Search Results (13,842)

Acoustofluidics has emerged as a transformative technology for contact-free manipulation of microparticles and fluids in microscale systems. Although bulk acoustic waves (BAWs) are known to displace inhomogeneous fluids through acoustic radiation force acting at fluid interfaces, the capability of surface acoustic waves (SAWs) to produce analogous relocation phenomena remains largely unexplored. This study addresses a critical gap in acoustofluidic theory by presenting the first comprehensive finite element method investigation of SAW-driven motion of inhomogeneous fluid confined within microchannels of widths equal to one full or one-half SAW wavelength. Unlike BAW-based system that generate uniform pressure fields across channel heights, SAW devices exhibit inherently nonuniform vertical pressure distributions and intense near-boundary streaming—features that fundamentally alter fluid relocation dynamics. Our simulations demonstrate that despite high-frequency operation (6.65 MHz) and strong ARF, standing SAW fields fail to achieve stable fluid relocation in both initially stable and unstable configurations due to vertical pressure stratification and rapid floor-level streaming. Nevertheless, these same characteristics generate vigorous transverse folding flows that enable exceptionally rapid homogenization, offering a distinct acoustofluidic mechanism for on-chip mixing. These findings not only elucidate fundamental physical differences between BAW and SAW actuation in multiphase microfluidic systems but also establish design principles for SAW-induced microfluidic mixers. The results provide crucial theoretical guidance for device optimization where rapid homogenization is desired over stable stratification. Full article

The increasing frequency and intensity of extreme climate events have posed more geohazards worldwide. It is therefore crucial to quantify and map risk to reduce disaster-related losses. The main objective of this study is to propose a quantitative framework to conduct risk assessment of buildings and infrastructures impacted by geohazards. A debris flow hazard in Tianjin, North China was taken as a case study. A physically based model and the Gumbel extreme value distribution were utilized to construct a range of extreme rainfall and runoff scenarios. The FLO-2D and ABAQUS software were subsequently employed to simulate the surging behavior of the debris flow and assess the structural vulnerability of buildings, respectively. Furthermore, the number of elements at risk and economic values were estimated to generate risk maps. The results revealed that variations in peak discharge in the channel evidently affected flow velocity and depth, thus elevating the debris flow intensity and the likelihood of the materials threatening buildings. The stiffness degradation of concrete was strategically used as the indicator to quantify structure vulnerability and effectively present the dynamic responses under the impacts of the debris flow. Under a 100-year return period rainfall scenario, the proportion of very high- and high-risk areas reached 31%, with the estimated economic loss approximately ¥167.7 million. This highlighted the critical role that extreme rainfall played in shaping both the spatial distribution and severity of debris flow risks. The proposed method provides a scientific basis for enhancing the resilience of mountainous regions to compound natural disasters exacerbated by climate change. Full article

Unlike traditional power systems, the heterogeneous energy support of electric–gas regional distribution networks brings new challenges to resilience assessment. On the basis of identifying N-k fault uncertainty risks, establishing a resilience assessment methodology is one of the important issues in resilience research. Existing reliability assessment methods cannot accurately quantify resilience under N-k extreme fault scenarios. To address this limitation, we propose a non-simulation resilience assessment method. The approach can simultaneously quantify the dynamic interactions of heterogeneous energy flows and the impact of repair process time uncertainty on system resilience under extreme fault scenarios. Specifically, the resilience indexes are established by combining the load outage and mathematical expectation during/after the extreme fault and applying probabilistic knowledge to express the N-k load outage event, so as to effectively offset the data scarcity due to the limited N-k fault data samples. The internal consistency and parametric responsiveness of the proposed non-simulation method are demonstrated through systematic case comparisons under varying failure rates, repair times, and coupling conditions. Full article

Ground vortex formation beneath aeroengine intakes during near-ground operations represents an energy-related aerodynamic issue, as it degrades inlet flow quality, induces pressure distortion, and reduces the effective utilization of incoming kinetic energy. This study investigates the unsteady characteristics of ground vortex flow under headwind conditions and its influence on foreign object ingestion (FOI) in an aeroengine intake. Three-dimensional unsteady Reynolds-averaged Navier–Stokes (URANS) simulations coupled with a Lagrangian Discrete Phase Model (DPM) are employed to resolve the interaction between intake-induced vortices and dispersed particles near the ground. The results indicate that the ground vortex rapidly develops into a quasi-periodic state, generating significant unsteady total pressure distortion at the intake face, with peak fluctuations reaching approximately 10% of the mean value. This flow non-uniformity reflects a deterioration of inlet energy distribution and is detrimental to downstream compression efficiency. Particle ingestion behavior is strongly dependent on particle density and diameter. Low-density and small particles are more readily entrained into the vortex core and ingested, whereas particles with higher density or larger size exhibit increased inertia and reduced sensitivity to vortex-induced energy transport. The ingestion region is biased toward the lower portion of the intake, consistent with the vortex core location. These findings provide insight into vortex-induced energy distortion and FOI mechanisms, offering guidance for improving aeroengine intake design and energy-efficient operation during near-ground conditions. Full article

