Experimental Investigation Of Thermal Conductivity Research Articles

Molecular simulation and experimental investigation of thermal conductivity of flexible graphite film

Flexible graphite film (FGF), as a traditional interface heat dissipation material, has high anisotropy. It is a challenge to enhance both in-plane and through-plane thermal conductivity of FGF. For this reason, the effects of oxygen content, layer spacing, density and particle size on the in-plane and through-plane thermal conductivity of FGF were studied by both molecular simulation and experimental investigation. The simulation results indicate that the ways to improve the thermal conductivity of FGF include reducing oxygen content and layer spacing, increasing the density and matching the size of graphite sheets. The FGF prepared from room temperature exfoliated graphite (RTFGF) has a wide range of adjustable density (1.3–2.0 g/cm3) and thickness (50–400 μm). The thermal conductivity of the RTFGF is significantly improved after heat treatment owing to reduced oxygen content and layer spacing, which is consistent with the simulation results. Moreover, RTFGF with both high in-plane (518 W⋅m−1⋅K−1) and through-plane (7.2 W⋅m−1⋅K−1) thermal conductivity can be obtained by particle size matching of graphite.

Experimental investigation of thermal conductivity during aging of nanoporous sintered silver

Silver (Ag) paste sintering is used as a die-bonding technology for the next generation of power electronic modules as Ag offers a high melting temperature as well as excellent thermal and electrical conductivities. Ag paste sintering is performed using specific conditions depending on the type of paste and the users’ specifications (temperature, time, pressure), ending up in a porous joint. As a result, the properties of those joints are heavily influenced by their densities (i.e. porosity). Despite the numerous studies reported in the literature, the relationship between the density of the joint and its thermal conductivity remains an issue since access to the density of an embedded thin joint is very challenging. Furthermore, little is known on the evolution of the thermal conductivity in operating conditions. In this study, these issues were investigated by developing self-standing specimens with microstructures representative of those of real joints. In order to study a wide range of porosity, sintering was performed using a single time/temperature under various pressures. The thermal conductivity was measured using 3D flash method, consisting in applying a short non-uniform laser excitation on the surface of the sample, leading to three-dimensional heat transfer. The relationship between porosity and thermal conductivity is established for the as-sintered state and after aging up to 500 h at temperatures ranging from 150 °C to 350 °C and is compared to existing models. The evolution of the thermal properties during thermal aging is discussed considering both the elaboration conditions and the microstructure evolution.

The experimental investigation of thermal conductivity of aluminum metal matrix composites

Aluminum and its alloys have grown in popularity as steel and other comparable material substitutes. These alloys have exceptional mechanical characteristics. Understanding the thermal behavior of hybrid metal matrix composites is critical in a variety of applications. Metal Matrix Composites' (MMCs') heat conductivity is one of its primary advantages. Because MMCs are utilized in a broad variety of temperatures, it is critical to examine their thermal characteristics at various temperatures in order to understand their behavior. Thermodynamic characterization of composite materials has received a lot of attention and has evolved into a crucial element of materials research and engineering. The thermal conductivity of aluminum alloys with Sic and Gr hybrid metal matrix composites is investigated in this work. Sic (0%, 1.26%, 2.6%, and 3.76%) and Gr (0%, 1.26%, 2.6%, and 3.76%) reinforcements are employed in various weight fractions. A variety of casting processes is used to create the composites, which have an Al-based matrix reinforced with Sic and Gr particles. Casting processes include advantages such as decreased material waste and lower porosity levels. The goal of this study is to examine the thermal conductivity behavior of hybrid composites reinforced with varied weight fractions, particularly at lower weight fractions.

Experimental Investigation with ANN Modeling of Thermal Conductivity and Viscosity of a Ternary Nanofluid at Different Mixing Ratios and Volume Concentrations

An experimental investigation of thermal conductivity and viscosity of a new ternary nanofluid with four different mixing ratios and three different volume concentrations is conducted for different temperatures. Graphene nanoplatelets, copper oxide and alumina nanoparticles are used in the preparation of the ternary nanofluid with water-ethylene glycol mixture as the base fluid. The thermal conductivity results reveal the predominant contribution of graphene nanoplatelets in the particle mix. The maximum enhancement in thermal conductivity is found to be 19% at 0.5% volume concentration. Increasing the nanofluid concentration beyond 0.3% gives only a marginal enhancement in terms of figure of merit. Artificial neural network is also designed to predict the thermal conductivity and the viscosity. Seventy-eight sets of experimental data are utilised to build the ANN model and an overall regression data of 0.99496 is obtained indicating good agreement between the ANN model and the present experimental data.

