Search Results (416)

The structural stability of lava tubes is a critical factor for their potential use in lunar base construction. Previous studies could not reflect the details of lava tube boundaries and perform accurate mechanical analysis. To this end, this study proposes a robust method to construct a high-precision, real-scene 3D model based on ground lava tube point cloud data. By employing finite element analysis, this study investigated the impact of real-world cross-sectional geometry, particularly the aspect ratio, on structural stability under surface pressure simulating meteorite impacts. A high-precision 3D reconstruction was achieved using UAV-mounted LiDAR and SLAM-based positioning systems, enabling accurate geometric capture of lava tube profiles. The original point cloud data were processed to extract cross-sections, which were then classified by their aspect ratios for analysis. Experimental results confirmed that the aspect ratio is a significant factor in determining stability. Crucially, unlike the monotonic trends often suggested by idealized models, analysis of real-world geometries revealed that the greatest deformation and structural vulnerability occur in sections with an aspect ratio between 0.5 and 0.6. For small lava tubes buried 3 m deep, the ground pressure they can withstand does not exceed 6 GPa. This process helps identify areas with weaker load-bearing capacity. The analysis demonstrated that a realistic 3D modeling approach provides a more accurate and reliable assessment of lava tube stability. This framework is vital for future evaluations of lunar lava tubes as safe habitats and highlights that complex, real-world geometry can lead to non-intuitive structural weaknesses not predicted by simplified models. Full article

We investigate the temperature evolution in the three-dimensional skin tissue exposed to a millimeter-wave electromagnetic beam that is not necessarily perpendicular to the skin surface. This study examines the effect of the beam’s incident angle. The incident angle influences the thermal heating in two aspects: (i) the beam spot projected onto the skin is elongated compared to the intrinsic beam spot in a perpendicular cross-section, resulting in a lower power per skin area; and (ii) inside the tissue, the beam propagates at the refracted angle relative to the depth direction. At millimeter-wavelength frequencies, the characteristic penetration depth is sub-millimeter, whereas the lateral extent of the beam spans at least several centimeters in applications. We explore the small ratio of the penetration depth to the lateral length scale in a nondimensional formulation and derive a leading-term asymptotic solution for the temperature distribution. This analysis does not rely on a small incident angle and is therefore applicable to arbitrary angles of incidence. Based on the asymptotic solution, we establish scaling laws for the three-dimensional skin temperature, the skin surface temperature, and the skin volume in which thermal nociceptors are activated. Full article

The article provides a comprehensive analysis of the Magal Gebreel granitic suites (MGGs) using petrological (fieldwork, petrography, mineral chemistry, and bulk rock analysis) aspects to infer their petrogenesis and emplacement setting. Our understanding of the development of the northern portion of the Arabian Nubian Shield is significantly improved by the Neoproterozoic granitic rocks of the seldom studied MGGs in Egypt’s south Eastern Desert. According to detailed field, mineralogical, and geochemical assessments, they comprise syn-collision (granodiorites) and post-collision (monzogranites, syenogranites, and alkali feldspar rocks). Granodiorite has strong positive Pb, notable negative P, Ti, and Nb anomalies, and is magnesian in composition. They have high content of LREEs (light rare-earth elements) compared to HREEs (heavy rare-earth elements) and clear elevation of LFSEs (low-field strength elements; K Rb, and Ba) compared to HFSEs (high-field strength elements; Zr and Nb), which are in accord with the contents of I-type granites from the Eastern Desert. In this context, the granodiorites are indicative of an early magmatic phase that probably resulted from the partial melting of high K-mafic sources in the subduction zone. Conversely, the post-collision rocks have low contents of Mg#, CaO, P₂O₅, MgO, Fe₂O₃, Sr, and Ti, and high SiO₂, Fe₂O₃/MgO, Nb, Ce, and Ga/Al, suggesting A-type features with ferroan affinity. Their P, Nb, Sr, Ba, and Ti negative anomalies are in accord with the findings for Eastern Desert granites of the A2-type. Furthermore, they exhibit a prominent negative anomaly in Eu and a small elevation of LREEs in relation to HREEs. The oxygen fugacity (fO₂) for the rocks under investigation can be calculated using the biotite chemistry. The narrow Fe/(Fe + Mg) ratio range (0.6–0.75) indicates that they crystallized under moderately oxidizing conditions between ~QFM +0.1 and QFM +1. The A-type rocks were formed by the partial melting of a tonalite source (underplating rocks) in a post-collisional environment during the late period of extension via slab delamination. The lithosphere became somewhat impregnated with particular elements as a result of the interaction between the deeper crust and the upwelling mantle. Full article

