Thermophysical Properties Of Materials Research Articles

Thermal modeling of porous medium integrated in PCM and its application in passive thermal management of electric vehicle battery pack

The integration of a composite of porous medium with phase change material (PCM) offers significant advantages in thermal management systems, enhancing heat transfer efficiency and addressing various thermal regulation challenges. This approach utilizes the PCM's latent heat absorption and the enhanced thermal conductivity provided by the porous medium, resulting in optimized system performance. Its applicability spans across electronics cooling and building insulation systems. However, predicting the thermal behavior of this composite material is challenging, necessitating computational tools to anticipate its response under different conditions and evaluate its influence on cooling strategies. The objective of this study is to create a computational tool specifically tailored to evaluate constitutive parameters of this composite material, thereby providing a comprehensive description of its thermal behavior. To achieve this goal, the multiscale homogenization principle is employed to assess the composite's effective thermophysical material properties using the representative volume element approach. The repeating unit cell of the aluminum lattice is incorporated into the PCM to define a representative volume element. The finite element method (FEM) is utilized to solve the three-dimensional homogenization problem, yielding an orthotropic effective thermal conductivity due to the inherent symmetry of the repeating material cell. Moreover, the study leverages the apparent heat capacity method to effectively manage the phase transitions within the PCM domain, utilizing smooth and temperature-dependent functions to accurately describe the thermophysical properties of the PCM. Integrating the composite into battery pack thermal management, this study thoroughly examines thermal dynamics by comparing outcomes with and without PCM integration. The transient thermal problem is accurately tackled using the FEM, employing the evaluated effective constitutive parameters of the homogenized composite to minimize computational effort. The results indicate a notable decline in the highest temperatures of the battery pack, leading to a reduction of about 14 °C at the specific moment when the phase change material fully transitions into its liquid form. The obtained results emphasize the effectiveness and practical feasibility of the proposed thermal management strategy. The modeling approach presented provides a robust tool with significant efficiency in reducing computational time for analyzing the thermal behavior of large models, as the utilization of the homogenization technique notably decreases the computational time.

Advancements in Nanomaterial Dispersion and Stability and Thermophysical Properties of Nano-Enhanced Phase Change Materials for Biomedical Applications.

Phase change materials (PCMs) are materials that exhibit thermal response characteristics, allowing them to be utilized in the biological field for precise and controllable temperature regulation. Due to considerations of biosafety and the spatial limitations within human tissue, the amount of PCMs used in medical applications is relatively small. Therefore, researchers often augment PCMs with various materials to enhance their performance and increase their practical value. The dispersion of nanoparticles to modify the thermophysical properties of PCMs has emerged as a mature concept. This paper aims to elucidate the role of nanomaterials in addressing deficiencies and enhancing the performance of PCMs. Specifically, it discusses the dispersion methods and stabilization mechanisms of nanoparticles within PCMs, as well as their effects on thermophysical properties such as thermal conductivity, latent heat, and specific heat capacity. Furthermore, it explores how various nano-additives contribute to improved thermal conductivity and the mechanisms underlying enhanced latent heat and specific heat. Additionally, the potential applications of PCMs in biomedical fields are proposed. Finally, this paper provides a comprehensive analysis and offers suggestions for future research to maximize the utilization of nanomaterials in enhancing the thermophysical properties of PCMs for biomedical applications.

Energy Absorption and Beam Damage during Microfocus Synchrotron X-ray Diffraction.

In this study, we combine in situ fast differential scanning calorimetry (FDSC) with synchrotron X-ray measurements to study simultaneously the structure and thermophysical properties of materials. Using the example of the organic compound BCH-52, we show that the X-ray beam can heat the sample and induce a shift of the heat-flow signal. The aim of this paper is to investigate the influence of radiation on sample behavior. The calorimetric data is used to quantify the absorbed beam energy and, together with the diffraction data, reveal an irreversible damage of the sample. The results are especially important for materials with high absorption coefficients and for high-energy X-ray and electron beams. Our findings illustrate that FDSC combined with X-ray diffraction is a suitable characterization method when beam damage must be minimized.

