Search Results (4,629)

An isolated roof is an indispensable component of overlapping goaf. Focusing on the influence of dislocated width and width ratio on the stability of the isolated roof, this study analyzes the change rule of the safety factor of the roof supported by misaligned pillars and reveals the evolution characteristics of it by integrating numerical simulation into the strength reduction method. Firstly, with the increase of the dislocated width, the safety factor experienced three stages of sharp decrease, change from decrease to increase, and rapid increase. Secondly, the width ratio λ = 2 can be determined as the critical value of the safety reserve of the roof. In the interval λ ˂ 2, F decreases sharply with the increase of λ, but when λ ˃ 2, F decreases slowly and tends to 0. Thirdly, the overlap rate of pillars is a determinant of the type of damage but not of the safety factor of the roof. When η = 0, the safety factor is independent of the overlap rate. Furthermore, increasing the dislocated width can make the failure units accumulate continuously and then promote the plastic zone to expand gradually, resulting in roof collapse due to the penetration of the failure units. In this process, the tensile failure zone evolves from a single fold line to a wavy line, and the shear failure zone changes from a diagonal strip to a square strip. The study provides a new method to improve the stability of the roof, which is helpful to significantly reduce the collapse risk of overlapping goaf. Full article

Background: Irritable bowel syndrome (IBS) is a prevalent gastrointestinal disorder with a complex pathogenesis that necessitates innovative therapeutic approaches for effective management. Among the commonly used treatments, mebeverine (MBH), an antispasmodic, is widely prescribed to alleviate IBS symptoms. However, challenges in delivering the drug precisely to the colonic region often hinder its therapeutic effectiveness. To address this limitation, silver nanoparticles (AgNPs) have emerged as promising drug delivery systems, offering unique physicochemical properties that can enhance the precision and efficacy of IBS treatments. Objectives: This study aimed to synthesize AgNPs as drug delivery vehicles for MBH and a previously reported analog. The research focused on evaluating the cytotoxic and genotoxic effects of the AgNPs and forecasting their possibly harmful effects on future sustainable development. Methods: AgNPs were synthesized using a rapid method and functionalized with MBH and its analog. The nanoparticles were characterized using different techniques. Cytotoxicity and genotoxicity were evaluated in vitro. Additionally, in silico docking analyses were performed to explore their safety profile further. Results: In vitro assays revealed concentration-dependent cytotoxic effects and a lack of genotoxic effects with MBH-loaded AgNPs. A molecular docking simulation was performed to confirm this effect. Conclusions: The study underscores the potential of AgNPs as advanced drug delivery systems for safe and significant therapeutic implications for IBS. Future in vivo and preclinical investigations are essential to validate the safe range of exposure doses and evaluation standards for assessing AgNPs’ safety in targeted and personalized medicine. Full article

With the rapid growth of photovoltaic power generation systems, fire incidents within the system have progressively increased. The lack of thorough studies on the temperature properties of direct current (DC) arc faults has resulted in an unclear ignition mechanism, significantly increasing the fire risk associated with such faults. Hence, this work presents a proposed experimental scheme for detecting photovoltaic DC series arc faults (SAFs) and the corresponding detection standards. Additionally, the temperature characteristics of the DC arc fault are further analyzed. The magnetohydrodynamic (MHD) arc fault simulation model is developed to investigate the temperature-related aspects of photovoltaic DC arc faults. Finally, our experimental validation confirms the precision of the model in simulating arc temperature. It is verified that the research presented in this paper can provide a good explanation for the rise time of DC arc temperature and the characteristic distribution of arc distance. This study elucidates the impact mechanism of line current, power supply voltage, and arc gap size on arc temperature in a photovoltaic system. Additionally, it proposes an evaluation method for assessing the arc fault ignition risk level. This method is essential for safeguarding against arc fault ignition risk in photovoltaic DC series cells. Full article

