Search Results (420)

Efficient thermal management is critical for proton exchange membrane fuel cells (PEMFCs). This study develops a bio-inspired active liquid cooling architecture to overcome the limitations of conventional flow channels, where convective heat transfer augmentation significantly increases pressure drop. The proposed configuration adheres to constructal theory and Murray’s law. A three-dimensional conjugate heat transfer model was formulated to evaluate the thermo-hydrodynamic performance against parallel and serpentine flow channels. Under identical conditions, the proposed configuration exhibits superior thermal uniformity and hydrodynamic behavior, alongside minimized parasitic pumping power. At an inlet Reynolds number (Re) of 400, this configuration stabilizes the average bipolar plate temperature at 349.63 K. It reduces the index of uniform temperature (IUT) to 1.49 K, representing a 52.8% thermal uniformity improvement over the parallel flow channel. Furthermore, at an inlet Re of 600, the overall pressure drop is restricted to 68.44 Pa, reducing the single-plate parasitic pumping power to 1.27 × 10⁻⁴ W, which represents reductions of 93.5% and 12.5% relative to the serpentine and parallel flow channels, respectively. This study provides an alternative architectural scheme for the design of active liquid cooling flow channels in PEMFCs. Full article

An adaptive immersed boundary method (IBM) for simulating non-isothermal incompressible flows with convective heat transfer involving a rotating circular cylinder is developed. Both Dirichlet- (isothermal) and Neumann (zero heat flux)-type temperature boundary conditions are implemented. In addition to the discrete momentum forcing and energy forcing adopted to effectively satisfy the prescribed velocity and temperature boundary conditions, a mass source/sink term is introduced into the continuity equation to meet the mass conservation at the immersed boundary. The Navier–Stokes equations are solved using the fractional step method implemented on a staggered Cartesian grid system. Time stepping is performed using a second-order Adams–Bashforth/backward-differentiation method, while spatial derivatives are approximated with a second-order centered scheme. Testing of the flow induced by a rotating disk demonstrates that the spatial accuracy of the presented algorithm is second-order. Furthermore, the proposed method is validated by forced convective flow past a rotating isothermal circular cylinder. Finally, mixed Rayleigh–Bénard convection in a square cavity with an embedded adiabatic rotating circular cylinder is simulated, showing that heat transport can be greatly enhanced by increasing the rotating rate and radius of the cylinder at larger Prandtl numbers in the laminar regime. Full article

A two-dimensional dimensionless model is developed to investigate heat transfer during the melting of a pure phase change material (PCM) confined in a horizontal rectangular cavity. The model describes isothermal solid–liquid phase change in the presence of natural convection and is formulated using the momentum and energy conservation equations. To avoid explicit tracking of the moving solid–liquid interface, an enthalpy–porosity approach is employed, allowing the governing equations to be solved over the entire computational domain on a fixed grid. The finite volume method is used for spatial discretization, and a FORTRAN code based on the SIMPLER algorithm is implemented to simulate the melting process. Fluid motion in the solid region is suppressed through a porosity function linked to the local liquid fraction. After validation, a parametric analysis is performed to evaluate the effects of interpolation schemes, Fourier number, PCM subcooling, and liquid-phase superheating on melting dynamics and thermal energy storage. The results reveal that these parameters significantly influence melting behavior and storage performance. A predictive correlation for the dimensionless liquid volume during gallium melting is also proposed. Full article

Biomass torrefaction represents a highly promising thermochemical pathway for upgrading low-density agricultural residues into high-value solid biofuels. However, optimizing reactor operations requires resolving the conflict between product energy enrichment and mass loss under transient heat transfer limitations. In this work, a transient kinetics-coupled Pareto optimization and techno-economic framework is developed for the torrefaction of rice husk residues (Oryza sativa), with pine wood (Pinus sp.) as a validation reference. The framework connects a transient 1D radial finite-difference heat transfer model in a cylindrical particle to a two-stage sequential chemical kinetics scheme, which was successfully calibrated against experimental thermogravimetric analysis (TGA) data. The physical model outputs (instantaneous species concentrations, temperature profiles, and process thermal demand) are dynamically coupled to an economic module to calculate the Levelized Cost of Torrefaction (LCOT). A grid sweep with Pareto non-dominance filtering is conducted on the active torrefaction design space (using a product quality constraint $Y_{BT}\le 0.96$ to avoid degenerate zero-conversion limits) to identify the Pareto frontier that minimizes LCOT while maximizing the efficiency index ($\eta$). To evaluate the financial and technical stability of the Pareto operating point for rice husk (523 K, 30 min), a global sensitivity and uncertainty analysis (GSA) is executed using 250 Latin Hypercube Sampling (LHS) Monte Carlo simulations coupled with Standardized Regression Coefficients (SRCs). The results show a baseline LCOT of 6.49 USD/GJ for rice husk at its 1 dry t/h pilot Pareto knee point (523 K, 30 min), which is projected to decrease to 4.12 USD/GJ under an industrial-scale techno-economic scenario (50 dry t/h). Under uncertainty, LCOT displays a mean value of $6.486\pm 0.565$ USD/GJ (95% CI: $5.517$–$7.644$ USD/GJ), which is heavily dominated by the raw feedstock acquisition cost ($\beta =0.7430$, $p<0.001$) and CAPEX contingency multiplier ($\beta =0.6129$). The efficiency index exhibited limited variability (mean $91.40\%\pm 0.96\%$, 95% CI: $89.80\%$–$93.26\%$), governed primarily by the particle diameter $d_p$ ($\beta =0.7828$) and secondary convective heat transfer coefficient h ($\beta =-0.5929$, $p<0.001$). This work successfully demonstrates that coupling transient transport phenomena to a techno-economic cash-flow layer provides a physics-informed framework for techno-economic evaluation and scale-up of thermochemical bioreactors. Full article

