Correlations For Thermophysical Properties Research Articles

Modeling with generalized flux theory for computational investigation of thermal enhancement in fluid with tri‐, di‐, and mono‐nanoparticles

AbstractTo study the influence of several factors (tri‐nanoparticles and relaxation time related to momentum, thermal, and concentration) on non‐Fourier transport of heat and mass, mathematical models are developed. The cases of tri‐, di‐, and mono‐nanofluids are considered. Flow and transport scenarios are translated into mathematical equations for which conservation laws and correlations for thermophysical properties are used. Boundary layer simplifications are used to approximate these mathematical models. The nondimensional set of problems is numerically solved using the finite element method (FEM). The solutions that are convergent and mesh‐free are obtained. The outcomes are compared to existing benchmarks. There is excellent consistency between the current and published results. The viscoelastic behaviors related to momentum, thermal, and solutal relaxation times are examined. It is also investigated how tri‐nanoparticles improve heat transmission in flow. The wall shear stresses for the mono‐, di‐, and tri‐nanofluids are calculated against momentum relaxation time. It is observed that tri‐nanofluid exerts the highest stress on the surfaces over which it flows. Therefore, while using these fluids, the surface should be ensured to bear the stresses; otherwise, failure of the system may take place. Thus, industrial applications and additional capability of surface be ensured. This looks at influence the Deborah number on the fluid motion. Deborah number is straightforwardly connected with relaxation time and it is found that higher is Deborah number lower will be the speed of fluid. As a consequence, viscous region will be narrow down. Thus, viscous dominant region is controllable by the using fluid of higher relaxation time. A significant enhancement in the thermal performance of Maxwell fluid occurs via the dispersion of tri‐nanoparticles ().

Experimental investigation on Ag NPs-rGO-water/ethylene-glycol hybrid nanofluids used in solar applications

In the current study, an experimental study on synthesis, characterization, stability and thermo-physical properties of silver nanoparticles - reduced graphene oxide dispersed in water and ethylene glycol mixture (Ag NPs-rGO/W + EG) is presented. Ag NPs-rGO sheets (1:1) synthesized and characterized by SEM method were prepared using a mixture of water and ethylene glycol (W + EG (1:1)) as base fluid and low-viscosity sodium carboxymethyl cellulose (CMCNa) as surfactant. Dynamic light scattering (DLS) measurements were performed to estimate particle size distribution of the Ag NPs-rGO sheets in the nanofluids. Polydispersity index (PI) was also used to estimate the average uniformity of particle size in the hybrid nanofluids. The measurements of the thermo-physical properties were carried out at temperatures varying from 293.15 K to 323.15 K and concentrations of Ag NPs-rGO sheets of 0.050, 0.075 and 0.10 wt% respectively. The results indicated that the thermo-physical properties of Ag NPs-rGO/W + EG hybrid nanofluids were generally dependent on concentration and temperature. The thermal conductivity was enhanced by about 1.13 times at 323.15 K and 0.10 wt%. The maximum increase in viscosity and density were 2.33 and 1.066 times compared to the base fluid at 293.15 K and 0.10 wt%. Based on the density measurements, the specific heat values of the Ag NPs-rGO/W + EG hybrid nanofluids were computed, recording a reduction up to 6.541 % at 323.15 K and 0.10 wt% compared to the water+ethylene glycol solution. The thermo-physical properties were compared to theoretical models and experimental results from literature. Based on the experimental data, new correlations for thermo-physical properties were established. Furthermore, this study analyzes the effectiveness of Ag NPs-rGO/W + EG hybrid nanofluids in a flat-plate solar collector (FPSC) in both laminar and turbulent flows by calculating the thermal efficiency.