Background: In recent years, more and more numerical tools have been utilized in medicine in or-der to assist the evaluation and decision-making processes for complex clinical cases. Towards this direction, Finite Element Models (FEMs) have emerged as a pivotal tool in medical research, particularly in simulating and understanding the complex fluid and structural behaviors of the circulatory system. Furthermore, this tool can be used for the calculation of certain risks regarding the function of the blood vessels. Methods: The current study developed a computational tool utilizing the finite element method in order to numerically evaluate stresses in aortas with abdominal aneurysms and provide the necessary data for the creation of a patient-specific digital twin of an aorta. More specifically, 12 different cases of aortas with abdominal aneurysms were examined and evaluated. Results: The first step was the 3D reconstruction of the aortas trans-forming the DICOM file into 3D surface models. Then, a finite element material model was developed simulating accurately the mechanical behavior of aortic walls. Conclusions: Through the results of these finite element analyses the values of tension, strain, and displacement were quantified and a rapid risk assessment was provided revealing that larger aneurysmatic regions elevate the risk of aortic rupture with some cases reaching an above 90% risk. Full article

Global urbanization has led to the overexploitation and pollution of groundwater resources, restricting the sustainable construction and development of cities. Groundwater environmental carrying capacity (GW-ECC) refers to the maximum total amount of pollutants that can be accommodated by a given groundwater system within a certain time period and under specified environmental goals. To better understand the changes in GW-ECC in the context of rapid urbanization, this study built a model of the urban GW-ECC driven by multiple factors. Taking the urban area of Zhengzhou as an example, rainfall infiltration and riverside seepage within the urban groundwater system were calculated considering the change in the impervious area over the past 20 years. The Mann–Kendall rank test was used to evaluate the varying trends of the two factors in the urbanization process. Based on this, the change in the GW-ECC in the current year was calculated, and the changes under different regulatory schemes after 10 years was calculated and evaluated. The results showed that the model constructed in this study could accurately simulate an urban groundwater system. With the acceleration of urbanization, the urban groundwater system recharges by precipitation, and rivers tend to decline. The GW-ECC of ammonia nitrogen in Zhengzhou exhibited an overall upward trend. By the end of 2030, the GW-ECC of ammonia nitrogen is expected to reach a maximum of 1964.5 t. Changes in groundwater resources caused by precipitation and extraction were the main factors driving variations in the urban GW-ECC. In areas with mature urbanization, measures such as increasing groundwater recharge and reducing groundwater extraction are more effective in improving the GW-ECC. Full article

Forest anomalies (e.g., pests, deforestation, and fires) are increasingly frequent phenomena on Earth’s surface. Rapid detection of these anomalies is crucial for sustainable forest management and development. On-orbit remote sensing detection of multi-type forest anomalies using single-temporal images is one of the most promising methods for achieving it. Nevertheless, existing forest anomaly detection methods rely on time series image analysis or are designed to detect a single type of forest anomaly. In this study, a Forest Anomaly Comprehensive Index (FACI) is proposed to detect multi-type forest anomalies using single-temporal Sentinel-2 images. First, the spectral characteristics of different forest anomaly events were analyzed to obtain potential band combinations. Then, the formulation of FACI was determined using imagery simulated by the LargE-Scale remote sensing data and image Simulation framework over heterogeneous 3D scenes (LESS) model. The thresholds for FACI for different anomalies were determined using the interquartile method and 90 in situ survey samples. The accuracy of FACI was quantitatively assessed using an additional 90 in situ survey samples. Evaluation results indicated that the overall accuracy of FACI in detecting the three forest anomalies was 88.3%, with a Kappa coefficient of 0.84. The overall accuracy of existing indices (NDVI, NDWI, SAVI, BSI, and TAI) is below 80%, with Kappa coefficients less than 0.7. In the end, a case study in Ji’an, Jiangxi Province, confirmed the ability of FACI to detect different stages of pest infection, as well as deforestation and forest fires, using single-temporal satellite images. The FACI provides a promising method for the on-orbit satellite detection of multi-type forest anomalies in the future. Full article

