Search Results (60)

This paper presents an integrated computational framework for predicting temperature fields in glulam beam–column connections under fire conditions, combining finite element modeling, automated parametric analysis, and deep learning techniques. A high-fidelity heat transfer finite element model was developed, incorporating the anisotropic thermal properties of wood and temperature-dependent material behavior, validated against experimental data with strong agreement. To enable large-scale parametric studies, an automated Abaqus model modification and data processing system was implemented, improving computational efficiency through the batch processing of geometric and material parameters. The extracted temperature field data was used to train a DeepONet neural network, which achieved accurate temperature predictions (with a L2 relative error of 1.5689% and an R² score of 0.9991) while operating faster than conventional finite element analysis. This research establishes a complete workflow from fundamental heat transfer analysis to efficient data generation and machine learning prediction, providing structural engineers with practical tools for the performance-based fire safety design of timber connections. The framework’s computational efficiency enables comprehensive parametric studies and design optimizations that were previously impractical, offering significant advancements for structural fire engineering applications. Full article

The growing demand for high-power battery output in the ever-evolving electric vehicle and energy storage sectors necessitates the development of efficient thermal management systems. High-power lithium-ion batteries (LIBs), known for their outstanding performance, are widely used across various applications. However, effectively managing the thermal conditions of high-power battery packs remains a critical challenge that limits the operational efficiency and hinders broader market acceptance. The high charge and discharge rates in LIBs generate significant heat, and, as a result, inadequate heat dissipation adversely impacts battery performance, lifespan, and safety. This study utilized theoretical analysis, numerical simulations, and experimental methodologies to address these issues. Considering the anisotropic heat transfer characteristics of laminated pouch cells, this study developed a fluid–solid coupling simulation model tailored to the liquid-cooled structure of pouch battery modules, supported by an experimental test setup. A U-shaped “bathtub-type” cooling structure was designed for a 48 V/8 Ah high-power-density battery pack intended for start–stop power supply applications. This design aimed to resolve heat dissipation challenges, optimize the cooling efficiency, and ensure stable operation under varying conditions. During the performance assessments of the cooling structure conducted through simulations and experiments, extreme discharge conditions (320 A) and pulse charging/discharging cycles (80 A) at ambient temperatures of up to 45 °C were simulated. An analysis of the temperature distribution and its temporal evolution led to critical insights. The results showed that, under these severe conditions, the maximum temperature of the battery module remained below 60 °C, with temperature uniformity maintained within a 5 °C range and cell uniformity within 2 °C. Consequently, the battery pack meets the operational requirements for start–stop power supply applications and provides an effective solution for thermal management in high-power-density environments. Full article

The issue of energy transfer is extremely important. In order to achieve the lowest possible energy consumption and the required thermal efficiency in energy-efficient buildings, it is necessary, among other things, to minimize the heat-transfer coefficient, which depends on the properties of the insulating material. Analyses of the relationship between the structure of a material and its thermal conductivity coefficient have shown that lower values of this coefficient can be achieved with a more complex structure that mimics natural forms. This paper presents a design method based on the Voronoi diagram to obtain a three-dimensional structure of a porous composite material. The method was found to be effective in producing structures with predefined and functionally graded porosity. The porous specimens were fabricated from a biodegradable soybean oil-based resin using mSLA additive technology. Analyses were performed to determine the thermal parameters of the anisotropic composites. Experimental results showed that both porosity and irregularity affect the thermal properties. The lowest thermal conductivity coefficients were obtained for a 100 mm-thick prototype composite with the following parameters: wall thickness D = 0.2 mm, cell size S = 4 mm, number of structural layers n = 2, and degree of irregularity R = 4. The lowest possible thermal conductivity of the insulation was 0.026 W/(m·K), and the highest possible thermal resistance was 3.92 (m²·K)/W. The method presented in this study provides an effective solution for nature-inspired design and topological optimization of porous structures. Full article

