논문 상세보기

공동주택 PC외피-UHPC리브 시스템의 유한요소해석 모델 제작과 검증 KCI 등재

Development and Verification of FEM Analysis Model for Precast Claddings-UHPC Ribs in Apartment Buildings

  • 언어KOR
  • URLhttps://db.koreascholar.com/Article/Detail/437377
구독 기관 인증 시 무료 이용이 가능합니다. 4,000원
한국지진공학회 (Earthquake Engineering Society of Korea)
초록

The precast concrete (PC) method allows for simple assembly and disassembly of structures; however, ensuring airtight connections is crucial to prevent energy loss and maintain optimal building performance. This study focuses on the analytical investigation of the shear capacity of precast ultra-high-performance concrete (UHPC) ribs combined with standard concrete PC cladding walls. Five specimens were tested under static loading conditions to evaluate their structural performance and the thermal behavior of the UHPC rib shear keys. Test results indicated that the specimens exhibited remarkable structural performance, with shear capacity approximately three times greater than that of standard concrete. Numerical models were subsequently developed to predict the shear capacity of the shear keys under various loading conditions. A comparison between the experimental results and finite element (FE) models showed a maximum strength difference of less than 10% and a rib displacement error of up to 1.76 mm. These findings demonstrated the efficiency of the FE model for the simulation of the behavior of structures.

목차
A B S T R A C T
1. 서 론
2. 본 론
    2.1 PC외피-UHPC접합리브 실험체 계획
    2.2 PC외피-UHPC접합리브 실험계획 및 결과
    2.3 해석 모델링 절차 및 물성치 선정
    2.4 PC외피-UHPC리브 구성요소 유형 결정
3. 해석모델의 검증
    3.1 SK0-EC100 해석결과
    3.2 SK2-EC30 해석결과
    3.3 SK1-EC100 해석결과
    3.4 SK1-EC125 해석결과
    3.5 RC-rib-wall-EC100 해석결과
    3.6 소결
4. 결 론
감사의 글
REFERENCES
저자
  • 진수민(세종대학교 건축공학과 딥러닝건축연구소 석사) | Jin Su-Min (Master, Deep Learning Architecture Research Center, Dept. of Architectural Engineering, Sejong University)
  • 조혜림(세종대학교 건축공학과 딥러닝건축연구소 석사과정) | Jo Hyerim (Master’s Course, Deep Learning Architecture Research Center, Dept of Architectural Engineering, Sejong University)
  • 안효서(세종대학교 건축공학과 딥러닝건축연구소 석사과정) | An Hyo-Seo (Master’s Course, Deep Learning Architecture Research Center, Dept of Architectural Engineering, Sejong University)
  • 나금옥(동서PCC(주) 전무) | Na Geum-Ok (Executive Director, Dong Su PCC Inc.)
  • 유영종((주)정양SG 연구소 소장) | Yoo Young-Jong (Laboratory Director, Jeong Yang SG Inc.)
  • 김형근((주)더픽알앤디 대표이사) | Kim Hyung-Geun (Chief Executive Officer, The Pick R&D Inc.)
  • 이기학(세종대학교 건축공학과 딥러닝건축연구소 교수) | Lee Kihak (Professor, Deep Learning Architecture Research Center, Dept of Architectural Engineering, Sejong University) Corresponding author