Search Results (610)

The wind energy sector is experiencing substantial growth, with global wind turbine capacity increasing and projected to expand further in the coming years. However, rain erosion on the leading edges of turbine blades remains a significant challenge, affecting both aerodynamic efficiency and structural longevity. The associated degradation reduces annual energy production and leads to high maintenance costs due to frequent inspections and repairs. To address this issue, researchers have developed numerical models to predict blade erosion caused by water droplet impacts. This study presents a finite element analysis model in Abaqus to simulate the interaction between a single water droplet and wind turbine blade material. The novelty of this model lies in evaluating the influence of several parameters on von Mises and S33 peak stresses in the leading-edge protection, such as friction coefficient, type of contact, impact velocity, and droplet diameter. The findings provide insights into optimising LEP numerical models to simulate rain erosion as closely as possible to real-world scenarios. Full article

The conductors of high-speed railway OCSs (Overhead Contact Systems) are susceptible to conductor galloping due to the impact of natural elements such as strong winds, rain, and snow, resulting in conductor fatigue damage and significantly compromising train operational safety. Consequently, monitoring the galloping status of conductors is crucial, and instance segmentation techniques, by delineating the pixel-level contours of each conductor, can significantly aid in the identification and study of galloping phenomena. This work expands upon the YOLO11-seg model and introduces an instance segmentation approach for galloping video and image sensor data of OCS conductors. The algorithm, designed for the stripe-like distribution of OCS conductors in the data, employs four-direction Sobel filters to extract edge features in horizontal, vertical, and diagonal orientations. These features are subsequently integrated with the original convolutional branch to form the FDSE (Four Direction Sobel Enhancement) module. It integrates the ECA (Efficient Channel Attention) mechanism for the adaptive augmentation of conductor characteristics and utilizes the FL (Focal Loss) function to mitigate the class-imbalance issue between positive and negative samples, hence enhancing the model’s sensitivity to conductors. Consequently, segmentation outcomes from neighboring frames are utilized, and mask-difference analysis is performed to autonomously detect conductor galloping locations, emphasizing their contours for the clear depiction of galloping characteristics. Experimental results demonstrate that the enhanced YOLO11-seg model achieves 85.38% precision, 77.30% recall, 84.25% AP@0.5, 81.14% F1-score, and a real-time processing speed of 44.78 FPS. When combined with the galloping visualization module, it can issue real-time alerts of conductor galloping anomalies, providing robust technical support for railway OCS safety monitoring. Full article

The coffee-ring effect, while harnessed in diverse fields such as biosensing and printing, poses challenges for achieving uniform particle deposition. Controlling this phenomenon is thus essential for precision patterning. This study proposes a novel method to regulate coffee-ring formation by tuning surface wettability via integrated nanoporous and hexagonal microstructures. Four distinct surface types were fabricated using UV nanoimprint lithography: planar, porous planar, hexagonal wall, and porous hexagonal wall. The evaporation behavior of colloidal droplets and subsequent particle aggregation were analyzed through contact angle measurements and confocal microscopy. Results demonstrated that nanoscale porosity significantly increased surface wettability and accelerated evaporation, while the hexagonal pattern enhanced droplet stability and suppressed contact line movement. The porous hexagonal surface, in particular, enabled the formation of connected dual-ring patterns with higher particle accumulation near the contact edge. This synergistic design facilitated both stable evaporation and improved localization of particles. The findings provide a quantitative basis for applying patterned porous surfaces in evaporation-driven platforms, with implications for enhanced sensitivity and reproducibility in surface-enhanced Raman scattering (SERS) and other biosensing applications. Full article