Study of the dielectric properties of decomposing materials during heating

The dielectric properties of materials when heated at ultrahigh frequencies are determined by methods based on the use of waveguide cavity resonators. However, as the sample is in the closed volume during measurements, the dielectric properties of destructive material thus determined can contain errors attributed filling of the resonator volume and depositing products of the sample decomposition on the internal conducting surfaces of the resonator. We present the results of studying the dielectric properties of destructive materials under heating in waveguide resonator cavity using methods that exclude the impact of destruction products on the accuracy of measurement. To reduce the influence of destructive vapors rising from the surface of the sample during the destruction process, additional thin quartz plates, placed on the sample surface were used. In addition, cuvettes with a lid were also used to prevent destruction products from entering the resonator volume. A method for taking into account the effect of plates and cuvettes in calculating the dielectric constant and dielectric loss tangent of a material sample when heated in a cavity resonator is presented. Changes in the dielectric properties of a composite material consisting of quartz fabric impregnated with an aluminochromophosphate binder and fiberglass laminate made of quartz fabric impregnated with a phenol-formaldehyde binder were studied in a temperature range above the onset of the destruction (up to temperatures at which loss of the structural strength of the material is observed). The developed method can be used in studying the thermophysical properties of destructive materials to assess changes in their dielectric characteristics under operation conditions of high-temperature heating.

Oil and Gas Structures: Forecasting the Fire Resistance of Steel Structures with Fire Protection under Hydrocarbon Fire Conditions

The hydrocarbon temperature–time curve is widely used instead of the standard curve to describe the temperature in the environment of structural surfaces exposed to fire in oil and gas chemical facilities and tunnels. This paper presents calculations of the ratio of time to reach critical temperatures at different nominal fire curves for steel structures such as bulkheads and columns with different types of fireproofing. The thermophysical properties of the fireproofing materials were obtained by solving the inverse heat conduction problem using computer simulation. It was found that the time interval for reaching critical temperatures in structures with different types of fireproofing in a hydrocarbon fire decreased, on average, by a factor of 1.2–1.7 compared to the results of standard fire tests. For example, for decks and bulkheads with mineral wool fireproofing, the K-factor of the ratio of the time for reaching the critical temperature of steel under the standard curve to the hydrocarbon curve was 1.30–1.62; for plaster, it was 1.56; for cement boards, it was 1.34; for non-combustible coatings, it was 1.38–2.0; and, for epoxy paints, it was 1.71. The recommended values of the K-factor for fire resistance up to 180 min (incl.) were 1.7 and, after 180 min, 1.2. The obtained dependencies would allow fireproofing manufacturers to predict the insulation thickness for expensive hydrocarbon fire experiments if the results of fire tests under standard (cellulosic) conditions are known.

High throughput screening of thermal interface materials by machine learning

Till now, it remains a challenge for effective prediction and screening of novel materials with high thermal conductivity, as well as further optimization of the interface thermal resistance. Normally, people have to spend long time on tedious calculations when predicting and screening these materials. In this paper, I combined machine learning with molecular dynamics simulations to investigate the thermal conductive properties of materials with the aim of significantly reducing computational consumption. I first applied molecular dynamics simulations to obtain the relevant properties of materials, then generated models for predicting physical properties by machine learning, and finally made predictions of thermophysical properties of materials. The use of machine learning significantly reduces the prediction time compared to direct molecular dynamics simulations. Especially when the XGBoost and the neural network models are employed, the prediction efficiency is significantly improved. This work guides a new way for the future screening of high-performance thermal interface materials.

Estimation of thermophysical properties of a pouch-type Li-ion battery using an inverse methodology

The growing popularity of electric vehicles highlights the crucial role of batteries. Effective battery thermal management is crucial for improving performance, reliability, and safety, especially in tropical areas where overheating is a key challenge. This necessitates a comprehensive understanding of the thermophysical properties of batteries. The present study concerns the estimation of the temperature-dependent orthotropic thermophysical properties (kx , ky , kz , cp ) of the active material in a pouch-type Li-ion battery using an inverse methodology. An experimental study is conducted on a commercial AMP20M1HD-A Li-ion battery to measure the surface temperature at various locations using thermocouples. The forward model consists of the three-dimensional unsteady conduction problem and is solved in COMSOL using experimental boundary conditions. The data generated is used to train an Artificial Neural Network, which acts as a replacement for the forward model. The Metropolis Hasting-Markov Chain Monte Carlo algorithm along with the Bayesian inference inverse model is used for analyzing the posterior distribution and the average estimates for thermophysical properties are obtained. The temperature dependence study shows a significant correlation between temperature and battery thermophysical properties. The accuracy of the employed inverse model is validated by obtaining the surface temperature using the estimated thermophysical properties and comparing it with the measured surface temperature.

