• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1269-1273
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• 2010

이러한 강우자료의 결측값이나 오자료를 보정하는 것은 그 유역의 정확한 수문학적 특성 파악 및 안전한 수공구조물의 설계에 영향을 미치게 되므로 매우 중요하다고 할 수 있다. 최근 이러한 강우자료를 비선형적 모델인 인공신경망(Artificial Neural Network)을 이용하여 보정하는 연구가 활발히 진행되고 있다(오재우 등, 2008). 그러나 이러한 인공신경망을 적용하는 경우, 선택한 신경망 구조의 형태와 학습(training)을 위해 사용되는 자료가 전체 자료의 특성을 반영하고 있는 정도에 따라 정확도에 차이를 보인다(한광희 등, 2010). 따라서 자료보정을 위한 입력 자료의 선택은 인공신경망을 이용한 결측치 보정의 중요한 과정이다. 본 연구에서는 이러한 입력 자료의 선택을 위한 여러 가지 기법 중 입력 변수간의 상호정보량 (Mutual Information)을 이용한 방법을 적용하여 대상 결측 지점을 보정할 강우지점을 선별한 후 선택된 지점만으로 인공신경망을 구성하여 강우자료를 보정하고 주변 자료를 모두 이용한 결과와 상관성분석으로 얻어진 결과와 비교하였다.

• Computational Structural Engineering
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• v.10 no.4
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• pp.303-313
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• 1997

Though many techniques for the damage assessment of structures have been studied recently, most of them can be only applied to simple structures. Therefore, practical damage assessment techniques that evaluate the damage location and the damage state for large structures need to be developed. In this study, a damage assessment technique using a neural network is developed, in which the bilevel damage assessment procedure is proposed to evaluate the damage of a large structure from the limited monitoring data. The procedure is as follows ; first, for the rational selection of damage critical members, the members that affect the probability of failure or unusual structural behavior are selected by sensitivity analysis. Secondly, the monitoring points and the number of sensors that are sensitive to the damage severity of the selected members are also selected through the sensitivity analysis with a proposed sensitivity measurement format. The validity and applicability of the developed technique are demonstrated by various examples, and it has been shown that the practical information on the damage state of the selected critical members can be assessed even though the limited monitoring data have been used.

• Explosives and Blasting
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• v.17 no.4
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• pp.67-88
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• 1999

Ground settlements induced by tunnel excavation cause the foundations of the neighboring superstructures to deform. An expert system called NESASS was developed to analyze the structural safety of such superstructures. NESASS predicts the trend of ground settlements to be resulted from tunnel excavation and carries out a safety analysis for superstructures on the basis of the predicted ground settlements. Using neural network techniques, NESASS learns a data base consisting of the measured ground settlements collected from numerous actual fields and infers a settlement trend at the field of interest. NESASS calculates the magnitudes of angular distortion, deflection ratio, and differential settlement of the structure and, in turn, determines the safety of the structure. In addition, NESASS predicts the patterns of cracks to be formed on the structure using Dulacskas model for crack evaluation. In this study, the ground settlements measured from the Seoul subway construction sites were collected and sorted with respect to the major factors influencing ground settlement. Subsequently, a database of ground settlement due to tunnel excavation was built. A parametric study was performed to verify the reliability of the proposed neural network structure. A comparison of the ground settlement trends predicted by NESASS with the measured ones indicates that NESASS leads to reasonable predictions. An examples is presented in this paper where NESASS is used to evaluate the safety of a structure subject to deformation due to tunnel excavation near to the structure.

