LOCAL VOID FRACTION AND WALL TEMPERATURE PREDICTIONS IN FORCED CONVECTION SUBCOOLED BOILING FLOW USING CFD CODE

Forced convection subcooled boiling flow is an efficient heat transfer process due to the latent heat of evaporation as well as the agitated convection induced by the departure of bubbles. In order to predict and hence prevent the possible occurrence of critical heat flux (CFH) at the heated wall, efforts are made to improve the predictability of wall nucleation boiling models. In this study, simulations are performed using 3-D CFD code ANSYS CFX to assess the predictive capabilities of 42 combinations of nucleation boiling models versus four experimental conditions. Simulation results show that no specific model combination can consistently give the best performance. Also, two major discrepancies are found in the local void fraction profile prediction as well as the wall temperature profile prediction:

1. Most of the local void fraction profile prediction results show smaller void fractions than the experimental data near the heated wall as well as in the bulk region.

2. All of the wall temperature profile prediction results show monotonically increasing trend, which is different from the decreasing-increasing pattern of the experimental data.

The first discrepancy is improved by using the Chen correlation in place of the bubble departure frequency model. The second discrepancy is improved by using modified single-phase heat transfer coefficient, which accounts for the pumping effect and the vapor blanket effect. The influence of condensation is also discussed by using variable bulk bubble diameter in place of the Laplace length. This simulation work is the first one in the literature that captures the decreasing-increasing pattern of the wall temperature profile. Although the local void fraction profile prediction and the wall temperature profile prediction are improved, the predicted departure frequency is much higher than the experimental data. In order to understand the possible reason for this discrepancy, more data for the important parameters, e.g., departure frequency, departure diameter, active nucleation site density, etc., along the whole flow channel are needed as the future work.