Search Results (457)

This work presents a case study detailing an end-to-end workflow for reconstructing a damaged plastic component when no original design data are available. The approach integrates microscopic inspection of fracture surfaces, selective enhancement of 3D scan data, CAD-based modification of geometrically and functionally critical features, and continuous fibre-reinforced additive manufacturing. The component examined functions as a structural mounting element in an automotive lighting module, where it maintains correct alignment and provides mechanical support in service. The study concentrates on the cost-effective replacement of unique parts produced in very small batches. The results indicate that this fracture-analysis-informed reverse engineering strategy offers a practical solution for reproducing low-volume, custom, or replacement components in situations where standard manufacturing methods are not economically viable. The reconstructed part matched the geometry necessary for installation in the original assembly and successfully passed initial functional checks; however, this study did not include quantitative measurements of mechanical performance. Full article

Personal thermal management systems, particularly neck fans, are increasingly popular for providing hands-free, localized cooling to enhance user comfort. We investigate the aerodynamic performance of compact forward-curved centrifugal impellers (<50 mm in diameter) with 30, 28, and 24 blades, selected through benchmarking of commercial products. A baseline impeller and casing were reverse engineered by using 3D scanning and CAD modeling methods, followed by blade count modifications under consistent geometric constraints. CFD simulations in ANSYS Workbench 19.1 were conducted to examine velocity fields, pressure distribution, and flow rate. Results indicate that blade number significantly influences airflow and efficiency: the 28-blade impeller achieved the highest outlet velocity, while the 30-blade configuration provided smoother pressure recovery but higher flow resistance. These insights aid the design of more efficient wearable cooling devices. Full article

This study presents a stator-focused electromagnetic optimization of a 350 W, 27-slot, 30-pole outer-rotor brushless direct current (BLDC) motor developed for electric scooter applications. Unlike conventional redesign approaches that modify rotor topology or overall motor dimensions, the proposed methodology preserves the rotor structure and external geometry of a commercially validated reference motor and improves performance primarily through targeted stator geometric refinement, with minor adjustments in the winding configuration. A two-stage optimization strategy combining parametric analysis and genetic algorithm (GA)-based multi-objective optimization is implemented to minimize cogging torque and torque ripple while maximizing efficiency. Finite element analyses (FEA) were conducted to evaluate back electromotive force (back-EMF) characteristics, magnetic flux density distribution, torque behavior, and current density. Experimental validation confirms a 54.86% reduction in cogging torque (from 257 mNm to 116 mNm), a 19.6% decrease in torque ripple, a 6.17% reduction in maximum current density, and a 2–3% improvement in efficiency within the nominal load range (5.2–6.45 Nm), reaching 85.69% efficiency at 350 W output power. The results demonstrate that systematic stator geometry optimization, supported by minor winding modifications, can significantly enhance efficiency, torque smoothness, and thermal margin without increasing motor size, rated power, or manufacturing complexity. This work provides a practical and manufacturable design pathway for high-performance outer rotor BLDC motors in light electric vehicle (LEV) propulsion systems. Full article

Hydrodynamic cavitation in Venturi devices is strongly influenced by geometry and is increasingly considered as a non-thermal route for process intensification in continuous-flow applications, including water-treatment contexts. However, Venturi design practice still relies largely on incremental modifications of circular throats and on loosely formalized heuristics, which limits reproducibility and systematic comparison. This work presents a reproducible geometry-driven framework for the design of an equal-width Venturi throat under a fixed transverse envelope constraint. Two parameterized configurations are considered: a constant-width Reuleaux-triangle cross section (VRA) and a controlled axial-twist variant (VRAt). A minimal set of geometric design indicators is formulated in terms of throat flow area, wetted perimeter, hydraulic diameter, and geometric near-wall coverage within a prescribed thickness; for VRAt, a dimensionless kinematic factor is additionally introduced to quantify the path-length increase associated with the imposed twist. Under equal-width conditions, the Reuleaux section preserves the wetted perimeter of the circular reference while reducing flow area, whereas the twisted variant preserves the same transverse throat metrics and isolates twist as an explicit geometric design variable. The contribution is methodological: it provides a reproducible framework for early-stage geometric design and comparison of Venturi configurations relevant to hydrodynamic cavitation. It does not, by itself, report experiments, validation, or hydraulic, cavitation, or water-treatment performance predictions. Full article