Interaction of phonons with spherical nanoparticles embedded densely in simple crystalline matrix. Case of nitrogen-palladium nanocomposite

The results of experimental investigations of thermal conductivity of nanocomposites built of palladium spherical nanoparticles embedded in the structure of crystalline nitrogen are presented in this paper. The investigations were carried out on the samples containing the Pd nanospheres of diameters of 6, 8, 10, 12, 18, and 24 nm at the palladium fraction amounting to 15% of the nanocomposite volume. The measurements were performed with a steady-state heat flow method in the temperature interval of 2–35 K. For the analysis of the experimental results, the relaxation time approximation in the frame of the thermal conductivity Debye model was used. The analysis shows that the nitrogen matrix phonons can effectively interact with spherical nanoparticles in, at least, four different mechanisms. Two of those mechanisms, a diffuse scattering by the boundary of two media (which are the matrix and the material of the nanoparticle) and an oscillating resultant of interaction of nanoparticle phonons with the matrix phonons, result in a decrease of the nanocomposite thermal conductivity. The remaining two mechanisms would be considered nonthermal resistive scattering processes: The first of them is the specular scattering of the matrix phonons by the matrix and the nanoparticle material interface. The second one is a forward scattering, in which the matrix phonon penetrates the nanoparticle and afterward penetrates another one without any resistive interaction with phonons of the crystalline matrix. The analysis shows that the nonresistive processes are significantly more frequent in the investigated nanocomposites than the resistive ones. Such a conclusion is in perfect agreement with the results of the analysis of the phonon mean free path in the nitrogen crystal-palladium nanospheres composite.

Numerical and Experimental Investigations of Thermal Conductivity of 3D Printed Polylactic Acid

AbstractPolylactic acid (PLA) is a plastic material used occasionally for thermal insulation. Thus, information is required with respect to the thermal insulation property specific to various types of PLA. On the other hand, the development of 3D printing processes has led to ensuring the conditions for manufacturing PLA parts, with properties that can be modified by varying the input factors of printing process. The proposed experimental research method uses the measurement of temperature variation on one surface of PLA panel, while applying a cooling process on the opposite surface. Several panels with different characteristics are tested. The experimental results are processed using a specialized software and an empirical mathematical model is developed. The model highlights the influence of panel thickness, cooling duration, infill, and deposited layer thickness with respect to the temperature of the panel surface opposite to the cooled one.

New prediction models for the compressive strength and dry-thermal conductivity of bio-composites using novel machine learning algorithms

Bio-composites have become the prime material selection for green concrete because of the increasing awareness of environmental issues. Due to their highly heterogenous nature, most of the existing studies have focused on the experimental investigation of thermal conductivity (TC) and compressive strength (CS) of hemp-based bio-composites (HBC). However, the tests to estimate the TC and CS may take long time and be costly. In this study, three different machine learning (ML) techniques known as artificial neural network (ANN), adaptive neuro-fuzzy interface system (ANFIS), and multi-gene expression programming (MEP) are used to predict and formulate a mathematical expression for determining the CS and TC of HBC. A total of 159 and 86 experimental records for CS and TC, respectively, were achieved from the past published literature and the ten most influential input variables were considered. The performance of the proposed models was tested using root squared error (RSE), mean absolute error (MAE), Nash-Sutcliffe efficiency (NSE), root mean square logarithmic error (RMSLE), root mean square error (RMSE), correlation coefficient (R), coefficient of determination (R2), performance index (PI), the objective function (OF), and other statistical measures recommended in the literature. Sensitivity and parametric studies were also conducted to assess the coherence of the developed MEP equations with the actual physical phenomenon. Based on R, R2 and NSE, the increasing order is ANFIS > MEP > ANN for both CS and TC. The overall R-value for CS models are 0.9929 (ANFIS), 0.9848 (MEP) and 0.9691 (ANN) while 0.9997 (ANFIS) 0.9759 (MEP) and 0.9601 (ANN) for TC. The integrated measurements of statistical performance (PI and OF) of all models approach 0, stating the outburst performance and generalization capability of the developed models. MEP also provides a simple empirical mathematical equation for the prediction of CS and TC. The increasing trend of the importance of inputs variables for CS and TC was calculated. The parametric trend of each input for CS and TC is in strong agreement and consistent with the experimental results in the database. Thus, the projected equations for estimating the CS and TC of HBC are accurate and feasible and can be used by the designer and practitioners to save the total time required of hectic laboratory tests. However, it is suggested to validate the results of this research with the latest experimental data and other ML algorithms must be studied.