In the oil and gas sectors, as well as in waste landfills, the commitment to greater sustainability is leading to increased efforts in the search for methane leaks, both to avoid the emission of a major greenhouse gas and to enable greater fuel recovery. For rapid leak detection and flow estimation, drone-mounted sensors are used, which require a balanced configuration of the detection and measurement system, adequate for the specific sensor used. In the present work, the search for methane leaks is carried out using a tunable diode laser absorption spectrometer (TDLAS) mounted on a drone. Once the survey is carried out, the data obtained feed the algorithms necessary for estimating the methane flow using the mass balance approach. Various algorithms are tested in the background measurement phases and in the actual detection phase, integrated with each other in order to constitute a single balanced set-up for the estimation of the flow emitted. The research methodology adopted is that of field testing through controlled releases of methane. Three different flows are released to simulate different emission intensities: 0.054, 1.91 and 95.9 kg/h. Various data configurations are developed in order to capture the set-up that best represents the emission situation. The results show that for the correction of methane background errors, the threshold that best fits appears to be the one that combines an initial application of the 2σ threshold on the mean values with the subsequent application of the new 2σ threshold calculated on the remaining values. Among the detection algorithms, however, the use of a threshold of the 75th percentile on a series of 25 consecutive readings to ascertain the presence of methane is reported as an optimal result. For a sustainable approach to become truly practicable, it is necessary to have effective and reliable measurement systems. In this context, the integrated use of the highlighted algorithms allows for a greater identification of false positives which are therefore excluded both from the physical search for the leak and from the flow estimation calculations, arriving at a more consistent quantification, especially in the presence of low-emission flows. Full article

Wind energy is essential for promoting sustainability and renewable power solutions. However, ensuring stability and consistent performance in DFIG-based wind turbine systems (WTSs) remains challenging due to rapid wind speed variations, grid disturbances, and parameter uncertainties. These fluctuations result in power instability, increased overshoot, and prolonged settling times, negatively impacting grid compliance and system efficiency. Conventional proportional-integral (PI) controllers are simple and effective in steady-state conditions, but they lack adaptability in dynamic situations. Similarly, artificial intelligence (AI)-based controllers, such as fuzzy logic controllers (FLCs) and artificial neural networks (ANNs), improve adaptability but suffer from high computational demands and training complexity. To address these limitations, this paper presents a hybrid adaptive neuro-fuzzy inference system (ANFIS)-PI controller for DFIG-based WTS. The proposed controller integrates fuzzy logic adaptability with neural network-based learning, allowing real-time optimization of control parameters. Implemented within the rotor-side converter (RSC) and grid-side converter (GSC), ANFIS enhances reactive power management, grid compliance, and overall system stability. The system was tested under a step wind speed signal varying from 10 m/s to 12 m/s to evaluate its robustness. The simulation results confirmed that the ANFIS-PI controller significantly improved performance compared with the conventional PI controller. Specifically, it reduced rotor speed overshoot by 3%, torque overshoot by 12.5%, active power overshoot by 2%, and DC link voltage overshoot by 20%. Additionally, the ANFIS-PI controller shortened settling time by 50% for rotor speed, by 25% for torque, by 33% for active power, and by 16.7% for DC link voltage, ensuring faster stabilization, enhanced dynamic response, and greater efficiency. These improvements establish the ANFIS-PI controller as an advanced, computationally efficient, and scalable solution for enhancing the reliability of DFIG-based WTS, facilitating seamless integration of wind energy into modern power grids. Full article