Laser Powder Bed Fusion (LPBF) enables the fabrication of complex titanium alloy components with high geometric freedom; however, surface integrity and tribological performance remain critical limitations for sliding-contact applications in biomedical and aerospace systems. In this study, the influence of in-layer laser remelting on the microstructure, surface topography, and dry sliding tribological behavior of LPBF-fabricated Ti-6Al-4V ELI (Grade 23) is systematically investigated. Disc-shaped specimens were produced using single-scan (SS) and double-scan (DS, in-layer remelting) strategies and tested in ball-on-disc configuration against AISI 52100 steel at a constant normal load of 10 N and three sliding speeds of 0.10, 0.15, and 0.20 m·s⁻¹. Microstructural and phase-related characteristics were analyzed by X-ray diffraction combined with Rietveld refinement and Warren–Averbach analysis, revealing that the DS strategy increases retained β-phase fraction (up to 5.2%) and promotes crystallite coarsening relative to the SS condition, without significantly altering bulk hardness. Surface morphology examined by SEM/EDS and AFM revealed a more homogeneous near-surface topography in the DS condition. Tribological results indicate that sliding speed governs steady-state friction and wear, with specific wear rates increasing progressively from 5.13 to 5.44 × 10⁻⁴ mm³·N⁻¹·m⁻¹ for SS and from 6.47 to 7.52 × 10⁻⁴ mm³·N⁻¹·m⁻¹ for DS across the investigated speed range. The DS specimens exhibited higher wear rates than the SS condition across all tested speeds, while steady-state COF values remained comparable between strategies, indicating that remelting-induced microstructural modifications affect material removal mechanisms without proportionally destabilizing the frictional regime. These findings suggest that in-layer laser remelting represents a process-integrated parameter with measurable consequences for surface integrity and tribological performance, though the generalizability of these results warrants validation across broader experimental conditions. Full article

The interaction between circular piers and turbulent open-channel flow generates complex three-dimensional structures, including horseshoe vortices at the pier base and wake vortices downstream. These structures increase vertical velocities, pressure fluctuations, and shear stresses, contributing to erosion and structural instability. Although these phenomena have been widely studied, limited attention has been given to surface geometric modifications as a flow-control strategy. This study employs Large Eddy Simulation (LES) to evaluate the influence of a hexagonal dimple pattern on circular piles in a free-surface channel. The dimples were defined by varying diameter, depth, and spacing to reduce vertical velocity and alter vortex formation. The computational domain represents a 0.40 m wide, 12 m long, and 1.2 m high rectangular channel, with an inlet mass flow of 9.4 kg/s and 0.10 m water depth. Model validation against particle image velocimetry (PIV) data showed 99% correlation, confirming numerical accuracy. Results demonstrate that textured surfaces modify flow dynamics by enhancing kinetic energy dissipation and generating micro-vortices that weaken dominant structures. The optimal configuration (6 mm diameter, 2 mm depth, 1 mm spacing) reduced downward vertical velocity by 42% and wake vortex shedding frequency by 24%, indicating improved hydraulic stability and erosion mitigation potential. Full article

Vertical axis wind turbines (VAWTs) suffer from dynamic stall (DS) at low tip-speed ratios (λ), where cyclic variations in angle of attack (α) dominate the blade aerodynamics, severely undermining aerodynamic performance and power extraction. The coupled influence of airfoil parameters on DS remains unexplored. To address this gap, a fully coupled parametric study using 126 incompressible URANS simulations is conducted, examining three geometric parameters of symmetric airfoils: maximum thickness (t/c), chordwise position of maximum thickness (x_t/c), and leading-edge (LE) radius index (I). The results show that coupled geometric modification fundamentally alters the stall mechanism, shifting it from abrupt, LE-driven separation toward a gradual, trailing-edge (TE)-controlled process as airfoils transition from thin, forward-x_t/c profiles to thicker configurations with aft x_t/c and reduced I. This transition enhances boundary-layer (BL) stability, delays DS onset, weakens dynamic stall vortex (DSV) formation, and mitigates unsteady aerodynamic loading. Within the investigated design space, the best-performing configuration (NACA0024–4.5/3.5) achieves a 73% increase in turbine power coefficient (C_P) relative to the baseline airfoil (NACA0018–6.0/3.0), mainly through passive control of BL separation and vortex development. These findings highlight the limitations of single-parameter optimization and establish a physics-based, coupled-design framework for mitigating DS-induced performance losses in VAWTs. Full article