Enhancement effects of hydrolysable/soluble Al-type dopants on the efficiency of CaO/CaCO3 thermochemical energy storage

Modification of CaO-based materials using Al-type dopants has been considered a promising method to enhance energy storage performance. The synergistic multi-doping effects of different Al-type dopants (soluble, hydrolysable and insoluble) on the energy storage performances, thermophysical and mechanical properties of CaO-based materials have never been reported. The hydrolysable/soluble Al-type supports co-doped CaO-based pellets were prepared, which exhibited superior energy storage density, multi-cycle stability, reaction rate, thermal conductivity and crushing strength compared to undoped CaO pellets. The regulation mechanisms of hydrolysable/soluble Al-type dopants (AlN/Al(NO3)3) on the reaction kinetics, multi-cycle stability, thermophysical properties and mechanical properties of CaO-based pellets were revealed. The addition of different Al-type dopants results in different dispersions of the formed Ca12Al14O33, which leads to different micro-morphologies and pore structures of CaO-based pellets. Hydrolysable Al-type dopants exhibit a more concentrated distribution in CaO-based pellets and the pellets have smaller crystallite sizes of CaO and predominantly microporous pores, which results in the high CO2 reactivity. Soluble Al-type dopants exhibit a more uniform dispersion in CaO-based pellets and the pellets have larger crystallite sizes of CaO and obvious pore channels, which results in the improved cyclic stability and decomposition kinetics. The optimized CaO-based pellets combine the advantages of the two Al-type dopants and present an increasing trend of energy storage density during the cyclic process. Its energy storage density remains 1571 kJ/kg after 50 cycles, and the value for CaO is only 569 kJ/kg. In addition, the optimal synthesized material has excellent thermal conductivity and crushing strength, which are 1.36 and 9.75 times those of CaO, respectively.

Thermophysical and adhesive properties of functional polymer materials based on epoxy resin and silicon-containing component

The work was aimed at developing an adhesive formulation with increased adhesive strength for metals. It contains an epoxy resin of the bisphenol type СHS-TROXY 520 (an analogue of ED-20), an amine hardener triethanolamine (TEA) and a silicon-containing component (3-isocyanatopropyl)triethoxysilane, designated as NCO-Si, with an optimal ratio of components. The content of NCO-Si in the formulations was 0.5, 1.0, 3.0 and 5.0 wt. %, respectively. The gradual transformation of the epoxy system into a three-dimensional network with the formation of ester and urethane groups was shown by IR spectroscopy method. Tensile and shear strength were determined using the tearing machine R-50 in accordance with current standards. It was found that the maximum values of physical and mechanical parameters were obtained when the amount of NCO-Si was 3 wt. %. The maximum values of adhesion strength to steel substrates δst. = 58.5 MPa significantly exceed those for neat epoxy formulations. The shear strength values for steel plates τst. = 21 MPa increase by 60 %, for aluminium plates they are δAl =14.5 MPa and increase by 48 %. The morphology of the samples has been studied by means of optical microscopy. It is shown that the modified NCO-Si samples are characterised by a phase-separated structure. At a minimum amount of NCO-Si (0.5 wt. %), structurally disordered spherical domains with a size of ~1÷3 μm are observed, an increase in the content of the organosilicon component leads to the formation of interconnected regular structures, which are less pronounced at 1.0 wt. % of NCO-Si and clear at 3.0 and 5.0 wt. % of NCO-Si. Thermogravimetric analysis (TGA) was performed as well. It is shown that the modification of epoxy resin by a silicon-containing component with NCO-Si groups leads to an improvement in thermophysical parameters, a decrease in internal stresses and the formation of a material with a structure close to equilibrium.

MULTIFACTOR ANALYSIS OF THE EFFICIENCY OF THE FERROALLOY PROCESS

Ore-reducing ferroalloy processes must be considered as a relationship of parameters and characteristics of subsystems and elements. The maximum energy capacity of the furnace and its productivity is achieved both due to the design parameters of the bath, the short network, the power of the furnace transformer, the diameter of the self-ignition electrodes, as well as the electrotechnological and thermophysical properties of the initial charge materials, ore-slag melt and final ferroalloy. The amount of carbon is one of the most significant technological parameters of the carbon reduction process for the production of manganese ferroalloys. In the work, the most significant final indicators are adopted and their correlation with electrical characteristics and technological parameters is determined.

