The objective of this paper is to make review and comparison between the methodologies used for modeling condensation with non-condensable, in two-phase flows channel. The important state-of-the art numerical algorithms for the solution of multi-phase conservation equations are reviewed. The methodology for modeling condensation in these algorithms is based on the stagnant film theory. The methodology used in RELAP5/MOD3 that was the most accurate model is rigorously treats the coupling between the heat and mass transfer process, and gas-liquid interphase without iteration.
The objective of this paper is to make review and comparison between the methodologies used for modeling condensation with non-condensable, in two-phase flows channel. The important state-of-the art numerical algorithms for the solution of multi-phase conservation equations are reviewed. The methodology for modeling condensation in these algorithms is based on the stagnant film theory. The methodology used in RELAP5/MOD3 that was the most accurate model is rigorously treats the coupling between the heat and mass transfer process, and gas-liquid interphase without iteration.
Ismail Mohammed, A. (2020). The Models Used in Predicting Steam Condensation Occurs during Nuclear Reactor Loss of Coolant Accident. Arab Journal of Nuclear Sciences and Applications, 53(1), 137-148. doi: 10.21608/ajnsa.2019.6413.1146
MLA
Adel Lotfy Ismail Mohammed. "The Models Used in Predicting Steam Condensation Occurs during Nuclear Reactor Loss of Coolant Accident". Arab Journal of Nuclear Sciences and Applications, 53, 1, 2020, 137-148. doi: 10.21608/ajnsa.2019.6413.1146
HARVARD
Ismail Mohammed, A. (2020). 'The Models Used in Predicting Steam Condensation Occurs during Nuclear Reactor Loss of Coolant Accident', Arab Journal of Nuclear Sciences and Applications, 53(1), pp. 137-148. doi: 10.21608/ajnsa.2019.6413.1146
VANCOUVER
Ismail Mohammed, A. The Models Used in Predicting Steam Condensation Occurs during Nuclear Reactor Loss of Coolant Accident. Arab Journal of Nuclear Sciences and Applications, 2020; 53(1): 137-148. doi: 10.21608/ajnsa.2019.6413.1146
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