Search Results (1,908)

To address the critical challenge of excessive junction temperature caused by ultra-high heat flux densities (>100 W/cm²) in deep-sea LED Fish-Attracting Lamp (FAL) arrays, this study proposes a hybrid thermal management scheme integrating interfacial micro-texturing, chimney-effect convection, and heat pipe phase-change heat transfer, achieving the unification of passive high-efficiency heat dissipation and pressure-resistant sealing. The FAL housing structure is reconfigured using topology optimization to construct chimney-effect enhanced flow channels integrated with heat pipe bundle arrays, thereby establishing efficient heat conduction pathways from the Phenolic Resin Substrate (PRS) to the structural periphery. Micro-Element Texture (MET) arrays are fabricated at the PRS thermal interface to enhance interfacial thermal conductance. Based on multi-physics coupled numerical simulation, a parametric mapping model correlating geometric topology with thermal performance is established through response interface methodology, enabling the parametric optimization of micro-texture configurations. A thermal interface performance testing platform is constructed to validate the accuracy and reliability of the numerical model. Experimental results demonstrate that the integrated heat pipe technology effectively suppresses LED junction temperature rise; moreover, groove-type MET arrays oriented perpendicular to the gravity direction not only significantly increase the effective heat dissipation area but also optimize the dynamic characteristics of natural convection. This proposed solution reduces the maximum operating temperature of deep-sea FALs by 6.70% compared with conventional structures, providing an effective engineering solution for thermal structural design of high-power illumination systems. Full article

This study investigates the coupling between flow dynamics, acoustic response, and convective heat transfer in a rectangular impinging jet striking on a heated slotted plate at two closely spaced Reynolds numbers (Re = 3550 and Re = 3750). Velocity fields were obtained using Particle Image Velocimetry (PIV), and coherent structures were analyzed using Proper Orthogonal Decomposition (POD) while acoustic measurements were used to characterize the tonal behavior. Infrared thermography was employed to determine local and mean Stanton numbers. The mean Stanton number increased by 6.6% when the Reynolds number increased from Re = 3550 to Re = 3750, while the sound pressure level decreased from 78 dB to 71 dB. At Re = 3550, the acoustic spectrum exhibited multi-tone behavior associated with distributed modal energy. In contrast, at Re = 3750, a single dominant frequency governed the flow dynamics. The energy of the first POD mode nearly doubled when passing from Re = 3550 to Re = 3750. The cross-correlation coefficients between the first POD mode and the acoustic field increase from 0.76 to 0.93 when changing from Re = 3550 to Re = 3750. These findings show that the dominant vortex mode which contains nearly 20% of the fluctuating energy (for Re = 3750), significant influences the energy transfer from the dynamic field to the acoustic field resulting in a strong noise reduction. Simultaneously, convective heat transfer increases, highlighting the key role of coherent flow organization on both acoustic and thermal behavior of the system. Full article

Mass transfer is central to food processing but remains difficult to quantify because food materials are heterogeneous, multiphase, porous, biologically structured, and dynamically changing. Under these conditions, experiments alone cannot fully capture the spatiotemporal complexity of transport behavior, making modeling and simulation essential for mechanism interpretation, process prediction, and engineering optimization. Existing reviews mainly address specific operations or numerical methods, with limited synthesis of governing equations, simulation workflows, application implementation, and practical applicability. This review examines food mass transfer by linking coupled momentum, heat, and mass transfer laws with governing equation selection, simulation workflow, and representative food processing applications. Governing formulations for Fickian diffusion, conservation-based transport, heat–mass coupling, multicomponent transfer, Darcy-type porous-medium flow, and related model extensions are summarized, together with their assumptions, geometric applicability, and dimensionless criteria. A unified simulation workflow is then organized, covering transport type identification, governing equation and physical model selection, geometric representation, parameter determination, initial and boundary condition specifications, numerical method and simulation tool selection, numerical implementation, validation, and transferability assessment. Representative applications are discussed for drying, heat–mass coupled processes, multicomponent transfer, transport in porous foods, and redistribution in multi-ingredient or multilayer foods. Overall, future progress requires more integrated, structure-aware, experimentally validated, transferable, and application-oriented simulation frameworks. Full article

