Search Results (2,440)

To ensure the safe and reliable operation of hydrogen-blended natural gas (HBNG) pipelines in urban utility tunnels, this study conducted a comprehensive CFD simulation of the leakage and diffusion characteristics of HBNG in confined underground environments. Utilizing ANSYS CFD software (2024R1), a three-dimensional physical model of a utility tunnel was developed to investigate the influence of key parameters, such as leak sizes (4 mm, 6 mm, and 8 mm)—selected based on common small-orifice defects in utility tunnel pipelines (e.g., corrosion-induced pinholes and minor mechanical damage) and hydrogen blending ratios (HBR) ranging from 0% to 20%—a range aligned with current global HBNG demonstration projects (e.g., China’s “Medium-Term and Long-Term Plan for Hydrogen Energy Industry Development”) and ISO standards prioritizing 20% as a technically feasible upper limit for existing infrastructure, on HBNG diffusion behavior. The study also evaluated the adequacy of current accident ventilation standards. The findings show that as leak orifice size increases, the diffusion range of HBNG expands significantly, with a 31.5% increase in diffusion distance and an 18.5% reduction in alarm time as the orifice diameter grows from 4 mm to 8 mm. Furthermore, hydrogen blending accelerates gas diffusion, with each 5% increase in HBR shortening the alarm time by approximately 1.6 s and increasing equilibrium concentrations by 0.4% vol. The current ventilation standard (12 h⁻¹) was found to be insufficient to suppress concentrations below the 1% safety threshold when the HBR exceeds 5% or the orifice diameter exceeds 4 mm—thresholds derived from simulations showing that, under 12 h⁻¹ ventilation, equilibrium concentrations exceed the 1% safety threshold under these conditions. To address these gaps, this study proposes an adaptive ventilation strategy that uses variable-frequency drives to adjust ventilation rates in real time based on sensor feedback of gas concentrations, ensuring alignment with leakage conditions, thereby ensuring enhanced safety. These results provide crucial theoretical insights for the safe design of HBNG pipelines and ventilation optimization in utility tunnels. Full article

Preeclampsia (PE) is not merely a pregnancy complication but a clinical manifestation of underlying vascular dysfunction with long-term health implications. It is diagnosed after 20 weeks of gestation as new-onset hypertension with proteinuria or organ involvement. The condition arises from impaired placental development, particularly defective spiral artery remodeling, which leads to placental ischemia and the release of antiangiogenic factors such as soluble fms-like tyrosine kinase-1 (sFlt-1) and soluble endoglin (sEng). These circulating factors contribute to systemic endothelial dysfunction, resulting in hypertension, inflammation, and multiorgan stress. Histopathological findings, including acute atherosis and abnormal vascular remodeling, further reflect the cardiovascular damage underlying PE. This review synthesizes emerging evidence on the vascular and histological mechanisms of PE, highlighting novel biomarkers such as microRNAs and neprilysin, and the potential of advanced diagnostic tools, including machine learning. Importantly, PE is now recognized not only as an obstetric disorder but also as an early marker of future cardiovascular disease. This paradigm shift emphasizes the need for personalized prevention strategies, close surveillance of high-risk women, and long-term cardiovascular follow-up. Pregnancy thus represents a critical window for early detection and intervention in women’s cardiovascular health. Full article

