• Proceedings of the Korean Geotechical Society Conference
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• 1998.05a
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• pp.35-81
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• 1998

Distinct Element Method(DEM) has a great advantage to model the discontinuous behaviour of jointed rock masses such as rotation, sliding, and separation of rock blocks. Geometrical data of joints by a field monitoring is not enough to model the jointed rock mass though the results of DE analysis for the jointed rock mass is most sensitive to the distributional properties of joints. Also, it is important to use a properly joint law in evaluating the stability of a jointed rock mass because the joint is considered as the contact between blocks in DEM. In this study, a stochastic modelling technique is developed and the dilatant rock joint is numerically modelled in order to consider th geometrical and mechanical properties of joints in DE analysis. The stochastic modelling technique provides a assemblage of rock blocks by reproducing the joint distribution from insufficient joint data. Numerical Modelling of joint dilatancy in a edge-edge contact of DEM enable to consider not only mechanical properties but also various boundary conditions of joint. Preprocess Procedure for a stochastic DE model is composed of a statistical process of raw data of joints, a joint generation, and a block boundary generation. This stochastic DE model is used to analyze the effect of deviations of geometrical joint parameters on .the behaviour of jointed rock masses. This modelling method may be one tool for the consistency of DE analysis because it keeps the objectivity of the numerical model. In the joint constitutive law with a dilatancy, the normal and shear behaviour of a joint are fully coupled due to dilatation. It is easy to quantify the input Parameters used in the joint law from laboratory tests. The boundary effect on the behaviour of a joint is verified from shear tests under CNL and CNS using the numerical model of a single joint. The numerical model developed is applied to jointed rock masses to evaluate the effect of joint dilation on tunnel stability.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.497-508
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• 2023

Agricultural reservoirs are crucial structures for water resources monitoring especially in Korea where the resources are seasonally unevenly distributed. Optical and Synthetic Aperture Radar (SAR) satellites, being utilized as tools for monitoring the reservoirs, have unique limitations in that optical sensors are sensitive to weather conditions and SAR sensors are sensitive to noises and multiple scattering over dense vegetations. In this study, we tried to improve water body detection accuracy through optical-SAR data fusion, and quantitatively analyze the complementary effects. We first detected water bodies at Edong, Cheontae reservoir using the Compact Advanced Satellite 500(CAS500), Kompsat-3/3A, and Sentinel-2 derived Normalized Difference Water Index (NDWI), and SAR backscattering coefficient from Sentinel-1 by K-means clustering technique. After that, the improvements in accuracies were analyzed by applying K-means clustering to the 2-D grid space consists of NDWI and SAR. Kompsat-3/3A was found to have the best accuracy (0.98 at both reservoirs), followed by Sentinel-2(0.83 at Edong, 0.97 at Cheontae), Sentinel-1(both 0.93), and CAS500(0.69, 0.78). By applying K-means clustering to the 2-D space at Cheontae reservoir, accuracy of CAS500 was improved around 22%(resulting accuracy: 0.95) with improve in precision (85%) and degradation in recall (14%). Precision of Kompsat-3A (Sentinel-2) was improved 3%(5%), and recall was degraded 4%(7%). More precise water resources monitoring is expected to be possible with developments of high-resolution SAR satellites including CAS500-5, developments of image fusion and water body detection techniques.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1611-1623
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• 2021

