Search Results (1,540)

In air jet looms, relay nozzles are critical components in governing airflow velocity and air consumption during the weft insertion process. Although computational fluid dynamics (CFD) offers high-fidelity simulation for aerodynamic analysis, its computational burden hinders its practicality in iterative aerodynamic design of relay nozzles. To address the challenge, this study proposes a data-driven framework integrating a Chebyshev polynomial Kolmogorov–Arnold Network (Chebyshev KAN) surrogate model with an Improved Multi-objective Red-billed Blue Magpie Optimizer (IMORBMO). The accuracy of the Chebyshev KAN model was benchmarked against conventional multilayer perceptrons (MLP), convolutional neural networks (CNN), and the standard Kolmogorov–Arnold Network (KAN). Experimental results demonstrate that the Chebyshev KAN model achieves the lowest mean absolute error (MAE) of 0.103 for airflow velocity and 0.115 for air consumption. Building upon the non-dominated sorting and crowding distance strategies, IMORBMO was developed, incorporating an adaptive mutation mechanism by information entropy for improvement of convergence, diversity, and uniformity of the Pareto-optimal solutions. Comprehensive evaluations on the ZDT and WFG benchmark suites confirm that the IMORBMO consistently attains the best and highly competitive performance, yielding the lowest generation distance (GD), inverted generational distance (IGD) values and the highest hypervolume (HV). Applied to the aerodynamic optimization of a relay nozzle, the proposed framework delivers an optimal aerodynamic design that increases airflow velocity by 10.5% while reducing air consumption by 15.4%, as verified by CFD simulation. The steady-state flow field was simulated by solving the Reynolds-Average NavierStokes equations with the k−ω turbulent model, utilizing Fluent 2025.R2. No-slip wall, inlet pressure and outlet pressures are boundary conditions to the relay nozzle surfaces. This work establishes a computationally efficient and accurate optimization paradigm that holds significant promise for aerodynamic design and other complex real-world engineering applications. Full article

Precise manipulation of two-phase flow in micro-confined electrowetting pixels is limited by contact angle hysteresis (CAH). To elucidate this non-equilibrium process, we establish a high-fidelity electrohydrodynamic (EHD) phase-field simulation framework. The model rigorously couples Navier–Stokes equations with molecular kinetic theory (MKT) to characterize energy dissipation at the three-phase contact line (TCL) and further integrates charge transport kinetics. Numerical results reveal CAH is driven by physical pinning and interfacial charge trapping, with the latter dominating interfacial retreat and causing significant residual displacement. Furthermore, analysis shows alternating current (AC) waveforms mitigate charge accumulation and promote depinning via micro-oscillations, minimizing the hysteresis loop compared to direct current (DC) waveforms. Additionally, an overdrive strategy utilizing a suprathreshold Maxwell stress pulse rapidly overcomes static friction. This strategy significantly improves transient dynamics, substantially reducing the time to reach 90% of the steady-state target from 19.6 ms (under standard DC waveform driving) to 7.4 ms. This work provides a comprehensive theoretical basis and design criteria for optimizing active driving strategies in optofluidic and digital microfluidic systems. Full article

The increase in utility-scale PV generation and the displacement of synchronous machines reduce system strength, reactive power headroom, voltage resilience, and overall power system stability, motivating a robust comparison of various mitigation technologies beyond static load-flow or PV assessments. RMS time-domain simulations are performed for balanced and unbalanced contingencies, and performance is quantified using post-fault voltage dip depth, undervoltage area (V < 0.9 pu.), recovery time to nominal, and RoCoF. These metrics are aggregated into a single weighted composite severity score, which is then normalised to the baseline to form the dynamic voltage resilience index (DVRI) and the Frequency Disturbance Relative Index (FDRI). The results show that the converter-based reactive power support devices deliver the fastest and most controllable post-fault voltage restoration, with the STATCOM achieving the lowest composite penalty and best DVRI under severe fault conditions but the poorest FDRI during PV plant trip/reconnection events. The synchronous condenser (SC) improves post-fault recovery through excitation driven reactive capability and increased short-circuit contribution, but its recovery to nominal voltage levels is slower and can produce negative-sequence current under unbalanced fault conditions whilst producing the smallest frequency disturbance and best FDRI. The SVC provides effective steady-state regulation but becomes less effective during extremely low voltages due to the voltage-dependent reactive power output, and its FDRI remains close to baseline. The BESS-GFM is dependent on the inverter current limits and the control priorities, which influence both voltage recovery and response times, achieving an FDRI scoring second to the SC. These metrics are combined into baseline normalised composite indices (DVRI and FDRI) using explicitly dimensionless sub-metrics (dip magnitude, exposure area, and recovery delay for voltage and deviation magnitude, windowed RoCoF, and exposure for frequency). Equal weights are used as a neutral baseline, and a weight sensitivity study is included to confirm that technology rankings are robust to plausible variations in weighting choice. Full article

