Search Results (97)

A series of multi-parameter, multi-layer observations was conducted to study possible electromagnetic precursors associated with the M 6.7 earthquake that struck Iburi, Hokkaido, Japan, at 18:07:59 UT on 5 September 2018. The most significant observation is seismogenic lower-ionospheric perturbations in the propagation anomalies of sub-ionospheric VLF/LF signals recorded in Japan and Russia. Other substantial observations include the GIM-TEC irregularities, the intensification of stratospheric atmospheric gravity waves (AGWs), and the satellite and ground monitoring of air temperature (T), relative humidity (RH), atmospheric chemical potential (ACP), and surface latent heat flux (SLHF). We have found that there were very remarkable VLF/LF anomalies indicative of lower-ionospheric perturbations observed on 4 and 5 September just before the EQ date and even after it from the observations in Japan and Russia. In particular, the anomaly was detected for a particular propagation path from the JJY transmitter (Fukushima) to a VLF station at Wakkanai one day before the EQ, i.e., on 4 September, and is objectively confirmed by machine/deep learning analysis. An anomaly in TEC occurred only on 5 September, but it is unclear whether it is related to a pre-EQ effect or a minor geomagnetic storm. We attempted to determine whether any seismo-related atmospheric gravity wave (AGW) activity occurred in the stratosphere. Although numerous anomalies were detected, they are most likely associated with convective weather phenomena, including a typhoon. Finally, the Earth’s surface parameters based on satellite monitoring seem to indicate some anomalies from 29 August to 3, 4, and 5 September, a few days prior to EQ data, but the ground-based observation close to the EQ epicenter has indicated a clear T/RH and ACP on 2 September with fair weather, but no significant data on subsequent days because of severe meteorological activities. By integrating multi-layer observations, the LAIC (lithosphere–atmosphere–ionosphere coupling) process for the Hokkaido earthquake appears to follow a slow diffusion-type channel, where ionospheric perturbations arise a few days after ground thermal anomalies. This study also provides integrated evidence linking concurrent lower-ionospheric, atmospheric, and surface thermal anomalies, emphasizing the diagnostic value of such multi-parameter observations in understanding EQ-associated precursor signatures. Full article

Effective metabolic waste clearance and maintaining ionic homeostasis are essential for the health and normal function of the central nervous system (CNS). To understand its mechanism and the role of fluid flow, we develop a multidomain electro-osmotic model of optic-nerve microcirculation (as a part of the CNS) that couples hydrostatic and osmotic fluid transport with electro-diffusive solute movement across axons, glia, the extracellular space (ECS), and arterial/venous/capillary perivascular spaces (PVS). Cerebrospinal fluid enters the optic nerve via the arterial parivascular space (PVS-A) and passes both the glial and ECS before exiting through the venous parivascular space (PVS-V). Exchanges across astrocytic endfeet are essential and they occur in two distinct and coupled paths: through AQP4 on glial membranes and gaps between glial endfeet, thus establishing a mechanistic substrate for two modes of glymphatic transport, at rest and during stimulus-evoked perturbations. Parameter sweeps show that lowering AQP4-mediated fluid permeability or PVS permeability elevates pressure, suppresses radial exchange (due mainly to hydrostatic pressure difference at the lateral surface and the center of the optic nerve), and slows clearance, effects most pronounced for solutes reliant on PVS–V export. The model reproduces baseline and stimulus-evoked flow and demonstrates that PVS-mediated export is the primary clearance route for both small and moderate solutes. Small molecules (e.g., A$\beta$) clear faster because rapid ECS diffusion broadens their distribution and enhances ECS–PVS exchange, whereas moderate species (e.g., tau monomers/oligomers) have low ECS diffusivity, depend on trans-endfoot transfer, and clear more slowly via PVS–V convection. Our framework can also be used to explain the sleep–wake effect mechanistically: enlarging ECS volume (as occurs in sleep) or permeability increases trans-interface flux and accelerates waste removal. Together, these results provide a unified physical picture of glymphatic transport in the optic nerve, yield testable predictions for how AQP4 function, PVS patency, and sleep modulate size-dependent clearance, and offer guidance for targeting impaired waste removal in neurological disease. Full article

