Temperature-dependent Thermophysical Properties Research Articles

Numerical study of the influence of the geometrical aspect ratio and nanoparticles diameter on forced convection in a micro-channel heat sink of a nanofluid water/CuO based on a Brownian diffusion model

In order to cool electronic equipment with a high efficiency we can use the flow of a nanofluid in a rectangular micro-channel heat sink. The paper reports the results of the study of a hydrodynamically fully developed laminar forced convective heat transfer flow in two different geometries G1and G2. The study is numerical and was achieved using as nanofluid with and a single-phase approach. Calculations were first made with constant thermo-physical properties at and then made using temperature and nanoparticles diameter dependent thermo-physical properties based on a Brownian diffusion model. A three-dimensional conjugate heat transfer model was used and numerical simulations were based on a finite volume method. The simulations were made for a range of Reynolds numbers , for nanoparticle diameter in the range of and for a heat flux through the bottom surface of the heat sinks .The results of thermal and hydrodynamic fields show that nanofluids can provoke an increase in the local and average Nusselt numbers, a decrease of bottom surface local temperature and a slight decrease of the shear stress on the wall, particularly in the case of geometry G2. At the end of the study, the best geometry, volume fraction of nanofluid and nanoparticle diameter to be recommended for cooling were found based on minimum total thermal resistance of the micro-channel heat sink.

A hybrid approach portraying the dynamics of free convection condensation around a circular cylinder

We introduce a hybrid framework to model the fluid dynamics of free convection condensation of saturated steam outside a circular cylinder. The liquid film is modeled analytically, and the adjacent vapor flow field is resolved numerically. The model incorporates temperature-dependent thermophysical properties of the condensate. We explore the subtle role of Jakob number (Ja) and Weber number (We) in the two-phase flow and establish the criteria for dynamic similarity of the flow field with two new dimensionless numbers, viz., free-fall Reynolds number and similarity number. For fixed base Prandtl number of the condensate, the increases in the subcooling rate with Ja and the cylinder's surface area to volume ratio with We cause film thickening. We develop a theoretical correlation to predict the average film thickness (δm). We identify entrainment and bypass zones in the vapor flow field demarcated by a separating streamline. The entrainment zone's streamlines converge to the interface, yielding a net condensate drainage. The bypass streamlines never reach the interface and reduce the condensation efficiency. The results show that the tangential velocity is dominant within the liquid film, the radial velocity is dominant within the vapor flow field, and they are of the same order at the interface. We locate the point of flow separation influenced by a surface tension-induced adverse pressure gradient. The location of the flow separation point shifts upstream, and the separating streamlines become steeper with the increase in We. Our investigation reveals the zone of tangential flow reversal near the interface, promoted with increasing We.

Similarity transform-based numerical analysis of natural convection over an inclined flat plate using nanofluid*

ABSTRACT Nanofluids serve as a working medium in many state-of-the-art heating and cooling systems, where natural convection is a primary medium of thermal energy transfer. Based on the review of recently published literature, the present study is devoted to heat transfer analysis, based on similarity transformations and numerical solutions. The study aims to provide reliable, predictive analytical expressions for heat transfer coefficients and heat transfer rates in a schematic of the natural convection phenomenon. The objective is to analyse laminar free convection across a stagnant Al2O3-water nanofluid layer, spread over an inclined plane surface and exposed to the ambient. A novel similarity transformation method is applied to laminar boundary layer flow, capable of handling coupled influences of flow parameters, thermal boundary conditions and temperature-dependent thermophysical properties. This analysis also considers the effects of concentration and shape factor of nanoparticles on heat transfer. The physical properties are transformed into equivalent (temperature-dependent) physical property factors, along with similarity transformations of velocity and temperature fields. The fifth-order Runge-Kutta method is used to solve the coupled governing equations. The solutions are compared with predictive formulae for wall temperature gradients, heat transfer rates, and the convection heat transfer coefficient. Calculations based on predictive formulae agree well with published data.