Thisstudy demonstratessoil moisture and evapotranspiration performance using Korea Land Data Assimilation System (KLDAS) under Korea Land Information System (KLIS). Spin-up was repeated 8 times in 2018. In addition, low-resolution and high-resolution meteorological data were generated using meteorological data observed by Korea Meteorological Administration (KMA), Rural Development Administration (RDA), Korea Rural Community Corporation (KRC), Korea Hydro & Nuclear Power Co.,Ltd. (KHNP), Korea Water Resources Corporation (K-water), and Ministry of Environment (ME), and applied to KLDAS. And, to confirm the degree of accuracy improvement of Korea Low spatial resolution (hereafter, K-Low; 0.125°) and Korea High spatial resolution (hereafter, K-High; 0.01°), soil moisture and evapotranspiration to which Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) and ASOS-Spatial (ASOS-S) used in the previous study were applied were evaluated together. As a result, optimization of the initial boundary condition requires 2 time (58 point), 3 time (6 point), and 6 time (3 point) spin-up for soil moisture. In the case of evapotranspiration, 1 time (58 point) and 2 time (58 point) spin-ups are required. In the case of soil moisture to which MERRA-2, ASOS-S, K-Low, and K-High were applied, the mean of R² were 0.615, 0.601, 0.594, and 0.664, respectively, and in the case of evapotranspiration, the mean of R² were 0.531, 0.495, 0.656, and 0.677, respectively, indicating the accuracy of K-High was rated as the highest. The accuracy of KLDAS can be improved by securing a large number of ground observation data through the results of this study and generating high-resolution grid-type meteorological data. However, if the meteorological condition at each point is not sufficiently taken into account when converting the point data into a grid, the accuracy is rather lowered. For a further study, it is expected that higher quality data can be produced by generating and applying grid-type meteorological data using the parameter setting of IDW or other interpolation techniques.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.3
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• pp.178-184
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• 2014

In this study, monitoring method which is more economic and easier in maintenance comparing to existing monitoring system was scrutinized for application to sewer intercepting chamber of 10.2 ha basin area by estimating CSOs (Combined Sewer Overflows) quantity and quality with 2 rainfall events using electrical conductivity data and civil research model. The result showed that determination coefficient of flow estimation by EC (Electrical Conductivity) dilution ratio and observed data was over 0.86 for all cases and the accuracy of estimation was improved from 0.5 to 0.8 for determination coefficient ($R^2$) and from 54.1% to 68.5% for accumulation frequency of relative error by considering antecedent dry days and rainfall duration. CSOs water quality estimation results by civil research model showed that determination coefficients were 0.64~0.97 for BOD and 0.70~0.95 for SS.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.7
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• pp.369-376
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• 2002

Although LRU is not adequate for database that has non-uniform reference pattern, it has been adopted in most database systems due to the absence of the proper alternative. We analyze database block reference pattern with the realistic database trace. Based on this analysis, we propose a new cache replacement policy. Trace analysis shows that extremely non-popular blocks take up about 70 % of the entire blocks. The influence of recency on blocks' re-reference likelihood is at first strong due to temporal locality, however, it rapidly decreases and eventually becomes negligible as stack distance increases. Based on this observation, RCB(Reference Characteristic Based) cache replacement policy, which we propose in this paper, classifies the entire blocks into four block groups by blocks' recency and re-reference likelihood, and operates different priority evaluation methods for each block group. RCB policy evicts non-popular blocks more quickly than the others and evaluates the priority of the block by frequency that has not been referenced for a long time. In a trace-driven simulation, RCB delivers a better performance than the existing polices(LRU, 2Q, LRU-K, LRFU). Especially compared to LRU. It reduces miss count by 5~l2.7%. Time complexity of RCB is O(1), which is the same with LRU and 2Q and superior to LRU-K(O(log$_2$N)) and LRFU(O(l) ~ O(log$_2$N)).

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.62-73
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• 2010

A bird is needed efficient conservation through habitat management, as the representative of an organism to evaluate the steady of complex ecosystem. So, this study will offer the useful basic data for preserving habitat from now on, as presenting a estimating model with the GIS program which selected factors effecting the habitat of a forest-dwelling bird in Changwon. As the resort of the survey, the number of forest-dwelling birds living in the 135 survey sites were 5 order, 15 family, 26 species and 922 individual. Also, as the result of making habitat analysis into a predict model, 'NDVI', 'Distance to valley', 'Distance to mixed forest' and 'Area of field' were significant and they had R-squares of 51.3%. Next, as the resort of researching the accuracy of Model, it was a reasonable prediction, as the correlation coefficient is 0.735 and MAPE is 20.7%, and a predict map of habitat was made with the model. This map could predict species diversity of no investigated areas and could be an useful basic data for preserving habitat, as an on-the-spot survey.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.4
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• pp.313-322
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• 2013

