This article experimentally and statistically reports the convective heat transfer performance of a cylindrical mesh-type heat pipe apparatus filled with ZrO2-CeO2/water-ethylene glycol nanofluids. In this regard, ZrO2-CeO2 nanoparticles were synthesized and characterized through the Scanning Electron Microscope and Powder X-ray diffraction methods followed by the preparation of hybrid ZrO2-CeO2 nanofluids of various concentrations ranging from 0.025 to 0.1%. The heat transfer features of a tubular heat pipe with a mixture of the ZrO2-CeO2 nanofluid were evaluated. A 5.33% decrease in thermal resistance value and a 41.16% increase in heat transfer ability with increased power input were observed. The potent regression models were proposed to estimate heat transfer features of the heat pipe. The ANOVA statistical method has been employed to determine the
P
value and the
F
value of the models towards enhancing the reliability and accuracy of the developed models. The outcome revealed that the proposed models are reliable and have the best fit with the experimental data for 30–60 W power. The correlations’ results were validated against the experimental data and showed high accuracy. Moreover, the accuracy of the developed models was ensured through
R
-squared and adjusted
R
-squared values.
Nanofluids are emerging two-phase thermal fluids that play a vital part in heat exchangers owing to its heat transfer features. Ceramic nanoparticles aluminium oxide (Al2O3) and silicon dioxide (SiO2) were produced by the sol-gel technique. Characterizations have been done through powder X-ray diffraction spectrum and scanning electron microscopy analysis. Subsequently, few volume concentrations (0.0125–0.1%) of hybrid Al2O3–SiO2 nanofluids were formulated via dispersing both ceramic nanoparticles considered at 50:50 ratio into base fluid combination of 60% distilled water (W) with 40% ethylene glycol (EG) using an ultrasonic-assisted two-step method. Thermal resistance besides heat transfer coefficient have been examined with cylindrical mesh heat pipe reveals that the rise of power input decreases the thermal resistance and inversely increases heat transfer coefficient about 5.54% and 43.16% respectively. Response surface methodology (RSM) has been employed for the investigation of heat pipe experimental data. The significant factors on the various convective heat transfer mechanisms have been identified using the analysis of variance (ANOVA) tool. Finally, the empirical models were developed to forecast the heat transfer mechanisms by regression analysis and validated with experimental data which exposed the models have the best agreement with experimental results.
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