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Assessment of the MELCOR 1.8.6 condensation heat transfer model under the presence of noncondensable gases

중대사고 해석코드 MELCOR 1.8.6의 비응축성기체 존재 시 응축열전달 모델 평가

  • Yoo, Ji Min (School of Mechanical Engineering, Pusan National University (PNU)) ;
  • Lee, Dong Hun (School of Mechanical Engineering, Pusan National University (PNU)) ;
  • Yun, Byong Jo (School of Mechanical Engineering, Pusan National University (PNU)) ;
  • Jeong, Jae Jun (School of Mechanical Engineering, Pusan National University (PNU))
  • Received : 2016.04.07
  • Accepted : 2016.06.16
  • Published : 2016.06.30

Abstract

A condensation heat transfer model is very important for the safety analysis of nuclear power plants. Especially, condensation under the presence of noncondensable gases (NCGs) is an important issue in nuclear safety because the presence of even a small quantity of NCGs in the vapor largely reduces the condensation rate. In this study, the condensation heat transfer model of the severe accident analysis code MELCOR 1.8.6 has been assessed using a set of condensation experiments performed under the thermal-hydraulic conditions similar to those inside a containment during design-basis accidents or severe accidents. Experiment conditions are categorized into 4 types according to the shape of the condensation surface: vertical flat plates, outer surface of vertical pipes, inner surface of vertical pipes, the inner surface of horizontal pipes. The results of the calculations show that the MELCOR code generally under-predicts the condensation heat transfer except the condensation on inner surface of vertical pipes.

원전의 설계기준사고 및 중대사고 해석에서 응축열전달 모델은 매우 중요하며, 특히 피동냉각계통의 개발이 활발히 진행됨에 따라 그 중요성이 더욱 부각되었다. 그런데, 원자로건물 내부에서와 같이 비응축성기체가 존재하는 경우 응축열전달은 현저히 감소하므로 원전 안전해석에서 이를 고려한 응축열전달 모델이 주목받고 있다. 본 연구에서는 냉각재상실사고 등이 발생하는 경우 원자로건물 내부의 상황과 유사한 열수력 조건에서 수행된 응축열전달 실험자료를 이용하여 중대사고 해석코드 MELCOR 1.8.6의 응축열전달 모델을 평가하였다. 실험조건을 응축면의 형상에 따라 네 가지(수직평판, 수직관 외벽, 수직관 내벽, 수평관 내벽)로 분류하였고, 각 분류별 실험들을 MELCOR 코드로 해석하였다. 해석결과, 수직관 내벽을 제외한 나머지 조건에서 MELCOR 코드가 응축열전달을 전체적으로 저 예측하여 개선이 필요한 것으로 나타났다.

Keywords

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