• Title/Summary/Keyword: 건축물 정보모델

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Development of Robust Semantic Segmentation Modeling on Various Wall Cracks (다양한 외벽에 강인한 균열 구획화 모델 개발)

  • Lee, Soo Min;Kim, Gyeong-Yeong;Kim, Dong-Ju
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.07a
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    • pp.49-52
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    • 2022
  • 건물 외벽에 발생하는 균열은 시설물 구조 안전에 영향을 미치며 그 크기에 따라 위험도가 달라진다. 이에 따라 전문검사관의 현장 점검을 통해 발생 균열 두께를 정밀하게 측정할 필요가 있고 최근에는 이러한 현장 안전점검에 인공지능을 도입하려는 추세다. 그러나 기존의 균열 데이터셋은 주로 콘크리트에만 한정되어 다양한 외벽에 강인한 모델을 구축하기 어렵고 균열 두께를 측정하기 위해 정확한 마스크(Mask) 정보가 필요하나 이를 만족하는 데이터셋이 부재하다. 본 논문에서는 다양한 외벽에 강인한 균열 구획화 모델을 목적으로 2,744장의 이미지를 촬영하고 매직 완드 기법으로 라벨링을 진행해 데이터셋을 구축 후, 이를 바탕으로 딥러닝 기반 균열 구획화 모델을 개발했다. UNet-ResNet50을 최종모델로 선정 및 개발 결과, 테스트 데이터셋에 대해 81.22%의 class IoU 성능을 보였다. 본 연구의 기술을 바탕으로 균열 두께를 측정하여 건축물 안전점검에 활용될 수 있기를 기대한다.

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A Study on the Damage Analysis of Chemical Substances Explosion Accident Using GIS (GIS를 활용한 화학물질 폭발사고 피해분석 연구)

  • Ham, Tae-Yuun;Kwon, Gi-Min;Song, Moon-Soo;Yun, Hong-Sik
    • Proceedings of the Korean Society of Disaster Information Conference
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    • 2022.10a
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    • pp.99-100
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    • 2022
  • 화학산업이 발전함에 따라 잠재적인 화학물질 폭발사고 위험 또한 증가하고 있다. 순식간에 치명적인 인명, 재산피해를 남기는 폭발에 대한 영향을 예측, 분석하기 위해 다양한 해석모델이 활용되고 있지만, 폭발의 물리적 특성상 다양한 형태의 건물이 밀집된 지역에 대해서는 해석모델 사용만으로 높은 정확도의 분석을 진행하기에는 어려움이 있다. 따라서 본 연구는 GIS 공간정보와 3D 폭발 시뮬레이션의 약결합 방식을 적용하였다. 실제 연구지역과 동일한 환경을 구현하여 시뮬레이션을 구동하였고 이에 따른 폭발 규모와 폭발에 노출된 대상별 가해지는 압력 값을 도출하였다. TNT를 기준으로 위험물 저장 및 취급시설에 대한 최저 기준인 지정수량 200kg을 적용하였음에도 최대 2,960kPa의 압력이 발생하는 것으로 확인되었다. 본 연구로 도출된 결과에 건축물의 용도와 중요도를 적용한다면 토지이용계획 및 공간활용에 반영할 수 있으며, 안전관리자로 하여금 리스크 평가, BC분석, 안전관리계획 수립 등에 활용 가능하다고 사료된다.

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Realistic Enhancement of 3D Expressions for Building Expressions with Hologram (건축물 홀로그램 표현에서 3D 실체감 표현 향상방안)

  • Shin, Seong-Yoon;Lee, Hyun-Chang
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.9
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    • pp.1104-1109
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    • 2019
  • Business utilization of holograms is widely used as a similar hologram. The use of holograms has been proposed in many cases. In this paper, we present an outline of similar holograms using up to 3 or 4 facets, and express the similar holograms using the results produced by 3D modeling for a building from dealing with the representation of buildings from hololens to pseudo-hologram by using 3D modeling results. In addition, to reflect the real image of the disadvantage of modeling, we propose a method to enhance the 3D expression of the object by reflecting the actual building surface on the 3D model through photographing. Virtual building seen by the human eye can be virtually shown in space through a hologram among various methods shown in a virtual space such as AR / VR / MR. Through this study, it will be possible to express holograms of various materials such as buildings or cultural properties with enhanced realism.

