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
Nader Fanaie (K. N. Toosi University of Technology) Morteza N. Monfared (K. N. Toosi University of Technology)
저널정보
국제구조공학회 Structural Engineering and Mechanics, An Int'l Journal Structural Engineering and Mechanics, An Int'l Journal Vol.60 No.3
발행연도
2016.1
수록면
507 - 527 (21page)

이용수

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

초록· 키워드

오류제보하기
The use of shape memory alloys (SMAs) has been seriously considered in seismic engineering due to their capabilities, such as the ability to tolerate cyclic deformations and dissipate energy. Five 3-D extended end-plate connection models have been created, including one conventional connection and four connections with Nitinol bolts of four different prestress forces. Their cyclic behaviors have been investigated using the finite element method software ANSYS. Subsequently, the moment-rotation responses of the connections have been derived by subjecting them to cyclic loading based on SAC protocol. The results obtained in this research indicate that the conventional connections show residual deformations despite their high ductility and very good energy dissipation; therefore, they cannot be repaired after loading. However, while having good energy dissipation and high ductility, the connections equipped with Nitinol bolts have good recentering capability. Moreover, a connection with the mentioned specifications has been modeled, except that only the external bolts replaced with SMA bolts and assessed for seismic loading. The suggested connection shows high ductility, medium energy dissipation and very good recentering. The main objective of this research is to concentrate the deformations caused by cyclic loading on the connection in order to form super-elastic hinge in the connection by the deformations of the shape memory alloy bolts.

목차

등록된 정보가 없습니다.

참고문헌 (30)

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