An intelligent approach to predicting the effect of nanoparticle mixture ratio, concentration and temperature on thermal conductivity of hybrid nanofluids
<p dir="ltr">Hybrid nanofluids are better heat transfer fluids than conventional nanofluids because of the combined properties of two or more nanoparticles. In this study, the thermal conductivity of Al<sub>2</sub>O<sub>3</sub>–ZnO nanoparticles suspended in a...
محفوظ في:
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| مؤلفون آخرون: | , , , |
| منشور في: |
2020
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إضافة وسم
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| الملخص: | <p dir="ltr">Hybrid nanofluids are better heat transfer fluids than conventional nanofluids because of the combined properties of two or more nanoparticles. In this study, the thermal conductivity of Al<sub>2</sub>O<sub>3</sub>–ZnO nanoparticles suspended in a base fluid of distilled water is investigated. The experiments were conducted for three mixture ratios (1:2, 1:1 and 2:1) of Al<sub>2</sub>O<sub>3</sub>–ZnO nanofluid at five different volume concentrations of 0.33%, 0.67%, 1.0%, 1.33% and 1.67%. X-ray diffractometric analysis, X-ray fluorescence spectrometry and scanning electron microscopy were used to characterise the nanoparticles. The highest thermal conductivity enhancement achieved for Al2O3–ZnO hybrid nanofluids with 1:2, 1:1 and 2:1 (Al<sub>2</sub>O<sub>3</sub>:ZnO) mixture ratios was 36%, 35% and 40%, respectively, at volume concentration 1.67%. The study observed the highest thermal conductivity for Al<sub>2</sub>O<sub>3</sub>–ZnO nanofluid was achieved at a mixture ratio of 2:1. A “deeping” effect was observed at a mixture ratio of 1:1 representing the lowest value of thermal conductivity within the considered range. The study proposed and compared three models for obtaining the thermal conductivity of Al<sub>2</sub>O<sub>3</sub>–ZnO nanofluids based on temperature, volume concentration and nanoparticle mixture ratio. A polynomial correlation model, the adaptive neuro-fuzzy inference system model and an artificial neural network model optimised with three different learning algorithms. The adaptive neuro-fuzzy inference system model was most accurate in forecasting the thermal conductivity of the Al<sub>2</sub>O<sub>3</sub>–ZnO hybrid nanofluid with an R<sup>2</sup> value of 0.9946.</p><h2>Other Information</h2><p dir="ltr">Published in: Journal of Thermal Analysis and Calorimetry<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="http://dx.doi.org/10.1007/s10973-020-09594-y" target="_blank">http://dx.doi.org/10.1007/s10973-020-09594-y</a></p> |
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