Wildfire behavior can roughly be described as wind-, fuel-, or topography-driven, but these labels usually rest on expert judgment and post-fire analysis rather than on simple, reusable rules. Here, we build a small, interpretable classifier that predicts the dominant fire behavior driver: fuel-driven (plume/convection dominated), wind-driven, or topography-driven, from basic environmental information. The classifier is built using ERA5 10 m wind and relative humidity, summary elevation metrics, and fuel descriptors for a 14-event dataset of coastal Croatian wildfires. We compare the performance of multinomial logistic regression, random forest, and decision tree-based classifiers, focusing on agreement between their coefficients, feature importances, and splits rather than on formal optimization. All three models converge on a simple common rule set. Relative humidity, mean elevation, and elevation range emerge as the main axes of variation, consistent with basic fire behavior physics and published fire type schemes. Despite the small dataset, the classifier formalizes expert intuition in a transparent way and offers a template for scaling larger datasets, where it could evolve into a quick diagnostic of the dominant spread driver for ongoing fires. Full article

Heat transport in heterogeneous materials can deviate markedly from classical Fourier behavior when microstructural disorder, trapping effects, nonlinear mobility, and long-range temporal correlations interact across multiple spatial and temporal scales. These mechanisms may produce delayed relaxation, persistent thermal footprints, front deformation, and non-classical spreading patterns that are not adequately represented by conventional integer-order diffusion models. In this study, a modeling and simulation framework is developed for anomalous heat transport in heterogeneous media using a two-dimensional time-fractional porous medium equation. The model combines a Caputo fractional time derivative, which represents thermal memory, with nonlinear degenerate porous-medium diffusion, spatially heterogeneous conductivity, localized volumetric heating, and Robin-type convective boundary exchange. A conservative fully discrete numerical scheme is constructed using flux-based finite differences for the heterogeneous nonlinear diffusion operator and an $L1$ approximation for the Caputo derivative. The nonlinear algebraic system at each time level is solved using an under-relaxed Picard frozen-coefficient iteration with non-negativity enforcement and sparse direct solution of the resulting linear systems. The numerical implementation is verified through a manufactured-solution convergence study, and additional analyses are performed to examine computational cost, Picard iteration behavior, coefficient-regularization sensitivity, strong-source effects, heterogeneous conductivity structures, and long-time thermal-footprint persistence. The results show that heterogeneous conductivity mainly redirects heat through preferential pathways and enlarges the spatial footprint while producing negligible changes in global heat content. Stronger fractional memory, represented by smaller fractional order, increases the persistence and spatial reach of moderate heating, whereas larger porous-medium exponents confine heat near the source and preserve higher local peaks. Source amplitude increases the thermal burden and footprint monotonically over the tested range, including strong forcing, without producing an abrupt localization-spreading transition. Boundary exchange remains secondary in the short-time interior-heating regime considered. These findings demonstrate that the proposed two-dimensional time-fractional porous medium framework provides a verified and physically interpretable model for non-Fourier heat transport in heterogeneous materials, where local intensity, global heat retention, and spatial thermal exposure must be assessed jointly. Full article

