Search Results (240)

This research presents a physics-informed deep learning framework for investigating the magnetohydrodynamic flow of a dissipative non-Newtonian micropolar nanofluid induced by a stretching sheet, incorporating Stefan blowing, internal heat generation, and the zero nanoparticle mass flux condition. The physical model consists of the interplay between the microrotation dynamics, resistance of porosity on the microrotation, Brownian diffusion, and thermophoretic transport phenomenon. The numerical solutions for the nonlinear yielded equations that result from the above interaction are obtained by employing a PINN that considers the laws of physics and boundary conditions. With this technique, the flow behavior, temperature, concentration, and microrotation fields can be predicted accurately without requiring huge datasets. This shows the ability of PINNs to numerically treat highly-coupled nonlinear transport equations in a very efficient manner compared to other traditional methods. The important discoveries from this study include that the porous and magnetic factors increased the skin friction coefficient, but the magnetic effect and viscous dissipation decreased the rate of heat transfer, and the thermophoresis effect decreased the rate of mass transfer while the Brownian effect increased it. The precision of the PINN algorithm is confirmed by comparison of the results with the earlier findings, which proves very high accuracy and hence the robustness of the current computing framework. Results of this research are useful for the development of some thermal management systems, energy converters, cooling methods, chemical reaction processes, fuel cell technology, porous media reactors, and ocean engineering involving the transport of complicated non-Newtonian nanofluids. Full article

Hairpin windings are increasingly adopted in permanent magnet (PM) traction machines owing to their high slot fill factor, compact end-winding structure, and suitability for automated manufacturing. However, limited heat dissipation and high copper losses under peak loading and high-frequency operation result in severe thermal constraints, which restrict the power rating of the machine. This paper presents a multi-physics comparison of different winding cooling topologies for a PM machine with hairpin winding, including hollow conductor cooling, end-winding cooling, and cooling channel insertion at slot-bottom, slot-middle, and slot-opening regions. A coupled electromagnetic–thermal model based on the finite element method (FEM), which accounts the heat transfer between different components, is used to analyze temperature distribution, losses, efficiency, loading capacity, and hydraulic requirements. The results show that the position of the cooling channel has great influence on the thermal behavior and electromagnetic performance of the machine under different working conditions. The study emphasizes the strong coupling between cooling design, conductor geometry, AC loss behavior, and efficiency and provides practical design guidelines for selecting appropriate cooling techniques in high-power-density traction machines. Consequently, an improved cooling system results in a reduced amount of PM for the same output power range. Full article

Adaptive construction techniques in traditional vernacular dwellings play an important role in improving the wind–thermal microclimate of buildings. However, comparative studies on such techniques across different regions remain limited. Moving beyond a static regional perspective, this study selects six representative skywell dwellings along the historical migration route from Jiangxi to Hunan. Through field monitoring and CFD numerical simulation using PHOENICS, the wind–thermal performance of these dwellings under extreme summer high-temperature conditions is comparatively analyzed. The results reveal case-based regional differences characterized by “shared origins and regional differentiation.” The western Jiangxi dwellings tend to adopt ventilation as the main spatial logic, using open spaces to enhance convective heat dissipation. In contrast, the northern Hunan dwellings show more prominent shading and heat control characteristics, relying on optimized skywell geometry to achieve geometric shading and reduce radiative heat gain. This study clarifies that adaptive construction techniques vary significantly under regional influences, and the findings may provide quantitative data support and design references for optimizing the microenvironment of contemporary buildings. Full article