This study examines the thermal conduction resistance in anisotropic bodies using linear extended irreversible thermodynamics. The fulfilment of the Onsager Reciprocal Relations in anisotropic bodies, such as crystals, has been demonstrated. This fulfilment is achieved by incorporating Newton’s heat transfer coefficients into the calculation of the entropy production rate. Furthermore, a basic principle for the transport of heat, similar to the Onsager–Fuoss formalism for the multicomponent diffusion at a constant temperature, was established. This work has the potential to be applied not just in the field of material science, but also to enhance our understanding of heat conduction in crystals. A novel formalism for heat transfer analogous to Onsager–Fuoss model for multicomponent diffusion was developed. It is believed that this work could be applied for educational purposes. Full article

Carbon fiber resin matrix composites (CFRP) are widely recognized for their exceptional properties such as high temperature resistance and high strength, making them indispensable in aerospace, automotive, and medical applications. Despite their growing use, precision machining of CFRP remains challenging. Traditional mechanical machining methods often lead to severe tool wear, matrix damage, fiber pullout, delamination, and chipping. In contrast, nanosecond pulsed laser machining has garnered significant attention due to its high precision, minimal heat-affected zone (HAZ), and versatility in processing various materials. In this study, a finite element model was developed to account for the anisotropic heat transfer and non-homogeneous properties of CFRP, enabling accurate simulation of laser machining processes. The study analyzed the influence of laser parameters on machining quality and revealed the ablation mechanism and HAZ evolution under varying laser conditions. Notably, it was observed that the thermal conductivity along the carbon fiber’s axial direction is higher than in the radial direction, resulting in an elliptical ablation pattern after laser irradiation. Additionally, the effects of the laser power, pulse frequency, and scanning speed on the depth and width of grooves were investigated through finite element simulations and validation experiments. A heat accumulation effect between laser pulses was observed, where resin matrix material around the grooves was removed once the accumulated heat exceeded the resin’s pyrolysis temperature. In addition, if there is too much laser power or too small a laser scanning speed, the fiber will undergo severe ablation removal, which will form serious thermal damage and a heat-affected zone. Gradually increasing the laser power or decreasing the scanning speed led to deeper and wider grooves, with an inverted triangular morphology. Moreover, the selection of different parameters had a significant effect on the ablation morphology, heat-affected zone, and the contour parameters of the grooves. This research contributes to understanding the laser–CFRP interaction mechanism and offers insights for optimizing laser processing parameters to improve material processing accuracy and efficiency, further expanding the potential applications of laser technology in composite material machining. Full article

Understanding the influence of heat transfer on the pyrolysis process is crucial for optimizing industrial biofuel production processes. While numerous scientific studies focus on experimental investigations of pyrolysis using laboratory-scale devices, many neglect the essential role of thermal energy in initiating and controlling thermal decomposition processes. This study presents a transient two-dimensional numerical model of biomass single-particle pyrolysis, which includes the energy balance, mass conservation equations and pyrolysis gas pressure and velocity equations. The model employs explicit numerical methods to manage the high computational demands of 2D transient simulations, but is successfully validated with the use of experimental data found in the literature. The model reflects the heterogeneous structure of wood by using different thermal conductivity coefficients depending on the wooden fibers’ orientation. The results demonstrate the impact of fiber orientation on the heat transfer and thermal decomposition processes. The anisotropic properties of wood led to varied temperature fields and pyrolysis decomposition stages, aligning well with experimental data, thus validating the model’s accuracy. The proposed approach can provide a better understanding and lead to improvement in biofuel production processes, enabling more efficient and controlled conversion of biomass into fuel. By optimizing the pyrolysis process, it contributes to the development of sustainable energy preservation and regeneration methods, supporting a shift towards more sustainable fuel production patterns using renewable biomass resources like wood. Full article