A data-driven intelligent learning algorithm for simultaneous prediction of aerodynamic heat and thermo-physical property parameters

It is of great importance and challenging to simultaneously determine time-varying aerodynamic heat and temperature-dependent thermo-physical property parameters with high accuracy, for the optimization of thermal protection systems of hypersonic vehicles. However, it is difficult to directly measure these parameters under high temperature conditions. It is an effective way to determine thermo-physical property parameters and aerodynamic heat by solving inverse problems, based on measurable or easily measured transient temperatures. However, the prediction error of these parameters may be too large, if the measurement error is large, due to the thermal inertia. To deal with this issue, an intelligent algorithm is proposed to simultaneously predict the aerodynamic heat and thermo-physical property parameters for the thermal protection systems of hypersonic vehicles, based on the temperature measurement information. It combines a genetic algorithm and a machine learning algorithm, and the genetic algorithm is employed to update the relevant parameters in the neural network. By training the neural network, the relationship among the predicted parameters and transient temperatures could be established. Thereafter, the aerodynamic heat subjected to the outer surface of the aircraft and the temperature-dependent non-linear thermo-physical property parameters could be predicted. Examples are given to verify the present algorithm. The results show that this work provides an accurate and efficient method for simultaneously determining the aerodynamic heat and thermo-physical property parameters for the thermal protection system of a hypersonic vehicle. The prediction errors of aerodynamic heat and thermo-physical property parameters are much smaller than the measurement errors, when there are relatively large measurement errors in the input data.

Analysis of visco-inelastic biphasic fluid flow in wire coating process

To ensure the safety of data transmission, wires and fibers undergo a coating process to shield against potential damage. This process is critical in fields such as telecommunications, power transmission, and electronics, where durability and insulation are key factors. The current investigation is focused on the coating process by employing Eyring–Powell fluid in the presence of the magnetic field. The governing equations are developed by employing the biphasic (Buongiorno) model and temperature-dependent thermophysical properties. These equations are subsequently transformed into dimensionless form and tackled numerically. The study extensively explores critical aspects including shear stress rate, flow rate, and heat transfer rate for pertinent parameters. Furthermore, utilizing the response surface methodology, the optimization of shear stress and heat transfer rates in coated wire is pursued. This approach determines optimal levels for the viscosity parameter, Eyring–Powell fluid parameter, and thermophoresis parameter. The analysis concludes that the best outcomes are achieved by minimizing the viscosity parameter while maximizing the Eyring–Powell fluid parameter.

Quantifying laser irradiation-induced temperature field of particle reinforced metal matrix composites

While particle-reinforced metal matrix composites (PMMCs) are composed of particles and matrix with distinctly different thermomechanical properties, the thermal differences and coupled interactions between individual phases greatly determine the thermal characteristics of PMMCs under laser irradiation. In this work, we quantify the temperature evolution characteristics within SiCp/Al under laser irradiation by microstructural thermal finite element simulations and experimental investigation. Specifically, a 2D thermophysical FE model of laser-SiCp/Al interaction for the two-phase PMMCs material under laser irradiation is developed, which incorporates the temperature-dependent thermophysical properties of particles, matrix and interfaces, along with the considerations of the shape and distribution characteristics of particles, as well as the comprehensive thermal conditions. Furthermore, a 3D equivalent thermal FE model for experimental validation of predicted laser-induced temperature of SiCp/Al is developed, based on the derived equivalent properties. Meanwhile, an in-situ temperature measurement system is constructed for exploring temperature evolution characteristics during the on-going laser irradiation process, which validates a derivation of 1.7 % of predicted temperature by the equivalent thermal FE model. Finally, the impact of laser processing parameters on the temperature field of SiCp/Al is addressed. These findings provide valuable insights for understanding the thermal mechanisms of PMMCs under laser irradiation, and also the parameter optimization for laser processing of PMMCs.