In recent years, solar energy has emerged as a pillar of sustainable development. However, maintaining panel efficiency under extreme environmental conditions remains a persistent hurdle. This study introduces an automated defect detection pipeline that leverages deep learning and computer vision to identify five standard anomaly classes: Non-Defective, Dust, Defective, Physical Damage, and Snow on photovoltaic surfaces. To build a robust foundation, a heterogeneous dataset of 8973 images was sourced from public repositories and standardized into a uniform labeling scheme. This dataset was then expanded through an aggressive augmentation strategy, including flips, rotations, zooms, and noise injections. A YOLOv11-based model was trained and fine-tuned using both fixed and adaptive learning rate schedules, achieving a mAP@0.5 of 85% and accuracy, recall, and F1-score above 95% when evaluated across diverse lighting and dust scenarios. The optimized model is integrated into an interactive dashboard that processes live camera streams, issues real-time alerts upon defect detection, and supports proactive maintenance scheduling. Comparative evaluations highlight the superiority of this approach over manual inspections and earlier YOLO versions in both precision and inference speed, making it well suited for deployment on edge devices. Automating visual inspection not only reduces labor costs and operational downtime but also enhances the longevity of solar installations. By offering a scalable solution for continuous monitoring, this work contributes to improving the reliability and cost-effectiveness of large-scale solar energy systems. Full article

Carbon fiber reinforced polymer (CFRP) composites are prone to developing localized material loss defects during long-term service, which can severely degrade their mechanical properties and structural reliability. To address this issue, this study proposes a multi-sensor synchronous monitoring method combining embedded fiber Bragg grating (FBG) sensors and surface-mounted electrical resistance strain gauges. First, finite element simulations based on the three-dimensional Hashin damage criterion were performed to simulate the damage initiation and propagation processes in CFRP laminates, revealing the complete damage evolution mechanism from initial defect formation to progressive failure. The simulations were also used to determine the optimal sensor placement strategy. Subsequently, tensile test specimens with prefabricated defects were prepared in accordance with ASTM D3039, and multi-sensor monitoring techniques were employed to capture multi-parameter, dynamic data throughout the damage evolution process. The experimental results indicate that embedded FBG sensors and surface-mounted strain gauges can effectively monitor localized material loss defects within composite laminate structures. Strain gauge measurements showed uniform strain distribution at all measuring points in intact specimens (with deviations less than 5%). In contrast, in defective specimens, strain values at measurement points near the notch edge were significantly higher than those in regions farther from the notch, indicating that the prefabricated defect disrupted fiber continuity and induced stress redistribution. The combined use of surface-mounted strain gauges and embedded FBG sensors was demonstrated to accurately and reliably track the damage evolution behavior of defective CFRP laminates. Full article

In urban construction, the efficient demolition of concrete structures imposes high-precision requirements on blasting technology. The mesoscopic evolution mechanism of concrete blasting damage is the key to optimizing blasting parameters. In this study, a numerical model of concrete blasting is established using Particle Flow Code (PFC). By comparing it with an experimental model containing a blast hole and a horizontal single fissure, the rationality and reliability of the model in simulating blasting damage evolution are verified. On this basis, four groups of control variable schemes are designed (concrete particle size distribution, aggregate content, prefabricated fissure inclination angle, and fissure length) to systematically explore the effects of mesoscopic structures and macroscopic defects on blasting damage. The results show that larger concrete particles make it easier for damage cracks to avoid large particles, forming sparse and irregular crack networks. A higher aggregate content enhances the “obstruction-guidance” effect of aggregate distribution on damage. When the aggregate content is 40%, the vertical damage expansion is the most prominent, reaching up to 3.05 cm. Fissure inclination angle affects the damage direction by guiding the propagation path of stress waves. Fissures inclined at 30°~60° serve as preferential damage channels, while 90° vertical fissures make vertical damage more significant. An increased fissure length expands the damage range, and the damage degree is the highest for a 40 mm long fissure, being 1.29 times that of a 30 mm fissure. The research results reveal the mesoscopic evolution laws of concrete blasting damage, providing a theoretical basis for the optimization of engineering blasting parameters and safety control. Full article

