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
Hong, Sin-Pyo (Global Core Research Center for Ships and Offshore Plants, Pusan National University) Cho, Jin-Rae (Department of Naval Architecture and Ocean Engineering, Hongik University)
저널정보
테크노프레스 Structural engineering and mechanics : An international journal Structural engineering and mechanics : An international journal 제61권 제6호
발행연도
2017.1
수록면
785 - 794 (10page)

이용수

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

초록· 키워드

오류제보하기
This paper is concerned with the comparative numerical and experimental study on the natural behavior and the motion responses of a 1/75 moored scale model of a 2.5 MW spar-type floating offshore wind turbine subject to 1-D regular wave. Heave, pitch and surge motions and the mooring tensions are investigated and compared by numerical and experimental methods. The upper part of wind turbine which is composed of three rotor blades, hub and nacelle is modeled as a lumped mass and three mooring lines are pre-tensioned by means of linear springs. The numerical simulations are carried out by a coupled FEM-cable dynamics code, while the experiments are performed in a wave tank equipped with the specially-designed vision and data acquisition system. Using the both methods, the natural behavior and the motion responses in RAOs are compared and parametrically investigated to the fairlead position, the spring constant and the location of mass center of platform. It is confirmed, from the comparison, that both methods show a good agreement for all the test cases. And, it is observed that the mooring tension is influenced by all three parameters but the platform motion is dominated by the location of mass center. In addition, from the sensitivity analysis of RAOs, the coupling characteristic of platform motions and the sensitivities to the mooring parameters are investigated.

목차

등록된 정보가 없습니다.

참고문헌 (0)

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