Lithium metal is a promising anode material for next-generation batteries due to its high specific capacity and low density. However, conventional mechanical processing methods are unsuitable due to lithium’s high reactivity and adhesion. Laser cutting offers a non-contact alternative, but photothermal effects can negatively impact the cutting quality and electrochemical performance. This study investigates the influence of pulse duration on the cutting-edge characteristics and electrochemical behavior of laser-cut 20 µm lithium metal on 10 µm copper foils using nanosecond and picosecond laser systems. It was demonstrated that shorter pulse durations significantly reduce the heat-affected zone (HAZ), resulting in improved cutting quality. Electrochemical tests in symmetric Li|Li cells revealed that laser-cut electrodes exhibit enhanced cycling stability compared with mechanically separated anodes, despite the presence of localized dead lithium “reservoirs”. While the overall pulse duration did not show a direct impact on ionic resistance, the characteristics of the cutting edge, particularly the extent of the HAZ, were found to influence the electrochemical performance. Full article

Lightning strikes pose a significant risk during outdoor activities. The connection between conventionally used rescue blankets in alpine emergencies and the risk of lightning injury is unclear. This experimental study investigated whether rescue blankets made of aluminum-coated polyethylene terephthalate increase the likelihood of lightning injuries. High-voltage experiments of up to 2.5 MV were conducted in a controlled laboratory setting, exposing manikins to realistic lightning discharges. In a balanced test environment, two conventionally used brands were investigated. Upward leaders frequently formed on the edges along the fold lines of the foils and were significantly longer in crumpled rescue blankets (p = 0.004). When a lightning strike occurred, the thin metallic layer evaporated at the contact point without igniting the blanket or damaging the underlying plastic film. The blankets diverted surface currents and prevented current flow to the manikins, indicating potentially protective effects. The findings of this experimental study suggest that upward leaders rise from the edge areas of rescue blankets, although there is no increased risk for a direct strike. Rescue blankets may even provide partial protection against exposure to electrical charges. Full article

Pest management is undergoing a transformative shift with the development of the cutting-edge antisense technologies: RNA interference (RNAi), contact unmodified antisense DNA biotechnology (CUADb), and the CRISPR-associated proteins (CRISPR/Cas). These approaches function by facilitating sequence-specific pairing of nucleic acids followed by nuclease-mediated cleavage, offering exceptional precision for targeted pest control. While RNA-guided mechanisms such as RNAi and CRISPR/Cas were initially characterized in non-insect systems, primarily as innate defenses against viral infections, the DNA-guided CUADb pathway was first identified in insect pests as a functional pest control strategy. Its broader role in ribosomal RNA (rRNA) biogenesis was recognized later. Together, these discoveries have revealed an entirely new dimension of gene regulation, with profound implications for sustainable pest management. Despite sharing a common principle of sequence-specific targeting RNAi, CUADb, and CRISPR/Cas differ in several key aspects, including their mechanisms of action, target specificity, and applicability. Rather than serving as universal solutions, each technology is likely to be optimally effective against specific pest groups. Moreover, these technologies allow for rapid adaptation of control strategies to overcome target-site resistance, ensuring long-term efficacy. This review summarizes the core functional characteristics, potential applications, and current limitations of each antisense technology, emphasizing their complementary roles in advancing environmentally sustainable pest control. By integrating foundational biological discoveries with applied innovations, this work provides a new perspectives on incorporating antisense-based strategies into next-generation integrated pest management systems. Full article

The edge effect refers to what occurs when an object undergoes elastic contact with the edge of a material. This is common in practical applications, but the understanding of this phenomenon is not yet mature enough, and understanding the microscopic characteristics of the material regarding this phenomenon is necessary. This article investigates the edge effects of single-crystal silicon at different indentation positions through molecular dynamics simulations. The results indicate that the edge effect of the indentation is influenced by the indentation position and depth. The closer the indentation head is to the edge of the workpiece, the more particles are extruded from the side of the workpiece and the wider the collapse range of the indentation surface. At the same time, the indentation position also affects the distribution of the von Mises stress and phase transition area. When the edge effect occurs, the von Mises stress and phase transition region tend to be concentrated near the workpiece edge. This study demonstrates the atomic-scale deformation mechanism of single-crystal silicon under varying indentation positions. Full article

