Search Results (554)

Entropy generation analysis provides a thermodynamic framework for quantifying irreversibility in thermal systems. However, most existing second-law studies rely on simplified boundary conditions and do not consider fully coupled conjugate heat transfer involving fluid convection, wall conduction, and external heat exchange. Consequently, thermodynamic assessments under realistic conditions remain limited. This study presents an entropy generation-based assessment of turbulent conjugate heat transfer in circular pipes by considering the combined effects of wall thickness ratio (0.02–0.08), wall thermal conductivity (0.2–400 W/m·K), and external convection (5–100 W/m²·K). A three-dimensional steady RANS-based conjugate heat transfer model is employed, and entropy generation is evaluated to quantify irreversibility within fluid and solid domains. The results indicate that wall-related thermal resistances significantly affect thermodynamic performance. Variations in wall conductivity lead to approximately 15–20% changes in total irreversibility, while increasing external convection from 5 to 20 W/m²·K results in up to 25–30% variation. Increasing wall thickness enhances conductive entropy generation, whereas higher Reynolds numbers increase overall irreversibility. These findings demonstrate that the Biot number is a key parameter governing irreversibility distribution. The results provide energy-efficient design insights for optimizing thermally coupled engineering systems under realistic operating conditions. Full article

The Eastern Mediterranean, notably Cyprus, is a climate change hotspot facing severe heatwaves. Accurate numerical weather prediction of these extremes requires precise land–atmosphere modeling and initial and boundary conditions. This study assesses replacing the default USGS Land-Use and Land-Cover (LULC) dataset with the 10 m ESA WorldCover 2021 dataset in the Weather Research and Forecasting (WRF) model to simulate the 15–29 July 2023 Cyprus heatwave. The updated LULC increased urban representation six-fold. Statistical validations showed significant improvements in 2 m temperature, relative humidity, and 10 m wind speed predictions across 85% of observational sites. Dynamically, it restored urban thermal memory, effectively capturing the daytime Urban Cool Island effect and nocturnal heat release. Furthermore, radiosonde validations showed that the update corrected nocturnal Planetary Boundary Layer Height (PBLH) underestimations and dampened exaggerated daytime convective mixing. However, crucial limitations remain. High-frequency diagnostics indicated the model still suffers from damped thermal inertia, missing the abrupt temperature spikes and rapid nocturnal cooling typical of semi-arid microclimates. Additionally, the updated configuration failed to capture severe atmospheric stagnation during peak heatwave conditions, highlighting that deep-rooted kinetic errors persist within default boundary layer parameterizations despite static surface improvements. Full article

Effective thermal insulation of cryogenic liquid hydrogen (LH₂) storage tanks remains a critical engineering challenge, as conventional vacuum-based or monolithic systems are constrained by manufacturing complexity, mechanical vulnerability, and poor geometric adaptability. This study presents the design and numerical verification of a four-layer octagonal composite thermal shield fabricated via additive manufacturing: an AA5083 structural layer (5 mm), a boron nitride-doped ceramic plate (1 mm), up to 290 stacked graphene sheets in a sealed compartment, and an outer Fe₃S₄-TiO₂ nanocomposite layer (~30 µm). Steady-state and transient FEA in ANSYS evaluated three convective boundary conditions (h = 10, 15, and 20 W/m²·K), with the inner wall fixed at 20 K. Temperature distributions remained essentially invariant across all cases (20 K inner, ~20.12 K outer), confirming that thermal performance is governed by the multilayer architecture rather than convective intensity. The shield achieved a mean heat flux of 1684 W/m², R_total ≈ 0.163 m²K/W, and a boil-off rate of 13.9 g/hour. Comparative FEA against NASA US9617069 (q = 193.35 W/m²) and JP2018-119634A (q = 37.975 W/m²) highlights the compactness advantage of the proposed 6 mm shield; the coupled thermo-structural assessment yielded a safety factor of 64,182, confirming elastic-regime operation at 20 K. Full article

