Search Results (100)

Suspended sediment in tidal flows progressively erodes composite turbine blades, with the leading edge being the most vulnerable region. While solid-particle erosion has been studied extensively for metallic components, predictive frameworks for fibre-reinforced polymers under tidal conditions remain limited. This study presents a two-dimensional computational framework that couples a Reynolds-averaged Navier–Stokes solution of the flow around a NACA 63-415 hydrofoil with Lagrangian erosion analysis (125 µm quartz particles) using the Oka erosion model previously calibrated for FR4 glass–fibre composite. Turbulent steady-state simulations were performed in STAR CCM+ (2510.0001) as the CFD software package at five angles of attack (0°, 2.5°, 5°, 7.5°, 10°) at a chord-based Reynolds number of 1.6 × 10⁶, with hydrodynamic predictions validated against published experimental lift-to-drag data. Using the relevant Oka model enabled computation of the erosion rate distribution along the blade section based on particles’ local impact velocities and angles. The resulting profiles consistently exhibit a near-zero erosion zone at the stagnation area, followed by a sharply localised peak erosion within the first 10 to 20 per cent of the chord on the upper surface. A B-spline functional representation of the chordwise erosion distribution is proposed, providing a compact and reproducible basis for subsequent roughness-based hydrodynamic analysis. Full article

Pin-fins are widely used to enhance heat transfer in compact heat exchangers, turbine cooling passages, and electronic devices, but their complex geometries make accurate thermal–fluid prediction computationally expensive. This paper presents a geometry-aware multiscale (GAMS) graph neural network (GNN) for predicting steady turbulent flow and heat transfer in a two-dimensional channel containing arbitrarily shaped pin-fin geometries. An automated framework integrating geometry generation, meshing, and ANSYS Fluent simulations was developed to construct the training dataset. Pin-fin geometries were parameterized using piecewise cubic splines, generating 1000 unique configurations through Latin Hypercube Sampling. Each simulation was converted into a graph representation, where nodes contained spatial coordinates, normalized streamwise position, one-hot boundary indicators, and signed distance to the nearest wall. These graph-based features were used to train the GNN to predict the temperature, velocity magnitude, and pressure fields directly from geometry. The network achieved excellent predictive accuracy, successfully capturing boundary layers, recirculation zones, and upstream stagnation regions while reducing computational wall time by 2–3 orders of magnitude compared to conventional CFD simulations. Overall, the proposed GNN provides a fast, reliable surrogate modeling framework for complex thermal–fluid flow configurations. Full article

Multi-UAV cooperative path planning is an important technical basis for improving offshore emergency response efficiency in complex maritime environments. However, in complex offshore environments, cooperative trajectory planning is affected not only by geometric obstacles but also by wind disturbances, island terrain, restricted flight zones, and inter-UAV safety and communication constraints. These coupled factors make it difficult for conventional swarm intelligence optimizers to maintain risk awareness, local correction capability, and stable late-stage refinement. To address this problem, this paper proposes a risk-aware Modified Traffic Jam Optimizer for cooperative multi-UAV path planning in complex offshore missions. Unlike the original Traffic Jam Optimizer, the proposed method explicitly incorporates risk information into the population update process. A risk-opposition collaborative guidance strategy is designed to adjust the global search direction away from high-risk regions; a risk-based geometric multiscale adaptive mutation strategy is developed to identify and correct high-risk local control blocks; and a generalized quadratic interpolation decision-vector reconfiguration mechanism is introduced to refine the current best solution during stagnation or late-stage search. Two-UAV and three-UAV simulations are conducted using the constructed offshore environment and cooperative constraint models. The results show that the proposed method can generate feasible cooperative trajectories and achieve better performance than the comparison algorithms in path cost, path length, synchronized flight time, and convergence behavior. These results verify the feasibility and effectiveness of the proposed method for risk-aware multi-UAV cooperative path planning in complex offshore environments. Full article

