Search Results (143)

Internal fins are commonly utilized as a passive technique to enhance natural convection, but their efficiency depends on complex interplay between fin design, material properties, and convective strength. This study presents an extensive numerical analysis of buoyancy-driven flow in square cavities containing a single horizontal fin on the hot wall. Over 9000 simulations were conducted, methodically varying the Rayleigh number (Ra = 10 to 10⁵), Prandtl number (Pr = 0.1 to 10), and fin characteristics, such as length, vertical position, thickness, and the thermal conductivity ratio (up to 1000), to assess their overall impact on thermal efficiency. Thermal enhancements compared to scenarios without fins are quantified using local and average Nusselt numbers, as well as a Nusselt number ratio (NNR). The results reveal that, contrary to conventional beliefs, long fins positioned centrally can actually decrease heat transfer by up to 11.8% at high Ra and Pr due to the disruption of thermal plumes and diminished circulation. Conversely, shorter fins located near the cavity’s top and bottom wall edges can enhance the Nusselt numbers for the hot wall by up to 8.4%, thereby positively affecting the development of thermal boundary layers. A U-shaped Nusselt number distribution related to fin placement appears at Ra ≥ 10³, where edge-aligned fins consistently outperform those positioned mid-height. The benefits of high-conductivity fins become increasingly nonlinear at larger Ra, with advantages limited to designs that minimally disrupt core convective patterns. These findings challenge established notions regarding passive thermal enhancement and provide a predictive thermogeometric framework for designing enclosures. The results can be directly applied to passive cooling systems in electronics, battery packs, solar thermal collectors, and energy-efficient buildings, where optimizing heat transfer is vital without employing active control methods. Full article

This study examined the comprehensive properties of Mg-Zn-Nd-Zr alloys in order to achieve both high strength and thermal conductivity simultaneously. The impact of rolling on the microstructure, mechanical properties, and thermal conductivity was analyzed for Mg-5Zn-xNd-0.4Zr alloys (x = 1, 2). The results indicate that the addition of Nd promotes the formation of the W phase (Mg₃Zn₃RE₂), which contributes to grain boundary strengthening and enhances the overall strength. Moreover, dynamic precipitation during the rolling process leads to the formation of nanoscale MgZn₂ and Zn₂Zr phases, significantly improving both the strength and thermal conductivity. After rolling, both the Mg-5Zn-1Nd-0.4Zr (ZNK510) and Mg-5Zn-2Nd-0.4Zr (ZNK520) alloys exhibited a notable enhancement in thermal conductivity, with ZNK520 demonstrating superior properties due to its higher Nd content. This study highlights that optimizing alloy composition and phase evolution through rolling can markedly enhance both the mechanical and thermal properties, offering a promising strategy for the development of high-performance magnesium alloys. Full article

The increasing complexity of urban structures has significantly elevated the risk and severity of façade fires in high-rise buildings. Unlike traditional models assuming continuous fuel beds, real-world fire scenarios often involve discrete combustible materials arranged in discrete fuel matrices. This study presents a systematic investigation into the influence of lateral spacing on vertical flame propagation behavior. Laboratory-scale experiments were conducted using vertically oriented polymethyl methacrylate (PMMA) fuel arrays under nine different spacing configurations. Results reveal that lateral spacing plays a critical role in determining flame spread paths and intensities. Specifically, with a vertical spacing fixed at 8 cm, a lateral spacing of 10 mm resulted in rapid flame growth, reaching a peak flame height of approximately 96.5 cm within 450 s after ignition. In contrast, increasing the lateral spacing to 15 mm significantly slowed flame development, achieving a peak flame height of just under 90 cm at approximately 600 s. This notable transition in flame dynamics is closely associated with the critical thermal boundary layer thickness (~11.5 mm). Additionally, at 10 mm spacing, a chimney-like effect was observed, enhancing upward air entrainment and resulting in intensified combustion. These findings reveal the coupled influence of geometric configuration and heat transfer mechanisms on façade flame propagation. The insights gained provide guidance for cladding system design, suggesting that increasing lateral separation between combustible elements may be an effective strategy to limit flame spread and enhance fire safety performance in buildings. Full article