In the present study, the coaxial waterjet-assisted nanosecond laser drilling of micro-holes in C_f/SiC composites, coupled with nanosecond laser drilling in air for fabricating micro-holes with high aspect ratios, were investigated. The surface morphology, reaction products, and micro-hole shapes were thoroughly examined. The results reveal that, for the coaxial waterjet-assisted nanosecond laser drilling of micro-holes in the C_f/SiC composite, the increasing of waterjet velocity enhances the material removal rate and micro-hole depth, but reduces the micro-hole diameter and taper angle. The coaxial waterjet isolates the laser-ablated region and cools down the corresponding region rapidly, leading to the formation of a mixture of SiC, SiO₂, and Si on the surface. As the coaxial waterjet velocity increases, the morphology of residual surface products changes from a net-like structure to individual spheres. Coaxial waterjet-assisted nanosecond laser drilling, with a waterjet velocity of 9.61 m/s, achieves micro-holes with a good balance between efficiency and quality. For the fabrication of micro-holes with a high aspect ratio in C_f/SiC composites, micro-holes fabricated by nanosecond laser drilling in air exhibit obvious taper features, which should be ascribed to the combined effects of spattering slag, plasma, and energy dissipation. The application of coaxial waterjet-assisted nanosecond laser drilling on micro-holes fabricated by laser drilling in air effectively expands the hole diameter. The fabricated micro-holes have very small taper angles, with clean wall surfaces and almost no reaction products. This approach, combining nanosecond laser drilling in air followed by coaxial waterjet-assisted nanosecond laser drilling, offers a promising technique for fabricating high-quality micro-holes with high aspect ratios in C_f/SiC composites. Full article

The underground coal mine environment is complex and dynamic, making the application of visual algorithms for object detection a crucial component of underground safety management as well as a key factor in ensuring the safe operation of workers. We look at this in the context of helmet-wearing detection in underground mines, where over 25% of the targets are small objects. To address challenges such as the lack of effective samples for unworn helmets, significant background interference, and the difficulty of detecting small helmet targets, this paper proposes a novel underground helmet-wearing detection algorithm that combines dynamic background awareness with a limited number of valid samples to improve accuracy for underground workers. The algorithm begins by analyzing the distribution of visual surveillance data and spatial biases in underground environments. By using data augmentation techniques, it then effectively expands the number of training samples by introducing positive and negative samples for helmet-wearing detection from ordinary scenes. Thereafter, based on YOLOv10, the algorithm incorporates a background awareness module with region masks to reduce the adverse effects of complex underground backgrounds on helmet-wearing detection. Specifically, it adds a convolution and attention fusion module in the detection head to enhance the model’s perception of small helmet-wearing objects by enlarging the detection receptive field. By analyzing the aspect ratio distribution of helmet wearing data, the algorithm improves the aspect ratio constraints in the loss function, further enhancing detection accuracy. Consequently, it achieves precise detection of helmet-wearing in underground coal mines. Experimental results demonstrate that the proposed algorithm can detect small helmet-wearing objects in complex underground scenes, with a 14% reduction in background false detection rates, and thereby achieving accuracy, recall, and average precision rates of 94.4%, 89%, and 95.4%, respectively. Compared to other mainstream object detection algorithms, the proposed algorithm shows improvements in detection accuracy of 6.7%, 5.1%, and 11.8% over YOLOv9, YOLOv10, and RT-DETR, respectively. The algorithm proposed in this paper can be applied to real-time helmet-wearing detection in underground coal mine scenes, providing safety alerts for standardized worker operations and enhancing the level of underground security intelligence. Full article