Computational investigation on transport of heat energy by flow of dusty Carreau fluid with nanoparticles using finite element method

Thermal performance of the working fluid depends on its thermal conductivity which can be enhanced by dispersion of nanoparticles. Therfore, the role of the simultaneous suspension of AA7072 and AA7072 and AA7072/AA7075 is analyzed in Carreau fluid, which has shear rate dependent viscosity and contains dust particles. The nanoparticles AA7072 is combination of aluminium, zinc and other alloys with ratio 98%:1%:1%, respectively. Whereas nanoparticles AA7075 is the combination of aluminium, zinc, magnesium, and copper in ratio 90%:6%:3%:1%, respectively. Further, the nanoparticle AA7072 in Carreau liquid form homogenized mixture which is mono nanofluid whereas nanoparticle AA7075 in Carreau liquid form homogenized mixture called hybrid nanofluid. Thermal radiation have significant impact on the temperature of AA7072 and AA7072/AA7075. The Carreau-constitutive model and correlations for thermo-physical properties are used with conservation laws for fluid and dust phases for modelling purposes. The governing equations are non-dimensionalized, and their numerical solutions are derived using the finite element method (FEM). These derived solutions are used to predict the behavior of physical quantities and flow fields for both AA7072/AA7075 and AA7072 nanoparticles. An increasing tendency in the temperature of dust particles in AA7072/AA7075 is greater than in AA7072. The simulations have exposed that AA7072/AA7075 is more radiative than AA7072. The velocity interaction parameter has an increasing tendency in affecting the transport of dust particles.

Modeling the viscosity of ionic liquids using combined friction theory with perturbed hard-chain equation of state and neural network approaches

Fast and accurate prediction and correlation of thermophysical properties are always important concerns for researchers and engineers. This work is the extension of our earlier friction theory (FT)-based approach for estimating the dynamic viscosities of pure ionic liquids using a perturbed hard-chain equation of state. The model used three molecular parameters along with 5 correlation coefficients in the friction terms. The correlation coefficients were obtained using 167 data points at 0.1 MPa with an average absolute deviation (AAD) of 0.61 % and then used to predict the viscosity values at higher pressures. Using the FT-based model, 2907 experimental viscosity data for 20 pure ILs were predicted. The calculations were carried out in 273–373 K range and pressures up to 298.9 MPa for 2907 data points with an AAD of 2.63 %. The present FT-based model was not able to accurately predict the viscosities of ILs outside the temperature range used for the fit procedure. Also, comparing the precision of our FT-based model with two rough-hard-sphere theory-based models of Hosseini et al. and Hossain-Teja as well as the group-contribution method led to AADs of 2.46 % (for 2664 data points), 2.65 % (for 1605 data points), 3.25 % (for 890 data points), and 7.73 % (for 2558 data points, respectively. Viscosities of several mixtures of IL + IL type were also correlated using the present model along with some simple combining equations and a binary interaction parameter as well. The AAD of the calculated viscosities from the experimental ones was found to be 5.10 % for 960 data points examined. In addition, a neural network was trained on 3074 data points to represent the viscosity of studied pure ILs. The artificial neural network (ANN) structure utilized two layers, four input parameters, and 13 neurons for each layer. This specific structure of ANN was carefully designed to ensure an optimal performance in predicting the viscosity of ILs. The overall AAD was obtained 1.44 %.

Measurements and Correlations of Thermophysical Properties for Multicomponent Solvent/Live Bitumen Mixtures

Measurements and Correlations of Thermophysical Properties for Multicomponent Solvent/Live Bitumen Mixtures

Performance Analysis on Heat Transfer Enhancement of Energy Pile with Nanofluid

Energy pile is a novel ground heat exchanger with the pipes buried within building piles. The heat transfer performance of energy piles is essential for the ground source heat pump system’s efficiency, economy, and reliability. Nanofluids can improve the convective heat transfer inside the heat exchange pipe and the heat transfer of ground heat exchangers. The improvement of the thermophysical properties of nanofluids has been studied previously. However, only a few research studied the heat transfer performance analysis of a spiral coil energy pile with nanofluids as the heat carrier. Hence, this study will investigate the heat transfer enhancement of the energy pile contributed by a nanofluid. The analytical model of a spiral coil energy pile with seepage and the correlations of thermophysical properties of the nanofluid were employed. The heat transfer capacity, wall temperature, and the outlet temperature of an energy pile under different factors were studied. The results showed that by adopting the nanofluid, the heat transfer of the energy piles increased by 1.21 % ∼ 3.12 %, and the pile wall temperature increased by 0.22 °C–0.47 °C. The increase in the outlet temperature caused by the nanofluid is more significant than that caused by increasing the spiral pitch. It is also is more constant than that caused by increasing the seepage velocity. This work can contribute to improving the heat transfer performance of energy piles.

