Temperature-dependent Thermal Properties Research Articles

A synergistic experimental and theoretical study elucidating the electronic and thermal properties in spinel CuInSnS4

Quaternary chalcogenides of different structure types continue to be of interest due to the novel physical properties they exhibit and for applications ranging from optoelectronics to energy-related technologies. Herein we report on the electronic and thermal properties of spinel CuInSnS4. UV–vis–NIR spectroscopy indicates strong absorption in the visible-light region with an indirect bandgap of 1.52 eV. First-principles computations corroborate our experimental data and reveal that the band-edge electronic properties are due to strong p−d and s−p hybridization and antibonding interactions. Analyses of temperature-dependent thermal properties together with first principles simulations reveal strong anharmonicity and low-lying optical branches that hybridize with the acoustic modes effectively suppressing thermal conductivity. This intrinsically very low thermal conductivity is much lower than that of related chalcogenides. Our findings are discussed in the light of ongoing interest in quaternary metal chalcogenide materials and may aid in the development of this and similar chalcogenides for applications of interest.

DEM-CFD Simulation Analysis of Heat Transfer Characteristics for Hydrogen Flow in Randomly Packed Beds

In this study, three randomly packed beds with varying tube-to-particle diameter ratios (D/d) are constructed using the discrete element method (DEM) and simulated via CFD under low pore Reynolds numbers (Rep < 100). An innovation of this research lies in the application of hydrogen in randomly packed beds, coupled with the consideration of its temperature-dependent thermal properties. The axial analysis of the heat transfer characteristics shows that PB−5 and PB−6 achieve thermal equilibrium 44% and 58% faster than PB−4, respectively, demonstrating enhanced heat transfer efficiency. However, at higher flow rates (0.8 m/s), the large-sized fluid channels in PB−6 severely impact the heat transfer efficiency, slightly reducing it compared to PB−5. Additionally, this study introduces a localized segmentation method for calculating the axial local Nusselt number, showing that the axial local Nusselt number (Nu) not only exhibits an inverse relationship with the axial porosity distribution, but also matches its amplitude fluctuations. The wall effect significantly impacts the flow and temperature distribution in the packed bed, causing notable velocity and temperature oscillations in the near-wall region. In the near-wall region, the average temperature is lower than in the core region, and the axial temperature profile exhibits more intense oscillations. These findings may provide insights into the use of hydrogen in randomly packed beds, which are vital for enhancing industrial applications such as hydrogen storage and utilization.

Thermal behavior of dry-cast concrete blocks masonry walls at elevated temperatures

This study aims to contribute to a better understanding of the behavior of masonry structures in the event of a fire, addressing a critical gap in both local and international standards and design guidance. Particularly in Brazil, the widespread adoption of structural masonry contrasts with the absence of national standards for evaluations at high temperatures, mainly due to the scarcity of research on the subject, potentially leading to severe consequences for life safety and property losses. This paper addresses a comprehensive study on the thermal behavior of dry-cast hollow concrete blocks masonry at high temperatures. The study combines both experimental and numerical analyses and involves underexplored topics, including characterization of thermal properties at elevated temperatures of commonly used blocks, post-fire condition of masonry's components, and determination of isotherms in the masonry cross-section in scenarios with one or both faces of the wall exposed to fire (separating and non-separating walls). Despite differences in the physical characteristics of the concrete used in block production, the temperature dependency of thermal properties obtained during experiments showed similar to that in Eurocode 2. Numerical and experimental results also indicate a low influence of block strength and mortar joints on the temperature evolution within the masonry. A key finding refers to a relatively fast temperature increase during heating due to the small thickness of the shells and webs of the blocks, thus impacting the performance of masonry structures in fire.

