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Modelling effective thermal properties is crucial for optimizing the thermal performance of materials such as new green insulating fibrous media. In this study, a numerical model is proposed to calculate the effective thermal conductivity of these materials. The fibers are considered to be non-overlapping and randomly oriented in space. The numerical model is based on the finite element method. Particular attention is paid to the accuracy of the results and the influence of the choice of the representative elementary volume (REV) for calculation (cubic or rectangular parallelepiped slice). The calculated effective thermal conductivity of fibrous media under different boundary conditions is also investigated. A set of usual mixed boundary conditions is considered, alongside the uniform temperature gradient conditions. The REV rectangular slice and uniform temperature gradient boundary conditions provide a more accurate estimate of the effective thermal conductivity and are therefore recommended for use in place of the usual cubic representative elementary volume and the usual mixed boundary conditions. This robust model represents a principal novelty of the work. The results are compared with experimental and analytical data previously obtained in the literature for juncus maritimus fibrous media, for different fiber volume fractions, with small relative deviations of 7%. Analytical laws are generally based on simplified assumptions such as infinitely long fibers, and may neglect heat transfer between different phases. Both short and long fiber cases are considered in numerical calculations. [ABSTRACT FROM AUTHOR]

To understand the transient heat transfer characteristics of nanoporous aerogel insulating composites, solving the inverse heat transfer problem would be crucial for identifying the temperature-dependent thermal properties of composites. In this study, with constructed a forward model to numerically investigate the heat transfer in composites, a deep neural network (DNN) model and a particle swarm optimized deep neural network (PSO-DNN) model are conducted to rapidly estimate the effective temperature-dependent thermal conductivity of the desiccated and moist composites from the temperature response measurements. With the DNN model, the retrieved thermal conductivities for desiccated composites possess low deviation to experimental measurements (<3.2%) and constantly low errors (<5.2%) from 280 K to 1080 K. The precision of the DNN solver could be enhanced by adjusting the hyperparameters of the neural networks using PSO. The retrieved thermal conductivities possess low deviation from experiments (<2.5%) and low relative errors within 1.5%. Furthermore, the robustness of the PSO-DNN solver is discussed when commercial thermocouple measurement errors are considered, within retrieving the thermal properties of desiccated and moist aerogel composites. [ABSTRACT FROM AUTHOR]

Purpose: The heat transfer properties play significant roles in the thermal comfort of the clothing products. The purpose of this paper is to find the relationship between heat transfer properties and fabrics' structure, yarn properties and predict the effective thermal conductivity of single layer woven fabrics by a parametric mathematical model. Design/methodology/approach: First, the weave unit was divided into four types of element regions, including yarn overlap regions, yarn crossing regions, yarn floating regions and pore regions. Second, the number and area proportion of each region were calculated respectively. Some formulas were created to calculate the effective thermal conductivity of each element region based on serial model, parallel model or series–parallel mixing model. Finally, according to the number and area proportion of each region in weave unit, the formulas were established to calculate the fabric overall effective thermal conductivity in thickness direction based on the parallel models. Findings: The influences of yarn spacing, yarn width, fabric thickness, the compressing coefficients of air layers and weave type on the effective thermal conductivity were further discussed respectively. In this model, the relationships between the effective thermal conductivity and each parameter are some polynomial fitting curves with different orders. Weave type affects the change of effective thermal conductivity mainly through the numbers of different elements and their area ratios. Originality/value: In this model, the formulas were created respectively to calculate the effective thermal conductivity of each element region and whole weave unit. The serial–parallel mixing characteristics of yarn and surrounding air are considered, as well as the compression coefficients of air layers. The results of this study can be further applied to the optimal design of mixture fabrics with different warp and filling yarn densities or different yarn thermal properties. [ABSTRACT FROM AUTHOR]

Metalized ceramic substrates are widely used as circuit boards for heat dissipation and electrical insulation in high output power modules and are becoming more important since the output power of the power devices has been increasing year by year. Designing a proper module structure requires not only measurements of constituting materials' properties but also understanding of the heat transfer characteristic in a module structure. An accurate assessment method of thermal conduction properties for such metalized ceramic substrates is currently still missing. Under the circumstances we have developed a method for evaluating in-plane effective thermal conductivities of metalized substrates in a mounted state. The key point of this method is that a cavity is made between a metalized ceramic substrate and a cooling plate by interposing a ring-shaped structure to control a heat flow from the center to the periphery. The in-plane effective thermal conductivities of various kinds of metalized substrates could be evaluated by means of surface temperature measurements at two points on the substrate during power supply. The evaluated values were consistent with those of estimated ones calculated by the rule of mixtures. [ABSTRACT FROM AUTHOR]

Most of the energy savings in the building sector come from the choice of the materials used and their microphysical properties. In the present study, through numerical simulations a link is established between the thermal performance of composite materials and their microstructures. First, a two-phase 3D composite structure is modeled, then the RSA (Random Sequential Addition) algorithm and a finite element method (FE) are applied to evaluate the effective thermal conductivity of these composites in the steady-state. In particular, building composites based on gypsum and clay, consolidated with peanut shell additives and/or cork are considered. The numerically determined thermal conductivities are compared with values experimentally calculated using the typical tools of modern metrology, and with available analytical models. The calculated thermal conductivities of the clay-based materials are 0.453 and 0.301 W.m−1 .K−1 with peanut shells and cork, respectively. Those of the gypsum-based materials are 0.245 and 0.165 W.m−1 .K−1 with peanut shells and cork, respectively. It is shown that, in addition to its dependence on the volume fraction of inclusions, the effective thermal conductivity is also influenced by other parameters such as the shape of inclusions and their distribution. The relative deviations, on average, do not exceed 6.8%, which provides evidence for the reliability of the used approach for random heterogeneous materials. [ABSTRACT FROM AUTHOR]

