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
저널정보
한국원자력학회 Nuclear Engineering and Technology Nuclear Engineering and Technology 제39권 제4호
발행연도
2007.1
수록면
327 - 336 (10page)

이용수

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

초록· 키워드

오류제보하기
The influence of density differences on the mixing of the primary loop inventory and the Emergency Core Cooling (ECC) water in the downcomer of a Pressurised Water Reactor (PWR) was analyzed at the ROssendorf COolant Mixing (ROCOM) test facility. ROCOM is a 1:5 scaled model of a German PWR, and has been designed for coolant mixing studies. It is equipped with advanced instrumentation, which delivers high-resolution information for temperature or boron concentration fields. This paper presents a ROCOM experiment in which water with higher density was injected into a cold leg of the reactor model. Wire-mesh sensors measuring the tracer concentration were installed in the cold leg and upper and lower part of the downcomer. The experiment was run with 5 % of the design flow rate in one loop and 10 % density difference between the ECC and loop water especially for the validation of the Computational Fluid Dynamics (CFD) software ANSYS CFX. A mesh with two million control volumes was used for the calculations. The effects of turbulence on the mean flow were modelled with a Reynolds stress turbulence model. The results of the experiment and of the numerical calculations show that mixing is dominated by buoyancy effects: At higher mass flow rates (close to nominal conditions) the injected slug propagates in the circumferential direction around the core barrel. Buoyancy effects reduce this circumferential propagation. Therefore, density effects play an important role during natural convection with ECC injection in PWRs. ANSYS CFX was able to predict the observed flow patterns and mixing phenomena quite well.

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