This study focuses on a 155 mm 32CrNi3MoV steel barrel and presents a thermochemically coupled phase transformation and diffusion dynamics model. The model leverages the significant disparity between radial and axial temperature gradients to simplify the heat conduction problem to a one-dimensional transient formulation. The temperature field distribution during firing sequences is solved analytically, accounting for the dynamic shift in critical phase transformation temperatures under high heating rates. The evolution of the martensitic layer thickness under repeated thermal shock is subsequently calculated. A numerical model for the pulsed diffusion of C and N is established based on Fick’s second law, incorporating the competitive diffusion–phase transformation mechanisms that govern martensite/austenite interface migration. To quantitatively evaluate the synergistic contribution of C and N to austenite stabilization, a carbon equivalent (Ceq) model is introduced, with the weight coefficient of N relative to C determined to be 0.68 and the critical Ceq required to lower the martensite start temperature below 25 °C calculated as 1.15 wt%. Concurrently, the microstructure and elemental distribution within the austenite layer of the retired barrel are systematically characterized using multi-scale techniques. The results indicate that the austenite layer on the inner bore surface arises from the synergistic effects of cyclic thermal-shock-induced phase transformation and elemental diffusion. Based on the Ceq criterion, the austenite layer thickness increases rapidly during the initial ~100 firing cycles, after which the growth rate slows significantly: it reaches approximately 1.27 μm after the first cycle and 2.94 μm after 1000 cycles, with only 0.2 μm of additional thickening between 100 and 1000 cycles—consistent with the experimentally observed range of 1.52–4.16 μm. The martensitic layer formed during the first firing cycle exhibits low thermal conductivity, which impedes subsequent heat transfer and leads to stabilization of its thickness at a characteristic depth. Grain refinement induced by repeated thermal shock provide short-circuit diffusion paths for elemental diffusion, accelerating compositional homogenization within the austenite layer and resulting in a stepped concentration profile at the interface. This study provides a representative example of non-equilibrium coupled phase transformation–diffusion phenomena under extreme transient loading. The established thickness prediction model can provide guidance for service life assessment of large-caliber barrels, offering both theoretical foundations and practical engineering guidance for their material design and performance optimization. Full article

Direct air capture (DAC) based on adsorption is a promising negative-emission technology owing to its operational flexibility, modular deployment potential, and comparatively low regeneration temperature. In this study, a dynamic three-dimensional mathematical model was developed to investigate a structured adsorption-based DAC reactor operating under a temperature–vacuum swing adsorption cycle. The model couples heat and mass transfer among the gas, adsorbent, metal structure, and heat-transfer fluid and was used to evaluate the temporal and spatial evolution of temperature and CO₂ adsorption capacity during adsorption and regeneration. The effects of internal cooling, heat-source temperature, and vacuum pressure on cyclic performance were systematically analyzed. The results show that introducing an internal cooling source significantly accelerates adsorbent-bed cooling and increases the cyclic working capacity by approximately 10%. Parametric simulations indicate that higher regeneration temperature and lower vacuum pressure enhance CO₂ desorption, with optimal performance achieved at a heat-source temperature of 90 °C and a vacuum pressure of 1 kPa. Under these conditions, the DAC system reaches an annual CO₂ productivity of 125 tCO₂·year⁻¹, with mechanical and thermal energy consumptions of 4.72 and 11.91 GJ·tCO₂⁻¹, respectively. This work provides a useful modeling framework for reactor design and operating-parameter optimization in adsorption-based DAC systems. Full article

Higher turbine inlet temperatures improve cycle efficiency but intensify blade thermal loading, so internal passages rely on turbulators that raise convection within coolant pressure budgets. Streamwise sinusoidal ribs introduce curvature and spanwise phasing beyond straight transverse bars, yet reconciled multi-row thermal–hydraulic data for such layouts in high-aspect-ratio blade-cooling analogues remain scarce. Steady three-dimensional computational fluid dynamics (CFD) of turbulent airflow in a 4:1 rectangular channel with uniform heat flux on one ribbed wall are applied to compare nine parametric sinusoidal-rib layouts and one transverse baseline at bulk Reynolds numbers from 20,000 to 90,000. The normalized Nusselt number ($Nu/N{u}_0$), Fanning friction factor ($f/f_0$), and composite thermal–hydraulic performance indices quantify the trade-off. Several layouts outperform the transverse baseline; a streamwise-increasing rib-height schedule achieves the highest pressure-drop-weighted index, whereas a large-amplitude uniform waviness gives the best heat-transfer-dominated index. The parametric matrix indicates when streamwise waviness merits further study in ribbed passage design. Full article