• Journal of the Earthquake Engineering Society of Korea
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• v.15 no.4
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• pp.33-43
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• 2011

This paper addresses a fundamental study that is necessary to complement and improve the current domestic design specifications for the strong motion duration criterion and the envelope function of artificial accelerograms that can be applied to the earthquake-proof design of nuclear structures. The criteria for the design response spectra and strong motion duration suggested by USNRC and ASCE Standard 4-98 are commonly being used in the profession, and they are first compared with each other and reviewed. By applying 209 real strong earthquake records that are greater than 5 in magnitude at rock sites to the strong motion duration criterion in ASCE 4-98, an empirical regression model that predicts the strong motion duration as a function of the earthquake magnitude was then developed. Using synthetically generated earthquake time histories for the 10 cases whose strong motion durations varied from 6 to 20 seconds, extensive seismic analyses were finally conducted to identify the effects of the strong motion durations on the seismic responses of the nuclear power plant containment structures.

• Geotechnical Engineering
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• v.14 no.2
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• pp.107-126
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• 1998

Ground settlements induced by tunnel excavation cause the foundations of the neighboring building structures to deform. An expert system called NESASS( Neural network Expert System for Adjacent Structure Safety analysis) was developed to analyze the structural safety of such building structures. NESASS predicts the trend of ground settlements resulting from tunnel excavation and carries out a safety analysis for building structures on the basis of the predicted ground settlements. Using neural network technique. the NESASS learns the database consisting of the measured ground settlements collected from numerous actual fields and infers a settlement trend at the field of interest. The NESASS calculates the magnitudes of angular distortion, deflection ratio, and differential settlement of the structure. and in turn, determines the safety of the structure. In addition, the NESASS predicts the patterns of cracks to be formed in the structure, using Dulacska model for crack evaluation. In this study, the ground settlements measured from Seoul subway construction sites were collected and classified with respect to the major factors influencing ground settlement. Subsequently, a database of ground settlement due to tunnel excavation was built. A parametric study was performed to select the optimal neural network model for the database. A comparison of the ground settlement predicted by the NESASS with the measured ones indicates that the NESASS leads to reasonable predictions. The results of confidence evaluation for safety evaluation system of the NESASS are presented in this paper.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.1
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• pp.1-9
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• 2008

In seismic response analysis of building structures, the input ground accelerations have considerable effect on the nonlinear response characteristics of structures. The characteristics of soil and the locality of the site where those ground motions were recorded affect on the contents of earthquake waves. Therefore, it is difficult to select appropriate input ground motions for seismic response analysis. This study describes a generation of artificial earthquake wave compatible with seismic design spectrum, and also evaluates the seismic response values of multistory reinforced concrete structures by the simulated earthquake motions. The artificial earthquake wave are generated according to the previously recorded earthquake waves in past major earthquake events. The artificial wave have identical phase angles to the recorded earthquake wave, and their overall response spectra are compatible with seismic design spectrum with 5% critical viscous damping. The input ground motions applied to this study have identical elastic acceleration response spectra, but have different phase angles. The purpose of this study is to investigate their validity as input ground motion for nonlinear seismic response analysis. As expected, the response quantifies by simulated earthquake waves present better stable than those by real recording of ground motion. It was concluded that the artificial earthquake waves generated in this paper are applicable as input ground motions for a seismic response analysis of building structures. It was also found that strength of input ground motions for seismic analysis are suitable to be normalize as elastic acceleration spectra.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2006.11a
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• pp.47-51
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• 2006

전주시의 도심 내에 고층건물의 건설전과 후의 풍속변화를 알아보기 위한 풍동실험을 통하여 다음과 같은 결론을 얻을 수 있었다. 고층건물의 건설은 도심주변의 풍속변화에 절대적 영향을 끼치는 요소인 것으로 파악되었다. 특히 건설 후에 최소 50% ${\sim}$ 최대 90%까지 풍속이 감소하는 부분이 발생하고 있다는 점은 고층건물과 같은 인공구조물의 건축과 입지가 주변의 기류변화가 급격한 영향을 주는 요소인 것이다. 이는 해당입지를 중심으로 바람의 원활한 소통이 발생하지 않아 국지적으로 도시기온이 신선한 바람의 흐름에 영향을 받지 않아 온실효과와 같은 현상을 발생시키게 되며, 이는 결과적으로 국지기온의 상승과 같은 문제를 발생시키게 됨을 의미하는 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.967-971
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• 2008

