• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.260-260
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• 2017

This study aims to compare the performance of TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope-stability model) and TiVaSS (Time-variant Slope Stability model) in the prediction of rainfall-induced shallow landslides. TRIGRS employs one-dimensional (1-D) subsurface flow to simulate the infiltration rate, whereas a three-dimensional (3-D) model is utilized in TiVaSS. The former has been widely used in landslide modeling, while the latter was developed only recently. Both programs are used for the spatiotemporal prediction of shallow landslides caused by rainfall. The present study uses the July 2011 landslide event that occurred in Mt. Umyeon, Seoul, Korea, for validation. The performance of the two programs is evaluated by comparison with data of the actual landslides in both location and timing by using a landslide ratio for each factor of safety class ( index), which was developed for addressing point-like landslide locations. In addition, the influence of surface flow on landslide initiation is assessed. The results show that the shallow landslides predicted by the two models have characteristics that are highly consistent with those of the observed sliding sites, although the performance of TiVaSS is slightly better. Overland flow affects the buildup of the pressure head and reduces the slope stability, although this influence was not significant in this case. A slight increase in the predicted unstable area from 19.30% to 19.93% was recorded when the overland flow was considered. It is concluded that both models are suitable for application in the study area. However, although it is a well-established model requiring less input data and shorter run times, TRIGRS produces less accurate results.

• Journal of Soil and Groundwater Environment
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• v.21 no.3
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• pp.21-34
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• 2016

In the present study, we applied various machine learning techniques comparatively for prediction of subsurface structures based on multiple secondary information (i.e., well-logging data). The machine learning techniques employed in this study are Naive Bayes classification (NB), artificial neural network (ANN), support vector machine (SVM) and logistic regression classification (LR). As an alternative model, conventional hidden Markov model (HMM) and modified hidden Markov model (mHMM) are used where additional information of transition probability between primary properties is incorporated in the predictions. In the comparisons, 16 boreholes consisted with four different materials are synthesized, which show directional non-stationarity in upward and downward directions. Futhermore, two types of the secondary information that is statistically related to each material are generated. From the comparative analysis with various case studies, the accuracies of the techniques become degenerated with inclusion of additive errors and small amount of the training data. For HMM predictions, the conventional HMM shows the similar accuracies with the models that does not relies on transition probability. However, the mHMM consistently shows the highest prediction accuracy among the test cases, which can be attributed to the consideration of geological nature in the training of the model.

• Journal of Soil and Groundwater Environment
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• v.15 no.3
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• pp.34-43
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• 2010

The fate of hydrophobic organic contaminants (HOCs) in ground water is highly affected by the distribution and property of the carbonaceous materials (CMs) in subsurface sediments. CMs in soils consist of organic matters (e.g., cellulose, fulvic acid, humic acid, humin, etc.) and black carbon such as char, soot, etc. The distribution and property of CMs are governed by source materials and geological evolution (e.g., diagenesis, catagenesis, etc.) of them. In this study, the distribution and property of CMs in subsurface sediments near the Imjin river in the Republic of Korea and HOC sorption property to the subsurface sediments were investigated. The organic carbon contents of sand and clay/silt layers were about 0.35% and 1.37%, respectively. The carbon contents of condensed form of CMs were about 0.13% and 0.45%, respectively. The existence of black carbon was observed using scanning electron microscopes with energy dispersive spectroscopy. The specific surface areas (SSA) of CMs in heavy fraction(HFrCM) measured with N2 were $35-46m^2/g$. However, SSAs of those HFrCM mineral fraction was only $1.6-4.3m^2/g$. The results of thermogravimetric analysis show that the mass loss of HFrCM was significant at $50-200^{\circ}C$ and $350-600^{\circ}C$ due to the degradation of soft form and condensed form of CMs, respectively. The trichloroethylene (TCE) sorption capacities of sand and clay/silt layers were similar to each other, and these values were also similar to oxidzed layer of glacially deposited subsurface sediments of the Chanute Air Force Base (AFB) in Rantoul, Illinois. However, these were 7-8 times lower than TCE sorption capacity of reduced layer of the Chanute AFB sediments. For accurate prediction of the fate of hydrophobic organic contaminants in subsurface sediments, continuous studies on the development of characterization methods for CMs are required.

• Journal of Soil and Groundwater Environment
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• v.26 no.6
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• pp.106-117
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• 2021

The purpose of this study is prediction of landslide occurrence reflecting the subsurface flow characteristics within the soil layer in the future due to climate change in a large scale watershed. To do this, we considered the infinite slope stability theory to evaluate the landslide occurrence with predicted soil moisture content by SWAT model based on monitored data (rainfall-soil moisture-discharge). The correlation between the SWAT model and the monitoring data was performed using the coefficient of determination (R²) and the model's efficiency index (Nash and Sutcliffe model efficiency; NSE) and, an accuracy analysis of landslide prediction was performed using auROC (area under Receiver Operating Curve) analysis. In results comparing with the calculated discharge-soil moisture content by SWAT model vs. actual observation data, R² was 0.9 and NSE was 0.91 in discharge and, R² was 0.7 and NSE was 0.79 in soil moisture, respectively. As a result of performing infinite slope stability analysis in the area where landslides occurred in the past based on simulated data (SWAT analysis result of 0.7~0.8), AuROC showed 0.98, indicating that the suggested prediction method was resonable. Based on this, as a result of predicting the characteristics of landslide occurrence by 2050 using climate change scenario (RCP 8.5) data, it was calculated that four landslides could occur with a soil moisture content of more than 75% and rainfall over 250 mm/day during simulation. Although this study needs to be evaluated in various regions because of a case study, it was possible to determine the possibility of prediction through modeling of subsurface flow mechanism, one of the most important attributes in landslide occurrence.