The knowledge of the thermal properties of textiles is important with regard to their vast applications in most industries. Thermal properties, as one of the physical features of a textile, are influenced by its structural parameters such as thickness, density, and so on. In this study, a new structural model is developed to predict the effective thermal conductivity in knitted spacer fabrics. In the first step, a spacer fabric was considered as a three-layer set. The thermal conductivity of each layer was calculated separately, and then the effective thermal conductivity of fabric was determined based on its structural parameters. The performance of the proposed model was evaluated using spacer fabrics, and the results were compared with those of other models. The results of the new model and the experimental method showed that the most effective parameters involved in thermal conductivity are thickness, porosity and density. A good agreement (with R2 = 0.91) was found between the results of the proposed model and the experimental values. [ABSTRACT FROM AUTHOR]

Floating offshore wind turbines (FOWTs) face a major challenge when focusing on the effect of biofouling: biofouling by mussels on bottom-surface mobile connections, such as dynamic submarine electrical cables and mooring lines. Mussels are one of the dominant species in offshore wind farms in North Atlantic area. Amongst other effects, mussels can cause significant thermal impacts on dynamic power cables, which can lead to reduced performance or even failure. To address this issue, it is essential to thermally characterize mussels, including estimating their thermal resistance, so that they can be properly incorporated into the design and maintenance phases of the submarine dynamic power cables. This study investigates three key factors that could affect mussel thermal resistance, including mussel water filtering, imposed power during measurement, porosity (mussel's age). Results reveal that the thermal resistance of living mussels is smaller than that of dead mussels due to the metabolic process of water filtering. Additionally, thermal resistance decreases as mussel age (porosity) and imposed power during measurement increase. The results of this study offer novel insights into the thermal properties of mussels and their impact on submarine dynamic electrical cables used in FOWTs. The findings have practical implications for the design and maintenance of FOWTs, enhancing the sustainability of offshore wind energy production and provide a complete protocol for further investigations. [ABSTRACT FROM AUTHOR]

In this study, ethylene glycol (EG)–water (35:65 %v)-based nanofluids have been prepared to study enhancement in thermal conductivity. Nanofluids containing nanoparticles of materials CuO, Al2O3 and TiO2 of different mass concentrations from 0.2 to 2% were prepared using ultrasonication. Thermal conductivity measurement was carried using KD2 Pro thermal properties analyser in the temperature range of 30–60 °C. The study investigated the effect of concentration of nanoparticles, temperature and nanoparticle material on effective thermal conductivity of nanofluids. The results showed a significant improvement in effective thermal conductivity due to the addition of nanoparticles to the base fluid. Correlations were developed for predicting the effective thermal conductivity considering each material separately, and a generalized correlation considering the three materials. Subsequently, ANN modelling was carried out for predicting the effective thermal conductivity of nanofluids and compared with developed correlations. The modelling work carried out in this study is more generalized as literature results were considered in addition to the results from the present study. ANN modelling predicts the effective thermal conductivity better than the proposed correlations. [ABSTRACT FROM AUTHOR]

The composition and microstructure of materials play important roles in their thermal properties. In this study, the temperature and composition dependence of the thermal conductivity of MoSi 2 –RSiC composites with a special 3D interpenetrating network structure was investigated experimentally and numerically. A microstructure-based model was established using serial sectioning technology. The model could describe the connectivity and distribution characteristics of the two phases in the composites. Finite element simulation could accurately predict the effective thermal conductivity of the MoSi 2 –RSiC composites, with a deviation of 6.8%–9.6% between numerical and experimental results at different temperatures. Furthermore, a novel simplified model was developed to predict the effective thermal conductivity of the composites with a 3D interpenetrating network structure at different network inclusions. Landauer's effective medium percolation theory (EMPT) was used to verify the numerical values and analytical results. The calculation results of EMPT and the simplified model fit well with the experimental data of the composites with a high volume fraction matrix or measured below 600 K; the former was due to the effect of matrix density on the porosity and interfacial phase content of the composites, and the latter was due to the reduced difference in thermal conductivity coefficient among SiC, MoSi 2 and the interfacial phase, and air with increased temperatures. [ABSTRACT FROM AUTHOR]

Thermal properties of sand are of importance in numerous engineering and scientific applications ranging from energy storage and transportation infrastructures to underground construction. All these applications require knowledge of the effective thermal parameters for proper operation. The traditional approaches for determination of the effective thermal property, such as the thermal conductivity are based on very costly, tedious and time-consuming experiments. The recent developments in computer science have allowed the use of soft and hard computational methods to compute the effective thermal conductivity (ETC). Here, two computation methods are presented based on soft and hard computing approaches, namely, the deep neural network (DNN) and the thermal lattice element method (TLEM), respectively, to compute the ETC of sands with varying porosity and moisture content values. The developed models are verified and validated with a small data set reported in the literature. The computation results are compared with the experiments, and the numerical results are found to be within reasonable error bounds. The deep learning method offers fast and robust implementation and computation, even with a small data set due to its superior backpropagation algorithm. However, the TLEM based on micro and meso physical laws outperforms it at accuracy. [ABSTRACT FROM AUTHOR]

Since pore network structures of porous materials have irregular shapes and may vary in size, the accurate characterization and virtual 3D reconstruction of these materials are of great importance for a deeper understanding of the structure and subsequent calculations. In this study, the scanning electron microscope (SEM) and X-ray microcomputed tomography (µCT) images of a graphite foam sample are used for image analysis method (IAM) and virtual 3D reconstruction as non-destructive scientific tools with high accuracy. The morphological characterization and determination of effective pore diameter, porosity, specific surface area (SSA), and effective thermal conductivity (ETC) of POCO graphite foam are investigated. By examining the results obtained from the method of image analysis, it is found that there is a good agreement among the IAM results. [ABSTRACT FROM AUTHOR]

An effective model to calculate thermal conductivity of polymer composites using core-shell fillers is presented, wherein a core material of filler grains is covered by a layer of a high-thermal-conductivity (HTC) material. Such fillers can provide a significant increase of the composite thermal conductivity by an addition of a small amount of the HTC material. The model employs the Lewis-Nielsen formula describing filled systems. The effective thermal conductivity of the core-shell filler grains is calculated using the Russel model for porous materials. Modelling results are compared with recent measurements made on composites filled with cellulose microbeads coated with hexagonal boron nitride (h-BN) platelets and good agreement is demonstrated. Comparison with measurements made on epoxy composites, using silver-coated glass spheres as a filler, is also provided. It is demonstrated how the modelling procedure can improve understanding of properties of materials and structures used and mechanisms of thermal conduction within the composite.