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 presents a comparative sensitivity analysis of the Hartmann number (Ha) and Brinkman number (Br) on magnetohydrodynamic (MHD) flow in rectangular channels and circular pipes. Normalized sensitivity coefficients quantify the response of key metrics, including velocity, wall shear stress, temperature, and convective heat transfer, with validation against recent experimental and numerical studies. The system equations were solved through a coupled analytical–numerical method coded in Python 3.14; velocity field was solved analytically whereas temperature field was discretized using a finite differences scheme and solved numerically using the Thomas algorithm. The entire code was written by the authors. The results show that Ha predominantly governs hydrodynamics, inducing velocity suppression, flow flattening, and enhanced wall shear stress. Rectangular channels experience stronger Hartmann layer effects, while circular pipes exhibit smoother velocity profiles. Conversely, Br primarily controls thermal behavior, with higher values intensifying internal heat generation and elevating centerline temperature, potentially attenuating the average Nusselt number at high Br levels. Nonlinear Ha–Br interactions define distinct operational regimes, from heat transfer enhancement to thermal degradation. Optimal performance windows are identified: Ha ≈ 8–12 and Br ≈ 0.05–0.3 for channels, and Ha ≈ 10–15 and Br ≈ 0.1–0.4 for pipes, balancing thermal and hydraulic efficiency. Deviations from benchmark studies remain within ±5%, confirming predictive reliability. This work provides practical design guidance for advanced MHD thermal systems and establishes a foundation for future studies on temperature-dependent properties, three-dimensional effects, and complex flow regimes. Full article

The aim of this work was to reveal the differences in the macro- and microphysical characteristics and precipitation mechanisms of tropical precipitation systems (TPSs) in different regions. Based on the GPM satellite observation from 2014 to 2022, global TPSs were identified, and eight high-frequency areas were defined. Subsequently, their horizontal and vertical development, precipitation characteristics, and microphysical vertical structure were systematically analyzed. The results show that the horizontal development scale of TPSs is mostly between 10⁴ and 10⁵ km², with vertical development exceeding 10 km. The convective area fraction (CAF) ranges from 20% to 60%, and TPSs have a higher CAF and lower vertical development over the ocean than over land. Continental TPSs exhibit significantly stronger vertical development and more intense precipitation in convective cores than oceanic TPSs. The stronger vertical development over land is mainly attributed to stronger updrafts associated with topographic lifting, which further enhances ice-phase microphysical processes and increases ice particle size. Meanwhile, the intensified updrafts also lead to higher collision–coalescence efficiency in the liquid layer, and temperature perturbations over land further enhance turbulent collision efficiency. Together, these processes result in stronger precipitation intensity in the convective cores of continental TPSs. Stratiform regions are characterized by weak precipitation dominated by raindrop breakup with small regional differences. These findings clarify the key land–ocean disparities in TPSs and provide critical observational evidence for optimizing cloud microphysical parameterization schemes in numerical models. Full article

Flash-flood and floodplain inundation simulations are highly sensitive to the spatiotemporal variability of convective rainfall, particularly during the initial runoff generation stage. However, coarse-resolution numerical weather prediction (NWP) forcing tends to smooth localized rainfall extremes, limiting its ability to accurately represent hydrological responses in low-relief floodplains. In this study, we couple a diffusion-enhanced radar nowcasting model, Diff_ConvLSTM, with a spatial resolution of 1 km and a temporal resolution of 6 min, to assess the hydrological value of high-resolution rainfall forcing over the middle Yangtze River floodplain. We introduce a monotone piecewise cubic Hermite interpolation scheme to ensure a stable transition from discrete high-frequency rainfall inputs to continuous hydrodynamic integration. Evaluation using a radar dataset from 2023 to 2024 shows that Diff_ConvLSTM better preserves intense convective echoes and rainband structures compared to the baseline ConvLSTM, increasing the Probability of Detection at the 40 dBZ threshold by 65.8%. A forcing-replacement experiment for the flood event on 30 June 2023 demonstrates that AI-based nowcasting rainfall forcing reduces peak-discharge underestimation, improves volumetric consistency, and produces inundation patterns that are closer to the observation-driven reference than those generated by low-resolution forecast forcing, although positive biases in inundation area and water depth persist. An additional event in 2024 confirms that the improvements are primarily reflected in discharge magnitude and flood volume representation, while enhancements in peak timing remain limited. Overall, the results illustrate both the added value and the remaining limitations of AI-enhanced nowcasting for hydrologically informed flood forecasting. Full article

Vento Norte (VNOR; Portuguese for North Wind) is a downslope windstorm that develops over modest terrain in the central region of Rio Grande do Sul (RS), southern Brazil. The regional topography is characterized by an abrupt terrain transition with elevation differences of approximately 400–500 m. This atmospheric flow typically occurs during the cold season and is characterized by strong wind gusts, rapid warming, and drying of the planetary boundary layer (PBL). In this study, the performance of different PBL parameterization schemes in the Weather Research and Forecasting (WRF) model is assessed for simulating a VNOR event that occurred between 19 and 20 August 2021 in Santa Maria (SMA), RS. Five high-resolution numerical simulations were conducted using the Yonsei University (YSU), Asymmetric Convective Model version 2 (ACM2), Mellor–Yamada–Nakanishi–Niino level 2.5 (MYNN2.5), Quasi-Normal Scale Elimination (QNSE), and Three-Dimensional Turbulent Kinetic Energy (3DTKE) PBL schemes. Model results were evaluated against observations from a flux tower providing turbulence measurements, twice-daily radiosoundings, and hourly surface meteorological observations. Statistical metrics indicate that the MYNN2.5 scheme provided the most accurate representation of the nighttime stable boundary layer preceding the VNOR, as well as its onset and subsequent evolution. Although this study analyzes a single VNOR event and the results may be case-dependent, the overall performance of the MYNN2.5 scheme suggests that it is a promising option for the operational forecasting of VNOR events. These findings provide new insights into the ability of different PBL schemes to reproduce the mean boundary-layer structure and turbulence characteristics associated with downslope windstorms over modest terrain, contributing to the understanding of these events. Full article

