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Present study aims to extend the lattice Boltzmann method (LBM) to simulate radiation in geometries with curved boundaries, as the first step to simulate radiation in complex porous media. In recent years, researchers have increasingly explored the use of porous media to improve the heat transfer processes. The lattice Boltzmann method (LBM) is one of the most effective techniques for simulating heat transfer in such media. However, the application of the LBM to study radiation in complex geometries that contain curved boundaries, as found in many porous media, has been limited.

The numerical evaluation of the effect of the radiation-conduction parameter and extinction coefficient on temperature and incident radiation distributions demonstrates that the proposed LBM algorithm provides highly accurate results across all cases, compared to those found in the literature or those obtained using the finite volume method (FVM) with the discrete ordinates method (DOM) for radiative information.

For the case with a conduction-radiation parameter equal to 0.01, the maximum relative error is 1.9% in predicting temperature along vertical central line. The accuracy improves with an increase in the conduction-radiation parameter. Furthermore, the comparison between computational performances of two approaches reveals that the LBM-LBM approach performs significantly faster than the FVM-DOM solver.

The difficulty of radiative modeling in combined problems involving irregular boundaries has led to alternative approaches that generally increase the computational expense to obtain necessary radiative details. To address the limitations of existing methods, this study presents a new approach involving a coupled lattice Boltzmann and first-order blocked-off technique to efficiently model conductive-radiative heat transfer in complex geometries with participating media. This algorithm has been developed using the parallel lattice Boltzmann solver.

Electrical characteristics of transformer oil (TO) have been studied during normal and thermal aging conditions. In this paper, breakdown voltage (BDV), partial discharge (PD), heat transfer results and the physical mechanisms considering the impact of varying the diameter of Al₂O₃ nanoparticles (NPs) have been investigated. Different quantities of the two sizes of Al₂O₃ were added to the oil using a two-step method to determine the positive effect of NPs on the electrical and thermal properties of TO. Finally, the physical mechanisms related to the obtained experimental results have been performed.

The implementation of nanoparticles in this paper was provided by US Research Nanomaterials, Inc., USA. The provided Al₂O₃ NPs have an average particle size of 20–80 nm and a specific surface area of 138 and 58 m²/g, respectively, which have a purity of over 99%. Thermal aging has been done. The IEC 60156 standard has been implemented to calculate the BDV, and a 500-mL volume test cell (Apar TO 1020) has been used. PD test is performed according to Standard IEC 60343, and a JDEVS-PDMA 300 device was used for this test.

BDV tests indicate that 20 nm Al₂O₃ is more effective at improving BDV than 80 nm Al₂O₃, with an improvement of 113% compared to 99% for the latter. The analysis of Weibull probability at BDV indicates that 20 nm Al₂O₃ performs better, with improvements of 141%, 125% and 112% at probabilities of 1, 10 and 50%, respectively. The results of the PD tests using the PDPR pattern also show that 20 nm Al₂O₃ is superior. For the heat transfer test, 0.05 g/L of both diameters were used to ensure fair conditions, and again, the advantage was with 20 nm Al₂O₃ (23% vs 18%).

The effect of Al₂O₃ NP diameter (20 and 80 nm) on various properties of virgin and aged TO has been investigated experimentally in this paper to examine the effect of proposed NP on electrical improvement of TO.

Beginners and even experienced ones have difficulties in completing the structural fire analysis due to numerical difficulties such as convergence errors and singularity and have to spend a lot of time making many repetitive changes on the model. The aim of this article is to highlight the advantages of explicit solver which can eliminate the mentioned difficulties in finite element analysis containing highly nonlinear contacts, clearance between modeled parts at the beginning and large deflections because of high temperature. This article provides important information, especially for researchers and engineers who are new to structural fire analysis.

The finite element method is utilized to achieve mentioned purposes. First, a comparative study is conducted between implicit and explicit solvers by using Abaqus. Then, a validation process is carried out to illustrate the explicit process by using sequentially coupled heat transfer and structural analysis.

Explicit analysis offers an easier solution than implicit analysis for modeling multi-bolted connections under high temperatures. An optimum mesh density for bolted connections is presented to reflect the realistic structural behavior. Presented explicit process with the offered mesh density is used in the validation of an experimental study on multi-bolted splice connection under ISO 834 standard fire curve. A good agreement is achieved.

What makes the study valuable is that the points to be considered in the structural fire analysis are examined and it is a guide that future researchers can benefit from. This is especially true for modeling and analysis of multi-bolted connections in finite element software under high temperatures. The article can help to shorten and even eliminate the iterative debugging phases, which is a problematic and very time-consuming process for many researchers.

For a thermal protection system (TPS) of long endurance hypersonic flight vehicle (HFV), its thermal insulation property not only determines by the manufactured morphology but also changes along time. A thermal conductivity prediction model for aerogel considering heat treatment effect is carried out and applied to solve the heat conduction problem of a TPS. The aim of this study is to provide theoretical and numerical references for further development of aerogels applying to TPSs.