Thermal and solutal analysis in power law fluid under non-Fourier's diffusion conditions

Non-Fourier thermal and solutal transport in non-Newtonian power law rheological fluid is model via conservations laws under boundary layer approximations. The correlations for thermo-physical properties of pure, power law fluid and hybrid nano-structures are solved numerically with approximated conservations laws. The finite element method (FEM) is used for simulations purpose. The convergence is ensured and mesh-free analysis is performed. Iterative processes are done under computational tolerance 10−5. Relaxation phenomenon plays a significant role in controlling thermal and solutal boundary layer thickness. The impact of Joule heating can be minimized via thermal relaxation time. The impact of heat generation of temperature is similar to the impact of constructive chemical reaction on solutal transport.

Thermal enhancement in hybrid nano-polymer using novel models for hybrid nanoparticles

Novel correlations for thermophysical properties of base fluid (micropolar fluid) and hybrid nanostructures are used to analyze the impact of the inclusion of copper oxide and titanium dioxide thermal enhancement in the polymer with microstructures. The polymers are assumed to be characterized by micropolar rheological equations. The models from governing laws are derived and are simplified by boundary approximations. The boundary conditions are based on no-slip. The finite element method (FEM) is used for numerical solutions. The mesh and convergence analysis are tested. The convergent solutions are further utilized for the simulation process. The wall shear and couple stresses are examined and the heat transfer rate is visualized. This study has predicted thermal optimization due to the simultaneous inclusion of copper oxide and titanium dioxide nanoparticles. The hybrid nanofluid is an efficient working fluid than the pure fluid. However, the presence of hybrid nanoparticles in micropolar fluid makes the viscous region wider. It is found that nano polymers with CuO experience less resistive force due to porous medium as compare to hybrid nanopolymers (CuO−TiO2−polymers). The angular motion slows down as the vortex viscosity parameter is increased. However, this decrease is more noticeable in hybrid nano-polymers than that in nanopolymers.

Generating a Machine-Learned Equation of State for Fluid Properties.

Equations of state (EoS) for fluids have been a staple of engineering design and practice for over a century. Available EoS are based on the fitting of a closed-form analytical expression to suitable experimental data. The mathematical structure and the underlying physical model significantly restrain the applicability and accuracy of the resulting EoS. This contribution explores the issues surrounding the substitution of machine-learned models for analytical EoS. In particular, we describe, as a proof of concept, the effectiveness of a machine-learned model to replicate the statistical associating fluid theory (SAFT-VR Mie) EoS for pure fluids. To quantify the effectiveness of machine-learning techniques, a large set of pseudodata is obtained from the EoS and used to train the machine-learning models. We employ artificial neural networks and Gaussian process regression to correlate and predict thermodynamic properties such as critical pressure and temperature, vapor pressures, and densities of pure model fluids; these are performed on the basis of molecular descriptors. The comparisons between the machine-learned EoS and the surrogate data set suggest that the proposed approach shows promise as a viable technique for the correlation and prediction of thermophysical properties of fluids.

Experimental investigation and correlations of thermophysical properties for bio-aviation kerosene surrogate containing n-decane with ethyl decanoate and ethyl dodecanoate

Physical fuel surrogate is always necessary to be proposed to match physical properties such as liquid density, viscosity and surface tension of the real bio-aviation kerosene for the characteristics of their spray performance. Thus, it is crucial to determine the related thermophysical properties over a wide temperature range for a further development of the fuel spray system. Therefore, binary surrogates of n-decane with ethyl decanoate and ethyl dodecanoate were proposed and their thermophysical properties were investigated in the present work. The liquid density was obtained using a U-tube densimeter in the temperature range between (293.15 and 433.15) K. The liquid kinematic viscosity and surface tension were investigated simultaneously by surface light scattering (SLS) method in the temperature range from (313 to 423) K. Additionally, the refractive index was measured by a refractometer in the temperature range from (278.15 to 358.15) K. Furthermore, correlations for these properties were developed as the function of mole fraction and temperature. The relative deviations of experimental liquid density, kinematic viscosity, surface tension and refractive index from those calculated according to the correlations were within the range of ±0.2%, ±2%, ±1% and ±0.08%, respectively.

