Search Results (2,253)

Pneumatic soft actuators have been drawing considerable attention in the field of soft robotics, thanks to their inherent flexibility, high power density, and safe interaction. However, the strong, intricate coupling between the material’s hyperelastic behavior and the reinforcement of anisotropic fibers creates significant challenges for both analytical modeling and numerical characterization of these actuators. In this paper, we design and fabricate a fiber-reinforced pneumatic soft actuator using Ecoflex 00-30 silicone rubber as the base material and helically wound fibers as the reinforcing layer. We set up a theoretical framework that combines the Neo-Hookean model for isotropic silicone rubber with a strain energy-based formulation for anisotropic wound fibers. This framework describes how the actuator is stretched, expanded, twisted, and bent. Finite element simulations are then carried out, focusing on three key design parameters: winding fiber density (three levels: high, medium, low), air cavity offset distance from the central axis (1, 2, 3, and 4 mm), and air cavity cross-sectional geometry (cube vs. cylindrical). The simulations reveal that a higher winding fiber density promotes more uniform stress distribution across both the strain and confinement layers. In contrast, a low fiber density can lead to local bulging and large stress variations, which ultimately compromises the bending performance. The offset distance of the air cavity from the neutral axis is directly linked to the bending curvature: a larger offset produces greater air cavity deformation and higher actuation efficiency. Furthermore, the cuboid air cavity yields a larger bending angle (experimentally validated up to 90° at 0.045 MPa) and better efficiency, while the cylindrical air cavity distributes stress more evenly across the outer surface of the strain layer and reduces stress concentration at the edges. These findings provide useful quantitative guidance for optimizing the structure of fiber-reinforced soft actuators and establish a framework for hybrid analytical–numerical prediction of their mechanical behavior. Full article

Soft magnetic materials determine the efficiency, size, thermal burden, and reliability of transformers, inductors, electrical machines, electromagnetic interference (EMI) components, and magnetic sensors. This review differs from property-by-property surveys by using a condition-aware, application-driven framework: magnetic performance is compared only together with frequency, peak magnetic flux density, temperature, waveform, direct current (DC) bias, geometry, and processing route. After a concise treatment of coercivity, permeability, saturation polarization, magnetostriction, and loss mechanisms, the major material families are quantitatively compared in terms of magnetic performance, processing, cost, and industrial maturity. The review then maps these families onto grid transformers, high-speed electrical machines, wide-bandgap power converters, integrated magnetics, wireless power transfer, aerospace electrical systems, and radiofrequency components. Particular attention is given to the trade-offs among saturation polarization, permeability, core loss, mechanical strength, thermal stability, manufacturability, and sustainability. Recent advances in strong and ductile soft magnets, wide-temperature ferrites, vortex and easy-plane composites, mixed-powder soft magnetic composites, nanocrystalline flake-ribbon cores, and additive manufacturing are assessed by technology maturity. A prioritized roadmap identifies near-term needs for standardized condition-specific data and manufacturing control, medium-term opportunities in magnetic–thermal co-design and digital twins, and longer-term prospects for adaptive, self-healing, and GHz magnetic architectures. The resulting framework is intended to support both material development and defensible industrial material selection. Full article

A three-ring hexagonal photonic crystal fiber (PCF), with its pitch Λ = 28 µm and airhole radius varied between 7 and 12.6 µm, was analyzed for efficient delivery of a 980 nm EDFA pump and guidance of 1.48–1.55 µm signal wavelengths. Using FEM solutions of the vector wave equation, the effective index, effective area (A_eff), and core region power fraction were obtained across all wavelengths. At 0.98 µm, the PCF exhibits tight confinement, small A_eff, and negligible confinement loss, confirming its suitability for efficient pump absorption. Increasing the airhole radius produced smooth, monotonic growth in A_eff and a slight decrease in the doped region overlap, while pump confinement remained consistently strong. Variations in the core refractive index demonstrated an effective means to control confinement, with A_eff decreasing and loss monotonically reducing as n_core increases. Mode field profiles validated a stable, centered fundamental mode at both the pump and signal wavelengths, with only moderate expansion at longer wavelengths. Overall, the PCF design showed predictable, fabrication-friendly behavior with stable confinement and very low leakage, making it highly suitable for EDFA pump delivery applications. The obtained modal characteristics and confinement behaviors indicate that the proposed structure can provide reliable pump delivery while maintaining stable guidance of signal wavelengths in the EDFA operating band. The simple three-ring geometry also offers a structural advantage for fabrication compared with more complex PCF configurations. Full article

