메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
Gen Li (The University of Sydney) Chao Hou (Southern University of Science and Technology) Lin-Hai Han (Tsinghua University) Luming Shen (The University of Sydney)
저널정보
국제구조공학회 Steel and Composite Structures, An International Journal Steel and Composite Structures, An International Journal Vol.35 No.1
발행연도
2020.1
수록면
93 - 109 (17page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
Developed from conventional concrete filled steel tubular (CFST) members, concrete-encased CFST has attracted growing attention in building and bridge practices. In actual construction, the inner CFST is erected prior to the casting of the outer reinforced concrete part to support the construction preload, after which the whole composite member is under sustained service load. The complex loading sequence leads to highly nonlinear material interaction and consequently complicated structural performance. This paper studies the full-range behaviour of concrete-encased CFST columns with initial preload on inner CFST followed by sustained service load over the whole composite section. Validated against the reported data obtained from specifically designed tests, a finite element analysis model is developed to investigate the detailed structural behaviour in terms of ultimate strength, load distribution, material interaction and strain development. Parametric analysis is then carried out to evaluate the impact of significant factors on the structural behaviour of the composite columns. Finally, a simplified design method for estimating the sectional capacity of concrete-encased CFST is proposed, with the combined influences of construction preload and sustained service load being taken into account. The feasibility of the developed method is validated against both the test data and the simulation results.

목차

등록된 정보가 없습니다.

참고문헌 (34)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0