Study of the photothermal response of a multilayer structure doped with VO2@Au nanoshells

In this paper, we demonstrate a theoretical study of a multiphysics problem to solve for the photothermal response of a one-dimensional multilayer structure containing a layer doped with VO2@Au nanoshells. The VO2@Au nanoshell consists of a gold (Au) shell and a core of the phase change material vanadium dioxide (VO2) where the VO2 core transitions from a semiconductor state to a conductor state at the critical temperature of 68 °C. This behaviour results in thermal induced optical tunability through this reversible phase change of the VO2, due to the temperature dependent optical and thermal properties. The presence of the VO2 core, functioning as an ultra-fast and reversible optical phase-change material, leads to the emergence of photothermal induced bistability. The layer doped with the VO2@Au nanoshell is approximated as an effective medium using the Maxwell-Garnett Theory to enable an analytical solution. In this study, the optical response of the multilayer structure is obtained using the Transfer Matrix Method, while the thermal response for both stationary and transient states is solved using the Green’s Function Method and Kirchhoff’s Transformation. These equations are interconnected through the heat source term in the heat diffusion equations, representing the local heat generation induced by the continuous-wave laser applied to the structure. Our findings indicate that at the wavelengths of 658 nm and 747 nm, there are two distinct photothermal responses arising from the phase change of the VO2 core. At these wavelengths, the absorption of light increases and decreases, respectively, because of the VO2 phase change. This analytical method not only offers a thorough exploration of the fundamentals of induced photothermal responses in multilayer structures but also holds considerable potential for various applications, including solar cells, photothermal therapy, and nanothermal sensors.

Contact rheological DEM model for visco-elastic powders during laser sintering

Laser sintering is a widely used process for producing complex shapes from particulate materials. However, understanding the complex interaction between the laser and particles is a challenge. This investigation provides new insights into the sintering process by simulating the laser source and the neck growth of particle pairs. First, a multi-physics discrete element method (DEM) framework is developed to incorporate temperature-dependent contact rheological and thermal properties, incorporating heat transfer and neck formation between the particles. Next, energy transport by ray tracing is added to allow for computing the amount of laser energy absorbed during sintering. The DEM model is calibrated and validated using experimental data on neck growth and temperature evolution of particle pairs made of polystyrene and Polyamide 12. The findings show that the proposed DEM model is capable of accurately simulate the neck growth during the laser sintering paving the way for better controlling and optimizing the process.Graphical

The effect of the viscoelastic support and GRPL-reinforced foam material on the thermomechanical vibration response of piezomagnetic sandwich nanosensor plates

This paper investigates the vibration characteristics of a sandwich nanosensor plate composed of piezoelectric materials, specifically barium and cobalt, in the upper and lower layers, and a core material consisting of either ceramic (silicon nitride) or metal (stainless steel) foams reinforced with graphene (GPRL). The study utilized the novel sinosoidal higher-order deformation theory and nonlocal strain gradient elasticity theory. The equations of motion for nanosensor sandwich graphene were derived using Hamilton's principle, considering the thermal, electroelastic, and magnetostrictive characteristics of the piezomagnetic surface plates. These equations were then solved using the Navier method. The core element of the sandwich nanosensor plate can be represented using three distinct foam variants: a uniform foam model, as well as two symmetric foam models. The investigation focused on analyzing the dimensionless fundamental natural frequencies of the sandwich nanosensor plate. This analysis considered the influence of three distinct foam types, the volumetric graphene ratio, temperature variation, nonlocal parameters, porosity ratio, electric and magnetic potential, as well as spring and shear viscoelastic support. Furthermore, an analysis was conducted on the impact of the metal and ceramic composition of the central section of the sandwich nanosensor plate on its dimensionless fundamental natural frequencies. In this context, the use of ceramic as the central material results in a mean enhancement of 33% in the fundamental natural frequencies. In contrast, the incorporation of graphene into the core material results in an average enhancement of 27%. The thermomechanical vibration behavior of the nanosensor plate reveals that the presence of graphene-supported foam and a viscoelastic support structure in the core layer leads to an increase in thermal resistance. This increase is dependent on factors such as the ratio of graphene, porosity ratio of the foam, and parameters of the viscoelastic support. Metal foam or ceramic foam has been found to enhance thermal resistance when compared to solid metal or ceramic core materials. The analysis results showed that it is important to take into account the temperature-dependent thermal properties of barium and cobalt, which are piezo-electromagnetic materials, and the core layer materials ceramics and metal, as well as the graphene used to strengthen the core. The research is anticipated to generate valuable findings regarding the advancement and utilization of nanosensors, transducers, and nano-electromechanical systems engineered for operation in high-temperature environments.

