Search Results (156)

To address roof overhang hazards (e.g., rock bursts and gas accumulation) in high-gas coal mines, this study proposes a static stress intervention method for controlled directional roof collapse. Using the 150110 fully mechanized face at Yiyuan Coal Mine as a case study, we investigate the mechanical mechanism of static stress intervention-induced roof collapse through theoretical modeling and FLAC3D simulations in the absence of pre-cracks. The study reveals that advanced boreholes filled with static expansion agents generate stress concentration zones along the drilling array. When superimposed with mining-induced stresses, this configuration induces tensile failure preferentially at borehole locations, thereby achieving controlled directional roof collapse. Theoretical calculations indicate that roof fracturing occurs at predetermined locations when expansion pressure reaches ≥9.11 MPa. FLAC3D simulations analyzed stress redistribution and plastic zone evolution under combined static and mining-induced stresses, demonstrating the method’s efficacy in optimizing roadway stability. Field trials implement spaced boreholes (65 mm diameter, 16 m depth, 1 m spacing) with alternating expansion agent charging, achieving a 6 m reduction in roof collapse intervals, effectively mitigating overhang hazards. Results confirm that static stress intervention reshapes the roof stress field, inducing tensile failure along predetermined paths without relying on pre-cracks. The findings provide theoretical and technical insights for roof stability control in high-gas coal mines. Full article

Transposable elements (TEs) are major drivers of plant genome plasticity, but the immediate molecular consequences of new TE insertions remain poorly understood. In this study, we generated a wild-type Arabidopsis thaliana population with novel insertions of ONSEN retrotransposon to investigate early epigenomic and transcriptomic changes using whole-genome and cDNA nanopore sequencing. We found that novel ONSEN insertions were distributed non-randomly, with a strong preference for genic regions, particularly in chromatin enriched for H2A.Z, H3K27me3, and H3K4me2. Most full-length ONSEN insertions within genes were rapidly recognized and spliced out as new introns (intronization), thereby mitigating potential deleterious effects on transcript isoforms. In some cases, ONSEN insertions provided alternative transcription start or termination sites, generating novel transcript isoforms. Genome-wide methylation analysis revealed that new ONSEN copies were efficiently and precisely targeted by DNA methylation. Independently on the location of the original ONSEN element, the euchromatic and heterochromatic insertions display distinct methylation signatures, reflecting the action of different epigenetic pathways. In conclusion, our results demonstrate that DNA methylation and alternative splicing are effective control mechanisms safeguarding the plant genome and transcriptome integrity after retrotransposition burst. Full article

Parallelepipeds specimens were made to further investigate the rockburst occurrence mechanism of ore pillars in underground mining units. The investigation was carried out with uniaxial compression systems and real-time testing systems, such as stress, video, and acoustic emission, combined with digital image correlation (DIC) and SEM electron microscope scanning technology, to systematically analyze the evolution of rockburst of ore pillars, strain field characteristics, acoustic emission characteristics, mesoscopic characteristics of the rockburst fracture, morphology of the bursting crater, and debris characteristics. The findings demonstrate that the pillar’s rockburst process went through four stages, including the calm period, the particle ejection period, the block spalling period, and the full collapse period. According to DIC digital image correlation technology, the development of cracks in the rock is not obvious during the calm period, but during the small particle ejection and block spalling periods, the microcracks started to form and expand more quickly and eventually reached the critical surface of the rock, resulting in the formation of a complete macro-rockburst rupture zone. During stage I of the test, the rate of acoustic emission events and energy was relatively low; from stages II to IV, the rate gradually increased; and in stage V, the rate of acoustic emission events and energy reached its maximum value at the precise moment the rock exploded, releasing all of its stored energy. The specimen pit section primarily exhibits shear damage and the fracture exhibits shear fracture morphology, while the ejecta body primarily exhibits tensile damage and the fracture exhibits tensile fracture morphology. The location of the explosion pit is distributed on the left and right sides of the middle pillar of the specimen, and the shape is a deep “V”. The majority of the rockburst debris is greater than 5 mm, and it mostly takes the shape of thin plates, which is comparable to the field rockburst debris’s shape features. Full article