To address the problems of high digging resistance, elevated energy consumption, and severe soil adhesion encountered during mechanized potato harvesting, a bionic potato digging shovel inspired by the corrugated dorsal structure of the white grub was developed. Based on reverse-engineered geometric curves, two longitudinally corrugated shovel models (L-S-1 and L-S-2) were constructed, and a coupled soil–potato–shovel model was established using the Discrete Element Method (DEM) to evaluate soil disturbance characteristics and digging resistance at a forward speed of 0.5 m/s and an entry angle of 35°. The simulation results indicated that the longitudinally corrugated shovel L-S-2 exhibited the best overall performance, reducing digging resistance by 13.87% and increasing the soil fragmentation rate by 20.67% compared with a conventional flat shovel (P-S). Using L-S-2 as the baseline design, additional DEM simulations were conducted at forward speeds ranging from 0.4 to 0.6 m/s to systematically investigate the influence of operating speed on digging performance. To further enhance anti-adhesion performance, a composite bionic shovel (H-L-S-2) was developed by embedding polytetrafluoroethylene (PTFE) hydrophobic material into the surface of L-S-2 and reinforcing the shovel tip using laser cladding. Soil-bin experiments were then performed under controlled conditions with forward speeds of 0.4–0.6 m/s and soil moisture contents of 15–20% at an entry angle of 35°, and the results showed an average resistance reduction rate of 17.46%, with a maximum reduction of 18.02%. Both DEM simulations and soil-bin tests confirmed the effectiveness of the composite bionic shovel in reducing soil adhesion, with the number of adhered soil particles decreasing by 41.2% in simulations and the mass of adhered soil reduced by 37.5% in physical tests. These results demonstrate that coupling a bionic corrugated structure with surface material modification can effectively reduce digging resistance, enhance soil fragmentation, and mitigate soil adhesion, providing a practical approach for optimizing the design of potato digging shovels. Full article

The complexity of an extrusion die profile is determined by its geometry. Various metrics such as the complexity index, shape factor, and form factor are used to quantify how geometric intricacy affects production costs, die life, energy consumption, product quality, and overall manufacturability. Bearing geometry plays a critical role in controlling metal flow and tool life in aluminum extrusion. In this study, a simulation-based investigation is performed to investigate the influence of bearing geometry on extrusion behavior using the finite element method. Two extrusion dies are examined: A single-cavity die with uniform bearing geometry and a dual-cavity die with controlled bearing geometry modification in one cavity. The results show that the bearing modification in the dual-cavity die causes severe flow imbalance, with exit velocity deviations. This imbalance leads to localized pressure amplification, increased thermal gradients, and stress concentration in critical die regions. In contrast, the single-cavity die, due to its simple geometry, exhibits uniform flow, stable pressure evolution, and low tool stress. These findings demonstrate the high sensitivity of multi-cavity extrusion dies to bearing geometry and highlight the importance of simulation-driven die design for achieving balanced flow and improved tool performance. Full article

