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
Norberto Dominguez (Seccion de Estudios de Posgrado e Investigación (SEPI) ESIA UZ Instituto Politecnico Nacional of Me) Jesús Pérez-Mota (Seccion de Estudios de Posgrado e Investigación (SEPI) ESIA UZ Instituto Politecnico Nacional of Me)
저널정보
한국계산역학회 Computers and Concrete, An International Journal Computers and Concrete, An International Journal Vol.21 No.3
발행연도
2018.1
수록면
299 - 310 (12page)

이용수

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

초록· 키워드

오류제보하기
When reinforced concrete structures are subjected to strong seismic forces, their beam-column connections are very susceptible to be damaged during the earthquake event. Consequently, structural designers try to fit an important quantity of steel reinforcement inside the connection, complicating its construction without a clear justification for this. The aim of this work is to evaluate –and demonstrate- numerically how the quantity and the array of the internal steel reinforcement influences on the nonlinear response of the RC beam-column connection. For this, two specimens (extracted from an experimental test of 12 RC beam-column connections reported in literature) were modeled in the Finite Element code FEAP considering different stirrup’s arrays. The nonlinear response of the RC beam-column connection is evaluated taking into account the nonlinear thermodynamic behavior of each component: a damage model is used for concrete; a classical plasticity model is adopted for steel reinforcement; the steel-concrete bonding is considered perfect without degradation. At the end, the experimental responses obtained in the tests are compared to the numerical results, as well as the distribution of shear stresses and damage inside the concrete core of the beam-column connection, which are analyzed for a low and high state of confinement.

목차

등록된 정보가 없습니다.

참고문헌 (35)

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