Viscosity Of Base Fluid Research Articles

Development of knowledge management in investigating the rheological behavior of SiO2/SAE50 nano-lubricant by response surface methodology (RSM)

The development of knowledge management in dynamic viscosity enables the effective use of fluid to optimize processes and innovations. By collecting, organizing, sharing and applying knowledge, professionals in various industries can take advantage of the potential of dynamic viscosity for optimal performance. Robust model results were developed to predict the viscosity of SiO2/SAE 50 nanofluid (NF) using RSM with a knowledge management approach in laboratory conditions of temperatures T = 25–50 °C, solid volume fractions in the range of SVF= 0–1.5% and shear rates in the range of SR= 666.5–7998 s−1 has been reported to establish a background in using the mentioned NF at high engine speed. After examining the four statistical models Linear, Quadratic, Cubic and Quartic in terms of statistical parameters extracted from ANOVA and measurement charts of the models, it was determined that the model Quartic has high precision compared to the three models in predicting the desired response. Thus, the values of R2 = 0.9923, Predicted R2 =0.9887 and Adjusted R2 = 0.9906 were reported for the selected model; and the MOD values of the Quartic model are − 7 < MOD < +8. Also, a correlation relationship consisting of three independent parameters has been presented to predict viscosity, and it has been determined that viscosity dependence on SR, and NF behavior is non-Newtonian. Comparison of base fluid (BF) viscosity contour with and without the use of nanoparticles (NPs) at high engine speed has shown that the use of SiO2 NPs has led to an increase in viscosity. Also, the use of SiO2 nanoparticles has led to an increase in viscosity by 33.27% and 25% respectively at the minimum and maximum temperature at high engine speed. Finally, the viscosity optimization was done by minimizing the amount of NP consumption and the maximum viscosity at high engine speed in laboratory conditions, and the optimal value was obtained as 212.063 mPa.sec

Influence of Variable Viscosity on Entropy Generation Analysis Due to Graphene Oxide Nanofluid Flow

Conventional investigations on fluid flows are undertaken with an assumption of constant fluid properties. But in reality, the properties such as viscosity and thermal conductivity vary with temperature. In such cases, considering these variabilities aids in modelling the flows with accuracy. Particularly, studying the flow of graphene based nanofluids with variable properties makes the best of both the advantageous thermophysical properties of graphene nanoparticles in heat transfer and the variable fluid properties in accuartely modelling the flow. In this article, the flow of graphene oxide nanofluid along a linearly stretching cylinder under no-slip and convective boundary conditions is investigated, by taking the base fluid viscosity to be a temperature dependant function. Buongiorno model is adapted to develop the flow of graphene nanofluids including the influence of variable heat source, cross-diffusion effects and the effects of nanoparticle characteristics such as thermophoresis and Brownian motion. The modelled equations are transformed and are numerically solved using linearization method. The impacts of embedded parameters including the Dufour and Soret numbers on temperature, concentration and velocity profiles of the chosen nanofluid and their consequent impacts on the predominant cause for the generated entropy are studied. The obtained results are depicted and interpreted in detail. From the tabulated values of skin friction and the values of Sherwood and Nusselt numbers, it is inferred that the conductive heat and mass transfer can be enhanced by variable viscosity parameter and skin friction can be reduced by Soret number. Furthermore, entropy generation is analysed and Bejan number is calculated to be lesser than 0.5, thus demonstrating the dominance of irreversibilty to fluid friction and mass transfer.

Numerical investigation of nanofluid deposition in a microchannel cooling system

Nanofluid-microchannels (NF-MCs) have emerged as an important topic for thermal management of electronic devices. However, deposition of nanoparticles is a tricky problem, and this paper conducts a numerical study to identify the best working conditions to prevent deposition of nanofluids in a microchannel cooling system. According to the findings, large nanoparticles, high velocity, low inlet temperature, high nanoparticle density, low nanofluid density, and high base fluid viscosity are the best working conditions for improving nanofluid stability. However, heat transfer rates and pressure drop must also be taken into account. The nanoparticle deposition rate and average heat transfer coefficient only increase by 2.71% and 0.92% respectively as the heat flux increases from 20 kW/m2 to 100 kW/m2, but the pressure drop decreases by 10.57%. Therefore, changing the heat flux is not the best option. Moreover, the inlet temperature has only a minor effect on the heat transfer coefficient, so it is crucial to balance the pressure drop and nanoparticle deposition when designing systems.

