Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
299046 | Nuclear Engineering and Design | 2008 | 8 Pages |
Experimental study has been conducted to examine the pool boiling occurs on a relative large downward-facing round surface with a diameter of 300 mm in confined water pool at atmospheric pressure. An artificial neural network (ANN) has been trained successfully based on the experimental data for predicting Nusselt number of transition boiling in the present study. The input parameters of the ANN are wall superheat, ΔTw, the ratio of the gap size to the diameter of the heated surface, δ/D, Prandtl number and Rayleigh number. The output is Nusselt number, Nu. The results show that: Nu decreases with increasing ΔTw, and increases generally with an increase of δ/D. Nu increases with increasing Pr when gap size is smaller than 4.0 mm. And Nu decreases initially and then increases with increasing Pr as gap size bigger than 5.0 mm. The results also indicate that the influence of Grashof number, Gr, could be negligible. Finally, a new correlation was proposed to predict the transition boiling heat transfer under the present condition. The comparisons between the prediction of the new correlation and experimental data show a reasonable agreement.