The vertical distribution of atmospheric water vapor plays a key role in the development of heavy precipitation and convective systems, yet conventional GNSS water vapor tomography remains constrained by uneven ray coverage and insufficient voxel support. To address this limitation, this study developed a three-dimensional GNSS water vapor tomography framework strengthened by weak constraints derived from the FY-4B/GIIRS atmospheric vertical profile product (AVP). Because the AVP provides vertically resolved humidity information, it has the potential to supplement the weakly constrained structure of regional GNSS tomography, particularly in the middle and upper troposphere. To evaluate the effectiveness of this strategy, four comparative experiments were designed under two background fields, with and without AVP weak constraints. The results showed that AVP-induced analysis increments and error reduction were concentrated mainly above 3 km and were more evident under the GFS background. Among the four schemes, Tomo-IV achieved the best overall performance, with relative RMSE of 26.0% for the full altitude range. Positive spatial gains were also observed in the regional ERA5-referenced evaluation under the GFS background. Unlike previous studies that incorporated FY-series satellite data primarily as geometric supplements to the GNSS observation system, the present framework introduces the FY-4B/GIIRS AVP as voxel-level weak constraints without modifying the native GNSS observation geometry, aiming to improve reconstruction stability and vertical moisture structure in the middle and upper troposphere. These results confirm the effectiveness of this strategy. Full article

Langmuir turbulence is a key and common process in the ocean surface boundary layer, playing a major role in vertical mixing, heat flux, and material transport. However, because direct simulation of Langmuir turbulence demands considerable computational resources, parameterizations within established schemes like the K-profile parameterization (KPP) offer a practical alternative for representing its effects in ocean and climate models. However, Langmuir turbulence parameterizations based on KPP may overestimate vertical mixing when convection is significant. To address this, we introduce a dynamic weighting factor, based on characteristic velocity scales, to balance the contributions of convective and Langmuir turbulence. The improved scheme shows a significant enhancement in performance, especially under strong convective conditions. We compare and evaluate the new parameterization schemes against other widely used schemes in three typical scenarios. Additionally, we validate it using large-eddy simulation results and field observation data. Our enhanced mixing scheme is highly competitive and performs robustly under a variety of conditions. Full article

This study investigates unsteady magnetohydrodynamic free convection flow past a rotating vertical plate embedded in a Darcy–Forchheimer porous medium. The formulation incorporates Hall current, thermal radiation, viscous dissipation, Joule heating, and an Arrhenius-type chemical reaction with activation energy to represent thermo-reactive transport in an electrically conducting fluid. The coupled nonlinear equations governing momentum, thermal energy, and species concentration are transformed into dimensionless form and solved numerically using the Crank–Nicolson scheme. Grid independence and validation tests confirm the accuracy and stability of the numerical procedure. The results show that electromagnetic forces, rotation, porous resistance, and thermo-reactive effects significantly influence wall shear stress, heat transfer, and mass transport. In particular, the interaction between magnetic field strength and Hall current alters near-wall transport behavior, highlighting the role of electromagnetic coupling in rotating porous systems. The study provides physical insight relevant to the design and analysis of transport processes in high-temperature energy systems, rotating reactors, and porous thermal management devices. Full article

Detonation phenomena in reactive flow systems continue to pose significant challenges for accurate simulation, particularly in 3D validation against experiments and achieving community standardization for schemes. Among the primary difficulties is the selection of suitable convective schemes, which are essential for capturing the complex dynamics of wave propagation and reaction fronts. This study provides a comprehensive historical review of the development and implementation of convective schemes in OpenFOAM, covering the period from 2013 to the present. In addition to documenting the evolution of these methods, we present a detailed technical description of various convective approximation techniques used in detonation simulations within OpenFOAM. This includes an exploration of their underlying principles, advantages, and limitations. Our analysis synthesizes key findings from recent studies and offers practical guidance to researchers when choosing schemes for specific detonation scenarios. It is found that currently, within OpenFOAM, the dominant schemes for convection are the HLLC and KN. Full article