The growing use of weathering steel in bridge engineering has highlighted the increasing impact of fatigue damage caused by the combined effects of welding residual stress and vehicular loading. This study investigates the fatigue performance of Q500qENH weathering steel bridge decks by proposing a coupled analysis method for residual stress and fatigue crack growth, utilizing collaborative simulations with Abaqus 2023 and Franc3D 7.0. An interaction model integrating welding-induced residual stress fields and dynamic vehicular loads is developed to systematically examine crack propagation patterns in critical regions, including the weld toes of the top plate and the weld seams of the U-ribs. The results indicate that the crack propagation rate at the top plate weld toe exhibits the most rapid progression, reaching the critical dimension (two-thirds of plate thickness) at 6.98 million cycles, establishing this location as the most vulnerable failure point. Residual stresses significantly amplify the stress amplitude under tension–compression cyclic loading, with life degradation effects showing 48.9% greater severity compared to pure tensile stress conditions. Furthermore, parametric analysis demonstrates that increasing the top plate thickness to 16 mm effectively retards crack propagation, while wheel load pressures exceeding 1.0 MPa induce nonlinear acceleration of life deterioration. Based on these findings, engineering countermeasures including welding defect control, optimized top plate thickness (≥16 mm), and wheel load pressure limitation (≤1.0 MPa) are proposed, providing theoretical support for fatigue-resistant design and maintenance of weathering steel bridge decks. Full article

The apoptotic mechanism is complex and involves many pathways. Defects can occur at any time along these pathways, resulting in malignant cell transformation and resistance to anticancer drugs. Collective efforts have made great progress in the implementation of natural products in clinical use and in discovering new therapeutic opportunities. This study aimed to screen volatile compounds of Warburgia salutaris leaf extracts and investigate their pro-apoptotic effects on MCF-7 cells. The approach was mainly based on determining cell viability using MTT and scratch assays, and DNA synthesis and damage using BrdU and comet assays, respectively. DAPI/PI stains were used for morphological analysis and expression was determined by RT-PCR and human apoptotic proteome profiler. Warburgia salutaris extracts exhibited antiproliferative effects on MCF-7 cells in a time- and dose-dependent manner. Acetone and methanol extracts exhibited low IC₅₀ at 24, 48 and 72 h. Furthermore, the scratch test revealed that MCF-7 does not metastasise when treated with IC₅₀. Expression showed upregulation of pro-apoptotic proteins and executioner caspases. Taken together, these findings suggest that leaves can promote apoptosis through the intrinsic apoptotic pathway, as observed by upregulation of the Bax and caspase 3 proteins. This paper provides new insights into the mechanisms of action of W. salutaris leaf extracts in the development of anticancer drugs. Full article

Low-temperature plasma cleaning technology has been widely used to clean various optical components precisely. After the complete removal of organic contaminants from fused silica surfaces through plasma cleaning, continuous plasma irradiation can lead to nano-defects on the fused silica surface, resulting in the degradation of optical performance. Thus, the microscale processes underlying plasma-induced surface damage on fused silica were investigated through molecular dynamics simulations, aiming to analyze the mechanisms of surface damage on optical components during plasma cleaning. Oxygen plasma bombardment disrupted fused silica bonds, leading to the successive sputtering of silicon–oxygen atoms. The quantity of sputtered silicon atoms demonstrated a linear correlation with irradiation time. The emergence of pit defects and distinctive interface damage patterns elucidated the impact of neutral oxygen atoms. Critical findings underscore the onset of significant damage beyond 33 eV, underlining plasma’s role in thinning fused silica. Temperature is a crucial factor affecting surface damage during plasma cleaning. Ultimately, investigating the surface damage mechanism of fused silica during plasma cleaning establishes a groundwork for achieving non-destructive optics cleaning. Full article