Predictive process diagram for parameters selection in laser powder bed fusion to achieve high-density and low-cracking built parts

The laser powder bed fusion process (LPBF) has been widely used in many industrial sectors, including automotive, aerospace, and biomedical devices. With the fast development of new materials designed for critical applications, the conventional design of experiments for determining an optimal LPBF process window is a time and material-consuming activity. This can impose difficulties on small-to-medium industrial businesses where investing resources are limited. To address these challenges, this study draws inspiration from a reliable diagram used in laser welding to construct a similar diagram for the LPBF process. The objective is to enable the "right-first-time" selection of parameters that achieve a minimum of 99% density, regardless of the metallic materials and machine platforms. The diagram is established based on dimensionless beam power and velocity, derived from multiple LPBF process parameters (e.g., laser power, scan speed, hatch spacing) and the thermophysical properties of materials (e.g., melting point, density, thermal diffusivity). Furthermore, hot cracking susceptibility is considered by a strain-rate approach incorporated with the dimensionless thermal strain factor, which benefits when processing hard-to-weld alloys. The diagram shows high reliability in determining parameters corresponding to lack of fusion, keyhole porosity and 99% dense parts when plotting against literature data of LPBF for several metallic materials. Similar results were observed when applying to a novel material ABD-900AM Ni-based alloy, for which no previously published data were available. Moreover, the diagram proved effective in selecting parameters to process the high-cracking susceptible CM247LC Ni-based alloy, resulting in significant mitigation of hot cracking in the as-fabricated parts.

Effect of varying the thermophysical properties of phase change material on the performance of photovoltaic/thermal-PCM hybrid module numerically

The present investigation uses ANSYS-Fluent to establish a three-dimensional computational model to examine the impact of varying thermophysical properties of phase change material on photovoltaic/thermal system performance. A merit function is employed to determine the impact of varying the PCM thermophysical properties on the system to assess the economic feasibility of a proposed PV/T-PCM setup. The findings indicate that, despite the coolant discharge temperature appearing to be somewhat greater for the PV/T-PCM layout than for the PV/T design, the average PV surface temperature seems to be lower for the PV/T-PCM module. Additionally, the coolant outlet temperature dramatically improves with elevating the PCM melting temperature and thermal conductivity. When the latent heat of PCM elevates from 80 to 240 kJ/kg, the thermal and total energy efficiencies for the PV/T-PCM structure decline from 60.8 to 49.2 % and 72.6 to 61 %, respectively. Moreover, boosting the PCM melting temperature and thermal conductivity, respectively, from 305 to 323 K and 0.1 to 0.5 W/m.K dramatically enhances the total energy efficiency by about 13 and 10 %. It is found that varying the PCM melting temperature has a significantly greater impact on the total energy efficiency of PV/T-PCM module than that for the latent heat of fusion and thermal conductivity, where the total energy efficiency marginally increases from about 47.5 to 77.75 %, when boosting the PCM melting temperature from 305 to 323 K. With increasing the melting temperature and the thermal conductivity of the PCM, the heat to electricity ratio and the merit function value are significantly enhanced for the PV/T-PCM layout.

Оптимизация параметров импульсной лазерной наплавки стали 30ХГСН2А с использованием генетического алгоритма

The paperpresents the optimization of pulsed laser cladding of structural steel using a genetic algo-rithm. Using the ANSYS Workbench software, finite element modelling of laser cladding on a 30ХГСН2А steel substrate with an additive in the form of wire was conducted, considering the temperature dependence of the material's thermophysical properties. A surrogate model for pulsed laser cladding of 30ХГСН2Аsteel was developed employing a face-centered version of the central composite design experiment. The time inter-vals corresponding to the end time of the three fronts of the laser pulse and the diameter of the filler wire were considered as variable factors. The maximum temperatures in the treatment zone were used as re-sponses. In order to optimize pulsed laser cladding of 30ХГСН2А steel, the maximum temperature limit val-ues in the treatment zone were established for three moments of time that corresponded to the laser pulse fronts at the three points in the finite element model. A comparison was made between the parameters ob-tained from optimization and those derived from finite element modelling. When determining temperatures, the maximum percentage error of the results obtained via the genetic algorithm did not exceed 3.5 %

Influence of Plastic Strain on Heat Capacity of L485ME Pipe Steel Grade

The aim of this work is an experimental evaluation of a specific heat capacity as a function of plastic strain for thermo-mechanically rolled pipe material, with application of an infrared thermographic camera. The tensile load tests of samples prepared of L485ME (X70M) steel grade were performed with the use of a strength machine. Based on other known material thermophysical properties, the determination of heat source parameters was conducted with the use of an infrared thermography and with an optimization task solution. A linear regression equation describing the specific heat capacity as a function of plastic percentage elongation for L485ME steel grade was determined. The experimental results of the present study showed a linear increase in the specific heat capacity in the range of the analyzed tensile deformation up to 16%. The presented methodology is suitable for assessment of the material specific heat capacity as a function of strain up to the occurrence of the sample narrowing in a direction perpendicular to the tensile force.