Heat transfer analysis using zinc Ferrite/water (Hybrid) nanofluids in a circular tube: An experimental investigation and development of new correlations for thermophysical and heat transfer properties

For heat transfer analysis, the thermal properties of the heat transfer fluid is aninterestingtopic of current research. The hybrid nanofluids have better effective thermal conductivity, which is being used to improve the heat transfer rate. This experimental study presents the heat transfer characteristic of aqueous Zinc Ferrite/water (ZnFe2O4/water) nanofluids. ZnFe2O4/waternanofluids were prepared, suspending hybrid nanoparticles in the basefluids with 0.01 wt% CTAB as surfactant with different weight concentrations i.e., (0.02, 0.05, 0.1, 0.2, 0.5 wt%). Detailed surface properties of ZnFe2O4/waternanofluids were characterized using EDS, TEM, and UV–vis spectroscopy. Experiments were conducted to find out the viscosity, thermal conductivity,and convective heat transfer coefficient of ZnFe2O4/waternanofluids using laminar flow in a tube geometry using constant heat flux (CHF) boundary condition. Results revealed 11.8% improvement in the thermal conductivity for ZnFe2O4/waternanofluids, whereas an enhancement of 42.99% was observed in the convective heat transfer coefficient using 0.5 wt% of the nanofluids.The thermal conductivity results indicate that ZnFe2O4/waternanofluids have higher thermal conductivity for all the studied nanofluids. From the experimental data, new correlations for finding the thermophysical properties and Nusselt number has been proposed. The novel correlation established will help scientists and engineers for further insight into future research.

Analysis of empirical correlations of thermophysical properties of water suspensions of aluminum oxide nanoparticles

Here, we consider the empirical relationships presented earlier in the literature that describe the thermophysical properties of H2O + Al2O3 nanofluids, such as viscosity and heat conductivity coefficients. The main parameters affecting these properties of nanofluid are considered to be the volume fraction of particles ϕ, fluid temperature T, and particle size dp. The suitability of approximation formulas for calculating the viscosity and heat conductivity coefficients is determined by comparing the data calculated by these formulas with the experimental results. The behavior of the analytical curves of thermophysical coefficients is analyzed in the following ranges of influencing parameters: 0 < ϕ ≤ 0.1, 280 K ≤ T ≤ 360 K, 1 nm ≤ dp ≤ 100 nm. Estimates of the degree of dependence of calculation results on the values of these parameters are given. Conclusions on the qualitative and quantitative reliability of the correlation formulas proposed in the literature, as well as on the limits of their applicability in the ranges of variation of the influencing parameters are drawn.

Measurement and correlation of thermophysical properties in aqueous solutions of some novel bio-based deep eutectic solvents (lactic acid/amino acids) at T = (298.15 to 313.15) K

Thermodynamic properties of novel bio-based deep eutectic solvents (DESs) and their mixture with other solvents is of great importance in extraction and pharmaceutical sciences. In the present study new class of these neoteric sustainable solvents composed of amino acids and lactic acid have been prepared, density and speed of sound data for neat lactic acid/alanine, lactic acid/glycine and lactic acid/histidine and their aqueous mixture have been measured over the entire composition range at T = (298.15, 303.15, 308.15 and 313.15) K. Based on these data, some of the thermodynamic properties including the excess molar volumes (VE), apparent molar volume (Vϕ), excess isobaric thermal expansion (αp,mE), the excess molar isentropic compressibility (κEs,m) and limiting apparent molar expansibility (ϕE,10) have been calculated. For all of the studied systems above, these important properties have been analysed based on various solute-solvent interactions, occurring between the components of the mixtures. Furthermore, it has been found that all the investigated DESs act as a structure-breaker in water over the whole temperature range using Hepler’s constant. The properties have been correlated by the Redlich-Kister type equations.

