Viscosity Correlation Research Articles

Experimental Studies and Analytical Analysis of Thermophysical Properties of Ethylene Glycol–Water-Based Nanofluids Dispersed with Multi-walled Carbon Nanotubes

The present study investigates the thermal conductivity and dynamic viscosity of ethylene glycol–water solutions dispersed with oxidized multi-walled carbon nanotubes. The physico-thermal properties and Mouromtseff number (Mo) were used to evaluate the heat transfer properties of the nanofluids. Ethylene glycol–water mixtures were chosen as base fluids, and the volume fraction of ethylene glycol varied from 100 % to 0 % (pure water). Oxidized multi-walled carbon nanotubes in weight percentages of 0.0625, 0.125, 0.25, and 0.5 were dispersed in ethylene glycol–water mixtures to achieve the best stability. The stability of the nanofluids was monitored by UV–Vis spectroscopy for 2 months. The dispersion of multi-walled carbon nanotubes in the base fluids resulted in a significant improvement in thermal conductivity. To derive correlations for thermal conductivity and dynamic viscosity, 1 500 data points were collected for all possible combinations of temperature, weight percent of multi-walled carbon nanotubes, and ethylene glycol content. The Mouromtseff number (Mo) showed that dilute nanofluids at low concentrations are the most effective heat transfer medium in turbulent flow.

Experimental study and rheological behavior of engine oil enriched with MWCNT and ZnO nanoparticles: Proposing a new relationship and sensitivity analysis

In the research, the viscosity of MWCNT and ZnO with a ratio of 30:70/SAE50 nanofluid (NF) at volume fractions (VFs) of 0–1% and different temperatures are studied experimentally. A prominent feature of this study is the reduction of NF viscosity at low VFs. By adding nanoparticles (NPs) at VF = 0.0625 % and 0.125 %, NF viscosity decreases (maximum reduction of 18 %). At VFs above 0.25 %, the NF viscosity increases so that at VF = 1 %, the highest viscosity increase of 14 % is happened. At the shear rate (SR) of 3999 s−1 and VF = 1 % and 0.0625 %, the NF viscosity decreases by 76.79 % and 76.11 %, respectively. In this research, a new correlation for the relative viscosity is presented. The value of R2 in the proposed equation for predicting the viscosity of the NF is 0.9247 indicating its exactitude. Other results of this study can be attributed to the low sensitivity of the investigated NF to temperature variation will result in the high performance of mentioned NF in industrial applications with a wide temperature range.

Performance Evaluation of Plate Heat Exchanger Using CuO-DI Water Nanofluid

Abstract Experimental and numerical investigations have been carried out for performance evaluation of plate heat exchanger (PHE) using CuO-DI water nanofluid at different volume concentrations of (ϕ = 0, 0.005, 0.01, 0.03, 0.05, and 0.07) for the Reynolds number, Re = 71–1350, Prandtl number, Pr = 3.18–13.7, and at fixed inlet temperatures of hot and cold fluids Thi = 60 °C and Tci = 20 °C, respectively. The two main influential thermo-physical properties of the nanofluid, namely, dynamic viscosity and thermal conductivity obtained for various volume fractions at different temperatures, are further utilized for performance analysis of the PHEs. The thermo-hydraulic performance of PHE is evaluated based on the J.F. factor. According to experimental and simulated results, volume concentration, ϕ = 0.03 is found to be the optimum concentration of nanofluids. The individual correlations for Nusselt number, friction factor, dynamic viscosity, and thermal conductivity in terms of nanofluid volume fraction are proposed based on the experimental results.

Permeability measurement of the fracture-matrix system with 3D embedded discrete fracture model

In this work, we performed the pulse-decay experiment on a fractured shale core and applied the 3D embedded discrete fracture model (EDFM) to simulate the experiment process. The irregularly rough fracture surface was depicted in detail using a 3D scanner. Then the fracture surface profile was imported in the discrete fracture network model to simulate the flow process in the fracture-matrix system realistically. History matching was efficiently performed to simultaneously obtain porosity and permeability for the matrix and fracture. Gas properties after applying nanopore confinement were obtained by modifying Sutton's viscosity correlation with sensitivity analysis on the pore diameter ranging from 2 to 50 nm. Nanopore confinement results in low matched permeability due to viscosity reduction in the matrix-only porous media. The fracture-matrix system complicates the interpretation of nanopore confinement impact on flow behavior in shale reservoirs. Different scenarios of the highly fractured and matrix-dominated systems were discussed in detail by constructing the digital twin model.