Experimental study on the dynamic viscosity of hydraulic oil HLP 68- Fe3O4-TiO2-GO ternary hybrid nanofluid and modeling utilizing machine learning technique

BackgroundConsidering the importance of hydraulic oils in various tasks, such as lubrication and cooling, this study evaluated the feasibility of improving the efficiency of hydraulic systems by modifying the thermophysical properties and rheological behavior of base hydraulic oil. MethodsThe rheological behavior of the hydraulic oil HLP 68 as a base fluid in the presence of a novel ternary combination of iron oxide (Fe3O4), titanium dioxide (TiO2), and graphene oxide (GO) as nano-additives were evaluated experimentally in a wide range of solid volume fractions (VFs) (0 to 1%), nanomaterial mixing ratios (MRs) (1:1:1, 2:1:1, 1:2:1 and 1:1:2), and temperatures (15 to 65 °C). Significant findingsAnalysis of changes in dynamic viscosity versus shear rate for all MRs revealed that the THNFs have a Newtonian behavior. It was found that the highest increase in base fluid viscosity in the presence of a 1% VF of GO: Fe3O4: TiO2 is 345%, 1821%, 1763%, and 1990% for MRs of 1:1:1, 1:1:2, 1:2:1, and 2:1:1, respectively, which occurs at a temperature of 15 °C. Also, the maximum increase in viscosity with temperature reduction from 65 °C to 15 °C for the MRs of 1:1:1, 1:1:2, 1:2:1, and 2:1:1 was found to be 66%, 75%, 60%, and 70%, respectively, which occurs at the highest solid VF. In addition, an algorithm for optimizing the structure/training parameters of the subtractive clustering-based ANFIS system as a leading regression technique in machine learning was developed.

Stability analysis of water-alumina nanofluid film at the spherical interface

The interface of a viscous fluid and [Formula: see text]-water nanofluid is analyzed through linear instability analysis in a spherical configuration. The viscous fluid lies inside the sphere while the outside region contains nanofluid. In this model, the viscosity of the nanofluid is considered a function of the base fluid viscosity, nanoparticles volume fraction, fractal aggregates, and nanoparticles shape. The perturbed flow is taken as irrotational, and the linear perturbation equations are solved through viscous irrotational theory. The perturbations growth rate can be computed through a 2-degree polynomial and the coefficients of this polynomial are the functions of the Atwood number, Richardson number, Weber number, Reynolds number, etc. The nanofluid interface is found more stable than the viscous fluid interface. The density of nanofluids raises the amplitude of disturbances while the nanofluid's viscosity has a reverse effect.

Study of a novel ternary second-order viscosity model on Al2O3-water nanofluid

In terms of heat dissipation, nanofluids with strong thermal conductivity are becoming more and more common, attracting more and more research and attention to date.In this study, Al2O3-H2O nanofluids were studied using molecular dynamics simulations and model parameterization. The dynamic viscosity distribution patterns were obtained at various temperatures(290K~360K), nanoparticle volume fractions(1.24%~6.2%), and particle sphericity(0.69~1.0), and an efficient ternary second-order polynomial viscosity prediction model was proposed on the basis of these results.The findings demonstrate the model's goodness-of-fit with a coefficient of determination over 0.96 and a root mean square error under 0.05, as well as its high predictive ability with a maximum relative error between simulated and predicted values under 9%. Using this viscosity prediction model, a subsequent parametric sensitivity study showsthat the volume fraction had the most significant impact on viscosity, exhibiting not just a second order effect but also an interacting effect with temperature and sphericity. The relative nanofluid viscosity, which is the ratio of nanofluid viscosity to aqueous base fluid viscosity, exhibits a convex parabolic growth at constant temperature and sphericity and increases more quickly at the same volume fraction the higher the temperature. The viscosity of the nanofluid increases by up to 34% when the volume fraction is equal to 6.28% and the particle sphericity is equal to 1.An efficient viscosity prediction model makes it easier to control important variables to reduce energy consumption during flow and increase its capacity to dissipate heat.