Experimental Investigation of Thermal Conductivity from Insulation Based on Rice Hulks: Guarded and Calibrated Hot Box Method

In developing countries, large quantities of agricultural residues associated with harvests are generated, given that agriculture is one of the most important economic activities. The valorization of these residues for the construction sector could contribute to the improvement of energy efficiency in buildings. Through passive techniques, the construction of insulating thermal-acoustics panels, blocks, and aggregate for reinforced concrete can improve the energy efficiency. In this study, an experiment was performed to measure thermal conductivity of the Agricultural-Thermal Insulation Panel (ATIP) based on rice hulks. These Agricultural-Thermal Insulation Panels were elaborated follow a standard process to compaction of the rice hulks to be employed as insulation material with a panel dimension of 200x200x34.5(mm3). A “Hot Box” configuration was used to obtain the thermal conductivity of the panels, using different temperature gradients between hot and cold chambers.

An experimental investigation of thermal conductivity and dynamic viscosity of Al2O3-ZnO-Fe3O4 ternary hybrid nanofluid and development of machine learning model

The growing interest in hybrid nanofluids is due to the synergistic effects of nanoparticles, which could give them better heat transfer properties as compared to base fluids, and conventional nanofluids. Several factors like temperature and volume fraction have been used in explaining the behaviours of hybrid nanofluids, however, the need to investigate comprehensively, the mixing ratios of hybrid nanofluids, remains a critical research area in the development of efficient nanofluids as heat transfer fluids. In this study, three mixture ratios of 1:1:1 (33.3% Al2O3, 33.3% ZnO, 33.3% Fe3O4), 1:2:1 (25% Al2O3, 50% ZnO, 25% Fe3O4), and 1:1:2 (25% Al2O3, 25% ZnO,50% Fe3O4) ternary hybrid nanofluid (THNF) are synthesized at volume concentrations of 0.5%, 0.75%, 1%, and 1.25%. All experiments were carried out at a temperature range between 25 °C-65 °C. The effect of temperature, volume concentration, mixture ratio, are examined, as well as the development of a machine learning model for accurate prediction. The thermal conductivity and dynamic viscosity behaviour of the THNF were investigated. The result showed that temperature and volume concentration significantly affected the thermophysical properties of the fluid. The optimum Thermal Conductivity enhancement (TCE) was retrieved for the 1:1:1 THNF, at 36.018%. The 2:1:1, and 1:2:1 mixture ratios had a 32.92%, and 31.68% TCE respectively. At 1% volume concentration, the optimum TCE (as compared with water) for the mono, hybrid, and THNF measured are 18.98%, 28.58%, and 32.45% respectively. It is seen that the least viscosity was recorded for the 1:1:1 mixture ratio (0.001 Pa.s), while the highest viscosity was measured for the 2:1:1 THNF mixture ratio (0.021 Pa. s). The Gaussian process regression (GPR) gave an excellent prediction showing an R2 value of 0.9656, and 0.934 for the thermal conductivity and dynamic viscosity prediction respectively. In terms of application to solar thermal systems, the low viscosity of 1:1:1 Al2O3–ZnO-Fe3O4 THNF makes that a low-pressure drop and pump work is required in practical applications of the 1:1:1 Al2O3–ZnO-Fe3O4 THNF.

Thermal Transport Evolution Due to Nanostructural Transformations in Ga-Doped Indium-Tin-Oxide Thin Films.

