Improvement of small channel heat transfer correlation using genetic algorithm for R290 refrigerant

The primary issues among the discussions on two-phase flow in small channels are the uncertainties about the contributions of nucleate boiling and forced convective towards the total two-phase heat transfer coefficient, the accuracy of the predicted two-phase heat transfer coefficient which remains...

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Main Author:	Mohd. Yunos, Yushazaziah
Format:	Thesis
Language:	English
Published:	2021
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://eprints.utm.my/id/eprint/102002/1/YushazaziahMohdYunosPSKM2021.pdf.pdf
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spelling	my-utm-ep.1020022023-07-25T10:16:17Z Improvement of small channel heat transfer correlation using genetic algorithm for R290 refrigerant 2021 Mohd. Yunos, Yushazaziah TJ Mechanical engineering and machinery The primary issues among the discussions on two-phase flow in small channels are the uncertainties about the contributions of nucleate boiling and forced convective towards the total two-phase heat transfer coefficient, the accuracy of the predicted two-phase heat transfer coefficient which remains unsatisfactory, measured by the mean absolute error (MAE) between the correlation and experimental data, particularly that can accommodate pre-and post-dryout regions, and the limited experimental work for alternative refrigerants for the establishment of related correlations for a specific refrigerant. This thesis presents the results obtained using an optimization approach, Multi-objective Genetic Algorithm (MOGA) to show the conflicting effect of nucleate boiling and forced convective during two-phase flow of the natural refrigerant R290 in a small channel at the saturation temperature of 10°C under optimized conditions of mass flux, heat flux, channel diameter, and vapor quality. Subsequently, Single Objective Genetic Algorithm (SOGA) was utilized to improve a selected superposition two-phase heat transfer correlation for R290. Experimental data points of R290 from reported experiments in 1.0 to 6.0 mm circular diameters were used to minimize the MAE while searching for the optimum constants and coefficients in the suppression factor (??), and convective factor (??), for the pre-and the post-dryout regions. The newly optimized correlation for R290 has MAE between 17 and 34% for all case studies which involves 40% improvement from the original correlation. Validation was done against a new data set to see the applicability and limitation of the developed correlations. The proposed method is capable of obtaining a precise empirical prediction that fits well with experimental data, as an approach to further improve any existing correlations which can reduce the number of experiments and consequently minimizes associated cost involved. The improved correlation obtained in the present study provides an improved prediction of heat transfer coefficient that in turn leads to accurate design and consequently saves material, refrigerant, and cost for compact heat exchanging devices. 2021 Thesis http://eprints.utm.my/id/eprint/102002/ http://eprints.utm.my/id/eprint/102002/1/YushazaziahMohdYunosPSKM2021.pdf.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:147272 phd doctoral Universiti Teknologi Malaysia Faculty of Engineering - School of Mechanical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery Mohd. Yunos, Yushazaziah Improvement of small channel heat transfer correlation using genetic algorithm for R290 refrigerant
description	The primary issues among the discussions on two-phase flow in small channels are the uncertainties about the contributions of nucleate boiling and forced convective towards the total two-phase heat transfer coefficient, the accuracy of the predicted two-phase heat transfer coefficient which remains unsatisfactory, measured by the mean absolute error (MAE) between the correlation and experimental data, particularly that can accommodate pre-and post-dryout regions, and the limited experimental work for alternative refrigerants for the establishment of related correlations for a specific refrigerant. This thesis presents the results obtained using an optimization approach, Multi-objective Genetic Algorithm (MOGA) to show the conflicting effect of nucleate boiling and forced convective during two-phase flow of the natural refrigerant R290 in a small channel at the saturation temperature of 10°C under optimized conditions of mass flux, heat flux, channel diameter, and vapor quality. Subsequently, Single Objective Genetic Algorithm (SOGA) was utilized to improve a selected superposition two-phase heat transfer correlation for R290. Experimental data points of R290 from reported experiments in 1.0 to 6.0 mm circular diameters were used to minimize the MAE while searching for the optimum constants and coefficients in the suppression factor (??), and convective factor (??), for the pre-and the post-dryout regions. The newly optimized correlation for R290 has MAE between 17 and 34% for all case studies which involves 40% improvement from the original correlation. Validation was done against a new data set to see the applicability and limitation of the developed correlations. The proposed method is capable of obtaining a precise empirical prediction that fits well with experimental data, as an approach to further improve any existing correlations which can reduce the number of experiments and consequently minimizes associated cost involved. The improved correlation obtained in the present study provides an improved prediction of heat transfer coefficient that in turn leads to accurate design and consequently saves material, refrigerant, and cost for compact heat exchanging devices.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Mohd. Yunos, Yushazaziah
author_facet	Mohd. Yunos, Yushazaziah
author_sort	Mohd. Yunos, Yushazaziah
title	Improvement of small channel heat transfer correlation using genetic algorithm for R290 refrigerant
title_short	Improvement of small channel heat transfer correlation using genetic algorithm for R290 refrigerant
title_full	Improvement of small channel heat transfer correlation using genetic algorithm for R290 refrigerant
title_fullStr	Improvement of small channel heat transfer correlation using genetic algorithm for R290 refrigerant
title_full_unstemmed	Improvement of small channel heat transfer correlation using genetic algorithm for R290 refrigerant
title_sort	improvement of small channel heat transfer correlation using genetic algorithm for r290 refrigerant
granting_institution	Universiti Teknologi Malaysia
granting_department	Faculty of Engineering - School of Mechanical Engineering
publishDate	2021
url	http://eprints.utm.my/id/eprint/102002/1/YushazaziahMohdYunosPSKM2021.pdf.pdf
_version_	1776100822596190208

Improvement of small channel heat transfer correlation using genetic algorithm for R290 refrigerant

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