Enhancement of Heat Transfer Performance of a Heat Pipe by Using Calcium Magnesium Carbonate-Ethylene Glycol/Water Nanofluid with Sodium Dodecylbenzene Sulfonate

In this paper, the effect of using CaMg(CO3)2/Ethylene Glycol-water (50:50%) as a working fluid on the thermal performance of thermosyphon heat pipe was experimentally studied. Nanofluid was prepared by two-step method using 2% concentration of CaMg(CO3)2 nanoparticle and 0.05% surfactant (Sodium dodecylbenzene sulfonate). For the experimental set-up, a straight copper pipe of one-meter length was used. The inner diameter of the pipe is 13 mm, and the outer diameter is 15 mm. Experiments were conducted at three different cooling water mass flow rates (5, 7.5, and 10 g/s) and different heating powers (200, 300, 400 W) to test heat pipe performance. It was observed that the CaMg(CO3)2 nanofluid reduced the average wall temperature of the heat pipe according to the base fluid. Furthermore, the efficiency and thermal resistance of the heat pipe were investigated separately for EG/water and CaMg(CO3)2 nanofluid. The maximum heat transfer enhancement was obtained as 9.55% under 400 W heating power and 10 g/s cooling water mass flow rate conditions and the maximum improvement in thermal resistance was observed as 21% at 200 W and 10 g/s cooling mass flow rate. Viscosity and specific heat of base fluid and CaMg(CO3)2 nanofluid were also determined and compared to each other.

A coupled CFD-DEM simulation of fracture sealing: Effect of lost circulation material, drilling fluid and fracture conditions

Lost circulation could be one of the most troublesome and expensive situations during drilling, especially in naturally fractured formations. Sealing fractures by granular lost circulation materials (LCMs) is one of the common methods for lost circulation control. However, this type of LCM has a limited effectiveness partly due to the poor understanding of how granular LCMs work. To fill this gap, a coupled CFD-DEM model is utilized for simulating the sealing process of a typical granular LCM (calcium carbonate) in a wedge-shaped fracture. In this paper, we first defined a set of comprehensive evaluation criteria for the sealing performance of LCMs, which include sealing probability, sealing time, location and stability of the seal, total loss volume and pressure gradient within the sealing zone. Effects of LCM, base fluid and fracture geometry on the sealing performance were investigated using the above-mentioned criteria based on differential pressure buildup, cumulative loss volume, and LCM loss rate, and differential pressure along depth. Our results show that LCM bridging and sealing in the fractures are initialed and controlled under interactive fluid-particle forces (drag force, viscous force and pressure gradient force), contact forces (normal and tangential) and friction forces (static and sliding). Essentially, it is the fluid-particle interactions, ratio of particle size to fracture width, volume concentration and friction effect that determine the fracture sealing performance. For the 1 mm–0.34 mm wedge-shaped fractures, sealing by LCM suspension with particle volume concentration of 9%, the critical bridging and sealing particle size are 200 μm and 330 μm, respectively. For the base simulation case considered in this paper, the critical bridging concentration and the sealing initiation concentration are both between 5% and 7%, and the critical sealing concentration is ranging between 7% and 9%. The critical coefficient of friction between particles for a stable fracture sealing varies between 0.2 and 0.4, and the critical coefficient of friction between particles and fracture surface for stable fracture sealing is ranging between 0 and 0.2. The critical Young’s modulus of particles for dual-particle bridging is between 0.1 and 1 GPa. The critical fluid injection rate is ranging between 1.25 and 3 m/s beyond which the LCM cannot seal the fracture. The rest of factors affect LCM bridging and sealing by changing these four factors to some extents. Particle size, volume concentration, Young’s modulus and the coefficient of friction of bridging granular LCM, and density, viscosity and injection rate of base fluid should be optimized synergistically to achieve an efficient fracture sealing. This research provides a better insight into the working principle of LCMs, which gives a solid scientific basis for LCM selection and design in practical problems.