Numerical assessment of hydrothermal and entropy generation characteristics of graphene quantum dots nanofluid in a microchannel heat sink incorporating secondary channels and ribs

Efficient heat dissipation from electronic chips is essential for enhancing their performance and longevity. Significant progress has been achieved through the introduction of nanofluids and microchannel heat sinks. However, there is still a need for nanofluids that demonstrate exceptional thermal properties and stability. Graphene quantum dots nanofluid, an innovative carbon-based coolant with zero-dimensional nanostructures, presents promising features such as excellent chemical stability, surfactant-free preparation, superior thermal properties, and minimal impact on rheological characteristics. This study explores, for the first time, the hydrothermal behavior and entropy generation of graphene quantum dots nanofluid in a microchannel heat sink comprising secondary flow channels and ribs. To this end, a three-dimensional conjugate heat transfer model is built using ANSYS Fluent software, and the governing equations are solved using the finite volume method. The simulations are carried out considering temperature-dependent thermophysical properties under different concentrations ranging from 0 to 0.5 % and Reynolds numbers ranging from 100 to 500. The results reveal that the maximum bottom wall surface temperature decreases by 5.88 K, while the heat transfer coefficient improves by 24.9 % compared to the base fluid. Moreover, the total entropy generation reduces by 14.7 %. On the other hand, the pressure drop increases by 43 %. Overall, the highest increment in Performance Evaluation Criteria is 10.8 % at a Reynolds number of 100 and a concentration of 0.5 %, making this particular condition suitable for practical applications.

Analysis of the tri-hybrid Maxwell nanofluid flow with temperature-dependent thermophysical characteristics on static and dynamic surfaces employing Levenberg-Marquardt artificial neural networks

Using the Levenberg-Marquardt Artificial Neural Network (LM-ANN) model, this study applies computational neuroscience to the analysis of flow, heat, and mass transport characteristics. The novel characteristics of MHD Maxwell tri-hybrid nanofluid passing through static and moving wedge with temperature-dependent thermophysical properties (thermal conductivity, viscosity, diffusivity, and electrical field) in permeable, radiative, and mixed convection processes are investigated in this paper. Nonlinear PDEs are transformed into nonlinear ODEs using similarity variables. A dataset for the LM-ANN is generated across various scenarios by varying parameters such as the temperature-dependent viscosity parameter ( 0.07 − 0.1 ) , variable diffusivity parameter ( 0.4 − 2.5 ) , thermal buoyancy parameter ( 0.1 − 0.5 ) , nonlinear thermal buoyancy parameter ( 0.2 − 0.5 ) , thermal radiation ( 1 − 1.5 ) , buoyancy ratio parameter ( 0.2 − 0.5 ) , chemical reaction parameter ( 1 − 3 ) , and Schmidt number ( 1 − 3 ) using the Bvp5c numerical algorithm. The testing, training, and validation procedure of LM-ANN is utilized to examine the estimated solutions of specific situations, and the proposed algorithm is then validated. After that, the proposed LM-ANN is validated using regression analysis, MSE, and histogram analysis. The prescribed approach impeccably mirrors the recommended and cited findings, evincing a precision level within the realm of 10−9. Results indicate that increasing the permeability parameter from 1 to 1.2 and the temperature-dependent thermal conductivity parameter from 0.4 to 2.5 enhances the Nusselt number. Additionally, increasing the chemical reaction parameter from 1 to 3 leads to an increase in the Sherwood number. The significance of this study lies in its potential applications in industries such as aerospace, chemical processing, and energy systems, where efficient heat and mass transfer processes are crucial. For instance, the findings can be applied to enhance cooling techniques in high-performance aerospace components, optimize reactor designs in chemical plants, and improve thermal management in power generation systems.