Steel lazy wave risers (SLWRs) are critical in offshore hydrocarbon transport for linking subsea wells to floating production facilities in deep-water environments. The incorporation of buoyancy modules reduces curvature-induced stress concentrations in the touchdown zone (TDZ); however, extended operational exposure under cyclic environmental and operational loads results in repeated seabed contact. This repeated interaction modifies the seabed soil over time, gradually forming a trench and altering the riser configuration, which significantly impacts stress patterns and contributes to fatigue degradation. Accurately reconstructing the riser’s evolving profile in the TDZ is essential for reliable fatigue life estimation and structural integrity evaluation. This study proposes a simulation-based framework for the autonomous tracking of SLWRs using a fin-actuated autonomous underwater vehicle (AUV) equipped with a monocular camera and multibeam echosounder. By fusing visual and acoustic data, the system continuously estimates the AUV’s relative position concerning the riser. A dedicated image processing pipeline, comprising bilateral filtering, edge detection, Hough transform, and K-means clustering, facilitates the extraction of the riser’s centerline and measures its displacement from nearby objects and seabed variations. The framework was developed and validated in the underwater unmanned vehicle (UUV) Simulator, a high-fidelity underwater robotics and pipeline inspection environment. Simulated scenarios included the riser’s dynamic lateral and vertical oscillations, in which the system demonstrated robust performance in capturing complex three-dimensional trajectories. The resulting riser profiles can be integrated into numerical models incorporating riser–soil interaction and non-linear hysteretic behavior, ultimately enhancing fatigue prediction accuracy and informing long-term infrastructure maintenance strategies. Full article

This survey provides a comprehensive review of the integration of large language models (LLMs) into autonomous robotic systems, organized around four key pillars: locomotion, navigation, manipulation, and voice-based interaction. We examine how LLMs enhance robotic autonomy by translating high-level natural language commands into low-level control signals, supporting semantic planning and enabling adaptive execution. Systems like SayTap improve gait stability through LLM-generated contact patterns, while TrustNavGPT achieves a 5.7% word error rate (WER) under noisy voice-guided conditions by modeling user uncertainty. Frameworks such as MapGPT, LLM-Planner, and 3D-LOTUS++ integrate multi-modal data—including vision, speech, and proprioception—for robust planning and real-time recovery. We also highlight the use of physics-informed neural networks (PINNs) to model object deformation and support precision in contact-rich manipulation tasks. To bridge the gap between simulation and real-world deployment, we synthesize best practices from benchmark datasets (e.g., RH20T, Open X-Embodiment) and training pipelines designed for one-shot imitation learning and cross-embodiment generalization. Additionally, we analyze deployment trade-offs across cloud, edge, and hybrid architectures, emphasizing latency, scalability, and privacy. The survey concludes with a multi-dimensional taxonomy and cross-domain synthesis, offering design insights and future directions for building intelligent, human-aligned robotic systems powered by LLMs. Full article

Laser ranging technology holds a key position in the military, aerospace, and industrial fields due to its high precision and non-contact measurement characteristics. As a core component, the performance of the photon detector directly determines the ranging accuracy and range. This paper systematically reviews the technological development of photonic detectors for laser ranging, with a focus on analyzing the working principles and performance differences of traditional photodiodes [PN (P-N junction photodiode), PIN (P-intrinsic-N photodiode), and APD (avalanche photodiode)] (such as the high-frequency response characteristics of PIN and the internal gain mechanism of APD), as well as their applications in short- and medium-range scenarios. Additionally, this paper discusses the unique advantages of special structures such as transmitting junction-type and Schottky-type detectors in applications like ultraviolet light detection. This article focuses on photon counting technology, reviewing the technological evolution of photomultiplier tubes (PMTs), single-photon avalanche diodes (SPADs), and superconducting nanowire single-photon detectors (SNSPDs). PMT achieves single-photon detection based on the external photoelectric effect but is limited by volume and anti-interference capability. SPAD achieves sub-decimeter accuracy in 100 km lidars through Geiger mode avalanche doubling, but it faces challenges in dark counting and temperature control. SNSPD, relying on the characteristics of superconducting materials, achieves a detection efficiency of 95% and a dark count rate of less than 1 cps in the 1550 nm band. It has been successfully applied in cutting-edge fields such as 3000 km satellite ranging (with an accuracy of 8 mm) and has broken through the near-infrared bottleneck. This study compares the differences among various detectors in core indicators such as ranging error and spectral response, and looks forward to the future technical paths aimed at improving the resolution of photon numbers and expanding the full-spectrum detection capabilities. It points out that the new generation of detectors represented by SNSPD, through material and process innovations, is promoting laser ranging to leap towards longer distances, higher precision, and wider spectral bands. It has significant application potential in fields such as space debris monitoring. Full article

