Journal of the Earthquake Engineering Society of Korea (한국지진공학회논문집)

Earthquake Engineering Society of Korea (한국지진공학회)
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ML-based Allowable Axial Loading Estimation of Existing RC Building Structures

기계학습 기반 노후 철근콘크리트 건축물의 축력허용범위 산정 방법

  • Hwang, Heejin (Department of Architectural Engineering, Gyeongsang National University) ;
  • Oh, Keunyeong (Department of Building Research, Korea Institute of Civil Engineering and Building Technology) ;
  • Kang, Jaedo (Division of Safety and Infrastructure Research, The Seoul Institute) ;
  • Shin, Jiuk (Department of Architectural Engineering, Gyeongsang National University)
  • 황희진 (경상국립대학교 건축공학과) ;
  • 오근영 (한국건설기술연구원 건축연구본부) ;
  • 강재도 (서울연구원 안전인프라연구실) ;
  • 신지욱 (경상국립대학교 건축공학과)
  • Received : 2024.02.27
  • Accepted : 2024.07.19
  • Published : 2024.09.01
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Abstract

Due to seismically deficient details, existing reinforced concrete structures have low lateral resistance capacities. Since these building structures suffer an increase in axial loads to the main structural element due to the green retrofit (e.g., energy equipment/device, roof garden) for CO2 reduction and vertical extension, building capacities are reduced. This paper proposes a machine-learning-based methodology for allowable ranges of axial loading ratio to reinforced concrete columns using simple structural details. The methodology consists of a two-step procedure: (1) a machine-learning-based failure detection model and (2) column damage limits proposed by previous researchers. To demonstrate this proposed method, the existing building structure built in the 1990s was selected, and the allowable range for the target structure was computed for exterior and interior columns.

Keywords

Acknowledgement

이 성과는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원(RS-2024-00348713) 및 과학기술정보통신부의 재원으로 수행된 한국건설기술연구원 주요사업의 결과물임(No.20240190-001).

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