Development of an Economic Material Selection Model for G-SEED Certification (녹색건축(G-SEED) 인증을 위한 경제적 자재선정 모델 개발)

  • Jeon, Byung-Ju;Kim, Byung-Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.40 no.6
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    • pp.613-622
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    • 2020
  • The South Korean government plans for a 37 % reduction in CO2 emissions against business as usual by 2030. Subsequently, the Ministry of Land, Infrastructure and Transport declared a 26.9 % reduction target in greenhouse gas emissions from buildings by 2020 and established the Green Standard for Energy and Environmental Design (G-SEED) to help improve the environmental performance of buildings. Construction companies often work with consulting firms to prepare for G-SEED certification. In the process, owing to inefficient data sharing and work connections, it is difficult to achieve economic efficiency and obtain certification. The objective of this study was to develop an economic model to assist contractors in achieving the required G-SEED scores for materials and resources. To do this, we automated the process for material comparison and selection on the basis of an analysis of actual consulting data, and developed a model that selects material alternatives that can meet the required scores at a minimum cost. Information on materials is input by applying a genetic algorithm to the optimization of alternatives. When the model was applied to actual data, the construction cost could be lowered by 79.3 % compared with existing methods. The economical material selection model is expected to not only reduce construction costs for owners desiring G-SEED certification but also shorten the project design time.

A STEP-based Integrated Structural Information System for Steel Framed Building Structures (STEP을 이용한 철골건물의 구조설계정보 통합시스템의 구축에 관한 연구)

  • 박순규;임경일;김이두
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.13 no.1
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    • pp.139-146
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    • 2000
  • This paper presents a prototype for structural analysis and design system by use of the STEP concepts for the representation and exchange of information on framed steel structures, and also integrates the product model of steel structures of AP 230, geometric and topological information of Part 42, and detailed Finite Element Analysis information of Part 104 into an unified system. Thus, the STEP-based system makes engineering information more clearable and exchangeable between computer applications than any other conventional methods. This system may be further extended to incorporate other computer applications for detailed engineering and manufacturing information on steel structures.

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Electrical fire prediction model study using machine learning (기계학습을 통한 전기화재 예측모델 연구)

  • Ko, Kyeong-Seok;Hwang, Dong-Hyun;Park, Sang-June;Moon, Ga-Gyeong
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.11 no.6
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    • pp.703-710
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    • 2018
  • Although various efforts have been made every year to reduce electric fire accidents such as accident analysis and inspection for electric fire accidents, there is no effective countermeasure due to lack of effective decision support system and existing cumulative data utilization method. The purpose of this study is to develop an algorithm for predicting electric fire based on data such as electric safety inspection data, electric fire accident information, building information, and weather information. Through the pre-processing of collected data for each institution such as Korea Electrical Safety Corporation, Meteorological Administration, Ministry of Land, Infrastructure, and Transport, Fire Defense Headquarters, convergence, analysis, modeling, and verification process, we derive the factors influencing electric fire and develop prediction models. The results showed insulation resistance value, humidity, wind speed, building deterioration(aging), floor space ratio, building coverage ratio and building use. The accuracy of prediction model using random forest algorithm was 74.7%.

A Study on the Estimating Process for Life Cycle Cost based on BIM (BIM기반 Life Cycle Cost 산정을 위한 프로세스에 관한 연구)

  • Lee, Hyun-Joo;Moon, Joon-Ho;Park, Gyu-Tae;Kim, Tae-Hee;Kim, Kwang-Hee
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2011.05a
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    • pp.149-151
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    • 2011
  • Recently, Architectural Design based on Building Information Modeling(BIM) is popular, construction management based on BIM is necessary. such as Quantity take off, scheduling, and Life Cycle Cost Estimating etc. Therefore, in the study, LCC Estimating using BIM Data, which is extracted from architectural designing process is proposed.

