• Journal of the Earthquake Engineering Society of Korea
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• v.14 no.3
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• pp.49-57
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• 2010

Most previous research on the seismic response of structures with plan irregularities have focused on the relationship between the eccentricity and the amount of torsion. This approach cannot provide the direct relationship between the irregularity and the damage. Therefore, an investigation on the relationship between the eccentricities of buildings with plan irregularities and the damage index was performed. Inelastic dynamic time-history analyses were performed on one-story buildings with various eccentricities. For the damage assessment, a 3D damage index was adopted to reflect the effect of the bi-directional response and torsion. Based on the analysis results, buildings with eccentricities of 10%, 20% and 30% will suffer 3~5%, 13~18%, and 33~47% more damage than their regular counterparts, respectively.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.11a
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• pp.241-244
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• 2008

The authors proposed a new rapid-screening method for more reasonably evaluating seismic capacities of medium and low-rise RC buildings controlled by both shear and flexure in Ref. [1]. The method proposed in Ref. [1] was based on relationships between required strengths of each failure system for ductility factors and damage degrees of overall system derived from the view-point of ductility factors. The proposed method was also verified using observed real damage data of low-rise RC buildings caused by past earthquakes. Results indicated that the methodology proposed in Ref. [1] compares well with real damages and is a useful strategy for rapidly identifying low-rise RC buildings having high potential seismic risk. In this study, in order to verify the applicability of the new methodology proposed in Ref. [1] to real RC building systems, seismic capacities of existing eleven low-rise RC buildings in Korea are evaluated based on the new method.

• The Journal of Bigdata
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• v.6 no.1
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• pp.133-144
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• 2021

This paper derives the fire risk of buildings in Seoul through the prediction of property damage and the occurrence of fires. This study differs from prior research in that it utilizes variables that include not only a building's characteristics but also its affiliated administrative area as well as the accessibility of nearby fire-fighting facilities. We use Ensemble Voting techniques to merge different machine learning algorithms to predict property damage and fire occurrence, and to extract feature importance to produce fire risk. Fire risk prediction was made on 300 buildings in Seoul utilizing the established model, and it has been derived that with buildings at Level 1 for fire risks, there were a high number of households occupying the building, and the buildings had many factors that could contribute to increasing the size of the fire, including the lack of nearby fire-fighting facilities as well as the far location of the 119 Safety Center. On the other hand, in the case of Level 5 buildings, the number of buildings and businesses is large, but the 119 Safety Center in charge are located closest to the building, which can properly respond to fire.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.75-87
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• 2011

This paper presents a method for region-based building extraction from high resolution satellite images(HRSI) using integrated information of spectral and color invariant features without user intervention such as selecting training data sets. The purpose of this study is also to evaluate the effectiveness of the proposed method by applying to IKONOS and QuickBird images. Firstly, the image is segmented by the MSRG method. The vegetation and shadow regions are automatically detected and masked to facilitate the building extraction. Secondly, the region merging is performed for the masked image, which the integrated information of the spectral and color invariant features is used. Finally, the building regions are extracted using the shape feature for the merged regions. The boundaries of the extracted buildings are simplified using the generalization techniques to improve the completeness of the building extraction. The experimental results showed more than 80% accuracy for two study areas and the visually satisfactory results obtained. In conclusion, the proposed method has shown great potential for the building extraction from HRSI.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.4
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• pp.19-33
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• 2008

Dynamic response measurements from natural excitation were carried out for 25- and 42-story buildings to evaluate their inherent properties, such as natural frequencies, mode shapes and damping ratios. Both are reinforced concrete buildings adopting a core wall, or with shear walls as the major lateral force resisting system, but frames are added in the plan or elevation. In particular, shear walls in a 25-story building are converted to frames from the 4th floor level downwards while maintaining a core wall throughout, resulting in a fairly complex structure. Due to this, along with similar stiffness characteristics in the principal directions, significantly coupled and closely spaced modes of motion are expected in this building, making identification rather difficult. By using various state-of-the-art system identification methods, the modal parameters are extracted, and the results are then compared. Three frequency-domain and four time-domain based operational modal identification methods are considered. Overall, all natural frequencies and damping ratios estimated from the different identification methods showed a greater consistency for both buildings, while mode shapes exhibited some degree of discrepancy, varying from method to method. On the other hand, in comparison with analysis results obtained using the initial finite element(FE) models, test results exhibited a significant difference of about doubled frequencies, at least for the three lower modes in both buildings. To improve the correlation between test and analysis, a few manual schemes of FE model updating based on plausible reasons have been applied, and acceptable results are obtained. The advantages and disadvantages of each identification method used are addressed, and some difficulties that might arise from the updating of FE models, including automatic procedures, for such large structures are carefully discussed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.5
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• pp.503-514
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• 2016

