Prediction of transition boiling concerning downward facing horizontal surface in confined space using artificial neural network

An artificial neural network (ANN) for predicting Nusselt number was trained successfully based on the data of transition boiling experiment, which was conducted in confined space with downward facing surface at atmospheric pressure. The effects of wall superheat, Δt_w, the ratio of the gap size to the diameter of heated surface, δ/D, Prandtl number and Rayleigh number on Nusselt number under transition boiling condition were analyzed based on the trained ANN. A correlation used to accurately predict the natural convection heat transfer under the present condition was obtained and it provides a reasonable agreement against the experimental data.