Diamond is an attractive substrate candidate for GaN high-electron-mobility transistors (HEMT) to enhance heat dissipation due to its exceptional thermal conductivity. However, the thermal boundary resistance (TBR) at the GaN–diamond interface poses a significant bottleneck to heat transport, exacerbating self-heating and limiting device performance. In this work, TCAD simulations were employed to systematically investigate the effects of thermal boundary layer (TBL) thickness (d_TBL) and thermal conductivity (κ_TBL) on the electrothermal behavior of GaN-on-diamond HEMTs. Results show that increasing the TBL thickness (5–20 nm) or decreasing its thermal conductivity (0.1–1.0 W/(m·K)) leads to elevated hotspot temperatures and degraded electron mobility, resulting in a notable deterioration of I–V characteristics. The nonlinear dependence of device performance on κ_TBL is attributed to Fourier’s law, where heat flux is inversely proportional to thermal resistance. Furthermore, the co-analysis of substrate thermal conductivity and interfacial quality reveals that interface TBR has a more dominant impact on device behavior than substrate conductivity. Remarkably, devices with low thermal conductivity substrates and optimized interfaces can outperform those with high-conductivity substrates but poor interfacial conditions. These findings underscore the critical importance of interface engineering in thermal management of GaN–diamond HEMTs and provide a theoretical foundation for future work on phonon transport and defect-controlled thermal interfaces. Full article

The extensive use of copper in thermal and electrical systems calls for constant performance enhancement by means of innovative material treatments. The effects on the microstructural, mechanical, and electrical characteristics of copper in deep cryogenic treatment (DCT) and deep cryogenic treatment followed by heat treatment (DCT + HT) are investigated in this work. Copper samples were treated for various soaking durations ranging from 6 to 24 h. Mechanical properties such as tensile strength, hardness, and wear rate were analyzed. In the DCT-treated samples, tensile strength increased, reaching a peak of 343 MPa at 18 h, alongside increased hardness (128 HV) and a refined grain size of 9.58 µm, primarily due to elevated dislocation density and microstrain. At 18 h of soaking, DCT + HT resulted in improved structural stability, high hardness (149 HV), a fine grain size (7.42 µm), and the lowest wear rate (7.73 × 10⁻¹⁰ mm³/Nm), consistent with Hall–Petch strengthening. Electrical measurements revealed improved electron mobility (52.08 cm²/V·s) for samples soaked for 24 h in DCT + HT, attributed to increased crystallite size (39.9 nm), reduced lattice strain, and higher (111) texture intensity. SEM–EBSD analysis showed a substantial increase in low-angle grain boundaries (LAGBs) in DCT + HT-treated samples, correlating with enhanced electrical conductivity. Overall, an 18 h soaking duration was found to be optimal for both treatments. However, the strengthening mechanism in DCT + HT is influenced by grain boundary stabilization and thermal recovery and is different to DCT, which is strain-induced enhancement. Full article

Dissolved gas analysis remains the most widely utilized non-intrusive diagnostic method for detecting incipient faults in insulating liquid-immersed transformers. Despite their prevalence, conventional ratio-based methods often suffer from ambiguity and limited potential for automation applicrations. To address these limitations, this study proposes a unified multiclass classification model that integrates traditional gas ratio features with supervised machine learning algorithms to enhance fault diagnosis accuracy. The performance of six machine learning classifiers was systematically evaluated using training and testing data generated through four widely recognized gas ratio schemes. Grid search optimization was employed to fine-tune the hyperparameters of each model, while model evaluation was conducted using 10-fold cross-validation and six performance metrics. Across all the diagnostic approaches, ensemble models, namely random forest, XGBoost, and LightGBM, consistently outperformed non-ensemble models. Notably, random forest and LightGBM classifiers demonstrated the most robust and superior performance across all schemes, achieving accuracy, precision, recall, and F1 scores between 0.99 and 1, along with Matthew correlation coefficient values exceeding 0.98 in all cases. This robustness suggests that ensemble models are effective at capturing complex decision boundaries and relationships among gas ratio features. Furthermore, beyond numerical classification, the integration of physicochemical and dielectric properties in this study revealed degradation signatures that strongly correlate with thermal fault indicators. Particularly, the CIGRÉ-based classification using a random forest classifier demonstrated high sensitivity in detecting thermally stressed units, corroborating trends observed in chemical deterioration parameters such as interfacial tension and CO₂/CO ratios. Access to over 80 years of operational data provides a rare and invaluable perspective on the long-term performance and degradation of power equipment. This extended dataset enables a more accurate assessment of ageing trends, enhances the reliability of predictive maintenance models, and supports informed decision-making for asset management in legacy power systems. Full article