Data movement constrains edge convolutional neural network (CNN) accelerators. We present Weight and Activation Compression for Tensor Traffic (WACT), a lossless framework for 8-bit signed integer (INT8) weights and consumer-facing activations. WACT calibrates a mode, tile geometry, and Rice parameter per invocation-aware tensor identity, freezes the policy, and uses a complete metadata- and alignment-inclusive comparison with strict uncompressed (RAW) fallback. Across five image-classification CNNs with one cold weight load and 320 activation passes per model, WACT reduced measured downstream occupied packet bytes by 44.48% (1.801×) over 78,339 events, with zero decoded-INT8 mismatches. A minimal aligned-RAW sensitivity changed this saving by 0.0293 percentage points. On MobileNetV2, FULL_WACT exceeded the best recalibrated single mode and a matched zero-value-compression-style baseline by at least 5.402 and 8.587 percentage points, respectively. A separate labeled 50,000-image validation measured FP32 and INT8 quantize–dequantize (QDQ) Top-1 accuracies of 72.148% and 71.392%, respectively; the latter used scales frozen from the canonical 32-image calibration subset, denoted S0. Explicitly bounded aggregate cold-start SCALE-Sim modeled-access projections were 11.00–17.70%. The complete WACT policy was evaluated in software, whereas the implemented hardware was limited to the single-tile Rice-mode encoder and decoder paths. The routed 28 nm CMOS blocks had standard-cell areas of 0.010942 and 0.010571 mm², passed post-layout SDF loopback, and consumed 4.939 mW of codec-logic power. The measured downstream-byte reduction therefore provides an energy-saving opportunity whose realization depends on codec overhead and the cost of memory movement in the target hierarchy. Full article

Insulator types and materials vary substantially across power system inspection scenarios, while damage defects occur infrequently; consequently, defect images that match a target insulator type and operating environment are often difficult to obtain. Existing open-source insulator image datasets provide limited coverage of equipment types, scene backgrounds, and defect morphologies. Their direct use for detector training may therefore cause domain mismatch and poor generalization. To address these limitations, this study proposes a scene-domain-adaptive sample expansion method for few-shot damaged-insulator detection. The method adapts a general-purpose pretrained diffusion model to the insulator inspection domain and incorporates three-dimensional (3D) structural constraints to generate targeted samples of damaged insulators. First, low-rank adaptation (LoRA) is used for scene-domain adaptation, enabling the generation model to learn the characteristic geometry, appearance, and material properties of insulators. Second, a 3D model of the target insulator is constructed, and physical damage simulation and edge extraction are applied to obtain geometric guidance maps containing shed boundaries and fracture contours. These maps constrain the locations and shapes of the generated defects. Finally, the geometric guidance is injected into the diffusion process to synthesize damaged-insulator images, which are combined with limited real samples to train detectors for damaged-insulator instances, which were evaluated exclusively on real validation images. Experimental results show that adding a moderate number of generated samples enriches the scarce defect features in the real dataset and improves detector performance. In the mixture-ratio experiment using YOLOv8, mAP@0.5 increased by 8.2 percentage points. Additional experiments with multiple detectors yielded performance gains of varying magnitudes, demonstrating that the generated samples provide an effective supplement to limited, real-world data. The proposed method alleviates the scarcity of insulator defect samples and offers a practical data-augmentation strategy for intelligent inspection of power equipment. Full article