A multiscale 3D CFD model of CO₂ methanation over Ni/Al₂O₃ was developed in COMSOL Multiphysics 6.3 for a lab-scale isothermal fixed-bed Sabatier reactor and validated against published data. The multiscale approach integrated bulk convection–diffusion, fluid flow, and pressure distribution with intraparticle diffusion–reaction phenomena coupled with Langmuir–Hinshelwood–Hougen–Watson-based kinetics, thus solving mass-transfer limitations without empirical effectiveness factors. Model validation was carried out by (i) kinetics, (ii) reactor performance, and (iii) hydrodynamics. Simulation results showed strong diffusion-dominated species transport at the bed entrance that lessened downstream as partial pressures decreased and products accumulated, resulting in a diffusion-relieved regime near the outlet. Sensitivity studies identified 320–350 °C and up to 10 bar as favorable conditions for high CH₄ yield. Additionally, slightly H₂-rich feed accelerated approach to equilibrium, while lower flow rates achieved near-complete conversion within the first half of the reactor bed. Simulations were carried out in COMSOL Multiphysics 6.3 on a dual Intel Xeon Platinum 8168 (48 cores at 2.7 GHz) workstation with 512 GB RAM to solve a 12-million-element mesh. The developed framework identifies a practical operating window and quantifies the conversion–throughput trade-off with flow rate, guiding operating condition selection and providing a basis for process intensification and lab-to-pilot scale-up of CO₂ methanation. Full article

We perform large-eddy simulations (LESs) with realistic radiation, including topographic shading, and an advanced land surface model to investigate drainage flow dynamics in an idealized compound-slope mountain geometry. This allows an analysis not only of fully developed profiles in steady state—the subject of existing analytical solutions—but also of transient two- and three-dimensional dynamics. The evening onset of downslope flow is related to the duration of shadow front propagation along the eastern slopes, for which an analytic form is derived. We demonstrate that the flow response to this radiation pattern is mediated by the thermal inertia of the land through sensitivity to soil moisture. Onset timing differences on opposite sides of the peak are explained by convective structures that persist after sunset over the western slopes when topographic shading is considered. Although these preceding convective systems, as well as the presence of neighboring terrain, inhibit the initial development of drainage flows, the LES develops an approximately steady-state, fully developed flow over the finite slopes and finite nocturnal period. This allows a comparison to analytical models restricted to such cases. New analytical solutions based on surface heat flux boundary conditions, which can be estimated by the coupled land surface model, suggest the need for improved representation of the eddy diffusivity for analytical models of drainage flows. Full article

During electron beam cold hearth melting (EBCHM) of Ti-6wt%Al-4wt%V titanium alloy, aluminum volatilization causes compositional segregation in the ingot, significantly degrading material performance. Traditional methods (e.g., the Langmuir equation) struggle to accurately predict aluminum diffusion and compensation behaviors, while computational fluid dynamics (CFD), although capable of resolving multiphysics fields in the molten pool, suffer from high computational costs and insufficient research on segregation control. To address these issues, this study proposes a CFD-machine learning (backpropagation neural network, CFD-ML(BP)) approach to achieve precise prediction and optimization of aluminum segregation. First, CFD simulations are performed to obtain the molten pool’s temperature field, flow field, and aluminum concentration distribution, with model reliability validated experimentally. Subsequently, a BP neural network is trained using large-scale CFD datasets to establish an aluminum concentration prediction model, capturing the nonlinear relationships between process parameters (e.g., casting speed, temperature) and compositional segregation. Finally, optimization algorithms are applied to determine optimal process parameters, which are validated via CFD multiphysics coupling simulations. The results demonstrate that this method predicts the average aluminum concentration in the ingot with an error of ≤3%, significantly reducing computational costs. It also elucidates the kinetic mechanisms of aluminum volatilization and diffusion, revealing that non-monotonic segregation trends arise from the dynamic balance of volatilization, diffusion, convection, and solidification. Moreover, the most uniform aluminum distribution (average 6.8 wt.%, R² = 0.002) is achieved in a double-overflow mold at a casting speed of 18 mm/min and a temperature of 2168 K. Full article