Meeting the rigorous performance standards of modern electrified transit necessitates the deployment of high-performance outer rotor PMSMs with elevated power-to-volume ratios. However, their unique internal heat source topology inherently restricts heat dissipation. This limitation risks permanent magnet demagnetization and winding insulation failure. To address these thermal bottlenecks, this paper proposes internal bio-inspired cooling channels. These channels feature micro-scale V-shaped ribs. This design targets a 60 kW outer rotor PMSM. The motor uses a fractional-slot concentrated winding. The analytical procedure commences with the formulation of a transient 2D numerical model utilizing the Time-Stepping Finite Element approach (TS-FEM). It is coupled with the Bertotti model to compute electromagnetic losses. This approach accurately determines losses under high-frequency rated conditions. Results reveal that stator iron loss constitutes the dominant heat source. It accounts for 76.4 percent of the total electromagnetic loss. Furthermore, these losses show severe spatial concentration at the stator teeth. Subsequently, a three-dimensional fluid-solid coupled CFD model is developed. This model evaluates the proposed internal cooling channels. The design integrates bio-inspired vein networks and V-shaped ribs. These internal ribs disrupt the near-wall thermal boundary layer. This disruption enhances the local convective heat transfer. Comparative multiphysics analyses indicate improved hydraulic and thermal performance of the bio-inspired design under the same numerical boundary conditions. The bio-inspired channel achieves a more uniform static pressure distribution and reduces severe fluid stagnation zones. In the numerical model, the maximum stator and permanent magnet temperatures are reduced to 48 °C and 42 °C, respectively. This work provides a numerical design reference for thermal management in high-performance electric aviation. Full article

In slab continuous casting, the internal hydrodynamics of the submerged entry nozzle (SEN) play a determining role in mold flow stability and product quality, particularly when external electromagnetic flow-control technologies are not employed. This study analyzes a novel bifurcated SEN design intended to promote stable, highly symmetric outlet jets under asymmetric inlet flow conditions produced by typical flow-control devices. The proposed configuration combines three geometric modifications: a square-section bore, a flow-divider bottom wall derived from a rotated mountain-type geometry, and two bell-shaped protrusions that act as flow modulators positioned immediately above the outlet ports. The hydrodynamic behavior inside the nozzle was investigated using complementary experimental and numerical approaches. Physical modeling was conducted in a scaled water model using particle image velocimetry (PIV) to characterize time-averaged velocity fields and flow fluctuations. In parallel, three-dimensional large-eddy simulations (LESs) were performed to resolve transient flow structures and quantify jet characteristics at the nozzle exits. Both approaches show consistent results. The combined action of the flow modulators and the flow-divider bottom wall robustly induces the formation of two nearly identical counter-rotating vortices in the lower region of the SEN. This flow structure suppresses stagnation and recirculation zones near the outlet ports, mitigates inlet-induced asymmetries, and enhances flow evacuation efficiency. Quantitative analysis of the outlet jets indicates a significant reduction in angular dispersion and a flow-rate imbalance below 0.2%, markedly lower than that observed in conventional SEN configurations. The results demonstrate that appropriate internal geometric design can effectively stabilize SEN hydrodynamics without active control systems, offering a feasible and scalable strategy for improving mold flow stability in industrial continuous casting operations. Full article

Wheel hubs in heavy-duty agricultural trailers operate under demanding conditions comprising rough terrain, impact loads, and highly variable load spectra. Current design practice relies predominantly on experience-based sizing rather than systematic multi-physics analysis. This study presents an integrated design methodology combining finite element analysis (FEA), density-based topology optimisation, and computational fluid dynamics (CFD) to concurrently improve the structural and tribological performance of a GGG40 spheroidal graphite cast iron agricultural trailer wheel hub. A reference commercial hub geometry was modelled and analysed under multiple load conditions with a safety factor of 5. Critical stress regions were identified, and the free design volume was optimised while preserving all functional surfaces. The optimised design achieved 35% mass reduction (14.9 to 9.6 kg), 30% lower maximum von Mises stress (235 to 165 MPa), and up to 40% stress reduction in the bearing seat region. Oil-circulation channels integrated into the bearing housing raised mean lubrication flow velocity by 28% and eliminated stagnation zones, yielding a more homogeneous oil-film distribution and directly benefiting bearing tribological performance. The proposed framework provides a manufacturable engineering methodology that concurrently addresses structural integrity and lubrication performance in agricultural wheel hub design. Full article