Shear viscosity and Stokes-Einstein violation in supercooled light and heavy water.

We report shear viscosity of heavy water supercooled 33K below its melting point, revealing a 15-fold increase compared to room temperature. We also confirm our previous data for the viscosity of supercooled light water and reach a better accuracy. Our measurements, based on the spontaneous Brownian motion of 350nm spheres, disagree at the lowest temperature with the only other available data, based on Poiseuille flow in a narrow capillary, which may have been biased by electro-osmotic effects. Here we provide a detailed description of the experiment and its analysis. We review the literature data about dynamic properties of water (viscosity, self-diffusion coefficient, and rotational correlation time), discuss their temperature dependence, and compare their decoupling in the two isotopes.

Comparative heat transfer analysis of γ -Al2O3−C2H6O2 and γ -Al2O3−H2O electroconductive nanofluids in a saturated porous square cavity with Joule dissipation and heat source/sink effects

Inspired by the applications in electromagnetic nanomaterials processing in enclosures and hybrid fuel cell technologies, a mathematical model is presented to analyze the mixed convective flow of electrically conducting nanofluids (γ-Al2O3−H2O and γ-Al2O3−C2H6O2) inside a square enclosure saturated with porous medium under an inclined magnetic field. The Tiwari–Das model, along with the viscosity, thermal conductivity, and effective Prandtl number correlations, is considered in this study. The impacts of Joule heating, viscous dissipation, and internal heat absorption/generation are taken into consideration. Strongly nonlinear conservation equations, which govern the heat transfer and momentum inside the cavity with associated initial and boundary conditions, are rendered dimensionless with appropriate transformations. The marker-and-cell technique is deployed to solve the non-dimensional initial-boundary value problem. Validations with a previous study are included. A detailed parametric study is carried out to evaluate the influences of the emerging parameters on the transport phenomena. When 5% γ-Al2O3 nanoparticles are suspended into H2O base-fluid, the average heat transfer rate of γ-Al2O3−H2O nanoliquid is increased by 25.63% compared with the case where nanoparticles are absent. When 5% γ-Al2O3 nanoparticles are suspended into C2H6O2 base-fluid, the average heat transfer rate of γ-Al2O3−C2H6O2 nanofluid is increased by 43.20% compared with the case where nanoparticles are absent. Furthermore, when the heat source is present, the average heat transfer rate of γ-Al2O3−C2H6O2 nanofluid is 194.92% higher than that in the case of γ-Al2O3−H2O nanofluid.

Interfacial interaction–driven rheological properties of quartz nanofluids from molecular dynamics simulations and density functional theory calculations

Correlations of the shear viscosity of quartz nanofluids with particle concentration, particle size, and temperature were investigated with molecular dynamics simulations and density functional theory (DFT) calculations. A new understanding to the experimentally concluded correlations was addressed in terms of microscopic particle–water interfacial interaction in three aspects. First, the viscosity of quartz nanofluids at different particle concentrations, particle sizes, and temperatures were simulated using the equilibrium molecular dynamics simulations method to reproduce the experimental observations. At the same particle size, the nanofluid viscosity decreases significantly with temperature and increases with nanoparticle volume concentration, and at the same volume concentration, the nanofluid viscosity increases with the decrease of particle size. Second, DFT calculations confirm a stronger particle–water interaction than that among water molecules. The important role of particle–water interaction in the viscosity determination of nanofluids was revealed. Finally, a correlation was proposed to fit the simulated results and compared with earlier two-parameter correlations. One parameter in the correlation is indeed a constant, while the other is a function of SiO2–water interaction energy. Our study proposes a physical basis for the experimentally concluded correlations on the viscosity of nanofluids.