Dynamic simulation of unsteady Casson–Carreau fluid flow considering temperature-dependent variable-properties and thermo-solutal mixed convection over flat and slendering sheets

The present investigation delves into the intricate interplay between surface effects and fluid dynamics, focusing on the flow characteristics of Casson and Carreau fluids endowed with temperature-dependent thermophysical properties. Specifically, the study explores the ramifications of radiative, mixed convection, and magnetized processes on heat and mass transfer phenomena. A comprehensive mathematical model is developed to analyze the behavior of Casson–Carreau fluids in conjunction with microscopic particles and gyrotactic microorganisms over both flat and slender surfaces. Leveraging similarity transformations, the governing equations are transformed into dimensionless form, facilitating numerical solutions using the bvp5c solver in MATLAB. The ensuing numerical and graphical analyses elucidate key physical quantities, including local skin friction coefficients, gyrotactic microorganism density, Nusselt number, and Sherwood number, across a spectrum of physical parameters. Notably, the investigation underscores the profound influence of flat surfaces on flow patterns and highlights the heightened consumption of fluid particles with increasing variable diffusivity and thermal conductivity. Moreover, enhanced values of parameters such as variable motile microorganism diffusion coefficient, Brownian motion parameter, and temperature-dependent thermal conductivity parameter are found to augment the Nusselt number, indicative of intensified heat transfer rates. This research underscores the imperative of comprehending the intricate dynamics of fluid flow and heat transfer, offering actionable insights for enhancing engineering designs and addressing multifaceted challenges across domains encompassing chemical engineering, environmental science, and biomedical applications.

Heat transfer performance of supercritical CO2 in a vertical U-tube

Supercritical carbon dioxide (sCO2) is taken as an excellent working medium for efficient and compact energy conversion devices. However, heat transfer performance (HTP) of sCO2 in a vertical U-tube is intricate owing to dramatic variation of its temperature-dependent thermophysical properties. In this study, flow and heat transfer performance (FHTP) of sCO2 in a vertical U-tube is studied with an improved shear stress transfer model. Additionally, the impacts of operational parameters (heat flux q, mass flux G and pressure P), flow directions and bending diameters (dbend) of U-tube on FHTP are investigated. In both directions, the differences in local pressure drop caused by buoyancy effect and thermal expansion are analyzed deeply. The results demonstrate that the bend section can disturb flow and vortexes persist in downstream, thus improve the HTP. However, an apparent heat transfer deterioration zone can be observed in the ascending section. Under both directions, the average heat transfer coefficient (havg) raises with the growing G and P and decreasing q and dbend, while the total pressure drop (ΔPtotal) rises with the raising G and q as well as decreasing P. Moreover, the U-tube with down-up direction obtains higher havg and lower ΔPtotal than up-down.

Estimation of thermophysical properties of a pouch-type Li-ion battery using an inverse methodology

The growing popularity of electric vehicles highlights the crucial role of batteries. Effective battery thermal management is crucial for improving performance, reliability, and safety, especially in tropical areas where overheating is a key challenge. This necessitates a comprehensive understanding of the thermophysical properties of batteries. The present study concerns the estimation of the temperature-dependent orthotropic thermophysical properties (kx , ky , kz , cp ) of the active material in a pouch-type Li-ion battery using an inverse methodology. An experimental study is conducted on a commercial AMP20M1HD-A Li-ion battery to measure the surface temperature at various locations using thermocouples. The forward model consists of the three-dimensional unsteady conduction problem and is solved in COMSOL using experimental boundary conditions. The data generated is used to train an Artificial Neural Network, which acts as a replacement for the forward model. The Metropolis Hasting-Markov Chain Monte Carlo algorithm along with the Bayesian inference inverse model is used for analyzing the posterior distribution and the average estimates for thermophysical properties are obtained. The temperature dependence study shows a significant correlation between temperature and battery thermophysical properties. The accuracy of the employed inverse model is validated by obtaining the surface temperature using the estimated thermophysical properties and comparing it with the measured surface temperature.