Ash dieback (ADB), driven by the invasive fungus Hymenoscyphus fraxineus, poses a significant environmental and financial risk throughout Europe. Fraxinus excelsior (European ash), an essential part of forest ecosystems, has seen death rates as high as 85% in impacted areas, threatening its ecological roles and economic importance. This study examines the relationship between the phenological traits of ash clones, particularly the timing of spring bud burst, and their susceptibility to H. fraxineus infection. The study was conducted in a clonal seed orchard located in Northeastern Poland, encompassing 31 ash clones from different bioclimatic regions. Phenological analyses of bud burst were carried out from early April to late May during the years 2018–2020, and crown damage and defoliation levels were assessed multiple times throughout the growing season. The results confirm that clones with earlier bud burst exhibit significantly higher survival rates and reduced crown damage. Observations revealed that clones with earlier bud burst showed a 30% higher survival rate and up to 40% less crown damage compared to clones with later phenology. The timing of bud burst was strongly correlated with susceptibility to ash dieback (R² = 0.37, p < 0.001). Statistical analyses, including ANOVA and mixed models, revealed significant differences in susceptibility to infection among clones from different bioclimatic regions. These findings underscore the importance of biological timing as a key factor in selecting genotypes resilient to ash dieback. The study highlights the potential of breeding approaches that focus on early bud burst traits to enhance the survival and vitality of ash populations. The results provide essential insights for developing adaptive forest management practices aimed at conserving ash resources and maintaining biodiversity in the face of climate change and the ongoing spread of the pathogen. Full article

Hydrogen, as a zero-emission fuel, produces only water when used in fuel cells, making it a vital contributor to reducing greenhouse gas emissions across industries like transportation, energy, and manufacturing. Efficient hydrogen storage requires lightweight, high-strength vessels capable of withstanding high pressures to ensure the safe and reliable delivery of clean energy for various applications. Type V composite pressure vessels (CPVs) have emerged as a preferred solution due to their superior properties, thus this study aims to predict the performance of a Type V CPV by developing its numerical model and calculating numerical burst pressure (NBP). For the validation of the numerical model, a Hydraulic Burst Pressure test is conducted to determine the experimental burst pressure (EBP). The comparative study between NBP and EBP shows that the numerical model provides an accurate prediction of the vessel’s performance under pressure, including the identification of failure locations. These findings highlight the potential of the numerical model to streamline the development process, reduce costs, and accelerate the production of CPVs that are manufactured by prepreg hand layup process (PHLP), using carbon fiber/epoxy resin prepreg material. Full article

The risk level and disaster scale of rock bursts in deeply buried and highly stressed tunnels are commonly high, posing serious threats to their construction safety. This study employed a combination of on-site measurements and discrete-continuous coupled numerical simulations to analyze the geo-stress distribution characteristics of surrounding rock masses in the Xuefeng Mountain No.1 Tunnel. The evolution processes of rock burst failure in surrounding rock masses with different lithologies and buried at different depths were discussed. The risk of rock bursts along this long tunnel was predicted using the stress–strength ratio criterion and the energy method. The results showed that the principal stress values of surrounding rock masses in the Xuefeng Mountain No.1 Tunnel followed a distribution pattern of σ_x > σ_y > σ_z (where x, y, and z denoted the directions of tunnel cross-section and tunnel axis and the direction perpendicular to the ground), with average stress levels exceeding 20 MPa. It should be a typical tunnel dominated by horizontal tectonic stress. Stress concentration and elastic strain energy accumulation zones in this tunnel were mainly located at the bottom, and the largest displacements always occurred at the inverted arch. The main characteristics of rock burst failure in this tunnel included the sheet-like splitting of rock mass layers and the ejection of rock blocks. The risk evaluation of rock bursts across different sections of the tunnel, considering various rock types and buried depths, presented that these deeply buried slate and granite exhibited the highest risk level when assessed using the elastic strain energy index criterion. The comparative analysis between the elastic strain energy method and the stress–strength ratio criterion showed that the evaluation results obtained by the latter were more conservative. The findings of this study can provide a valuable reference for cognizing the geo-stress characteristics and predicting rock bursts in the surrounding rock masses of deep-buried and highly stressed tunnels. Full article

This paper provides a comprehensive review of the methods and techniques developed for detecting leaks in water distribution systems, with a focus on highlighting their strengths, weaknesses, and areas for future research. Given the substantial economic, social, and environmental impacts of undetected leaks, timely detection and precise location of leaks are critical concerns for water authorities. This review categorizes existing methods into traditional approaches, such as manual sounding, and modern techniques involving smart water management and sensor technologies. A multidimensional bibliometric analysis was employed to systematically identify, select, and evaluate 600 scholarly articles on water leak detection, sourced from the Scopus database over a 23-year period (2000–2023). The paper evaluates each method based on leak sensitivity, burst detection, continuous monitoring, alarm accuracy, and implementation costs. Novel insights include an analysis of emerging smart water technologies and their integration into real-world water distribution networks, offering improved efficiency in leak detection. The paper also identifies key gaps in current research and suggests future directions for advancing the accuracy and cost-effectiveness of these technologies. Full article