Batteries, which are being used as energy sources in various applications, tend to degrade, and their capacity declines with repeated charging and discharging cycles. A battery is considered to fail when it reaches 80% of its initial capacity. To predict this, prognosis techniques are attracting attention in recent years in the battery community. In this study, a method is proposed for estimating the battery health and predicting its remaining useful life (RUL) based on the slope of the charge voltage curve. During this process, a Bayesian framework is employed to manage various uncertainties, and a Particle Filter (PF) algorithm is applied to estimate the degradation of the model parameters and to predict the RUL in the form of a probability distribution. Two sets of test data-one from the NASA Ames Research Center and another from our own experiment-for an Li-ion battery are used for illustrating this technique. As a result of the study, it is concluded that the slope can be a good indicator of the battery health and PF is a useful tool for the reliable prediction of RUL.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1139-1149
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• 2017

Measuring tree's volume is very important input data of various environmental analysis modeling However, It's difficult to use economical and equipment to measure a fragmented small green space in the city. In addition, Trees are sensitive to seasons, so we need new and easier equipment and quantification methods for measuring trees than lidar for high frequency monitoring. In particular, the tree's size in a city affect management costs, ecosystem services, safety, and so need to be managed and informed on the individual tree-based. In this study, we aim to acquire image data with UAV(Unmanned Aerial Vehicle), which can be operated at low cost and frequently, and quickly and easily quantify a single tree using SfM-MVS(Structure from Motion-Multi View Stereo), and we evaluate the impact of reducing number of images on the point density of point clouds generated from SfM-MVS and the quantification of single trees. Also, We used the Watertight model to estimate the volume of a single tree and to shape it into a 3D structure and compare it with the quantification results of 3 different type of 3D models. The results of the analysis show that UAV, SfM-MVS and solid model can quantify and shape a single tree with low cost and high time resolution easily. This study is only for a single tree, Therefore, in order to apply it to a larger scale, it is necessary to follow up research to develop it, such as convergence with various spatial information data, improvement of quantification technique and flight plan for enlarging green space.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.785-789
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• 2006