This research analyzes the wavy, axisymmetric flow of a Ree–Eyring non-Newtonian nanofluid, infused with motile microorganisms, within a porous, tapered cylindrical channel under a transverse magnetic field. This investigation presents a theoretical framework that may inform the improvement of energy efficiency and thermal management in biomedical engineering applications, such as drug delivery systems and microfluidic biosensors. The work provides an extended insight by a contribution to the evaluation of entropy generation, explicitly considering the influence of motile microorganisms, thereby bridging a gap in the existing literature. The comprehensive physical model further incorporates the combined effects of Joule heating, viscous dissipation, nonlinear thermal radiation, and chemical reactions. Methodologically, the governing nonlinear equations of the system were rendered tractable under long-wavelength and low-Reynolds-number assumptions and subsequently solved using the numerical Runge–Kutta–Fehlberg technique. The key conclusion is that, based on the present numerical model, careful selection of magnetic field strength and microorganism motility parameters may reduce irreversible energy losses, potentially improving the net usable work in advanced nanofluid transport systems for biomedical applications, subject to experimental validation. The most significant finding reveals that the magnetic field serves as a dual-purpose control parameter: increasing its strength boosts total entropy generation by 20–30% while simultaneously raising the Bejan number, confirming heat transfer as the dominant irreversibility mechanism in the system. Additionally, nanoparticle concentration diminishes substantially with elevated chemical reaction rates and Schmidt numbers, while microorganism density is highly sensitive to the Péclet number, which causes flow disruptions. Full article

The rapid growth of Deep Neural Networks (DNNs) has led to the development of application-specific DNN accelerators. Conventional 2D von Neumann architectures suffer from memory bandwidth limitations between the memory and the processing core. 3D DNN accelerators have emerged as a promising solution by leveraging 3D integration to enable near-memory logic or in-memory computation. By shifting computation closer to memory, these accelerators significantly reduce data movement and therefore latency, resulting in more energy-efficient operations. Monolithic 3D (M3D) integration, in particular, enables high-bandwidth systems by utilizing high-density monolithic inter-tier vias (MIVs). This paper provides a critical review of recent advances in 3D DNN accelerators that combine near-memory and compute-in-memory with various 3D technologies, offering a useful discussion and future prospects of the available technologies and architectures that have advanced the performance of DNN accelerators. Particular attention is devoted to accelerators for emerging transformer-based large language model (LLM) networks due to the higher memory demands. Thermal-aware design techniques of 3D DNN accelerators are also discussed as a means to address the fundamental challenge of heat dissipation. A detailed review is finally conducted on package-level constraints, considering signal integrity, power delivery, and thermo-mechanical reliability. Full article

This study proposes a multi-objective optimization strategy for the structural design of liquid-cooled channels in battery systems, aiming to identify liquid-cooled plate design schemes with better cooling performance and acceptable flow resistance. Optimal Latin hypercube sampling (OLHS) was combined with computational fluid dynamics (CFD) simulations to construct a CFD-generated dataset that includes the maximum temperature and system pressure drop. Then, modeFRONTIER was employed to integrate surrogate-model training, rapid prediction, and non-dominated sorting genetic algorithm II (NSGA-II) optimization, thereby obtaining the Pareto optimal set. The technique for order preference by similarity to ideal solution (TOPSIS) decision method was further introduced to determine the final optimal design. Results indicate that the optimized liquid-cooling system exhibits outstanding comprehensive performance in terms of balancing heat dissipation and flow resistance at a 5 C discharge rate. Remarkably, sensitivity analysis shows that inlet velocity is the dominant factor affecting the maximum battery temperature, with a correlation coefficient of −0.789. The maximum temperature of the battery module is effectively limited to 30.07 °C, while the flow pressure drop is only 799.58 Pa, achieving an excellent balance between heat dissipation efficiency and energy consumption. Full article