The chlorophyll molecule is considered a low-cost material, easy to synthesize, and easily extracted from plant leaves. It exhibits high chemical stability, structural flexibility, and high absorbance ability at the visible range of electromagnetic radiation. In this work, the geometrical, electronic, and optical properties of pure, dissolved, and doped chlorophyll (C1) natural organic dye were computed by density functional theory (DFT) and time-dependent density functional theory (TD-DFT). The solvents considered include water (H₂O), acetone (C₂H₆O), dichloromethane (CH₂Cl₂), chloroform (CH₃Cl), and dimethyl-sulfoxide (DMSO) (C₂H₆OS). The solar photovoltaic parameters, such as light-harvesting efficiency (LHE), oscillation strength (f), free energy of electron injection (${\Delta \mathrm{G}}_{\mathrm{I}\mathrm{n}\mathrm{j}.}$) and regeneration (${\Delta \mathrm{G}}_{\mathrm{R}\mathrm{e}\mathrm{g}.}$), open-circuit voltaic (V_OC), and efficiency ($\eta$), were also investigated. The evaluated energy gap slightly shifted from 1.920 eV to 1.980 eV based on the solvent polarity, while the UV-Visible absorption spectrum red-shifted from 422.3 nm to 439.8 nm, improving the overall efficiency up to 21.5% in DMSO solvent. The (LHE) and (${\Delta \mathrm{G}}_{\mathrm{I}\mathrm{n}\mathrm{j}.}$) properties regarding Cl molecules improved up to 69.1% and −1.384 eV when dissolved in chloroform and DMSO solvents, respectively. Doping C1 molecule via metal transition atoms such as zinc (Zn), nickel (Ni) and copper (Cu) further modified the optical and photovoltaic performance. Doped C1 molecule via Cu atom shows the best photonic results, including the highest open-circuit voltage (V_oc) and conversion efficiency ($\mathrm{Ƞ}$), while the Ni-doped C1 dye displays the longest lifetime, 1.699 µs, and the highest electronic coupling constant, 1.975 eV; thus, it has the superior photovoltaic performance. These results demonstrate that both solvents and transition metal atom modification significantly improve C1 performance, making metal-doped C1 a promising low-cost and eco-friendly sensitizer for dye-sensitized solar cells (DSSCs). Full article

This study aims to address the acoustic resonance control problem of a three-dimensional nose landing gear (NLG) cavity. We propose a refined numerical approach based on an eigenvalue solver for the Helmholtz equation. A high-order finite element method (FEM) combined with perfectly matched layer (PML) boundary conditions was employed to accurately capture complex eigenmodes. The radiation damping characteristics of the system were then quantitatively characterized using the quality factor (Q-factor) and resonance frequency. Results indicate that the Helmholtz-type (0,0,0) mode dominates the cavity’s resonance response, with its frequency coinciding with the shear layer-driven Rossiter mode. This study reveals a strong coupling mechanism with the shear-layer-driven Rossiter mode at Mach 0.57, confirming that this interaction is the primary driver of cavity aeroacoustic tonal noise. Taking radiation damping as the core design parameter, a systematic sensitivity analysis was conducted on geometric modifications: aft door length, front door angle, cavity volume, and the introduction of a longitudinal gap. Key findings: shortening the aft door reduces the resonance peak by 8.5 dB; introducing a longitudinal gap with a 10% width reduces the Q-factor by approximately 50%; a combined control strategy (2.5% gap width and 6% cavity volume reduction) achieves 4.9 dB of noise attenuation. Finally, this study establishes a validated acoustic-damping control framework, providing quantitative design criteria and technical guidance for aeroacoustic noise control of NLG cavities. Full article

To enhance the aerodynamic performance of organic Rankine cycle (ORC) turbines under increasing energy demands, surrogate-based optimization was applied to a 100 kW ORC turbine rotor. Four representative surrogate models—a radial basis neural network (RBNN), Kriging, response surface approximation (RSA), and a PRESS-based weighted (PBW) ensemble—were comparatively evaluated under identical numerical conditions. Independent optimizations of the first- and second-stage rotors enabled an examination of how different design variable space characteristics influenced surrogate predictive behavior. A fractional factorial sampling strategy was used to construct the training dataset, and learning curve analysis was conducted to assess sample size adequacy. Sensitivity estimation revealed distinct response surface characteristics between stages, allowing the interpretation of variations in surrogate stability. In both stages, geometric modifications were primarily concentrated near the outlet blade angle, identified as a dominant variable influencing efficiency. CFD validation confirmed that surrogate-based exploration successfully identified improved rotor geometries. Flow-field analysis indicated reduced entropy generation near the trailing edge region, suggesting the mitigation of aerodynamic losses. The results demonstrate that surrogate-based optimization can reliably improve turbine performance within a bounded design space, while the relative effectiveness of surrogate models depends on the sensitivity structure of the underlying problem. Full article

