Search Results (1,333)

Fibre-reinforced composites are facing new challenges in the context particular in sustainability and recyclability. Vitrimers could be useful as new matrices to support the increase in sustainability. Due to their high strength, which is comparable to that of thermosets often used in composites, and their covalent adaptive networks, which make them reshapeable for scaled-up manufacturing and recycling purposes, they are very useful. Orthogonal cutting is used for precise reshaping and functional integration into carbon fibre reinforced plastics. Vitrimers could improve processing results at the cutting edge as well as surface quality thanks to their self-healing properties compared to brittle matrices, as well as enabling the recycling of formed chips and scrap. This study showcases the manufacturing of a carbon fibre-reinforced vitrimer using 4-aminophenyl disulfide as a hardener, with vacuum-assisted resin infusion. The temperature of chip formation and the cutting parameters are then shown for different fibre orientations, cutting widths and speeds. The observed cutting forces are lower (less than 140 N) and more irregular for fibre orientations 45°/135°, increasing with cutting depth, and fluctuating periodically during machining. Despite varying cutting speeds, the forces remain relatively constant in range between 85 N and 175 N for 0°/90° fibre orientation and 50 N and 120 N for 45°/135° fibre orientation, with no significant tool wear observed and lower-damage depth and overhanging fibres observed for 0°/90° fibre orientation. Damage observation of the cutting tool shows promising results, with lower abrasion observed compared to thermoset matrices. Microscopic images of the broached surface also show good quality, which could be improved by self-healing of the matrix at higher temperatures. Temperature measurements of chip formation using a high-speed camera show a high temperature gradient as cutting speeds increase, but the temperature only ever exceeds 180 °C at cutting speeds of 150 m/min, ensuring reprocessability since this is below the degradation temperature. Therefore, orthogonal cutting of vitrimers can impact sustainable composite processing. Full article

The aim of the study was to explore the impact of an intervention based on the manipulation of the margin of error and the provision of ball speed feedback on the ability to spike in introductory volleyball. To this end, an exploratory study without a control group was conducted. The sample consisted of two U-14 volleyball teams, one male team with 14 players (13.2 ± 0.75 years), and one female team with 12 players (14 ± 0 years). The intervention involved reducing the height of the net, providing immediate feedback on the speed of the ball after the spike, and challenging the target zone of the spike. It was applied across 12 sessions, with eight spikes per player per session. The study variables recorded in each spiking were ball speed (which was measured using the Pocket Radar Ball Coach instrument), jump height (which was measured using the VERT Wearable Jump Monitor), and target area for sending the ball (which was filmed using a high-speed video camera). The players’ perception of the intervention was also assessed. The most significant results indicated that the achievement of the impact in the more restricted target area of the spiking, compared to the larger target area, led to a significant increase in jumping, both in men and women. As maintaining spike ball speed was necessary to validate the challenge, speed values did not decrease when hitting toward the restricted zone. In fact, for male players, there was an unexpected significant increase in spike ball speed. The initial speed was the variable that best predicted the maximum speed acquired throughout the treatment. Reducing the net height while restricting the spiking area can have a positive impact on spike kinematics, provided that spike velocity is maintained. Full article

In recent years, the demand for both high accuracy and real-time performance in 3D object detection has increased alongside the advancement of autonomous driving technology. While multimodal methods that integrate LiDAR and camera data have demonstrated high accuracy, these methods often have high computational costs and latency. To address these issues, we propose an efficient 3D object detection network that integrates three key components: a DepthWise Lightweight Encoder (DWLE) module for efficient feature extraction, an Efficient LiDAR Image Fusion (ELIF) module that combines channel attention with cross-modal feature interaction, and a Mixture of CNN and Point Transformer (MCPT) module for capturing rich spatial contextual information. Experimental results on the KITTI dataset demonstrate that our proposed method outperforms existing approaches by achieving approximately 0.6% higher 3D mAP, 7.6% faster inference speed, and 17.0% fewer parameters. These results highlight the effectiveness of our approach in balancing accuracy, speed, and model size, making it a promising solution for real-time applications in autonomous driving. Full article

A straightforward ex vivo approach has been developed and refined to enable high-resolution imaging and quantitative assessment of motile cilia function in mouse airway epithelial tissue, allowing critical insights into cilia motility and cilia generated flow using different mouse models or following different sample treatments. In this method, freshly excised mouse trachea is cut longitudinally through the trachealis muscle which is then sandwiched between glass coverslips within a thin silicon gasket. By orienting the tissue along its longitudinal axis, the natural curling of the trachealis muscle helps maintain the sample in a configuration optimal for imaging along the full tracheal length. High-speed video microscopy, utilizing differential interference contrast (DIC) optics and a fast digital camera capturing at >200 frames per second is then used to record ciliary motion. This enables detailed measurement of both cilia beat frequency (CBF) and waveform characteristics. The application of 1 µm microspheres to the bathing media during imaging allows for additional analysis of fluid flow generated by ciliary activity. The entire procedure typically takes around 40 min to complete per animal: ~30 min for tissue harvest and sample mounting, then ~10 min for imaging samples and acquiring data. Full article