Geothermal energy extraction, hydrocarbon recovery, and CO₂ geological sequestration are frequently hindered by interfacial barriers and slow mass transfer. While high-power ultrasound offers a sustainable, purely physical method for reservoir stimulation, its field effectiveness remains debated because traditional macroscopic experiments fail to isolate mechanisms like acoustic streaming and cavitation. This review systematically examines acoustic mechanisms in porous media via microfluidic visualization, focusing on pore-scale fluid dynamics during enhanced oil recovery, hydrate dissociation, and CO₂ sequestration. Microscopic evidence reveals that fluid transport mechanisms depend heavily on pore geometry and local acoustic intensity. In wider channels, nonlinear acoustic flow provides sustained, directed convection to strip away concentration boundary layers; in narrow throats, microjets and pulsed stresses generated by transient cavitation are responsible for physically breaking capillary barriers. The spatiotemporal synergy of these mechanisms is critical for multiphase fluid transport in tight porous networks. Pore geometry serves not only as the application context but also as a core physical variable. To translate microfluidic results into reservoir-scale applications, future research must address two-dimensional simplifications, thermodynamic discrepancies under high-temperature and high-pressure conditions, and bubble cluster interactions, alongside the development of adaptive frequency-modulated control and multiscale computational models. Full article

Sweeping jet (SWJ) actuators are widely used in active flow control, but explicitly resolving actuator-scale unsteadiness in full-configuration computational fluid dynamics (CFD) remains prohibitively expensive because of the small geometric scales and high-frequency oscillations involved. Existing reduced-order boundary-condition models constructed from exit-plane data alone can reproduce the observed switching waveform, but they treat the actuator as an input–output black box and provide limited insight into the internal dynamics that generate the response. This work develops a causal state-space reduced-order modeling framework that links internal mixing-chamber dynamics to time-resolved exit-plane boundary conditions. Proper orthogonal decomposition (POD) is used to obtain a low-dimensional representation of the internal flow, and a data-driven linear evolution operator is identified in the reduced space by least-squares regression of successive snapshot pairs. A POD truncation rank of $r=60$ is selected from cumulative-energy and validation-error sensitivity analyses, capturing well above 99% of the fluctuation energy while lying within the converged performance regime. A corresponding reduced operator is identified for the exit plane, and spectral comparison reveals near-neutrally stable oscillatory modes in both regions. Using a $\pm 1\%$ relative frequency-matching tolerance, the dominant reduced-operator modes exhibit a 28.3% frequency overlap, providing operator-level evidence that exit-plane oscillations are dynamically linked to internal coherent structures. This correspondence is further supported by cross-spectral coherence analysis between representative internal and exit-plane probe signals, which shows strong coherence at dynamically relevant frequencies. A delayed causal output mapping is then formulated in which the internal reduced state drives the exit-plane response after an identified lag of 149 time steps, corresponding to $2.98\times {10}^{-3}$ s. This delay provides a physically interpretable convective transport timescale from the mixing chamber to the actuator exit. Over the validation interval, the model maintains a mean relative $L_2$ error below 0.02, with maximum normalized errors below 0.04 for most of the prediction horizon, and localized increases are confined to rapid jet-switching events. Field-level reconstructions of streamwise velocity and total pressure show that the model captures both phases of the jet-switching cycle, with errors concentrated primarily in high-gradient shear-layer regions. Compared with exit-only reduced-order models, the proposed internal-driven formulation improves amplitude and phase fidelity over extended prediction horizons. The resulting framework provides a compact, interpretable, operator-based representation of SWJ actuator dynamics suitable for use as a CFD-embeddable dynamic boundary condition. Full article