Cooling-water intake basins in coastal power plants may experience particle retention and sediment deposition when complex inlet geometry produces large-scale recirculation and low-velocity zones near intake structures. This study examines the use of submerged barriers to mitigate particle retention in a de-identified coastal power-plant intake basin using hydraulic model experiments and hydraulic-model-supported three-dimensional computational fluid dynamics (CFD). A geometrically consistent model-scale configuration, including the inlet channel, main basin, three intake openings, and two outlet passages, was used to preserve site confidentiality while retaining the essential hydraulic mechanisms. Surface-flow patterns, water-depth variations, and sediment-deposition behavior were measured in the physical model and used to assess the numerical model. The numerical results, supported by the available hydraulic-model observations, reproduced the dominant counterclockwise recirculation and a broadly similar retention-prone region. The simulated water depths agreed closely with the measurements, with relative errors below 0.50% for the finest mesh. A water-depth-based grid-sensitivity assessment using 1,221,165; 2,414,216; and 3,378,840 computational cells further showed that the predicted mean water depths remained within 1.15% of the experimental measurements. The assessed numerical model was then applied to examine submerged-barrier configurations installed near the inlet-to-basin transition, with the barrier-performance interpretation limited to the tested mesh, the assumed representative particle condition, and the available qualitative flow/deposition evidence. Under this assumed particle-tracking condition, the original configuration retained 6989 particles at t = 200 s, whereas the 6 cm submerged barrier reduced the retained-particle count to 4956, corresponding to a reduction of approximately 29.1%. In contrast, the 15 cm emergent barrier increased the retained-particle count to 7573 because it blocked overtopping flow and induced new separated low-velocity regions. These results indicate that, among the tested configurations and under the assumed representative particle condition, the 6 cm submerged barrier yielded the lowest retained-particle count, whereas an excessively high barrier may deteriorate the internal flow structure and increase particle accumulation. Full article

Mine leachate and saline industrial wastewater streams are often treated as liabilities to be remediated or disposed of. These flows often contain substantial water and dissolved mineral resources that can be reclaimed. In this work, a waste-heat-assisted falling-film evaporation reactor was developed and assessed for application as a pre-concentration step before water and mineral recovery processes. Two case studies were considered: synthetic saline wastewater containing 80 g/L Na₂SO₄ and 70 g/L NaCl for salt recovery, and iron-rich mine water containing approximately 4000 mg/L Fe²⁺, 95 mg/L Fe³⁺, and 13,000 mg/L acidity as CaCO₃ for downstream pigment and magnetite recovery. Saline water or mine leachate flows down a bank of vertical conduit pipes as a thin film while air flows through the pipe cores. Heat is transferred to the system from industrial waste gas externally. Psychrometric relationships, heat transfer, energy balances, and techno-economic analysis were used to assess the impact of air temperature, conduit diameter, column height, pipe material, and waste-gas temperature on overall reactor performance. Experiments were carried out to confirm expected psychrometric operation and establish appropriate operating temperatures while confirming the impact of conduit geometry on heat-transfer characteristics. A benchmark case of design evaporation rate equal to 100 L/h was chosen for comparison of all tests. Dry air operation was shown to be technically possible but severely limited by the moisture capacity of air; at 26 °C and 101.3 kPa, approximately 205,000 m³/h of air was required. When using industrial waste heat, the operation changed from psychrometric/mass-transfer-limited to heat-transfer-controlled. Using waste gas entering at 144 °C and exiting at 80 °C reduced airflow requirements to approximately 880 m³/h, allowing a much more compact reactor design with approximately 635 (12 mm diameter) conduit pipes. Relative to the 40 °C air benchmark, electrical power was reduced from approximately 24.7 kW to 2.9 kW, and screening-level reactor cost by ~84%. Findings demonstrated that appropriate waste heat enables the application of evaporation if there is sufficient local heat flux. Smaller conduit diameters, sufficient column height, and greater waste-gas inlet temperatures were all beneficial. Choice of material required trade-offs between heat-transfer coefficient, corrosion, and material cost. Full article