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Estimation Method of the Amount of Demolition Waste through Automated Calculation of Volumetric Spaces using Drones (드론 활용 체적산출 자동화를 통한 해체 폐기물량 예측기법에 관한 연구)

  • Ryu, Jung-Rim;Kim, Hye-Ri;Park, Won-Jun
    • Journal of the Korea Institute of Building Construction
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    • v.22 no.6
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    • pp.681-688
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    • 2022
  • In this study, the process of drone photography, automatic volume calculation, total floor area conversion, and waste calculation was constructed as a QGIS plug-in to predict the demolition waste (DW) generated in an aged area where drawing information or building information is uncertain. Through a case study, the high consistency between the automatically calculated volume using the drone and the BIM volume based on the field measurement was confirmed. Field application was carried out for the planned demolition work site, and the consistency between the drone-based volume and the actual measurement-BIM-based volume was reconfirmed. The waste generation unit was applied and the amount of DW was calculated by setting the floor height and building type, and the entire process was completed within 6 hours. Although the difference between building information and building objects through drones occurred according to the setting of temporary structures, loads, and floor heights, it was found that the actual amount of DW was generated more than the initial estimate. It is expected that measures to improve the accuracy of volume and floor area conversion will be required through case studies in the future.

Seismic Vulnerability Assessment and Mapping for 9.12 Gyeongju Earthquake Based on Machine Learning (기계학습을 이용한 지진 취약성 평가 및 매핑: 9.12 경주지진을 대상으로)

  • Han, Jihye;Kim, Jinsoo
    • Korean Journal of Remote Sensing
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    • v.36 no.6_1
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    • pp.1367-1377
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    • 2020
  • The purpose of this study is to assess the seismic vulnerability of buildings in Gyeongju city starting with the earthquake that occurred in the city on September 12, 2016, and produce a seismic vulnerability map. 11 influence factors related to geotechnical, physical, and structural indicators were selected to assess the seismic vulnerability, and these were applied as independent variables. For a dependent variable, location data of the buildings that were actually damaged in the 9.12 Gyeongju Earthquake was used. The assessment model was constructed based on random forest (RF) as a mechanic study method and support vector machine (SVM), and the training and test dataset were randomly selected with a ratio of 70:30. For accuracy verification, the receiver operating characteristic (ROC) curve was used to select an optimum model, and the accuracy of each model appeared to be 1.000 for RF and 0.998 for SVM, respectively. In addition, the prediction accuracy was shown as 0.947 and 0.926 for RF and SVM, respectively. The prediction values of the entire buildings in Gyeongju were derived on the basis of the RF model, and these were graded and used to produce the seismic vulnerability map. As a result of reviewing the distribution of building classes as an administrative unit, Hwangnam, Wolseong, Seondo, and Naenam turned out to be highly vulnerable regions, and Yangbuk, Gangdong, Yangnam, and Gampo turned out to be relatively safer regions.

The Simulation of Periodic Disturbance Controller (주기적 외란 제어기 시뮬레이션)

  • Kim, Jun-su;Kim, Gi-ryang;Kim, Hyun-soo;Jeong, Tae-il;Kim, Gwan-hyung;Lee, Hyung-ki
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.1058-1059
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    • 2015
  • 최근 건축 구조물 설계에 있어서 외부 또는 내부로부터 발생될 수 있는 미지의 진동에 대하여 대책을 수립하여 구조물을 설계하고 있다. 뿐만 아니라 기타 제조업 분야에 있어서 정밀할 가공이 필요한 특수한 기계 가공기에 있어서 내부 또는 외부에서 발생될 수 있는 진동을 감안하여 시스템을 구성하고 있다. 이러한 구조물 및 기계시스템에 대하여 진동을 억제할 수 있는 진동 억제 알고리즘에 관해서는 많이 연구되고 있다. 본 논문에서는 구조물 및 기계시스템에서 발생될 수 있는 미지의 외란을 제거하기 위하여 내부모델제어(IMC)를 기반으로 수정된 적응 알고리즘을 매트랩 시뮬링크(matlab simulink)를 통하여 제어성능을 제시하고자 한다.

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