Physical Stability, Rheology, Thermal Conductivity and Optical and Corrosion Properties of a Graphene Quantum Dot Fluid

Because of their unique and tunable photoluminescence properties, exceptional physicochemical properties, high photostability, biocompatibility and small size, Graphene quantum dots (GQDs) have received a lot of attention. However, insufficient investigations have been carried out on GQD fluids. In this paper, the properties of a prepared GQD fluid are studied experimentally, involving the physical stability, rheology, thermal conductivity, optical properties and corrosion characteristics. It is found that a highly physically stable GQD fluid could be easily achieved because the selected GQDs are well dispersed. It is also found that the addition of GQDs had a slight effect on the base fluid viscosity, but it could significantly increase the thermal conductivity of the fluid. In addition, the investigation of the optical properties shows that the GQD fluid exhibited high absorption to sunlight. The transmittance of ultraviolet and near-infrared light is close to zero. In contrast, the transmittance of GQDs to visible light is high at low weight concentrations, but significantly decreases with the increase of the proportion of GQDs. The corrosion characteristics of the copper and carbon steel samples in the selected GQD fluid or deionized water were experimentally investigated. It is found that the selected GQD fluid can greatly accelerate the corrosion of copper. However, nearly the same corrosion rate is observed for carbon steel in the GQD fluid as that in deionized water. The high stability, low viscosity, enhanced thermal conductivity and unique optical and corrosion properties allowed the GQD fluid to have excellent potential for applications in the energy sector.

Heat transfer properties of metal, metal oxides, and carbon water-based nanofluids in the ethanol condensation process

This work investigates the convective heat transfer enhancement of water-based nanofluids in pipe heat exchanger used for the ethanol condensation process. The nanofluids were produced with different nature of nanoparticles, Cu, Fe3O4, MWCNT, and graphene, in the volume concentration 0.01–0.1%, using different surfactants. These nanoparticles are characterized by X-ray powder diffraction (XRD), Scanning electron microscopy (SEM), specific surface area (BET), and Dynamic light scattering (DLS). Density, thermal conductivity, and viscosity of base fluids and nanofluids were experimentally determined at a relevant temperature of 20 °C. Convective heat transfer enhancement under laminar regime was evaluated from a well-designed experimental setup. As the main results, the thermal conductivity of nanofluids increases up to 3–5% and the viscosity can increase or decrease with nanoparticle concentration, showing a lubricating effect of nanoparticles coupled with respective surfactant. It was shown that the heat transfer properties, heat transfer coefficient, and Nusselt number, are increased with nanofluids compared to water and base-fluids, up to 20%, in the range of Pe 2000–10000. Experimental heat transfer properties are shown to be greater than theoretical ones. Finally, copper nanofluid at low concentration appear to be the best candidate for the application and pipe flow geometry considered.

A systematic review on graphene-based nanofluids application in renewable energy systems: Preparation, characterization, and thermophysical properties

Graphene has attracted much attention from various researchers because of its enhanced mechanical, thermal, and physio-chemical properties. Graphene exhibits high thermal conductivity and stability, less erosion and corrosion than other available nanoparticles. Various existing literature signifies a large portion of the research focuses on stability, heat transfer characteristics and thermal conductivity of Graphene nanofluids. This review article represents a detailed analysis of the preparation techniques, characterization methods stability evaluation, and thermal properties enhancements of Graphene nanofluids. Comparative analysis of the effects of nanoparticle size, volume concentration and temperature on thermal conductivity and viscosity of Graphene nanofluids are reviewed based on heat transfer application. Graphene nanoparticles significantly enhances the thermal conductivity, viscosity, and heat transfer capacity of base fluid. It is noticed that the thermal conductivity of Graphene nanofluids increases with an increase in temperature and volume concentration. Applications of Graphene based nano coolant in automotive radiator, electronic cooling, solar cells and fuel cells are presented. This article can be the rapid reference model with investigational and theoretical analysis for highly critical considerations that impact the thermal performance of graphene based nanofluids in different heat transfer trends. This review also outlined the imminent challenges and future scope of research in Graphene.

