Temperature-dependent Thermal Properties Research Articles

Temperature-dependent thermal conductivity of MBE-grown epitaxial SrSnO3 films

As an ultrawide bandgap (∼4.1 eV) semiconductor, single crystalline SrSnO3 (SSO) has promising electrical properties for applications in power electronics and transparent conductors. The device performance can be limited by heat dissipation issues. However, a systematic study detailing its thermal transport properties remains elusive. This work studies the temperature-dependent thermal properties of a single crystalline SSO thin film prepared with hybrid molecular beam epitaxy. By combining time-domain thermoreflectance and Debye–Callaway modeling, physical insight into thermal transport mechanisms is provided. At room temperature, the 350-nm SSO film has a thermal conductivity of 4.4 W m−1 K−1, ∼60% lower than those of other perovskite oxides (SrTiO3, BaSnO3) with the same ABO3 structural formula. This difference is attributed to the low zone-boundary frequency of SSO, resulting from its distorted orthorhombic structure with tilted octahedra. At high temperatures, the thermal conductivity of SSO decreases with temperature following a ∼T−0.54 dependence, weaker than the typical T−1 trend dominated by the Umklapp scattering. This work not only reveals the fundamental mechanisms of thermal transport in single crystalline SSO but also sheds light on the thermal design and optimization of SSO-based electronic applications.

Parametric analysis of the thermal model of electric discharge machining of Al-10%SiCmicro-SiCnano hybrid composites

The authors developed a finite element model for electric discharge machining (EDM) that utilizes a Gaussian heat source. The model takes into account the spark radius and the energy distribution factor, which are both dependent on the pulse on time and pulse current. The model also incorporates latent heat, specific heat, and temperature-dependent thermal conductivity properties. The authors emphasize the paucity of study on simulating EDM of hybrid composites utilizing the energy distribution factor as a function of performance parameters, which adds novelty to the research. This study used an aluminum-based hybrid composite reinforced with micro and varying percent of nano SiC particles due to their strength-enhancing properties. The L9 orthogonal array was used for experimental design.A parametric analysis was conducted to investigate the effects of SiC nanoparticle percentage, pulse current, and pulse on time on material removal rate (MRR) and surface roughness (SR). The simulation results were compared with experimental data from previous study. The findings revealed that an increase in the percentage of SiC nanoparticles, pulse current, and pulse on time resulted in a higher MRR. Furthermore, these factors initially caused an increase in SR, followed by a subsequent decrease. Notably, the pulse current exhibited the greatest impact on both MRR and SR, while the pulse on time was the second most significant factor for MRR and the least influential factor for SR. Increasing the percentage of SiC nanoparticles in the Al-based hybrid composite had the least effect on MRR but emerged as the second most influential factor for SR. In summary, the simulation results aligned with the outcomes of prior experimental investigations.

Iterative Solutions for the Nonlinear Heat Transfer Equation of a Convective-Radiative Annular Fin with Power Law Temperature-Dependent Thermal Properties

The temperature distribution in a conductive-radiative rectangular profiled annular fin with internal heat generation is scrutinized in the present investigation. The nonlinear variation of thermal conductivity and heat transfer coefficient governed by the power law is considered. The analytical approximation for the non-dimensional temperature profile is obtained using the differential transform method (DTM)-Pade approximant. The nondimensionalization of the governing energy equation using dimensionless terms yields a nonlinear ordinary differential equation (ODE) with corresponding boundary conditions. The resulting ODE is analytically solved with the assistance of the DTM-Pade approximant procedure. Furthermore, the impact of thermal parameters on the temperature field and thermal stress is elaborated with graphs. The important results of the report divulge that temperature distribution greatly enhances with an augmentation of the heat generation parameter, but it gradually reduces with an increment in the magnitude of the thermogeometric and radiative-conductive parameter.

An inverse analysis to estimate the thermal properties of nanoporous aerogel composites using the particle swarm optimized deep neural network

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.