A thermal conductivity prediction model for aerogel is established considering treatment effect. The heat conduction problem of a TPS is derived and solved by combining the differential quadrature method and the Runge–Kutta method. The prediction results of aerogel thermal conductivities are verified by comparing with those in literature, while the calculated temperature field of TPS is verified by comparing with that by ABAQUS.

Numerical results show that when applying the current prediction model, the calculated high temperature area in the aerogel layer is narrowed due to the decrease of the thermal conductivity during heat treatment process.

This study will be beneficial to carry out the precise design of TPS for long endurance HFVs.

Natural convection in finite enclosures is a common phenomenon in various thermal applications. To provide the thermal design guidelines, this study aims to numerically explore the potential of using internal baffles and nanofluids to either enhance or suppress heat transport in a vertical annulus. Furthermore, the annular-shaped enclosure is filled with aqueous-silver nanofluid and the effects of five distinct nanoparticle shapes are examined. In addition, the influence of baffle design parameters, including baffle position, thickness and length, is thoroughly analyzed.

The finite difference method is used in conjunction with the alternating direction implicit and successive line over relaxation techniques to solve nonlinear and coupled partial differential equations. The single phase model is used for nanofluid which is considered as a homogeneous fluid with improved thermal properties. The independence tests are carried out for assessing the sufficiency of grid size and time step for obtaining results accurately.

The baffle dimension parameters and nanoparticle shape exhibit significant impact on the convective flow and heat transfer characteristics, leading to the following results: sphere- and blade-shaped nanoparticles demonstrate around 30% enhancement in the heat transport capability compared with platelet-shaped nanoparticles, which exhibit the least. When considering the baffle design parameter, either a decrease in the baffle length and thickness or an increase in baffle height leads to an improvement in heat transport rate. Consequently, a threefold increase in baffle height yields a 40% improvement in thermal performance.

Understanding the impact of nanoparticle shapes and baffle design parameters on flow and thermal behavior will enable engineers to provide valuable insight on thermal management and overall system efficiency. Therefore, the current work focuses on exploring buoyant nanofluid flow and thermal mechanism in a baffled annular-shaped enclosure. Specifically, an internal baffle that exhibits conductive heat transfer through it is considered, and the impact of baffle dimensions (thickness, length and position) on the fluid flow behavior and thermal characteristics is investigated. In addition, the current study also addresses the influence of five distinct nanoparticle shapes (e.g. spherical, cylindrical, platelet, blade and brick) on the flow and thermal behavior in the baffled annular geometry. In addition to deepening the understanding of nanofluid behavior in a baffled vertical annulus, the current study contributes to the ongoing advancements in thermal applications by providing certain guidelines to design application-specific enclosures.

One of the major challenges in the design of thermal equipment is to minimize the entropy production and enhance the thermal dissipation rate for improving energy efficiency of the devices. In several industrial applications, the structure of thermal device is cylindrical shape. In this regard, this paper aims to explore the impact of isothermal cylindrical solid block on nanofluid (Ag – H₂O) convective flow and entropy generation in a cylindrical annular chamber subjected to different thermal conditions. Furthermore, the present study also addresses the structural impact of cylindrical solid block placed at the center of annular domain.

The alternating direction implicit and successive over relaxation techniques are used in the current investigation to solve the coupled partial differential equations. Furthermore, estimation of average Nusselt number and total entropy generation involves integration and is achieved by Simpson and Trapezoidal’s rules, respectively. Mesh independence checks have been carried out to ensure the accuracy of numerical results.

Computations have been performed to analyze the simultaneous multiple influences, such as different thermal conditions, size and aspect ratio of the hot obstacle, Rayleigh number and nanoparticle shape on buoyancy-driven nanoliquid movement, heat dissipation, irreversibility distribution, cup-mixing temperature and performance evaluation criteria in an annular chamber. The computational results reveal that the nanoparticle shape and obstacle size produce conducive situation for increasing system’s thermal efficiency. Furthermore, utilization of nonspherical shaped nanoparticles enhances the heat transfer rate with minimum entropy generation in the enclosure. Also, greater performance evaluation criteria has been noticed for larger obstacle for both uniform and nonuniform heating.

The current numerical investigation can be extended to further explore the thermal performance with different positions of solid obstacle, inclination angles, by applying Lorentz force, internal heat generation and so on numerically or experimentally.

A pioneering numerical investigation on the structural influence of hot solid block on the convective nanofluid flow, energy transport and entropy production in an annular space has been analyzed. The results in the present study are novel, related to various modern industrial applications. These results could be used as a firsthand information for the design engineers to obtain highly efficient thermal systems.

This study aims to examine the impacts of higher memory dependencies on a novel semiconductor material that exhibits generalized photo-piezo-thermo-elastic properties. Specifically, the research focuses on analyzing the behavior of the semiconductor under three distinct temperature models.

