Variable Thermal Conductivity Research Articles

Peristalsis of Carreau–Yasuda nanofluid possessing variable thermal conductivity regulated by electroosmosis via an expanding asymmetric channel

Peristalsis of non-Newtonian nanofluid via a non-uniform conduit has several applications in physiology and industry. This study proposes a mathematical model as well as exploration of the impacts of entropy generation for peristalsis of magneto nanofluid with temperature-dependent thermal conductivity via an expanding asymmetric channel. Buongiorno’s model for study of nanofluid flow has been adopted. Rheological aspects are accounted using the Carreau–Yasuda model due to its experimentally validated significance. Impacts of applied electric and magnetic fields have been taken into account. Thermophoresis, ohmic heating, viscous heating and Brownian motion effects are incorporated in the model. Numerical method is used via NDSolve in Mathematica after implementing the lubrication approach and Debye–Huckel linearization. The effects of embedded parameters on the flow, heat transfer, entropy generation and Bejan number are studied using graphical depictions. Outcomes indicate that a rise in electroosmotic parameter enhances heat transfer rate, whereas it reduces entropy generation and mass transfer rate at the boundary. Therefore, this study can provide basics to study nanofluidic systems which has applications in drug delivery. Increasing trends for temperature, heat transfer rate and entropy generation, while declining trends in the concentration of the particles are noted for higher joule heating.

Two-phase simulation of entropy optimized mixed convection flow of two different shear-thinning nanomaterials in thermal and mass diffusion systems with Lorentz forces

This research compares the momentum, thermal energy, mass diffusion and entropy generation of two shear thinning nanofluids in an angled micro-channel with mixed convection, nonlinear thermal radiation, temperature jump boundary condition and variable thermal conductivity effects. The RKF 45 approach was used to solve the Buongiorno nonlinear governing model. The effect of different parameters on the flow, energy, concentration, and entropy generating fields have been graphically illustrated and explained. The hyperbolic tangent nanoliquid has a better velocity than the Williamson nanofluid. The Williamson nanofluid has higher thermal energy and concentration than the hyperbolic tangent nanoliquid in the microchannel. The Grashof number, both thermal and solutal, increases the fluid flow rate throughout the flow system. The energy of the nanoliquid is reduced by the temperature jump condition, while the energy field of the nanoliquid is enhanced by the improving thermal conductivity value. The nanoliquids concentration rises as the Schmitt number rises. The irreversibility rate of the channel system is maximized by the variable thermal conductivity parameter.

Darcy-Forchheimer hybrid nanofluid flow in an asymmetric channel with an exponential heat source, variable thermal conductivity, and activation energy

Background Heat transfer in nanofluid flows plays a vital role in many industrial, medical, and manufacturing industries. Hybrid nanofluid (HNF) has a significant potential to enhance the thermal characteristics of several fluids employed in a wide range of thermal systems and thus uses reduced energy and provides increased sustainability. Also, the thermal conductivity of nanofluid depends on the mobility of nanoparticles and that can be improved by activation energy (AE) besides the latent micro convection. Literature reveals that the research works available on the enhanced heat transfer due to the appropriate combination of nanoparticles along with AE in an asymmetric channel is very limited. Aim This study aims to explore the impact of the AE and the variable thermal conductivity (VTC) on the HNF flow in an asymmetric channel with permeable walls. The effects of radiation, thermal conductivity, and exponential heat sources are also considered. Method An effective similarity transformation is used to convert the governing equations into a system of nonlinear ordinary differential equations (ODEs). The nonlinear ODEs with appropriate boundary conditions are solved numerically by a shooting method. Results The consequences of the physical parameters on the axial velocity, temperature, and species concentration are explained and are presented through graphs. In comparison to viscous fluid, the dual nanofluids have a 5.8% higher heat transfer rate with VTC parameter at the lower wall. However, the species concentration rate of HNF is 20.0% higher than that of viscous fluid with AE parameter.