The rapid development of remote sensing technology has provided new sources of data for marine rescue and has made it possible to find and track survivors. Due to the requirement of tracking multiple survivors at the same time, multi-object tracking (MOT) has become the key subtask of marine rescue. However, there exists a significant gap between fine-grained objects in realistic marine rescue remote sensing data and the fine-grained object tracking capability of existing MOT technologies, which mainly focuses on coarse-grained object scenarios and fails to track fine-grained instances. Such a gap limits the practical application of MOT in realistic marine rescue remote sensing data, especially when rescue forces are limited. Given the promising fine-grained classification performance of recent text-guided methods, we delve into leveraging labels and attributes to narrow the gap between MOT and fine-grained maritime rescue. We propose a text-guided multi-class multi-object tracking (TG-MCMOT) method. To handle the problem raised by fine-grained classes, we design a multi-modal encoder by aligning external textual information with visual inputs. We use decoding information at different levels, simultaneously predicting the category, location, and identity embedding features of objects. Meanwhile, to improve the performance of small object detection, we also develop a data augmentation pipeline to generate pseudo-near-infrared images based on RGB images. Extensive experiments demonstrate that our TG-MCMOT not only performs well on typical metrics in the maritime rescue task (SeaDronesSee dataset), but it also effectively tracks open-set categories on the BURST dataset. Specifically, on the SeaDronesSee dataset, the Higher Order Tracking Accuracy (HOTA) reached a score of 58.8, and on the BURST test dataset, the HOTA score for the unknown class improved by 16.07 points. Full article

This study introduces a methodology for the real-time detection and localization of bursts in water transmission lines by comparing estimated and measured Hydraulic Gradient (HG) values across pipe segments. Employing a deep learning approach, the method analyzes the complex relationships between system states such as flows, HGs, pump and valve operations. The approach capitalizes on the difference in HG values before and after a burst, enabling precise burst localization. Tested on a real incident, the method proved effective in accurately identifying burst locations, offering a practical solution for operators. Full article

In this paper, a hazard-vulnerability-risk approach is implemented to assess the impacts of water main break flooding events in an urban setting. The hazard component is evaluated through a combination of estimated burst likelihoods for each water distribution pipe and a two-dimensional flooding model for the city’s overland area. Vulnerability is assessed using the damage curves available in the literature for overland flooding. The output of risk is computed in the form of expected annual losses. The application of the proposed approach and the implemented simulation tools are illustrated through a real-life case study at an undisclosed location. Full article

Burst events in Water Distribution Networks (WDNs) pose a significant threat to the safety of water supply, leading people to focus on efficient methods for burst localization and prompt repair. This paper proposes a multi-stage burst localization method, which includes preliminary region determination and precise localization analysis. Based on the hydraulic model and spatio-temporal information, the effective sensor sequences and monitoring areas of the nodes are determined. In the first stage, the preliminary burst region is determined based on the monitoring region of sensors and the alarm sensors. In the second stage, localization metrics are used to analyze the dissimilarity degree between burst data from the hydraulic model and the monitoring data from the effective sensors at each node. This analysis helps identify candidate burst nodes and determine their localization priorities. The localization model is tested on the C-Town network to obtain comparative results. The method effectively reduces the burst region, minimizes the search region, and significantly improves the efficiency of burst localization. For precise localization, it accurately localizes the burst event by prioritizing the possibilities of the burst location. Full article

The ultra-high-energy cosmic ray (UHECR) puzzle is reviewed under the hints of a few basic results: clustering, anisotropy, asymmetry, bending, and composition changes with energies. We show how the lightest UHECR nuclei from the nearest AGN or Star-Burst sources, located inside a few Mpc Local Sheets, may explain, at best, the observed clustering of Hot Spots at tens EeV energy. Among the possible local extragalactic candidate sources, we derived the main contribution of very few galactic sources. These are located in the Local Sheet plane within a distance of a few Mpc, ejecting UHECR at a few tens of EeV energy. UHECR also shine at lower energies of several EeV, partially feeding the Auger dipole by LMC and possibly a few nearer galactic sources. For the very recent highest energy UHECR event, if a nucleon, it may be explained by a model based on the scattering of UHE ZeV neutrinos on low-mass relic neutrinos. Such scatterings are capable of correlating, via Z boson resonance, the most distant cosmic sources above the GZK bound with such an enigmatic UHECR event. Otherwise, these extreme events, if made by the heaviest composition, could originate from the largest bending trajectory of heaviest nuclei or from nearby sources, even galactic ones. In summary, the present lightest to heavy nuclei model UHECR from the Local Sheet could successfully correlate UHECR clustering with the nearest galaxies and AGN. Heavy UHECR may shine by being widely deflected from the Local Sheet or from past galactic, GRB, or SGR explosive ejection. Full article

