Abstract
A great amount of research is focused, nowadays, on experimental, theoretical, and numerical analysis of transient pool boiling. Knowing the minimum film boiling temperature (Tmin) for rods with different substrate materials that are quenched in distilled water pools at various system pressures is known to be a complex and highly non-linear process. This work aims to develop a new correlation to predict the Tmin in the above process: Random forest machine learning technique is applied to predict the Tmin. The approach trains a machine learning algorithm using a set of experimental data collected from the literature. Several parameters such as liquid subcooling temperature (Tsub), fluid to the substrate material thermophysical properties (βf/βw), and system saturated pressure (Psat) are collected and used as inputs, whereas Tmin is measured and used as the output. Computational results show that the algorithm achieves superior results compared to other correlations reported in the literature.
Highlights
Intensive efforts to understand phase-change processes have increased over the last decade in many industrial sectors
This study focused on the unsteady film boiling heat transfer for various degrees of liquid subcooling pools, system pressures, and substrate materials
When accounting for surface roughness, the results showed that the empirical correlation had an mean absolute error (MAE) of 1.5% and an root mean square error (RMSE) of 9.3%
Summary
Intensive efforts to understand phase-change processes have increased over the last decade in many industrial sectors. Solidification, boiling, condensation, and sublimation are several forms of phase-change processes These processes are widely encountered in energy applications due to their association with latent heat rather than sensible heat. They are used in fields such as desalination, metallurgy, electronics cooling, and during thermal generation of electricity and food processing (Collier, 1972). A great amount of research has been focused on experimental, theoretical, and numerical analysis of transient pool boiling which is an example of phase-change processes. It is highly favored in various traditional and modern technologies due to its relative simplicity, high heat transfer rate, and low cost.
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