Inclined Magnetic Field on Mixed Convection Darcy–Forchheimer Maxwell Nanofluid Flow Over a Permeable Stretching Sheet With Variable Thermal Conductivity: The Numerical Approach

The behavior of a Maxwell nanofluid in mixed convection Darcy–Forchheimer inclined MHD flow across a stretched sheet is investigated in this research study. In order to analyze heat and mass transfer, the inquiry takes into account a number of variables, including the magnetic field, variable thermal conductivity, activation energy, suction/injection, and nonlinear thermal radiation. The controlling nonlinear PDEs with BCs are converted via similarity transformation into nonlinear ODEs in order to solve the ensuing nonlinear ODEs. These ODEs are then solved using the shooting method and a fourth‐order Runge‐Kutta methodology. The study explores how fluid flow velocity is affected by magnetic field inclination and suction/injection effects. This is attributed to the strengthening of the magnetic field with an increase in the inclination angle α. Additionally, the imposed magnetic field generates an opposing force, known as the Lorentz force, which contributes to a reduction in the velocity curve. Furthermore, various parameters affect the profiles of concentration, temperature, velocity, and Nusselt number. A number of parameters are looked at, such as the response rate constant, mixed convection, buoyancy ratio, suction/injection, Brownian motion, Lewis number, and thermophoresis. Interestingly, the results show that activation energy and mixed convection parameters, respectively, have an increasing effect on concentration and velocity curves.

Mechanical regulation to interfacial thermal transport in GaN/diamond heterostructures for thermal switch.

Gallium nitride offers an ideal material platform for next-generation high-power electronics devices, which enable a spectrum of applications. The thermal management of the ever-growing power density has become a major bottleneck in the performance, reliability, and lifetime of the devices. GaN/diamond heterostructures are usually adopted to facilitate heat dissipation, given the extraordinary thermal conduction properties of diamonds. However, thermal transport is limited by the interfacial conductance at the material interface between GaN and diamond, which is associated with significant mechanical stress at the atomic level. In this work, we investigate the effect of mechanical strain perpendicular to the GaN/diamond interface on the interfacial thermal conductance of heterostructures using full-atom non-equilibrium molecular dynamics simulations. We found that the heterostructure exhibits severe mechanical stress at the interface in the absence of loading, which is due to lattice mismatch. Upon tensile/compressive loading, the interfacial stress is more pronounced, and the strain is not identical across the interface owing to the contrasting elastic moduli of GaN and diamond. In addition, the interfacial thermal conductance can be notably enhanced and suppressed by tensile and compressive strains, respectively, leading to a 400% variation in thermal conductance. More detailed analyses reveal that the change in interfacial thermal conductance is related to the surface roughness and interfacial bonding strength, as described by a generalized relationship. Moreover, phonon analyses suggest that the unequal mechanical deformation under compressive strain in GaN and diamond induces different frequency shifts in the phonon spectra, leading to an enhancement in phonon overlapping energy, which promotes phonon transport at the interface and elevates the thermal conductance and vice versa for tensile strain. The effect of strain on interface thermal conductance was investigated at various temperatures. Based on the mechanical tunability of thermal conductance, we propose a conceptual design for a mechanical thermal switch that regulates thermal conductance with excellent sensitivity and high responsiveness. This study offers a fundamental understanding of how mechanical strain can adjust interface thermal conductance in GaN/diamond heterostructures with respect to mechanical stress, deformation, and phonon properties. These results and findings lay the theoretical foundation for designing thermal management devices in a strain environment and shed light on developing intelligent thermal devices by leveraging the interplay between mechanics and thermal transport.