This paper focuses on the use of advanced optimization design strategies to improve the performance and service life of engine pistons, with emphasis on enhancing their stiffness, strength, and dynamic characteristics. As a core component of the engine, the structural design and optimization of the piston are of great significance to its efficiency and reliability. First, a three-dimensional (3D) model of the piston was constructed and imported into ANSYS Workbench for finite element modeling and high-quality meshing. Based on the empirical formula, the actual working environment temperature and heat transfer coefficient of the piston were accurately determined and used as boundary conditions for thermomechanical coupling analysis to accurately simulate the thermal and deformation state under complex working conditions. Dynamic characteristic analysis was used to obtain the displacement–frequency curve, providing key data support for predicting resonance behavior, evaluating structural strength, and optimizing the design. In the optimization stage, five geometric dimensions are selected as design variables. The deformation, mass, temperature, and the first to third natural frequencies are considered as optimization goals. The response surface model is constructed by means of the design of the experiments method, and the fitted model is evaluated in detail. The results show that the models are all significant. The adequacy of the model fitting is verified by the “Residuals vs. Run” plot, and potential data problems are identified. The “Predicted vs. Actual” plot is used to evaluate the fitting accuracy and prediction ability of the model for the experimental data, avoiding over-fitting or under-fitting problems, and guiding the optimization direction. Subsequently, the sensitivity analysis was carried out to reveal the variables that have a significant impact on the objective function, and in-depth analysis was conducted in combination with the response surface. The multi-objective genetic algorithm (MOGA), screening, and response surface methodology (RSM) were, respectively, used to comprehensively optimize the objective function. Through experiments and analysis, the optimal solution of the MOGA algorithm was selected for implementation. After optimization, the piston mass and deformation remained relatively stable, and the working temperature dropped from 312.75 °C to 308.07 °C, which is conducive to extending the component life and improving the thermal efficiency. The first to third natural frequencies increased from 1651.60 Hz to 1671.80 Hz, 1656.70 Hz to 1665.70 Hz, and 1752.90 Hz to 1776.50 Hz, respectively, significantly enhancing the dynamic stability and vibration resistance. This study integrates sensitivity analysis, response surface models, and genetic algorithms to solve multi-objective optimization problems, successfully improving piston performance. Full article

Medium- and large-scale heat sinks are critical for thermal load management in high-performance systems. However, their high heat flux densities and limited space complicate cooling, leading to risks of overheating, performance degradation, or failure. This study employs the Cascaded Lattice Boltzmann Method (CLBM) to enhance their thermal performance. This numerical approach is known for being stable, accurate when dealing with complex boundaries, and efficient when computing in parallel. The numerical code was validated against a benchmark configuration and an experimental setup to ensure its reliability and accuracy. While previous studies have explored mixed convection in cavities or heat sinks, few have addressed configurations involving side air injection and boundary conditions periodicity in the transition-to-turbulent regime. This gap limits the understanding of realistic cooling strategies for compact systems. Focusing on mixed convection in the transition-to-turbulent regime, where buoyancy and forced convection interact, the study investigates the impact of Rayleigh number values ($5\times {10}^7$ to $5\times {10}^8$) and Reynolds number values (${10}^3$ to $3\times {10}^3$) on heat transfer. Simulations were conducted in a rectangular cavity with periodic boundary conditions on the vertical walls. Two heat sources are located on the bottom wall ($T_h$ = 50 °C). Two openings, one on each side of the two hot sources, force a jet of fresh air in from below. An opening at the level of the cavity ceiling’s axis of symmetry evacuates the hot air. Mixed convection drives the flow, exhibiting complex multicellular structures influenced by the control parameters. Calculating the average Nusselt number (Nu) across the surfaces of the heat sink reveals significant dependencies on the Reynolds number. The proposed correlation between Nu and Re, developed specifically for this configuration, fills the current gap and provides valuable insights for optimizing heat transfer efficiency in engineering applications. Full article

