An optimization approach in the development of a new correlation for two-phase heat transfer coefficient of R744 in a microchannel
To date, no single method has been found to satisfactorily predict the two-phase heat transfer coefficient of R744 refrigerant in small channels. Studies are continuously being done to obtain a coefficient with acceptable mean absolute error (MAE) which measures the difference between the predicted...
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Society of Refrigeration and Air Conditioning Engineers
2022
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Online Access: | http://eprints.utm.my/id/eprint/100925/1/WanMuhammadZaidWanZaidi2022_AnOptimizationApproachinTheDevelopment.pdf http://eprints.utm.my/id/eprint/100925/ http://dx.doi.org/10.1007/s44189-022-00004-6 |
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my.utm.1009252023-05-18T04:30:18Z http://eprints.utm.my/id/eprint/100925/ An optimization approach in the development of a new correlation for two-phase heat transfer coefficient of R744 in a microchannel Wan Zaidi, Wan Muhammad Zaid Mohd. Yunos, Yushazaziah Mohd. Ghazali, Normah Pamitran, Agus Sunjarianto Oh, Ong Taek TJ Mechanical engineering and machinery To date, no single method has been found to satisfactorily predict the two-phase heat transfer coefficient of R744 refrigerant in small channels. Studies are continuously being done to obtain a coefficient with acceptable mean absolute error (MAE) which measures the difference between the predicted and experimentally determined coefficient values. It is important to have available accurate heat transfer coefficient correlation for the two-phase heat transfer coefficient so that a compact heat exchanger that maximizes device performance while reducing cost and energy needs can be designed. In this study, genetic algorithm (GA) is used as an optimization tool to achieve a more accurate correlation for R744 in a microchannel by minimizing the MAE. Over 536 sets of experimental data from previous studies were utilized, optimizing the six constants appearing in the force convective factor, F, and nucleate boiling suppression factor, S, of the selected superposition correlation. The results showed that the MAE between the newly optimized correlation and selected experimental data at all ranges of vapor quality has been successfully reduced from 38.39 to 34.40%. With more available data, the suggested method can be utilized to achieve a more accurate empirical prediction that matches well with the experimental data. Society of Refrigeration and Air Conditioning Engineers 2022 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/100925/1/WanMuhammadZaidWanZaidi2022_AnOptimizationApproachinTheDevelopment.pdf Wan Zaidi, Wan Muhammad Zaid and Mohd. Yunos, Yushazaziah and Mohd. Ghazali, Normah and Pamitran, Agus Sunjarianto and Oh, Ong Taek (2022) An optimization approach in the development of a new correlation for two-phase heat transfer coefficient of R744 in a microchannel. International Journal of Air-Conditioning and Refrigeration, 30 (1). pp. 1-9. ISSN 2010-1325 http://dx.doi.org/10.1007/s44189-022-00004-6 DOI: 10.1007/s44189-022-00004-6 |
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TJ Mechanical engineering and machinery Wan Zaidi, Wan Muhammad Zaid Mohd. Yunos, Yushazaziah Mohd. Ghazali, Normah Pamitran, Agus Sunjarianto Oh, Ong Taek An optimization approach in the development of a new correlation for two-phase heat transfer coefficient of R744 in a microchannel |
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To date, no single method has been found to satisfactorily predict the two-phase heat transfer coefficient of R744 refrigerant in small channels. Studies are continuously being done to obtain a coefficient with acceptable mean absolute error (MAE) which measures the difference between the predicted and experimentally determined coefficient values. It is important to have available accurate heat transfer coefficient correlation for the two-phase heat transfer coefficient so that a compact heat exchanger that maximizes device performance while reducing cost and energy needs can be designed. In this study, genetic algorithm (GA) is used as an optimization tool to achieve a more accurate correlation for R744 in a microchannel by minimizing the MAE. Over 536 sets of experimental data from previous studies were utilized, optimizing the six constants appearing in the force convective factor, F, and nucleate boiling suppression factor, S, of the selected superposition correlation. The results showed that the MAE between the newly optimized correlation and selected experimental data at all ranges of vapor quality has been successfully reduced from 38.39 to 34.40%. With more available data, the suggested method can be utilized to achieve a more accurate empirical prediction that matches well with the experimental data. |
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Article |
author |
Wan Zaidi, Wan Muhammad Zaid Mohd. Yunos, Yushazaziah Mohd. Ghazali, Normah Pamitran, Agus Sunjarianto Oh, Ong Taek |
author_facet |
Wan Zaidi, Wan Muhammad Zaid Mohd. Yunos, Yushazaziah Mohd. Ghazali, Normah Pamitran, Agus Sunjarianto Oh, Ong Taek |
author_sort |
Wan Zaidi, Wan Muhammad Zaid |
title |
An optimization approach in the development of a new correlation for two-phase heat transfer coefficient of R744 in a microchannel |
title_short |
An optimization approach in the development of a new correlation for two-phase heat transfer coefficient of R744 in a microchannel |
title_full |
An optimization approach in the development of a new correlation for two-phase heat transfer coefficient of R744 in a microchannel |
title_fullStr |
An optimization approach in the development of a new correlation for two-phase heat transfer coefficient of R744 in a microchannel |
title_full_unstemmed |
An optimization approach in the development of a new correlation for two-phase heat transfer coefficient of R744 in a microchannel |
title_sort |
optimization approach in the development of a new correlation for two-phase heat transfer coefficient of r744 in a microchannel |
publisher |
Society of Refrigeration and Air Conditioning Engineers |
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2022 |
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http://eprints.utm.my/id/eprint/100925/1/WanMuhammadZaidWanZaidi2022_AnOptimizationApproachinTheDevelopment.pdf http://eprints.utm.my/id/eprint/100925/ http://dx.doi.org/10.1007/s44189-022-00004-6 |
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