Non-Fourier Bioheat Transfer Analysis in Brain Tissue During Interstitial Laser Ablation: Analysis of Multiple Influential Factors

This work presents the dual-phase lag-based non-Fourier bioheat transfer model of brain tissue subjected to interstitial laser ablation. The finite element method has been utilized to predict the brain tissue's temperature distributions and ablation volumes. A sensitivity analysis has been conducted to quantify the effect of variations in the input laser power, treatment time, laser fiber diameter, laser wavelength, and non-Fourier phase lags. Notably, in this work, the temperature-dependent thermal properties of brain tissue have been considered. The developed model has been validated by comparing the temperature obtained from the numerical and ex vivo brain tissue during interstitial laser ablation. The ex vivo brain model has been further extended to in vivo settings by incorporating the blood perfusion effects. The results of the systematic analysis highlight the importance of considering temperature-dependent thermal properties of the brain tissue, non-Fourier behavior, and microvascular perfusion effects in the computational models for accurate predictions of the treatment outcomes during interstitial laser ablation, thereby minimizing the damage to surrounding healthy tissue. The developed model and parametric analysis reported in this study would assist in a more accurate and precise prediction of the temperature distribution, thus allowing to optimize the thermal dosage during laser therapy in the brain.

Cracking and thermal resistance in concrete: Coupled thermo-mechanics and phase-field modeling

Modeling damage and fracture in concrete accurately is crucial for a comprehensive analysis of structures under concurrent thermal and mechanical actions. This paper presents a novel coupled thermo-mechanical phase field model for concrete at high temperatures. Derived from principles of thermodynamics and unified phase field theory, the model integrates temperature-dependent thermal and mechanical properties, accounting for thermal expansion and transient creep. Mechanical damage, represented by the crack phase field, is augmented by a temperature-dependent thermal damage variable for heat-induced degradation. Addressing the impact of cracks on heat conduction and stress redistributions, the model introduces a novel approach to depict thermal resistance, seamlessly integrating mechanics, heat transfer, and crack propagation. Governing equations for damage evolution are derived, and the numerical implementation is detailed. Numerical illustrations showcase the model's ability to simulate diverse thermo-mechanical cracking patterns without explicit fracture path tracking or assumed criteria. Moreover, the model captures the influence of thermal actions on concrete cracking behavior and mechanical performance. This research is significant for predicting multi-field coupling damage in concrete and structures exposed to elevated temperatures.

An inverse methodology to estimate the thermal properties and heat generation of a Li-ion battery

Accurate estimation of temperature-dependent orthotropic thermal properties and volumetric heat generation of a Li-ion battery is crucial for thermal modeling, thermal safety, and the design of thermal management systems for electric vehicles. Though various studies are available on estimating thermophysical properties and heat generation, simple and easily applicable methods are rare. Moreover, these studies failed to report temperature sensitivity and standard deviation of the estimates. In this study, the temperature-dependent orthotropic thermal conductivities (kr,kθ,kz), specific heat (cp), and volumetric heat generation (qv) of Panasonic NCR18650BD cylindrical battery are estimated using an inverse approach (Metropolis Hastings-Markov Chain Monte Carlo algorithm based Bayesian method) with the help of experimentally obtained surface temperatures measured at convenient locations on the battery. From the estimation, the average values of kr,kθ,kz and cv are observed to be 3.18 ± 0.19, 20.34 ± 1.26, 19.89 ± 1.29 (W/mK), and 3180 ± 202 (J/kgK), respectively. The average heat generation rates from the same battery obtained using the same methodology are 0.1 ± 0.005, 0.34 ± 0.012, and 1.51 ± 0.026 W for 0.5, 1, and 2C discharge rates, respectively. The estimated thermophysical properties and heat generation rates are in good agreement with the results obtained from both in-house experiments and literature. In addition to the estimation of thermophysical properties and heat generation, the proposed methodology opens vistas to predict the strength and location of hotspots in the battery domain, which helps in designing appropriate and effective thermal management systems for battery packs.