Bayesian calibration and reliability analysis of ultra high-performance fibre reinforced concrete beams exposed to fire

A study of uncertainty quantification and reliability of ultra-high-performance fibre reinforced concrete (UHPFRC) beams exposed to fire is presented. The study sets forth two methodologies, the first involving the stochastic calibration of temperature-dependent thermal properties of UHPFRC via Bayesian inversion, and the second concerning the computation of the reliability of UHPFRC beams in fire via Monte Carlo Simulation (MCS). Using the calibrated posterior probability distributions of temperature-dependent thermal properties of UHPFRC in stochastic heat transfer analyses results in predictive temperature distributions that reasonably track (within 95% confidence interval) the temperature response reported on UHPFRC beams specimen subjected to 80 and 60 minutes standard fire. Stochastic temperature distributions based on the calibrated thermal properties were sequentially transferred via a time series surrogate model, into a structural-fire reliability analysis of UHPFRC beams designed to the specifications of the ACI 544. Reliability analysis is conducted and the obtained reliability index generally reduced with increasing fire exposure for the UHPFRC beam considered and fire resistance is estimated based on a reliability target of 0.7.

Analytical and experimental investigations of rake face temperature considering temperature-dependent thermal properties

In metal cutting, rake face temperature is a critical factor affecting the quality of processed parts and tool wear. However, this temperature is difficult to estimate because of the high strain rate and barrier effect of chips. This paper presents an integrated analytical and experimental approach to predict rake face temperature, which proposes an improved analytical model considering temperature-dependent thermal properties. The considered temperature properties mainly include thermal conductivity (TC) and thermal diffusivity (TD) of the workpiece and cutting tool, which has rarely been considered in previous studies. With the measured cutting force and tool–chip contact length, the improved analytical model can predict the tool temperature based on an adaptive method to match the thermal properties and temperature at an arbitrary point. Moreover, a relatively new in situ measurement method for directly capturing the radiation of the rake face temperature using a two-colour pyrometer and slotted workpiece is presented. This new technique can eliminate the barrier effect of the chip without interrupting the cutting process. This experimental method is proved to be able to stably measure the rake face temperature with a deviation less than 3%, furthermore, the captured temperatures are much higher when compared with conventional methods under the comparable cutting conditions. The comparison of rake face temperature between the predicted and the measured results shows an average prediction error of 8.6% of the proposed method, proving its superiority over conventional models using constant thermal properties.

A new general analytical PBEM for solving three-dimensional transient nonlinear heat conduction problems with spatially-varying heat generation

In this paper, a polygonal boundary element method (PBEM) is presented, to solve the transient nonlinear heat conduction problems with spatially variable heat generation and temperature-dependent thermal physical properties. A new general method is developed to analytically compute the domain integrals regarding arbitrary nonlinearly-varying thermal conductivity, specific heat, and density, by which the computations of numerous Gaussian points in the numerical method can be circumvented and the efficiency of the PBEM can be significantly improved. The finite difference scheme is employed to evaluate the transient term, and the Newton iterative method is used to search the exact solution of the nonlinear system equation. Four numerical examples are designed to examine the property of the proposed method. The results indicate that the proposed analytical PBEM can accurately solve the three-dimensional transient nonlinear heat conduction problems with heat generation.

Temperature-Dependent Thermal Parameter Identification of Ceramic Nanorod Aerogels Composite in the Ultrahigh Temperature Environment

The identification of the thermal properties of advanced materials is of great importance in engineering application. In this work, an inverse scheme is proposed to identify the temperature-dependent thermal parameters of ceramic nanorod aerogels (CNRAs) composite in the ultrahigh temperature environment up to 1873 K. The feasibility of the proposed method is successfully tested by an analytical solution for CNRAs with known material properties. Furthermore, the temperature-dependent thermal properties of CNRAs are successfully obtained using the experimental data acquired from the heat conduction experimental testing for a CNRAs plate. Lastly, the obtained thermal properties are used to simulate an arc-heated wind tunnel (AHWT) test of a receiving satellite antenna assembly using the FEM method. The simulated temperature at measured data has a very good agreement with the experimental data. This further demonstrates the strong capability of the proposed inverse method. In summary, the proposed approach provides an important approach for the identification of nonlinear and temperature-dependent thermal properties of advanced materials.