Reversible Solid Oxide Cells (rSOCs) are highly efficient energy conversion systems for power generation in fuel cell mode (SOFC) and energy storage in electrolysis mode (SOEC). These devices are typically manufactured through multi-step processing routes based on conventional functional ceramic fabrication techniques, such as tape-casting, extrusion, screen-printing and spraying. In this work, an alternative mold-casting approach is proposed for the fabrication of planar electrolyte-supported rSOCs. Electrolytes made of 8 mol% yttria-stabilized zirconia (YSZ) were prepared via an aqueous gel-casting process using agarose as the gelling agent. The casting molds were fabricated by 3D printing with polylactic acid (PLA) filament. Dense electrolytes with well-controlled geometries were successfully obtained. Complete cells were produced using porous Ni–YSZ as a fuel electrode and porous lanthanum strontium manganite–YSZ. The cells were microstructurally characterized, and their electrochemical performance was evaluated under both SOFC and SOEC operating conditions at 800–900 °C. At 900 °C, the cell achieved a peak power density of 220 mW cm⁻² in fuel cell mode and an injected current density of 340 mA cm⁻² at 1.3 V in electrolysis mode. Mid-term galvanostatic testing in SOFC mode at 850 °C for 400 h demonstrated good durability and structural stability of the fabricated cells. After the initial stabilization period, the cell exhibited a low degradation rate of 3 mV kh⁻¹. Full article

The 4 km/15 min downward surface shortwave radiation (DSSR) product from Fengyun-4B (FY-4B)/AGRI shows great potential for solar energy assessment in China, but its applicability requires further validation. This study conducts a comprehensive evaluation of the FY-4B DSSR product over Guangxi for 2025, using ground-observed irradiance from a dense network of 101 photovoltaic (PV) power stations. The overall comparison shows a correlation coefficient (R) of 0.84, a root-mean-square error (RMSE) of 161.78 W/m², a relative prediction error (RPE) of 51.02%, and a mean bias error (MBE) of 56.23 W/m², indicating systematic overestimation. Seasonally, the largest discrepancies occur in spring (MBE = 85.27 W/m², RPE = 53.12%) and summer (R = 0.82, RMSE = 184.10 W/m²). Diurnally, retrievals are most reliable around 09:00–13:00 local time, deteriorating notably in the early morning and, especially, the afternoon and evening. Spatially, errors are larger in the hilly, elevated terrain of northwestern Guangxi (e.g., Hechi) than in flatter southern and coastal cities, with RPE rising from roughly 40–60% at lower elevations to around 80% above 600–700 m. Sky-condition classification confirms that data quality follows clear > cloudy > overcast sky, while AOD-binned analysis shows aerosol loading playing a secondary but non-negligible role, especially under high-AOD pollution events. Solar zenith angle (SZA) also strongly affects accuracy: R peaks around 0.75–0.8 in the 30–50° SZA range and drops below 0.4 beyond about 75°. This study offers the most spatially and dimensionally comprehensive validation of FY-4B DSSR over Guangxi to date, characterizing accuracy across seasonal, diurnal, spatial, cloud, aerosol, solar-geometry, and elevation dimensions using a denser ground-truth network than previously available, with direct implications for photovoltaic resource assessment and power forecasting in subtropical hilly regions. Full article