The geometric variability of industrial components represents a persistent challenge in robotic arc welding, particularly in high-volume manufacturing environments where parts are positioned in fixtures based on nominal CAD assumptions. Even moderate deviations in dimensions or seating conditions can lead to weld defects, rework, and reduced process capability when conventional offline programming is employed. This paper presents an applied industrial workflow for adaptive robotic welding trajectory correction that integrates full-field 3D optical metrology with a data-driven deep reinforcement learning (DRL) model. Prior to welding, each component is scanned using a structured-light 3D system, and critical geometric deviations are extracted relative to the nominal CAD model. These deviations define a compact state representation that is mapped, via a trained DRL agent, to corrective translational and rotational adjustments of the welding trajectory. Importantly, all trajectory corrections are computed offline, ensuring compatibility with standard industrial robot controllers and avoiding real-time computational overheads. The proposed approach is validated using real production data from an industrial batch of 5000 components characterized by significant dimensional variability and limited process capability. Experimental results demonstrate a reduction in welding defects exceeding 90%, elimination of rework associated with improper part positioning, and an improvement of the overall process performance to a sigma level of 5.219. The results show that combining 3D optical metrology with learning-based trajectory adaptation enables robust compensation of part-level geometric deviations without mechanical fixture modifications. The proposed method provides a practical and scalable solution for improving welding quality in manufacturing environments affected by upstream variability and imperfect part positioning. Full article

The proliferation of intelligent sensor networks in urban surveillance and remote sensing has triggered the explosive growth of unstructured visual sensor data. Accurately retrieving targets from these massive streams based on complex cross-modal user intents remains a critical bottleneck for efficient intelligent perception. Composed Image Retrieval (CIR) addresses this by enabling retrieval via a multi-modal query that combines a reference image with semantic control signals. However, existing methods often struggle with abstract instructions in real-world scenarios. Consequently, models often suffer from feature distribution shifts due to focus ambiguity, as well as semantic erosion caused by highly entangled visual and textual features. To address these challenges, we propose a geometry-based Selective Orthogonal Projection Network (SOP). First, the Selective Focus Recovery module quantifies instruction uncertainty via information entropy and calibrates shifted query features to the true target distribution using structural consistency regularization. Second, to ensure data fidelity, we introduce Orthogonal Subspace Projectionand Geometric Composition Fidelity. These mechanisms employ Gram–Schmidt orthogonalization to decouple features into a constant visual base and an orthogonal modification increment, restricting semantic modifications to the null space. Extensive experiments on FashionIQ, Shoes, and CIRR datasets demonstrate that SOP significantly outperforms SOTA methods, offering a novel solution for efficient large-scale sensor data retrieval and analysis. Full article

The recent development of 3D generative AI encompassing generation and editing technologies has been increasingly investigated to advance immersive applications. To enrich visual aesthetics, 3D stylization techniques focus on transferring artistic effects from reference style images to 3D scenes. However, existing 3D stylization techniques primarily focus on global style transfer, which can result in unwanted modifications to background regions and a lack of localized control. To address these limitations, we propose LocalGaussStyle, a novel approach for localized style transfer on scenes represented by 3D Gaussian splatting. The proposed pipeline consists of two phases: object localization and localized stylization. First, 2D instance segmentation masks are projected into a 3D scene to precisely localize target objects. Next, a boundary-aware optimization is designed to perform style transfer and mitigate style leakage caused by the spatial overlap of Gaussians. In addition, geometry-decoupled adaptive densification (GDAD) is employed to enhance the geometric resolution of Gaussians within the target object, thereby improving the representation capacity. The LocalGaussStyle facilitates high-fidelity style transfer that preserves the geometry and appearance of the non-target regions. In terms of style fidelity and background preservation, the effectiveness and efficiency of the proposed method are demonstrated through extensive experiments conducted on various scenes and reference style images. Full article