Aircraft brake discs undergo rapid temperature rises during braking, critically impacting safety, lifespan, and adjacent components. Therefore, it is particularly important to study the heat transfer mechanism during the braking process and predict the temperature distribution of the brake disc. To address challenges in experimental studies (e.g., high costs and extreme conditions), this study employs full-scale numerical simulations to investigate heat transfer behaviours in medium-sized passenger aircraft brake discs. In the numerical simulation process, a coupling model that comprehensively considers the friction heat generation of the brake disc, the solid heat transfer between the discs, and the heat dissipation of the outer surface of the disc and the surrounding air is constructed to accurately describe the heat transfer characteristics of the brake disc under dynamic conditions. The study shows that the surface temperature of the brake disc rises sharply during the braking process, resulting in a significant increase in the temperature gradient; at the same time, the surrounding air flow state significantly affects the heat dissipation efficiency of the brake disc and affects its temperature distribution. Finally, the effectiveness of the numerical simulation was verified by experiments, and the maximum relative error between the experimental results and the simulation results was about 4.5%. This study provides a research basis for optimizing the structural design of the brake disc, improving its heat dissipation performance and operating safety. Full article

Despite their excellent mechanical properties, martensitic stainless steels present significant welding challenges due to their susceptibility to cracking and forming brittle microstructures during thermal cycles. While electron beam welding offers advantages through its high energy density and precise control over conventional welding methods, the induced residual stresses remain a critical concern. This study aims to determine surface residual stresses in electron beam welded AISI 410 martensitic stainless steel using a self-developed C-scan mode Magnetic Barkhausen Noise (MBN) measurement system. A novel calibration and measurement methodology was developed to establish a quantitative relationship between MBN signals and residual stress state. The residual stresses in the welded specimens were analyzed systematically using MBN and X-ray diffraction (XRD) measurements and microstructural characterization. The results revealed a strong correlation between MBN parameters and residual stress states, showing notable variations across the weld zones, i.e., approximately +350 MPa in the heat-affected zone and −50 MPa in the base metal. The experimental findings were also validated through finite element simulations. The correlation between experimental and numerical results confirms the reliability of the proposed MBN-based methodology and system. These findings provide valuable insights for industrial applications, offering a rapid and reliable non-destructive method for residual stress assessment in critical welded components. Full article

With the rapid development of fifth-generation (5G) mobile communication technology, the performance requirements for radio frequency front-end surface acoustic wave (SAW) devices have become increasingly stringent. Surface acoustic wave devices on piezoelectric thin film-based layered structures with high electromechanical coupling coefficients and low-frequency temperature compensation characteristics have emerged as a key solution. In this work, a SAW resonator based on an Al/41° Y-X LiNbO₃/SiO₂/poly-Si/Si multi-layered structure is proposed. FEM modeling of the proposed resonator and the influences of the thicknesses of the LiNbO₃, SiO₂, and Al electrodes on performances such as the parasitic noise, bandwidth, and electromechanical coupling coefficient are analyzed. Optimal parameters for the multi-layer piezoelectric structure are identified for offering large coupling up to 24%. Based on these findings, a single-port SAW resonator with an Al/41° Y-X LiNbO₃/SiO₂/poly-Si/Si substrate structure is fabricated. The experimental results align well with the simulation results; meanwhile, the SAW filter based on the proposed resonator demonstrates that a center frequency of 2.3 GHz, a 3-dB fractional bandwidth of 23.48%, and a minimum in-band insertion loss of only 0.343 dB are simultaneously achieved. This study provides guidance for the development of multi-layer film SAW resonator-based filters with high-performance. Full article

The combined use of laser beam and electric arc for welding thick clad steel plates in a single pass has been developed to solve the issues concerning the individual applications of the heat sources, such as the low filling efficiency of conventional electric arc methods and the drawbacks concerning laser beam defects due to rapid cooling and solidification. This work was addressed to the weldability assessment of ferritic steel plates, clad with austenitic stainless steel, under the laser-leading configuration, testing the effects of two different values of the inter-distance between the laser beam and the electric arc. Specimens of the welded zone were investigated by metallographic observations and EDS measurements; mechanical properties were characterized by the Vickers microhardness test and by the FIMEC instrumented indentation test to obtain the local values of the yield strength. Welding simulations by theoretical modelling were also carried out to outline the differences in the thermal fields generated by the two heat sources, their interaction, and their effect on the configurations of the weld pool and the thermal profiles to which the materials are subjected. The welding setup with higher inter-distance was more suitable for joining clad steel plates, since the action of the deep keyhole mode is substantially separated from that of the shallower electric arc. In this way, the addition of alloying elements, performed by melting the filler wire, concentrated in the cladding layer, helping maintain the austenitic microstructure, while the laser beam acts in depth along the thickness, autogenously welding the base steel. Full article