Thermal analysis for in-situ consolidation in the AFP process

An analytical approach was developed for assessing the thermal history of thermoplastic composites during tape placement for in-situ consolidation of the automated fiber placement (AFP) technique. In this study, the heat-conduction equation is developed and solved for internal energy instead of temperature because the diffusivity does not significantly change over a wide range of temperatures in the AFP process, despite the significant change in the specific heat and conductivity. The three-dimensional internal energy history is derived in an integrated form using the Green function technique. The temperature field obtained from the internal energy field agreed with the finite element solution, where the temperature-dependent thermal properties were considered. The effects of manufacturing parameters, such as the placement speed and thickness of the placed laminates, on the thermal history of laminated composites during AFP are discussed using the present approach and finite element analysiss.

3D numerical modeling for thermo-mechanical behavior of additively manufactured titanium alloy parts with process-induced defects

The defects due to the rapid heating and cooling in powder bed fusion affect significantly the mechanical properties of additively manufactured as-built parts. However, the effect of process-induced defects on the thermo-mechanical behaviors of as-built parts is still unclear. In this paper, considering the process-induced interfacial lack of fusion (LoF) and pores, we developed a coupled thermo-mechanical model of titanium alloy parts in the powder bed fusion process. The equivalent temperature-dependent thermal properties of the parts with defects are calculated based on mixture theory. The three-dimensional thermal, mechanical, and displacement fields are predicted based on the differential quadrature method (DQM). The accuracy of the proposed model is verified by the comparison with the predictions and experimental data in the references. The effect of crucial parameters on the thermo-mechanical responses of as-built parts is analyzed, including energy densities, scan patterns, preheating temperature, LoF dimension, porosity, and powder layer thickness. The predicted results show that the process and geometry parameters play a vital role in the temperature distribution, residual stress buildup, and deformation of the printed parts. In addition, the LoF defect triggers the stress jump at the interface of the defect/powder bed and powder bed/substrate. The predicted results can be beneficial to provide a guideline for the design and additive manufacturing of titanium alloys.

A heat flux-corrected experimental inverse technique for simultaneously estimating the thermal properties of a metallic medium as functions of temperature

ABSTRACT This paper presents an experimental inverse approach to simultaneously estimate the temperature-dependent thermal properties of AISI 316 stainless steel. The heat flux conducted to the sample was corrected by using a transducer, evaluating contact resistance at microscopic level, and performing experiments under vacuum. Estimates were severely biased when heat flux correction was not applied. Metaheuristics were used to enlarge the search space, which can cover the thermal properties of all known metallic materials, thereby taking advantage of better thermal modeling adequacy. The estimation reliability was shown by comparison with literature data, statistical significance, uncertainty analysis, and inverse heat flux retrieval.

Structural and thermal properties of Eu2Ga11Sn35

Clathrates have been reported to form in a variety of different structure types; however, inorganic clathrate-I materials with a low-cation concentration have yet to be investigated. Furthermore, tin-based compositions have been much less investigated as compared to silicon or germanium analogs. We report the temperature-dependent structural and thermal properties of single-crystal Eu2Ga11Sn35 revealing the effect of structure and composition on the thermal properties of this low-cation clathrate-I material. Specifically, low-temperature heat capacity, thermal conductivity, and synchrotron single-crystal x-ray diffraction reveal a departure from Debye-like behavior, a glass-like phonon mean-free path for this crystalline material, and a relatively large Grüneisen parameter due to the dominance of low-frequency Einstein modes. Our analyses indicate thermal properties that are a direct result of the structure and composition of this clathrate-I material.

Determination of elevated temperature material properties by ANN-based FE model

PurposeElevated temperature material properties are essential in predicting structural member's behavior in high-temperature exposures such as fire. Even though experimental methodologies are available to determine these properties, advanced equipment with high costs is required to perform those tests. Therefore, performing those experiments frequently is not feasible, and the development of numerical techniques is beneficial. A numerical technique is proposed in this study to determine the temperature-dependent thermal properties of the material using the fire test results based on the Artificial Neural Network (ANN)-based Finite Element (FE) model.Design/methodology/approachAn ANN-based FE model was developed in the Matlab program to determine the elevated temperature thermal diffusivity, thermal conductivity and the product of specific heat and density of a material. The temperature distribution obtained from fire tests is fed to the ANN-based FE model and material properties are predicted to match the temperature distribution.FindingsElevated temperature thermal properties of normal-weight concrete (NWC), gypsum plasterboard and lightweight concrete were predicted using the developed model, and good agreement was observed with the actual material properties measured experimentally. The developed method could be utilized to determine any materials' elevated temperature material properties numerically with the adequate temperature distribution data obtained during a fire or heat transfer test.Originality/valueTemperature-dependent material properties are important in predicting the behavior of structural elements exposed to fire. This research study developed a numerical technique utilizing ANN theories to determine elevated temperature thermal diffusivity, thermal conductivity and product of specific heat and density. Experimental methods are available to evaluate the material properties at high temperatures. However, these testing equipment are expensive and sophisticated; therefore, these equipment are not popular in laboratories causing a lack of high-temperature material properties for novel materials. However conducting a fire test to evaluate fire performance of any novel material is the common practice in the industry. ANN-based FE model developed in this study could utilize those fire testing results of the structural member (temperature distribution of the member throughout the fire tests) to predict the material's thermal properties.