The considerable heat generated in electronic devices, resulting from their high-power consumption and dense component integration, underscores the importance of developing effective thermal interface materials. While composite materials are ideal for this application, the random distribution of filling materials leads to numerous interfaces, limiting improvements in thermal transfer capabilities. An effective method to improve the thermal conductivity of composites is the alignment of anisotropic fillers, such as hexagonal boron nitride (BN). In this study, the repeat blade coating method was employed to horizontally align BN within a polydimethylsiloxane (PDMS) matrix, followed by flipping and cutting to prepare BN/PDMS composites with vertically aligned BN (V-BP). The V-BP composite with 30 wt.% BN exhibited an enhanced out-of-plane thermal conductivity of up to 1.24 W/mK. Compared to the PDMS, the V-BP composite exhibited outstanding heat dissipation capacities. In addition, its low density and exceptional electrical insulation properties showcase its potential for being used in electronic devices. The impact of coating velocity on the performance of the composites was further studied through computational fluid dynamics simulation. The results showed that increasing the coating velocity enhanced the out-of-plane thermal conductivity of the V-BP composite by approximately 40% compared to those prepared at slower coating velocities. This study provides a promising approach for producing thermal interface materials on a large scale to effectively dissipate the accumulated heat in densely integrated electronic devices. Full article

One of the technological hurdles in the widespread application of additive manufacturing is the formation of undesired microstructure and defects, e.g., the formation of columnar grains in Ti-6Al-4V—the columnar microstructure results in anisotropic mechanical properties, a reduction in ductility, and a decrease in the endurance limit. Here, we present the potential implementation of a hexagonal array of synchronized lasers to alter the microstructure of Ti–6Al–4V toward the formation of preferable equiaxed grains. An anisotropic heat transfer model is employed to obtain the temporal/spatial temperature distributions and construct the solidification map for various process parameters, i.e., laser power, scanning speed, and the internal distance among lasers in the array. Approximately 55% of the volume fraction of equiaxed grains is obtained using a laser power of P = 500 W and a scanning speed of v = 100 mm/s. The volume fraction of the equiaxed grains decreases with increasing scanning velocity; it drops to 38% for v = 1000 mm/s. This reduction is attributed to the decrease in absorbed heat and thermal crosstalk among lasers, i.e., the absorbed heat is higher at low scanning speeds, promoting thermal crosstalk between melt pools and subsequently forming a large volume fraction of equiaxed grains. Additionally, a degree of overlap between lasers in the array is required for high scanning speeds (v = 1000 mm/s) to form a coherent melt pool, although this is unnecessary for low scanning speeds (v = 100 mm/s). Full article

The heat transfer surfaces of heat exchangers are usually made of metals which may suffer from severe corrosion. When corrosive fluids are present, highly corrosion-resistant metals, graphite or ceramics are used, resulting in high costs. This study presents measured data on the thermophysical and mechanical properties of recently developed corrosion-resistant polymer composite tubes for use in heat exchangers. Extruded polymer composite tubes based on polypropylene or polyphenylene sulfide filled with graphite flakes were investigated. The anisotropic thermal conductivities of the polymer composite tubes were measured at various temperatures. The through-wall thermal conductivity of the tubes made of polypropylene filled with 50 vol.% graphite is increased by a factor of 30 compared to pure polypropylene, resulting in a thermal conductivity of 6.5 W/(m K) at 25 °C. The tubes composed of polyphenylene sulfide filled with 50 vol.% graphite have a through-wall thermal conductivity of 4.5 W/(m K) at 25 °C. The mechanical properties of the polymer composites were measured using tensile and flexural tests at different temperatures. The composite materials are more rigid and keep their mechanical properties up to a higher temperature level compared to the unfilled polymers. Surface roughness measurements show the very smooth and sealed surface of the composite tubes. The results contribute to establishing the viability of using polymer composites for heat exchanger applications with corrosive fluids. Full article

