What question did this study set out to answer?

The aim is to create a reliable prediction method for heat transfer characteristics across various flow conditions and gravitational environments.

March 27, 2026Journal of Thermal Science and Engineering Applications

Machine-Learning and Experimental Study on Predicting the Heat Transfer Coefficient in Vertical and Microgravity Flow Boiling Using Horizontal Flow Data

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Authors

TKTomihiro KinjoUniversity of Electro-Communications TMTakeshi MochizukiUniversity of Electro-Communications HNH. NakanoUniversity of Electro-Communications

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Implication

Experimental investigations predict heat transfer coefficients in boiling systems, indicating improved accuracy without dependency on environmental conditions.

Key Points

The aim is to create a reliable prediction method for heat transfer characteristics across various flow conditions and gravitational environments.
Developed a new experimental facility to measure heat transfer coefficients of R1233zd(E) from low quality to post-dryout.
Conducted experiments under varying heat flux and mass flux conditions in upward flow.
Combined data from this study with literature to construct a comprehensive database for analysis.
Utilized a machine-learning approach that included pre-training with horizontal flow data and fine-tuning with target datasets.
Experimental results revealed deviations from existing correlations, clarifying the effects of heat flux and mass flux on dryout onset.
Created a comprehensive dataset combining 3,289 upward flow points, alongside additional data for downward (467 points) and microgravity (222 points) flows.
The machine-learning model provided accurate predictions of heat transfer coefficients across different conditions without relying on refrigerant properties.

Cite This Study

Kinjo et al. (2026) studied this question.

synapsesocial.com/papers/69c6209315a0a509bde190fb https://doi.org/10.1115/1.4071502

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Implication

Experimental investigations predict heat transfer coefficients in boiling systems, indicating improved accuracy without dependency on environmental conditions.

Machine-Learning and Experimental Study on Predicting the Heat Transfer Coefficient in Vertical and Microgravity Flow Boiling Using Horizontal Flow Data

Discussion

Member takes

Implication

Key Points

Cite This Study

Machine-Learning and Experimental Study on Predicting the Heat Transfer Coefficient in Vertical and Microgravity Flow Boiling Using Horizontal Flow Data

Discussion

Member takes

Implication

Key Points

Cite This Study

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