Accurate evaluation of subgrade behaviour under dynamic loading is essential for the long-term performance of transport infrastructure. While the Light Weight Deflectometer (LWD) is commonly used to assess subgrade stiffness, it provides only a single stiffness value and may not fully capture the time-dependent response of soil. This study presents an image-based vision system developed to monitor soil surface displacements during loading, enabling more detailed analysis of dynamic behaviour. The system incorporates high-speed cameras and MATLAB-based computer vision algorithms to track vertical movement of the plate during impact. Laboratory and field experiments were conducted to evaluate the system’s performance, with results compared directly to those from the LWD. A strong correlation was observed (R² = 0.9901), with differences between the two methods ranging from 0.8% to 13%, confirming the accuracy of the vision-based measurements despite the limited dataset. The findings highlight the system’s potential as a practical and cost-effective tool for enhancing subgrade assessment, particularly in applications requiring improved understanding of ground response under repeated or transient loading. Full article

Biomass is a key energy resource in the current context of climate and energy crises, due to its lower carbon footprint compared to fossil fuels. However, wood-based energy presents several drawbacks: public health concerns related to pollutant emissions from combustion, and questions about the sustainability of the resource given the increasing demand for cleaner fuels. This study investigates the combustion of mixtures of wood pellets (WPs) and barley straw pellets (BSPs) in a domestic biomass boiler, with the aim of evaluating how such blends affect pollutant emissions and energy production under standard boiler operation, without modifications. Pellets were characterized using a bomb calorimeter and thermogravimetric analysis (TGA), while gaseous and particulate emissions were measured at the chimney using gas analyzers and an Engine Exhaust Particle Sizer (EEPS), respectively. The results show that high BSP proportions (>50%) are not compatible with domestic biomass boilers, as they led to a significant increase in gaseous pollutant emission. However, blends with moderate BSP shares (10 and 25%) can be successfully used, offering benefits in terms of reduced pollutant emissions and improved sustainability. Additionally, infrared and high-speed cameras were installed above the boiler furnace, equipped with an optical window, to provide new insights into the combustion process. Full article

The evaporation of sessile water drops involves coupled heat and mass transfer and is influenced by temperature, relative humidity, and the nature of the surface on which the drop rests. This work investigates the possibility of using vibration to enhance evaporation kinetics. For this purpose, experiments were conducted with vertical vibration near the resonant frequency. An original experimental device was designed, including a shaker controlled by a signal generator and an amplifier, a high-speed camera, and an adapted lighting system. The amplitude–frequency relationship was first examined to select the resonance frequency. As expected, the evaporation kinetics of two drops—one with vibration at the resonance frequency and the other without vibration—demonstrate that vibration accelerates evaporation and reduces drying time by 20.6% on PTFE substrate and by 23.5% on glass substrate. Full article

In order to study the damage evolution and fracture characteristics of rock with different composite modes in three layers under dynamic loading, rock specimens with different composite modes were made by using three materials: sandstone, marble and granite. The dynamic fracture impact test was carried out by using the Hopkinson pressure bar impact loading system, the voltage signal on the Hopkinson pressure bar was calculated and processed, and the crack propagation mode of the specimen was captured by using a high-speed camera, and the stress wave characteristics, stress time–history relationship and energy change characteristics of rocks with different composite modes were studied. At the same time, combined with Distinct Lattice Spring Model numerical simulation, the fracture process of the specimen was inverted, and the changes in stress intensity factor, stress change and load–displacement change in monitoring point were analyzed to compare the dynamic fracture behavior differences between different composite rocks. The results show that the dynamic fracture process captured by the high-speed camera has a good fit with the crack propagation process simulated by numerical simulation. When marble is used as the upper material, the energy transmittance is larger, and the transmission energy ratio between sandstone and granite is basically the same due to the large difference in hardness. When the comprehensive hardness of the specimen is the same, the smaller the hardness of the material at the cracking position, the faster the cracking will be, and the smaller the hardness of the second layer of the specimen at the cracking position, the faster the cracking speed of the specimen. In terms of dynamic fracture toughness, for specimens with little difference in hardness, when the impact end material is sandstone, the dynamic fracture extreme value of the specimen is lower, and when the sandstone material is used as the impact end material, it is more likely to crack. When the first layer of material is the same, the dynamic fracture toughness of the specimen with less hardness of the second layer of material is smaller, and the easier the crack development is. Full article