Surface Treatment Effect on the Mechanical and Thermal Behavior of the Glass Fabric Reinforced Polysulfone.

The chemical structure of the surface of glass fibers, including silanized fibers, was studied. Highly efficient heat-resistant composites were obtained by impregnating silanized glass fiber with a polysulfone solution, and the effect of modification of the surface of glass fibers on the physical, mechanical and thermophysical properties of the composite materials was studied. As a result of the study, it was found that the fiber-to-polymer ratio of 70/30 wt.% showed the best mechanical properties for composites reinforced with pre-heat-treated and silanized glass fibers. It has been established that the chemical treatment of the glass fibers with silanes makes it possible to increase the mechanical properties by 1.5 times compared to composites reinforced with initial fibers. It was found that the use of silane coupling agents made it possible to increase the thermal stability of the composites. Mechanisms that improve the interfacial interaction between the glass fibers and the polymer matrix have been identified. It has been shown that an increase in adhesion occurs both due to the uniform distribution of the polymer on the surface of the glass fibers and due to the improved wettability of the fibers by the polymer. An interpenetrating network was formed in the interfacial region, providing a chemical bond between the functional groups on the surface of the glass fiber and the polymer matrix, which was formed as a result of treating the glass fiber surface with silanes, It has been shown that when treated with aminopropyltriethoxysilane, significant functional unprotonated amino groups NH+/NH2+ are formed on the surface of the fibers; such free amino groups, oriented in the direction from the fiber surface, form strong bonds with the matrix polymer. Based on experimental data, the chemical structure of the polymer/glass fiber interface was identified.

Analysis of heat flow in modified transient plane source (MTPS) measurements of the thermal effusivity and thermal conductivity of materials.

An iterative algorithm for the diffusion of heat in layered structures is solved in cylindrical coordinates for the geometry used in measurements of thermophysical properties of materials by the modified transient plane source (MTPS) method. This solution for the frequency-domain temperature response is then used to model the transient temperature excursion and evaluate the accuracy of the measurements. We evaluate when the MTPS method is capable of separately determining the thermal conductivity and heat capacity per unit volume of a material. For a typical sensor design, data acquisition, and data analysis, the MTPS measurement has a small sensitivity to the thermal diffusivity of the sample when the thermal diffusivity is <5 mm2 s-1. We analyze the propagation of errors from uncertainties in the thermal contact between the sensor and the sample and evaluate the limitations of the MTPS method in accurately measuring samples with extremely low thermal effusivity, e.g., low density foam insulation. We find that uncertainties in the thickness of the contact region limit the accuracy of MTPS measurements when the data are analyzed in a conventional manner based on a single parameter, m-1, the inverse of the slope of the temperature excursion as a function of the square root of time.

Theoretical study of the synergic relationships between the design parameters in energy-saving building design

With the rapid development of the economy, people have increasingly higher requirements for the comfort of living spaces, and the result is the sharp increase in building energy consumption. Several design parameters influence living space comfort and building energy efficiency. Since the same design standard can include different design parameter combinations, synergic relationships may exist between these criteria for one case. Identifying these synergic relationships requires an inverse problem approach. This paper established a model by combining an improved genetic algorithm (IGA) and numerical calculation to determine the synergic design parameter relationships (e.g. the thermophysical building material properties and energy-saving factors). For Isum=0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\ ext{I}}}_{{\ ext{sum}}}= {0} $$\\end{document}, the shading coefficient significantly influenced the linear function between the thermal conductivity and insulation thickness. In this case, the insulation thickness was exponentially related to the shading coefficient, while the thermal conductivity of the insulation material significantly impacted the synergic relationship. For ESR=65%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{ESR}}{=65}\\%$$\\end{document}, the insulation thickness was a segmented function of the shading coefficient. The results verified that the proposed model was efficient and reliable for identifying the synergic relationships between energy-saving parameters. In engineering applications, designers can select the optimal design parameter combination based on the relationship curve between the parameters in this paper according to the local market conditions and specific design requirements.

