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기계학습 기반 노후 철근콘크리트 건축물의 축력허용범위 산정 방법
- 황희진;
- 오근영;
- 강재도;
- 신지욱
SCOPUS
0초록
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.
키워드
- 제목
- 기계학습 기반 노후 철근콘크리트 건축물의 축력허용범위 산정 방법
- 제목 (타언어)
- ML-based Allowable Axial Loading Estimation of Existing RC Building Structures
- 저자
- 황희진; 오근영; 강재도; 신지욱
- 발행일
- 2024-09
- 저널명
- 한국지진공학회논문집
- 권
- 28
- 호
- 5
- 페이지
- 257 ~ 266