The numerical simulation of unsteady, high-Reynolds-number incompressible flows governed by the Navier–Stokes (NS) equations presents significant challenges in computational fluid dynamics, primarily concerning numerical stability and computational efficiency. Standard Galerkin finite element methods often suffer from non-physical oscillations in convection-dominated regimes, while the multiscale nature of these flows demands prohibitively high computational resources for uniformly refined meshes. This paper proposes an improved Galerkin framework that synergistically integrates a Variational Multiscale Stabilization (VMS) method with an adaptive mesh refinement (AMR) strategy to overcome these dual challenges. Based on the Ritz–Galerkin formulation with the stable Taylor–Hood ($P_2-P_1$) element, a VMS term is introduced, derived from a generalized $\theta$-scheme. This explicitly constructs a subgrid-scale model to effectively suppress numerical oscillations without introducing excessive artificial diffusion. To enhance computational efficiency, a novel a posteriori error estimator is developed based on dual residuals. This estimator provides the robust and accurate localization of numerical errors by dynamically weighting the momentum and continuity residuals within each element, as well as the flux jumps across element boundaries. This error indicator guides an AMR algorithm that combines longest-edge bisection with local Delaunay re-triangulation, ensuring optimal mesh adaptation to complex flow features such as boundary layers and vortices. Furthermore, the stability of the Taylor–Hood element, essential for stable velocity–pressure coupling, is preserved within this integrated framework. Numerical experiments are presented to verify the effectiveness of the proposed method, demonstrating its ability to achieve stable, high-fidelity solutions on adaptively refined grids with a substantial reduction in computational cost. Full article

Semi-annual climate oscillations in the Western Hemisphere (20 S–35 N, 150 W–20 E) were studied via empirical orthogonal function (EOF) eigenvector loading patterns and principal component time scores from 1980 to 2023. The spatial loading maximum for 850 hPa zonal wind extended from the north Atlantic to the east Pacific; channeling was evident over the southwestern Caribbean. The eigenvector loading maximum for precipitation reflected an equatorial trough, while the semi-annual SST formed a dipole with loading maxima in upwelling zones off Angola (10 E) and Peru (80 W). Weakened Caribbean trade winds and strengthened tropical convection correlated with a warm Atlantic/cool Pacific pattern (R = 0.46). Wavelet spectral analysis of principal component time scores found a persistent 6-month rhythm disrupted only by major El Nino Southern Oscillation events and anomalous mid-latitude conditions associated with negative-phase Arctic Oscillation. Historical climatologies revealed that 6-month cycles of wind, precipitation, and sea temperature were tightly coupled in the Western Hemisphere by heat surplus in the equatorial ocean diffused by meridional overturning Hadley cells. External forcing emerged in early 2010 when warm anomalies over Canada diverted the subtropical jet, suppressing subtropical trade winds and evaporative cooling and intensifying the equatorial trough across the Western Hemisphere. Climatic trends of increased jet-stream instability suggest that the semi-annual amplitude may grow over time. Full article