To enhance the economic and safety aspects of tunnel structural design, this study optimizes the mix proportion of steel fiber-reinforced concrete (SFRC). It investigates the stress characteristics and support parameters of SFRC secondary lining structures via small-scale model tests and finite element analysis. The research focuses on the cracking process, deformation, and stress characteristics of SFRC linings under various loads. Compared with conventional reinforced concrete tunnels, SFRC tunnels show a significant increase in lining stiffness and load capacity, with a 20% reduction in reinforcement yielding load. When the damage factor is 0.43, the addition of steel fibers increases compressive stress by 22.18%. Using ABAQUS, simulations of SFRC linings with thicknesses ranging from 400 mm to 600 mm and reinforcement ratios of 0% to 0.28% were conducted. The results indicate that a 450 mm thick SFRC lining matches the mechanical performance of a 600 mm thick conventional reinforced concrete lining. Notably, an SFRC lining with a 0.20% circumferential reinforcement ratio equals a conventional lining with a 0.28% reinforcement ratio in overall mechanical performance. Full article

The accurate identification of pulmonary nodules is critical for the early diagnosis of lung diseases; however, this task remains challenging due to inadequate feature representation and limited localization sensitivity. Current methodologies often utilize channel attention mechanisms and intersection over union (IoU)-based loss functions. Yet, they frequently overlook spatial context and struggle to capture subtle variations in aspect ratios, which hinders their ability to detect small objects. In this study, we introduce an improved YOLOV11 framework that addresses these limitations through two primary components: a spatial squeeze-and-excitation (SSE) module that concurrently models channel-wise and spatial attention to enhance the discriminative features pertinent to nodules and explicit aspect ratio penalty IoU (EAPIoU) loss that imposes a direct penalty on the squared differences in aspect ratios to refine the bounding box regression process. Comprehensive experiments conducted on the LUNA16, LungCT, and Node21 datasets reveal that our approach achieves superior precision, recall, and mean average precision (mAP) across various IoU thresholds, surpassing previous state-of-the-art methods while maintaining computational efficiency. Specifically, the proposed SSE module achieves a precision of 0.781 on LUNA16, while the EAPIoU loss boosts mAP@50 to 92.4% on LungCT, outperforming mainstream attention mechanisms and IoU-based loss functions. These findings underscore the effectiveness of integrating spatially aware attention mechanisms with aspect ratio-sensitive loss functions for robust nodule detection. Full article

To address the challenges in ship plate detection under complex maritime scenarios—such as small target size, extreme aspect ratios, dense arrangements, and multi-angle rotations—this paper proposes a multi-module collaborative detection algorithm, RT-DETR-HPA, based on an enhanced RT-DETR framework. The proposed model integrates three core components: an improved High-Frequency Enhanced Residual Block (HFERB) embedded in the backbone to strengthen multi-scale high-frequency feature fusion, with deformable convolution added to handle occlusion and deformation; a Pinwheel-shaped Convolution (PConv) module employing multi-directional convolution kernels to achieve rotation-adaptive local detail extraction and accurately capture plate edges and character features; and an Adaptive Sparse Self-Attention (ASSA) mechanism incorporated into the encoder to automatically focus on key regions while suppressing complex background interference, thereby enhancing feature discriminability. Comparative experiments conducted on a self-constructed dataset of 20,000 ship plate images show that, compared to the original RT-DETR, RT-DETR-HPA achieves a 3.36% improvement in mAP@50 (up to 97.12%), a 3.23% increase in recall (reaching 94.88%), and maintains real-time detection speed at 40.1 FPS. Compared with mainstream object detection models such as the YOLO series and Faster R-CNN, RT-DETR-HPA demonstrates significant advantages in high-precision localization, adaptability to complex scenarios, and real-time performance. It effectively reduces missed and false detections caused by low resolution, poor lighting, and dense occlusion, providing a robust and high-accuracy solution for intelligent ship supervision. Future work will focus on lightweight model design and dynamic resolution adaptation to enhance its applicability on mobile maritime surveillance platforms. Full article