Laser cladding, a cutting-edge surface modification technique for metals, offers a novel approach to enhancing the wear and corrosion resistance of substrates due to its rapid heating and cooling capabilities, precise control over coating thickness and dilution rates, and non-contact processing characteristics. However, disparities in the physical properties between the coating material and the substrate, coupled with the improper utilization of process parameters, can lead to coating defects, thereby compromising the quality of the coating. This paper examines the effects of material systems and process parameters on laser cladding composite coatings and shows that cracking is mainly caused by thermal and residual stresses. This article summarizes the methods for crack improvement and prevention in five aspects: the selection of processes in the preparation stage, the application of auxiliary fields in the cladding process, heat treatment technology, the use of auxiliary software, and the search for new processes and new structural materials. Finally, the future development trends of laser cladding technology are presented. Full article

Users of technical blades expect new generations of tools to feature reduced power requirements for process and maximized tool life. The second aspect is reflected in the reduction in costs associated with the purchase of tools and in the reduction in process line downtime due to tool replacement. Meeting these demands is particularly challenging in cutting operations involving heterogeneous materials, especially when the processed raw material contains inclusions and impurities significantly harder than the material itself. This situation occurs, among others, during flatfish skinning operations analyzed in this paper, a common process in the fish processing industry. These fish, due to their natural living environment and behavior, contain a significant proportion of hard inclusions and impurities (shell fragments, sand grains) embedded in their skin. Contact between the tool and hard inclusions causes deformation, wrapping, crushing, and even chipping of the cutting edge of planar knives, resulting in non-uniform blade wear, which manifests as areas of uncut skin on the fish fillet. This necessitates frequent tool changes, resulting in higher tooling costs and longer operating times. This study provides a unique opportunity to review the results of in-service pre-implementation tests of planar knives in the skinning operation conducted under industrial conditions. The main objective was to verify positive laboratory research results regarding the extension of technical blade tool life through optimization of sharpening conditions during grinding. Durability test results are presented for the skinning process of fillets from plaice (Pleuronectes platessa) and flounder (Platichthys flesus). The study also examined the effect of varying cooling and lubrication conditions in the grinding zone on the tool life of technical planar blades. Sharpening knives under flood cooling conditions and using the hybrid method (combining minimum quantity lubrication and cold compressed air) increased their service life in the plaice skinning process (Pleuronectes platessa) by 12.39% and 8.85%, respectively. The increase in effective working time of knives during flounder (Platichthys flesus) skinning was even greater, reaching 17.7% and 16.3% for the flood cooling and hybrid methods, respectively. Full article

The wear failure of vertical shaft planetary mixer blades under complex working conditions directly affects the quality and productivity of concrete. Given that it is time-consuming and labor-intensive to obtain the wear characteristics of mixer blades by experimental methods, this study used numerical simulation to analyze the effects of different factors on the wear characteristics of mixer blades based on the Hertz–Mindlin with JKR cohesive contact model and the Archard wear model. The results of this study show that under the influence of different factors, the blade is subjected to tangential cumulative contact energy and contact force is significantly larger than that in the normal direction, the wear of the blade is judged to be the form of abrasive wear accompanied by impacts, and the wear on the outer middle and lower edge regions of the blade is the most serious. Specifically, for every 5 rpm increase in mixing speed, the blade wear rate increases by 24.14% on average; for every 5° increase in blade angle, the blade wear rate decreases by 2.9% on average; for every 10% increase in the mass ratio of stone aggregate, the blade wear rate increases by 5.95% on average; conical aggregates have the most serious effect on blade wear, while spherical aggregates have the most minor effect. This study provides the theoretical basis and numerical support for understanding the reasons for blade wear loss and enhancing the service life of mixer blades. Full article