We report on a comprehensive theoretical and experimental investigation of thermal conductivity in indium-tin-oxide (ITO) thin films with various Ga concentrations (0–30 at. %) deposited by spray pyrolysis technique. X-ray diffraction (XRD) and scanning electron microscopy have shown a structural transformation in the range 15–20 at. % Ga from the nanocrystalline to the amorphous phase. Room temperature femtosecond time domain thermoreflectance measurements showed nonlinear decrease of thermal conductivity in the range 2.0–0.5 Wm−1 K−1 depending on Ga doping level. It was found from a comparison between density functional theory calculations and XRD data that Ga atoms substitute In atoms in the ITO nanocrystals retaining Ia-3 space group symmetry. The calculated phonon dispersion relations revealed that Ga doping leads to the appearance of hybridized metal atom vibrations with avoided-crossing behavior. These hybridized vibrations possess shortened mean free paths and are the main reason behind the thermal conductivity drop in nanocrystalline phase. An evolution from propagative to diffusive phonon thermal transport in ITO:Ga with 15–20 at. % of Ga was established. The suppressed thermal conductivity of ITO:Ga thin films deposited by spray pyrolysis may be crucial for their thermoelectric applications.

Micromechanical and experimental analysis of thermal conductivity of hemp-palmyra reinforced hybrid composites

The present work investigates the longitudinal and transverse thermal conductivity of hemp and palmyra fiber reinforced hybrid composites to use as thermal insulation material in buildings. Investigations are carried in accordance with ASTM-E1530. A total of thirteen test specimens of hybrid composites were fabricated with different fiber weight percentages (0, 10, 20, 30, and 40 wt%) by varying the weight ratio of hemp and palmyra as 1:1, 1:2, and 2:1 using hand lay-up method. The transverse thermal conductivity is also determined by developing a mathematical model based on microstructural mechanics and laws of heat transfer. The experimental investigations of thermal conductivity are compared and validated with FEA, developed mathematical model and analytical methods available in the literature. The effect of fiber orientation, volume fraction and inter-facial thermal resistance to determine the longitudinal and transverse thermal conductivity is incorporated by using finite element analysis. Investigations revealed that longitudinal thermal conductivity decreased by 36.08% and transverse thermal conductivity decreased by 37.74% at maximum fiber loading of 40 wt%.

Experimental Investigation of Thermal Conductivity and Specific Heat of the Calcium Phosphate Ore for a Drying Application

This paper discusses an experimental investigation to determine regression models for thermal properties of phosphate particles and to analyze the performances of the phosphate flash dryer. For this purpose, the specific heat capacity and thermal conductivity of phosphate particles were experimentally determined by the modulated differential scanning calorimetry (MDSC) and the modified transient plane source method (MTPS), respectively. Multiple regression models were developed to correlate the specific heat and thermal conductivity to moisture content, particle size, and temperature. Experimental results showed that the measured thermal conductivity and dry specific heat were found in the range of 0.07–0.61 W/m K and 510–630 J/kg·K, respectively. Furthermore, the specific heat increased almost linearly with temperature but decreased with particle size, while the thermal conductivity increased with moisture content and temperature but decreased with particle size. These correlations were integrated to the phosphate flash dryer mathematical model and used to analyze the thermal behavior of phosphate drying. Simulation results were compared to experimental data obtained on a bench-scale dryer, where the model exhibits an average error of 2% and 4% for moisture content and air temperature estimation, showing good fitting for practical data.

A comprehensive experimental investigation of thermal conductivity of a ternary hybrid nanofluid containing MWCNTs- titania-zinc oxide/water-ethylene glycol (80:20) as well as binary and mono nanofluids

In this study, the thermal conductivity (knf) of a ternary hybrid nanofluid containing Multi-walled Carbon Nanotubes (MWCNTs) - titania-zinc oxide/water-ethylene glycol (EG) (80:20) as well as binary and mono nanofluids has been studied. The nanofluid fabrication was performed by the two-step method by dispersing the nanoparticles in the base fluid using ultrasonic waves. The volume fractions of ternary hybrid nanofluids were φ= 0.1 % to 0.4 %, and mono and binary hybrid nanofluids were fabricated in φ= 0.1 % and φ= 0.4 %, respectively. After ensuring the stability of the nanofluids, the knf was measured by the transient hot-wire method at a temperature range of T = 25−50 °C. The experimental results show that with increasing the temperature, the knf also increases. Also, increasing the φ increases the knf. At higher φ, the effect of increasing temperature is even more evident. According to the results, the highest increase in knf containing MWCNTs/water-EG was observed at a φ= 0.4 % and T = 50 °C, which showed an increase of 17.82 % compared to the base fluid. Finally, a mathematical model was proposed as a function of temperature and φ to estimate the knf of a ternary hybrid nanofluid. A comparison of the results of the proposed mathematical model with the experimental results showed that the proposed model is highly accurate.