Highlights • An effective thermal conductivity model is derived based on fractal theory. • Predictions of proposed model show good consistent with experimental data. • The proposed theoretical model reveals the physical basis of heat transfer in porous media. Abstract Thermal conduction in porous media has received wide attention in science and engineering in the past decades. Previous models of the effective thermal conductivity of porous media contain empirical parameters typically with ambiguous or even no physical rationales. This study proposes a theoretical model of effective thermal conductivity in porous media with various liquid saturation based on the fractal geometry theory. This theoretical model considers geometrical parameters of porous media, including porosity, liquid saturation, fractal dimensions for both the granular matrix and liquid phases, and tortuosity fractal dimension of the liquid phase. Effects of these geometrical parameters on the effective thermal conductivity of porous media are also evaluated. This proposed fractal model has been validated using published experimental data, compared with previous models, and thus provides a physics-based theoretical model that can provide insight to geoscience and thermophysics studies on thermal conduction in porous media. [ABSTRACT FROM AUTHOR]

Highlights • A short description of the newly built NWTCTF test facility is provided. • Experimental investigation of effective thermal conductivity in the near-wall region. • Effects of conduction and radiation heat transfer are included. • Results are presented for structured and randomly packed beds of graphite spheres. • Near-wall effects have a notable influence on the effective thermal conductivity. Abstract The effective thermal conductivity is an important parameter that represents the overall heat transfer in packed beds, including packed pebble beds. Experimental test facilities have been used to determine the effective thermal conductivity of packed pebble beds; however, the experimental results are often case specific and do not account for wall effects in the near-wall region. Recently the Near-Wall Thermal Conductivity Test Facility (NWTCTF) was developed at the North-West University in Potchefstroom, South Africa to perform detailed investigations of the conduction and radiation heat transfer phenomena in the near-wall region of a packed bed of spheres. The experimental test facility was introduced in a previous paper and some results were presented. This paper provides a short description of the test facility and then presents extensive experimental results obtained for structured and randomly packed beds consisting of 60 mm diameter graphite spheres at temperatures of up to 800 °C, together with associated uncertainties. Results obtained demonstrate the effect of the near-wall region, the packing structure and the presence of the wall on the effective thermal conductivity. [ABSTRACT FROM AUTHOR]

Rigid polyurethane foam (PUF) is one of the outstanding insulation materials and has been widely used in freezers and cryogenic facilities. Among the various blowing agents used in the manufacturing PUF, water-blown PUF is attracting much attention as environmentally friendly PUF as prominent replacements for the environmentally hazardous CFCs and HCFCs due to their significant ozone depletion potential. We investigated the effective thermal conductivity of PUF blown with different amounts of water, on the basis of the heat transfer mechanisms in terms of thermal conduction of solids and gases and the thermal conductivity of radiation in the cells. A predictive model for the effective thermal conductivity of PUFs with different densities is presented. The predictive model was validated by comparing the predicted values with the experimentally measured ones. The result showed that the effective thermal conductivity increased from 0.023 to 0.027 W m−1 K−1 as the PUF density increased from 48 to 120 kg m−3: increased by 158% from 0.0034 to 0.0089 W m−1 K−1 for the thermal conductivity of solid PUF and decreased by 50% from 0.0037 to 0.0018 for the thermal conductivity of radiation. [ABSTRACT FROM AUTHOR]

This paper presents a recent implementation of the radial heat flow method, a classical technique used to measure the thermal conductivity of materials, including the hardware designed to this end, as well as the theoretical formalism used to analyse the data. The novelty is in its application to high-aspect-ratio hollow cylindrical samples, more specifically sections of nuclear cladding tube, whereby samples representative of full length fuel clads can be measured instead of platelets, like in usual laser-flash measurements. The apparatus designed and built to this end can accommodate tubular samples of varying length, diameter and wall thicknesses made of most materials, with the specific goal of determining the through-thickness thermal conductivity of silicon carbide composites, a highly anisotropic material under consideration as a fuel cladding material. [ABSTRACT FROM AUTHOR]

• The pores act as a "thermal barrier wall" on the heat transfer path in the MPL. • The fractal characteristics of the MPL inhibit heat transfer. • The structural parameters of the MPL is correlated with the thermal properties. Heat transfer in the fuel cells is generally limited by the effective thermal conductivity of the microporous layer (MPL). Due to the complexity of the microstructure and the difficulty of the test conditions, studies on the key parameters that affect the thermal conductivity of MPL is lacking. In this paper, we develop an analytical fractal model for the effective thermal conductivity of the MPL based on a lumped parametric model of the cube and a fractal particle chain model, and provide the contact ratio of the agglomerates using a 3D FIB-SEM reconstruction. The results indicate that the main factors affecting the thermal conductivity of MPL include the structural parameters, fractal dimension, and the thermal conductivity of the carbon particles and pores. The fractal characteristics of the MPL inhibit heat transfer rate and the pores act as a "thermal barrier wall" on the heat transfer path in the MPL. When the volume fraction of the MPL is 40 percent, the contact area ratio and fractal factor of the agglomerates are 0.351 and 0.84, respectively. In addition, this research will help to develop novel MPL structures with high thermal conductivity and improve simulation results for fuel cell temperatures. [ABSTRACT FROM AUTHOR]