Y₅F₃[AsO₃]₄ crystallizes needle-shaped in the tetragonal space group P4/ncc with the lattice parameters a = 1143.80(8) pm, c = 1078.41(7) pm and c/a = 0.9428 for Z = 4. The yttrium-fluoride substructure linked via secondary contacts forms a three-dimensional network $\begin{array}{c}3\\ \infty \end{array}${[Y₅F₃]¹²⁺} and the remaining part consists of ψ¹-tetrahedral [AsO₃]³⁻ units, which leave lone-pair channels along [001]. In contrast, platelet-shaped Y₅Cl₃[AsO₃]₄ crystals adopt the monoclinic space group C2/c with the lattice parameters a = 1860.56(9) pm, b = 536.27(3) pm, c = 1639.04(8) pm and β = 105.739(3)° for Z = 4. Condensation of [(Y1,2)O₈]¹³⁻ polyhedra via four common edges each leads to fluorite-like $\begin{array}{c}2\\ \infty \end{array}$ {[(Y1,2)O $\begin{array}{c}e\\ 8/2\end{array}$ ]⁵⁻} layers spreading out parallel to the (100) plane. Their three-dimensional linkage occurs via the (Y3)³⁺ cations with their Cl⁻ ligands on the one hand and the As³⁺ cations with their lone-pairs of electrons on the other, which also form within [AsO₃]³⁻ anions lone-pair channels along [010]. Both colorless compounds can be obtained by solid-state reactions from corresponding mixtures of the binaries (Y₂O₃, As₂O₃ and YX₃ with X = F and Cl) at elevated temperatures of 825 °C, most advantageously under halide-flux assistance (CsBr for Y₅F₃[AsO₃]₄ and ZnCl₂ for Y₅Cl₃[AsO₃]₄). By replacing a few percent of YX₃ with EuX₃ or TbX₃, Eu³⁺- or Tb³⁺-doped samples are accessible, which show red or green luminescence upon excitation with ultraviolet radiation. Full article

Accurate and effective fruit tracking and counting are crucial for estimating tomato yield. In complex field environments, occlusion and overlap of tomato fruits and leaves often lead to inaccurate counting. To address these issues, this study proposed an improved lightweight YOLO11n network and an optimized region tracking-counting method, which estimates the quantity of tomatoes at different maturity stages. An improved lightweight YOLO11n network was employed for tomato detection and semantic segmentation, which was combined with the C3k2-F, Generalized Intersection over Union (GIoU), and Depthwise Separable Convolution (DSConv) modules. The improved lightweight YOLO11n model is adaptable to edge computing devices, enabling tomato yield estimation while maintaining high detection accuracy. An optimized region tracking-counting method was proposed, combining target tracking and region detection to count the detected fruits. The particle swarm optimization (PSO) algorithm was used to optimize the detection region, thus enhancing the counting accuracy. In terms of network lightweighting, compared to the original, the improved YOLO11n network significantly reduces the number of parameters and Giga Floating-point Operations Per Second (GFLOPs) by 0.22 M and 2.5 G, while achieving detection and segmentation accuracies of 91.3% and 90.5%, respectively. For fruit counting, the results showed that the proposed region tracking-counting method achieved a mean counting error (MCE) of 6.6%, representing a reduction of 5.0% and 2.1% compared to the Bytetrack and cross-line counting methods, respectively. Therefore, the proposed method provided an effective approach for non-contact, accurate, efficient, and real-time intelligent yield estimation for tomatoes. Full article