인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 저자정보
초록·키워드
Due to higher stiffness to weight, higher corrosion resistance, higher strength to weight ratios and good durability, concrete composite structures provide many advantages as compared with conventional materials. Thus, they have wide applications in the field of concrete construction. This research focuses on the structural behavior of steel-tube CFRP confined concrete (STCCC) columns under axial concentric loading. A nonlinear finite element analysis (NLFEA) model of STCCC columns was simulated using ABAQUS which was then, calibrated for different material and geometric models of concrete, steel tube and CFRP material using the experimental results from the literature. The comparative study of the NLFEA predictions and the experimental results indicated that the proposed constitutive NLFEA model can accurately predict the structural performance of STCCC columns. After the calibration of NLFEA model, an extensive parametric study was performed to examine the effects of different critical parameters of composite columns such as; (i) unconfined concrete strength, (ii) number of CFRP layers, (iii) thickness of steel tube and (iv) concrete core diameter, on the axial load capacity. Furthermore, a large database of axial strength of 700 confined concrete compression members was developed from the previous researches to give an analytical model that predicts the ultimate axial strength of composite columns accurately. The comparison of the predictions of the proposed analytical model was done with the predictions of 216 NLFEA models from the parametric study. A close agreement was represented by the predictions of the proposed constitutive NLFEA model and the analytical model.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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