Smart manufacturing demands ever-increasing equipment reliability and continuous availability. Traditional fault diagnosis relies on attached sensors and complex wiring to collect vibration signals. This approach suffers from poor environmental adaptability, difficult maintenance, and cumbersome preprocessing. This study pioneers the use of high-temporal-resolution dynamic visual information captured by an event camera to fine-tune a multimodal large model for the first time. Leveraging non-contact acquisition with an event camera, sparse pulse events are converted into event frames through time surface processing. These frames are then reconstructed into a high-temporal-resolution video using spatiotemporal denoising and region of interest definition. The study introduces the multimodal model Qwen2.5-VL-7B and employs two distinct LoRA fine-tuning strategies for bearing fault classification. Strategy A utilizes OpenCV to extract key video frames for lightweight parameter injection. In contrast, Strategy B calls the model’s built-in video processing pipeline to fully leverage rich temporal information and capture dynamic details of the bearing’s operation. Classification experiments were conducted under three operating conditions and four rotational speeds. Strategy A and Strategy B achieved classification accuracies of 0.9247 and 0.9540, respectively, successfully establishing a novel fault diagnosis paradigm that progresses from non-contact sensing to end-to-end intelligent analysis. Full article

Collagen is the primary load-bearing component in connective tissues, and its organization dictates the biomechanical properties and functions of the tissue. Polarized light imaging has been an effective tool for characterizing collagen organization. Recently, with the integration of structured light illumination (SLI), structured polarized light imaging (SPLI) has enabled quantification of collagen fiber orientation in the superficial layers of thick tissues with higher specificity and accuracy. However, SPLI typically requires 12 images to perform depth discrimination and collagen quantification, limiting its application in imaging tissue dynamics. To overcome this limitation, we developed a high-speed SPLI system that can perform continuous tracking and quantification of tissue deformation at 75 frames per second (FPS). High-speed SPLI was achieved by pairing a polarization camera with a rolling image processing technique. We evaluated the performance of high-speed SPLI on a bovine heart valve leaflet under uniaxial deformation. We were able to continuously track and quantify collagen fiber orientation at 75 FPS, with improved accuracy due to effective depth discrimination using SLI. Additionally, we demonstrated that reflectance with SLI is more sensitive to local collagen deformation compared to imaging without SLI, offering a complementary perspective for studying the dynamics of collagenous tissues. Full article

Photogrammetry-based 3D reconstruction of the shape of fast-moving objects from image sequences presents a complex yet increasingly important challenge. The 3D reconstruction of a large number of fast-moving objects may, for instance, be of high importance in the study of dynamic phenomena such as impact experiments and explosions. In this context, analyzing the 3D shape, size, and motion trajectory of the resulting fragments provides valuable insights into the underlying physical processes, including energy dissipation and material failure. High-speed cameras are typically employed to capture the motion of the resulting fragments. The high cost, the complexity of synchronizing multiple units, and lab conditions often limit the number of high-speed cameras that can be practically deployed in experimental setups. In some cases, only a single high-speed camera will be available or can be used. Challenges such as overlapping fragments, shadows, and dust often complicate tracking and degrade reconstruction quality. These challenges highlight the need for advanced 3D reconstruction techniques capable of handling incomplete, noisy, and occluded data to enable accurate analysis under such extreme conditions. In this paper, we use a combination of photogrammetry, computer vision, and artificial intelligence techniques in order to improve feature detection of moving objects and to enable more robust trajectory and 3D shape reconstruction in complex, real-world scenarios. The focus of this paper is on achieving accurate 3D shape estimation and motion tracking of dynamic objects generated by impact loading using stereo- or monoscopic high-speed cameras. Depending on the object’s rotational behavior and the number of available cameras, two methods are presented, both enabling the successful 3D reconstruction of fragment shapes and motion. Full article

