A study on accuracy range of multiphase mixture model for turbulent convective heat transfer enhancement simulation of Water-Al2O3 Nanofluid
Because of complications and cost of experimental studies, simulating heat transfer of nanofluids using the methods of computational fluid dynamics (CFD) has become a reliable approach to work with them. As Mixture model remains as one of the most heavily used CFD models to examine the heat transfer...
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Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
American Scientific Publishers
2023
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Subjects: | |
Online Access: | http://irep.iium.edu.my/101919/1/101919_A%20study%20on%20accuracy%20range%20of%20multiphase%20mixture%20model.pdf http://irep.iium.edu.my/101919/ https://www.ingentaconnect.com/content/asp/jon/2023/00000012/00000002/art00013;jsessionid=yhmxjtnjngsh.x-ic-live-01 |
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Institution: | Universiti Islam Antarabangsa Malaysia |
Language: | English |
Summary: | Because of complications and cost of experimental studies, simulating heat transfer of nanofluids using the methods of computational fluid dynamics (CFD) has become a reliable approach to work with them. As Mixture model remains as one of the most heavily used CFD models to examine the heat transfer enhancement of nanofluids according to literature, finding out the range of nanofluid configurations for which the Mixture model is able to provide satisfactory results is a necessity. In this study, turbulent flow of water-Al2O3 inside a circular pipe under uniform wall temperature has been simulated in order to find out the conditions for Mixture model to yield reliable results in terms of predicting heat transfer enhancement of nanofluids. Along with depicting significant increase in heat transfer with particle concentration hike, the results suggested that Mixture model predicts heat transfer enhancement the most accurately for nanoparticle concentration of around 3% with an average discrepancy of less than 1% from experimental data, though the results for particle concentration range of 2.5% to 3.5% are quite satisfactory yielding average error lower than 8% |
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