The continuous increase in power density of electronic devices imposes stringent requirements on the design of lightweight, high-efficiency heat sinks. To overcome the limitations of conventional single-gradient or monomaterial heat sinks—namely, their suboptimal heat-transfer efficiency and poor structural adaptability—this study proposes a dual-gradient, triply periodic minimal surface (TPMS)-based multimaterial heat sink architecture fabricated from CuCrZr and AlSi₇Mg. Thermal performance was quantified experimentally using infrared thermography, while the underlying flow-field mechanisms were investigated numerically via computational fluid dynamics (CFD) simulations employing the standard k–ε turbulence model. With the TPMS material volume ratio fixed at 3:3 (CuCrZr:AlSi₇Mg), the Z-axis gradient configuration P-Z4-5 delivered the best overall thermal performance, achieving a heat-transfer coefficient (HTC) of 1557.63 W·m⁻²·K⁻¹ and a thermal resistance as low as 1.83 K·W⁻¹ at an inlet velocity of 5 m·s⁻¹. In contrast, the Y-axis gradient configuration P-Y3-6 yielded the most uniform temperature distribution, exhibiting a maximum surface temperature difference of only 21.5 °C under the same inlet condition. Velocity and turbulence distribution analyses reveal that the dual-gradient design enhances both the narrow-tube effect and flow-induced disturbances; furthermore, increasing the inlet velocity from 5 m·s⁻¹ to 21.65 m·s⁻¹ significantly intensifies vorticity-driven fluid mixing. Among all configurations evaluated, P-Z4-5 exhibited the highest j/f factor (i.e., the ratio of Colburn j-factor to Fanning friction factor), followed by P-Z3.5-5.5 and P-Z3-6. These findings establish a promising new pathway for the development of high-performance, lightweight heat sinks tailored for next-generation high-power electronics. Full article

This study investigates the separation performance of a novel hydrocyclone design incorporating side filtration flow. Experiments were conducted using black silicon carbide powder in an 18.5 mm diameter hydrocyclone, while computational fluid dynamics (CFD) simulations were performed using FLUENT to analyze the flow behavior. The cylindrical section of the hydrocyclone was modified into a porous filter column, allowing controlled side filtrate discharge. The Volume of Fluid (VOF) multiphase model and Large Eddy Simulation (LES) turbulence model were applied to capture the flow field, while the Discrete Phase Model (DPM) was used to track particle motion and assess classification efficiency. Experimental results showed that when the side filtration flow rate was approximately 1/200 of the feed flow rate, the cumulative particle size distribution at the overflow shifted toward smaller particle sizes, indicating improved separation of fine particles. Simulations further revealed an optimal side flow ratio of 0.004–0.005: higher side flow reduced rotational velocity and classification efficiency, while lower side flow provided insufficient pressure relief. Particle tracking demonstrated that side filtration reduced particle recirculation in the cylindrical region, accelerating underflow discharge. These findings highlight the potential of side filtration for enhancing hydrocyclone classification efficiency, providing quantitative insights for future design optimization. Full article

Current research lacks systematic understanding of cross-scale correlations between micro-texture geometry and macro-lubrication behavior. This study presents a multi-scale collaborative optimization methodology for gear Micro-Textured Meshing Interface (MTMI). An objective function targeting macroscopic interfacial performance is formulated, and a topology optimization strategy is employed to achieve optimal MET configuration. The homogenization analysis captures the modulating effects of MET on local flow and stress fields, while topology optimization transcends conventional parametric geometric constraints, enabling the generation of non-regular MET topological patterns tailored to complex operating conditions, thereby ensuring optimal macroscopic ASLBC. The proposed scheme is validated through numerical simulations of two representative problems capturing distinct lubrication regimes: (1) IEL, characterizing transient load-bearing dynamics governed by temporally evolving MET configurations; and (2) ASLBC, elucidating steady-state load-bearing capacity modulation via spatially heterogeneous MET distributions. A Taylor expansion-based surrogate model is developed to efficiently explore the MET configuration design space, significantly enhancing computational efficiency and solution accuracy for multi-scale optimization. While the gradient-based algorithm cannot guarantee global optimality, extensive numerical simulations and cross-validation studies demonstrate consistent convergence toward high-performance MET configurations, with sensitivity analyses of design parameters further confirming the engineering applicability of the optimized solutions. Full article