A WILLIAMSON NANOFLUID WITH MOTILE MICROORGANISMS ACROSS A VERTICAL EXPONENTIALLY STRETCHING POROUS SHEET WITH VARYING THERMAL CHARACTERISTICS

The present work demonstrates a boundary layer movement of an incompressible non-Newtonian Williamson nanoliquid. The boundary layer is around an exponentially stretching permeable vertical surface. Moving motile microorganisms are implicated in the movement throughout a permeable medium considering modified Darcy law. The buoyancy-driven flow is presumed, where the density is expressed as being multiplied by gravity and chosen as a linear function of heat, nanoparticle, and microorganism concentrations. Analogous to the exponentially stretching sheet, an exponential variable magnetic strength is taken normal to the surface. Variable thermal conductivity and mass diffusivity are considered together with chemical reactions. The motivation for this study arises from the involvement of microorganisms in the flow and the contribution of its density equation with the velocity, temperature, and nanoparticles system of equations with suitable boundary restrictions. The fundamental governing scheme of nonlinear partial differential equations (PDEs) is transferred to ordinary ones (ODEs) by employing convenient similarity transforms. These equations are analyzed by the homotopy perturbation method (HPM). Therefore, a major objective graphical formation of the distributions is concluded to recognize the impacts of the produced nondimensional physical factors. Some important physiognomies are concluded from the results. The nanoparticle distribution enhances most of the effective parameters and in turn improves heat transmission, which is a good finding that can be useful in several applications. Microorganisms tend to collect with the growth of the Lewis number and infinity value, whereas its condensation damps with the rise of the bioconductivity and the Peclet number. Those results can be useful in identifying factors that help to get rid of microbes, viruses, and harmful bacteria from surfaces.

Stochastic wave propagation in magneto-thermoelastic materials subjected to the change in electrical and thermal conductivity

This paper presents the results of an investigation that focuses on the stochastic wave propagation that occurs within an elastic medium when the thermoelectric properties are taken into consideration. It has been found that there is a clear association between the characteristics of electrical conductivity and thermal conductivity. As a result, the current topic focuses on the influence a magnetic field has on the variable thermal conductivity and electrical conductivity that exists within a material. This is done within the context of dual phase lag thermoelasticity. Several parameters are incorporated into the governing equations, which exhibit coupling. Thermal shock has been applied to the boundary of the medium that represents the non-traction barrier. At the border of the problem, stochasticity is imposed in order to make the problem appear more realistic. Within the boundary conditions, it is presumed that the white-noise function is present. Utilizing the Laplace transform method is the approach that is taken to address the issue. It is possible to determine the inverse transformations using numerical approximation approaches. Both graphical and visual analyses are performed on the dataset. In conclusion, graphical representations are utilized in order to make comparisons between the deterministic and stochastic solutions of all physical fields.

Thermal analysis of generalized Cattaneo–Christov theories in Burgers nanofluid in the presence of thermo-diffusion effects and variable thermal conductivity

Thermal analysis of generalized Cattaneo–Christov theories in Burgers nanofluid in the presence of thermo-diffusion effects and variable thermal conductivity

Molecular dynamics simulation of thermal transport properties of phonons at interface of Au-TiO<sub>2</sub> photoelectrode

Thermoplasmonics originating from the relaxation process of plasmon resonances in nanostructures can be utilized as an efficient and highly localized heat source in solar-hydrogen conversion, but there have been few researches on the interfacial heat transport properties of photoelectrode with the thermoplasmonics effect in a photoelectrochemical water splitting system. In this work, the effects of temperature, interfacial coupling strength and the addition of graphene layers on the interfacial thermal conductance of Au-TiO<sub>2</sub> electrodes are investigated by the non-equilibrium molecular dynamics simulation, and the variation of interfacial thermal conductance is analyzed by the phonon density of states. The results show that the interfacial thermal conductivity is increased by 78.55% when the temperature increases from 300 to 800 K. This is related to the fact that more low-frequency phonons participate in the interface heat transport, allowing more heat to be transferred to TiO<sub>2</sub> to promote the interface reaction. As the coupling strength of the Au-TiO<sub>2</sub> interface increases, the interfacial thermal conductivity of the electrode increases and then tends to stabilize. The interfacial thermal conductivity can be optimized by increasing the degree of overlap of the phonon state densities of Au and TiO<sub>2</sub>. The addition of a single layer of graphene can increase the interfacial thermal conductivity to 98.072 MW⋅m<sup>–2</sup>⋅K<sup>–1</sup>, but the addition of 2 and 3 layers of graphene can hinder interfacial heat transfer in Au and TiO<sub>2</sub> due to the interaction between the layers of graphene. When adding graphene layer, medium-frequency phonons and high-frequency phonons are stimulated to participate in the interfacial heat transfer, but with the increase of the graphene layers, the number of low-frequency phonons in a range of 0—30 THz decreases, and these low-frequency phonons make the greatest contribution to the interfacial thermal conductivity. The obtained results are useful in regulating the thermal transport properties of the photoelectrode interface, which can provide new insights into and theoretical basis for the design and construction of composite photoelectrodes.