Cermet tools possess favorable mechanical and tribological properties and are widely adopted for machining hard-to-cut materials. However, their performance can further be enhanced with different cooling and lubrication techniques. In this study, the tool wear mechanisms of cermet tools during hard turning of AISI 4340 alloy steel are investigated under dry and minimum quantity lubrication (MQL) environments to identify the prevalent causes of tool failure through comprehensive analysis of tool wear progression, chip temperature, and chip morphological analysis. The results revealed that the application of MQL exhibited prolonged and stable steady-state tool wear progression with retained cutting-edge geometry, thus demonstrated 30.27% improvement in tool life compared to dry cutting. On the contrary, a rapid increase in tool wear due to excessive friction and higher thermal load is noticed with dry cutting in the absence of any heat-dissipating medium. Chip temperature measurements supported these observations, as chip temperature increases sharply from 358 °C (with a fresh tool) to about 1090 °C (with a worn tool) under a dry environment. Conversely, with MQL, the corresponding increase was in the range between 294 °C and 843 °C with a fresh and worn tool, respectively. Chip analysis revealed a serrated type of chip morphology. Dry cutting exhibited intensified feed marks, indicative of severe tool–chip friction, whereas MQL demonstrated smoother morphology with closely spaced saw-tooth patterns. Tool wear mechanisms indicate abrasion, adhesion, and edge chipping as dominant wear mechanisms under both environments; however, in the absence of any lubricant, these mechanisms were more intensified with higher crater formation. Full article

Laser-based Powder Bed Fusion (LPBF) enables the fabrication of complex metal components but often results in high porosity and microdefect densities, compromising fatigue performance despite acceptable static properties. Standard fatigue characterisation methods are time-consuming and costly and yield scattered results due to defect-induced brittleness and residual stresses. This study investigates the application of thermographic techniques as a rapid alternative for evaluating the intrinsic fatigue behaviour of tensile coupons fabricated by LPBF employing AISI 316L steel. By monitoring surface temperature during stepwise static monotone and fatigue loading, thermographic methods aim to detect early hints of heat dissipation associated with microdamage initiation. Approaches based on temperature harmonic analysis have been implemented, allowing near-real-time and full-field mapping of stress distribution and damage development. Results show that harmonic metrics correlate with the material state and effectively track the thermoelastic effect-induced temperature changes. Some evidence is found regarding the onset of intrinsic heat dissipation, which needs to be confirmed by more focused and extensive experimental tests. Full article

Solid-state lighting, especially light-emitting diodes (LEDs), is revolutionizing indoor lighting due to its energy efficiency, long lifespan, low heat output, and enhanced color rendering. LEDs can quickly adjust light intensity, enabling the development of visible light communication (VLC) technology. However, the modulation bandwidth of phosphor-converted white LEDs commonly used for illumination is limited, potentially affecting the speed of the VLC links. This paper presents a receiver-side equalization technique to overcome bandwidth limitations in VLC links due to LEDs. The proposed approach utilizes a novel transimpedance amplifier with an embedded T-network shunt-feedback equalizer (TIA-TE) to introduce adjustable high-frequency peaking in the TIA’s frequency response. By incorporating this peaking, the system’s bandwidth is extended without sacrificing important performance parameters like gain, noise, or power dissipation. The TIA-TE is followed by a main amplifier and a standalone continuous-time linear equalizer (CTLE) for further signal conditioning, while a 50 Ω buffer interfaces the receiver with measurement equipment. Post-layout simulations in a 0.35 µm CMOS process validate the approach. Using a 4 pF photodiode, the system bandwidth was initially limited by the LED’s 3 MHz modulation bandwidth. The proposed TIA-TE extends the bandwidth to 8.4 GHz without sacrificing the gain or power dissipation. The subsequent CTLE further extends the bandwidth to 14 MHz. The receiver front end achieves a mid-band transimpedance of 110 dBΩ and an input-referred noise current of 7.2 nA_rms, while dissipating 2.48 mW (excluding the 50 Ω buffer). Simulated 28 Mb/s NRZ eye diagrams demonstrate the feasibility of the proposed TIA-TE architecture for LED-limited VLC links. Full article