Significance: This study addresses critical industrial and biomedical applications including glass blowing (thermal management of shrinking sheets), polymer sheet extrusion (controlled cooling), magnetic drug delivery (nanoparticle targeting), and nuclear reactor cooling (enhanced heat transfer). Aim: We present a novel nonlinear analysis of magnetohydrodynamic (MHD) boundary layer flow of a Jeffery Al₂O₃ nanofluid over a shrinking permeable plate with convective boundary conditions, uniquely integrating mixed convection, Ohmic dissipation, heat generation, Brownian motion, and thermophoresis within a non-Newtonian nanofluid framework. Methodology: The governing partial differential equations are transformed using similarity transformations and solved via the Adomian decomposition method (ADM). Comprehensive validation against RK4, RK45, and bvp4c demonstrates excellent agreement with maximum relative errors below $5\times {10}^{-4}$. Key Contribution: (i) Normal velocity decreases by 15–25% as the Biot number increases from $Bi=0.4$ to $0.6$; (ii) tangential velocity decreases by 20–30% as the magnetic parameter increases from $M=5$ to 15; (iii) temperature increases by 30–40% as the Eckert number increases from $Ec=0.5$ to $2.5$; (iv) ADM converges within 12–15 terms with $L_2$ errors $<{10}^{-5}$; (v) skin friction coefficient increases from $C_f=3.02713$ to $3.90082$ as $Q_0$ increases from 1 to 4; (vi) Nusselt number values: $Nu/\sqrt{Re}=0.4621$ at $Pr=0.7$, $0.8954$ at $Pr=2$, $3.2890$ at $Pr=20$. These quantitative findings provide design guidelines for engineers in thermal management and biomedical applications. Full article

In order to design suitable heat-dissipating clothing for people engaged in high-temperature conditions, the vapor-dominated moisture transfer and heat dissipation properties of polyester fabric (Coolmax) with irregular cross-section in sweat-wicking protective clothing were analyzed by establishing a three-dimensional thermal–moisture coupled numerical model. In this study, moisture transport was mainly considered as water vapor transport within the porous fabric domain under a prescribed vapor-input boundary condition, rather than as a complete liquid-sweat-wicking, condensation, and re-evaporation process. The effects of convective heat transfer coefficient, ambient temperature, fabric thickness, and porosity on the thermal and moisture regulation behavior of the fabric were analyzed. The results show that Coolmax fabric can realize more efficient vapor transfer and heat diffusion under different ambient conditions due to its irregular grooved fiber structure, and its skin-side temperature is lower, and the relative-humidity distribution is more uniform than that of cotton material. Through the comparative analysis of temperature and relative humidity under different parameter combinations, the reasonable structural parameter range considering heat dissipation efficiency and perspiration ability is determined as follows: a fabric thickness of 0.8–1.2 mm and a porosity of 0.70–0.80, which can effectively improve the heat and moisture regulation performance of fabrics. This study provides a theoretical basis and numerical simulation reference for material selection and structure design of sweat-protective clothing and functional sportswear, which is helpful to improve wearing comfort and reduce thermal stress. Full article

The underwater explosion bubble is one of the primary loads generated by underwater explosive detonations, and the presence of complex detonation products results in its unique physical evolution characteristics. Based on classical bubble dynamics theory, this paper introduces the JWL equation of state for explosives and the instantaneous detonation assumption to determine the initial boundary conditions of the explosion bubble, establishing a second-order analytical model. Addressing the mass loss during bubble pulsation, the physical mechanisms of convective mass transfer in the boundary layer and the inertial scattering of insoluble elements are analyzed. Accordingly, a modified dynamic model incorporating mass loss is established. The accuracy and reliability of the proposed model are verified through comparison with experimental data from underwater explosions. The results indicate that the inertial scattering of insoluble elements is the dominant mechanism governing bubble mass loss, while the macroscopic effects of the mass loss of detonation products primarily manifest during the secondary pressure pulsation and subsequent evolution stages. This study provides reliable theoretical predictions within the primary pulsation cycles of explosion bubble pulsation characteristics, providing theoretical support for further elucidating the underlying mechanisms of underwater explosion bubble dynamics. Full article

