• 한국수자원학회논문집
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• 제38권9호
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• pp.713-725
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• 2005

본 연구에서는 미국 지질조사국에서 개발한 PRMS 모형을 국내 7개 댐유역에 적용하여 국내 적용성과 모의한 계를 분석하였다. 모형의 적용성을 평가하기 위해 모형 이론과 매개변수에 대해 검토하고, 국내 실정을 고려한 입력자료와 매개변수 추정의 가용성을 분석하였다. 각 적용유역들에서 GIS자료를 활용하여 추정 가능한 매개변수들은 추정하고 나머지 변수들은 Rosenbrock 방법을 이용하여 보정하였다. 모의결과를 다각적으로 분석하여 PRMS 모형의 모의 능력과 한계를 분석한 결과 PRMS 모형은 모든 적용유역에서 관측치에 높은 적합성을 나타내었다. 기본값을 사용한 융설모의에서도 비교적 정확한 모의가 가능한 것으로 나타났다. 적용 유역면적에 상관없이 신뢰성 높은 유출분석이 가능하였으나, 대유역인 경우 준분포형적인 특성보다는 일체형모형에 가까운 유출모의를 하는 것으로 나타났다.

• 한국수자원학회논문집
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• 제34권1호
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• pp.91-103
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• 2001

본 연구에서는 지표면유출과 하천유출의 실시간 연계를 통하여 하천 각 구간에서의 수위와 유량을 예측하는 수리학적 홍수추적 모형을 개발하였다. 주로 유역의 지형특성에 따라 결정되는 수문곡선의 형상을 반영하여 홍수 유출량 산정방법을 개선하였으며, 침투과정을 고려하여 강우초가 첨두유량의 과다산정을 제거하였다. 지표면유출의 하천유입을 연속방정식에 반영하여 여러 단면에서의 유입이 용이하였으며, 이는 강우의 급격한 변이에서도 수치적 안정을 가져다 주었다. 폭우시 양양 남대천 유역에서 현장 관측을 실시하였으며, 관측자료에 적용하여 개발된 모형의 현장 적용성과 신뢰성을 확보하였다.

• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2003년도 Proceedings of the international symposium on the fusion technology
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• pp.321-327
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• 2003

[ $CO_2$ ] sequestration in oil reservoirs can be one of the most effective strategies for long-term removal of greenhouse gas from atmosphere. This paper presents an advantage of the localized nonlinear approximation of integral equation solutions for inverting crosswell electromagnetic data, which are observed as a part of pilot project of $CO_2$ flooding at the Lost Hills oil field in central California, U.S.A. To monitor the migration of $CO_2$, we have used 2-D cylindrically symmetric and 2.5-D tomographic inversion methods. These two schemes produce nearly the same images if the borehole separation is large compared with the skin depth. However, since the borehole separation is much less than five skin depths in this $CO_2$ injection experiment, the 2.5-D model seems to be more reliable than the 2-D model. In fact, the pre-injection 2.5-D image is more successfully compared with induction logs observed in the two wells than the 2-D model. From the time-lapse crosswell imaging, we can confirm the replacement of brine with $CO_2$ makes a decrease of conductivity.

• Geomechanics and Engineering
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• 제21권6호
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• pp.551-564
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• 2020

High-stress and complex geological conditions impose great challenges to maintain excavation stability during deep underground mining. In this research, large anisotropic deformation and its management by support system at a deep underground mine in Western Australia were simulated through three-dimensional finite-difference model. The ubiquitous-joint model was used and calibrated in FLAC3D to reproduce the deformation and failure characteristics of the excavation based on the field monitoring results. After modeling verification, the roles of mining depth also the intercept angle between excavation axis and foliation orientation on the deformation and damage were studied. Based on the results, quantitative relationships between key factors and damage classifications were presented, which can be used as an engineering tool. Subsequently, the performance of support system installation sequences was simulated and compared at four different scenarios. The results show that, first surface support and then reinforcement installation can obtain a better controlling effect. Finally, the influence of bolt spacing and ring spacing were also discussed. The outcomes obtained in this research may play a meaningful reference for facing the challenges in thin-bedded or foliated ground conditions.

• Geosciences Journal
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• 제22권6호
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• pp.1053-1067
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• 2018

This paper uses a probability-based approach to study the spatial relationships between landslides and their causative factors in the Mingchukur area, Bostanlik districts of Tashkent, Uzbekistan. The approach is based on digital databases and incorporates methods including probability analysis, spatial pattern analysis, and interactive mapping. First, an object-oriented conceptual model for describing landslide events is proposed, and a combined database of landslides and environmental factors is constructed by integrating various databases within a unifying conceptual framework. The frequency ratio probability model and landslide occurrence data are linked for interactive, spatial evaluation of the relationships between landslides and their causative factors. In total, 15 factors were analyzed, divided into topography, hydrology, and geology categories. All analyzed factors were also divided into numerical and categorical types. Numerical factors are continuous and were evaluated according to their $R^2$ values. A landslide susceptibility map was constructed based on conditioning factors and landslide occurrence data using the frequency ratio model. Finally, the map was validated and the accuracy showed the satisfactory value of 83.3%.

