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Improvement of two-phase heat transfer correlation superposition type for propane by genetic algorithm

The prediction accuracies of the two-phase heat transfer coefficient for the flow in a small channel, which are usually based on the mean absolute error (MAE) between the correlation and experimental data, have remained unsatisfactory. Conventionally, the regression method has been used to determine...

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Main Authors: Mohd. Yunos, Yushazaziah, Mohd. Ghazali, Normah, Mohamad, Maziah, Pamitran, Agus Sunjarianto, Oh, Jong Taek
Format: Article
Published: Springer-Verlag GmbH Germany 2020
Subjects:
TJ Mechanical engineering and machinery
Online Access:http://eprints.utm.my/id/eprint/93488/
http://dx.doi.org/10.1007/s00231-019-02776-x
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spelling my.utm.934882021-11-30T08:35:12Z http://eprints.utm.my/id/eprint/93488/ Improvement of two-phase heat transfer correlation superposition type for propane by genetic algorithm Mohd. Yunos, Yushazaziah Mohd. Ghazali, Normah Mohamad, Maziah Pamitran, Agus Sunjarianto Oh, Jong Taek TJ Mechanical engineering and machinery The prediction accuracies of the two-phase heat transfer coefficient for the flow in a small channel, which are usually based on the mean absolute error (MAE) between the correlation and experimental data, have remained unsatisfactory. Conventionally, the regression method has been used to determine the correlation that best represents the experimental data. In this paper, an improved heat transfer correlation for the evaporation of propane is developed by applying the genetic algorithm method. A total of 789 data points from 4 sources with circular diameters ranging from 1.0 to 6.0 mm are used to minimise the MAE while searching for the optimum conditions for the suppression factor, S, and convective factor, F, in a selected superposition correlation for two different vapour quality ranges. The optimisation can minimise the MAE at 33% and 25% for Case I and Case II, respectively. The proposed method assists in attaining a precise empirical prediction that fits well with the experimental data. Springer-Verlag GmbH Germany 2020-04-01 Article PeerReviewed Mohd. Yunos, Yushazaziah and Mohd. Ghazali, Normah and Mohamad, Maziah and Pamitran, Agus Sunjarianto and Oh, Jong Taek (2020) Improvement of two-phase heat transfer correlation superposition type for propane by genetic algorithm. Heat and Mass Transfer/Waerme- und Stoffuebertragung, 56 (4). pp. 1087-1098. ISSN 0947-7411 http://dx.doi.org/10.1007/s00231-019-02776-x DOI:10.1007/s00231-019-02776-x
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Mohd. Yunos, Yushazaziah
Mohd. Ghazali, Normah
Mohamad, Maziah
Pamitran, Agus Sunjarianto
Oh, Jong Taek
Improvement of two-phase heat transfer correlation superposition type for propane by genetic algorithm
description The prediction accuracies of the two-phase heat transfer coefficient for the flow in a small channel, which are usually based on the mean absolute error (MAE) between the correlation and experimental data, have remained unsatisfactory. Conventionally, the regression method has been used to determine the correlation that best represents the experimental data. In this paper, an improved heat transfer correlation for the evaporation of propane is developed by applying the genetic algorithm method. A total of 789 data points from 4 sources with circular diameters ranging from 1.0 to 6.0 mm are used to minimise the MAE while searching for the optimum conditions for the suppression factor, S, and convective factor, F, in a selected superposition correlation for two different vapour quality ranges. The optimisation can minimise the MAE at 33% and 25% for Case I and Case II, respectively. The proposed method assists in attaining a precise empirical prediction that fits well with the experimental data.
format Article
author Mohd. Yunos, Yushazaziah
Mohd. Ghazali, Normah
Mohamad, Maziah
Pamitran, Agus Sunjarianto
Oh, Jong Taek
author_facet Mohd. Yunos, Yushazaziah
Mohd. Ghazali, Normah
Mohamad, Maziah
Pamitran, Agus Sunjarianto
Oh, Jong Taek
author_sort Mohd. Yunos, Yushazaziah
title Improvement of two-phase heat transfer correlation superposition type for propane by genetic algorithm
title_short Improvement of two-phase heat transfer correlation superposition type for propane by genetic algorithm
title_full Improvement of two-phase heat transfer correlation superposition type for propane by genetic algorithm
title_fullStr Improvement of two-phase heat transfer correlation superposition type for propane by genetic algorithm
title_full_unstemmed Improvement of two-phase heat transfer correlation superposition type for propane by genetic algorithm
title_sort improvement of two-phase heat transfer correlation superposition type for propane by genetic algorithm
publisher Springer-Verlag GmbH Germany
publishDate 2020
url http://eprints.utm.my/id/eprint/93488/
http://dx.doi.org/10.1007/s00231-019-02776-x
_version_ 1718926075392688128
score 13.244367

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