This paper comprehensively investigates the ultraviolet (UV) nanosecond laser fabrication of micro-groove textures on planar PEEK surfaces, as well as their surface performance in terms of wettability and frictional properties. Firstly, a three-dimensional finite element model, incorporating a moving Gaussian heat source, solid heat transfer and deformed geometry, was established to simulate the transient temperature field and ablation profile of PEEK during UV laser ablation. The predicted groove depth agreed with the experimental value with a low deviation of 11.19%. Based on the simulation and single-factor experiments, the optimized single-track laser parameters were determined as a laser power of 1.2 W, a scanning speed of 100 mm/s and a repetitive frequency of 100 kHz. Secondly, systematic single-factor and multi-pass laser ablation experiments of PEEK surfaces were conducted to fabricate micro-groove textures with precisely tailored geometric parameters. Furthermore, ablated surface characterization showed that the laser-textured surfaces exhibited increased roughness, apparent crystallinity up to 22.13%, and pronounced anisotropic wettability, with improved liquid spreading along the groove direction and restricted spreading across the grooves. Finally, fretting wear tests under simulated body fluid lubrication were carried out. The research findings reported in this paper provide a systematic theoretical and experimental basis for the application of UV nanosecond laser surface texturing in the fabrication of PEEK-based components. Full article

Wireless power transfer (WPT) can eliminate moving power-supply harnesses in automotive power-seat systems, but seat travel and nearby metallic structures cause substantial variations in magnetic coupling and electromagnetic loss. This paper proposes a structure-aware, partially overlapped segmented transmitter and evaluates two predefined excitation states according to receiver position. In the single-segment state, only the reference segment CP1 is energized; in the simultaneous dual-segment state, CP1 and the adjacent segment CP2 are energized together. Three-dimensional finite element method (FEM) simulations compare candidate transmitter structures and evaluate the electromagnetic influence of the aluminum lower rail, steel upper rail, and steel seat frame. The transmitter geometry is determined by considering mutual inductance, winding loss, structural eddy-current loss, and partial-overlap characteristics. A three-coil equivalent circuit clarifies the branch-current distribution, and a two-state switched-capacitor network accommodates the different equivalent transmitter impedances. A 100 W, 110 kHz prototype separately evaluates representative states at x = 0 and 80 mm; automatic position-based state switching is not implemented. At x = 0 mm, CP1-only excitation achieves 78.79% efficiency. At x = 80 mm, CP1 + CP2 excitation produces 32.13 V and 72.15%, compared with 18.78 V and 67.84% under CP1-only excitation, thereby satisfying the 30 V minimum output requirement. Full article

A girth cycle refers to a cycle that has the minimum length within a graph. The graphs $D(k,q)$ form an important family of algebraically defined bipartite graphs over finite fields, and their short-cycle structure is closely related to questions in extremal graph theory and finite geometry. Motivated by the problem of determining the edge-girth-regular parameter of $D(k,q)$, we determine the exact number of girth cycles in $D(4,q)$ for every prime power q. Our proof uses a convenient isomorphic model $\Gamma (4,q)$ and edge-transitivity to reduce the global enumeration to counting the girth cycles containing one fixed edge. Specifically, we prove that when q is odd with $q>3$, the number of girth cycles in $D(4,q)$ is $q^5{(q-1)}^2(q-3)/8$. Moreover, when q is even, the number of girth cycles in $D(4,q)$ is $q^5{(q-1)}^2(2q-3)/8$. When $q=3$, the girth is 12 and the number of girth cycles is 729. Together, these results resolve the case $k=4$ of the problem posed in our earlier work. Full article