This study conducted a numerical simulation of laminar flow within a cylindrical pipe using a semi-implicit method. The full Navier–Stokes equations in cylindrical coordinates were solved, with modifications to the SIMPLE algorithm to handle pressure-linked equations. We evaluated three key thermophysical parameters—dynamic viscosity, specific heat capacity, and thermal conductivity—under both constant and variable conditions in the entrance region. Due to the process’s two-dimensional, time-dependent nature, third-kind boundary conditions were used to accurately model the effects of ambient temperature, external wind, and the pipe’s geometric and physical features. From the numerical results, we analyzed the velocity field, pressure distribution, surface friction coefficient, and temperature distribution at various pipe cross-sections. These findings are of practical and scientific importance: they offer insights into the hydrodynamics and thermal behavior of the internal flow and enhance understanding of fluid flow and heat transfer, improving predictive models. This advancement supports better design and operational control in pipeline systems. Full article

This study analyzes and explores the influence of multiple physical mechanisms—namely the influences of heat and mass transfer, thermal radiation, and magnetic field effects on the peristaltic transport of a Rabinowitsch-type non-Newtonian fluid within an inclined channel. To accurately represent the intricate behavior of the fluid under these coupled physical phenomena, a nonlinear model was formulated that integrates thermal, magnetic, and radiative forces into its framework. The given coupled differential equations are transformed into ordinary differential equations (ODEs). Using assumptions of long-wavelength and low-Reynolds-number approximations, the governing equations were significantly simplified. The resulting set of equations was solved analytically using Mathematica, subject to appropriate boundary conditions for velocity, temperature, and concentration. Graphs for velocity, temperature and concentration are illustrated. Thermal radiation was incorporated into the energy equation via the Rosseland approximation, thereby enabling a more accurate characterization of heat transport within the system. Moreover, the rate of heat and mass transfer for different variables was also examined. These findings are essential for the progression of advanced fluid transport systems in biomedical engineering, chemical processing, and energy generation, improving the design and management of non-Newtonian fluid dynamics. Full article

Accurate prediction of fatigue performance in Ni-based superalloys is hindered by scarce data and poor generalization of conventional machine learning. This study proposes a framework combining dynamic ensemble learning with transfer learning. A tensile prediction model using five base regressors (SVR, RFR, DTR, XGB, MLP) on 1025 tensile samples is first built. A dynamic weighted error feedback ensemble algorithm (DWELA) adjusts base model weights in real-time based on validation errors, improving tensile R² from 0.90 (best single model) to 0.95. To transfer knowledge to fatigue prediction, a feature alignment transfer learning (FATL) strategy aligns shared features (composition and heat treatment) between source (tensile) and target (fatigue) domains while fine-tuning domain-specific strain features, adapting effectively to a limited fatigue dataset of 622 samples. The resulting ETFPM model evaluated on five independent samples achieves R² of 0.93 (fatigue stress) and 0.81 (fatigue life), outperforming the best fatigue-trained single model (SVR: R² = 0.89 and 0.72). Twenty candidate alloys are predicted for screening. The method offers a practical route for fatigue prediction under data-limited conditions. The main novelties are: (i) DWELA’s real-time error-driven weight adaptation with hard constraints and early stopping, which improves tensile R² from 0.90 (best single model) to 0.95; and (ii) FATL’s explicit separation of frozen shared features and trainable exclusive features, enabling accurate fatigue prediction (R² = 0.93 for FS, 0.81 for FL) using only 622 fatigue samples. However, the independent validation is limited to five samples, and the datasets are compiled from the literature with potential heterogeneity in testing protocols and imputation bias for missing values. Further experimental validation is required to confirm broader applicability. Full article