This study examines the behavior of Rayleigh waves propagating through a homogeneous, isotropic material, analyzed using a three-phase-lag thermoelastic diffusion framework enhanced by modified couple stress theory. The mathematical model integrates coupled thermoelastic and diffusive effects, incorporating phase-lags associated with (1) temperature gradients, (2) heat flux, and (3) thermal displacement gradients. By solving the derived governing equations analytically subject to stress-free, thermally insulated, and impermeable boundary conditions, we obtain the characteristic secular equation for Rayleigh wave propagation. Numerical simulations conducted on a copper medium evaluate how the secular equation’s determinant, wave velocity, and attenuation coefficient vary with angular frequency. The analysis focuses particularly on the influence of phase-lag parameters, including thermal and diffusion gradients and relaxation times. Results demonstrated that increasing the displacement gradient phase-lag elevated the secular determinant but reduced wave velocity and attenuation, while temperature gradient phase-lags exhibited the opposite trend. The study highlights the sensitivity of Rayleigh wave propagation to thermo-diffusive coupling and microstructural effects, offering insights applicable to seismic wave analysis, geophysical exploration, and material processing. Comparisons with prior theories underscore the model’s advancement in capturing size-dependent and memory-dependent phenomena. Full article

Underground spaces offer significant potential for sustainable urban development, particularly in cold climate regions where surface thermal fluctuations are extreme. However, optimizing the wind–heat environmental performance of such spaces remains insufficiently explored, especially in relation to spatial morphology. This study addresses this gap by investigating how underground spatial configurations influence thermal comfort and ventilation efficiency. Six representative spatial prototypes—fully enclosed, single-side open, double-side open, central atrium, wind tower, and earth kiln—were constructed based on common underground design typologies. Computational fluid dynamics (CFD) simulations were conducted to evaluate airflow patterns and thermal responses under winter and summer conditions, incorporating relevant geotechnical properties into the boundary setup. The results indicate that deeper burial depths enhance thermal stability, while central atrium and wind tower prototypes offer the most balanced performance in both ventilation and heat regulation. These findings provide valuable design guidance for climate-responsive underground developments and contribute to the interdisciplinary integration of building physics, spatial design, and geotechnical engineering. Full article

This study investigates the grain characteristics and high-temperature tensile properties of an additively manufactured (AM) TA15 titanium alloy. Directed energy deposition (DED) was utilized for its high material efficiency and design flexibility to explore the alloy’s applicability in aerospace manufacturing, where TA15 is valued for its excellent high-temperature performance. A comparative analysis between DED and hot-rolled TA15 alloys was conducted at 25 °C and 600 °C to examine the influence of grain size and crystallographic texture on mechanical behavior. The AM TA15 alloy exhibited superior tensile properties at both temperatures compared to its hot-rolled counterpart. Microstructural analysis revealed finer grain size, stronger α-phase diffraction intensity, and altered grain boundary misorientation in the AM alloy after high-temperature testing, accompanied by improved plasticity. These findings highlight the potential of thermal process optimization and microstructural tailoring to enhance the high-temperature performance of AM TA15, offering valuable insights for the fabrication of critical aerospace components. Full article

This study introduces an innovative analytical solution to the time-fractional Cattaneo heat conduction equation, which models photothermal transport in metallic thin films subjected to short laser pulse irradiation. The model integrates the Caputo fractional derivative of order 0 < p ≤ 1, addressing non-Fourier heat conduction characterized by finite wave speed and memory effects. The equation is nondimensionalized through suitable scaling, incorporating essential elements such as a newly specified laser absorption coefficient and uniform initial and boundary conditions. A hybrid approach utilizing the finite Fourier cosine transform (FFCT) in spatial dimensions and the Laplace transform in temporal dimensions produces a closed-form solution, which is analytically inverted using the two-parameter Mittag–Leffler function. This function inherently emerges from fractional-order systems and generalizes traditional exponential relaxation, providing enhanced understanding of anomalous thermal dynamics. The resultant temperature distribution reflects the spatiotemporal progression of heat from a spatially Gaussian and temporally pulsed laser source. Parametric research indicates that elevating the fractional order and relaxation time amplifies temporal damping and diminishes thermal wave velocity. Dynamic profiles demonstrate the responsiveness of heat transfer to thermal and optical variables. The innovation resides in the meticulous analytical formulation utilizing a realistic laser source, the clear significance of the absorption parameter that enhances the temperature amplitude, the incorporation of the Mittag–Leffler function, and a comprehensive investigation of fractional photothermal effects in metallic nano-systems. This method offers a comprehensive framework for examining intricate thermal dynamics that exceed experimental capabilities, pertinent to ultrafast laser processing and nanoscale heat transfer. Full article