The electrochemical behavior and corrosion fatigue property of the surface-strengthened EA4T axle steel subjected to foreign object damage (FOD) is investigated in this study. It is found that the corrosion resistance can be enhanced after being impacted by the foreign object due to the introduced hardening layer. Specifically, compared to the smoothed sample, the 167 m/s sample exhibited a 13.88% higher corrosion potential (E_corr) and a 67.61% lower current density (i_corr). The facture surface demonstrates that the corrosion pits on the surface are the main crack initiation location for the smoothed specimens. In contrast, for the surface-damaged specimens, cracks initiate around the crater. The foreign object impact speed has a significant influence on the corrosion fatigue strength; specifically, the faster the impact velocity, the greater the surface damage of the axle specimen, and the shorter its fatigue life at the same stress level. To address the combined influence of size effect and surface defects on fatigue performance, we constructed an improved Kitagawa–Takahashi (KT) diagram by incorporating the theoretical corrosion fatigue limit of full-scale axles with a surface damage of 270 MPa based on conditional probability density function (CPDF). Comparative analysis demonstrates that the revised KT diagram defines a narrower yet more conservative fatigue loading safety zone than the standard KT diagram. This refinement enhances reliability in practical applications where surface imperfections and scale effects dominate failure mechanisms. Full article

Innovative and reliable structural health monitoring (SHM) is indispensable for ensuring the safety, dependability, and longevity of urban infrastructure. However, conventional methods lack full efficiency, remain labor-intensive, and are susceptible to errors, particularly in detecting subtle structural anomalies such as micro-cracks. To address this issue, this study proposes a novel deep-learning framework based on a modified Detection Transformer (DETR) architecture. The framework is enhanced by integrating a Vision Transformer (ViT) backbone and a specially designed Local Feature Extractor (LFE) module. The proposed ViT-based DETR model leverages ViT’s capability to capture global contextual information through its self-attention mechanism. The introduced LFE module significantly enhances the extraction and clarification of complex local spatial features in images. The LFE employs convolutional layers with residual connections and non-linear activations, facilitating efficient gradient propagation and reliable identification of micro-level defects. Thorough experimental validation conducted on the benchmark SDNET2018 dataset and a custom dataset of damaged bridge images demonstrates that the proposed Vision-Local Feature Detector (ViLFD) model outperforms existing approaches, including DETR variants and YOLO-based models (versions 5–9), thereby establishing a new state-of-the-art performance. The proposed model achieves superior accuracy (95.0%), precision (0.94), recall (0.93), F1-score (0.93), and mean Average Precision (mAP@0.5 = 0.89), confirming its capability to accurately and reliably detect subtle structural defects. The introduced architecture represents a significant advancement toward automated, precise, and reliable SHM solutions applicable in complex urban environments. Full article

As a form of non-destructive testing, eddy current testing is widely used for detecting surface micro-damage on metal components in sectors such as aerospace. Conventional frequency-domain analysis techniques often fail to effectively extract defect-related features from non-stationary eddy current signals. This paper proposes an ECT system based on the Discrete Wavelet Transform to address this limitation. In hardware design, the system employs a DDS to generate a 1 MHz excitation signal for the probe. High-precision acquisition of defect response signals is achieved using an IQ demodulator and a 24-bit ADC. For signal processing, the Haar wavelet is applied for single-level decomposition. This method successfully isolates the defect response signal within the high-frequency detail coefficients. Experimental results demonstrate that for a metal surface notch with a depth of 1 mm, the system significantly improves the SNR, resulting in a ΔSNR improvement of 3.64 dB, which is 0.36 dB higher than that achieved using time-domain processing. Full article

Acoustic Emission tomography (AET) has the potential to visualize damage in existing structures, contributing to structural health monitoring. Further, AET requires only the arrival times of elastic waves at sensors to identify velocity distributions, as source localization based on ray-tracing is integrated into its algorithm. Thus, AET offers the advantage of easy acquisition of measurement data. However, accurate source localization requires a large number of elastic wave source candidate points, and increasing these candidates significantly raises the computational resource demand. Lagrange Interpolation has the potential to reduce the number of candidate points, optimizing computational resources, and this potential has been validated numerically. In this study, AET incorporating Lagrange Interpolation is applied to identify the velocity distribution in a defective concrete plate, validating its effectiveness using measured wave data. The validation results show that the defect location in the concrete plate is successfully identified using only 36 source candidates, compared to the 121 candidates required in conventional AET. Furthermore, when using 36 source candidates, the percentage error in applying Lagrange Interpolation is 8.4%, which is significantly more accurate than the 25% error observed in conventional AET. Therefore, it is confirmed that AET with Lagrange Interpolation has the potential to identify velocity distributions in existing structures using optimized resources, thereby contributing to the structural health monitoring of concrete infrastructure. Full article

