Machine learning based approach for the prediction of flow boiling/condensation heat transfer performance in mini channels with serrated fins-Reference-Cited by-同舟云学术

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Machine learning based approach for the prediction of flow boiling/condensation heat transfer performance in mini channels with serrated fins

Published:2021-02 Issue: Volume:166 Page:120783
ISSN:0017-9310
Container-title:International Journal of Heat and Mass Transfer
language:en
Short-container-title:International Journal of Heat and Mass Transfer

Author:

Zhu Guangya,Wen Tao,Zhang Dalin

Funder

Nanjing University of Aeronautics and Astronautics

Publisher

Elsevier BV

Subject

Fluid Flow and Transfer Processes,Mechanical Engineering,Condensed Matter Physics

Reference45 articles.

1. Experimental study and CFD modelling on the thermal and flow behavior of EG/water ZnO nanofluid in multiport mini channels;Wen;Appl. Therm. Eng.,2021

2. Thermal properties measurement and performance evaluation of water/ZnO nanofluid in a mini channel with offset fins;Wen;Int. J. Heat Mass Transf.,2020

3. Experimental investigation of R1234ze (E) flow boiling inside a 2.4 mm ID horizontal microfin tube;Diani;Int. J. Refrig.,2016

4. An experimental study on two-phase flow patterns and heat transfer characteristics during boiling of R134a flowing through a multimicro hannel eat sink;Thiangtham;Int. J. Heat Mass Transfer,2016

5. Experimental investigation and development of new correlation for flow boiling heat transfer in mini-channel;Wen;Int. J. Therm. Sci,2018

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2. Machine-learning-based modeling of saturated flow boiling in pin-fin micro heat sinks with expanding flow passages;International Communications in Heat and Mass Transfer;2024-11

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4. Comprehensive study of flow boiling modeling inside helical micro-finned tubes: Empirical, non-convex optimization and deep learning predictive models;International Journal of Heat and Mass Transfer;2024-10

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