This study investigates, both experimentally and theoretically, the impact of incorporating window shutters on the thermal resistance of double-glazed window units, employing computational fluid dynamics (CFD) modelling. The integration of shutters, whether installed internally or externally, introduces an additional air layer that significantly influences heat transfer between indoor and outdoor environments. This effect on the thermal performance of the transparent structure was analysed through experimental measurements under real operating conditions and numerical simulations involving fluid dynamics and energy equations for the air gaps, alongside heat conduction equations for the solid components. Fourth-kind boundary conditions, considering both radiative and conductive components of the total heat flux emanating from the building’s interior, were applied at the solid–gas interfaces. The simulation results, comparing heat transfer through double-glazed windows with and without shutters, demonstrate a substantial increase in thermal resistance, ranging from 2 to 2.5 times, upon shutter implementation. These findings underscore the effectiveness of employing shutters as a strategy to enhance the energy efficiency of windows and, consequently, the overall energy performance of buildings. This research contributes to the advancement of sustainable materials for engineering applications by providing insights into the optimisation of thermal performance in building envelopes. Full article

Transpiration cooling is an efficient thermal protection technology used for scramjet combustors and other components. However, a conventional transpiration cooling plate structure with uniform porous media distribution suffers from a large temperature difference between the upstream and downstream surfaces and high coolant injection pressure (p). To enhance the overall cooling effect and reduce the maximum surface temperature and coolant injection pressure, the combined particle diameter plate structure (CPD−PS) is proposed. Numerical simulations show that compared with the single-particle diameter plate structure (SPD−PS), the CPD−PS with a larger upstream particle diameter (d_p) than that of the downstream (d_pA > d_pB) can effectively reduce the upstream temperature and improve average cooling efficiency (η_ave). Meanwhile, gradually increasing d_p will increase the permeability of porous media, reduce coolant flow resistance, and thus lower coolant injection pressure. An optimization analysis of CPD−PS is conducted using response surface methodology (RSM), and the influence of design variables on the objective function (η_ave and p) is analyzed. Further optimization with the multi-objective genetic algorithm (MOGA) determines the optimal structural parameters. The results suggest that porosity (ε) and d_p are the most crucial parameters affecting η_ave and p of CPD−PS. After optimization, the maximum temperature of the porous plate is significantly reduced by 8.40%, and the average temperature of the hot end surface is also reduced. The overall cooling performance is effectively improved, η_ave is increased by 6.02%, and p is significantly reduced. Additionally, the upstream surface velocity of the optimized structure changes and the boundary layer thickens, which enhances the thermal insulation effect. Full article

This study systematically investigates the combustion behavior and kinetic characteristics of oil shale semi-coke. Thermogravimetric analysis (TGA) experiments, combined with both model-free and model-based methods, were used to explore the thermal characteristics, kinetic parameters, and reaction mechanisms of the combustion process. The results show that the combustion process of oil shale semi-coke can be divided into three stages: a low-temperature stage (50–310 °C), a mid-temperature stage (310–670 °C), and a high-temperature stage (670–950 °C). The mid-temperature stage is the core of the combustion process, accounting for approximately 28–37% of the total mass loss, with the released energy concentrated and exhibiting significant thermal chemical activity. Kinetic parameters calculated using the model-free methods (OFW and KAS) and the model-based Coats–Redfern method reveal that the activation energy gradually increases with the conversion rate, indicating a multi-step reaction characteristic of the combustion process. The F2-R3-F2 model, with its segmented mechanism (boundary layer + second-order reaction), better fits the physicochemical changes during semi-coke combustion, and the analysis of mineral phase transformations is more reasonable. Therefore, the F2-R3-F2 model is identified as the optimal model in this study and provides a scientific basis for the optimization of oil shale semi-coke combustion processes. Furthermore, scanning electron microscopy (SEM) and X-ray diffraction (XRD) analyses were conducted on oil shale semi-coke samples before and after combustion to study the changes in the combustion residues. SEM images show that after combustion, the surface of the semi-coke sample exhibits a large number of irregular holes, with increased pore size and a honeycomb-like structure, indicating that the carbonaceous components were oxidized and decomposed during combustion, forming a porous structure. XRD analysis shows that the characteristic peaks of quartz (Q) are enhanced after combustion, while those of calcite (C) and pyrite (P) are weakened, suggesting that the mineral components underwent decomposition and transformation during combustion, particularly the decomposition of calcite into CO₂ at high temperatures. Infrared spectroscopy (IR) analysis reveals that after combustion, the amount of hydrocarbons in the semi-coke decreases, while aromatic compounds and incompletely decomposed organic materials are retained, further confirming the changes in organic matter during combustion. Full article