Characterization and modelling of density, thermal conductivity, and viscosity of TiN–W/EG nanofluids

Thermal conductivity, dynamic viscosity, and density of TiN nanofluids (NFs) with different base mediums have been characterized for the prospect of developing new thermophysical property correlations in this work. Characterizations of morphology and crystal structure of nanopowder were made using scanning electron microspore and X-ray diffractometer. Set of NFs was prepared in a base liquid mixture of water–ethylene glycol W/EG 60:40 and 40:60 by an ultrasound-assisted two-step method. Meter Group KD 2 Pro analyzer operated on transient line heat source method was used for the thermal conductivity test. The viscosity and density of NFs were measured with Anton Paar rotational rheometer MCR 302 and oscillating densimeter DMA 4500M. All experiments were implemented for volume fractions of NF between 0.25 and 1.0 vol% in the temperatures range of 293.15–333.15 K. The findings indicate that density and viscosity decrease with increasing temperature, whereas the thermal conductivity of nanofluids is enhanced depending on NP concentration. The W/EG 60:40 base mixture exhibited higher thermal conductivity enhancement and 40:60 base mixture had greater viscosity growth among all analyzed NFs. Moreover, the difference in base fluid fractions does not lead to a significant variance in the density ratios of NFs. Empirical correlations developed for examined properties with effects of particle concentration, temperature, and base liquid ratio are capable of accurately reproducing the properties data within 15% deviation.

Phase-Field Modeling of Freeze Concentration of Protein Solutions.

Bulk solutions of therapeutic proteins are often frozen for long-term storage. During the freezing process, proteins in liquid solution redistribute and segregate in the interstitial space between ice crystals. This is due to solute exclusion from ice crystals, higher viscosity of the concentrated solution, and space confinement between crystals. Such segregation may have a negative impact on the native conformation of protein molecules. To better understand the mechanisms, we developed a phase-field model to describe the growth of ice crystals and the dynamics of freeze concentration at the mesoscale based on mean field approximation of solute concentration and the underlying heat, mass and momentum transport phenomena. The model focuses on evolution of the interfaces between liquid solution and ice crystals, and the degree of solute concentration due to partition, diffusive, and convective effects. The growth of crystals is driven by cooling of the bulk solution, but suppressed by a higher solute concentration due to increase of solution viscosity, decrease of freezing point, and the release of latent heat. The results demonstrate the interplay of solute exclusion, space confinement, heat transfer, coalescence of crystals, and the dynamic formation of narrow gaps between crystals and Plateau border areas along with correlations of thermophysical properties in the supercooled regime.

Experimental investigation of hydronic air coil performance with nanofluids

The objective of this study is to experimentally characterize and compare the performance of a nanofluid comprised of Al2O3 nanoparticles with 1% volumetric concentration in a 60% ethylene glycol/40% water (60% EG) solution to that of 60%EG in a liquid to air heat exchanger. The test bed used in the experiment was built to simulate a small air handling system typical of that used in HVAC applications. Previously established empirical correlations for thermophysical properties of fluids were used to determine the values of various parameters (e.g. Nusselt number, Reynolds number, and Prandtl number). The testing shows that the 1% Al2O3 nanofluid generates a marginally higher rate of heat transfer than the 60% EG under certain conditions. At Re = 3000, the nanofluid produced a rate of heat transfer that was 2% higher than that of the 60% EG. The empirically determined Nusselt number associated with the convection in the coil tubing for the nanofluid follows the behavior predicted by the Dittus-Boelter correlation (R2 = 0.97), while the empirically determined Nusselt number for the 60% EG follows the Petukhov correlation similarly (R2 = 0.97). Pressure loss and hydraulic power for the nanofluid were higher than for the base fluid over the range of conditions tested. The exergy destroyed in the heat exchange and fluid flow processes were between 9% and 12% lower for the nanofluid than the base fluid over the tested range of Reynolds numbers.

Measurement and correlation of the physical properties of aqueous solutions of ammonium based ionic liquids

In this study, thermo physical properties such as density, viscosity, refractive index and surface tension of aqueous solutions of tetramethylammonium hydroxide (TMAOH), tetraethylammonium hydroxide (TEAOH), tetrapropylammonium hydroxide (TPAOH) and tetrabutylammonium hydroxide (TBAOH) was investigated as a function of temperature. These properties were measured in temperatures ranging from 298.15 to 333.15 K and the temperature was increased by an interval of 5 K from 298.15 K and after 303.15 K, it was increased by an interval of 10 K, while the concentrations of all the aqueous solutions were changed from 2.5 to 30 mass percent. The results revealed that the measured properties of all aqueous ILs are inversely related to temperature, while the increase in concentration had different effects on these properties. In the case of density, an increase in the concentration of ILs TMAOH and TEAOH increased their density, while the increase in the concentration of TPAOH and TBAOH decreased their density. On the other hand, the viscosities and refractive indices of all aqueous ILs increased with an increase in concentration, but the surface tensions decreased with the increase in concentration. The derived properties including thermal expansion and excess molar volume of all the aqueous ILs were determined using density data. The thermal expansion data showed an increasing trend with an increase in the temperatures and concentrations of ILs whereas the negative values of excess molar volumes decreased with an increase in temperatures. The correlation of thermo physical properties with temperatures exhibits a good agreement between experimental and predicted values.