Most computational studies of vehicle hydroplaning have emphasized structural realism through fluid–structure interaction, tire deformation, tread geometry, and pavement surface characterization. By contrast, the hydrodynamics governing the flow in the tire vicinity, particularly the role of turbulence, have received comparatively limited attention. In a significant number of studies, the flow has been treated as laminar despite turbulent flow conditions, while in a few other studies turbulence modeling has been adopted without an explicit assessment of its impact on hydroplaning predictions. In this study, we present a simplified three-dimensional computational fluid dynamics (CFD) model designed to isolate the flow regimes governing hydroplaning and to quantify the mean effect of the turbulence modeling on the predicted hydroplaning speed. Using a finite-volume formulation with a volume-of-fluid representation of the air–water interface, the flow around and beneath a smooth 0.7 m-diameter tire sliding in locked-wheel mode over a flooded, nominally smooth pavement is simulated. The tire is represented as a rigid body with an idealized rectangular bottom patch whose area is determined from the tire load and inflation pressure, avoiding the need to prescribe a measured or assumed deformed footprint. Steady-state hydroplaning is modeled for a uniform upstream water film thickness of 7.62 mm with a 0.5 mm gap between the tire and the pavement, over tire inflation pressures ranging from approximately 100 to 300 kPa, and predictions are verified against the empirical NASA hydroplaning equation. For these conditions, simulations without turbulence closure exhibit a consistent, systematic underprediction of the hydroplaning speed of approximately 13.5% relative to the NASA relation. Incorporating turbulence effects through Reynolds-averaged closures substantially reduces this bias, with average deviations of about 6% for the realizable k–ε model and 2.4% for the shear stress transport (SST) k–ω model. An analysis of the results indicates that hydrodynamic lift is dominated by pressure buildup associated with stagnation at the lower leading edge of the tire, with a significant contribution from shear-dominated flow in the thin under-tire gap, and that turbulence acts to moderate the integrated lift from these pressure fields. These results demonstrate that explicitly accounting for turbulence in the tire vicinity is essential for reproducing empirical hydroplaning trends and for avoiding systematic bias in CFD-based hydroplaning predictions. Full article

To investigate the influence of working fluid composition on the thermo-hydraulic performance of plate heat exchangers (PHEs) under single-phase sensible heat transfer conditions, a three-dimensional steady-state numerical model was developed for a transverse corrugated channel with a chevron angle of 60°. The governing equations were solved using the finite volume method implemented in ANSYS Fluent, in conjunction with the standard k–ε turbulence model. The analysis considered pure refrigerants R134a and R245fa, as well as their mixtures with mass ratios of 0.2, 0.5, and 0.8, with thermophysical properties assumed to be temperature-independent constants. The results indicate that as the mass fraction of R134a decreases from 1.0 to 0, the heat transfer coefficient (h) decreases from 1025 to 815 W/(m²·K), primarily attributed to the combined effects of reduced thermal conductivity and increased viscosity. Among the investigated cases, the R134a/R245fa mixture with a mass ratio of 0.8 provides the most favorable performance trade-off, exhibiting a heat transfer coefficient only 3.0% lower than that of pure R134a while achieving a 12.5% reduction in flow resistance compared with pure R245fa. Furthermore, the heat transfer coefficient is found to be weakly affected by heat flux in the range of 8000–20,000 W/m²; in contrast, increasing the mass flow rate from 0.001 to 0.005 kg/s enhances heat transfer coefficient by 65.1%, accompanied by a significant increase in pressure drop. Comparisons with established single-phase correlations for corrugated channels show average deviations of 6.5% for the Nusselt number and 3.8% for the friction factor. The present study provides useful guidance for working fluid selection and operational optimization of PHEs in applications dominated by sensible heat transfer, such as specific stages of heat pump cycles and medium-temperature waste heat recovery. Full article