Thermal environment of the Chang&amp;rsquo;E-5 landing site and its effect on the external temperature of the lander

<p indent="0mm">The thermal environment of the lunar surface is extremely important to the thermal design of the lander, the placement of the detection instruments, and the interpretation of scientific exploration data. Clarifying the source and intensity of radiation on the outer surface of the lander is the key to its thermal management. In this paper, we first reported continuous temperature records over a 47.2 h period from five thermal couple sensors mounted on the auxiliary pillars of the landing gear of Chang’E-5 (CE-5). The recorded temperatures varied from a relatively small range of <sc>245.68–272.52 K</sc> at the beginning to a considerably wider range of <sc>284.86–369.76 K</sc> at the end of the recording period. To analyze the obtained CE-5 temperature records, we first developed a lunar surface thermal environment model with a layered regolith and temperature-dependent thermal physical properties. The model calculated that the ambient temperature of the CE-5 landing site over the sensor recording period increased from 341.40 to <sc>356.15 K.</sc> The calculated temperature was comparable to the estimates based on the <italic>in</italic>-<italic>situ</italic> spectral measurement, whereas it was systematically <sc>6–12 K</sc> higher than Diviner thermal infrared brightness temperature. We further developed a heat conduction model of the sensor-mounted auxiliary pillar and considered the surface temperature and the pillar geometry with respect to the Sun’s and the Earth’s orbital parameters. By introducing an impact factor<italic> F</italic> and via trial and error, we fitted the five CE-5 lunar temperature records with the RMESs of 0.72, 2.14, 0.53, 1.35, and <sc>3.36 K,</sc> respectively. Our analysis showed that the lunar surface thermal environment has a significant effect on the temperatures of both the shaded and sunny sides of the lunar lander. The environmental impact on the shaded side even exceeds that on the sunny side during the CE-5 recording period. The results of this paper are of great significance to both the theoretical research on the mechanism of the lunar thermal environment and the engineering applications in the thermal management design of a lunar lander, site selection of a lunar exploration mission, and temperature-related data interpretations, such as <italic>in</italic>-<italic>situ</italic> spectral data analysis.

Temperature Dependence of Thermal Properties of Ex Vivo Porcine Heart and Lung in Hyperthermia and Ablative Temperature Ranges

This work proposes the characterization of the temperature dependence of the thermal properties of heart and lung tissues from room temperature up to > 90 °C. The thermal diffusivity (α), thermal conductivity (k), and volumetric heat capacity (Cv) of ex vivo porcine hearts and deflated lungs were measured with a dual-needle sensor technique. α and k associated with heart tissue remained almost constant until ~ 70 and ~ 80 °C, accordingly. Above ~ 80 °C, a more substantial variation in these thermal properties was registered: at 94 °C, α and k respectively experienced a 2.3- and 1.5- fold increase compared to their nominal values, showing average values of 0.346 mm2/s and 0.828 W/(m·K), accordingly. Conversely, Cv was almost constant until 55 °C and decreased afterward (e.g., Cv = 2.42 MJ/(m3·K) at 94 °C). Concerning the lung tissue, both its α and k were characterized by an exponential increase with temperature, showing a marked increment at supraphysiological and ablative temperatures (at 91 °C, α and k were equal to 2.120 mm2/s and 2.721 W/(m·K), respectively, i.e., 13.7- and 13.1-fold higher compared to their baseline values). Regression analysis was performed to attain the best-fit curves interpolating the measured data, thus providing models of the temperature dependence of the investigated properties. These models can be useful for increasing the accuracy of simulation-based preplanning frameworks of interventional thermal procedures, and the realization of tissue-mimicking materials.