• Geomechanics and Engineering
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• 제36권5호
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• pp.441-453
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• 2024

Sinkhole subsidence and collapse is a common geohazard often formed in karst areas such as the state of Florida, United States of America. To predict the sinkhole occurrence, we need to understand the formation mechanism of sinkhole and its karst hydrogeology. For this purpose, investigating the factors affecting sinkholes is an essential and important step. The main objectives of the presenting study are (1) the development of a machine learning (ML)-based model, namely C5.0 decision tree (C5.0 DT), for the prediction of sinkhole susceptibility, which accounts for sinkhole/subsidence inventory and sinkhole contributing factors (e.g., geological/hydrogeological) and (2) the construction of a regional-scale sinkhole susceptibility map. The study area is east central Florida (ECF) where a cover-collapse type is commonly reported. The C5.0 DT algorithm was used to account for twelve (12) identified hydrogeological factors. In this study, a total of 1,113 sinkholes in ECF were identified and the dataset was then randomly divided into 70% and 30% subsets for training and testing, respectively. The performance of the sinkhole susceptibility model was evaluated using a receiver operating characteristic (ROC) curve, particularly the area under the curve (AUC). The C5.0 model showed a high prediction accuracy of 83.52%. It is concluded that a decision tree is a promising tool and classifier for spatial prediction of karst sinkholes and subsidence in the ECF area.

• Geomechanics and Engineering
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• 제13권6호
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• pp.1011-1025
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• 2017

The geological conditions surrounding the Jijiapo Tunnel of the Three Gorges Fanba Highway project in Hubei Province are very complex. In this paper, a 3-D physical model was carried out to study the evolution process of filling-type fracture water inrush and mud gush based on the conditions of the section located between 16.040 km and 16.042 km of the Jijiapo Tunnel. The 3-D physical model was conducted to clarify the effect of the self-weight of the groundwater level and tunnel excavation during water inrush and mud gush. The results of the displacement, stress and seepage pressure of fracture and surrounding rock in the physical model were analyzed. In the physical model the results of the model test show that the rock displacement suddenly jumped after sustainable growth, rock stress and rock seepage suddenly decreased after continuous growth before water inrushing. Once water inrush occured, internal displacement of filler increased successively from bottom up, stress and seepage pressure of filler droped successively from bottom up, which presented as water inrush and mud gush of filling-type fracture was a evolving process from bottom up. The numerical study was compared with the model test to demonstrate the effectiveness and accuracy of the results of the model test.

• 한국지반공학회논문집
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• 제26권2호
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• pp.33-43
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• 2010

지열은 고효율 신재생에너지로 각광을 받고 있으며 건축물의 냉난방 설비 시스템으로 활용이 점차 확산되고 있다. 지열 히트펌프 중에서 지하수를 열원으로 사용하는 단일심정(Standing column well)은 특히 효율이 높고 초기설치비용이 저렴하며 국내 지반 수리조건에 적합하다. 반면, 국내에는 아직 SCW의 성능을 평가할 수 있는 수치해석 모델이 없으며 국내 자료를 적용한 수치해석이 수행된 바 없다. 본 연구에서는 SCW 수치해석 모델을 유한체적해석 프로그램을 이용하여 구축하였다. 수치적 모델은 수리 열 연계해석을 수행하여 열이류, 대류, 전도를 모두 모사한다. SCW 모델은 미국과 국내에서 계측된 현장 데이터를 통하여 검증하였다. 비교 결과 본 연구에서 구축된 수치해석 모델은 정확하게 SCW의 거동을 예측할 수 있는 것으로 나타났다. 검증된 수치해석 모델은 동반논문에서 매개변수연구에 활용되었다.

• 한국물환경학회지
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• 제38권6호
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• pp.306-315
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• 2022

In this study, long-term measurement data were applied to the LOADEST model and used as an analysis tool to identify and interpret trends in pollution load. The LOADEST model is a regression equation-based pollution load estimation program developed by the United States Geological Survey (USGS) to estimate the change in the pollution load of rivers according to flow rate and time and provides 11 regression equations for pollution load evaluation. As a result of simulating the Gwangjuchen2, Pungyeongjeongchen, and Pyeongdongchen in the Yeongbon B unit basin in the middle and upper reaches of the Yeongsan River with the LOADEST model using water quality and flow measurement data, lower values were observed for the Gwangjuchen2 and Pyeongdongchen, whereas the Pungyeongjeongchen had higher values. This was judged to be due to the characteristics of the LOADEST model related to data continuity. According to the parameters estimated by the LOADEST model, pollutant trends were affected by increases in the flow. In addition, variability increased with time, and BOD and T-P were affected by the season. Thus, the LOADEST model can contribute to water quality management as an analytical tool for long-term data monitoring.

• 한국대기환경학회지
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• 제25권3호
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• pp.196-210
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• 2009

The land surface precesses is very important to predict urban meteorological conditions. Thus, the latest land use data set to reflect the rapid progress in urbanization was applied to simulate urban thermal environment in Daegu. Because use of the U.S geological Survey (USGS) 25-category data, currently in the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5), does not accurately described the heterogeneity of urban surface, we replaced the land use data in USGS with the latest land-use data of the Korea Ministry of Environment over Daegu. The single urban category in existing 24-category U.S. Geological survey land cover classification used in MM5 was divided into 5 classes to account for heterogeneity of urban land cover. The new land cover classification (MC-LULC) improved the capability of MM5 to simulate the daytime part of the diurnal temperature cycle in the urban area. The 'MC-LULC' simulation produced the observed temperature field reasonably well, including spatial characteristics. The warm cores in western Daegu is characterized by an industrial area.