Foreign direct investment (FDI) plays a vital role in Africa’s economic development; however, the rapidly expanding body of literature on this topic remains highly fragmented. This dispersion creates a significant research problem, obscuring structural evolution, persistent thematic gaps, and collaborative networks within the field. To address this, a bibliometric analysis is necessary, as it provides an objective, macro-level methodology capable of synthesising vast amounts of publication data and uncovering hidden intellectual structures that traditional systematic reviews cannot easily capture. Consequently, this study maps the development of FDI research in Africa by analysing and visualising scientific publications to reveal the structure, evolution, and interdisciplinary nature of the field, identifying leading scholars, collaboration networks, and core thematic areas. Using data from the Scopus database, the study examines 2003 documents through Biblioshiny and VOSviewer. The findings are presented in three sections. The descriptive analysis shows a steady rise in FDI publications from 1986 to 2024, with strong growth in the past two decades. The most productive institutions are in South Africa and Nigeria, while major contributing countries include South Africa, the United States, China, and the United Kingdom. Keyword and collaboration analyses highlight themes such as Sub-Saharan Africa, economic growth, capital flow, renewable energy, and natural resources. Ultimately, this mapping goes beyond descriptive trends to provide critical analytical insights, revealing a significant thematic shift from traditional economic paradigms toward sustainable development and environmental economics. Practically, these findings offer strategic guidance for policymakers and investors by identifying key institutional hubs and regional knowledge gaps. Scientifically, the study establishes a foundation for future research by directing attention toward underexplored, emerging issues such as climate resilience, digital transformation, and subnational FDI dynamics. Full article

The paper presents SFPD, the new open algorithm developed by the University of Padova (PD in the acronym) for computing the steady-state regime due to any number of simultaneous faults (SF at the beginning of the acronym) both short circuits and open conductors. The algorithm does not have simplified hypotheses, since it benefits from the pre-fault regime based on PFPD_MCA (power flow by University of Padova with multiconductor cell analysis), a multiconductor power flow (developed and published by the first author) which takes into account both the active conductors (i.e., the phases subjected to the impressed voltages) and the passive conductors (i.e., the interfered metallic conductors, namely earth wires of overhead lines, metallic screens and armors of land and submarine cables, enclosures of gas insulated lines, return and earth wires of 2 × 25 kV AC high-speed railway supply system, etc.). Different types of faults are considered, and where they occur (also along the lines), by means of a suitable admittance matrix in phase frame of reference and embedded inside the overall network bus admittance matrix. Some comparisons with simplified approaches are presented in order to demonstrate the power of the method. Eventually, application to the real Italian network is comprehensively shown. Full article

Background/Objectives: MRI-guided neurovascular interventions could benefit from lower-field systems due to reduced magnetic and radiofrequency hazards. However, safety and practical visibility of commonly used neurointerventional devices at 0.55 T remain insufficiently characterized. We evaluated magnetic field interactions, RF-induced heating, and qualitative device visibility in 11 commercially available and commonly used neurovascular devices on a 0.55 T MRI system. Methods: Eleven devices, including stent retrievers, guidewires, catheters, and one embolization implant, were tested at 0.55 T. Magnetostatic interactions were quantified using the American Society for Testing and Materials (ASTM)-guided deflection methods for translational force (ASTM-F2052) and a two-string suspension apparatus for torque (adapted from Stoianovici et al.). RF-induced heating was measured in an in vitro perfused cerebral vessel phantom using a 15 min high-specific absorption rate spin echo sequence under static and flow conditions. Qualitative device visibility was assessed using a turbo spin echo (TSE) and balanced steady-state free precession (bSSFP) imaging on each device individually. Results: Eight of eleven devices passed the translational force test, while three devices (D, E, and G), containing significant ferromagnetic components, failed with deflection angles > 45°. Eight devices passed torque testing, remaining below the critical threshold in all rotation positions; three devices (D, G, and J) failed by exceeding the 54° criterion, including one guidewire and two devices with braided/coiled metallic structures. Under static conditions, RF-induced heating ranged from negligible to 10.4 °C (maximum in device D) and generally decreased under flow; in the flow configuration, temperature rise remained below 2 °C for 6/11 devices. Qualitative imaging performance differed by sequence, with bSSFP enabling improved delineation of device structure (best for devices A, C, and H), whereas devices D, E, F, and J produced extensive signal voids that precluded reliable visualization in both sequences. Overall, three devices satisfied all safety criteria while remaining clearly visible under MRI. Conclusions: Devices that pass safety thresholds at 0.55 T can serve as candidates for further sequence optimization and preclinical workflow development, enabling the design of low-SAR, device-compatible imaging protocols tailored for neurointerventional workflows. These results provide key safety data supporting the feasibility of MR-guided neurovascular procedures at 0.55 T. Full article