Known as one of the super adiabatic materials today, vacuum insulation panels (VIPs) is wildly applied in building industry. It has the double advantage of saving energy and improving space utilization. However, its expensive cost is the application obstacle. A new type of VIPs with recycled and economical cotton fiber core was prepared and innovated in this study. The micromorphology of the recycled cotton core material, as well as the barrier and thermal conductivity of the prepared VIPs, was experimentally and mathematically investigated. A designed vacuum measurement device was introduced to analyze the variation of thermal conductivity versus gas pressure. Three types of laminated films were prepared to investigate VIPs' adiabatic properties. Three typical barriers, respectively AF, MF-Ⅰ, MF-Ⅱ, were involved to investigate the impact of sustainability. The final results showed that AF as the barrier layer for VIPs with performed better than other VIPs considering thermal conductivity. The effective thermal conductivity (ETC) of the VIPs is sensitive to inner pressure and the optimum gas pressure is less than 0.1Pa. The drying process for porous cotton fibers is a continuous heating at a temperature of 120 °C for 30–40 min. The ETC of the VIPs prepared using AF barrier envelopes was about 3.17 mWm−1K−1. The VIPs with cotton fiber core material has good thermal properties and also has the dual characteristics of low price and environmental protection. As a potential candidate for the VIPs core material, the recycled wasted cotton fiber core material is a new development direction. [ABSTRACT FROM AUTHOR]

[Display omitted] • Importance of thermal/geometric features of composite structures to effective thermal conductivity is studied. • Effective thermal conductivity is correlated with the features using machine learning. • Using a machine learning model, composites are classified based on the existence of percolation path. • Volume fraction of particles and interface thermal resistance are most influential parameters on effective thermal conductivity. Data-driven thermal and percolation analyses are conducted to elucidate the effects of various characteristics on the effective thermal conductivity of complex 3D composite structures. These characteristics include the thermal and geometric properties of the composite constituents, the interface resistance, and the existence of percolation paths. A series of voxel-wise microstructure samples with various characteristics are generated. Their effective thermal conductivities are evaluated using a diffuse-interface-based computational homogenization method. A voxel-based algorithm is employed to identify the potential percolation paths in the structures. The homogenization results show particularly significant effects of the percolation path in composite samples with higher aspect ratios and interface resistances. The importance of different thermal and geometric features to the effective thermal conductivity is analyzed using a data-driven sensitivity study. The analysis also demonstrates that the particle volume fraction and interface thermal resistance are the most influential characteristics for determining the effective thermal conductivity. Finally, employing a surrogate-based classification model, microstructures with and without percolation can be distinguished with an accuracy of 93%. [ABSTRACT FROM AUTHOR]

Concrete structures are subjected to various loadings during their service life and their internal structures will be changed, resulting variations in mechanical and thermo-physical properties. To investigate the effect of mechanical stress on thermal conduction, a computational homogenization method from a mesoscopic perspective was proposed in the present work. In the simulations, concrete was considered as a three-phase composite material consisting of aggregate, mortar matrix and the interfacial transition zones (ITZs) between them. The mechanical analysis was conducted firstly to study the damage distribution within concrete. The outcomes of mechanical computation were then used as the initial input data in the thermal conduction computation. The equivalent thermal conductivity of damaged element was homogenized by a composite mechanical method based on damage and the initial thermal conductivity of sound material. Accordingly, a meso-scale model in which the mechanical and thermal behavior were one-way coupled was built. The method was calibrated by comparing the numerical results with the available experimentally measured ones. Based on the verified simulation method, effective thermal conductivity (ETC) and temperature field of concrete subjected to different loading levels were calculated. Besides, the effects of loading type (compressive and tensile loadings) on ETC and temperature field of concrete were studied. It is found that ETC of concrete decreases with an increasing loading level. In addition, the effect of tensile loading on thermal behavior depends on whether the direction of thermal conduction is parallel or perpendicular to loadings. [ABSTRACT FROM AUTHOR]

The effective thermal conductivity (ETC) of particle beds has been shown to be anisotropic under uniaxial compression. The objective of this study is to validate the assumption that vertical and horizontal effective thermal conductivities of particle beds under uniaxial (vertical) compression can be correlated to compressive stresses in each direction. The horizontal compressive pressure, which is perpendicular to the applied compressive pressure, can be calculated with the use of the at-rest pressure coefficient and subsequently used in a modified macro-contact thermal resistance model to predict the horizontal ETC. The vertical ETC is obtained using the same model by substituting the vertical compressive pressure into the macro-contact thermal resistance. The modified model prediction is shown to match well with experimental data of both vertical and horizontal ETCs of particle beds under uniaxial compression in air and vacuum. [ABSTRACT FROM AUTHOR]

In Korea, the Very High Temperature Gas-Cooled Reactor (VHTR) PMR200 is being developed in the Nuclear Hydrogen Development and Demonstration project. Its core consists of hexagonal prism-shaped graphite blocks for the fuel and reflector, and each hexagonal fuel block contains 108 cylindrical coolant holes and 210 fuel compacts. Because of these holes and fuels, the heat transfer in lateral directions in the fuel blocks becomes very complicated. Especially in accident situations when forced convection is lost, the majority of the afterheat flows in the radial direction by conduction across the large number of coolant holes. Moreover, radiation heat transfer is supposed to be added to the radial heat transfer modes owing to the high temperature of the VHTR core. Because of these complexities in radial heat transfer, reliable modeling for effective thermal conductivity (ETC) is required in order to analyze the reactor core thermal behavior using lumped-parameter codes, which are often used to evaluate the integrity of nuclear fuel embedded in the graphite block. In this study, the ETC model adopted in the GAMMA+ code was introduced, and the adequacy of the model was assessed by the commercial computational fluid dynamics (CFD) code CFX-13. The results of the CFD analysis were consistent with, the ETC model in general even if a slight disagreement was shown for the case of high temperature. From these analyses, it could be concluded that the ETC model adopted in the GAMMA+ code is an adequate model for the analysis of the PMR200 reactor core. Moreover, it was found that the effect of fuel gap can cause an overprediction of the ETC if the fuel compact thermal conductivity is larger than the applicable range of the model. [ABSTRACT FROM AUTHOR]

A new, alternative approach is proposed for natural convection simulation by means of stimulated thermocapillary currents created by virtual walls. In contrast to the well-known effective thermal conductivity model, in the proposed approach it is the mass motion due to the convective currents which is intended to be simulated and the heat flux is a consequence of such flows. As a result, no a priori knowledge of the Nusselt number is needed and thus the approach is more suitable for complex geometries. Utilizing a simplified physical model and the definition of hydraulic diameter, a generalized expression for enclosed geometries is derived which offers thermal engineers a powerful analysis tool that can use virtual walls with an associated fictitious Marangoni stress for pre-screening and estimation of Nusselt numbers. [ABSTRACT FROM AUTHOR]