A new biomass pyrolyzer, named Biochar Oven, has been developed using flameless combustion technology, which provides uniform high temperature in the pyrolysis reactor. A computational fluid dynamics (CFD) model of flameless combustion was developed to analyze how the fuel inlet depth controls the reaction and heat transfer to a vertical biomass pyrolysis reactor. The combustor was modeled using the k–ε turbulence model, the discrete ordinates radiation model, and species transport with the reaction. The fuel nozzle relative depth ratios (RDR) of chamber height and equivalence ratios (ER) were varied to obtain optimal combustion and heat transfer performance. The internal recirculation ratio (Z) was calculated to evaluate the flameless combustion condition, with maximum values generally found at RDR 0.73 for each ER. Increasing depth strengthens the mixing zone closer to the reactor wall. With an ER of 0.9 and RDR of 0.73, the wall heat flux is up to 16.36 kW m⁻², the average wall reactor temperature is up to 900 °C, and the heat transfer efficiency is up to 59.79%. These flow patterns and chamber–reactor results indicate that deeper nozzle insertions (RDR 0.73) provide better overall performance by improving recirculation intensity, wall heat flux, and heat transfer efficiency with lower CO emissions. Full article

Conventional solar power tower (SPT) systems often suffer from significant heat transfer exergy destruction due to large temperature differences between the heat source and the working fluid during the heat exchange process. To overcome this limitation, a high–low dual-tower configuration based on segmented thermal utilization is proposed. In this arrangement, the high-temperature tower is mainly responsible for the evaporation, superheating, and reheating processes, whereas the low-temperature tower primarily handles feedwater preheating. Such a configuration improves the temperature matching characteristics during the heat exchange process. A comprehensive model integrating the heliostat field, receiver, thermal energy storage system, and power block was developed and validated against Solar Two experimental data, showing good agreement. Comparative analyses were conducted under identical solar resource and operating conditions. The results indicate that the proposed system achieves a comparable power output while reducing total heat transfer exergy destruction by approximately 24%, with a significant reduction of over 80% in the preheating section. Sensitivity analysis further reveals that optimizing the high tower outlet temperature can effectively reduce irreversibility and slightly enhance power output, although constrained by the pinch temperature difference. Dynamic simulations based on typical meteorological year data demonstrate that the system maintains stable operation and improves cycle efficiency. From an economic perspective, the proposed system reduces the levelized cost of electricity (LCOE) by about 6.6% and shortens the dynamic payback period, indicating enhanced long-term competitiveness. Overall, the high and low dual-tower system effectively improves thermodynamic and economic performance, providing a promising approach for high-efficiency concentrating solar power (CSP) development. Full article

Hyperloop transport operates in a low-pressure environment in which convective heat transfer is strongly limited, making conventional air-based cooling ineffective. One promising thermal management approach is therefore to absorb the waste heat generated during travel in a thermal energy storage (TES) system and dissipate it during stops. In this context, latent heat storage based on water–ice systems is particularly attractive because of its high energy density and nearly constant-temperature heat absorption. However, experimental validation of such systems beyond laboratory scale is still lacking. This study therefore investigated a large-scale direct contact latent heat storage (DCLHS) system for Hyperloop thermal management, using water as heat transfer fluid and ice as phase change material. The system was evaluated for two ice morphologies, crushed ice and ice block, under both constant and time-variant cooling power profiles representative of Hyperloop operation. The objective was to assess thermal performance, exergy efficiency, and hydraulic stability at application-relevant scale, and to identify morphology-dependent trade-offs relevant for system integration. The results show that the large-scale system can operate reliably under dynamic loads and that upscaling leads to smoother thermal behavior and reduced boundary effects. Crushed ice demonstrated superior thermal responsiveness, maintaining outlet temperatures close to the phase change temperature and achieving exergy efficiencies up to 0.72 at cooling powers up to 3.8 kW while enabling stable operation at 15 °C. In contrast, the ice block configuration provided higher volumetric energy density but exhibited delayed thermal response and required substantially higher mass flow rates, which limited operation to approximately 25 °C and reduced exergy efficiency to 0.03–0.35. Overall, the results show that large-scale DCLHS is a feasible option for Hyperloop thermal management, while also revealing that system behavior at larger scale is strongly influenced by storage morphology. Full article