UAV-based small target detection is crucial in environmental monitoring, circuit detection, and related applications. However, UAV images often face challenges such as significant scale variation, dense small targets, high inter-class similarity, and intra-class diversity, which can lead to missed detections, thus reducing performance. To solve these problems, this study proposes a lightweight and high-precision model UAV-YOLO based on YOLOv8s. Firstly, a double separation convolution (DSC) module is designed to replace the Bottleneck structure in the C2f module with deep separable convolution and point-by-point convolution fusion, which can reduce the model parameters and calculation complexity while enhancing feature expression. Secondly, a new SPPL module is proposed, which combines spatial pyramid pooling rapid fusion (SPPF) with long-distance dependency modeling (LSKA) to improve the robustness of the model to multi-scale targets through cross-level feature association. Then, DyHead is used to replace the original detector head, and the discrimination ability of small targets in complex background is enhanced by adaptive weight allocation and cross-scale feature optimization fusion. Finally, the WIPIoU loss function is proposed, which integrates the advantages of Wise-IoU, MPDIoU and Inner-IoU, and incorporates the geometric center of bounding box, aspect ratio and overlap degree into a unified measure to improve the localization accuracy of small targets and accelerate the convergence. The experimental results on the VisDrone2019 dataset showed that compared to YOLOv8s, UAV-YOLO achieved an 8.9% improvement in the recall of mAP@0.5 and 6.8%, while the parameters and calculations were reduced by 23.4% and 40.7%, respectively. Additional evaluations of the DIOR, RSOD, and NWPU VHR-10 datasets demonstrate the generalization capability of the model. Full article

This paper presents a comparative study examining the effects of carbon nanotubes (CNTs) and expanded graphite (EG) on the thermal, mechanical, morphological, electrical, and piezoresistive properties of poly(ethylene-co-methacrylic acid) (EMAA) nanocomposites. To this end, different amounts of carbonaceous fillers (EG and CNTs separately) were added to the EMAA thermoplastic matrix, and the relative electrical percolation thresholds (EPTs) were determined. The effect of filler concentration on thermo-oxidative degradation and the EMAA crystallinity was investigated via thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), respectively. Dynamic mechanical analysis (DMA) demonstrated that both fillers enhance the Young’s and storage moduli, as well as the glass transition temperature, with a greater improvement for the bidimensional nanofiller, most likely due to the cumulative effect of more extensive EG-matrix interactions. In tensile tests, a very relevant difference was detected in the Gauge Factor (G.F.) and the elongation at break of the two typologies of nanocomposites. The G.F. of EMAA 10% CNT and EMAA 15% EG were found to be 0.5 ± 0.08 and 165 ± 14, respectively, while elongation at break was about 68% for EMAA 10% CNT and 8% for EMAA 15% EG. Emission Scanning Electron Microscopy (FESEM) and Tunneling Atomic Force Microscopy (TUNA) have contributed to explaining the differences between EG- and CNT-based nanocomposites from a morphological point of view, underlying the pivotal role of the filler aspect ratio and its structural features in determining different mechanical and piezoresistive performance. The comprehensive analysis of EMAA-EG and EMAA-CNT nanocomposites provides a guide for selecting the best self-sensing system for the specific application. More specifically, EMAA-CNT nanocomposites with high elongation at break and lower sensitivity to small strains are suitable for movement sensors in the soft robotic field, where high deformation has to be detected. On the other hand, the high sensitivity at a low strain of EMAA-EG systems makes them suitable for integrated sensors in more rigid composite structures, such as aeronautical and automotive components or wind turbines. Full article