Piston pumps are core components in hydraulic systems, and their performance, efficiency, and stability significantly impact the operation of the entire system. The flow distribution method is a key factor determining the overall performance of the piston pump, directly affecting the pump’s output flow rate, pressure, and efficiency, and significantly influencing its working stability and reliability under different operating conditions. This paper reviews the structural principles, advantages, and disadvantages of current mainstream valve distribution, disc distribution, and shaft distribution methods, and discusses the main challenges they face in various applications. It focuses on analyzing how to improve piston pump performance by optimizing structural parameters, control strategies, and flow channel design. Furthermore, this paper introduces new flow distribution structures such as piston distribution and cylinder block distribution. The above provides a theoretical basis for the selection and innovation of flow distribution structures for piston pumps under different operating conditions in the future. Full article

This work presents a systematic design flow for the fundamental building blocks (namely, the low-noise amplifier and the down-conversion mixer) of an analog receiver for 5G backhauling systems implemented in SiGe BiCMOS technology. The proposed methodology enables the sizing and optimization of receiver blocks up to post-layout simulations, starting from the specified performance requirements. It accounts for both the parasitic effects of active devices and the distributed effects of interconnects. The design flow was applied using STMicroelectronics BiCMOS55X technology to develop low-noise amplifiers and D-band to E-band downconverters capable of covering the 130–150 GHz and 150–165 GHz sub-bands. Preliminary measurement results obtained from both the standalone LNA blocks and the complete receivers are presented and discussed. Full article

Theoretical models of polyelectrolyte systems with cross-linked polymer networks are often simplified to linear differential equations by means of the linearized Poisson–Boltzmann approximation, whose validity is traditionally limited to cases where the electrostatic potentials are small. However, the limits of applicability of the linear theory remain debatable in many cases. Moreover, the Poisson–Boltzmann equation is, in principle, not applicable to the description of non-equilibrium systems, particularly those through which an electric current flows. In the present work, a direct comparison is carried out between the exact solution and the approximate solution (i.e., the solution obtained within the framework of the linearization procedure) of the equations describing the contact region between a cross-linked polyelectrolyte network and a low-molecular-mass salt solution. This makes it possible to determine the conditions under which the linear model is applicable, including for the analysis of promising systems in the field of organic electronics. The conclusions obtained in this work are based on basic electrostatics equations and transport equations of low-molecular-mass ions. The proposed approach also makes it possible to obtain a generalized linear differential equation that is not subject to a Boltzmann distribution approximation and is valid for polyelectrolyte systems rather far from thermodynamic equilibrium and even carrying steady electric currents. Full article

The increasing penetration of rooftop photovoltaic (PV) systems has introduced significant challenges to voltage regulation and power quality within low voltage (LV) distribution networks. Reverse power flows during periods of high solar generation and low local demand can lead to overvoltage issues, voltage unbalance, and increased neutral-to-ground potential. This paper presents a comprehensive review of voltage regulation challenges and mitigation strategies for PV-rich distribution networks. The review consolidates findings from recent literature, focusing on traditional methods such as on-load tap changers and reactive power compensation, as well as modern techniques including smart inverter functionalities, community energy storage, static compensators, and advanced coordinated control schemes. A detailed examination of the suitability and limitations of these approaches in the Australian regulatory and network context is provided. The literature review demonstrates that previous work has mainly considered generic LV regulation issues without explicit four-wire MEN modelling or detailed LV–MV time series impact analysis. As a response to the lack of detailed practical analysis, a detailed three-phase four-wire LV–MV modelling and case study analysis, which illustrates the technical implications of high PV penetration on a representative Australian LV feeder, has been completed. The network is modelled using a three-phase four-wire unbalanced load flow formulation, explicitly incorporating the neutral conductor and multiple earthed neutral (MEN) system configuration. Results demonstrate pronounced voltage rise and unbalance during midday generation periods, highlighting the need for distributed and adaptive voltage-management solutions. The paper concludes by identifying key research gaps and future directions for voltage regulation in Australian distribution networks, emphasizing the importance of low voltage visibility, coordinated control architectures, and the integration of emerging distributed energy resources. The novelty of this work lies in combining a focused review of state-of-the-art with respect to management of voltage regulation in the presence of high penetration of distributed PV generation with a detailed three-phase four-wire LV–MV modelling framework and time-series case study of a representative Australian residential feeder, which illustrates the practical implications of increasing PV penetration. Full article

