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 제5호
발행연도
2007.1
수록면
591 - 602 (12page)

이용수

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

초록· 키워드

오류제보하기
The results of Reactivity-Initiated Accidents (RIA) experiments have been analysed and the main variables affecting the fuel failure propensity identified. Fuel burn-up aggravates the mechanical loading of the cladding, while corrosion, or better the hydrogen absorbed in the cladding as a consequence of corrosion, may under some conditions make the cladding brittle and more susceptible to failure. Experiments point out that corrosion impairs the fuel resistance for RIA transient occurring at cold conditions, whereas there is no evidence of important embrittlement effects at hot conditions, unless the cladding was degraded by oxide spalling. A fuel failure threshold correlation has been derived and compared with experimental data relevant for BWR and PWR fuel. The correlation can be applied to both cold and hot RIA transients, account taken for the lower ductility at cold conditions and for the different initial enthalpy. It can also be used for non-zero power transients, provided that a term accounting for the start-up power is incorporated. The proposed threshold is easy to use and reproduces the results obtained in the CABRI and NSRR tests in a rather satisfactory manner. The behaviour of advanced PWR alloys and of MOX fuel is discussed in light of the correlation predictions. Finally, a probabilistic approach has been developed in order to account for the small scatter of the failure predictions. This approach completes the RIA failure assessment in that after determining a best estimate failure threshold, a failure probability is inferred based on the spreading of data around the calculated best estimate value.

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