Sandstone reservoirs exhibit strong heterogeneity and complex microscopic pore structures, presenting challenges for quantitative characterization. This study investigates the Chang 8 tight sandstone reservoir in the Jiyuan, Ordos Basin through analyses of its physical properties, high-pressure mercury injection (HPMI), casting thin sections (CTS), and scanning electron microscopy (SEM). Deep learning techniques were employed to extract the geometric parameters of the pores from the SEM images. Fractal geometry was applied for the combined quantitative characterization of pore parameters and fractal dimensions of the tight sandstone. This study also analyzed the correlations between the fractal dimensions, sample properties, pore structure, geometric parameters, and mineral content. The results indicate that the HPMI-derived fractal dimension (D_MIP) reflects pore connectivity and permeability. D_MIP gradually increases from Type I to Type III reservoirs, indicating deteriorating pore connectivity and increasing reservoir heterogeneity. The average fractal dimensions of the small and large pore-throats are 2.16 and 2.52, respectively, indicating greater complexity in the large pore-throat structures. The SEM-derived fractal dimension (D_SEM) reflects the diversity of pore shapes and the complexity of the micro-scale geometries. As the reservoir quality decreases, the pore structure becomes more complex, and the pore morphology exhibits increased irregularity. D_MIP and D_SEM values range from 2.21 to 2.49 and 1.01 to 1.28, respectively, providing a comprehensive quantitative characterization of multiple pore structure characteristics. The fractal dimension shows negative correlations with permeability, porosity, median radius, maximum mercury intrusion saturation, mercury withdrawal efficiency, and sorting factor, while showing a positive correlation with median and displacement pressures. Among these factors, the correlations with the maximum mercury intrusion saturation and sorting factor are the strongest (R² > 0.8). Additionally, the fractal dimension is negatively correlated with pore circularity and major axis length, but positively correlated with pore perimeter, aspect ratio, and solidity. A higher proportion of circular pores and fewer irregular or long-strip pores correspond to lower fractal dimensions. Furthermore, mineral composition influences the fractal dimension, showing negative correlations with feldspar, quartz, and chlorite concentrations, and a positive correlation with carbonate content. This study provides new perspectives for the quantitative characterization of pore structures in tight sandstone reservoirs, enhances the understanding of low-permeability formation reservoir performance, and establishes a theoretical foundation for reservoir evaluation and exploration development in the study area. Full article

This experimental study examines the particle-level combustion behavior of high-volatile bituminous coal and walnut shell particles in oxyfuel environments, with a particular focus on the gas-phase ignition characteristics and the structural development of volatile flames. Particles with similar size and shape distributions (a median diameter of about 126 µm and an aspect ratio of around 1.5) are combusted in hot flows generated using lean, flat flames, where the oxygen mole fraction is systematically varied in both CO₂/O₂ and N₂/O₂ atmospheres while maintaining comparable gas temperatures and particle heating rates. The investigation employs a high-speed multi-camera diagnostic system combining laser-induced fluorescence of OH, diffuse backlight-illumination, and Mie scattering to simultaneously measure the particle size, shape, and velocity; the ignition delay time; and the volatile flame dynamics during early-stage volatile combustion. Advanced detection algorithms enable the extraction of these multiple parameters from spatiotemporally synchronized measurements. The results reveal that the ignition delay time decreases with an increasing oxygen mole fraction up to 30 vol%, beyond which point further oxygen enrichment no longer accelerates the ignition, as the process becomes limited by the volatile release rate. In contrast, the reactivity of volatile flames shows continuous enhancement with an increasing oxygen mole fraction, indicating non-premixed flame behavior governed by the diffusion of oxygen toward the particles. The analysis of the flame stand-off distance demonstrates that volatile flames burn closer to the particles at higher oxygen mole fractions, consistent with the expected scaling of O₂ diffusion with its partial pressure. Notably, walnut shell and coal particles exhibit remarkably similar ignition delay times, volatile flame sizes, and OH-LIF intensities. The substitution of N₂ with CO₂ produces minimal differences, suggesting that for 126 µm particles under high-heating-rate conditions, the relatively small variations in the heat capacity and O₂ diffusivity between these diluents have negligible effects on the homogeneous combustion phenomena observed. Full article