Single-crystal 4H silicon carbide (4H-SiC) is a key substrate material for third-generation semiconductor devices, where surface and subsurface integrity critically affect performance and reliability. This study systematically examined the evolution of surface morphology and subsurface damage (SSD) during nanoscratching of 4H-SiC under varying normal loads (0–100 mN) using a nanoindenter equipped with a diamond Berkovich tip. Scratch characteristics were assessed using scanning electron microscopy (SEM), while cross-sectional SSD was characterised via focused ion beam (FIB) slicing and transmission electron microscopy (TEM). The results revealed three distinct material removal regimes: ductile removal below 14.5 mN, a brittle-to-ductile transition between 14.5–59.3 mN, and brittle removal above 59.3 mN. Notably, substantial subsurface damage—including median cracks exceeding 4 μm and dislocation clusters—was observed even within the transition zone where the surface appeared smooth. A thin amorphous layer at the indenter-substrate interface suppressed immediate surface defects but promoted subsurface damage nucleation. Crack propagation followed slip lines or their intersections, demonstrating sensitivity to local stress states. These findings offer important insights into nanoscale damage mechanisms, which are essential for optimizing precision machining processes to minimise SSD in SiC substrates. Full article

Background: Reconstruction of nasal, septal, and nasosinusal defects is challenging when the native mucosa is absent or damaged. Oral mucosal grafts have been proposed as a reconstructive option due to their favorable biological properties, but their use in rhinology remains poorly defined. Objective: To evaluate the clinical efficacy and technical characteristics of oral mucosal grafting for nasal, septal, nasosinusal, and skull base reconstruction. Data Sources: PubMed, Embase, Web of Science, and Cochrane Library were searched for studies published between January 2005 and May 2025. Study Eligibility Criteria: We included original human studies (case reports or series) reporting the use of free or pedicled oral mucosal grafts in nasal, septal, nasosinusal, or skull base reconstruction. Non-original studies, animal or preclinical studies, and articles not in English or Spanish were excluded. Methods of Review: One reviewer screened titles, abstracts, and full texts using Rayyan. Methodological quality was assessed using JBI tools for case reports and case series. A narrative synthesis was conducted due to clinical heterogeneity and absence of comparison groups. The resulting assessments were reviewed by the co-authors to confirm accuracy and resolve any potential discrepancies. Results: Of 467 records identified, 10 studies were included. All were case reports or series involving buccal, palatal, or labial mucosa. Most reported good graft integration, low complication rates, and favorable functional outcomes. No randomized studies or comparative analyses were found. Limitations: Included studies had small sample sizes, lacked control groups, and showed heterogeneous methods and follow-up. The certainty of evidence could not be formally assessed. Conclusions: Oral mucosal grafting is a promising reconstructive option in selected nasosinusal and skull base defects. However, stronger comparative studies are needed to determine its clinical superiority. Registration: This review was not registered in any public database. Full article

This article investigates the formation of solidification cracks in steel forgings used for bearing rings in gear reducers of robotic arms. The forging and heat treatment processes, conducted under consistent technological conditions, revealed the occurrence of high-temperature annealing cracks caused by plasticity depletion during stress relaxation. Additionally, solidification cracks were analyzed, with chemical compositions and hardness measurements indicating susceptibility due to elevated carbon and chromium content, as well as a high cracking parameter. Die tool wear and damage during forging were identified as key contributors to crack formation, transferring surface defects, inclusions, and creating cracks that propagate during subsequent processing. The findings underscore the influence of the tooling conditions, material properties, and process parameters on the quality and reliability of steel forgings. Full article