Thermal transport properties of gas-filled silica aerogels.

Silica aerogel (SA), recognized as an efficient insulating material, is characterized by its extremely low thermal conductivity (TC) and high porosity, presenting extensive application potential in aerospace and building energy conservation. In this study, the thermal transport properties of gas-filled SA are explored using molecular dynamics (MD) methods. It is found that an increase in porosity leads to a significant decrease in TC, primarily due to enhanced phonon scattering and reduced material stiffness. Additionally, the TC of SA influenced by gas exhibits a pattern of initial decrease, followed by an increase, and then a decrease again, driven by complex interactions between gas molecules and pore walls, phonon localization, and scattering mechanisms. At a gas concentration of 80%, the TC in confined spaces is significantly increased by nitrogen, attributed to enhanced intermolecular interactions and increased collision frequency. The impact of gases on the TC of gas-solid coupled composite materials is also investigated, revealing that gas molecules serve as a "bridge" for phonons, playing a crucial role in reducing interfacial scattering and enhancing low-frequency vibrational modes, thus further enhancing heat transfer efficiency. The TC of these composite materials is primarily regulated by the gas-phase TC in response to temperature, while the response to strain is predominantly governed by variations in the solid-phase TC. These results provide essential theoretical support and design guidelines for the development and design of new high-efficiency insulating materials.

Mathematical modelling and heat transfer observations for Jeffrey nanofluid with applications of extended Fourier theory and temperature dependent thermal conductivity

The suspension of non-Newtonian materials with nanoparticles is important to enhance the thermal phenomenon in various engineering and industrial processes. The versatile research in nanomaterials provide different applications in thermal processes, heat exchangers, thermoelectric devices, HVAC systems, energy processes etc. Following to such novel motivations in mind, current research endorsed the enhancement in heat transfer due to suspension of Jeffrey nanofluid comprising the variable thermal conductivity. The cause of flow is associated to two disks attaining fixed distance. The modified developed relations for Fourier's hypothesis are utilized to model the problem. The flow problem is modeled with appliance of fundamental novel laws. By applying suitable transformations, corresponding differential equations are renovated into dimensionless forms which are solved with applications of analytic homotopic algorithm. The behavior of temperature and velocity due to various parameters is discussed. The numerical calculations have been done for wall shear force and Nusselt number. The results show that the velocity profile boosted due to variation of stretching ratio constant. The enhancement in heat transfer is observed due to Reynolds number. Moreover, the increasing observations for wall shear force in upper and lower disk surfaces are obtained against larger material parameter. The simulated results may find applications in improving heat transfer phenomenon, manufacturing systems, recovery processes, cooling systems, chemical phenomenon, fuel cells etc.