Decoupling Segmental Dynamics and Ionic Transport for Superionic Anhydrous Proton Conductors of Polyoxometalate-poly(ethylene glycol) Nanocomposites.

Superionic anhydrous proton conductors can be obtained from the complexation of nanoscale polyoxometalates (POMs) and poly(ethylene glycol) (PEG) in the "polymer in salt" regime. The reduced energy barrier of H+ hopping is facilitated from the increased H+ concentration and shortened inter-POM distances. POMs with identical structure/size (≈1nm) but different charge densities are complexed with PEG, respectively, with concentrations ranging from 10 to 60 % wt. Increasing trends of viscosities can be observed with the rising charge densities of POMs due to the increasing confinement strength on PEG substrate from POMs. Fractional Walden rule is further applied to analyze the viscosity and proton conductivity correlations, and microscopic mechanisms of proton conduction for PEG-POM nanocomposites are revealed: 1) ion transport is highly associated with polymer chain dynamic for POMs concentrations ranging from 10 to 30 % wt.; 2) ionic conduction is largely decoupled from chain dynamic of polymer matrix for concentrations ranging from 40 to 60 % wt. with Walden plots shifted to the superionic regime. The decoupling of proton transport from polymer segment dynamics allows the simultaneous enhancements of the nanocomposites' mechanical properties and proton conductions, providing guidelines for the rational design of anhydrous proton conductors with integrated functionalities.

Evaluation of fatigue characteristics of asphalt mixtures using Cracking Tolerance index (CTIndex)

Evaluation of the cracking potential of asphalt mix during the design phase can considerably limit the fatigue cracking and increase the service life of the flexible pavement. Thus, attention needs to be paid to employing a simple yet reliable performance test indicator. Indirect Tension Asphalt Cracking Test (IDEAL-CT) is one such emerging test method and is widely used in research across the world. The present study examines the potential of using the cracking tolerance index (CTIndex) as an appropriate parameter to explain the fatigue resistance of mixtures with both unmodified and modified binders. This test can be conducted using a Marshall testing machine or multispeed tester, routinely used for asphalt mixture design in India and many other countries. To evaluate the effectiveness of this parameter, fatigue resistance indicators for different binders, i.e., recovery at 3.2 kPa stress level (R3.2) from multiple stress creep and recovery (MSCR) test, fatigue life (TNf3.5) from the time sweep (TS) test at 3.5% strain, fatigue life at 2.5% (LNf2.5), and 5% (LNf5) strain from linear amplitude sweep (LAS) test, as well as for different mixtures, i.e., fatigue life from Indirect tensile fatigue test (ITFT) at 150 microstrain were considered. Two unmodified (viscosity grade 30, viscosity grade 40) and three modified (polymer, crumb rubber, sasobit) binders were evaluated for their fatigue parameters which were further correlated with CTIndex. The CTIndex exhibited good to excellent correlations (R2 ∼ 0.85 to 0.92) with the fatigue lives of the binders and the mixtures. To examine the effect of rheology and chemistry of the binder on the CTIndex, correlations of complex shear viscosity using Dynamic Shear Rheometer (DSR) at 60 °C and asphaltenes content from Thin-layer chromatography with flame ionization detector (TLC-FID) with CTIndex were explored. Viscosity, asphaltenes content, and elastic recovery of the binders depicted good correlations (R2 ∼ 0.88) with CTIndex, indicating higher cracking tolerance of stiffer yet elastic binders. Further, the sensitivity of CTIndex to binder type, binder content, aggregate gradation, and test temperature was examined. Overall, the values of the CTIndex displayed less variability (coefficient of variation < 10%) in this study.The observed sensitivity of CTIndex to asphalt mix parameters and the correlations of the CTIndex with fatigue resistance indicating parameters suggested that the CTIndex is an effective parameter for evaluating the fatigue characteristics of asphalt mixes.