Decomposition mechanism of lumpy dolomite particles

Cylindrical cm-sized dolomite particles were decomposed using the two steps decomposition scheme. Several studies on dolomite decomposition have been done using µm- to mm-sized samples over the years. However, these sizes are too small for industrial kiln application and ignore the influence of important parameters, e.g. thermal conductivity, on the decomposition process. In this work, the decomposition behavior of lumpy dolomite particles in each step was investigated. Experimentally measured sample temperature and conversion profiles in steps 1 and 2 are respectively similar to those obtained for the decomposition of pure magnesite and limestone. To measure the core temperature and conversion is to essentially analyze the decomposition behavior. The thermophysical material properties of the decomposition product in each step as a function of temperature was estimated using the shrinking core model. Finite difference method was employed in solving the 1D heat equation describing the process. The reaction rate coefficient in step 1 is shown to have a weak temperature dependence, the thermal conductivity of the product, MgO∙CaCO3, slightly increases with temperature but the permeability is not dependent. In step 2, the reaction coefficient and MgO∙CaO thermal conductivity and pore diffusivity do not show a clear temperature dependence. Finally, the sensitivity of the material and transport properties on the decomposition process was studied under shaft kiln condition. Thermal conductivity is observed to have the highest influence on decomposition with a value of up to 60 % at 1400 °C and for 120 mm particles.

Dealkylation of Poly(methyl methacrylate) by TiCl4 Vapor Phase Infiltration (VPI) and the Resulting Chemical and Thermophysical Properties of the Hybrid Material.

This study examines the chemical reaction pathways for vapor phase infiltration (VPI) of TiCl4 into poly(methyl methacrylate) (PMMA). VPI is a processing method that transforms organic polymers into organic-inorganic hybrid materials with new properties of interest for microelectronic patterning, technical textiles, and chemical separations. Understanding the fundamental chemical mechanisms of the VPI process is essential for establishing approaches to design the chemical structure and properties of these hybrid materials. While prior work has suggested that TiCl4 infiltration into PMMA does not disrupt the polymer's carbonyl bond, a clear reaction mechanism has yet to be proposed. Here, we present a detailed X-ray photoelectron spectroscopy study that presents evidence for a concerted reaction mechanism that involves TiCl4 coordinating with the PMMA's ester group to dealkylate the methyl side group, creating a chloromethane byproduct and primary chemical bonds between the organic and inorganic components of the hybrid material. Additional spectroscopy, quartz crystal microbalance gravimetry, and thermophysical and chemical property measurements of this material, including solubility studies and thermal expansion measurements, provide further evidence for this chemical reaction pathway and the subsequent creation of inorganic cross-links that network these TiOx-PMMA hybrid materials.

Monte Carlo functional estimation of the radiative source term in a semi-transparent medium: A faster coupled conductive–radiative model resolution

The estimation of thermo-physical properties of materials at high temperatures requires the development of robust and fast-enough direct models that takes into account the strong coupling between conduction and radiation. The interest in using the Monte Carlo method to obtain a conduction–radiation model in a semi-transparent material solved in a reduced computational time is addressed in this study. An academic configuration that consists of an absorbing/emitting and non-scattering gray medium with steady-state conduction is investigated since this study is meant to be a proof of concept. It is demonstrated that the radiative source term of the heat equation may be estimated as a function of the temperature field to the fourth power, using a Finite Differences algorithm and a single Monte Carlo simulation of radiation. The results of the numerical study show that, on the one hand, they are in good agreement with those found in the literature and, on the other, that the coupled model can be resolved in a significantly shorter amount of computational time than with traditional methods thanks to the functional estimation of the radiative source term. In fact, in each of the fifteen analyzed cases, the coefficients of the function were determined in approximately 6 s using the Monte Carlo method using a laptop with standard computational resources. The computation of the function and its application revealed that, depending on the studied configuration, a resolution with the finite differences–functional Monte Carlo algorithm can be around twenty to one thousand times faster than a classic Finite Differences–Monte Carlo algorithm. Due to these characteristics, as well as the fact that the functional estimation is insensitive to geometry complexity and can be extended to configurations with heterogeneous radiative properties, it becomes possible to utilize this method in inversion procedures, since the direct model must be evaluated numerous times.