Earthquake Damage Assessment of Buildings in Urban Area using Disaster Management Platform

재난관리플랫폼을 이용한 도심지 건물군의 지진피해평가

  • Jang, Sung-Hyun (Department of Civil Engineering, Keimyung University) ;
  • Kwon, Dong-Hee (Department of Civil Engineering, Keimyung University) ;
  • Hwang, Chan-Gyu (Dept. of Convergence Industry, Seoul Venture University) ;
  • Choi, Soo-Young (Geospatial Information Technology Institute, GEO C&I) ;
  • Chey, Min-Ho (Faculty of Architecture & Civil Engineering, Keimyung University)
  • 장성현 (계명대학교 토목공학과) ;
  • 권동희 (계명대학교 토목공학과) ;
  • 황찬규 (서울벤처대학원대학교 융합산업학과) ;
  • 최수영 (GEO C&I 공간정보기술연구소) ;
  • 최민호 (계명대학교 건축토목공학부)
  • Received : 2019.05.04
  • Accepted : 2019.06.20
  • Published : 2019.06.28


Because of its physical characteristics, earthquake has a great impact on a wide area in a short time, so it needs a resilience based seismic countermeasures to restore the community function. For this reason, in this study, the seismic damages of urban buildings were assessed stochastically by virtual earthquakes using public data information and disaster management program(Ergo-EQ). A geographical map reflecting geological characteristics of the target area was created with the buildings and topographic data in Dalseo-gu, Daegu City. In addition, an integrated database including building characteristics was modified to be linked with the Ergo-EQ program. The seismic damages for the buildings were evaluated through the exceedance probability of four different damage levels. From the damage results, it can be identified not only the seismic damage of each building, but also the major factors affecting earthquake damage.


Earthquake Disaster;Ergo-EQ;School;Government Office;Damage

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Fig. 1. 3D visualized seismic damage using Ergo-EQ

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Fig. 2. Data flow of distributed & parallel framework(Ergo-EQ)

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Fig. 3. Location of the epicenter adopted

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Fig. 4. PGA distribution of Dalseo-gu region(Scenario 1)

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Fig. 5. PGA distribution of Dalseo-gu region(Scenario 2)

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Fig. 6. Flowchart of damage assessment (Ergo-EQ)

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Fig. 7. Computing probabilities of damage states

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Fig. 8. Damage distribution of the buildings inDalseo-gu Region (scenario 1)

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Fig. 9. Mean damage VS. year of built (scenario 1)

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Fig. 10. Mean damage VS. year of built (scenario 2)

Table 1. Number of earthquakes per year (Earthquake annals of the Korea meteorological administration, 2017)

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Table 2. Fault information

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Table 3. Scenario earthquakes used

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Table 4. Building information (Ergo-EQ)

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Table 5. Description of damage states

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Table 6. Probabilistic model for structural damage ratio

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Table 7. Mean damage VS. built year and story

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Table 8. Mean damage VS. built year and total floor area

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Supported by : KISTI


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