Mathematical models of heat and moisture transfer for anisotropic materials, based on the use of the fractional calculus of integro-differentiation, are considered because such two-factor fractal models have not been proposed in the literature so far. The numerical implementation of mathematical models for determining changes in heat exchange and moisture exchange is based on the adaptation of the fractal neural network method, grounded in the physics of processes. A fractal physics-informed neural network architecture with a decoupled structure is proposed, based on loss functions informed by the physical process under study. Fractional differential formulas are applied to the expressions of non-integer operators, and finite difference schemes are developed for all components of the loss functions. A step-by-step method for network training is proposed. An algorithm for the implementation of the fractal physics-informed neural network is developed. The efficiency of the new method is substantiated by comparing the obtained numerical results with numerical approximation by finite differences and experimental data for particular cases. Full article

Latent Heat Transfer Thermal Energy Storage (LHTES) units are crucial in managing the variability of solar energy in solar thermal storage systems. This study explores the effectiveness of strategically placing layers of anisotropic and uniform metal foam (MF) within an LHTES to optimize the melting times of phase-change materials (PCMs) in three different setups. Using the enthalpy–porosity approach and finite element method simulations for fluid dynamics in MF, this research evaluates the impact of the metal foam’s anisotropy parameter (Kn) and orientation angle (ω) on thermal performance. The results indicate that the configuration placing the anisotropic MF layer to channel heat towards the lower right corner shortens the phase transition time by 2.72% compared to other setups. Conversely, the middle setup experiences extended melting periods, particularly when ω is at 90°—an increase in Kn from 0.1 to 0.2 cuts the melting time by 4.14%, although it remains the least efficient option. The findings highlight the critical influence of MF anisotropy and the pivotal role of ω = 45°. Angles greater than this significantly increase the liquefaction time, especially at higher Kn values, due to altered thermal conductivity directions. Furthermore, the tactical placement of the anisotropic MF layer significantly boosts thermal efficiency, as evidenced by a 13.12% reduction in the PCM liquefaction time, most notably in configurations with a lower angle orientation. Full article

In order to improve the accuracy of internal temperature estimation in batteries, a 10-parameter time-varying multi-surface heat transfer model including internal heat production, heat transfer and external heat transfer is established based on the structure of a lithium iron phosphate pouch battery and its three directional anisotropic heat conduction characteristics. The entropy heat coefficient, internal equivalent heat capacity and internal equivalent thermal resistance related to the SOC and temperature state of the battery were identified using experimental tests and the least square fitting method, and were then used for online calculation of internal heat production and heat transfer in the battery. According to the time-varying and nonlinear characteristics of the heat transfer between the surface and the environment of the battery, an internal temperature estimation algorithm based on the square root cubature Kalman filter was designed and developed. By iteratively calculating the estimated surface temperature and the measured value, dynamic tracking and online correction of the internal temperature of the battery can be achieved. The verification results using FUDS and US06 dynamic working condition data show that the proposed method can quickly eliminate the influence of initial temperature deviations and accumulated process errors and has the characteristics of a high estimation accuracy and good robustness. Compared with the estimation results of the adaptive Kalman filter, the proposed method improves the estimation accuracy of FUDS and US06 working conditions by 67% and 54%, respectively, with a similar computational efficiency. Full article

