Optimal characteristics and heat transfer efficiency of SiO ₂ /water nanofluid for application of energy devices: A comprehensive study

Abstract

Summary In a comprehensive study, the thermal conductivity, dynamic viscosity, and the rheological behavior of a SiO2/water nanofluid are investigated experimentally at the temperatures, solid concentrations, and the shear rates of 25°C to 50°C, 0% to 1.5%, and 400 to 1400(s−1), respectively. The Response Surface Methodology (RSM) is utilized to obtain regression models for the thermal conductivity and the dynamic viscosity. Subsequently, the sensitivity of the aforementioned models to 10% changes in the temperature, and the nanofluid concentration is analyzed. Afterward, Nondominated Sorting Genetic Algorithm II (NSGA‐II) is utilized to find the maximum thermal conductivity and the minimum viscosity. The nondominated optimal points are presented through a fitted correlation on a Pareto front to make the results more practical. The measurements of the investigated nanofluid could be summarized as a paper of a handbook. The workability of the investigated nanofluid is also examined in both laminar and turbulent flow regimes through analysis of the heat transfer merit graphs. To this end, the ratio of the dynamic viscosity enhancement to the thermal conductivity enhancement and the Mouromtseff number are chosen as two criteria of the laminar and turbulent flow regimes, respectively. Finally, the results are compared with those for SiO2/glycerin and SiO2/ethylene glycol nanofluids to check the workability in different base fluids. From a thermal‐efficiency point of view, the SiO2/water nanofluid is not suggested for use in both laminar and turbulent pipe flows, except in temperatures higher than 30°C and volume concentrations lower than 1% for the case of laminar flow. This is because the favorable heat transfer enhancement of the nanofluid is more than the unfavorable increase of the pumping power. From the rheological point of view, though, a SiO2/water nanofluid would be a good choice in lubricating moving surfaces for both laminar and turbulent flow regimes. It is found that in higher nanofluid concentrations, the thermal conductivity of a SiO2/water nanofluid is highly influenced by temperature. Moreover, adding nanoparticles at temperatures of 35°C to 40°C would have the highest increasing effect on the thermal conductivity. It is also revealed that increasing the temperature does not significantly affect the viscosity when 1% SiO2 nanoparticles are suspended within the water.

Analysis of the Gaseous Reduction of Porous Wustite Pellets by Response Surface Methodology

“…In this method, the interactions between variables are not studied and their effect in the process cannot be displayed. [25] Also, a large number of experiments are needed to conduct a research, resulting in increased time, cost, and materials. To overcome this problem, the use of RSM, initially developed by Box and Wilson, [23] is suggested as an appropriate option.…”

“…Terms with an F-value less than 1 and with a P-value larger than 0.05 are removed from the model. [25] Thus, as can be seen, the term Td p is eliminated from the regression model of the reduction time. In this way, the regression correlation becomes reduced and handier with fewer terms.…”

“…Response surface methodology (RSM) is one of the best mathematical-statistical methods to quantify relationships between the governing variables and the outputs by providing correlations. [23][24][25] It is noted that a correlation obtained from such a statistical approach is simpler to use than solving complex governing differential equations involving gas concentrations and the temperature needed for models based on first principles. It is emphasized, however, that such a correlation equation is applicable mainly within the selected ranges of variables, and any extrapolation beyond these ranges risks the possibility of a serious error.…”

The impacts of utilizing nano‐encapsulated PCM along with RGO nanosheets in a pulsating heat pipe, a comparative study

“…Nanofluids are prepared by dispersing nano‐additives such as nanotubes and nanosheets in water or other suitable solvents 21,22 . Because of the higher thermal conductivity of carbon and metal in comparison with water, adding carbon or metal nano‐additives to the fluid enhances the thermal conductivity of fluid 23‐25 . As for the specific heat increment, nano‐encapsulated PCM (NPCMs) could be an appropriate solution.…”

Optimized modeling and experimental investigation on the thermal/electrical characteristics of MWCNT nanofluid for effective solar thermal applications

“…37,38 Similarly to examine the individual impact of various factors and their relation with each other that collectively contribute to the variation in the thermal properties of nanofluids, Box-Behnken design (BBD), and RSM techniques were utilized. 39,40 Recently, Hemmat Esfe et al developed a correlation methodology for evaluating the TC of water/ethylene glycol (EG) blend-based CNT nanofluids using the artificial neural network (ANN) method along with experimental measurements. 41 EG blend has been predominantly adopted as an effective HTF in solar thermal-based applications owing to its advantageous properties such as high boiling point, adaptability over a wide range of operating temperature, low viscosity, high TC, and stability.…”