Estimating Aqueous Nanofluids Viscosity Via GEP Modeling: Correlation Development and Data Assessment

This paper focuses on developing a new method that represents user-accessible correlation for estimation of water-based nanofluids viscosity. For this, an evolutionary algorithm, namely Gene Expression Programming (GEP), was adapted based on a wide selection of literature published databanks including 819 water-based nanofluids viscosity points. The developed model utilized the base fluid viscosity as well as volume fraction and size of the nanoparticles as the inputs of the model. Several statistical parameters integrated with graphical plots were employed in order to assess the accuracy of the proposed GEP-based model. Results of the evaluation demonstrate fairly enough accuracy of the developed model with statistical parameters of AARD%=11.7913, RMSE=0.3567, and SD=0.1851. Furthermore, the trend analysis indicates that the GEP calculated points satisfactorily follow the trend of the nanofluid viscosity variation as a function of different model inputs. To provide more verification, the proposed GEP model was compared with some literature theoretical and empirical correlations leading to the supremacy of the developed model here. The applied sensitivity analysis reveals that the highest impact value is assigned to the volume fraction of the nanoparticle. Moreover, the outliers detection by Williams’ technique illustrates that about 96.5% of the GEP estimates are in the applicability domain resulting in the validity of the proposed model in this study. At last, the results of this study demonstrate that the new method here outperforms other literature published correlations from the standpoint of accuracy and reliability.

Development and Field Application of a New Ultralow Guar Gum Concentration Weighted Fracturing Fluid in HPHT Reservoirs

A weighted fracturing fluid with superlow guar gum concentration was developed by synthesizing a polyboric acid cross-linker. The density of this fluid is 1.365 g/cm3 and can withstand very high temperature up to 175°C. In this study, a weighting agent was selected, and crosslinking ligands and boric acid were optimized. The crosslinking performance, base fluid viscosity, rheology, and gel-breaking performance of this fracturing fluid were studied. Compared with the conventional weighted fracturing fluid, the concentration of guar gum in the new weighted fracturing fluid can be reduced by 30% at the same temperature condition; moreover, crosslinking can be delayed by 2 minutes. The concentration of gel breaker used in this fluid can be significantly reduced to 0.005%∼0.01%. Two field tests were conducted in Jidong oil field, and both of them achieved great success.

Modeling the viscosity of nanofluids using artificial neural network and Bayesian support vector regression

This study demonstrates the application of artificial neural networks (ANNs) and Bayesian support vector regression (BSVR) models for predicting the relative viscosity of nanofluids. The study examined 19 nanofluids comprising 1425 experimental datasets that were randomly split in a ratio of 70:30 as a training dataset and a testing dataset, respectively. To establish the inputs that will yield the best model prediction, we conducted a systematic analysis of the influence of volume fraction of nanoparticles, the density of nanoparticles, fluid temperature, size of nanoparticles, and viscosity of base fluids on the relative viscosity of the nanofluids. Also, we analyzed the results of all possible input combinations by developing 31 support vector regression models based on all possible input combinations. The results revealed that the exclusion of the viscosity of the base fluids (as a model input) leads to a significant improvement in the model result. To further validate our findings, we used the four inputs—volume fraction of nanoparticles, the density of nanoparticles, fluid temperature, and size of nanoparticles to build an ANN model. Based on the 428 testing datasets, the BSVR and ANN predicted the relative viscosity of nanofluids with an average absolute relative deviation of 3.22 and 6.64, respectively. This indicates that the BSVR model exhibits superior prediction results compared to the ANN model and existing empirical models. This study shows that the BSVR model is a reliable approach for the estimation of the viscosity of nanofluids. It also offers a generalization ability that is much better than ANN for predicting the relative viscosity of nanofluids.

MWCNT and COOH–MWCNT aqueous nanofluids: thermophysical and rheological characterization