This study numerically investigates the aerodynamic and thermal interactions between a full-scale metro train and the surrounding airflow within a confined tunnel environment using steady-state Reynolds-averaged Navier–Stokes (RANS) simulations. The six-car train, with a total length of 108 m and a cross-sectional area of 5.97 m², operates in a tunnel with a 9.83 square meter cross-section, resulting in a high blockage ratio of approximately 60 percent. The Shear Stress Transport (SST) k–ω turbulence model and a high-resolution finite-volume mesh comprising over 8.5 million elements were employed to capture detailed near-wall phenomena. Six representative motion scenarios were analyzed, including early acceleration, peak cruising, and deceleration phases, with realistic thermal boundary conditions applied by assigning the tunnel air temperature as 29.2 °C and the train surface temperature as 35.0 °C. Velocity, pressure, temperature, and turbulence kinetic energy distributions were extracted from both longitudinal and cross-sectional planes. In addition to visual contour assessments, pointwise and spatially averaged field data were examined to quantify the development of airflow structures, pressure distribution, and thermal behavior. The results reveal speed-dependent aerodynamic resistance, pronounced recirculation and stagnation zones around the train nose and tail, and variations in convective heat transfer rates that evolve with train velocity. These findings provide insights into tunnel ventilation design and thermal management for underground metro operations, representing a novel integration of full-scale computational fluid dynamics (CFD) with thermal characterization under realistic conditions. Full article

We develop a high-order space-time spectral method for nonlinear convection–diffusion equations with a Riemann–Liouville time-fractional derivative and a spectrally defined space-fractional Laplacian. The spatial discretization uses a Fourier spectral method that diagonalizes the fractional Laplacian under periodic boundary conditions. The temporal discretization employs a Petrov–Galerkin method based on generalized Jacobi functions which capture the initial singularity exactly. The nonlinear convection term is treated pseudo-spectrally, and the resulting algebraic system is solved with a damped Newton iteration. Rigorous error analysis proves exponential convergence in both space and time. Numerical experiments for various fractional orders confirm the spectral accuracy. Simulations of the fractional Burgers equation demonstrate that increasing the viscosity enhances diffusion and stabilizes the solution, while a nonlinear coefficient that significantly exceeds the viscosity leads to error growth over long time intervals. The method provides an efficient and accurate tool for simulating anomalous transport phenomena. Full article

Nanofluids, which are suspensions of nanoparticles within base fluids, are employed in industries such as electronics, automotives, nuclear power, and defense to enhance thermal management, mass transfer, and microchip cooling. This study investigates heat transfer generation on a stretching sheet incorporating aluminum oxide ${(\mathrm{A}\mathrm{l}}_2{\mathrm{O}}_3)$ and magnetite ${(\mathrm{F}\mathrm{e}}_3{\mathrm{O}}_4)$ nanoparticles under conditions of constant and varying wall temperatures. Key factors considered include variable viscosity, a periodic magnetic field, and thermal radiative flux, underscoring the thermal advantages of nanoparticles in nuclear reactor applications. The Crank–Nicolson method, an implicit finite difference technique, was utilized to solve the mathematical model, with partial differential equations discretized and approximated using an explicit method. An explicit iterative method was employed to solve the momentum and energy equations in a Python solver, while boundary values were analytically resolved based on discretized equations. In the explicit method, values at the subsequent time step (n + 1) were directly computed from the current time step (n) values. This approach necessitated a sufficiently small time step to satisfy the Courant–Friedrichs–Lewy (CFL) condition for numerical stability. The study examined the mass and heat transfer characteristics of a magnetizable nanofluid. While nanoparticles enhanced heat transfer, magnetic interactions, viscosity, and thermal radiation impeded it. A periodic magnetic field was applied perpendicularly to the plates with a constant pressure gradient, utilizing a magnetic phase angle to decelerate and control flow and heat convection modulation. 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