This study proposes a new computational framework for the multi-objective topology optimization of conjugate heat transfer systems using a continuous adjoint approach. It relies on a monolithic solver for the coupled steady-state Navier–Stokes and heat equations, which combines finite elements stabilized by the variational multi-scale method, level set representations of the fluid–solid interfaces and immersed modeling of heterogeneous materials (fluid–solid) to ensure that the proper amount of heat is exchanged to the ambient fluid by solid objects in arbitrary geometry. At each optimization iteration, anisotropic mesh adaptation is applied in near-wall regions automatically captured by the level set. This considerably cuts the computational effort associated with calling the finite element solver, in comparison to traditional topology optimization algorithms operating on isotropic grids with a comparable refinement level. Given that we operate within the constraint of a specified number of nodes in the mesh, this allows not only to improve the accuracy of interface representation and motion but also to retain the high fidelity of the numerical solutions at the grid points just adjacent to the interface. Finally, the remeshing and resolution steps both run within a highly parallel environment, which makes it possible for the proposed algorithm to tackle large-scale problems in three dimensions with several tens of millions of state degrees of freedom. The developed solver is validated first by minimizing dissipation in a flow splitter device, for which the method delivers relevant optimal designs over a wide range of volume constraints and flow rate distributions over the multiple outlet orifices but yields better accuracy compared to reference data from literature obtained using uniform meshes (in the sense that the layouts are more smooth, and the solutions are better resolved). The scheme is then applied to a two-dimensional heat transfer problem, using bi-objective cost functionals combining flow resistance and thermal recoverable power. A comprehensive parametric study reveals a complex arrangement of optimal solutions on the Pareto front, with multiple branches of symmetric and asymmetric designs, some of them previously unreported. Finally, the algorithmic developments are substantiated with several three-dimensional numerical examples tackled under fixed weights for heat transfer and flow resistance, for which we show that the optimal layouts computed at low Reynolds number, that are intrinsically relevant to a broad range of microfluidic application, can also serve as smooth solutions to high-Reynolds-number engineering problems of practical interest. Full article

This study presents a comprehensive approach for simulating the additive manufacturing process of semi-crystalline composite polymers using Fused Deposition Modeling (FDM). By combining thermomechanical Finite Element Analysis (FEA) with experimental validation, our main objective is to comprehend and model the complex behaviors of 50 wt.% carbon fiber-reinforced Polyphenylene Sulfide (CF PPS) during FDM printing. The simulations of the FDM process encompass various theoretical aspects, including heat transfer, orthotropic thermal properties, thermal dissipation mechanisms, polymer crystallization, anisotropic viscoelasticity, and material shrinkage. We utilize Abaqus user subroutines such as UMATHT for thermal orthotropic constitutive behavior, UEPACTIVATIONVOL for progressive activation of elements, and ORIENT for material orientation. Mechanical behavior is characterized using a Maxwell model for viscoelastic materials, incorporating a dual non-isothermal crystallization kinetics model within the UMAT subroutine. Our approach is validated by comparing nodal temperature distributions obtained from both the Abaqus built-in AM Modeler and our user subroutines, showing close agreement and demonstrating the effectiveness of our simulation methods. Experimental verification further confirms the accuracy of our simulation techniques. The mechanical analysis investigates residual stresses and distortions, with particular emphasis on the critical transverse in-plane stress component. This study offers valuable insights into accurately simulating thermomechanical behaviors in additive manufacturing of composite polymers. Full article

This research proposes a numerical approach to improve the thermal performance of shape memory polymers (SMPs) while their mechanical properties remain intact. Sixteen different 3D minichannel structures were numerically designed to investigate the impact of embedded water flow in microchannel networks on the thermal response and shape recovery of SMPs. This work employs two approaches, each with different physics: approach A focuses on solid mechanics analysis and, accordingly, thermal analysis in solids without considering the fluid. approach B tackles solid and fluid mechanics analysis and thermal analysis in both solid and fluid subdomains, which inherently calls for fluid–structure coupling in a uniform procedure. Finally, the results of these two approaches are compared to predict the SMP’s thermal and mechanical behavior. The structural designs are then analyzed in terms of their shape recovery speed, recovery ratio, and recovery parameters. The results indicate that isotropic structures thermally outperform their anisotropic counterparts, exhibiting improved thermal characteristics and faster shape recovery. Additionally, it was observed that polymeric structures with a low volume fraction of embedded branches thermally perform efficiently. The findings of this study predict that the geometrical angle between the main branch and sub-branches of SMP favorably impacts the enhancement of thermal characteristics of the structure, accelerating its shape recovery. Approach B accelerates the shape recovery rate in SMPs due to fluid flow and uniform heat transfer within the structures. Full article