하상변화는 하천정비기본계획을 수립함에 있어 매우 중요한 고려사항 중에 하나이다. 이는 하상의 변화가 이 치수 및 생태계에 있어 큰 영향을 주기 때문이다. 적절하지 못한 하상변화의 예측은 기 축조된 하천구조물의 기능과 안정성을 위협하며, 이는 직접적으로 큰 경제적 피해를 일으킬 수 있다. 특히, 인공적으로 지어지는 댐과 같은 수공구조물의 축조는 하천의 상 하류간의 연결성을 끊어놓음으로서 자연상태에서의 유사이송 변화를 일으키며 이는 하천의 급격한(자연상태와 비교하여 비교적 단시간동안 일어나는) 하상변화의 주 원인으로 작용한다. 본 연구는 댐 축조에 의해 상류지역의 하상이 어떻게 변화하는지를 연구하기 위하여 대상지역으로 충주댐 상류 지역을 설정하였으며, 충주댐 축조 후 1996년 측량자료와 최근의 2007년 측량자료를 수집하여 충주댐 상류구간의 하상변화를 분석하였다. 또한, 현장에서 채취한 하상토 입도분포 자료와 관련 수문자료를 수집하여 Hec-Ras 와 Hec-6 프로그램을 이용하여 하상변화에 대한 모의 시뮬레이션 결과를 측량자료와 비교하여 댐 상류지역의 하상변화 특성을 도출하는 것을 목적으로 하였다.

• Journal of Wetlands Research
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• v.15 no.3
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• pp.301-315
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• 2013

The purpose of this study is to investigate characteristics of hydromorpological structures that affect landscape preference and visual characteristics on the sections of the designated streams where have dynamic ecological characteristics. We evaluated the ecological status of the streams utilizing LAWA to assess hydromorpological structures of streams. We also investigated preference and visual characteristics of stream landscapes through Semantic Differential Scale(SD scale). The differences of visual images according to the characteristics of hydromorpological structures in the sites were analyzed by descriptive statistics, One-way ANOVA, and t-test. As a result, this study showed that sections represented as "good" ecological status are shown to be harmonious, beautiful, natural, and clean comparing to sections represented as "poor" ecological status. The hydromorpological structures that have significant impacts on the visual characteristics are considered as riparian vegetation, cross-sectional shape, and the artificial structures. Results of this study can help guide the stream restoration of the damaged stream to improving ecological function and positive landscape.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2001.10a
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• pp.71-82
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• 2001

인공위성을 이용한 범 지구 위치결정시스템인 GPS(Global Positioning System)는 수 밀리의 정밀도로 정적, 동적 위치측정이 가능한 시스템으로 교량, 건축물, 댐 등 각종 구조물의 미세한 변위를 측정하는데 이용되고 있다. 최근 국내에서도 대형구조물의 변위 측정에 GPS를 활용하려는 시도가 부분적으로 이루어지고 있으나 초보적인 단계이며 체계적인 연구가 이루어지지 못하고 있는 실정이다. 본 연구에서는 RTK(Real Time Kinematic) GPS로 구조물의 변위를 실시간 측정하고 모니터링 할 수 있는 시스템을 개발하였다. 먼저 예비실험으로 반송파의 차분에 의해서 증폭되는 수신기의 측정잡음 오차, 다중경로 오차, GDOP(Geometric Dilution of Precision)가 RTK GPS의 위치정확도에 미치는 영향을 분석하였다. 그리고, RTK GPS를 이용하여 마포대교를 관측한 결과, 수 센티미터 정도 발생하는 구조물의 변위를 3차원으로 정밀 관측할 수 있었으며, 본 연구에서 개발한 모니터링프로그램을 이용하여 구조물의 거동을 실시간으로 모니터링 할 수 있었다.