Power generation prediction of a geothermal-thermoelectric hybrid system using intelligent models

This study focuses on the most effective use of energy resources, which is the main goal of sustainable energy systems. The first contribution of the research is to ensure that the waste and geothermal fluids generated during the geothermal energy production process are evaluated in the most efficient way and reused for energy production. For this purpose, a geothermal-thermoelectric hybrid experimental system has been designed to produce electrical energy through heat exchange and how waste thermal energy could be reused in this process has been examined. Experimental tests have been performed under electrical load and in the presence of real-time uncertainties such as temperature changes, thermal conductivity, electrical noise, heat losses and random variations in thermal interaction. The second main contribution of the study is to predict and evaluate different power generation performances in the Thermoelectric Generator (TEG) system, which is affected by the mentioned experimental limitations based on artificial intelligence models. In addition, the optimal prediction performance of artificial intelligence models using hyper-parameter optimization has also been compared. Experimental results have shown that intelligent models are a successful tool for energy prediction in geothermal power generation. As a result of the hyper-parameter optimization, each model is improved by ∼5 % to ∼30 % in various error metrics. However, it was observed that the decision tree-based learning techniques resulted in ∼46 % to ∼96 % less inaccurate predictions on various error metrics compared to other methods. Power production predictions obtained using intelligent models have been obtained with 98.7 % accuracy with LightGBM learning algorithms. Most of the models used to classify different hot and cold water levels exhibit very high classification performance. The results show the successful integration of artificial intelligence models in effectively utilizing waste thermal energy and adopting a sustainable approach to energy production.

Spatio-temporal variation in soil thermal conductivity during the freeze-thaw period in the permafrost of the Qinghai–Tibet Plateau in 1980–2020

The Qinghai–Tibet Plateau (QTP) has the largest amount of permafrost in the low and middle latitudes, making it highly susceptible to the effects of global warming. In particular, the degradation of permafrost can be intensified by anomalous amplified warming. To accurately model the hydrothermal dynamics of permafrost and its future trends, the accumulation of high-precision, long-term data for the soil thermal conductivity (STC) in the active layer is crucial. However, no previous research has systematically investigated the spatio-temporal variation in the STC on the QTP over an extended period. Therefore, this study aims to fill this gap using the XGBoost model to analyze the STC in the permafrost on the QTP from 1980 to 2020. The findings of this study provide some preliminary insights. First, areas with high variation in the STC between the freeze–thaw periods over the 40 years gradually migrated from the western region to the central region. Second, since 2015, STC in more than 90 % of the permafrost region in the thawing period has shown positive growth. While, during the freezing period, the STC also exhibited an increase over most regions of the QTP, though the western region and parts of the northeastern region exhibited a decrease. Third, the spatial center of gravity for the STC during the freezing and thawing periods from 1980 to 2020 shifted. The mean STC was larger in the eastern and northeastern regions during the freezing period and larger in the western region during the thawing period. Fourth, both alpine swamp meadow and alpine meadow exhibited a gradual increase in the STC during the freeze–thaw period from 1980 to 2020. The conclusions and data products from this study are expected to support spatiotemporal modeling of the permafrost on the QTP and assist in the prognosis for its future.

Heat transfer analysis of Carreau–Yasuda nanofluid flow with variable thermal conductivity and quadratic convection

Abstract Brownian motions and Thermophoresis are primary sources of nanoparticle diffusion in nanofluids, having substantial implications for the thermo-physical characteristics of nanofluids. With such a high need, the 2D, laminar MHD (Magnetohydrodynamic) quadratic convective stream of Carreau–Yasuda nano liquid across the stretchy sheet has been reported. The flow is caused by surface stretching. The principal purpose of this extensive study is to enhance thermal transmission. The effects of variable thermal conductivity and heat source are considered as well. The governing boundary layer equations are transmuted using similarity parameters into a series of non-linear ODEs (ordinary differential equations). The bvp4c algorithm is adopted to fix the translated system numerically. The effects of prominent similarity variables over the temperature, velocity and concentration field are graphically visualized and verified via tables. It explored that fluid’s speed diminishes for the more significant inputs of the magnetic coefficient, Brownian motion coefficient and Prandtl number. The thermal efficiency is improved for larger values of thermophoretic constant, varying thermal conductance and heat-generating parameters. The concentration field has proved to be a decreasing function of nanofluid constants.

