Search | Korea Science

Yun, Byong-Jo;Kwon, Tae-Soon;Song, Chul-Hwa;Euh, Dong-Jin;Park, Jong-Kyun;Cho, Hyoung-Kyu;Park, Goon-Cherl
- Nuclear Engineering and Technology
- /
- v.33 no.3
- /
- pp.315-326
- /
- 2001
Direct ECC bypass phenomena that occur in a reactor vessel downcomer with a Direct Vessel Injection (DVI) system during the reflood phase of a Large Break Loss-of-Coolant Accident (LBLOCA) are experimentally investigated using a transparent l/7.5 scaled down test facility of the Upper Plenum Test Facility (UPTF). A series of separate effect tests are peformed in order to investigate the mechanisms of direct ECC bypass and to find out its scaling parameters. Various flow regimes and phasic distribution in downcomer are identified and mapped, and the fraction of direct ECC bypass is measured under a wide range of air and water injection conditions. From the counterpart test of the UPTF Test 21-D, the dimensionless gas velocity ( $j^{*}$$_{g,eff}$) is derived experimentally, which is believed to be a major scaling parameter for the fraction of direct ECC bypass. And it is found out that the direct ECC bypass is greatly affected by the spreading width of ECC water film and the geometric configuration of the downcomer.r.
PDF

Park, Jong-Ho;Lee, Sang-Yong;Han, Ki-In
- Nuclear Engineering and Technology
- /
- v.20 no.2
- /
- pp.80-87
- /
- 1988
Predicted in this paper are flow distributions in average and hot channels of the reactor core during small and large break LOCAs. Also estimated based on REALP5/MOD2 calculations are the effects of cross flow between channels on LOCA analysis results. It has been so far generally accepted that a single average channel is sufficient for small break LOCA core hydraulic modelling. However, based on these calculation results, hot channel modeling (two channel modeling) is found necessary in order to guarantee more reliable and conservative results. In large break LOCA blowdown phase, the hot channel thermal hydraulics is worse than that of average channel in both cases with the without consideration of cross flow.
PDF

Wazif, Muhammad;Diab, Aya
- Journal of the Korean Society of Systems Engineering
- /
- v.16 no.2
- /
- pp.38-46
- /
- 2020
The accurate measurement of critical heat flux (CHF) in flow boiling is important for the safety requirement of the nuclear power plant to prevent sharp degradation of the convective heat transfer between the surface of the fuel rod cladding and the reactor coolant. In this paper, a System Engineering approach is used to develop a model that predicts the CHF using machine learning. The model is built using artificial neural network (ANN). The model is then trained, tested and validated using pre-existing database for different flow conditions. The Talos library is used to tune the model by optimizing the hyper parameters and selecting the best network architecture. Once developed, the ANN model can predict the CHF based solely on a set of input parameters (pressure, mass flux, quality and hydraulic diameter) without resorting to any physics-based model. It is intended to use the developed model to predict the DNBR under a large break loss of coolant accident (LBLOCA) in APR1400. The System Engineering approach proved very helpful in facilitating the planning and management of the current work both efficiently and effectively.
https://doi.org/10.14248/JKOSSE.2020.16.2.038 인용 PDF KSCI