The study assumes a homogeneous and orthotropic piezo-semiconductor medium during photo-thermal excitation. The field equations have been devised to encompass higher order parameters, temporal delays and a specifically tailored kernel function to address the problem. The eigenmode technique is used to solve these equations and derive analytical expressions.

The research presents graphical representations of the physical field distribution across different temperatures, higher order plasma heat conduction models and time. The results reveal that the amplitude of the distribution profile is markedly affected by factors such as the memory effect, time, conductive temperature and spatial coordinates. These factors cannot be overlooked in the analysis and design of the semiconductor.

Specific cases are also discussed in detail, offering the potential to advance the creation of precise models and facilitate future simulations.

The research offers valuable information on the physical field distribution across various temperatures, allowing engineers and designers to optimize the design of semiconductor devices. Understanding the impact of memory effect, time, conductive temperature and spatial coordinates enables device performance and efficiency improvement.

This manuscript is the result of the joint efforts of the authors, who independently initiated and contributed equally to this study.

Light emitting diode (LED) has been the best resource for commercial and industrial lighting applications. However, thermal management in high power LEDs is a major challenge in which the thermal resistance (R_th) and rise in junction temperature (T_J) are critical parameters. The purpose of this work is to evaluate the R_th and T_j of the LED attached with the modified heat transfer area of the heatsink to improve thermal management.

This paper deals with the design of metal substrate for heatsink applications where the surface area of the heatsink is modified. Numerical simulation on heat distribution proved the influence of the design aspects and surface area of heatsink.

T_J was low for outward step design when compared to flat heatsink design (ΔT ∼ 38°C) because of increase in surface area from 1,550 mm² (flat) to 3,076 mm² (outward step). On comparison with inward step geometry, the T_J value was low for outward step configuration (ΔT_J ∼ 6.6°C), which is because of efficient heat transfer mechanism with outward step design. The observed results showed that outward step design performs well for LED testing by reducing both R_th and T_J for different driving currents.

This work is authors’ own design and also has the originality for the targeted application. To the best of the authors’ knowledge, the proposed design has not been tried before in the electronic or LED applications.

The purpose of this study is to examine the effects of inclination angle on the thermal energy storage capability of a phase change material (PCM) within a disc-shaped container. Different container materials are also tested such as plexiglass and aluminium. This study aims to assess the energy storage capacity, melting behaviour and temperature distributions of PCM with a specific melting range (22°C–26°C) for various governing parameters such as inclination angles, aspect ratios (AR) and temperature differences (ΔT) and compare the melting behaviour and energy storage performance of PCM in aluminium containers to those in plexiglass containers.

A finite volume approach was adopted to evaluate the thermal energy storage capability of PCMs. Five inclination angles ranging from 0° to 180° were considered and the energy storage capacity. Also, the melting behaviour of the PCM and temperature distributions of the container with different materials were tested. Two different AR and ΔT values were chosen as parameters to analyse for their effects on the melting performance of the PCM. Conjugate heat transfer problem is solved to see the effects of conduction mode of heat transfer.

The results of the study indicate that as AR decreases, the effect of the inclination angles on the energy storage capacity of the PCM decreases. For lower ΔT, the difference between the maximum and minimum stored energies was 20.88% for AR = 0.20, whereas it was 6.85% for AR = 0.15. Furthermore, under the same conditions, the PCM stored 8.02% more energy in plexiglass containers than in aluminium containers.

This study contributes to the understanding of the influence of inclination angle, container material, AR and ΔT on the thermal energy storage capabilities of PCM in a novel designed container. The findings highlight the importance of AR in mitigating the effect of the inclination angle on energy storage capacity. Additionally, comparing aluminium and plexiglass containers provides insights into the effect of container material on the melting behaviour and energy storage properties of PCM.

This study aims to assess the efficacy of thermal analysis of concrete slabs by including different insulation materials using ANSYS. Regression equations were proposed to predict the thermal conductivity using concrete density. As these simulation and regression analyses are essential tools in designing the thermal insulation concretes with various densities, they sequentially reduce the associated time, effort and cost.

Two grades of concretes were taken for thermal analysis. They were designed by replacing the natural fine aggregates with thermal insulation aggregates: expanded polystyrene, exfoliated vermiculite and light expanded clay. Density, temperature difference, specific heat capacity, thermal conductivity and time were measured by conducting experiments. This data was used to simulate concrete slabs in ANSYS. Regression analysis was performed to obtain the relation between density and thermal conductivity. Finally, the quality of the predicted regression equations was assessed using root mean square error (RMSE), mean absolute error (MAE), integral absolute error (IAE) and normal efficiency (NE).

ANSYS analysis on concrete slabs accurately estimates the thermal behavior of concrete, with lesser error value ranges between 0.19 and 7.92%. Further, the developed regression equations proved accurate with lower values of RMSE (0.013 to 0.089), MAE (0.009 to 0.088); IAE (0.216 to 5.828%) and higher values of NE (94.16 to 99.97%).

The thermal analysis accurately simulates the experimental transfer of heat across the concrete slab. Obtained regression equations proved helpful while designing the thermal insulation concrete.