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Prediction of experimental condensation heat transfer characteristics of helically coiled tube-in-shell type heat exchangers by Artificial Neural Network and XGBoost

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Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science

Published online on

Abstract

Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, Ahead of Print.
This study addresses the inherent limitations of empirical correlations in accurately predicting condensation heat transfer and pressure drop within helical tubes, a crucial area given their superior thermal performance compared to straight ...