This article is devoted to numerically modeling the effect of the geometric modification of the surfaces of ion-exchange membranes in electromembrane systems (EMSs) on the salt ion transport using a 2D mathematical model of the transport process in the desalination channel based on boundary value problems for the coupled system of Nernst–Planck–Poisson and Navier–Stokes equations. The main patterns of salt ion transport are established taking into account diffusion, electromigration, forced convection, electroconvection, and the geometric modification of the surface of ion-exchange membranes. It is shown that the geometric modification of the surface of ion-exchange membranes significantly changes both the formation and development of electroconvection. A significant combined effect of electroconvection and geometric modification of the surface of ion-exchange membranes in the desalination channel on the salt ion transport is shown, as well as a complex, nonlinear, and non-stationary interaction of all the main effects of concentration polarization in the desalination channel. Full article

This study established a numerical model for ammonia leakage and diffusion in confined ship engine room spaces and validated its effectiveness through existing experiments. The research revealed the evolution patterns of ammonia cloud dispersion under various working conditions. Multi-parameter coupling analysis demonstrated that the combined effect of leakage source location and obstacle distribution alters the spatial configuration of gas clouds. When leakage jets directly impact obstacles, the resulting vortex structures maximize the coverage area of high-concentration ammonia near the ground. Ventilation system efficiency shows a significant negative correlation with hazardous zone volume. The hazardous zone volume was reduced by 50% when employing a bottom dual-side air intake combined with a top symmetric exhaust scheme, compared to the bottom single-side intake with an opposite-side top exhaust configuration. By enhancing the synergistic effect between longitudinal convection and top suction, harmful gas accumulation in lower spaces was effectively controlled. These findings not only provide a theoretical basis for ventilation system design in ammonia-fueled ships but also offer practical applications for risk prevention and control of maritime ammonia leakage. Full article

In the study of underground gas diffusion, traditional methods often emphasize diffusion while neglecting the potential impact of convection. This research constructs a coupled model of diffusion and convection to investigate gas transmission characteristics in complex underground environments. The model is validated and calibrated using field measurement data. The results indicate that the coupled model provides a more accurate representation of gas concentration distribution and diffusion time compared to models that consider only diffusion. Furthermore, this study examines the influence of horizontal well inclination angle on gas diffusion time within the framework of convection–diffusion coupling, revealing its underlying variation patterns. This analysis offers a theoretical foundation for enhancing efficiency and safety in oil and gas production as well as related operations. Under the convection–diffusion coupling mechanism, it is found that the inclination angle of horizontal wells significantly affects gas diffusion time; specifically, larger inclination angles result in shorter durations for gas to diffuse from the bottom to the wellhead. Understanding these variation patterns can facilitate optimization in horizontal well design, rational arrangement of production processes, precise prediction of diffusion times, enhancement of existing safety measures, and provision of forward-looking methodologies and technical support for addressing potential risk events within the oil and gas industry. This has substantial practical implications for engineering applications. Full article

This research investigates the impact of second-order slip conditions, Stefan flow, and convective boundary constraints on the stagnation-point flow of couple stress nanofluids over a solid sphere. The nanofluid density is expressed as a nonlinear function of temperature, while the diffusion-thermo effect, chemical reaction, and thermal radiation are incorporated through linear models. The governing equations are transformed using appropriate non-similar transformations and solved numerically via the finite difference method (FDM). Key physical parameters, including the heat transfer rate, are analyzed in relation to the Dufour number, velocity, and slip parameters using an artificial neural network (ANN) framework. Furthermore, response surface methodology (RSM) is employed to optimize skin friction, heat transfer, and mass transfer by considering the influence of radiation, thermal slip, and chemical reaction rate. Results indicate that velocity slip enhances flow behavior while reducing temperature and concentration distributions. Additionally, an increase in the Dufour number leads to higher temperature profiles, ultimately lowering the overall heat transfer rate. The ANN-based predictive model exhibits high accuracy with minimal errors, offering a robust tool for analyzing and optimizing the thermal and transport characteristics of couple stress nanofluids. Full article