Viscosity measurement and correlation research of one biodiesel component (methyl octanoate) with five 1-alcohols

Alcohols are commonly used as additives in biodiesel to improve its viscous and dense properties for better applicability in the industrial field. In this work, experimental investigations are conducted on the dynamic viscosities for the binary mixture of methyl octanoate (one component of biodiesel) with one 1-alcohol containing 1-propanol, 1-butanol, 1-pentanol, 1-hexanol, and 1-heptanol from 293.15 to 333.15 K at atmospheric pressure. The excessive viscosity shows negative deviation from the ideal solution for each binary system and is fitted with the Redlich-Kister equation. The McAllister three-body model is used for the kinematic viscosity correlation of binary mixtures. To acquire dynamic viscosity, the experimental density is measured and correlated as a function of temperature and mole fraction of methyl octanoate. Meanwhile, the McAllister three-body model, Heric's model, Frenkel model, and Grunberg-Nissan model are used to correlate the viscosities of the mixtures. Furthermore, some research has also been done on the improvement of the prediction performance for McAllister three-body model based on the studied systems.

A novel empirical equation for the effective viscosity of nanofluids based on theoretical and empirical results

In practice, nanofluids' thermal conductivity and viscosity are the most important parameters in engineering applications. Viscosity affects pumping performance. Theoretical viscosity correlations are widely used in numerical studies. However, existing correlations show an underestimation of the actual viscosity compared to the measurement results. Although many nanofluid viscosity correlations have been developed, there is no generally accepted correlation. This paper reviews the theoretical, numerical, and experimental viscosity correlations and proposes a new correlation based on an analysis of approximately 1200 experimental and 4000 theoretical data tested for about 50 types of nanofluids in the temperature range 273–333 K and particle diameters 2–300 nm. The studied volume fraction range for the nanofluids was up to 10%. Existing correlations take into account the impact of up to two to three parameters The new viscosity correlation is proposed to predict the effective viscosity of nanofluids based on regression analysis of theoretical and experimental viscosity results, and it considers several factors that significantly affect the effective viscosity of nanofluids, such as nanoparticle diameter, density, temperature, types of nanoparticles, and base fluid.

A comprehensive study to predict the rheological behavior of different hybrid nano-lubricants: A novel RSM-based analysis

In this study, two hybrid nano-lubricants MWCNT-ZnO (10:90)/oil 5W50 and MWCNT-MgO (35:65)/oil 5W50 are compared in terms of rheological behavior and viscosity. Temperature conditions are 5–55 °C and volume fractions are in the range of ϕ = 0.05–1%. Based on the curve fitting on experimental data by using of the power-law model in τ- γ̇ curves, it is shown that both nano-lubricants are non-Newtonian (shear thinning). Comparison of relative viscosity (μr) and viscosity (μnf) curves in different laboratory conditions shows that the slope of viscosity changes of the two above mentioned nano-lubricants have the same trend and even close values. In addition for time-saving goals and to have higher accuracy for both nano-lubricants, a new viscosity correlation relationship is proposed based on response surface methodology (RSM) with R2 > 0.999. According to results, the maximum error in prediction of μnf for MgO-MWCNT (65:35)/oil 5W50 is 8% and on the other hand, maximum 10% error reported for estimating the μnf of MWCNT-ZnO (10:90)/oil 5W50.

Entropy Scaling for Viscosity of Pure Lennard-Jones Fluids and Their Binary Mixtures

In this work, entropy scaling approaches for viscosity of pure Lennard-Jones (LJ) fluids and their mixtures have been investigated. To do so, we have employed reliable viscosity database available in literature for the pure LJ fluids, and performed the molecular dynamics simulation to generate viscosity database over a wide range of thermodynamic condition for the LJ mixture fluids. It has shown that for the pure LJ fluid, the entropy scaling approaches using the macroscopic properties for the reduction of viscosity yield noticeably better collapse of data than the one using the zero-density viscosity in the dense fluid region. In addition, we have developed viscosity correlations based on these approaches. It has been obtained that the correlations of macroscopic properties approaches predict the pure LJ fluid viscosity with average absolute deviation of around 4% more coming from the low-density states, whereas it is of around 8.50% more coming from the dense states for the other one. Finally, the viscosity correlations have been applied to the LJ mixtures. Interestingly, the correlations of macroscopic properties approaches are able to provide good estimations for all mixtures studied. However, it deteriorates for the viscosity of dense mixtures when the other employed.