Pneumatic conveying of stiff shotcrete material plays a crucial role in mine support; however, the flow regime evolution mechanism of its complex multi-scale particle system during conveying remains insufficiently studied. This study establishes a customized pneumatic conveying experimental platform, integrating a high-speed camera and pressure sensors to systematically investigate the flow regime evolution and characteristics of stiff shotcrete material under different operating parameters. Experimental results indicate that air velocity and water–cement ratio significantly influence flow regime evolution: at low air velocities, the material primarily exhibits dune flow and stratified flow. As the air velocity increases to 475 m³/h, the flow regime gradually transitions to suspended flow. An increase in the water–cement ratio significantly enhances liquid bridge forces between particles, intensifying particle agglomeration and making the bottom-layer flow characteristics more pronounced. Additionally, pipe diameter plays a crucial role in flow regime distribution, with suspended flow dominating in smaller pipes and bottom-layer flow becoming more prominent in larger pipes. In the downstream section of the elbow, the abrupt decrease in airflow velocity causes the flow regime to degrade from suspended flow to bottom-layer flow, leading to significant particle deposition. This study reveals the flow regime evolution patterns of stiff shotcrete material in pneumatic conveying, providing essential experimental evidence and theoretical support for optimizing long-distance pneumatic conveying systems in mine support applications. Full article

The high-precision attitude estimation technique for non-cooperative targets in space, based on monocular cameras, has important application value in missions such as space debris removal, autonomous rendezvous and docking, and on-orbit services. However, due to the inherent missing information problem of monocular vision systems and the high complexity of target geometry, existing monocular pose estimation methods find it difficult to realize an effective balance between accuracy and computational efficiency. Current solutions commonly adopt deep neural network architectures to improve estimation accuracy; but, this method is often accompanied by the problems of a dramatic expansion of the number of model parameters and a significant increase in computational complexity, which limits its deployment and real-time inference capabilities in real spatial tasks. To address the above problems, this paper proposes a spacecraft pose estimation network, called Balance-URSONet, which weighs the trade-off between accuracy and the number of parameters, and makes the pose estimation model have a stronger feature extraction capability by innovatively using RepVGG as the feature extraction network. In order to effectively improve the performance and inference speed of the model, this paper proposes the feature excitation unit (FEU), which is able to flexibly adjust the feature representation of the network and thus optimize the utilization efficiency of spatial and channel information. The experimental results show that the Balance-URSONet proposed in this paper has excellent performance in the spacecraft pose estimation task, with an ESA score of 0.13 and a parameter count 13 times lower than that of URSONet. Full article

In the face of growing demand for emergency treatment in mass casualty incidents involving acute hemorrhagic shock, disaster sites often suffer from limited search and rescue manpower and inadequate medical detection capabilities. With the rapid development of robot technology, the deployment of robots provides greater flexibility and reliability in disaster emergency response and search and rescue work, which can effectively address the shortage of search and rescue forces and medical resources at disaster sites. This paper introduces a snake-like robot designed for the rapid triage of casualties with hemorrhagic shock. Through a structural design combining active wheels and orthogonal joints, the robot integrates the advantages of high-speed mobility of wheeled robots with the high flexibility of jointed robots so as to adapt to the complex environments typical of search and rescue scenarios. Meanwhile, the end of the robot is equipped with a visible light camera, an infrared camera and a voice interaction system, which realizes the rapid triage of casualties with hemorrhagic shock by collecting visible light, infrared and voice dialog data of the casualties. Through Webots software simulation and outdoor site simulation experiments, seven indicators of the designed snake-like search and rescue robot are verified, including walking speed, minimum passable hole size, climbing angle, obstacle-surmounting height, passable step size, ditch-crossing width and turning radius, as well as the effectiveness of collecting visible light images, infrared images and voice dialog data of the casualties. Full article

Dynamic fatigue of rocks under repeated cyclic impact is a nonconservative property, as surrounding rocks in real environments subjects them to variable impact disturbances, and the degree of damage varies under different energy level loads. To evaluate the dynamic response and fatigue damage characteristics of rocks under multi-level cyclic impacts, uniaxial cyclic impact tests were carried out on granite with various stress paths and energy levels using a modified split Hopkinson pressure bar. Dynamic deformation characteristics of specimens under different loading modes were investigated by introducing the deformation modulus of the loading stage. Evolution of macroscopic cracks during the impact process was investigated based on high-speed camera images, and the microscopic structure of damaged specimens was examined using SEM. In addition, cumulative energy dissipation was used to assess the damage of rocks. Results show that the deformation modulus of the loading stage, dynamic peak stress and strain of specimens increase with the impact energy, and the deformation modulus of the loading stage decreases as the damage level increases. Propagation rate of tensile cracks in rock was correlated with participation time of the higher energy level, which observed the following sequence: linearly decreasing > same > linearly increasing energy level, and cyclic loading of nonlinear energy level produced more tensile cracks and rock spalling than the same energy level. Compared with cyclic impacts of the same energy level, multi-level impacts form more microcracks and fatigue striations. The cumulative rate of specimen damage under the same energy change rate is as follows: linear decreasing > same > linear increasing loading. This provides a new case study for evaluating the dynamic damage, crushing efficiency and load-bearing capacity of rocks in real engineering environments. Full article