The nanofluids characterization is of fundamental importance to predict their applicability in a real heat transfer situation. In addition to the transport properties, the nanofluid stability is an important factor to be studied, due to the long pumping, heating, cooling and resting cycles the fluids are usually subjected to. Carbon nanotubes have great potential to be used in nanofluids, due to their high thermal conductivity and low density. However, for aqueous medium, stability requires the use of stabilization methods. This work carried out the study of the transport properties and stability of nanofluids with multiwalled carbon nanotubes (MWCNT), using three stabilization methods: Triton X-100 (TrX–MWCNT) and Arabic gum (AG–MWCNT) as surfactants and functionalized carbon nanotubes with COOH group (COOH–MWCNT). These three nanofluids were compared to investigate the best configuration for heat transfer processes. The thermal conductivity was studied using the hot wire method; rheology was studied through three curves in rotational rheometer of concentric cylinders; specific heat was studied by the differential scanning calorimetry method; density was measured by the Coriolis Effect method; nanoparticles size and zeta potential were measured by the dynamic light scattering method. The COOH–MWCNT nanofluids present the highest thermal conductivity increase reaching 15% at 60 °C and 12% at 30 °C with 1wt% while the A.G–MWCNT and TrX–MWCNT reach 11% and 7.5%, respectively, at 30 °C. A.G–MWCNT nanofluids showed greater stability after long sonication times, while COOH–MWCNT presents best dispersion at 0.125 and 0.25 wt%, from 40 to 160 min of sonication. The specific heat increases with temperature and decreases with MWCNT concentration; however, it presents a peculiar increase in the concentration of 0.25 wt%, increasing about 0.5% and 4.5% for A.G–MWCNT and COOH–MWCNT, respectively at 60 °C. COOH–MWCNT nanofluids showed a thixotropic behavior for 0.5 and 1.0 wt% and large viscosity increase reaching 3.75 and 5.5 times the base fluid viscosity at 5 °C and 60 °C, respectively, with 1 wt%. The nanofluids A.G–MWCNT and COOH–MWCNT present good stability, as well as an increase in transport properties, optimized at a concentration close to 0.25 wt% and the COOH–MWCNT nanofluids can be stabilized simply by changing the water pH.

A Comparison of Empirical Correlations of Viscosity and Thermal Conductivity of Water-Ethylene Glycol-Al2O3 Nanofluids.

Because of their superb thermal conductivity, nanofluids are seen as new generation of cooling mediums in many engineering applications. It is well established that even a small amount of nanoparticles mixed with a base fluid may result in distinct thermal conductivity enhancement. On the other hand, addition of nanoparticles to the base fluid results in its substantial viscosity increase. Therefore, it is very difficult to evaluate the relative importance of viscosity and thermal conductivity of the nanofluid on convective heat transfer performance. In order to estimate such resultant impact properly, it is necessary to develop reliable correlation equations for predictions of these two thermophysical properties of nanofluids. In this paper, the thermal conductivity and dynamic viscosity of five fluids, i.e., pure water, ethylene glycol (EG) and three mixtures of water and EG with volume ratio of 40:60, 50:50 and 60:40 have been experimentally determined. The aforementioned fluids served as base fluids in nanofluids with Al2O3 nanoparticles at the concentration of 0.01%, 0.1% and 1% by weight. A set of 20 correlations for prediction of thermal conductivity and dynamic viscosity of base fluids and corresponding nanofluids has been developed. Moreover, present results have been confronted with literature data and predictions made by use of carefully selected recognized literature correlations.

Viscosity and rheology of the ethylene glycol based nanofluids with single-walled carbon nanotubes

The work is devoted to the experimental study of the viscosity and rheology of nanofluids based on ethylene glycol with single-walled nanotubes. Polyvinylpyrrolidone is used as a dispersant. The weight concentration of nanotubes ranged from 0.01 to 1%. In all cases, the weight concentration of the dispersant was controlled. The measurements were carried out in the temperature range from 20 to 40°C. It was shown that at all weight concentrations the solution of ethylene glycol and dispersant is a Newtonian liquid, and at a maximum concentration (4%) the viscosity of the solution is two and a half times higher than the viscosity of ethylene glycol. At the same time, all the studied nanofluids turned out to be non-Newtonian and have a pseudoplastic character. It was established that ultrasonic treatment of nanofluids leads to partial degradation of the dispersant and a decrease the base fluid viscosity. The degree of this degradation increases with increasing ultrasonic processing power. With the considered low weight concentrations of nanotubes, the dependence of the viscosity coefficient of the nanofluid on temperature is determined by the corresponding dependence of the base fluid.