Investigation of heat and mass transfer of oldroyd – 8 constant fluid in wire coating process employing response surface methodology

Wire coating is widely used for electrical insulation, shock protection, preventing leakage, and facilitating smooth current flow. This study aims to evaluate the applicability of Oldroyd-8 constant fluid for wire applications in a magnetic field using a pressure-type die. Based on the Buongiorno model with a constant pressure gradient and temperature-dependent thermophysical properties, governing equations are developed. These equations are transformed into dimensionless form and solved numerically. The study thoroughly investigates key features, including momentum, thermal distribution, nanoparticle volume fraction, and shear stress rate. Also, this study employs Response Surface Methodology to optimize heat transfer and shear stress rates in coated wire. Quadratic models, developed through a central-composite design, determine optimal levels for the Oldroyd-8 constant fluid parameter and nanofluid parameters, ensuring optimal heat transfer and shear stress rates for the melt. Nanofluid parameters contribute to an improvement in the thermal distribution profile. Optimal heat transfer and shear stress rate occur when the nanofluid parameters are minimized, and non – Newtonian fluid parameter is maximized.

Application of Caputo fractional approach to MHD Casson nanofluid with alumina nanoparticles of various shape factors on an inclined quadratic translated plate

The present study aims to examine the effect of convective heat transfer of nanofluid past an inclined plate. This paper scrutinizes heat transfer over an inclined surface of alumina nanofluids under the influence of radiation and magnetic fields with temperature-dependent thermophysical properties. The mathematical findings of velocity and temperature distributions are examined and visualized using non-dimensional flow parameters. The core of the research is to know the impact of using shape effects of alumina nanoparticles with a variety of base fluids like water, ethylene glycol, and engine oil. The outcomes concluded that the friction of the non-Newtonian viscous fluid decreased with increasing the inclination of the surface. The governing equations of the flow have been developed by using a few approximations such as Boussinesq's, and Roseland's. Using the dimensional analysis, the initial governing equations are simplified to dimensionless partial differential equations. A fractional model is developed using the Caputo fractional derivative. The solution of the proposed fractional partial differential equations is obtained in terms of special functions, Wright function, and Mittag-Leffler function by using the Laplace transformation method. Based on the interpretation, it is found that a reduction in velocity is observed with an increase in the angle of inclination i.e., γ = π/3 to γ = π/2. From the analysis, it is found that alumina/engine oil can carry higher temperatures than compared to other nanofluids and thus is a good option for heat transfer devices.

Numerical simulation on coking process of coke oven with external flue gas recirculation

The coking behaviour and NOx emission characteristics of the coke oven are of great significance for coke production. Based on the realisation k-epsilon turbulence model, the P-1 radiation model, the species transport model with eddy dissipation, and the thermal NOx model. A comprehensive model for traditional regenerative coke oven was established with reversing mode and external flue gas recirculation model considering temperature-dependent thermophysical properties. The convective term of model equations was the discretised using the second-order upwind scheme, while the others were applied by the central difference scheme. The coking behaviour of the coke oven with external flue gas recirculation was numerically solved through the SIMPLE algorithm, and the effects of reversing period and external flue gas recirculation ratio on the coking behaviour were explored. When increasing the reversing period, the mean temperature of the vertical flue increases, and the coking time decreases, but the temperature uniformity of the carbonisation chamber becomes worse. As the external flue gas recirculation ratio increases, the average temperature of the vertical flue decreases, and the NOx concentration at the outlet decreases, yet the coking time increases. These results would provide useful information for guiding the improvement of coke oven operation and reducing NOx emissions.

Influence of Lanthanum Additives on the Temperature Dependence of Thermophysical Properties and Changes in the Thermodynamic Functions of Lead Babbitt BLa (PbSb15Sn10)

Influence of Lanthanum Additives on the Temperature Dependence of Thermophysical Properties and Changes in the Thermodynamic Functions of Lead Babbitt BLa (PbSb15Sn10)

Modeling the effect of shape deformation induced by gravity on the evaporation of pendant and sessile drops