Incident neutrons in irradiated W can cause the formation of solid transmutation elements, of which Rhenium (Re) is the most abundant. We apply the phase-field method to investigate the clustering and growth of the Re-rich precipitate in irradiated W based on the spinodal decomposition mechanism, and their effects on the mechanical and thermal properties of W. Needle-like precipitates are reproduced and comparable to experimental observations. We then vary the irradiation dose and temperature to study their influences on the microstructure evolution of the Re-rich precipitate. Simulation results show that the average diameter, the number density, and the coverage rate of the precipitates significantly increase with the increase of the irradiation doses but slightly increase with the increase of the temperature. The effects of the Re-rich precipitate on the mechanical and thermal properties of W are also investigated. Results show that the Vickers hardness increase and the thermal conductivity degrade due to the formation of the Re-rich precipitate, especially at high irradiation doses. Conventional simulation methods can hardly handle the effect of the needle-like precipitates on the mechanical and thermal properties. In this work, we compare these two properties by using needle-like precipitates and circular precipitates. Our results clearly show that the needle-like precipitates give a better consistency with experimental results of the Vickers hardness increase, and reveal the anisotropic ability of the heat transfer in neutron-irradiated W. The current results can provide a systematic understanding of the Re clustering behavior from the microstructure evolution to its influences on the mechanical and thermal properties of W materials. [ABSTRACT FROM AUTHOR]

Nonwoven aramid fabric is widely used as thermal barrier of fireproofing clothing due to its inherent flame retardancy and light weight. In fire or high temperature scenario, radiative heat transfer becomes the predominant heat transfer mode inside firefighters' clothing. In this work, Fourier transform infrared spectroscopy (FTIR) was adopted to measure the spectral transmittance and spectral extinction coefficients of four aramid fabrics with different porosity in infrared wavelength range between 2.5 and 25 μm. It was found that the radiative properties of fibrous aramid fabric are strongly dependent on its bulk density or porosity. The spectral extinction coefficient decreases with increasing porosity or decreasing bulk density. The infrared optical properties combined with infrared imaging measurements demonstrate that aramid fabric may be used as infrared semi-transparent textile. A predicted model, combined the effects of conduction-radiation heat transfer, has been developed to calculate the effective thermal conductivity of aramid fiber materials. The model implemented the Rosseland diffusion approximation to evaluate radiative thermal conductivity, and the Parallel-Series structural model to evaluate tortuosity-weighted phonic thermal conductivity. The predicted results were also compared with experimental data obtained from TPS method. This work provides useful information for future studies of heat transfer mathematical modeling of firefighters' clothing. [ABSTRACT FROM AUTHOR]

Nanoparticle Enhanced Ionic Liquids (NEILs) were synthesized by dispersing aluminum oxide (Al 2 O 3 ) nanoparticles in 1-butyl-3-methylimidazolium bis{(trifluoromethyl)sulfonyl}imide, ([C 4 mim][NTf 2 ]) ionic liquids (ILs). The experimental assessment of NEILs includes investigating the effective thermophysical properties and forced convection heat transfer under laminar and turbulent flow regime. The results show that thermal conductivity and heat capacity enhanced up to ∼11% and ∼49% respectively for 0.9 vol% NEILs. The rheological behavior of NEILs shows non-Newtonian shear thinning behavior with shear viscosity decreasing with increasing shear rate. The viscosity of NEILs shows much higher value compared to the base ILs for a small amount of nanoparticles dispersion and also has a strong temperature dependency. Measured viscosity and thermal conductivity were found to be much higher than predicted by the well-established model for dilute suspensions. The convective heat transfer performance increases with the nanoparticles concentration within the measured nanoparticles vol%; up to ∼27% and ∼40% enhancement in heat transfer coefficient was found in laminar and turbulent flow regime respectively. The possible mechanisms of the enhanced thermal performance are discussed. [ABSTRACT FROM AUTHOR]

Measurements of the effective thermal conductivity $$(\lambda _{\mathrm{e}})$$ and effective thermal diffusivity $$(k_{\mathrm{e}})$$ of $$\hbox {Ge}_{30-x}\hbox {Se}_{70}\hbox {Sb}_{x}\,(x = (10, 15, 20$$ , and 25) at. wt.%) chalcogenide glasses have been carried out in the temperature range from room temperature to above the glass transition temperature using the transient plane source technique. In the heating process, variations of $$\lambda _{\mathrm{e}}$$ and $$k_{\mathrm{e}}$$ are observed. Both quantities remain approximately constant in the temperature range from room temperature to $$160\,^{\circ }$$ C, beyond which a linear increase is observed and they reach a maximum in the vicinity of a critical temperature called the glass transition temperature $$(T_{\mathrm{g}})$$ . It is interesting to note that $$\lambda _{\mathrm{e}}$$ and $$k_{\mathrm{e}}$$ decrease above the glass transition temperature of the glasses. Such a type of behavior can be explained on the basis of structural changes occurring in $$\hbox {Ge}_{30-x}\hbox {Se}_{70}\hbox {Sb}_{x}\,(x = (10, 15, 20$$ , and 25) at. wt.%) chalcogenide glasses. Results also indicate that both $$\lambda _{\mathrm{e}}$$ and $$k_{\mathrm{e}}$$ increase with increasing weight percentage of Sb. This is because of an increase of the weak bond density in the glassy system with the addition of Sb. [ABSTRACT FROM AUTHOR]