The prevailing fire-resistant design of steel structures typically relies on the premise of localized heating, whereas the overall temperature increase resulting from the dispersion of hot smoke is frequently oversimplified. These theoretical simplifications may result in considerable structural safety risks. This research utilized the Transient Thermo-Mechanical Coupling Theory and developed a double-layer steel frame finite element model using ABAQUS 2023 software. The simulation of multi-physics field coupling involving smoke convection-radiation heat transfer and nonlinear structure response in fire situations was accomplished by establishing 24 sets of comparative conditions over three distinct premises. Upon comparing the conditions with the greatest displacement values across the three situations, it was concluded that when hot smoke is produced in the initial room, it commences diffusion into adjacent rooms both horizontally and vertically. In comparison to the scenario that disregards the dispersion of hot smoke, the displacement of the components escalated by 342.3%. The dispersion of hot smoke reveals that the displacement of components in the center room of the fire’s origin was 23.1% greater than in the corner room, while the displacement in the second-story room was 115.6% greater than in the first-story room. The use of fireproof coating markedly diminished component displacement in the context of hot smoke dispersion, achieving an 82.8% reduction in displacement among components in identical positions. The enhanced vulnerability model augmented the precision of forecasting the ongoing failure of steel frames by 29.1%. Full article

In this study, we sought numerical solutions for three-dimensional coupled Burgers’ equations. Burgers’ equations are fundamental partial differential equations in fluid mechanics. They integrate the characteristics of both the first-order wave equation and the heat conduction equation, serving as crucial tools for modeling the interaction between convection and diffusion. First, the fractional step method was applied to decompose the equations into one-dimensional forms. Then, implicit finite difference approximations were used to solve the resulting one-dimensional equations. To assess the accuracy of the proposed approach, we tested it on two benchmark problems and compared the results with existing methods in the literature. Additionally, the symmetry of the solution graphs was analyzed to gain deeper insight into the results. Stability analysis using the von Neumann method confirmed that the proposed approach is unconditionally stable. The results obtained in this study strongly support the effectiveness and reliability of the proposed method in solving three-dimensional coupled Burgers’ equations. Full article

The two-dimensional semiconductor material MoS₂, grown via chemical vapor deposition, has shown significant potential to surpass silicon in advanced electronic technologies. However, the mass transfer and chemical reaction processes critical to the nucleation and growth of MoS₂ grains remain poorly understood. In this study, we conducted an in-depth investigation into the mass transfer and chemical reaction processes during the chemical vapor deposition of MoS₂, employing a novel multi-physics coupling model that integrates flow fields, temperature fields, mass transfer, and chemical reactions. Our findings reveal that the intermediate product Mo₃O₉S₄ not only fails to participate directly in MoS₂ film growth but also hinders the diffusion of MoS₆, limiting the growth process. We demonstrate that increasing the growth temperature accelerates the diffusion rate of MoS₆, mitigates the adverse effects of Mo₃O₉S₄, and promotes the layered growth of MoS₂ films. Additionally, lowering the growth pressure enhances the convective diffusion of reactants, accelerating grain growth. This research significantly advances our understanding of the mass transport and reaction processes in MoS₂ film growth and provides critical insights for optimizing chemical vapor deposition systems. Full article

The instability of the double-diffusive convection of an Oldroyd-B fluid in a vertical Brinkman porous layer caused by temperature and solute concentration differences with the Soret effect is studied. Based on perturbation theory, an Orr–Sommerfeld eigenvalue problem is derived and numerically solved using the Chebyshev collocation method. The effects of dimensionless parameters on the neutral stability curves and the growth rate curves are examined. It is found that Lewis number Le, Darcy–Prandtl number Pr_D, and normalized porosity η have critical values: When below these thresholds, the parameters promote instability, whereas exceeding them leads to suppression of instability. In addition, for Le < Le_c2 (a critical value of Le), S_r strengthens the instability of the flow, while for Le > Le_c2, S_r suppresses it. These results highlight the complex coupling of heat and mass transfer in Oldroyd-B fluids within porous media. Full article