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A Taguchi approach for optimization of design parameters on Rayleigh-Bénard convection in water-based Al2O3 nanofluids

A Taguchi approach for optimization of design parameters on Rayleigh-Bénard convection in... This study aims to deal with the optimization of experimental parameters to obtain maximum heat transfer rate in a Rayleigh–Bénard enclosure filled with the water-based Al2O3 nanofluids using the Taguchi method.Design/methodology/approachThe particle size and particle concentration of the Al2O3 nanoparticles are 40 nm and 0.01 Vol. %, respectively. A two-step approach has been used to prepare the nanofluids of the required concentration by mixing the nanoparticles in the distilled water (DW). A Rayleigh–Bénard enclosure, having a hot bottom and a cold top copper plate with insulated side walls, is used for the experiments. Experiments have been conducted first with the DW, for the validation of experimental facility, and second with nanofluid (Al2O3 + DW), for the heat transfer improvement, at three different values of enclosure aspect ratios (ratio of height to width of an enclosure), i.e. 0.5, 1.0 and 1.5.FindingsSignal-to-noise ratio (SNR) analysis has been used to determine the optimal levels of design parameters and their contribution toward heat transfer augmentation. The heat transfer, i.e. Nusselt number, is determined for L9 (33) orthogonal array designed by Taguchi method along with corresponding SNR values. The SNR values are plotted for DW and nanofluid to study the effect of different parameters and to identify their optimal levels. It was found that the aspect ratio has the maximum contribution ratio of 78% for the nanofluid and 76.12% for the DW, followed by the heat flux and the height.Originality/valueThe present results demonstrated the great reliability of the Taguchi method in the optimization of the thermal system to save the time and cost of experiments. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png World Journal of Engineering Emerald Publishing

A Taguchi approach for optimization of design parameters on Rayleigh-Bénard convection in water-based Al2O3 nanofluids

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References (20)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1708-5284
DOI
10.1108/wje-12-2020-0623
Publisher site
See Article on Publisher Site

Abstract

This study aims to deal with the optimization of experimental parameters to obtain maximum heat transfer rate in a Rayleigh–Bénard enclosure filled with the water-based Al2O3 nanofluids using the Taguchi method.Design/methodology/approachThe particle size and particle concentration of the Al2O3 nanoparticles are 40 nm and 0.01 Vol. %, respectively. A two-step approach has been used to prepare the nanofluids of the required concentration by mixing the nanoparticles in the distilled water (DW). A Rayleigh–Bénard enclosure, having a hot bottom and a cold top copper plate with insulated side walls, is used for the experiments. Experiments have been conducted first with the DW, for the validation of experimental facility, and second with nanofluid (Al2O3 + DW), for the heat transfer improvement, at three different values of enclosure aspect ratios (ratio of height to width of an enclosure), i.e. 0.5, 1.0 and 1.5.FindingsSignal-to-noise ratio (SNR) analysis has been used to determine the optimal levels of design parameters and their contribution toward heat transfer augmentation. The heat transfer, i.e. Nusselt number, is determined for L9 (33) orthogonal array designed by Taguchi method along with corresponding SNR values. The SNR values are plotted for DW and nanofluid to study the effect of different parameters and to identify their optimal levels. It was found that the aspect ratio has the maximum contribution ratio of 78% for the nanofluid and 76.12% for the DW, followed by the heat flux and the height.Originality/valueThe present results demonstrated the great reliability of the Taguchi method in the optimization of the thermal system to save the time and cost of experiments.

Journal

World Journal of EngineeringEmerald Publishing

Published: May 10, 2022

Keywords: Nanofluid; Optimization; Taguchi method; Heat transfer; Nusselt number; Rayleigh–Bénard convection

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