Thermal interface materials (TIMs) are essential for addressing heat dissipation challenges in high-performance electronic devices. Among various TIMs, thermal conductive gels exhibit significant potential in high heat flux applications due to their excellent flexibility and superior gap-filling capability. Current research primarily concentrates on the fabrication and performance characterization of novel thermal conductive gels, while comparatively little attention has been devoted to the optimization of processing parameters. Furthermore, existing characterization methods often fail to accurately replicate real-world operating conditions, resulting in discrepancies between laboratory measurements and actual performance. An orthogonal experimental design was adopted to systematically elucidate the influence of filler ratio, wetting time, and silicone oil viscosity on the bonding strength of thermal conductive gels. The filler ratio exerts the most significant influence, followed by silicone oil viscosity and wetting time. Subsequently, the thermal conductivity and thermal resistance of both commercial thermal conductive gels and the as-prepared gels were characterized using the steady-state heat flow method and the double-interface method, respectively. Under the optimized preparation conditions (filler ratio of 88%, silicone oil viscosity of 600 cP, and wetting time of 14 h), the self-developed thermal conductive gel exhibits a thermal conductivity of 3.75 W·m⁻¹·K⁻¹ and a bonding strength of 0.248 MPa, outperforming commercial counterparts and demonstrating promising application potential. It was further concluded, through comparisons of curing rheology and long-term reliability evolution with commercial counterparts, that the self-developed thermal conductive gel possesses enhanced stability and reliability. This study provides a practical reference for the development and engineering application of high thermal conductivity, low thermal resistance gels. Full article

This study aims to advance the understanding of laminar magnetohydrodynamic (MHD) fluid flow between two parallel plates subjected to a uniform transverse magnetic field, motivated by its significant applications in engineering and industrial systems such as nuclear reactor cooling, MHD generators, and electromagnetic pumping devices. The governing equations are simplified using a one-parameter Lie group symmetry transformation, which exploits the inherent symmetry properties of the system to reduce the original unsteady partial differential equations to a system of ordinary differential equations. The reduced equations are solved exactly under appropriate boundary and initial conditions, ensuring mathematically consistent and physically realistic solutions. A comprehensive analysis is conducted to examine the influence of key physical parameters, along with the applied magnetic field, on the velocity, temperature, and concentration profiles. The selected parameter ranges encompass a broad spectrum of physically relevant cases, enabling a detailed assessment of their effects. The results indicate that the transverse magnetic field exerts a damping effect on the flow, reducing the velocity profile due to the Lorentz force. Moreover, an increase in the Schmidt number accelerates the achievement of a steady-state concentration, while higher Prandtl numbers reduce the temperature profile. In contrast, the radiation parameter enhances the temperature distribution. In addition, the skin-friction coefficient is presented graphically, and the Nusselt number is evaluated to characterize the heat transfer performance. Overall, the findings provide valuable insight into the effects of magnetic, thermal, and solutal parameters on laminar MHD flow between parallel plates. Full article

In recent years, copper-based conductive and heat dissipation components have required fine structures for miniaturization and enhanced functionality. Micro-forming is an excellent processing method characterized by high productivity and suitability for mass production. Since small workpieces can be formed within a short stroke in micro-extrusion, it is important to understand the deformation behavior immediately after the start of extrusion. However, before steady state is attained, the evolution of microstructure and plastic flow with stroke progression during non-steady-state deformation has not yet been sufficiently clarified. In this study, to investigate the effect of changes in plastic flow on force behavior, micro-extrusion tests were conducted using pure copper. The geometric and crystallographic characteristics of the deformation structure were then analyzed. The extrusion force behavior exhibited three distinct stages, including a peak of the force. The force peak was attributed to changes in plastic flow associated with the deformation structure formed at the sample tip immediately after the start of extrusion. This change leads to the evolution of the effective extrusion ratio, which significantly influences the force response during non-steady-state deformation. Full article

