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
Memduh Karalar (Bülent Ecevit University) Murat Dicleli (METU)
저널정보
국제구조공학회 Steel and Composite Structures, An International Journal Steel and Composite Structures, An International Journal Vol.34 No.1
발행연도
2020.1
수록면
35 - 51 (17page)

이용수

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

초록· 키워드

오류제보하기
Integral abutment bridges (IABs) are those bridges without expansion joints. A single row of steel H-piles (SHPs) is commonly used at the thin and stub abutments of IABs to form a flexible support system at the bridge ends to accommodate thermal-induced displacement of the bridge. Consequently, as the IAB expands and contracts due to temperature variations, the SHPs supporting the abutments are subjected to cyclic lateral (longitudinal) displacements, which may eventually lead to low-cycle fatigue (LCF) failure of the piles. In this paper, the potential of using finite element (FE) modeling techniques to estimate the LCF life of SHPs commonly used in IABs is investigated. For this purpose, first, experimental tests are conducted on several SHP specimens to determine their LCF life under thermal-induced cyclic flexural strains. In the experimental tests, the specimens are subjected to longitudinal displacements (or flexural strain cycles) with various amplitudes in the absence and presence of a typical axial load. Next, nonlinear FE models of the tested SHP specimens are developed using the computer program ANSYS to investigate the possibility of using such numerical models to predict the LCF life of SHPs commonly used in IABs. The comparison of FE analysis results with the experimental test results revealed that the FE analysis results are in close agreement with the experimental test results. Thus, FE modeling techniques similar to that used in this research study may be used to predict the LCF life of SHP commonly used in IABs.

목차

등록된 정보가 없습니다.

참고문헌 (31)

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