• Magazine of korean Tunnelling and Underground Space Association
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• v.21 no.1
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• pp.101-112
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• 2019

This case study presented a simplified failure mechanism approach used as a preliminary deformation prediction for the Mexico City's metro system expansion. Because of the Mexico City's difficult subsoils, Line 12 project was considered one of the most challenging projects in Mexico. Mexico City's subsurface conditions can be described as a multilayered stratigraphy changing from soft high plastic clays to dense to very dense cemented sands. The Line 12 trajectory crossed all three main geotechnical Zones in Mexico City. Starting from to west of the City, Line 12 was projected to pass through very dense cemented sands corresponding to the Foothills zone changing to the Transition zone and finalizing in the Lake zone. Due to the change in the subsurface conditions, different constructions methods were implemented including the use of TBM (Tunnel Boring Machine), the NATM (New Austrian Tunneling Method), and cut-and-cover using braced Diaphragm walls for the underground section of the project. Preliminary crown and excavation front deformations were determined using a simplified failure mechanism prior to performing finite element modeling and analysis. Results showed corresponding deformations for the crown and the excavation front to be 3.5cm (1.4in) and 6cm (2.4in), respectively. Considering the complexity of Mexico City's difficult subsoil formation, construction method selection becomes a challenge to overcome. The use of a preliminary results in order to have a notion of possible deformations prior to advanced modeling and analysis could be beneficial and helpful to select possible construction procedures.

• Tribology and Lubricants
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• v.22 no.6
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• pp.320-328
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• 2006

In this study, the simulation of rolling contact fatigue based on stress analysis is conducted under Elastohydrodynamic Lubrication state. To predict a crack initiation life accurately, it is necessary to calculate contact stress and subsurface stresses accurately. Contact stresses are obtained by contact analysis of a semi-infinile solid based on the use of influence functions and the subsurface stress field is obtained using rectangular patch solutions. And a numerical algorithm using Newton-Rapson method was constructed to calculate the Elastohydrodynamic lubrication pressure. Based on these stress values, several multiaxial high-cycle fatigue criteria are used and the critical loads corresponding to fatigue limits are calculated.

• Ocean and Polar Research
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• v.23 no.2
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• pp.181-188
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• 2001

We describe here the Korea ocean prediction system that closely resembles operational numerical weather prediction systems. This prediction system will be served for real-time forecasts. The core of the system is a three-dimensional primitive equation numerical circulation model, based on ${\sigma}$-coordinate. Remotely sensed multi-channel sea surface temperature (MCSST) is imposed at the surface. Residual subsurface temperature is assimilated through the relationship between vertical temperature structure function and residual of sea surface height (RSSH) using an optimal interpolation scheme. A unified grid system, named as [K-E-Y], that covers the entire seas around Korea is used. We present and compare hindcasting results during 1990-1999 from a model forced by MCSST without incorporating RSSH data assimilation and the one with both MCSST and RSSH assimilated. The data assimilation is applied only in the East Sea, hence the comparison focuses principally on the mesoscale features prevalent in the East Sea. It is shown that the model with the data assimilation exhibits considerable skill in simulating both the permanent and transient mesoscale features in the East Sea.

• Tribology and Lubricants
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• v.18 no.2
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• pp.160-166
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• 2002

In case of rough contact fatigue, the accurate calculation of surface tractions is essential to the prediction of crack initiation life. Accurate Surface tractions influencing shear stress amplitude can be obtained by contact analysis based on the morphology of contact surfaces. In this study, to simulate rough contact under sliding condition, gaussian rough surface generated numerically in the previous study was used and to calculate clack initiation life in the substrate, dislocation pileup theory was used.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2000.11a
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• pp.72-79
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• 2000

In case of rough contact fatigue, the accurate calculation of surface tractions is essential to the prediction of crack initiation life. Accurate Surface tractions influencing shear stress amplitude can be obtained by contact analysis based on tile morphology of contact surfaces. In this study, to simulate rough contact under sliding condition, gaussian rough surface generated numerically in the previous study was used and to calculate crack initiation life in the substrate, dislocation pileup theory was used.

• Journal of the Korean earth science society
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• v.26 no.7
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• pp.706-713
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• 2005

Subsurface oceanic data (Z20; Depth of $20^{\circ}C$ isotherm and WWV; Warm Water Volume) from the tropical Pacific Ocean from 1980 to 2004 were utilized to examine upper ocean variations in relation to E1 Nino. Time series analysis using EOF, composite, and cross-correlation methods indicated that there are significant time delays between subsurface oceanic parameters and the Nino3.4 SST. It implied that Z20 and WWV would be more reliable predictors of El Nino events. Based on analyzed results, we also constructed neural network model to predict the Nino3.4 SST from 1996 to 2004. The forecasting skills for the model using WWV were statistically higher than that using the trade wind except for short range forecasting less than 3 months. This model greatly predicted SST than any other previous statistical model, especially at lead times of 5 to 8 months.