One of the key factors determining energy consumption and control stability in hydraulic servovalves with direct electric drive is the flow forces acting on the spool. These forces are complex in nature and consist of both steady-state and transient components, with the steady-state component exerting the dominant influence on the performance and dynamics of spool valves. In recent years, this issue has become the subject of intensive research aimed at reducing undesirable hydraulic loads while maintaining high nominal flow capacity, strong energy efficiency, and low manufacturing cost. In engineering practice, the most effective approach has proven to be the modification of the spool geometry in order to control the direction and jet angle of the outflow while keeping the valve sleeve design as simple as possible. This solution reduces the forces acting on the spool without the need to redesign the flow channels or increase production complexity. This study presents classical analytical methods used to calculate flow forces in typical spool valve designs, which serve as a reference point for subsequent investigations. Then, using CFD simulation tools, a method of flow force compensation is demonstrated for selected spool geometries, followed by a detailed comparative analysis of their effectiveness. The results may provide a foundation for developing more energy-efficient and dynamically stable direct-drive servovalve constructions. Full article

This article details a matrix-based mathematical method to calculate power flows and transmission losses in an electric grid specifically attributable to low-carbon and renewable energy sources (LCRES) (wind, solar, nuclear). The goal is to improve the transparency and reliability of Guarantees of Origin (GO) certificates. Current GO schemes rely on contractual accounting and neglect physical power losses, undermining consumers’ confidence that they receive “clean” energy. The method uses steady-state power flow analysis to derive a power-loss distribution coefficient matrix. This matrix accurately allocates grid losses back to the LCRES generating nodes, complying strictly with electrical engineering principles. It accommodates both time-varying renewable output and stable nuclear generation. The results offer highly accurate loss-attribution data, supporting more verifiable GOs, ensuring fair compensation for losses, and enhancing energy balance accuracy in hybrid power systems. Full article

The complex architecture and stacking patterns of deepwater turbidite channel sandbodies introduce significant uncertainty in injector–producer connectivity. This uncertainty affects both the mechanisms and the quantitative evaluation of the waterflood sweep. In this study, a representative reservoir in the Niger Delta Basin is selected as a case study. Injector–producer well groups are first classified into three connectivity patterns—coeval, cross-stage, and hybrid based on geological and seismic constraints. Time-lapse seismic data are then interpreted to delineate sweep morphology and to infer the controlling mechanisms associated with each pattern. Coeval connectivity exhibits a relatively uniform and continuous front advance with minimal barriers. Cross-stage connectivity shows fragmented swept regions with pronounced bypassing, and localized preferential breakthrough caused by discontinuous sandbodies and pervasive barriers. Hybrid connectivity is characterized by intermediate behavior, combining features of both patterns. To translate these mechanistic differences into quantitative metrics for development evaluation, an oil–water relative permeability ratio correlation for low viscosity oil is established that remains valid across the full water cut range, thereby overcoming the limitations of conventional semi-log linear correlations at both low and ultra-high water cut stages. Based on this framework, a production data-driven predictive model for waterflood sweep efficiency is derived using production data and steady state flow theory. The model is validated across well groups representing different connectivity patterns. Field application yields a consistent ranking of sweep efficiency: coeval > hybrid > cross-stage, with group average values of 0.86, 0.80, and 0.70, respectively. These results agree with the mechanistic interpretation derived from time-lapse seismic analysis. The proposed methodology provides a practical quantitative framework for evaluating injector–producer connectivity and comparing development strategies in deepwater turbidite channel reservoirs. Full article

Electric vehicles (EVs) experience substantially reduced driving range in cold weather, primarily due to cabin heating energy demands. This paper proposes a control allocation strategy for positive temperature coefficient (PTC) heater-based electric minibus cabin thermal management, aimed at minimizing energy consumption. The strategy is of a hierarchical structure, where a supervisory PI cabin temperature controller commands the heating power demand, which is then achieved through optimal allocation and low-level control of the cabin inlet air temperature, coolant pump flow, and radiator blower air flow control inputs. Based on the assumption of fast heating system dynamics relative to cabin thermal dynamics, quasi-steady-state optimization of control input allocation is carried out by employing a grid-search algorithm over a dataset resulting from high-fidelity simulations. For the system heat-up transient conditions, where the steady-state allocation proves to be suboptimal, dynamic programming is applied on a validated reduced-order model to optimize the control trajectories. Insights gained through control trajectory optimization are then used to develop a rule-based modification of the control allocation strategy for the heat-up scenario. Simulation verification of the overall control system demonstrates energy consumption reduction in the range from 4 to 12% when compared to the industrial baseline system across both steady-state and transient operating conditions. Full article