Genetic resources of small ruminants are essential for food security in arid regions; however, basic data for each breed in Saudi Arabia remain incomplete. This study establishes a comprehensive national database through a systematic survey of 104 farms, covering 21,214 heads of livestock (sheep and goats) across the kingdom’s primary agro-ecological zones between January and October 2025. Although national census data indicate that major breeds of sheep such as Naeemi, Najdi, Arabi, and Harri or goats such as Ardi exceed the FAO’s numerical thresholds for “not at risk,” our analysis reveals a fundamental paradox of “genetic vulnerability,” defined as a high risk of inbreeding depression and genetic stagnation despite high census numbers. The results show significant regional variations in prolificacy (p < 0.05), with the southern region displaying a substantial productivity gap compared to the central and eastern regions, mainly due to reliance on traditional grazing (46.7%) and limited infrastructure. This vulnerability is driven by a high risk of systematic inbreeding, with 65.7% of breeders acquiring sires from their own herds, a situation worsened by a severe 80% shortage of high-quality breeding males in the central region. Furthermore, selection criteria heavily emphasize esthetic phenotypic traits (over 80%) rather than production indicators (less than 8%), hindering genetic progress. Correlation analysis showed that higher farmer education levels were negatively associated with reproductive challenges (r = −0.216), while high feed prices remained a near-universal obstacle (97.1%). To mitigate these risks, we recommend implementing region-specific sire exchange programs to break closed breeding loops and establishing a national performance recording system to shift selection focus from phenotypic traits to measurable productivity. This study provides a vital, evidence-based framework for transitioning toward data-driven, resilient conservation and breeding strategies. Full article

Understanding the spatial organisation of small towns is essential for sustainable spatial planning and regional development. This study examines the spatio-functional pattern of Brzeziny, a small town located within the Łódź Metropolitan Area in Central Poland, selected as a representative case due to its typical Central European small-town morphology shaped by historical continuity, demographic stagnation, and metropolitan influence. The analysis is based on updated cadastral land-use data verified through field surveys and supplemented with topographic datasets (BDOT10k and OpenStreetMap). A modified land-use classification comprising nine categories is applied, and spatial analysis is performed using a regular grid and GIS tools. Dominant land-use structures are identified using the K. Doi method, enabling the delineation of spatio-functional zones. The results reveal a strong dominance of undeveloped land (77% of the total area), particularly agricultural land, alongside a compact central zone characterised by residential and service functions. The study demonstrates how historical development, economic structure, and metropolitan proximity shape the spatial organisation of small towns. The proposed methodology highlights the usefulness of cadastral data combined with grid-based spatial analysis for identifying S-FPs and supporting local planning processes. 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

Additive manufacturing (AM) enables the fabrication of complex three-dimensional components with embedded internal flow channels, but the as-built inner surfaces often exhibit high roughness and poor surface-quality uniformity, particularly at non-coplanar corner regions such as sharp bends and junctions. Conventional abrasive flow machining (AFM) can improve the overall surface finish of such channels; however, corner regions commonly remain weak-removal zones because of local flow stagnation and insufficient abrasive action. To address this limitation, this study proposes a six-degree-of-freedom (6-DOF) robotic-arm-assisted liquid metal-driven abrasive flow (LM-AF) polishing strategy in which robotic pose regulation is used to guide the liquid metal droplet to designated corner regions while preserving its responsiveness to the electric field. Numerical simulations and conventional AFM experiments on S-shaped and M-shaped spatial channels were first conducted to identify the corner regions as the primary sources of polishing non-uniformity. A robotic posture-control framework was then established through manipulator kinematics, point-cloud-based flow-direction identification, and Rodrigues-matrix-based pose transformation. On this basis, localized secondary polishing was experimentally performed on an S-shaped channel using an AC electric-field-driven liquid-metal abrasive system. The results show that corner-region roughness was significantly reduced and approached the straight-channel benchmark after secondary polishing, demonstrating a marked improvement in inner-surface uniformity. This study provides a practical route for targeted compensation polishing in complex three-dimensional internal channels and offers a new framework for robotic-assisted post-processing of AM-fabricated flow paths. Full article