Experimental investigation of thermal conductivity and its ANN modeling for glycol-based Ag/ZnO hybrid nanofluids with low concentration

A novel glycol-based silver-coated zinc oxide (Ag/ZnO) hybrid nanofluids has been synthesized to investigate its thermo-physical properties with low volume concentrations (ϕ = 0.05% to ϕ = 0.2%) in comparison with ZnO nanofluids. The Ag/ZnO nanoparticles of size 25–40 nm are synthesized by chemical precursor method. The synthesized nanoparticles were characterized by scanning electron microscopy, transmission electron microscopy and X-ray diffraction analysis. The stability of the dispersed Ag/ZnO hybrid nanoparticles in glycol was observed visually and by zeta potential values. The thermal conductivity of the prepared nanofluids was measured experimentally by KD2 Pro, and maximum enhancement of 15.66% and 20.53% is reported at 25 °C and 55 °C, respectively, due to the coating of higher thermal conductivity Ag on the ZnO nanoparticles. An empirical correlation has been developed by the curve fitting technique to predict the thermal conductivity enhancement at different concentrations and temperatures. Also, experimentally measured results have been compared with the model developed by an artificial neural network. The correctness of the model has been evaluated by the R-squared value, mean square error, and average absolute relative deviation percent. Based on an experimental data test set of 104 samples, the ANN model consisting of 2 hidden layers with 10 neurons in each layer was the most accurate fit.

Experimental investigation of thermal conductivity and stability of TiO2-Ag/water nanocompositefluid with SDBS and SDS surfactants

In recent times, addition of two nanoparticles in base fluid called hybrid (or) nanocompositefluid is the subject of research in the area of nanofluid. In general, stability of single or composite nanoparticles in base fluid is the key issue that restricts the practical applications of nanofluids. In this paper, stability of TiO2-Ag/water nanocompositefluid with and without the addition of common surfactants like sodium dodecyl sulfate (SDS) and sodium dodecyl benzene sulfonate (SDBS) in different weight fractions (0.1, 0.3, 0.5, and 0.7 wt.%) is investigated. Thermal conductivity of water is increased by 12.2% by the addition of TiO2-Ag nanocomposite particle (≈ 9:1). It is found that addition of surfactant alters the enhancement in thermal conductivity of TiO2-Ag/water i.e. 29.6% for 0.1 wt.% SDS and 2.1% for 0.1 wt.% SDBS. The zeta potential is measured as −50.7 mV for 0.1 wt.% SDBS and −26.2 mV for 0.1 wt.% SDS which confirms good stability.

Estimation of thermal conductivity of snow by its density and hardness in Svalbard

The results of experimental investigation of thermal conductivity of snow on the Svalbard archipelago in the conditions of natural occurrence are considered. The observations were carried out in the spring of 2013–2015 in the vicinity of the meteorological station «Barentsburg». The obtained data were processed using the Fourier equation of thermal conductivity that allowed determination of the coefficient t of thermal conductivity of the snow with different structure and density. The thermal conductivity of snow depends on the contacts between ice crystals. The larger the contact area, the better the heat transfer from one layer to another. But the strength characteristics of snow, and especially its hardness, depend on the bonds between ice crystals, so the thermal conductivity and hardness of snow depend on the structure of snow. Note, that measurements of snow hardness are less laborious than measurements of its thermal conductivity. For layers of snow cover of different hardness the relationship between snow thermal conductivity and its density has been established. To verify the reliability of the approach to the determination of snow thermal conductivity, numerical experiments were performed on a mathematical model, which did show good convergence of the results. The obtained formulas for the coefficient of thermal conductivity of very loose, loose, medium and hard snow (according to the international classification of seasonal snow falls) are compared with the data of other studies. It was found that when the snow density is within the range 0.15–0.40 g/cm3 these formulas cover the main variety of thermal conductivity of snow. This allows estimating the coefficient of thermal conductivity and to determine the thermal resistance of snow cover in the field by measuring the density and hardness of different layers of snow.