Through mechanical analysis, a comparison of the same type of cold rolled steel produced by two steel manufacturers, supplier 1 and supplier 2, has been carried out. The considered material is a steel that has undergone a quenching and partitioning heat treatment, i.e., a rapid cooling from the austenitizing temperature, followed by a holding treatment at a suitable temperature, so that the residual austenite is stabilized at room temperature. The following tests for mechanical properties were carried out: formability, through Nakajima test, tensile test, bending test, hole expansion test and fatigue strength analysis, through high cycle fatigue and low cycle fatigue test. In addition, to derive useful data for future simulations, tensile and Nakajima tests were analyzed by digital image correlation, which uses a monochrome camera to capture frames during the test, in order to analyze local deformations on investigated samples. Finite elements modeling has been carried out. A suitable calibration of a material card for the Abaqus Finite Element Analysis software has been performed. Through the combination of obtained results, a rational comparison of the two analyzed products has been obtained. Full article

The rapid urbanization of recent decades has intensified climate change challenges, demanding sophisticated solutions to build resilient and sustainable cities. A key aspect of sustainable urban planning is decentralizing and democratizing its processes, which requires citizen involvement from the early design stages. While current solutions such as digital tools, participatory workshops, gamification, and social media can enhance participation, they often exclude non-experts or those lacking digital skills. To address these limitations, this manuscript proposes a VR/AR gamified solution using open-source software and open GIS data. Specifically, it investigates the euPOLIS game as an innovative participatory tool offering an alternative to traditional approaches. This game decentralizes urban planning by shifting technical tasks to experts while citizens engage interactively, focusing solely on proposing solutions. To explore the potential of the proposed methodology, the euPOLIS game was demonstrated as a workshop activity in TNOC 2024 Festival, where 30 individuals from different academic background (i.e., citizens, architects, planners, etc.) voluntarily engaged and provided their impressions and feedback. The findings suggest that gamified solutions such as serious/simulation AR/VR games can effectively promote co-design, co-participation, and co-creation in urban planning in an inclusive and engaging manner. Full article

Imaging sonar is a crucial tool for underwater visual perception. Compared to 2D sonar images, 3D sonar images offer superior spatial positioning capabilities, although the data acquisition cost is higher and lacks open source references for data annotation, target detection, and semantic segmentation. This paper utilizes 3D imaging sonar to collect underwater data from three types of targets with 1534 effective frames, including a tire, mannequin, and table, in Liquan Lake, Shanxi Province, China. Based on these data, this study focuses on three innovative aspects as follows: rapid underwater data annotation, loss function optimization, and unsupervised moving target extraction in water. For rapid data annotation, a batch annotation method combining human expertise and multi-frame superposition is proposed. This method automatically generates single-frame target detection boxes based on multi-frame joint segmentation, offering advantages in speed, cost, and accuracy. For loss function optimization, a density-based loss function is introduced to address the issue of overfitting in dense regions due to the uneven distribution of point cloud data. By assigning different weights to data points in different density regions, the model pays more attention to accurate predictions in a sparse area, resulting in a 6.939 improvement in mIOU for semantic segmentation tasks, while lakebed mIOU achieved a high score of 99.28. For unsupervised moving target extraction, a multi-frame joint unsupervised moving target association extraction method called the Double DBSCAN, D-DBSCAN, is proposed. This method simulates human visual sensitivity to moving targets in water and uses a joint D-DBSCAN spatial clustering approach with single-frame and inter-frame superposition, achieving an improvement of 21.3 points in mAP. Finally, the paper summarizes the three proposed innovations and provides directions for further research. Full article