This study numerically investigates the flow characteristics of submerged impinging jets at a standoff distance of H/d = 3. The computational analysis is performed utilizing large eddy simulation (LES) alongside the one-equation Wray-Agarwal and the two-equation SST k-ω and RNG k-ε turbulence models. The current work emphasizes the hydrodynamic structures developing in the unconfined jet region and the variations in flow behavior at the stagnation zone across a range of impact angles (θ ≤ 90°) at Re (Reynolds number) = 23,400. Compared with PIV data, the Wray-Agarwal model accurately predicts the free-jet flow, whereas the RNG k-ε model excels in the wall-jet region. As the impingement angle increases, the pressure distribution calculated by the LES method gradually approaches the experimental results. When the impinging angle θ = 90°, LES has high prediction accuracy in both regions. In general, under the grid scheme used in this study, RNG k-ε can make a more accurate prediction of the average characteristics of the submerged impinging jet flow field. Full article

Urban micro-tidal canals frequently suffer from severe hypoxia due to restricted hydrodynamic exchange and untreated discharges. Field monitoring during a 2022 mass fish mortality event at the Dongsam tidal canal revealed that during the ‘tidal window gap’—a hydraulic stagnation period required for passive tidal flushing—bottom-layer dissolved oxygen (DO) plummeted to a lethal 0.44 mg/L. To address the limitations of passive tidal exchange, this study proposes a conceptual hybrid water purification framework integrating active ecological interventions: wall-mounted spiral flow aeration for continuous oxygenation and vertical bio-curtains for pollutant interception. By synergizing fluid mechanics with ecological engineering, core design parameters were systematically derived: an effective mixing width ($W_{eff}=2.2 h$), longitudinal spacing ($L_s$ = 13.6$\times W_{eff}$), an optimal root immersion ratio ($D_r/h$ = 0.6), and climate-adaptive planting densities (${\rho }_p\approx$12–32 plants/m²). Additionally, a corrosion-resistant FRP guide rail system was incorporated to facilitate autonomous adaptation to tidal fluctuations. The framework was conceptualized through a prototype design for the Dongsam canal and subsequently scaled to 15 international micro-tidal canals across diverse climatic zones. The optimized bilateral staggered configuration established a continuous 528 m² ecological refuge, ensuring DO levels recover above the critical 3 mg/L threshold. Ultimately, this research presents a comprehensive methodological framework and a flexible engineering toolkit to guide water quality and ecological resilience enhancements in shallow urban waterways worldwide. Full article