Radar echo extrapolation under severe convective conditions remains challenging because efficient prediction models still tend to suffer from strong-echo attenuation, boundary blurring, and performance degradation at longer lead times. To address these issues, this study proposes SMG-Net, a SimVP-based radar echo extrapolation model with a collaborative multistage design. The proposed framework integrates multiscale spatial enhancement, trend–disturbance differentiated temporal modeling, and gated hierarchical feature fusion to improve structural preservation and temporal stability. Experiments on a regional radar dataset show that SMG-Net achieves the lowest MSE (0.032) and the highest SSIM (0.830) among the compared models. At the 30 dBZ threshold, CSI, POD, and FAR reach 0.042, 0.045, and 0.250, respectively, indicating improved strong-echo detectability and reduced false alarms. The results further show that SMG-Net is particularly effective in preserving the morphology, boundary structure, and intensity distribution of medium- and strong-echo regions at longer lead times, while introducing only limited additional computational cost over the baseline SimVP. These findings indicate that SMG-Net improves the preservation of medium- and strong-echo structures in efficient radar echo extrapolation and has practical value for short-term precipitation nowcasting in severe convective scenarios. Full article

The present work examines a severe, long-lived bow echo in South China during 12–13 April 2016 and investigates the favorable factors for its strength and longevity using a series of 20 cloud-resolving ensemble experiments. Analysis of observational data indicated that this system developed near a surface front under unstable and favorable conditions with dynamic uplifting by approaching troughs at 500–700 hPa. After formation, it propagated rapidly toward the east–southeast across South China and made landfall in Southern Taiwan. The ensemble used four different datasets as initial and boundary conditions and started at five different initial times, whereby comparing the better-performing members with worse ones, four key factors promoting its strength and longevity were identified: (1) A stronger and moister low-level southwesterly flow to the south of the front to enhance convergence and moisture flux at the leading edge—where a stronger inflow with higher equivalent potential temperature (θ_e) values could feed into the bow echo—leading to a stronger and taller updraft and overall more abundant hydrometeors and rainfall; (2) stronger northwesterly to westerly winds near 700 hPa and thus stronger low-level vertical wind shear, resulting in a stronger rear inflow jet (RIJ), bookend vortices behind the bow apex, and, eventually, a faster propagation speed; (3) a deeper low to the northeast of the bow echo near 850 hPa, where its circulation also helped to bring in low-θ_e air from farther away and enhance the RIJ and cold pool; and (4) a convective initiation location farther to the east in a more favorable environment, with higher θ_e and a faster speed to remain in such a better environment. Helped by the above factors, the bow echo in the present case could reach the observed severity and long duration (~15 h) through interactions and reinforcement among its structural components, including the tilted updraft/downdraft, the low-level inflow and stratiform region, the RIJ and bookend vortices, and the cold pool and gust front. Full article

This paper describes the thermal and energy performance of three roof configurations: a conventional concrete slab, a BIPV system, and a BIPV system equipped with passive aluminum fins. Three-dimensional transient finite element simulations were carried out under field-measured 24 h meteorological boundary conditions characteristic of hot climates. The objective of this study is to quantify the impact of PV integration and passive cooling strategies on heat transfer behavior and building energy performance. The BIPV roof achieved a 38.4% lower residual temperature than the concrete slab at 19:00, indicating superior heat dissipation. The addition of passive fins reduced module temperature by up to 10–12 °C and decreased peak roof temperature by up to 12%. This temperature reduction decreased electrical losses from 13.2% to 10.4%, resulting in a 21% relative reduction in temperature-induced losses. The predicted temperature ranges (≈60–75 °C under peak conditions) are consistent with values reported in experimental and numerical studies of BIPV systems in hot climates, supporting the physical realism of the model. Convective heat transfer was represented using effective coefficients, providing a computationally efficient engineering approximation of air-side heat exchange. Despite construction cost increases of up to 38%, PV integration achieved competitive payback periods of approximately 8.5–9 months under hot climate conditions. This economic assessment is based on a simple payback approach using an incremental cost formulation, where the photovoltaic system replaces the conventional concrete roof, reducing the effective investment. This study introduces a reproducible 3D transient FEM methodology for evaluating BIPV roofs under field-measured climatic boundary conditions. The framework explicitly couples geometry-resolved passive cooling, full-day thermal evolution, and temperature-dependent electrical losses, providing a physically consistent basis for assessing BIPV design alternatives in hot climates. Full article