Effects of Temperature and Particles Concentration on the Dynamic Viscosity of Graphene-NiO/Coconut Oil Hybrid Nanofluid: Experimental Study

In practice, lubricants are used to minimize the friction and wear of frictional surfaces. The disposal of mineral-based lubricating oil possesses environmental issues and forced the development of bio-degradable lubricating agents. The simultaneous mono-dispersion of metallic and metal oxides nanomaterials into lubricating agents may concurrently reveal superior thermo-physical and rheological characteristics. This paper proposes an experimental and theoretical investigation on the dynamic viscosity enhancement of flat platelets textured Graphene/NiO-coconut oil hybrid nanofluids. The results reveal that the dynamic viscosity enhancement of hybrid nanofluids increases with nanomaterial concentration and decreases with temperature. The squat hybrid nanomaterial concentration has less collusion probability and dynamic contact between the mono-dispersed hybrid nanomaterials as it has enough interfacing gaps to conquer superficial surface energy. The high nanomaterial concentration revamps the formation of lamellar-composite agglomerated particles and enhances the dynamic viscosity of base fluid. Further, a theoretical correlation is recommended to estimate the dynamic viscosity of hybrid nanofluid with minimum margin of deviation using artificial neural network (ANN).

Effect of initial susceptibility and relaxation dynamics on radio frequency alternating magnetic field induced heating in superparamagnetic nanoparticle dispersions

Radiofrequency alternating magnetic field (RFAMF) induced heating of superparamagnetic nanoparticle dispersions (magnetic nanofluids) have attracted wide attention due to its superior potential for various industrial and bio-medical applications. Here, we probe the role of initial susceptibility and relaxation dynamics on RFAMF induced heating efficiency of magnetic nanofluids containing oleic acid capped single domain Fe3O4 magnetic nanoparticles (MNP) with nearly similar saturation magnetization values. Our results suggest that the initial susceptibility of MNP plays a major role in RFAMF induced heating efficiency and the variation of MNP size dependant relaxation dynamics alone is not sufficient to account for the field induced heating efficiency. Calculations on quasi-static hysteresis loops revealed a decrease in initial susceptibility with increasing MNP loading due to enhanced dipolar interaction, which resulted in the observed decrease in heating efficiency with increasing MNP concentration. The effect of relaxation dynamics on SAR, probed by varying the base fluid viscosity, showed that the heating efficiency is largely unaffected with increasing medium viscosity for magnetic nanofluids with Neel dominated relaxation modes, whereas heating efficiency decreased by ∼70% for magnetic nanofluids with Brownian dominant relaxation modes. This study attempts to decouple the individual contributions of initial susceptibility and relaxation dynamics and the results obtained are beneficial for designing magnetic nanofluids with enhanced magneto-thermal conversion efficiency.

Experimental study on stability and rheological behaviour of hybrid Al2O3-TiO2 Therminol-55 nanofluids for concentrating solar collectors

In this paper, an experimental study on rheological behaviour and stability analysis of Al2O3-TiO2 Therminol-55 hybrid nanofluid for use in solar collectors has been done. Various hybrid nanofluid samples with varying concentration of 0.05 wt%, 0.075 wt%, 0.1 wt%, 0.25 wt%, 0.5 wt% were prepared using two step technique. Particle size distribution was experimentally determined using Smoluchowski approximation. Zeta potential (ZP) measurements were performed using univette and it was found that all hybrid nanofluid samples have ZP values in the range of 68.5 mV to 57.64 mV after 3 h of preparation, 64.3 mV to 48.36 mV after 72 h of preparation, 54.52 mV to 34.43 mV after 7 days of preparation. Flow behaviour was studied by varying shear rate from 10s−1 to 500 s−1 and it was found that all hybrid nanofluid samples possess Newtonian behaviour. With the increase in nanoparticle concentration, viscosity of nanofluid increases. Further dependence of viscosity on temperature is determined and it was found that increase in temperature causes decrease in viscosity and approaches to base fluid viscosity at higher temperature An increase in viscosity of 24% for 0.5 wt% and 2.2% for 0.05 wt% as compared to pure Therminol-55 at 20 °C was found which decreases to 15%–0.07% at 145 °C. The viscosity increments are insignificant at elevated temperatures as such candidature of Al2O3-TiO2 Therminol-55 hybrid nanofluid as heat transfer fluid is more strengthen and widens its scope of utility.