Effect of sodium dodecyl sulfate on CO2 and H2S absorption enhancement of functionalized multiwall carbon nanotubes in water: Experimental study and empirical model

A single bubble absorption column was used to examine the effect of hydrodynamic on carbon dioxide (CO₂) and hydrogen sulfide (H₂S) absorption in pure water and water-based nanofluids dispersed with neat, and OH and NH₂ functionalized multiwall carbon nanotubes (MWCNTs). Sodium dodecyl sulfate (SDS) was used as a surfactant and stabilizer. The maximum absorption of CO₂ and H₂S were found to be 0.0038 mmol/m²·s and 0.056 mmol/m²·s using NH₂-MWCNTs /nanofluid with 0.5 wt% content, respectively. The diffusion coefficients of gases into the nanofluids were computed by using an equation attained based on Dankwert’s theory. A last, an empirical correlation was proposed to determine the Sherwood number for the absorption of the aforementioned gases into the nanofluids.     

Fully developed mixed convection in horizontal and inclined tubes with uniform heat flux using nanofluid

Fully developed laminar mixed convection of a nanofluid consists of water and Al₂O₃ in horizontal and inclined tubes has been studied numerically. Three-dimensional elliptic governing equations have been solved to investigate the flow behaviors over a wide range of the Grashof and Reynolds numbers. Comparisons with previously published experimental and numerical works on mixed convection in a horizontal and inclined tube are performed and good agreements between the results are observed. Effects of nanoparticles concentration and tube inclinations on the hydrodynamics and thermal parameters are presented and discussed. It is shown that the nanoparticles concentration does not have significant effects on the hydrodynamics parameters. Heat transfer coefficient increases by 15% at 4 Vol.% Al₂O₃. Skin friction coefficient continually increases with the tube inclination, but the heat transfer coefficient reaches a maximum at the inclination angle of 45°.     

Boiling heat transfer characteristics of nanofluids in a flat heat pipe evaporator with micro-grooved heating surface

An experimental study was performed to understand the nucleate boiling heat transfer of water–CuO nanoparticles suspension (nanofluids) at different operating pressures and different nanoparticle mass concentrations. The experimental apparatus is a miniature flat heat pipe (MFHP) with micro-grooved heat transfer surface of its evaporator. The experimental results indicate that the operating pressure has great influence on the nucleate boiling characteristics in the MFHP evaporator. The heat transfer coefficient and the critical heat flux (CHF) of nanofluids increase greatly with decreasing pressure as compared with those of water. The heat transfer coefficient and the CHF of nanofluids can increase about 25% and 50%, respectively, at atmospheric pressure whereas about 100% and 150%, respectively, at the pressure of 7.4 kPa. Nanoparticle mass concentration also has significant influence on the boiling heat transfer and the CHF of nanofluids. The heat transfer coefficient and the CHF increase slowly with the increase of the nanoparticle mass concentration at low concentration conditions. However, when the nanoparticle mass concentration is over 1.0 wt%, the CHF enhancement is close to a constant number and the heat transfer coefficient deteriorates. There exists an optimum mass concentration for nanofluids which corresponds to the maximum heat transfer enhancement and this optimum mass concentration is 1.0 wt% at all test pressures. The experiment confirmed that the boiling heat transfer characteristics of the MFHP evaporator can evidently be strengthened by using water/CuO nanofluids.     

A study on Brinkman number variation on water based nanofluid heat transfer in partially heated tubes

Even if the variation of Nusselt number with Reynolds number has been observed before, little to no studies are concerning nanofluids. The present numerical data in the laminar regime were also found to correlate well with the Brinkman number for the individual sets and much better globally, by combining all the data sets for nanofluids and water.Thus, this work proposes a new correlation between heat transfer rate and Brinkman number which is a nondimensional number of viscosity, flow velocity and temperature. The results showed a good empirical equation that Nu/(Re^0.62 Pr^0.33) is dependent on a power law function to the Brinkman number in laminar flow regime. The proposed correlation can be applied both to water and nanofluid flow, with respect to the nanoparticle loading. It is expected that the equation suggested by this work can be useful to design heating/cooling devices.     

Thermal performance of stable SiO2 nanofluids and regression correlations to estimate their thermophysical properties

The present work investigates the best mix ratio of Glycerol in Water as a medium to prepare a stable nanofluid. Increasing the proportion of glycerol enhances the aqueous mix's dynamic viscosity and improves the prepared nanofluid's stability. The thermal conductivity and viscosity of the Glycerol and Water mixtures determination were undertaken at various Glycerol ratios. The best percentage of glycerol in the mixture is found to have the least amount of thermal conductivity loss and the optimum viscosity gain. Silica (SiO₂) nanofluid of 0.25%, 0.5%, 1%, and 1.5% weight concentrations was prepared with this optimal mixture of Glycerol and Water. The stability of these SiO₂ nanofluids is evaluated by determining the zeta potential at different time intervals. The nanofluids prepared were observed to be stable for one month. The thermal conductivity and viscosity of the nanofluids are measured between the temperature limits of 30°–70°C. A peak increment of 32.1%and 46.3% in thermal conductivity and viscosity is observed. Furthermore, when the percentage enhancement ratio (PER) and Mouromtseff ratio of these nanofluids is examined, it is observed that they have more excellent thermal performance at higher temperatures. Regression correlations are developed to estimate the thermal conductivity and viscosity of the prepared nanofluids with a maximum deviation of 9%.     