This article raises the topic of the critical examination of polypropylene, a key polymeric material, and its extensive application within the automotive industry, particularly focusing on the manufacturing of brake fluid reservoirs. This study aims to enhance the understanding of polypropylene’s behavior under mechanical stresses through a series of laboratory destruction tests and numerical simulations, emphasizing the finite element method (FEM). A novel aspect of this research is the introduction of the PEAK parameter, a groundbreaking approach designed to assess the material’s resilience against varying states of strain, known as triaxiality. This parameter facilitates the identification of critical areas prone to crack initiation, thereby enabling the optimization of component design with a minimized safety margin, which is crucial for cost-effective production. The methodology involves conducting burst tests to locate crack initiation sites, followed by FEM simulations to determine the PEAK threshold value for the Sabic 83MF10 polypropylene material. The study successfully validates the predictive capability of the PEAK parameter, demonstrating a high correlation between simulated results and actual laboratory tests. This validation underscores the potential of the PEAK parameter as a predictive tool for enhancing the reliability and safety of polypropylene automotive components. The research presented in this article contributes significantly to the field of material science and engineering by providing a deeper insight into the mechanical behavior of polypropylene and introducing an effective tool for predicting crack initiation in automotive components. The findings hold promise for advancing the design and manufacturing processes in the automotive industry, with potential applications extending to other sectors. Full article

Urban water systems worldwide are confronted with the dual challenges of dwindling water resources and deteriorating infrastructure, emphasising the critical need to minimise water losses from leakage. Conventional methods for leak and burst detection often prove inadequate, leading to prolonged leak durations and heightened maintenance costs. This study investigates the efficacy of logic- and machine learning-based approaches in early leak detection and precise location identification within water distribution networks. By integrating hardware and software technologies, including sensor technology, data analysis, and study on the logic-based and machine learning algorithms, innovative solutions are proposed to optimise water distribution efficiency and minimise losses. In this research, we focus on a case study area in the Sunbury region of Victoria, Australia, evaluating a pumping main equipped with Supervisory Control and Data Acquisition (SCADA) sensor technology. We extract hydraulic characteristics from SCADA data and develop logic-based algorithms for leak and burst detection, alongside state-of-the-art machine learning techniques. These methodologies are applied to historical data initially and will be subsequently extended to live data, enabling the real-time detection of leaks and bursts. The findings underscore the complementary nature of logic-based and machine learning approaches. While logic-based algorithms excel in capturing straightforward anomalies based on predefined conditions, they may struggle with complex or evolving patterns. Machine learning algorithms enhance detection by learning from historical data, adapting to changing conditions, and capturing intricate patterns and outliers. The comparative analysis of machine learning models highlights the superiority of the local outlier factor (LOF) in anomaly detection, leading to its selection as the final model. Furthermore, a web-based platform has been developed for leak and burst detection using a selected machine learning model. The success of machine learning models over traditional logic-based approaches underscores the effectiveness of data-driven, probabilistic methods in handling complex data patterns and variations. Leveraging statistical and probabilistic techniques, machine learning models offer adaptability and superior performance in scenarios with intricate or dynamic relationships between variables. The findings demonstrate that the proposed methodology can significantly enhance the early detection of leaks and bursts, thereby minimising water loss and associated economic costs. The implications of this study are profound for the scientific community and stakeholders, as it provides a scalable and efficient solution for water pipeline monitoring. Implementing this approach can lead to more proactive maintenance strategies, ultimately contributing to the sustainability and resilience of urban water infrastructure systems. Full article

Rockbursts represent one of the most serious and severe natural hazards emerging in underground copper mines within the Legnica–Glogow Copper District (LGCD) in Poland. The contributing factor determining the scale of this event is mining-induced seismicity of the rock strata. Extensive expertise of the copper mining practitioners clearly indicates that high-energy tremors are the consequence of tectonic disturbances or can be attributed to stress/strain behaviour within the burst-prone roof strata. Apparently, seismic activity is a triggering factor; hence, attempts are made by mine operators to mitigate and control that risk. Underlying the effective rockburst control strategy is a reliable seismicity forecast, taking into account the causes of the registered phenomena. The paper summarises the geomechanics analyses aimed to verify the actual seismic and rockburst hazard levels in one of the panels within the copper mine Rudna (LGCD). Two traverses were designated at the face range and comparative analyses were conducted to establish correlations between the locations of epicentres of registered tremors and anomaly zones obtained via analytical modelling of changes in stress/strain behaviours within the rock strata. The main objective of this study was to evaluate the likelihood of activating carbonate/anhydrite layers within the main roof over the excavation being mined, with an aim to verify the potential causes and conditions which might have triggered the registered high-energy events. Special attention is given to two seismic events giving rise to rockbursts in mine workings. Results seem to confirm the adequacy and effectiveness of solutions provided by mechanics of deformable bodies in the context of forecasting the scale and risk of dynamic phenomena and selecting the appropriate mitigation and control measures in copper mines employing the room-and-pillar mining system. Full article