Pendant and sessile drops form a spherical cap only in the absence of gravity. The effect of gravity on drop shape is often neglected on the basis of the assumption that the drop size is smaller than the capillary length [Lc=(σ/gρ)1/2], although the deformation may not be fully negligible even in those cases. This paper focuses on evaluation of the effect that deformation due to gravity has on the evaporation characteristics of pendant and sessile drops. The drop shape is described by the Bashforth–Adams equation, a non-linear second order ordinary differential equation, which is solved numerically using a Runge–Kutta method with variable time steps. Under quasi-steady approximation, the species and energy conservation equations in the gas phase have analytical solutions, even for temperature-dependent gas thermophysical properties, once the solution of a basic Laplace problem is known. The Laplace equation is solved in axial symmetric geometry by using COMSOL Multiphysics®, for a wide range of drop sizes and contact angles, yielding vapor distribution, vapor fluxes, and evaporation rates. Comparison with the results from drops of same size in microgravity (i.e., having a spherical cap shape) shows that the effect is also perceptible for drops with a size smaller than the capillary length and that it can become quite important for those with larger sizes. Complementary results are found for sessile and pendant drops with respect to wall wettability, suggesting that the phenomenon can be analyzed using a unitary approach.

Numerical Simulation of Graphene-Nanoplatelet Nanofluid Convection in Millimeter-Sized Automotive Radiator

The depletion of fossil fuels and environmental considerations in transportation sector motivate the researchers to enhance the efficiency and performance of the automotive systems. However, the poor thermal performance of conventional coolant poses a limitation in the development of energy-efficient vehicle due to the cooling constraint. In the present study, a comprehensive numerical study is conducted to scrutinize the convective performance of graphene nanoplatelets (GnP) nanofluid in millimeter-sized automotive radiator, aiming to enhance the understandings on the underlying physical significance of the suspension of graphene-based nanoparticle in water for the performance enhancement of automotive radiator. The temperature-dependent thermophysical properties of GnP-water nanofluid is predicted via existing correlations, while a modified viscosity correlation is developed. ANSYS Fluent is employed in the present numerical simulation to investigate the effects of various pertinent parameters such as Reynolds number, nanoparticles aspect ratio, tube aspect ratio and tube hydraulic diameter on the heat transfer performance of the radiator. Double precision and second-order upwind scheme with inclusion of viscous heating, and convergent criteria of 10˗6 are adopted for the present simulation. It is observed that the convective performance of the radiator is significantly enhanced by increasing Reynolds number and nanoparticle volume fraction while decreasing the aspect ratios of nanoparticle and radiator tube, with an enhancement rate as much as 1816%. Therefore, it is evident that the suspension of GnP intensifies the heat transfer performance of millimeter-sized automotive radiator, which could possibly lead to a more efficient radiator that is smaller and lighter.

Flow instability in high-Prandtl-number liquid bridges with fully temperature-dependent thermophysical properties

The axisymmetric steady two-phase flow of a differentially heated thermocapillary liquid bridge in air and its linear stability is investigated numerically, taking into account dynamic interfacial deformations in the basic flow. Since most experiments require a high temperature difference to drive the flow into the three-dimensional regime, the temperature dependence of the material properties must be taken into account. Three different models are investigated for a high-Prandtl-number thermocapillary liquid bridge with nominal Prandtl number ${\textit {Pr}}=28.8$ : the Oberbeck–Boussinesq (OB) approximation, a linear temperature dependence of all material properties and a full nonlinear temperature dependence of all material properties. For all models, critical Reynolds numbers are computed as functions of the volume of the liquid bridge, its aspect ratio, its dimensional size and as a function of the strength of a forced axial flow in the ambient air. Under most circumstances the OB approximation overpredicts and the linear model underpredicts the critical Reynolds number, compared with the model based on the full temperature dependence of the material properties. Among the main influence factors are the proper selection of the reference temperature and, at larger temperature differences, the temperature dependence of the viscosity of the liquid.

Effect of calcium addition on temperature dependence of thermophysical properties and changes in thermodynamic functions of lead babbit B (PbSb15Sn10)

Effect of calcium addition on temperature dependence of thermophysical properties and changes in thermodynamic functions of lead babbit B (PbSb15Sn10)

Temperature-dependent thermophysical properties of CPAS and tissues relevant to cryobiology

Temperature-dependent thermophysical properties of CPAS and tissues relevant to cryobiology