This study proposes a heterogeneous fusion path planning framework for unmanned aerial vehicles (UAVs) operating in complex emergency rescue and civil environments. Existing single-mechanism metaheuristics—including Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Genetic Algorithms (GAs)—suffer from fundamental limitations in three-dimensional kinematic path planning: PSO converges rapidly but stagnates at local optima due to population variance collapse; ACO offers robust local exploitation but incurs prohibitive cold-start overhead; GAs maintain diversity at the cost of expensive crossover operations. To address these complementary deficiencies simultaneously, the proposed framework introduces a spherical coordinate representation that reduces computational complexity and naturally enforces UAV kinematic constraints, combined with adaptive weight factors and a serial PSO-ACO fusion strategy, and subsequently incorporates adaptive weight factors. A serial fusion strategy is then introduced, wherein the sub-optimal trajectory generated by the Spherical PSO phase is mapped into the ACO pheromone field via a Gaussian Kernel Density Mapping (GKDM) mechanism, enabling the ACO phase to perform fine-grained local exploitation within a kinematically feasible corridor. Various constraints along the flight path are formulated into distinct cost functions, which cover aircraft track length, pitch angle variation, altitude difference variation, obstacle avoidance, and smoothness; the core task of the algorithm is to find the flight path with the minimum total cost. The proposed algorithm is dedicated to UAV path planning in complex emergency rescue environments (disaster-stricken areas, hazardous zones) and is further applicable to civil low-altitude logistics delivery, industrial facility inspection, ecological environment monitoring and urban air mobility (UAM) scenarios with complex obstacle constraints. It can effectively improve the safety and efficiency of UAVs in reaching rescue points, delivering emergency supplies, conducting disaster surveys, and completing various civil low-altitude operation tasks. Full article

Mountain forests on the western edge of the Sichuan Basin are challenging to monitor at high resolution because rugged topography, cloud cover, and Landsat-7 SLC-off artifacts create data gaps, while the 2008 Wenchuan earthquake and subsequent restoration further alter vegetation dynamics. We fused Landsat 5/7/8/9 surface reflectance with MODIS MOD13Q1 using an index-then-fusion STARFM framework to reconstruct a continuous 30 m NDVI record for 2000–2024 and quantified forest fraction dynamics using annual forest/non-forest maps, transition analysis, and K-means clustering of pixel-wise NDVI trajectories. To identify dominant controls, we applied a multi-output random forest with spatial block cross-validation and SHAP attribution. The fused NDVI agrees well with MODIS across 100,000 samples (R² = 0.953; RMSE = 0.032), and the regional mean NDVI increased from 0.711 (2000) to 0.774 (2024), showing a post-2008 decline–stagnation–recovery pattern. Forest fraction rose from 48.2% to 72.9%, with accelerated gains after 2010 (+21.4%), and improving trajectories dominated (70.95%), concentrating near the Longmenshan fault zone. The driver model generalized well (micro-mean R² = 0.875), and SHAP ranked elevation (32.6%) and initial forest fraction (32.3%) above temperature and precipitation. These results provide high-resolution evidence of mountain forest change and its primary controls to support terrain-informed ecological management. Full article

Background: Successful root canal treatment depends on the synergy between mechanical instrumentation and chemical disinfection. The internal canal geometry, particularly taper configuration, critically influences irrigant flow and penetration. Conventional taper designs tend to displace irrigants coronally, creating stagnation zones and limiting cleaning efficacy. The MEA Inverse Taper^® technique introduces a reversed taper geometry designed to retain irrigant within the canal during shaping, forming a fluid reservoir termed the Radicular Tank (RT). This proof-of-concept study aimed to experimentally demonstrate the formation of the RT generated by the MEA Inverse Taper^® design and to compare its qualitative hydrodynamic and shaping behavior with a conventional rotary system (MTWO). Methods: Standardized transparent canal models were instrumented using either the MEA Inverse Taper^® or MTWO sequence. A 1% methylene blue dye served as a visual tracer to assess potential intracanal retention at successive shaping stages. Standardized photographic documentation and digital image superimposition were used to evaluate residual dye retention, canal morphology, and taper variation. Results: The MEA Inverse Taper^® sequence maintained residual dye in the coronal and middle thirds, confirming the formation of the RT. Compared with MTWO, it produced a more conservative taper, minimized coronal and apical displacement of dye, and preserved canal curvature, removing less coronal dentin. Conclusion: The MEA Inverse Taper^® technique creates a qualitative dye-retention phenomenon (Radicular Tank) that allows continuous instrumentation within a visually persistent dye environment. This novel concept may support disinfection efficiency, alongside preserving dentin structure and reducing mechanical stress on rotary instruments, representing a potential advancement in endodontic shaping and irrigation protocols. Full article