Enzymatic synthesis of wet-resistant lignosulfonate-starch adhesives

This work describes a new method for improving the properties, mainly the wet-resistance, of starch-based adhesives using enzymatically polymerized lignosulfonates. A correlation of viscosity with molecular weight was found, allowing simple control of enzymatic polymerization of lignosulfonates. Incorporation of lignosulfonates polymerized from 29 kDa to > 4500 kDa using laccase led to a considerable increase in wet-resistance (from 15 to 20 min for the laminating glue and from 150 to 1200 min for the bag glue) while not affecting (for the laminating glue) or even improving the bonding time (from 80 to 60 s for the bag glue). Finally, the effect of active laccase in the final adhesive was investigated by enzymatic inactivation using NaN3 before formulation of the glue, as well as by extra laccase addition. In conclusion, this study shows that enzymatically polymerized lignosulfonate is a robust strategy for improving wet resistance of starch-based adhesives.

Water-Based Graphene Oxide-Silicon Hybrid Nanofluids-Experimental and Theoretical Approach.

In the current paper, a new hybrid nanofluid based on graphene oxide sheets and silicon nanoparticles is proposed for thermal applications. GO sheets and Si nanoparticles with different mixture ratios are dispersed in distilled water. Dynamic viscosity is measured at temperatures within the range 20–50 °C and the values are compared to the results available in the literature. The results indicated that the viscosity increases with increasing the mixture ratio of graphene oxide. A new correlation for the dynamic viscosity based on the experimental findings is proposed. Finally, the criteria for the performance of new hybrid nanofluid for thermal applications are analyzed.

The Development of Forecasting Technique for Cyclic Steam Stimulation Technology Effectiveness in Near-Wellbore Area

The analytical review has shown that the scientific inquiry for effective technologies for high-viscosity oil field development is a critical task of the present-day oil industry. The paper presents a technique for determining the expediency and effectiveness of deploying the near-wellbore cyclic steam stimulation technology for oil recovery enhancement. The method involves the calculation of process parameters of the technology cycle and the comparative analysis of cumulative oil production before the treatment (base case) and after its deployment. Separately, the work focuses on studying the impact of dynamic oil viscosity over the entire temperature range on the technology effectiveness and expediency. The laboratory studies showed dynamic viscosity correlation dependencies for six different oils of the Nozhovskaya group of oil fields (Russian Federation) characterized as viscous and highly viscous. As a case study of the proposed method application, a numerical simulation of the technology deployment was carried out for six oil samples. The calculations determined inexpediency of cyclic steam stimulation for one of the samples since oil well downtime for workover operation prevailed over the time of near-wellbore cooling.

Physicochemical Properties of Explanted Silicone Oil After Use as an Intraocular Tamponade.

PurposeWe studied the effects of exposure to biological media within the eye, such as contamination with lipophilic and amphiphilic substances, on the physicochemical parameters of silicone oil used as an intraocular tamponade.MethodsWe removed silicone oil with visible emulsification from 15 patients and measured each sample for shear viscosity and surface tension. We induced in vitro emulsification with balanced salt solution. Using the zeta-potential, we evaluated the emulsion droplet's electrochemical stability. We repeated all experiments in a control group of unused oil. Electrochemical stability and viscosity were additionally measured in oils with high-molecular-weight components.ResultsWe recovered silicone oils implanted between 30 and 506 days (mean, 196 days). Viscosity did not differ between explanted and control groups. Surface tension and zeta potential remained unchanged (P = 0.61 and P = 0.84, respectively). All oils showed a significant correlation of viscosity with temperature (P < 0.01 for all). Oils with added high-molecular-weight components showed a lower emulsion stability.ConclusionsProlonged contact to hydrophilic biological media does not alter high-viscosity silicone oil's physicochemical parameters. During typical durations of intraocular use, lipophilic and amphiphilic molecules had no deleterious effect. The addition of high-molecular-weight components might decrease the silicone oil's electrochemical emulsion stability, possibly easing the confluence of emulsion droplets.Translational RelevanceAlthough the physicochemical parameters of silicone oils are not altered after clinically relevant durations within the eye, emulsion stability significantly differs between oil types.