This study numerically investigates the hydrothermal behaviour of a Jeffrey nanofluid with relevance to maritime thermal systems. The coupled nonlinear governing equations for momentum, heat, and mass transport are solved using a shooting technique that accounts for magnetohydrodynamic effects, Darcy porous-media resistance, viscous dissipation, and spatially varying internal heat generation. Variable thermophysical properties, including temperature-dependent viscosity and density, are also considered. The results reveal that porous resistance, fluid elasticity, and thermophysical variations significantly influence velocity, temperature, and concentration fields. The combined effects of porous drag and variable properties markedly alter the characteristics of heat and mass transfer. These findings provide insights into thermal and mass-transport performance, including skin friction, heat transfer, and concentration distributions, which are critical metrics for porous heat exchangers and nanofluid-based maritime coatings. Here, maritime relevance is represented via a generalised porous nanofluid model rather than a specific material. Among the key findings, increasing the slip velocity factor can reduce the surface skin-friction coefficient by approximately 48.7%, while the heat-transfer rate increases by nearly 27.1%, accompanied by a decrease of about 18.9% in the Sherwood number. Conversely, raising the density factor enhances the skin friction coefficient by roughly 103.8% and also augments the heat and mass transfer rates by about 61.3% and 106.1%, respectively. Likewise, at zero relaxation–retardation ratio, the flow reduces to the Newtonian case. Increasing this factor reduces the local Nusselt number by about 1.45%, indicating a slight weakening of heat transfer due to elastic effects. Furthermore, the reliability of the current numerical framework is established through a dual-validation approach, including an analytical assessment of limiting cases and a rigorous comparison with established data from the literature. Full article

In this study, a novel and efficient solid-state additive manufacturing technique, friction rolling additive manufacturing (FRAM), was employed to fabricate an aluminum alloy ring component, significantly reducing process complexity and mitigating solidification defects typical of melt-based techniques. However, previous studies on FRAM have primarily focused on the microstructural characteristics and mechanical properties of flat components, with limited attention paid to ring-shaped components. Owing to the unique geometric constraints imposed during the forming process, ring components exhibit markedly different microstructural evolution and defect formation mechanisms compared with flat counterparts, and these mechanisms remain insufficiently and systematically understood. To address this knowledge gap, the coupled Eulerian–Lagrangian (CEL) method was introduced for the first time to numerically simulate the temperature distribution and residual stress evolution during the FRAM process of ring-shaped components. In addition, tracer particles were incorporated into the simulations to analyze the material flow behavior, thereby systematically elucidating the forming behavior and microstructural evolution characteristics under geometric constraint conditions. Moreover, scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD) were employed to systematically characterize the microstructural evolution and defect morphology. The CEL numerical simulations exhibited good consistency with the experimental observations, demonstrating the reliability and accuracy of the simulation method. The results showed that the peak temperatures were primarily concentrated at the advancing side of the rotation tool, and the temperature on the outer diameter side of the ring was consistently higher than that on the inner diameter side. The lack of shoulder friction on the inner side led to an increased heat dissipation rate, thereby resulting in higher residual stress compared to other regions. The particle analysis revealed that, due to ring geometry, material flow varied across radial regions, resulting in distinct microstructures. Further EBSD analysis revealed that, after the rotating tool passed, the material first developed a preferential orientation with {111} planes parallel to the shear direction, and with more layers, dynamic recrystallization produced an equiaxed grain structure. This study provides a theoretical basis and process reference for the application of the FRAM technique in the manufacturing of large ring components. Full article

The present study investigates the magnetohydrodynamic (MHD) flow characteristics of a blood-based ternary nanofluid (Au/Cu/Al₂O₃-blood) in stenosed arteries, with a focus on symmetry-inspired modeling rooted in the axial symmetry of arterial geometry and the symmetric distribution of external physical fields (magnetic field, thermal radiation). The findings offer significant insights into the realm of hyperthermia therapy and targeted drug delivery within the domain of biomedical engineering. A mathematical model is established under a cylindrical coordinate system (consistent with arterial axial symmetry), integrating key physical effects (thermal radiation, chemical reactions, viscous dissipation, body acceleration) and fractional-order dynamics via Caputo derivatives—while ensuring the symmetry of governing equations in time and space. The numerical solutions for velocity and temperature profiles are obtained using the Laplace transform and Concentrated Matrix-Exponential (CME) method, a technique that preserves symmetric properties during the solution process. The results of the study indicate the following: The Hartmann number, which is increased, has been shown to reduce axial velocity due to the Lorentz force, thereby maintaining radial symmetry. Furthermore, thermal radiation has been demonstrated to raise fluid temperature, a critical factor in heat-based therapies, with the temperature field evolving symmetrically. In addition, it has been observed that ternary nanoparticles outperform single and binary systems in heat and mass transfer via symmetric dispersion. This work contributes to the existing body of knowledge by integrating symmetry principles into the study of fractional dynamics, electromagnetic fields, and body acceleration modeling. It establishes a comprehensive biomedical flow framework. It is imperative that future research explore pulsatile flow under symmetric boundaries and validate the model through experimental means. Full article