Combination of RSM and NSGA-II algorithm for optimization and prediction of thermal conductivity and viscosity of bioglycol/water mixture containing SiO2 nanoparticles

The fluids containing nanoparticles have enhanced thermo-physical characteristics in comparison with conventional fluids without nanoparticles. Thermal conductivity and viscosity are thermo-physical properties that strongly determine heat transfer and momentum. In this study, the response surface method was firstly used to derive an equation for the thermal conductivity and another one for the viscosity of bioglycol/water mixture (20:80) containing silicon dioxide nanoparticles as a function of temperature as well as the volume fraction of silicon dioxide. Then, NSGA-II algorithm was used for the optimization and maximizing thermal conductivity and minimizing the nanofluid viscosity. Different fronts were implemented and 20th iteration number was selected as Pareto front. The highest thermal conductivity (0.576 W/m.K) and the lowest viscosity (0.61 mPa.s) were obtained at temperature on volume concentration of (80 °C and 2%) and (80 °C without nanoparticle) respectively. It was concluded that the optimum thermal conductivity and viscosity of nanofluid could be obtained at maximum temperature (80 °C) or a temperature close to this temperature. An increase in the volume fraction of silicon dioxide led to the enhancement of thermal conductivity but the solution viscosity was also increased. Therefore, the optimum point should be selected based on the system requirement.     

Dispersibility dependence of thermal conductivity of carbon nanotube based nanofluids

A differential effective medium theory together with Brownian motion is used to predict Effective Thermal Conductivity (ETC) of CNT nanofluids. ETC was influenced significantly by Brownian motion and enhancement was higher in dilute nanofluids. A theoretical model employing an effective volume fraction with dispersibility factor agrees well with experimental data.     

Effect of Lorentz forces on forced-convection nanofluid flow over a stretched surface

Magnetic nanofluid hydrothermal analysis over a plate is studied that includes consideration of thermal radiation. The Runge–Kutta (RK4) method is utilized to get solution of ODEs which are obtained from similarity solution. In considering the impacts of Brownian motion, we applied Koo–Kleinstreuer–Li correlation to simulate the properties of CuO–water. The influence is discussed of important parameters such as the temperature index, magnetic, radiation, and velocity ratio parameters and volume fraction of nanoparticle on hydrothermal behavior. Results illustrate that the coefficient of skin friction enhances with enhancing magnetic parameter while reduces with enhancing velocity ratio parameter. Also the Nusselt number was found to directly depend on the velocity ratio and temperature index parameters but has an inverse dependence on the magnetic and radiation parameters.     

Thermophysical effects of carbon nanotubes on MHD flow over a stretching surface

This article is intended for investigating the effects of magnetohydrodynamics (MHD) and volume fraction of carbon nanotubes (CNTs) on the flow and heat transfer in two lateral directions over a stretching sheet. For this purpose, three types of base fluids specifically water, ethylene glycol and engine oil with single and multi-walled carbon nanotubes are used in the analysis. The convective boundary condition in the presence of CNTs is presented first time and not been explored so far. The transformed nonlinear differential equations are solved by the Runge–Kutta–Fehlberg method with a shooting technique. The dimensionless velocity and shear stress are obtained in both directions. The dimensionless heat transfer is determined on the surface. Three different models of thermal conductivity are comparable for both CNTs and it is found that the Xue [1] model gives the best approach to guess the superb thermal conductivity in comparison with the Maxwell [2] and Hamilton and Crosser [3] models. And finally, another finding suggests the engine oil provides the highest skin friction and heat transfer rates.     

Application of SAXS to the study of particle-size-dependent thermal conductivity in silica nanofluids

Knowledge of the size and distribution of nanoparticles in solution is critical to understanding the observed enhancements in thermal conductivity and heat transfer of nanofluids. We have applied small-angle X-ray scattering (SAXS) to the characterization of SiO₂ nanoparticles (10–30 nm) uniformly dispersed in a water-based fluid using the Advanced Photon Source at Argonne National Laboratory. Size distributions for the suspended nanoparticles were derived by fitting experimental data to an established model. Thermal conductivity of the SiO₂ nanofluids was also measured, and the relation between the average particle size and the thermal conductivity enhancement was established. The experimental data contradict models based on fluid interfacial layers or Brownian motion but support the concept of thermal resistance at the liquid–particle interface.