Thermal properties of cubic NaSbS2: diffusion dominant thermal transport above the Debye temperature.

We elucidate the thermal properties of superionic conductors, which are of intense current interest for solid-state battery applications. The temperature-dependent thermal properties of superionic NaSbS2 were investigated by analyses of appropriate models revealing that a predominant contribution to thermal transport above the Debye temperature is from thermal diffusion.

Temperature-Dependent Thermal and Mechanical Properties of a Wire Arc Additively Manufactured Low Transformation Temperature Steel

Temperature-Dependent Thermal and Mechanical Properties of a Wire Arc Additively Manufactured Low Transformation Temperature Steel

Progressive collapse resistance of reinforced concrete beam-column connection under fire conditions

To reveal the reinforced concrete (RC) structural response under fire-induced progressive collapse scenarios, 3D finite element (FE) models were developed to investigate the effect of high temperatures on the collapse resisting mechanisms of RC beam-column connections. To describe the behavior of RC connections at elevated temperatures, temperature-dependent thermal and mechanical properties of concrete and reinforcing steel were adopted in the 3D FE model. The sequentially coupled thermal–mechanical analysis was performed with the explicit solver in a quasi-static manner. The concrete damaged plasticity (CDP) and ductile damage for metals (DDM) were adopted to better describe the failure of concrete and steel rebar, respectively. The proposed numerical model was validated by experimental data at different temperatures from literature. To understand better the collapse resistance of RC beam-column connections, a new loading scheme was adopted in the developed model. The load capacity of RC connection under fire conditions was investigated analytically and numerically. The effects of top and bottom reinforcement ratios, concrete strength, beam depth and fire severity on the collapse resisting mechanisms were investigated. The regulated chord rotation failure criteria recommended by the U.S. Department of Defense (DoD) were utilized and showed to be conservative on the collapse identification of RC structures under fire conditions.

Complementary transient thermal models and metaheuristics to simultaneously identify linearly temperature-dependent thermal properties of austenitic stainless steels

This paper presents an experimental approach for simultaneously identifying the temperature-dependent thermal conductivity (k) and specific heat (c p ) of 304 austenitic stainless steel (ASS) using complementary transient experiments and metaheuristics. Inverse thermal analysis was based on two heat conducting solids with different geometries. In estimation problems in general, one seeks to obtain as much sensitive data as possible using as few sensors as possible. Single thermocouple data were collected for each thermal model. An objective function fitting these complementary measurements to the corresponding numerical temperatures was minimized using the Lichtenberg algorithm. This metaheuristic algorithm takes advantage of more sensitive information provided by using complementary data, enabling for an accurate inverse solution, even when dealing with wide search ranges. The proposed technique provides a cost-effective and robust property estimation from tests conducted at room temperature. Single-step estimation occurred throughout the whole temperature domain to determine the parameters for linear functions representing the temperature dependence of k and c p . The obtained lines agreed well with curves from the literature. The 95% confidence bounds for the parameters of interest indicated deviations below ± 8.5%. Error analysis considering numerical and experimental processes showed an uncertainty close to ± 3%, applied to all estimated parameters.

Heat Transfer and Structural Characteristics of Dissimilar Joints Joining Ti-64 and NiTi via Laser Welding

This study investigates the thermal-stress characteristics of a bi-metallic Ti-6Al-4V-Nitinol butt joints manufactured via laser welding. Particularly, the thermal profile along the weld interface and the deformation profile of the finished welded workpiece. A decoupled transient thermomechanical simulation model was constructed to recreate the welding process. This decoupled thermomechanical simulation model consisted of two transient simulation models. A transient thermal simulation model and a transient structural simulation model, with the thermal history of the transient thermal model being fed into the transient structural model. Both the thermal and structural portions of the model utilized temperature-dependent thermal and structural properties of Ti-6Al-4V and Nitinol. The temperature profile of the transient thermal-stress model aligns with the experimental thermal profile within 5% error. The deformation profile also matches the experimental results within 5% error. This approach to modeling laser welding can stand as a guide to predict both thermal and deformation profiles generated during the laser welding process.