Building Information Modeling (BIM)-enabled performance assessment workflows for rural constructions remain relatively unexplored. This is even more important for buildings implementing process-oriented systems, such as airflow networks. This study presents a BIM-integrated framework for the early-stage design and performance assessment of rural constructions, with application to solar barn dryers and their ventilation systems through reduced-order airflow-network modeling. The proposed workflow combines parametric BIM-based geometry generation with lumped-parameter fluid-dynamic modeling to evaluate the influence of airflow-network topology on pressure losses, airflow distribution, fan power demand, and energy consumption. Nine BIM-generated design alternatives and ten geometric parameter sets were investigated under equivalent operating conditions. The airflow system was represented as a pressure-driven network including solar air panels, ducts, collectors, fan chambers, ventilation channels, and drying cells, accounting for both localized and distributed pressure losses. Results show that airflow-network geometry significantly affects system performance. Configurations characterized by more compact and aerodynamically efficient layouts reduced cumulative pressure losses by approximately 10–20% compared with less optimized solutions. More efficient designs enable reductions in required airflow rates of ~22% and in fan power demand of up to ~40% (≈11–18 kW). The most efficient configurations also exhibited lower annual energy consumption while maintaining the minimum overpressure required for effective hay drying. The study demonstrates how BIM environments can support physics-informed comparative evaluation of alternative ventilation layouts during the early design stage, extending BIM applications toward performance-oriented design and digital management of agricultural building systems. The proposed methodology provides a computationally efficient design-support framework that may also apply to other controlled-environment agricultural infrastructures governed by airflow-network dynamics. Full article

Overlapping optical cells create geometry-dependent inter-cell interference, while receiver-geometry and channel-estimation errors can reverse the effective non-orthogonal multiple access (NOMA) decoding order and increase successive interference cancelation (SIC) failures. This paper develops a chance-constrained receiver–scheduler co-design framework for a multi-cell NOMA visible-light communication network with an asymmetrically clipped DC-biased optical orthogonal frequency-division multiplexing physical layer. Correlated position, photodetector-orientation, and channel-estimation errors are propagated through nonlinear geometry-based scenarios. For each SIC direction, a joint three-SINR event defines a layer-, resource-, and direction-labeled probabilistic decodability graph. Candidate NOMA and orthogonal modes are screened on optimization scenarios, admitted by independent one-sided confidence bounds, and selected through resource-constrained mixed-integer linear programming. With the matching fixed, hierarchical powers are adapted under empirical conditional-value-at-risk constraints using trust-region sequential quadratic programming. Because candidate-edge certificates need not remain valid after global matching and power redistribution, the frozen complete assignment is independently recertified before held-out testing. Under the specified uncertainty generator, the proposed method maintains selected-pair outage probabilities of approximately $2.7\times {10}^{-3}$–$3.3\times {10}^{-3}$ over the half-power-angle sweep, compared with $0.027$–$0.060$ for nominal-CSI allocation. Additional experiments quantify network-wide outage, model misspecification, unbalanced deployments, feasibility, and computational cost. The results support reliable slow-timescale scheduling under the adopted link and uncertainty models, without implying distribution-free, waveform-level, or real-time guarantees. Full article

Hybrid solar–thermal energy harvesting systems are an important advancement in renewable energy technology, enabling simultaneous production of electrical power and useful thermal energy within a single compact platform. However, their performance is often limited by poor heat transfer and inefficient mass transport of working fluids, leading to photovoltaic thermal degradation and significant exergy losses. This study aims to optimize heat and mass transport processes in a hybrid solar–thermal mechanical system to enhance energy recovery and ensure long-term operational reliability. A three-dimensional numerical model based on the finite volume method (FVM) was developed using the governing equations of continuity, momentum, and energy conservation. A Multi-Objective Genetic Algorithm (MOGA) was employed to determine optimal microchannel geometries by analyzing variable cross-section effects on flow behavior and thermal boundary layer disruption. At the Reynolds number of 2000, the optimized configuration increases the average Nusselt number by 43.5% compared to a smooth channel. Consequently, the photovoltaic operating temperature decreases by 12.6 °C, improving electrical efficiency by 9.3%. The system achieves a maximum thermal efficiency and net energy gain of 76.8%, while maintaining an acceptable 16.3% increase in pumping power. The results confirm that optimizing mass transport is essential for effective thermal regulation and improved energy conversion performance, providing a strong foundation for high-efficiency solar collector design. Full article