Energy and mobility are currently powered by conventional fuels, and for the specific case of spark ignition (SI) engines, gasoline is dominant. Converting these power-units to hydrogen is an efficient and cost-effective choice for achieving zero-carbon emissions. The use of this alternative fuel can be combined with a circular-economy approach that gives new life to the existing fleet of engines and minimizes the need for added components. In this context, the current work scrutinizes specific aspects of converting a small-size passenger car to hydrogen fueling. The approach combined measurements performed with gasoline and predictive 0D/1D models for correctly including fuel chemistry effects; the experimental data were used for calibration purposes. One particular aspect of H₂ is that it results in lower volumetric efficiency compared to gasoline, and therefore boosting requirements can feature significant changes. The results of the 0D/1D simulations show that one of the main conclusions is that only stoichiometric operation would ensure the reference peak power level; lean fueling featured relative air–fuel ratios too low for ensuring the minimum value of 2 that would allow mitigating NO_x formation. Top speed could be instead feasible in lean conditions, with the same gearbox, but with an extension of the engine speed operating range to 7000 rpm compared to the 3700 rpm reference point with gasoline. Full article

Wire electrochemical discharge machining (WECDM) integrates the effectiveness of electrical discharge machining (EDM) with the superior quality of electrochemical machining (ECM), leading to enhanced machining efficiency, excellent surface finish, and significant potential for advancement. However, previous research has mainly focused on the processing of non-metallic materials, with little research in the field of the microfabrication of thick metal materials. The wire electrochemical discharge machining process with large aspect ratios is more complex. Accordingly, a unidirectional traveling wire electrochemical discharge micromachining (UWECDMM) method using a glycol-based electrolyte was proposed. The method employs a glycol solution with low conductivity and a neutral salt, facilitating enhanced mass transfer efficiency through a unidirectional traveling wire, and enabling the realization of high-efficiency, high-precision, and recast-free processing. The phenomenon of discharge in UWECDMM was observed in real-time with a high-speed camera, while the voltage and current waveforms throughout the machining process were carefully analyzed. It was found that electrolysis and discharge alternate. Experiments were conducted to investigate the wire traveling pattern, the recast layer, and the wear of the wire electrode. It was found that due to the small energy of a single discharge, the wear of wire electrodes is minimal after multiple uses and can be reused. Under optimal parameters, a machined surface without a recast layer can be obtained. In the final stages, a standard structure was machined on plates of 10 mm thickness made of pure nickel and 304 stainless steel, using a tungsten wire measuring 30 μm in diameter. The feed rate achieved was 1 μm/s, the surface roughness (Ra) measured 0.06 μm, and the absence of a recast layer confirmed the method’s sustainability and quality traits, indicating significant potential in microfabrication. Full article

In this research work, two distinct types of three-dimensional (3D) capacitors were successfully fabricated, each with its own unique features and advantages. The first type of capacitor is centered around a 3D nanoporous structure. This structure is formed on a nickel substrate through anodic oxidation. After undergoing high-temperature thermal oxidation, a monolithic Ni-NiO-Pt metal–insulator–metal (MIM) capacitor with a nanoporous dielectric architecture is achieved. Structurally, this innovative design brings about several remarkable benefits. Due to the nanoporous structure, it has a significantly increased surface area, which can effectively store more charges. As a result, it exhibits an equivalent capacitance density of 69.95 nF/cm², which is approximately 18 times higher than that of its planar, non-porous counterpart. This high capacitance density enables it to store more electrical energy in a given volume, making it highly suitable for applications where miniaturization and high energy storage in a small space is crucial. The second type of capacitor makes use of Through-Glass Via (TGV) technology. This technology is employed to create an interdigitated blind-via array within a glass substrate, attaining an impressively high aspect ratio of 22.5:1 (with a via diameter of 20 μm and a depth of 450 μm). By integrating atomic layer deposition (ALD), a conformal interdigital electrode structure is realized. Glass, as a key material in this capacitor, has outstanding insulating properties. This characteristic endows the capacitor with a high breakdown field strength exceeding 8.2 MV/cm, corresponding to a withstand voltage of 5000 V. High breakdown field strength and withstand voltage mean that the capacitor can handle high-voltage applications without breaking down easily, which is essential for power-intensive systems like high-voltage power supplies and some high-power pulse-generating equipment. Moreover, due to the low-loss property of glass, the capacitor can achieve an energy conversion efficiency of up to 95%. Such a high energy conversion efficiency ensures that less energy is wasted during the charge–discharge process, which is highly beneficial for energy-saving applications and systems that require high-efficiency energy utilization. Full article