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
질문

논문 기본 정보

자료유형
학술저널
저자정보
Byung-Kon Kim (DSK Engineering)
저널정보
한국유체기계학회 한국유체기계학회 논문집 한국유체기계학회 논문집 제18권 제6호
발행연도
2015.12
수록면
45 - 56 (12page)

이용수

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

초록· 키워드

오류제보하기
This paper aims to develop a submerged propeller turbine for micro hydropower plant which allows to sustain high values of efficiency in a broad range of hydrological conditions (H=2~6 m, Q=0.15~0.39 m³/s ). The two aspects to be considered in this development are mechanical simplicity and high-efficiency operation. Unlike conventional turbines that have spiral casing and gear box, this is directing driving and no spiral casing. A 10 kW class turbine which has the most high potential of the power generation has been developed. The most important element in the design of turbine is the runner blade. The initial blade is designed using inverse design method and then the runner geometry is modified by classical hydraulic method. The design process is carried out in two steps. First, the blade shape is fix and then other components of submerged propeller turbine are designed. Computational fluid dynamics analyses based on the Navier-Stokes equations have been used to obtain overall performance data for the blade and the full turbine, respectively. The results generated by performance parameters(head, guide vane opening angle and rotational speed) variations are theoretically analysed. The evaluation criteria for the blade and the turbine performances are the pressure distribution and flow"s behavior on the runner blades and turbine. The results of simulation reveals an efficiency of 91.5% and power generation of 10.5kW at the best efficiency point at the head of 4m and a discharge of 0.3 m³/s.

목차

ABSTRACT
1. Introduction
2. Preliminary design
3. Geometric design of propeller turbine
4. Numerical analysis
5. Results and Discussions
6. Conclusion
References

참고문헌 (9)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

이 논문과 함께 이용한 논문

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2016-554-002329011