condition for validation purpose. A number of simulations are conducted next under a variety of heating and cooling conditions, from which the best solution to achieve minimum time for crack with wanted size is found. In the simulation, general purpose software ANSYS is used for the stress analysis, MATLAB is used to compute crack initiation life, and ZENCRACK, which is special purpose software for crack growth prediction, is used to compute crack propagation life. As a result of the study, the time for the crack to reach the size of 1mm is predicted from the 418 hours at the initial condition to the 319 hours at the optimum condition, which is about 24% reduction.

• Journal of Navigation and Port Research
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• v.39 no.4
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• pp.345-351
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• 2015

This study investigated the optimum depth for the application of bioremediation in contaminated coastal sediment using a lab scale column experiment. The biostimulants were placed in the top surface of the sediment facing seawater, 3cm, 6cm and 10cm of the depth from the surface, respectibely. During the experiment, the changes of organic pollutants and heavy metal fractions in the sediment were monitored in 1 month and 3month time intervals. The organic pollutants found during various analysis such as chemical oxygen demand, total solids and volatile solids, significantly reduced when the depth of the biostimulant was 3cm or less. In contrast, at a depth of over 6cm, the reduction of organic pollutants decreased, and the results were similar to the control. Heavy metals fractions in the sediment also changed with the depth of the biostimulants. The exchangeable fraction of the metals was quite reduced at the sediment surface in the column, but the organic bound and residual fractions considerably increased at a depth of 3cm. Based on this study, the optimum biostimulants depth for in-situ bioremediation of contaminant coastal sediment is 3cm from the sediment surface.

• Journal of the Korean Institute of Gas
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• v.7 no.4 s.21
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• pp.44-52
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• 2003

In this work dynamic heat transfer in a CPFS (cable penetration fire stop) system built in the firewall of nuclear power plants is three-dimensionally investigated to develop a test-simulator that can be used to verify effectiveness of the sealant. Dynamic heat transfer in the fire stop system is formulated in a parabolic PDE (partial differential equation) subjected to a set of initial and boundary conditions. First, the PDE model is divided into two parts; one corresponding to heat transfer in the axial direction and the other corresponding to heat transfer on the vertical planes. The first PDE is converted to a series of ODEs (ordinary differential equations) at finite discrete axial points for applying the numerical method of SOR (successive over-relaxation) to the problem. The ODEs are solved by using an ODE solver In such manner, the axial heat flux can be calculated at least at the finite discrete points. After that, all the planes are separated into finite elements, where the time and spatial functions are assumed to be of orthogonal collocation state at each element. The initial condition of each finite element can be obtained from the above solution. The heat fluxes on the vertical planes are calculated by the Galerkin FEM (finite element method). The CPFS system was modeled, simulated, and analyzed here. The simulation results were illustrated in three-dimensional graphics. Through simulation, it was shown clearly that the temperature distribution was influenced very much by the number, position, and temperature of the cable stream, and that dynamic heat transfer through the cable stream was one of the most dominant factors, and that the feature of heat conduction could be understood as an unsteady-state process.

• 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.

• Korean Chemical Engineering Research
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• v.61 no.2
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• pp.175-188
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• 2023

Global interest in hydrogen energy is increasing as an eco-friendly future energy that can replace fossil fuels. Accordingly, a next-generation hydrogen production technology using microorganisms, nuclear power, etc. is being developed, while a lot of time and effort are still required to overcome the cost of hydrogen production based on fossil fuels. As a way to minimize greenhouse gas emissions in the hydrocarbon-based hydrogen production process, methane direct decomposition technology has recently attracted attention. In order to improve the economic feasibility of the process, the simultaneous production of value-added carbon materials with hydrogen can be one of the most essential aspects. For that purpose, various studies on catalysis related to the quality and yield of high-value carbon materials such as carbon nanotubes (CNTs). In terms of process technology, a number of the research and development of fluidized-bed reactors capable of continuous production and improved gas-solid contact efficiency has been attempted. Recently, methane direct decomposition technology using a fluidized bed has been developed to the extent that it can produce 270 kg/day of hydrogen and 1000 kg/day of carbon. Plus, with the development of catalyst regeneration, separation and recirculation technologies, the process efficiency can be further improved. This review paper investigates the recent development of catalysts and fluidized bed reactor for methane direct pyrolysis to identify the key challenges and opportunities.