The New Method for Correlation and Prediction of Thermophysical Properties of Fluids. Critical Temperature

On the basis of the linear free energy relationships theory and thermodynamics formulas, a new method predicting critical temperature (Tc) of pure fluids is proposed for the first time. Sixteen homologues of 616 substances have been regressed and correlation equations between Tc and molecular descriptors are obtained. The mean relative deviations of the 16 equations are from 0.01% to 2.73%, and most of them are under 2%. In addition, the squared correlation coefficients are from 0.90 to 0.98. Moreover, the equations are tested through cross-validation by the leave-one-out procedure and most of the squared correlation coefficients are greater than 0.90. The results reveal that the equations exhibit better effect with simple form of equation, high prediction accuracy, and definitude theory meaning. This study successfully combines macroscopic physical properties of fluids with their molecular microstructure and breaks through the experimental or theoretical application scope, perfecting calculation of criti...

Measurement and correlation of thermophysical properties of waste lubricant oil

Measurements of viscosity, density and surface tension of waste lubricant oil (WLO) were conducted at different temperatures. The dataset was constituted by nine WLO samples from different producers. The main objective of the work is the investigation of the temperature dependence of viscosity, including the glass transition, Tg, and dynamic crossover, Tx, temperatures. In addition, different correlations were evaluated to predict viscosity and surface tension starting from a property easily obtained such as density. WLO show rapid decrease of viscosity with shear rate, followed by an extensive and well defined Newtonian plateau. The temperature dependence of viscosity at the Newtonian plateau of WLO deviated from the Arrhenius behavior, and was accurately described by four different models: Williams–Landel–Ferry (WLF), MYEGA, power law and Ghatee. The minimum and maximum absolute average relative deviation (AARD) were 0.08% and 0.9%, respectively. Tg predicted by WLF equation varied between T=170.5K and T=198.7K, while MYEGA tends to predict lower Tg (about T=20K). The power law and Ghatee models estimate Tx nearly with the same accuracy. A ratio Tx/Tg of about 1.28±0.03 was obtained for WLO, which agrees with the literature. Waste oil is a moderately fragile glass forming fluid with a fragility parameter, m, ranging from 47.8 and 64.5. New correlations were developed for the prediction of viscosity and surface tension from density at different temperatures. AARD of 7% was observed for viscosity and 2% for surface tension.

Statistical correlations for thermophysical properties of Supercritical Argon (SCAR) used in cooling of futuristic High Temperature Superconducting (HTS) cables

High Temperature Superconducting (HTS) cables are emerging as an alternative to conventional cables in efficient power transmission. However, these HTS cables require cooling below the critical temperature of superconductors used to transmit larger currents. With the invention of high temperature superconductors whose critical temperatures are up to 134K (Hg based), it is a great challenge to identify a suitable coolant which can carry away the heating load on the superconductors. In order to accomplish such challenge, an attempt has been made in the present work to propose supercritical Argon (SCAR) as the alternative to cool the HTS cables. Further, a statistical correlation has been developed for the thermophysical properties such as density, viscosity, specific heat and thermal conductivity of SCAR. In addition, the accuracy of developed correlations is established with the help of few statistical parameters and validated with standard database available in the literature. These temperature dependent accurate correlations are useful in predicting the pressure drop and heat transfer behaviour in HTS cables using numerical or computational techniques. In recent times, with the sophistication of computer technology, solving of various complex transport equations along with the turbulence models became popular and hence the developed correlations would benefit the technological community. It is observed that, a decrease in pressure, density and viscosity are found to be decreasing whereas the thermal conductivity and specific heat increase significantly. It can be concluded that higher heat transfer rate and lower pumping power can be achieved with SCAR as coolant in the HTS cables.