The traditional Discrete Element Method (DEM) can track the motion details of individual particles, but its computational cost becomes excessively high when simulating large-scale systems involving millions or even billions of particles. In this study, a coarse-grained DEM approach was employed to analyze the flow behavior of mixed particles in a coal powder silo. This method maintains reasonable simulation accuracy while effectively reducing the total number of computational particles and significantly improving computational efficiency. After conducting investigations on the mesh-to-particle size ratio and model validation, this paper focuses on examining the effects of coal particle size distribution and mixing ratio on the characteristics of particle motion. The results indicate that during the discharge process of mixed particles, the downward velocity of particles in the central axis region near the outlet is significantly higher than that in the wall region, exhibiting typical funnel flow characteristics. The particle size distribution has a notable impact on the particle descent velocity. The uniform distribution case shows the highest descent velocity, the linear distribution case the lowest, while the normal distribution case falls between the two. Notably, in the normal distribution case, the descent velocity in the central axis region is similar to that of the uniform distribution, while the descent velocity in the wall region approaches that of the linear distribution. This presents a combined characteristic of the two extreme distributions rather than a simple transitional state. In contrast, the particle mixing ratio has a relatively minor influence on the overall motion characteristics. The mass flow rate of particles and the cross-sectional velocity distribution remain largely consistent, with only slight differences observed in the velocity within the central axis region. Full article

Distributed denial-of-service (DDoS) attacks have become a critical threat to Internet of Things (IoT) infrastructures due to their high traffic dynamics, strong class imbalance, and strict resource constraints at the edge. This paper proposes ChebyKANRes, a lightweight intrusion detection model that combines Chebyshev polynomial expansions to parameterize learnable univariate transformations, a gate mechanism to modulate feature flow, and residual connections to stabilize optimization in deeper KAN-style stacks. Experiments were conducted on the CICIoT2023 dataset focusing on benign traffic and 12 DDoS subtypes, using a reproducible pipeline with stratified splitting, cross-validation (k = 5), and early stopping. The proposed model consistently improves multi-class performance (Accuracy: 0.9983) over an optimized MLP baseline (Accuracy: 0.9641), while maintaining a compact size suitable for edge deployment (≈123 k parameters; ~0.47 MB). Within CICIoT2023 and the evaluated split/training protocol, the proposed ChebyKANRes configuration shows improved imbalance-robust multiclass detection while maintaining a compact model size and comparable batch inference time. Full article

Populations in areas with limited hydrological data face ongoing challenges related to water supply and management, with climate change increasing the risks of floods and droughts. New remote sensing and modeling tools can improve land and water management in these regions, especially when combined with limited ground measurements and local knowledge of extreme events. This study examined hydrological extremes and land cover change impacts in the Grande Rivière du Nord watershed, Haiti, using satellite and model-based data. Precipitation extremes were obtained from the Global Precipitation Measurement Integrated Multi-satellite Retrievals for GPM (GPM IMERG; 2000–2025), and streamflow data were sourced from the Group on Earth Observation Global Water Sustainability (GEOGLOWS) system and bias-corrected with a small historical hydrologic database. Annual maximum series were created and fitted with Gumbel, Lognormal, and Generalized Extreme Value (GEV) distributions using the L-moment method. Goodness-of-fit tests identified the best models, and precipitation amounts for return periods of 2–100 years were estimated. The precipitation maxima aligned with locally reported extreme events, and GEV provided the best overall fit. Using the bias-corrected streamflow, a hydrologic model was calibrated and validated and then applied to land cover change scenarios. Simulations suggest that moderate land-use change can increase peak flows beyond channel capacity, raising flood risk and informing adaptation planning in northern Haiti, which has limited data. Full article

Bidirectional Interleaved Converters (BICs) are widely used in Battery Energy Storage Systems (BESSs) due to their modular structure, high efficiency, and reduced current ripple. However, under partial-load operation, conventional control strategies with fixed or purely current-based phase shedding repeatedly activate the same converter branches, resulting in increased switching losses, thermal imbalance, and uneven aging of power semiconductors. This paper proposes a temperature-adaptive control strategy for BICs aimed at improving light-load efficiency while actively balancing thermal stress between converter branches. The approach combines a current-adaptive phase-shedding algorithm with a temperature-based branch rotation mechanism, where real-time transistor junction temperature is used as the primary decision variable for branch activation and deactivation. An electro-thermal real-time simulation model of a two-branch BIC is developed using the Controller Hardware-in-the-Loop (CHIL) methodology in the Typhoon HIL environment. The proposed control strategy is validated through real-time CHIL experiments in both boost and buck operating modes under representative battery load profiles. The results demonstrate a reduction in average and peak transistor junction temperatures, improved thermal distribution between converter branches, and more uniform branch utilization, while preserving stable current regulation and power flow. The presented method represents a practical extension of conventional phase-shedding techniques and provides an implementation solution for improving efficiency and reliability of BICs in BESS applications. Full article