Comparison between homogeneous and separated flow models of isobutane flowing through adiabatic capillary tubes

Capillary tubes have been widely used as expansion devices in small-scale refrigeration and heat-pump systems. However, adiabatic flow through a capillary tube is extremely complicated, despite its simple geometry. This work presents a comparative study on the homogenous flow model and separated flow model, which were used to simulate the flow of isobutene (R600a) through adiabatic capillary tubes. The influence of different combinations of friction factor and two-phase viscosity correlations, and the effect of metastable flow on the flow characteristics were investigated. The predicted mass flow rate was lower when the separated flow model was used. The separated flow model performed better in predicting a mass flow rate over 2 kg·h&lt;sup&gt;−1&lt;/sup&gt;. The Colebrook friction factor correlation combined with the Dukler or McAdams viscosity correlation yielded smaller deviations of 5.43%, 5.49% and 5.44%, 5.43% when ignoring and considering the metastable flow, respectively. Additionally, the homogenous flow model adopting the Bittle and Pate friction factor and Dukler viscosity correlations achieved the highest accuracy with a mass flow rate under 2 kg·h&lt;sup&gt;−1&lt;/sup&gt;. The mean error was 4.12% in the case without metastable flow, and 3.37% in the case with metastable flow.

PEG 400-Based phase change materials Nano-Enhanced with Alumina: An experimental approach

This article depicts several novel experimental data on thermophysical properties of Al2O3/PEG 400 nanoparticle enhanced fluids. Both temperature variation and nanoparticle mass concentration are investigated as main factors for influencing the viscosity and heat capacity of studied nanofluids. Different approaches were used in this study to compare the data and to outline the theoretical interpretation of our experimental data.Rheological experiments at two temperatures, 288.15 K and 298.15 K show a Newtonian behavior for PEG 400 and the fluids with Al2O3 nanoparticles, while the increase in viscosity is up to 32 %, depending on the mass concentration of nanoparticles. The experimental work involved also several heating–cooling cycles and it was noticed that viscosity decreases while temperature increase and a small hysteresis (up to 10 %) was noticed for higher loadings of nanoparticles. Viscosity data analysis involved a comparison with well-known correlations as well as a VFT analysis followed by a 3D analysis of all experimental data. Specific heat for most of the nanofluids increase both with nanoparticle mass concentration and temperature; exception is the 5 %wt alumina–PEG 400. The goodness of theoretical correlations for viscosity are discussed and new correlations for viscosity and specific heat are proposed.

Multivariate Statistical Modeling of Crude Oil Viscosity and Mole Percent Components for Reservoir Fluids

This study presents multivariate statistical modeling of PVT properties in a Hydrocarbon Reservoir. Traditionally, these properties are modeled by correlating them with the changes in pressure and temperature associated with them. However, these changes are often a direct corollary of the changing composition as each component’s presence and/or absence contributes to the overall property of the fluid system. In this work, Multiple Linear and Multiple Nonlinear regression models were used to develop a correlation for the crude oil viscosity and the mole percent of the components as they change with pressure and temperature. A fluid system was modelled using the PVT Package of Integrated Production System Modelling (IPM) Suite. The model was then used to perform a differential liberation test simulation to predict the changes in composition of the crude oil. The composition included three lumped crude oil fractions. After the PVT modelling, the generated PVT Composition was used to perform the Multivariate statistical analysis (MVA) and modelling.Two MVA techniques were compared – the Multiple Linear Regression (MLR) and Multiple Non-Linear Regression (MLNR).Analysis of residuals generated from the prediction run based on both techniques showed that the multiple linear regression method had trending residuals, contrary to the law of parametric estimation upon which it is based. However, the multiple nonlinear regression yielded 100% correlation with adequate residual trend and is thus recommended for adaptation to distinct fluid systems. It is imperative to note that the accuracy of this adaptive PVT modeling and prediction is hinged primarily on the accuracy of the PVT model used to estimate the compositional variation.