• Tunnel and Underground Space
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• v.34 no.1
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• pp.28-53
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• 2024

In general, high-level radioactive waste (HLW) generated as a result of nuclear power generation should be disposed within the country. Determination of the disposal site and host rock for HLW deep geological repository is an important issue not only scientifically but also politically, economically, and socially. Considered host rock types worldwide for geological disposal include crystalline rocks, sedimentary rocks, volcanic rocks, and salt dome. However, South Korea consists of various rock types except salt dome. This paper not only analyzed the geological and rock mechanical characteristics on a nationwide scale with the preliminary results on various rock type studies for the disposal host rock, but also reviewed the characteristics and possibility of various rock types as a host rock through deep drilling surveys. Based on the nationwide screening for host rock types resulted from literature review, rock distributions, and detailed case studies, Jurassic granites and Cretaceous sedimentary rocks (Jinju and Jindong formations) were derived as a possible candidate host rock types for the geological disposal. However, since the analyzed data for candidate rock types from this study is not enough, it is suggested that the disposal rock type should be carefully determined from additional and detailed analysis on disposal depth, regional characteristics, multidisciplinary investigations, etc.

• Journal of Korea Water Resources Association
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• v.57 no.10
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• pp.657-671
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• 2024

The objectives of this study propose a parameter estimation method that can consider both the total runoff and the runoff component by integrating the digital filter method and the long-term runoff models (SWAT, TANK), and evaluate the appropriateness of the applied methods. The study area is the Soyang River Dam basin, and parameter calibration and validation are performed by dividing it into a parameter estimation method considering the total runoff and a parameter estimation method considering the runoff component. In both methods, the fit between the observation and simulation runoff was excellent, and the model performance was found to be good with a coefficient of determination (R²) of 0.73~0.87, and NSE of 0.67~0.85. As a result of comparison with each method, it was confirmed that the simulation accuracy was improved when applying the method considering the runoff component in both the SWAT model and the TANK model. When comparing between the models, the SWAT model showed better statistics in both methods, but the effect of applying to the method was found to be insignificant. However, even though the TANK model did not specifically consider the physical characteristics of the methodology, the statistical value of NSE increased by 17% when integrating a method such as a digital filter. In other words, the applicability to the digital filter method was found to be better in the TANK model, and when a hydrograph separation method such as a digital filter is applied to a conceptual model such as this model, it is judged that more improved simulation results can be obtained than the physical model. Accordingly, it is judged that estimating the parameters by considering the runoff component will be more accurate than estimating the parameters by considering only the total runoff when simulating the hydrological model.

• Korean Journal of Environmental Biology
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• v.34 no.4
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• pp.304-313
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• 2016

One of the issues currently facing nuclear power plants is how to store spent nuclear waste materials which are contaminated with radionuclides such as $^{134}Cs$, $^{135}Cs$, and $^{137}Cs$. Bioremediation processes may offer a potent method of cleaning up radioactive cesium. However, there have only been limited reports on $Cs^+$ tolerant bacteria. In this study, we report the isolation and identification of $Cs^+$ tolerant bacteria in environmental soil and sediment. The resistant $Cs^+$ isolates were screened from enrichment cultures in R2A medium supplemented with 100 mM CsCl for 72 h, followed by microbial community analysis based on sequencing analysis from 16S rRNA gene clone libraries(NCBI's BlastN). The dominant Bacillus anthracis Roh-1 and B. cereus Roh-2 were successfully isolated from the cesium enrichment culture. Importantly, B. cereus Roh-2 is resistant to 30% more $Cs^+$ than is B. anthracis Roh-1 when treated with 50 mM CsCl. Growth experiments clearly demonstrated that the isolate had a higher tolerance to $Cs^+$. In addition, we investigated the adsorption of $0.2mg\;L^{-1}$ $Cs^+$ using B. anthracis Roh-1. The maximum $Cs^+$ biosorption capacity of B. anthracis Roh-1 was $2.01mg\;g^{-1}$ at pH 10. Thus, we show that $Cs^+$ tolerant bacterial isolates could be used for bioremediation of contaminated environments.