The thermal conductivities of ordered mesoporous carbon CMK-3 filled with Al nanoclusters were studied in this article. CMK-3 is a typical example of carbon rods which are arranged in a relatively regular two-dimensional hexagonal array. The initial structure of CMK-3 was generated from the amorphous carbon and validated by XRD simulation which is coincident with experimental data. The thermal conductivities of carbon rods in CMK-3 and Al nanoclusters with 133 atoms were simulated by an equilibrium molecular dynamics method. Then, the effective thermal conductivity (ETC) of a mesoporous composite, CMK-3 filled with $$\text {Al}_{133}$$ , was obtained via one-dimensional heat conduction analysis. The influences of the substrate porosity, nanocluster filling ratio, and temperature were discussed. As an anisotropic material, ETCs along the $$X$$ and $$Y$$ directions are extremely poor, due to the overwhelming effect of the air thermal resistance. However, in the $$Z$$ direction, the ETC improves almost linearly as the porosity decreases, and the value is much higher than those of $$X$$ and $$Y$$ directions. In the case of a 70 % filling ratio, when the porosity is below 59.7 %, the ETC in the $$Z$$ direction exceeds the thermal conductivity of Al nanoclusters and approaches a peak value around the melting temperature of $$\text {Al}_{133}$$ nanoclusters. The results indicate that the carbon-based mesoporous CMK-3 filled with Al nanoclusters might become a promising phase change material. [ABSTRACT FROM AUTHOR]

In the present study, the accuracy of predicted effective thermal conductivity of composite materials, determined by the finite volume method (FVM) and the thermal lattice Boltzmann method (TLBM) using single relaxation time (SRT), is investigated. In addition, computational efforts required by both solution methods are also compared. Two- and three-dimensional heat conduction problems in two-phase domains with a high thermal conductivity ratio are considered, where oblique and curved interfaces are represented by the staircase approximation. The discretisation is carried out on a uniform mesh. For TLBM, different stencils are employed and a wide range of relaxation frequencies, corresponding to relative magnitudes of thermal conductivities of different phases, is investigated. For comparison, wherever available, the analytical expression for the effective thermal conductivity is considered. Otherwise, the reference effective thermal conductivity is determined using a commercial software employing an appropriate body-fitted mesh. The present results show that the accuracy of TLBM depends on the employed stencil, relaxation frequency and arrangement of two materials in the computational domain. It is also observed that TLBM can be even more accurate than FVM, although the accuracy of FVM is independent of individual values of thermal conductivities. For the same convergence criterion, however, TLBM requires a higher number of iterations than FVM, although TLBM shows a potential for speed-up. [ABSTRACT FROM AUTHOR]

Steel bars are manufactured in the rolling process, whereby they are characterized by strain hardening and poor plastic properties. In many application cases such properties are improper, therefore, additional heat treatment is required. Crucial influence on the products quality after heat treatment has an appropriate selection of process parameters. In many modern technologies of heat treatment the charge of porous structure is subjected to the heating process. Proper control of heat treatment parameters of bundles of rods requires knowledge on their thermal properties. However, it also requires accurate identification of complex heat transfer processes occurring in the porous material. Such analysis, with respect to bundles of bars, provide a response of qualitative nature of the heat exchange area of these charges. The article describes the emissivity measurements of samples of the steel charge using a thermal imaging camera. [ABSTRACT FROM AUTHOR]

• Complex heat transfer in steel bar bundles is expressed by the effective thermal conductivity k ef. • The paper analyses the k ef coefficient of bundles within the temperature range 25–700 °C. • The k ef coefficient of bar bundles rises linearly with temperature. • Simple models do not determine the k ef coefficient correctly. Transport phenomena of heat in porous media have been focus of many investigations. Most studies deal with low-porosity granular media. A specific example of such a medium are steel bars heated during heat treatment in the form of cylindrically shaped bundles. The intensity of heating is determined by the processes of heat transfer which occur in the radial direction of the bundle, in which the considered charge is characterized by the lack of continuity of the solid phase. Therefore, the ability of the bundles to transfer heat is expressed by effective thermal conductivity k ef. Knowing this coefficient is necessary to optimize heat treatment processes of bar bundles. The article presents the results of calculations of the k ef for packed beds of round and square steel bars obtained for a few selected analytical models. The quality of the results was verified on the basis of experimental measurements performed in a guarded hot plate apparatus. The results indicate that simple models are not suitable for determining thermal properties of bundles. The k ef values obtained with their use significantly vary from the measured values. Complex models are much more valuable in this respect. The best results were obtained for the Zehner-Bauer-Schlünder model. [ABSTRACT FROM AUTHOR]

Nanoparticle aggregation has been found to be crucial for the thermal properties of nanofluids and their performance as heating or cooling agents. Most relevant studies in the literature consider particles of uniform size with point contact only. A number of forces and mechanisms are expected to lead to deviation from this ideal description. In fact, size uniformity is difficult to achieve in practice; also, overlapping of particles within aggregates may occur. In the present study, the effects of polydispersity and sintering on the effective thermal conductivity of particle aggregates are investigated. A simulation method has been developed that is capable of producing aggregates made up of polydispersed particles with tailored morphological properties. Modelling of the sintering process is implemented in a fashion that is dictated by mass conservation and the desired degree of overlapping. A noticeable decrease in the thermal conductivity is observed for elevated polydispersity levels compared to that of aggregates of monodisperse particles with the same morphological properties. Sintered nanoaggregates offer wider conduction paths through the coalescence of neighbouring particles. It was found that there exists a certain sintering degree of monomers that offers the largest improvement in heat performance. [ABSTRACT FROM AUTHOR]

• The computational microstructure modeling including randomly dispersed coated fibers is established. • The graded interphase has significant influence on the effective thermal conductivity. • The linear form of interphase property can cause higher prediction than the nonlinear form. • The high-conductivity fiber causes a plateau value of the prediction. • The magnitude of plateau value dramatically increases with the increase of interphase thickness. To assess the overall thermal properties of lightweight natural fiber-reinforced cementitious composites (NFRCCs) developed for low-carbon constructions, the comprehensive understanding of properties and characteristics of graded interphase between fiber and matrix is vital. However, there is rare study on the graded interphase in the NFRCCs so far. The main objective of this work is to present a comprehensive numerical investigation of the influence of functionally graded interphase on the effective thermal conductivity of such composites. A computational microstructure model including randomly dispersed fibers coated by functionally graded interphase is established and verified by comparison to the experimental results. Then, the effective thermal conductivity of the composites is characterized with respect to the microstructure parameters. It is found that the overall thermal conductivity is weakly dependent of the fiber distribution, whilst it is significantly affected by fiber content, constituent properties, as well as interphase graded form and thickness. Moreover, the study reveals that the linear variation of the interphase property can cause higher predictions than the nonlinear variation. The proposed work will provide fundamental insight about the role of functionally graded interphase in NFRCCs, which is helpful in guiding the designing and processing of NFRCCs. [ABSTRACT FROM AUTHOR]