Legendre wavelet collocation method for investigating thermo-mechanical responses on biological tissue during laser irradiation

Objective of the present work is to propose a numerical approach based on the Legendre wavelet to address a problem of biological tissue in the presence of superficial cancer and analyze the thermo-mechanical behavior during laser irradiation. The model of thermoelasticity with variable thermal conductivity is considered to investigate transient thermoelastic coupling response in the framework of Moore–Gibson–Thompson (MGT) bioheat transfer. The Kirchhoff mapping is first performed to linearize the nonlinear governing equations due to variable thermal properties, then finite difference discretization is applied for the time domain and subsequently space domain is approximated using Legendre wavelets. The collocation points are taken to transform the system of partial differential equations into a set of algebraic equations, from which the solution can be determined. A thorough parametric analysis is carried out to examine the effects of some material and geometrical parameters on the behavior of various fields such as the displacement, temperature, stress and the tumor-normal tissue interface. The outcomes of the present work are graphically shown and compared to the predictions of other existing models. The advantages of the current numerical procedure include its simplicity, effectiveness and low computational cost even with the few collocation points.

Numerical treatment of the radiated and dissipative power-law nanofluid flow past a nonlinear stretched sheet with non-uniform heat generation

The main aim of this paper is to investigate the effect of non-uniform heat generation and viscous dissipation on the boundary layer flow of a power-law nanofluid over a nonlinear stretching sheet. Within the thermal domain, the analysis considers both thermal radiation and variable thermal conductivity. Through the use of similarity transformations, the governing boundary layer equations are transformed into a system of ODEs. The spectral collocation method (SCM) with shifted Vieta-Lucas polynomials (VLPs) is implemented to give an approximate expression for the derivatives and then use it to numerically solve the proposed system of equations. By employing this technique, the system of ODEs is converted into a system of nonlinear algebraic equations. The dimensionless temperature, concentration, and velocity are graphically presented and analyzed for various values of the relevant governing parameters. Through the presented graphical solutions, we can see that the main outcomes indicate that an increase in the power law index, thermal conductivity parameter, and radiation parameter leads to a noticeable decrease in the local Nusselt number, with reductions of around 0.05 percent, 0.23 percent, and 0.11 percent, respectively. In contrast, the Prandtl parameter demonstrates an opposing effect, elevating the local Nusselt number by about 0.1 percent. We validated the accuracy of the numerical solutions by comparing them in some special cases with existing literature.

Thermal and mass transfer analysis of Casson-Maxwell hybrid nanofluids through an unsteady horizontal cylinder with variable thermal conductivity and Arrhenius activation energy

In this study, the flow, thermal transfer, and mass transport of Casson-Maxwell hybrid nanofluids are explored. The governing PDEs are converted into nonlinear ODEs using similarity transformations and then solved using MATLAB's Bvp4c scheme. Various non-dimensional parameters’ influences on fluid behaviour and transport are investigated. Results indicate that higher curvature parameter values boost velocity, temperature, and concentration fields, enhancing mass and heat transfer as well as fluid motion. The unsteadiness parameter affects velocity profiles and heat/mass transfer processes. Thermal and mass relaxation times, alongside parameters like thermophoresis, Brownian motion, variable thermal conductivity, Arrhenius activation energy, chemical reaction, and temperature difference ratio, significantly shape temperature and concentration profiles and optimise heat and mass transfer rates. Additionally, combining the Casson and Maxwell hybrid nanofluid models shows marked changes in skin friction performance: absolute skin friction rises by 30%, while heat transmission increases by almost 11% compared to the Casson-Maxwell nanofluid model.