Chinese shale reservoirs are typically deep, clay-rich, and highly water-sensitive, which severely limits the effectiveness of conventional hydraulic fracturing. To address this challenge, we propose a microwave-assisted waterless fracturing method and investigate its feasibility through laboratory experiments on core samples from the Gulong shale and tight sandstone formations in the Daqing Oilfield. A coupled model integrating microwave power dissipation, pore water heating, and thermal stress evolution is developed to interpret the underlying mechanisms. Experimental results show that, under microwave irradiation (200 W, 40 s) and initial pore water content of 2.1–6%, fracturing is successfully induced without external fluid injection. The tensile failure of the rock coincides with the peak internal pore pressure generated by rapid vaporization and thermal expansion of pore water, as confirmed by a modified tensile strength measurement method. Fracture patterns observed in SEM and post-treatment imaging align with model predictions, demonstrating that microwave energy absorption by pore water is the primary driver of rock failure. The technique eliminates water-related formation damage and is inherently suitable for deep, water-sensitive reservoirs. This study provides experimental evidence and mechanistic insight supporting microwave-based waterless fracturing as a viable approach for challenging shale formations. Full article

A thermal management system is crucial to ensure temperature uniformity in electric vehicle battery packs. Maintaining the battery system’s temperature within a safe range is critical to prolonging the service life of lithium-ion cells. This study investigates the efficiency of direct liquid immersion cooling systems for lithium-ion battery units in electric vehicles. In this work, Computational Fluid Dynamics (CFD) simulations were employed to analyze the thermal behavior of a 23-cell battery module cooled by immersion, coded by commercial software ANSYS Fluent 2025 R1. For the optimization calculations, an in -hose code was developed in in Python and implemented. The module was optimized by adjusting various design and operating parameters. Immersion cooling, achieved by submerging the battery in a cooling fluid, offers markedly higher heat transfer performance than conventional cooling techniques. The optimal temperature distribution and heat dissipation were achieved by modifying the cell length and diameter, followed by adjustments to the width, length, and height of the battery case, and finally, the coolant inlet velocity. The outcomes of this study are expected to provide valuable guidance for researchers and engineers in both academia and industry, contributing to the development of more powerful, reliable, and long-lasting electric vehicles. Full article

This scientific research examines the intricate dynamics of Maxwell nanofluid flow across a stretching surface with Stefan blowing impacts, with a particular focus on maritime thermal management applications. The analysis integrates multiple physical phenomena including magnetohydrodynamic forces, the energy dissipation phenomenon, and thermal density variations within Darcy porous media. Special attention is given to Stefan blowing’s role in modifying thermal and mass transfer boundary layers. We derive an enhanced mathematical formulation that couples Maxwell fluid properties with nanoparticle transport under combined magnetic and density-gradient conditions. Computational results demonstrate the crucial influence of viscous heating and blowing intensity on thermal performance, with direct implications for naval cooling applications. The reduced governing equations form a nonlinear system that requires robust numerical treatment. We implemented the shooting technique to solve this system, verifying its precision through systematic comparison with established benchmark solutions. The close correspondence between results confirms both the method’s reliability and our implementation’s accuracy. The primary results of this study indicate that raising the Stefan blowing and density parameters causes notable changes in the temperature and concentration fields. The Stefan blowing parameter enhances both temperature and concentration near the wall by affecting thermal diffusion and nanoparticle distribution. In contrast, the density parameter reduces these values because of increased fluid resistance. Full article