Experimental investigation of thermal conductivity of nanofluids containing of hybrid nanoparticles suspended in binary base fluids and propose a new correlation

In this experimental study, preparation, stability and thermal conductivity of the MWCNTs-SiC/Water-EG hybrid nanofluid were investigated. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) methods were used to characterize the nanoparticles. Nanofluid stability was monitored by DLS test. According to the DLS results, the nanofluid contained nanoparticles. The thermal conductivity of the hybrid nanofluid was measured using the KD2-Pro thermal analyzer and the KS-1 sensor at a temperature range of 25–50 °C and a solid volume fraction range of 0–0.75%. According to the results, the thermal conductivity of the nanofluid increased further at higher concentrations of the nanoparticles. Therefore, the effect of temperature on the thermal conductivity was higher at higher temperatures. The maximum thermal conductivity of the nanofluid increased up to 33% relative to the base fluid at a temperature of 50 °C and a concentration of 0.75%. A correlation with high accuracy was obtained by fitting the experimental data. The correlation was used to calculate the thermal conductivity of the nanofluid. Given the desirable thermal properties of this nanofluid, it can be used as an alternative fluid in practical systems with high heat transfer potential in the field of heat transfer.

Modelling and Characterization of Effective Thermal Conductivity of Single Hollow Glass Microsphere and Its Powder.

Tiny hollow glass microsphere (HGM) can be applied for designing new light-weighted and thermal-insulated composites as high strength core, owing to its hollow structure. However, little work has been found for studying its own overall thermal conductivity independent of any matrix, which generally cannot be measured or evaluated directly. In this study, the overall thermal conductivity of HGM is investigated experimentally and numerically. The experimental investigation of thermal conductivity of HGM powder is performed by the transient plane source (TPS) technique to provide a reference to numerical results, which are obtained by a developed three-dimensional two-step hierarchical computational method. In the present method, three heterogeneous HGM stacking elements representing different distributions of HGMs in the powder are assumed. Each stacking element and its equivalent homogeneous solid counterpart are, respectively, embedded into a fictitious matrix material as fillers to form two equivalent composite systems at different levels, and then the overall thermal conductivity of each stacking element can be numerically determined through the equivalence of the two systems. The comparison of experimental and computational results indicates the present computational modeling can be used for effectively predicting the overall thermal conductivity of single HGM and its powder in a flexible way. Besides, it is necessary to note that the influence of thermal interfacial resistance cannot be removed from the experimental results in the TPS measurement.

Application of Poensgen apparatus for determining the thermal conductivity of reflective insulations

Multilayer reflective insulations are a combination of several or a dozen low emission screens compressed together, separated by layers of bubble foil or polyethylene foam. This paper presents the results of experimental investigation of thermal conductivity of multilayer reflective insulations. The measurements were made with Poensgens LaserComp FOX 314 apparatus. Five samples of reflective insulation and one sample of foamed polystyrene have been tested. The difficulties of determining the replacement thermal resistance for the discussed materials have been presented. Information about the apparatus used, theory of the measurement method, procedure of the experiment and method of sample preparation were presented. The study was performed for four different temperature pairs representing the real thermal conditions in Poland throughout the year. On the basis of the obtained measurement results the average thermal conductivity and average thermal resistance of the tested materials were determined. The relation between the obtained thermal conductivity and thermal resistance depending on the temperature was discussed.

Experimental Investigation of Thermal Conductivity of Meat During Freezing

The cryogenic technologies of processing and storage of agricultural products are becoming increasingly indispensable in the food industry as an important factor of ensuring food safety. One of such technologies is the shock freezing of meat, which provides a higher degree of preservation of the quality of frozen products in comparison with traditional technologies. The thermal conductivity of meat is an important parameter influencing the energy consumption in the freezing process. This paper presents the results of an experimental investigation of the temperature dependence of the thermal conductivity of beef. The measurements were taken by using a specially designed measurement cell, which allows covering the temperature range from 80 to 300 K.