Delineation of accurate object boundaries is crucial to provide reliable spatial information products such as digital topographic maps, building models, and spatial database. In LiDAR(Light Detection and Ranging) data, real boundaries of the buildings exist somewhere between outer-most points on the roofs and the closest points to the buildings among points on the ground. In most cases, areas of the building footprints represented by LiDAR points are smaller than actual size of the buildings because LiDAR points are located inside of the physical boundaries. Therefore, building boundaries determined by points on the roofs do not coincide with the actual footprints. This paper aims to estimate accurate boundaries that are close to the physical boundaries using airborne LiDAR data. The accurate boundaries are determined from the non-gridded original LiDAR data using initial boundaries extracted from the gridded data. The similar method implemented in this paper is also found in demarcation of the maritime boundary between two territories. The proposed method consists of determining initial boundaries with segmented LiDAR data, estimating accurate boundaries, and accuracy evaluation. In addition, extremely low density data was also utilized for verifying robustness of the method. Both simulation and real LiDAR data were used to demonstrate feasibility of the method. The results show that the proposed method is effective even though further refinement and improvement process could be required.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.471-475
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• 2004

LiDAR의 표고점 데이터에서 건물, 수목 등과 같이 주위보다 높은 고도 값을 가지는 대상물을 제거하여 DEM을 생성하기 위한 여러 가지 필터링 기법들이 개발되고 있으며 대표적인 필터링 방법으로는 분산을 이용한 linear prediction 기법, 주변 점들과의 경사관계를 이용한 slope-based 기법, morphology 필터, dual rank 필터 등이 있다. 이러한 기법들은 커널(kernel)의 크기를 대상 지역에 맞도록 사용자가 직접 지정해주어야 하고, 건물의 크기가 다양한 지역에 적용하기 위해서는 가변 크기(variable size)의 커널을 필요로 한다. 본 연구에서는 다양한 크기의 건물이 존재하는 지역에 대하여 커널의 크기를 변화시키지 않고 필터링을 수행하는 새로운 커널 연산 기법을 제안하였다. 또한 기존 필터링 기법에서는 커널에 의해 갱신된 연산값이 다음 연산에 반영되지 않으나 본 연구에서는 갱신된 값이 바로 다음 연산에 반영되도록 하였다. 건물과 수목 등을 제거하기 위하여 주변 화소와의 높이 차를 이용하였으며 대상물이 제거된 부분은 주변 화소를 이용하여 보간하였다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.221-224
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• 2009

최근 사회기반시설을 대상으로 900 MHz - 2.45 GHz 대역의 무선 센서 네트워크 시스템을 이용한 구조반응 모니터링 연구가 수행되고 있다. 건물의 경우 수직, 수평으로 구조 부재, 칸막이 벽, 외장재 등에 의해서 공간이 차단되어 있고, 전파 간섭의 영향이 상대적으로 크기 때문에 900 MHz - 2.4 GHz 대역의 무선 네트워크 시스템은 그 한계가 있다. 본 논문에서는 이러한 문제점을 고려하여 장애물에 대한 회절성이 뛰어나고 전파의 간섭이 상대적으로 작은 저주파 대역의 무선 라디오 주파수를 도입한다. 이로부터 특히 지진 또는 바람의 영향 등의 외부 하중에 의하여 대규모 인명 손실을 초래할 수 있는 중요도가 매우 높은 대형 건물을 대상으로 실제 적용이 가능한 무선 센서 네트워크를 구성해 보았다.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.535-536
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• 2015

장기적인 에너지 수급 불안정과 기후변화에 대응하여 지속 가능한 에너지 공급체계인 신재생 에너지의 이용은 1차 에너지 소비 절감을 위한 중요한 요소로 인식되어가고 있다. 이에 국내 총 에너지 소비량의 약 25%를 차지하는 건물 분야에서도 신재생 에너지원의 적용을 확대함에 따라 생산과 소비 최적화를 통한 효율적인 통합 운용 및 제어가 가능한 건물에너지관리시스템의 필요성이 부각되고 있다. 본 논문에서는 신재생 분산자원을 도입하여 건물에너지관리시스템을 구축 및 실증하고 그에 따른 에너지 절감효과를 분석하였다.

• Journal of the Earthquake Engineering Society of Korea
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• v.4 no.2
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• pp.13-24
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• 2000

최근 국내에서 많이 건설되어지고 있는 주상복합 건축물은 하부의 골조형식과 상부의 벽식 구조가 결합된 구조형식을 가지고 있다 따라서 지진 발생시 동일한 형식을 가진 건축물과는 상이하고 복잡한 반응을 보이게 된다 이러한 건축물의 등가정적 해석시 국내 규준에서는 기타구조물로 분류하여 3.5 의 반응수정계수를 적용하고 있다 그러나 이 계수는 검증되어지지 않는 상태로 사용되어지고 있으므로 상당한 위험성을 내포하고 있다 본 연구에서는 단순화한 주상복합 건물의 해석 및 실제의 건물에 대한 3차원 비선형 해석을 통하여 반응수정계수를 유도하였다 유도된 반응수정계수는 ATC 기준과 우리나라 기준의 차이를 고려한 보정을 수행하였다.