This study investigates the mechanical and thermodynamic effects of evaporating ocean spray on the structure and dynamics of a hurricane marine atmospheric boundary layer using Eulerian multifluid and mixture model approaches coupled with the $E-ϵ$ turbulence closure. The multifluid framework treats air and spray as interpenetrating phases, enabling a physically consistent representation of air–droplet interactions governing momentum transfer, enthalpy exchange, and turbulence modulation. The mixture approach is based on a simplified description that captures only part of the underlying physics yet offers an advantage in its ability to yield analytical insight. Mechanically, spray produces competing effects: on one hand, droplet inertia causes wind deceleration, and on the other, spray-induced turbulence attenuation, primarily resulting from the air–droplet friction, leads to strengthening the wind. Analytical and numerical results show that the latter effect prevails for typical spray droplet sizes leading to wind acceleration and drag reduction at hurricane wind speeds. Thermodynamically, evaporating droplets redistribute total heat flux in favor of its latent component, with effects strongly dependent on the droplet size. Small droplets suppress turbulence and reduce the total enthalpy flux, whereas large ones enhance it. Furthermore, spray significantly increases the total enthalpy-to-drag coefficient ratio with wind speed, which agrees with field observations. Full article

Urban green spaces play a critical role in mitigating heat stress and enhancing urban livability, in line with the objectives and expectations of the United Nations Sustainable Development Goals 10 (Reduced Inequalities) and 11 (Sustainable Cities and Communities). This study employs Physarealm (Grasshopper), a lightweight agent-based simulation (ABS) model, to dynamically simulate pedestrian behaviors for different mobility groups. Together with Space Syntax, the results—time-extended movement and interaction patterns—are conceptualized as a relational configuration of green space provision (supply), pedestrian activity intensity (demand), and thermal exposure (environmental resistance). Three contrasting urban areas in northern Italy (Lambrate, Bolognina, and Ispra) are selected as case studies. The results demonstrate that urban inequality cannot be sufficiently explained by the inadequacy of single components, but emerges from imbalanced relational configurations of supply, demand, and environmental resistance. In May, 100% and 95% of traversed cells in Lambrate and Bolognina fall within the high-heat-stress range (>32 °C), compared with 59% in Ispra. Correspondingly, average green provision within the 5 min walking range is 5.4% in Lambrate, 7.2% in Bolognina, and 37% in Ispra. By uncovering relational mismatch patterns that are often overlooked in conventional urban analyses, this study enables a multi-dimensional diagnosis of imbalances. By positioning ABS as a front-end process generator and Space Syntax as a structural interpretation step, it demonstrates how dynamic behavioral processes can be reorganized into network-scale diagnostic representations. The study supports a climate-sensitive and human-centered diagnosis of walkability and green space accessibility, while contributing a transferable analytical approach for identifying relational inequality patterns within open urban data science contexts. Full article

Laser powder bed fusion (LPBF) poses significant simulation challenges due to its highly nonlinear thermo-fluid-solid coupling. To address this, we propose an adaptive framework coupling the edge-based smoothed finite element method (ES-FEM) and smoothed particle hydrodynamics (SPH) via a bidirectional element-particle transformation algorithm. This integration leverages ES-FEM for modeling solid thermo-mechanical responses and SPH for resolving melt pool dynamics, enabling fully coupled simulation of temperature, fluid flow, and stress within a unified model. The framework comprises three key components: a nodal mass normalization scheme ensuring conservation during transformations, a ghost particle algorithm for solid-fluid heat transfer and interaction, and a bidirectional finite-element-to-particle conversion mechanism. This work represents the first implementation of bidirectional coupling between mesh-free Lagrangian SPH and Lagrangian FEM. The validation against benchmark cases confirms the framework’s accuracy in capturing transient thermal, hydrodynamic, and mechanical behavior. It successfully reproduces key LPBF phenomena, including melt pool morphology, Marangoni flows, and residual stress evolution, demonstrating its suitability for high-fidelity LPBF process simulation. It should be noted that the current ES-FEM-SPH framework has not taken into account the recoil pressure, evaporation, and the interaction between the powder and the molten pool. The powder is regarded as a rigid body. Future work will focus on incorporating these neglected physical factors to further improve the predictive capability of the proposed framework. Full article