유역 수자원의 효율적인 관리 및 배분을 위해서는 세밀한 강우-유출관계의 규명이 무엇보다 중요하다. 이를 위해서는 먼저 하천 유출지점의 정확한 유량정보가 획득되어야 하며, 장기간에 걸쳐 신뢰성 있는 유량자료의 확보는 더욱 중요한 사항이다. 본 연구에서는 하천에서 관측된 유량자료를 장기간(1983년${\sim}$2004년)에 걸친 유출성분으로 분리하는 기법을 활용하여 제어지점의 유출량을 검증하였다. 유량자료를 출구지점의 관측유량$(Q_{ob})$을 회귀수$({\alpha}Q_e)$, 상류유입량$(Q_{up})$ 및 관측강우-유출량$({\beta}Q_{Rain})$의 성분으로 구분하여 산정하는 방식으로 유출량을 추정하였다. 여기서, 회귀수$({\alpha}Q_e)$란 유역 및 하도내 용수이용량의 회귀수, 상류유입량$(Q_{up})$은 상류 유출 제어지점의 관측유량으로 대청댐 방류량, 관측강우-유출량$({\beta}Q_{Rain})$은 유역내 강우에 의한 자연유출량이다. 여기서 사용된 수문기초자료는 대청댐 방류량, 대전 및 청주권 취수량, 강우에 의한 자연유출량, 공주관측유량 등으로 각 성분별로 생성된 일자료를 이용하여 공주지점의 월별, 분기별, 년도별 유출량을 산정하였다. 이 결과는 금강유역에 이미 구축되어있는 SSARR모형을 기반으로 한 RRFS(Rainfall Runoff Forecasting System, 유출예측 시스템)의 결과 및 관측치와 비교되었다. 계산결과 RRFS에 의한 유출량과 대청-공주구간의 유출성분분리에 의한 유출량은 관측값과 전반적으로 근사함을 확인하였으며, 검증지점의 정확한 유출율을 산정할 수 있다면, 관측자료의 연속성 및 신뢰도를 파악하는 척도를 제공할 수 있을 것으로 판단된다.측결과 있는 대상유역에 대한 적용이 요구된다.-Moment 방법에 의해 추정된 매개변수를 사용한 Power 분포를 적용하였으며 이들 분포의 적합도를 PPCC Test를 사용하여 평가해봄으로써 낙동강 유역에서의 저수시의 유출량 추정에 대한 Power 분포의 적용성을 판단해 보았다. 뿐만 아니라 이와 관련된 수문요소기술을 확보할 수 있을 것이다.역의 물순환 과정을 보다 명확히 규명하고자 노력하였다.으로 추정되었다.면으로의 월류량을 산정하고 유입된 지표유량에 대해서 배수시스템에서의 흐름해석을 수행하였다. 그리고, 침수해석을 위해서는 2차원 침수해석을 위한 DEM기반 침수해석모형을 개발하였고, 건물의 영향을 고려할 수 있도록 구성하였다. 본 연구결과 지표류 유출 해석의 물리적 특성을 잘 반영하며, 도시지역의 복잡한 배수시스템 해석모형과 지표범람 모형을 통합한 모형 개발로 인해 더욱 정교한 도시지역에서의 홍수 범람 해석을 실시할 수 있을 것으로 판단된다. 본 모형의 개발로 침수상황의 시간별 진행과정을 분석함으로써 도시홍수에 대한 침수위험 지점 파악 및 주민대피지도 구축 등에 활용될 수 있을 것으로 판단된다. 있을 것으로 판단되었다.4일간의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월이하의 중단기가 적합함을 발견하였다. 이상의 행태적 측면과 투자성과측면의 실증결과를 통하여 한국주식시장에 있어서 시장수익률을 평균적으로 초과할 수 있는 거래전략은 존재하므로 이러한 전략을 개발 및 활용할 수 있으며, 특히, 한국주식시장에 적합한 거래전략은 반전거래전략이고, 이 전략의 유용성은 투자자가 설정한 투자기간보다 더욱 긴

• Journal of Korea Water Resources Association
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• v.45 no.11
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• pp.1131-1141
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• 2012

In this study, factors that influence water supply capacities of dams are extracted using factor analysis, and multiple regression equations for estimating water supply capacities of dams are developed using the analysis results. Twenty-one multi-purpose dams and twelve Municipal and Industrial (M&I) water supply dams are selected for case studies, and eight variables influencing water supply capacities of dams, namely: watershed area, inflow, effective reservoir storage, grade on amount of M&I water supply, grade on amount of agricultural water supply, grade on amount of in-stream flow supply, grade on river administration, and grade on average rainfall, are determined. Two case studies for multi-purpose dams and M&I water supply dams are performed, employing factor analysis, respectively. For the two cases, preliminary tests, such as reviewing matrix of correlation coefficient, Bartlett's test of sphericity, and Kaiser-Meyer-Olkin (KMO) test, are conducted to evaluate the suitability of the variables for factor analysis. In case of multi-purpose dams, variables are grouped into three factors; M&I water supply dams, two factors. The factors are rotated using Varimax method, and then factor loading of each variable is computed. The results show that the variables influencing water supply capacities of dams are reasonably selected and appropriately grouped into factors. In addition, multiple regression equations for predicting the amounts of annual water supply of dams are established using the factor scores as explanatory variables, it is identified that the models' accuracies are high, and their applications to determining effective storage capacity of a dam during dam planning and design steps are presented. Consequently, it is thought that the variables and factors are useful for dam planning and dam design.