Investigation of dissipation phenomenon of non-Newtonian nanofluid due to a horizontal stretching rough sheet through a Darcy porous medium

Recent advancements in thermal engineering have led to the development of stable thermal properties and practical applications for nanofluid flow. Consequently, this study aims to explore the heat and mass transfer characteristics of a non-Newtonian Maxwell nanofluid when it comes into contact with a stretched surface containing porous features that allow for fluid suction velocity. Additionally, the research takes into account how the Soret and Dufour effects impact the processes of heat and mass transfer. A less-explored aspect of research in this field relates to the velocity slip boundary conditions when nanofluids with changing viscosity are involved. Additionally, the model employed in this study illustrates the influence of both viscous dissipation and variable thermal conductivity on the processes of heat and mass transfer. The mathematical flow model is described by nonlinear partial differential equations, which are subsequently transformed into non-dimensional ordinary differential equations. The resulting system is then solved numerically using the shooting method. This study visually examines the impact of physical variables on temperature, flow characteristics, and concentration patterns. Furthermore, it provides graphical representations of estimated values for the skin friction coefficient, Sherwood numbers, and local Nusselt numbers, which are also organized in tables for analysis. In conclusion, by comparing our data with previous results, we confirm the accuracy and reliability of the proposed method. A significant discovery is that the nanofluid velocity decreases as the Maxwell, porous, and slip velocity parameters are increased. Furthermore, the nanofluid concentration rises when the thermophoresis and viscosity parameters increase.

Entropy optimized flow subject to variable fluid characteristics and convective conditions

Background and objectiveNanofluids possess significant enhancement in nanomaterial properties such as convective heat transfer coefficient, thermal conductivity (which increases volumetric fraction of nanoparticles) and diffusivity at reasonable nanoparticle concentration. Nanofluids provide interesting new opportunities to develop nanotechnology-based operative coolants for different kinds of innovative applications. Hydromagnetic radiative flow of nanomaterial by curved stretched sheet is addressed in presence of Darcy-Forchheimer relation. Heat generation and dissipation are deliberated. Variable mass diffusivity and thermal conductivity behaviors are under consideration. Convective conditions are taken into account. Random diffusion and thermophoresis behaviors are considered. Dufour and Soret behaviors are taken. Binary chemical reaction and thermal radiation are explored. Entropy rate is taken into consideration. MethodologyNonlinear formulation is reduced to ordinary differential system. Convergent solutions for nonlinear ordinary systems are developed invoking Optimal homotopy analysis method (OHAM). ResultsImpacts for influential parameters regarding fluid flow, pressure, thermal distribution, entropy and concentration are discussed. Larger magnetic variable has reverse behavior on entropy rate and pressure. Higher magnetic field intensifies thermal distribution whereas reverse effect noted for liquid flow. Thermal distribution has increasing trend for Dufour number and variable thermal conductivity. Concentration reduces for random motion and Schmidt number. Concentration has increasing behavior for Soret number and variable mass diffusivity parameter. Larger estimation of thermal Biot number has same impact on thermal distribution and entropy. Increasing behaviors of entropy rate and concentration for solutal Biot number are observed. Bejan number reduces against Brinkman number whereas opposite trend holds for radiation parameter.

Energy storage and hydrophobicity characteristics of cement-based materials containing paraffin-pumice at low air pressure

Pumice is an environmental friendliness and low-cost carrier material for development of paraffin-pumice phase change energy storage composites (PP) at low air pressure in this work. PP was incorporated into cement to obtain CBM-PP. Microstructural, chemical, and thermal characteristics of PP were investigated by scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET), Fourier transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC) tests. Moreover, thermal energy storage and hydrophobicity characteristics of CBM-PP were performed by thermal conductivity, drip, and water absorption experiments. Results show that paraffin is effectively impregnated into pumice pores. There exists a physical interaction between paraffin and pumice. And PP possesses excellent compatibility and thermal stability, while its phase change temperatures and thermal energy storage capacities are in the ranges of 51.84–54.69 °C and 77.22–110.60 J/g, respectively. Furthermore, CBM-PP possesses excellent thermal energy storage and hydrophobicity at low air pressure in plateau areas, thus exhibiting a good application prospect in building thermal management and impermeability. Moreover, the thermal conductivity variation of CBM-PP is studied by the thermal conductivity model, which can predict the thermal conductivity with an error of no >9 %.