• Prediction of the effective thermal conductivity of the composite material. • Establishing representative numerical simulation models at multiple scales. • Heat transfer under the condition of conduction & radiation. • Effects of the porosity and fiber volume fraction on the effective thermal conductivity of the composite materials. Composite materials are widely used in the fields of aviation and space, where their thermal properties are of importance since they are often challenged by variations of environmental temperatures. However, thermal properties of composite materials under conditions of conduction & radiation (a key mode of heat transfer in space) remain elusive. In order to address this issue, in this study, numerical simulations of the glass/polyimide composite materials were conducted to determine its effective thermal conductivity under the conduction condition with and without radiation. More specifically, unit cell models of polyimide matrix, glass-fiber yarns, and the composite materials were constructed sequentially to study the effects of the porosity and the fiber volume fraction on the effective thermal conductivities of the composite materials. Simulation results revealed that 1) an increase in porosity can reduce the effective thermal conductivity of the polyimide matrix with the maximal decreasing ratio of 39.5%; 2) an increase in fiber volume fraction can increase the transverse effective thermal conductivity of the glass-fiber yarns with the maximal increasing ratio of 49.0%; 3) differences of 26.0% and 27.6% of the in-plane and out-of-plane effective thermal conductivities of the composite materials were located under the conduction condition with and without radiation. This study provided a simulation approach to investigate thermal properties of composite materials, paving ways for their applications in the fields of aviation and space. [Display omitted] [ABSTRACT FROM AUTHOR]

• Adaptive thermal cloaking is proposed by rotating three-layer configuration. • Effective thermal conductivity of the three rotating-layer configuration is deduced. • Different functions of the three rotating layers are identified and explained. Thermal metamaterials have been extensively studied due to their extraordinary properties beyond natural materials and offered great flexibilities to tune heat flow for desired thermal functionalities, like thermal cloaking, concentrating, rotating, etc. Whereas, the thermal properties of thermal metamaterials are usually fixed once the configuration and the constituent materials are designed and fabricated. For instance, the thermal cloaking effect may be deteriorated when background changes, which limits its practical application significantly. By deducing the effective thermal conductivities of rotating objects, we propose an adaptive thermal cloaking metadevice that is composed by three rotating layers with different roles. The joint effect of three rotating layers makes the effective thermal conductivity a real number on the reciprocity line for feasible implementation. When background changes, we only need change the angular velocities rather than change the configuration or the constituent materials to restore the cloaking effect, which is much more convenient and real-time for practical applications. The underlying physics of the rotating thermal cloak is discussed to identify the key parameters and upper and lower limits of the effective thermal conductivity for further improving the cloaking effect. The present study can trigger more rotating metadevices for novel applications beyond thermal cloaking. [ABSTRACT FROM AUTHOR]

A method to obtain a radiation exchange factor FR in the bundle of steel round bars is presented. This parameter is required for determination of the radiative thermal conductivity krd, which is one of the basic thermal properties of the bar bundles. In the presented approach, the analyzed parameter is calculated indirectly. The initial point for calculations is the geometric model of the medium defined as a unit cell. Then, for the elements present in this cell, the thermal resistance of both conduction and radiation is determined. The radiation resistance is calculated from the radiosity balance of the surfaces enclosing the analyzed system. On this basis, the radiation thermal conductivity krd is calculated. Next, taking into account the bar diameter, the value of parameter FR is also determined. The analysis is performed at the process temperature range of 200 to 800 °C for three bar diameters: 10, 20 and 30 mm, and for the three porosities of the bundle. Different emissivity of bars in the range of 0.5 to 0.9 was also taken into account. Finally, a relationship that allows calculating the FR factor correlated with the emissivity of the bars and the bundle porosity was established. The krd obtained from the methodology presented and compared with the values calculated directly do not exceed 9%; however, after averaging over the entire temperature range of the process, the difference does not exceed 0.2%. [ABSTRACT FROM AUTHOR]

• Some factors influencing effective thermal conductivity changes were studied • Different effective thermal conductivity changes at measuring positions were found • Key factors of effective thermal conductivity changes in two settings were analyzed The effect of hydrate distribution on the effective thermal conductivity changes of the actual hydrate-bearing sediments is uncertain. To define this effect, in the hydrate-bearing quartz sands, the effective thermal conductivity was measured by the transient hot-wire method, and hydrate distribution was analyzed by the electrical resistance changes. At first, the effective thermal conductivity changes were investigated from gas saturation, gas pressure, water saturation, water pressure, and temperature. Afterward, in three kinds of hydrate formation processes, compared with hydrate distribution, the changing trends of the effective thermal conductivity at five measuring points were analyzed. The results showed that the effective thermal conductivity was increased with decreasing gas saturation and increasing water saturation or water pressure, and impacted slightly by gas pressure and temperature. Moreover, at five measuring points, the non-uniform hydrate distribution caused different changing trends of the effective thermal conductivity during hydrate formation. In the excess-water setting, an increasing trend was only observed at some local measuring point. The decreasing trends at the most of the measuring points were governed by the reduced water distribution. But in the excess-gas setting, at the most of the measuring points, this increasing trend was observed and controlled by the enlarged hydrate distribution. Besides, for some actual sediments in the excess-water setting, hydrate distribution may be not the key factor of the effective thermal conductivity changes, and further studies were required. This research could offer some valuable reference to the thermal properties in the actual sediments. [ABSTRACT FROM AUTHOR]