Computational modeling of microwave ablation with thermal accelerants

Purpose To develop a computational model of microwave ablation (MWA) with a thermal accelerant gel and apply the model toward interpreting experimental observations in ex vivo bovine and in vivo porcine liver. Methods A 3D coupled electromagnetic-heat transfer model was implemented to characterize thermal profiles within ex vivo bovine and in vivo porcine liver tissue during MWA with the HeatSYNC thermal accelerant. Measured temperature dependent dielectric and thermal properties of the HeatSYNC gel were applied within the model. Simulated extents of MWA zones and transient temperature profiles were compared against experimental measurements in ex vivo bovine liver. Model predictions of thermal profiles under in vivo conditions in porcine liver were used to analyze thermal ablations observed in prior experiments in porcine liver in vivo. Results Measured electrical conductivity of the HeatSYNC gel was ∼83% higher compared to liver at room temperature, with positive linear temperature dependency, indicating increased microwave absorption within HeatSYNC gel compared to tissue. In ex vivo bovine liver, model predicted ablation zone extents of (31.5 × 36) mm with the HeatSYNC, compared to (32.9 ± 2.6 × 40.2 ± 2.3) mm in experiments (volume differences 4 ± 4.1 cm3). Computational models under in vivo conditions in porcine liver suggest approximating the HeatSYNC gel spreading within liver tissue during ablations as a plausible explanation for larger ablation zones observed in prior in vivo studies. Conclusion Computational models of MWA with thermal accelerants provide insight into the impact of accelerant on MWA, and with further development, could predict ablations with a variety of gel injection sites.

Phase and thermodynamics-informed predictive model for laser beam additive manufacturing of a multi-principal element alloy

The complex solidification cycles experienced by multi-principal element alloys (MPEAs) during laser-based additive manufacturing (LBAM) often lead to structural defects that affect the build quality. The underlying thermal processes and phase transformations are a function of the process parameters employed. With a moving Gaussian heat source to mimic LBAM and leveraging material thermodynamics guidelines from CALculation of PHAse Diagrams (CALPHAD), we estimate the temperature-dependent thermal properties, phase fractions, and melt pool geometry using an experimentally validated computational fluid dynamics model. The results substantiate that the peak temperatures are inversely correlated to the scan speeds, and the melt pool dimensions can assist in the predictive selection of process parameters such as hatch distance and layer thickness. A relatively low cooling rate recorded during the process is ascribed to the preheating of the substrate to ensure printability of the alloy.

Progressive collapse resistance of RC beam-column substructures under fire conditions

To better understand the performance of reinforced concrete (RC) structures subjected to fire under column-removal scenarios, 3D numerical models were established to analyze the structural behavior of pre-loaded beam-column substructures under elevated temperatures in this paper. The temperature-dependent thermal and mechanical properties of concrete and steel were adopted to perform the sequentially coupled thermal-mechanical analysis in an ABAQUS/Explicit solver in a quasi-static manner. To capture the damage evolution of concrete and steel rebar, the concrete damaged plasticity (CDP) and ductile damage for metals (DDM) models were calibrated in the numerical model. Existing experimental data under both ambient and high temperatures were used to validate the feasibility of the proposed numerical model. The structural performance of the RC substructure under the loading stage and heating stage was investigated and the contributions of the resisting mechanisms were quantified using the analytical method. The effects of structural design features, such as reinforcement ratios, concrete strengths, span-to-depth ratios, and fire curves, on the collapse-resisting performance were analyzed in the parametric study. The chord rotation limit criteria regulated by the US Department of Defense (DOD) were utilized to identify the failure of substructures under fire and middle column-removal scenarios.

A finite element approach for nonlinear, transient heat conduction problems with convection, radiation or contact boundary conditions

Heat conduction problems with convection and/or radiation boundary conditions arise in nuclear and other engineering fields. This paper presents a finite element approach to solve transient, three-dimensional (3-D), nonlinear heat conduction problems using quadratic tetrahedral elements with area/volume coordinates and quadrature integrations. Boundary conditions modeled include surface convection, to-ambient radiation, and surface-to-surface radiation (using the radiosity matrix method, RMM). Instead of the commonly used hemi-cube method, L′Huilier’s theorem is used here to calculate view factors. Contact constraints are also imposed. Interface condition is set up for the interfaces of different material. The one- and two-step backward differentiation are used for time integration. Nonlinearities introduced by temperature-dependent material thermal properties and the Stefan–Boltzmann law for radiation are handled using the Picard and/or Newton–Raphson methods. The convergence rate of the numerical scheme is verified using an analytical solution obtained using the method of manufactured solutions (MMS). Several practical cases are simulated, including that of two spheres in contact with each other, and results are compared to those obtained using commercial codes.

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.