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On the Comparative Analysis of Machine Learning Models with Empirical Models for Predicting Flow Boiling Heat Transfer Coefficient at High Saturation Temperatures

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A general correlation for flow boiling in tubes and annuli
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Consolidated modeling and prediction of heat transfer coefficients for saturated flow boiling in mini/micro-channels using machine learning methods
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Experimental investigation on high-temperature flow boiling heat transfer characteristics of R245fa in a horizontal circular tube
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A framework for data regression of heat transfer data using machine learning
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Machine and deep learning driven models for the design of heat exchangers with micro-finned tubes
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Flow boiling of halogenated refrigerants at high saturation temperature in a horizontal smooth tube
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Carbon dioxide flow boiling in a single microchannel – Part II: Heat transfer
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Flow boiling characteristics of R-245fa in a minichannel at medium saturation temperatures
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Machine learning-based approach for predicting flow boiling heat transfer coefficient at high saturation temperatures
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Correlation for boiling heat transfer of R-134a in horizontal tubes including effect of tube diameter
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An evaluation of prediction methods for saturated flow boiling heat transfer in mini-channels
inferredcites →https://doi.org/10.1016/j.ijheatmasstransfer.2013.04.014openalex-snapshot
Universal approach to predicting saturated flow boiling heat transfer in mini/micro-channels – Part II. Two-phase heat transfer coefficient
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Flow boiling heat transfer in minichannels at high saturation temperatures: Part II – Assessment of predictive methods and impact of flow regimes
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Flow boiling heat transfer in minichannels at high saturation temperatures: Part I – Experimental investigation and analysis of the heat transfer mechanisms
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Heat transfer during convective boiling inside microchannels
inferredcites →https://doi.org/10.1016/j.ijheatmasstransfer.2017.10.062openalex-snapshot
Flow regime based heat transfer correlation for R245fa in a 3 mm tube
inferredcites →https://doi.org/10.1016/j.ijheatmasstransfer.2019.119211openalex-snapshot
An artificial neural network model to predict mini/micro-channels saturated flow boiling heat transfer coefficient based on universal consolidated data
inferredcites →https://doi.org/10.1016/j.ijheatmasstransfer.2020.120783openalex-snapshot
Machine learning based approach for the prediction of flow boiling/condensation heat transfer performance in mini channels with serrated fins
inferredcites →https://doi.org/10.1016/j.ijheatmasstransfer.2023.123855openalex-snapshot
Experimental study of flow boiling pressure drop and heat transfer of R1233zd(E) at moderate and high saturation temperatures
inferredcites →https://doi.org/10.1016/j.ijheatmasstransfer.2023.124188openalex-snapshot
Predictive modeling for the boiling heat transfer coefficient of R1234yf inside a multiport minichannel tube
inferredcites →https://doi.org/10.1016/j.ijheatmasstransfer.2023.124986openalex-snapshot
An experimental investigation on R245fa and R1233zd(E) flow boiling at high saturation temperatures in a horizontal small diameter channel
inferredcites →https://doi.org/10.1016/j.ijheatmasstransfer.2024.125495openalex-snapshot
Flow boiling heat transfer of R1234ze(E) in a horizontal mini-channel at medium and high saturation temperatures
inferredcites →https://doi.org/10.1016/j.ijhydene.2023.09.058openalex-snapshot
Assessment of machine learning models and conventional correlations for predicting heat transfer coefficient of liquid hydrogen during flow boiling
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Two-phase flow heat transfer of CO2 vaporization in smooth horizontal minichannels
inferredcites →https://doi.org/10.1016/j.ijrefrig.2022.06.036openalex-snapshot
Forecasting of saturated boiling heat transfer inside smooth helically coiled tubes using conventional and machine learning techniques
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Heat resources and organic Rankine cycle machines
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Recent research trends in organic Rankine cycle technology: A bibliometric approach
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Heat Flow Rates in Saturated Nucleate Pool Boiling-A Wide-Ranging Examination Using Reduced Properties
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Correlations for the prediction of boiling heat transfer in small-diameter channels
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An Introduction to Kernel and Nearest-Neighbor Nonparametric Regression
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Permutation importance: a corrected feature importance measure
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Machine learning-based prediction methods for flow boiling in plate heat exchangers
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Intercoder Reliability and Validity of WebPlotDigitizer in Extracting Graphed Data
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Classification And Regression Trees
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Greedy function approximation: A gradient boosting machine.
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