• A closed-loop MPHP with a hydraulic diameter of 350 μm is fabricated. • Effective thermal conductivities of the MPHP charged with FC-72 are measured. • Semantic segmentation-based image recognition is applied to recorded flow images. • Heat transfer simulations are performed using the extracted flow patterns. • Latent heat transfer via liquid films proves to be the most significant. We investigate the relationship between the thermal properties of a micro pulsating heat pipe (MPHP) and the internal flow characteristics via measurements of effective thermal conductivities, flow visualization followed by image recognition of the flow patterns, and heat transfer simulations employing the extracted flow patterns. The MPHP consists of an eleven-turn closed-loop of a meandering square microchannel with a hydraulic diameter of 350 μm engraved on a silicon substrate, which is covered with a transparent glass plate to allow internal flow visualization. The MPHP charged with Fluorinert FC-72 tends to exhibit higher effective thermal conductivities for the coolant temperature of T c = 40 °C compared to T c = 20 °C, and provides the highest effective thermal conductivity of about 700 W/(m K) for T c = 40 °C and a filling ratio of 48%. Interestingly, we observe two different self-oscillation modes having different thermal conductivities, even for identical heat input rates. This tendency indicates a hysteresis of the effective thermal conductivity, which originates from the difference in the heat input rates at which the MPHP falls into and recovers from dryout. Subsequently, semantic segmentation-based image recognition is applied to the recorded flow images to identify the flow characteristics, successfully extracting four different flow patterns involving liquid slugs, liquid films, dry walls, and rapid-boiling regions. The image recognition results indicate that high effective thermal conductivities of the MPHP relate to stable self-oscillations with large amplitudes and high frequencies, along with long and thin liquid films beneficial for latent heat transfer. Finally, we perform numerical simulations of latent/sensible heat transfer via vapor plugs and of sensible heat transfer via liquid slugs using the extracted flow patterns and measured channel temperatures as inputs. We find that latent heat transfer via liquid films accounts for a considerable portion of the overall heat transfer, while the sensible heat transfer via liquid slugs is much less significant. Image, graphical abstract [ABSTRACT FROM AUTHOR]

An effective model to calculate thermal conductivity of polymer composites using core-shell fillers is presented, wherein a core material of filler grains is covered by a layer of a high-thermal-conductivity (HTC) material. Such fillers can provide a significant increase of the composite thermal conductivity by an addition of a small amount of the HTC material. The model employs the Lewis-Nielsen formula describing filled systems. The effective thermal conductivity of the core-shell filler grains is calculated using the Russel model for porous materials. Modelling results are compared with recent measurements made on composites filled with cellulose microbeads coated with hexagonal boron nitride (h-BN) platelets and good agreement is demonstrated. Comparison with measurements made on epoxy composites, using silver-coated glass spheres as a filler, is also provided. It is demonstrated how the modelling procedure can improve understanding of properties of materials and structures used and mechanisms of thermal conduction within the composite. [ABSTRACT FROM AUTHOR]

• A DEM-CFD model considering contact conduction was used to study the effective thermal conductivity (ETC) of pebble beds. • The ETC predicted by the current model is consistent with experimental data in a wide range of k s / k f from 1 to 10000. • If k s / k f is larger than 20, the difference of the ETC for the contact model and the non-contact model is greater than 10%. Pebble beds are main schemes for tritium breeding zones in the solid blanket for fusion reactors. The effective thermal conductivity of pebble beds (k e f f) is an important thermal property used in the thermal hydraulic design of solid blankets. In this study, a 3D DEM-CFD one-way coupling method considering contact conduction is applied to analyze the influence of solid contact conduction and solid-fluid-solid conduction on the effective thermal conductivity of pebble beds. The current numerical model gives a k e f f consistent with experimental data in a wide range of solid-to-fluid conductivity ratio k s / k f from 1 to 10,000. It can be concluded that when the k s / k f is more than 20, contact conduction should be taken into account to make a good prediction for k e f f. [ABSTRACT FROM AUTHOR]

Effective thermal conductivity (ETC), as a necessary parameter in the thermal properties of rock, is affected by the pore structure and the thermal conduction conditions. To evaluate the effect of fractures and saturated fluids on sandstone's thermal conductivity, we simulated thermal conduction along three orthogonal (X, Y, and Z) directions under air- and water-saturated conditions on reconstructed digital rocks with different fractures. The results show that the temperature distribution is separated by the fracture. The significant difference between the thermal conductivities of solid and fluid is the primary factor influencing the temperature distribution, and the thermal conduction mainly depends on the solid phase. A nonlinear reduction of ETC is observed with increasing fracture length and angle. Only when the values of the fracture length and angle are large, a negative effect of fracture aperture on the ETC is apparent. Based on the partial least squares (PLS) regression method, the fluid thermal conductivity shows the greatest positive influence on the ETC value. The fracture length and angle are two other factors significantly influencing the ETC, while the impact of fracture aperture may be ignored. We obtained a predictive equation of ETC which considers the related parameters of digital rocks, including the fracture length, fracture aperture, angle between the fracture and the heat flux direction, porosity, and the thermal conductivity of saturated fluid. [ABSTRACT FROM AUTHOR]

In the present paper, the effective thermal conductivities of Li4SiO4-packed beds with both ordered and random packing structures were investigated using thermal resistance network methods based on both an Ohm's law model and a Kirchhoff's law model. The calculation results were also validated and compared with the numerical and experimental results. Firstly, it is proved that the thermal resistance network method based on the Kirchhoff's law model proposed in the present study is reliable and accurate for prediction of effective thermal conductivities in a Li4SiO4-packed bed, while the results calculated with the Ohm's law model underestimate both ordered and random packings. Therefore, when establishing a thermal resistance network, the thermal resistances should be connected along the main heat transfer direction and other heat transfer directions as well in the packing unit. Otherwise, both the total heat flux and effective thermal conductivity in the packing unit will be underestimated. Secondly, it is found that the effect of the packing factor is remarkable. The effective thermal conductivity of a packed bed would increase as the packing factor increases. Compared with random packing at similar packing factor, the effective thermal conductivity of packed bed would be further improved with an ordered packing method. [ABSTRACT FROM AUTHOR]