Search Results (2,443)

China is one of the countries severely affected by earthquakes, making precise and timely identification of earthquake precursors essential for reducing casualties and property damage. A novel method is proposed that combines a rock acoustic emission (AE) detection technique with deep learning methods to facilitate real-time monitoring and advance earthquake precursor detection. The AE equipment and seismometers were installed in a granite tunnel 150 m deep in the mountains of eastern Guangdong, China, allowing for the collection of experimental data on the correlation between rock AE and seismic activity. The deep learning model uses features from rock AE time series, including AE events, rate, frequency, and amplitude, as inputs, and estimates the likelihood of seismic events as the output. Precursor features are extracted to create the AE and seismic dataset, and three deep learning models are trained using neural networks, with validation and testing. The results show that after 1000 training cycles, the deep learning model achieves an accuracy of 98.7% on the validation set. On the test set, it reaches a recognition accuracy of 97.6%, with a recall rate of 99.6% and an F₁ score of 0.975. Additionally, it successfully identified the two biggest seismic events during the monitoring period, confirming its effectiveness in practical applications. Compared to traditional analysis methods, the deep learning model can automatically process and analyse recorded massive AE data, enabling real-time monitoring of seismic events and timely earthquake warning in the future. This study serves as a valuable reference for earthquake disaster prevention and intelligent early warning. Full article

This study presents a comparative analysis of the annual performances of stationary and dual-axis sun-tracked photovoltaic–thermal (PVT) systems. The experimental research was conducted at a demonstration site in Oświęcim, Poland, where both systems were evaluated in terms of electricity and heat production. The test installation consisted of thirty stationary PVT modules and five dual-axis sun-tracking systems, each equipped with six PV modules. An innovative cooling system was developed for the PVT modules, consisting of a surface-mounted heat sink installed on the rear side of each panel. The system includes embedded tubes through which a cooling fluid circulates, enabling efficient heat recovery. The results indicated that the stationary PVT system outperformed a conventional fixed PV installation, whose expected output was estimated using PVGIS data. Specifically, the stationary PVT system generated 26.1 kWh/m² more electricity annually, representing a 14.8% increase. The sun-tracked PVT modules yielded even higher gains, producing 42% more electricity than the stationary system, with particularly notable improvements during the autumn and winter seasons. After accounting for the electricity consumed by the tracking mechanisms, the sun-tracked PVT system still delivered a 34% higher net electricity output. Moreover, it enhanced the thermal energy output by 85%. The findings contribute to the ongoing development of high-performance PVT systems and provide valuable insights for their optimal deployment in various climatic conditions, supporting the broader integration of renewable energy technologies in building energy systems. Full article

Surface Air-Cooled Oil Coolers (SACOCs) can become a critical component in managing the increasing thermal loads of modern turbofan engines. Installed within the bypass duct, SACOCs utilize high-mass flow bypass air for convective heat rejection, reducing reliance on traditional Fuel-Oil Heat Exchangers. This review explores SACOC design principles, integration challenges, aerodynamic impacts, and performance trade-offs. Emphasis is placed on the balance between thermal efficiency and aerodynamic penalties such as pressure drop and flow distortion. Experimental techniques, including wind tunnel testing, are discussed alongside numerical methods, and Conjugate Heat Transfer modeling. Presented studies mostly demonstrate the impact of fin geometry and placement on both heat transfer and drag. Optimization strategies and Additive Manufacturing techniques are also covered. SACOCs are positioned to play a central role in future propulsion systems, especially in ultra-high bypass ratio and hybrid-electric architectures, where traditional cooling strategies are insufficient. This review highlights current advancements, identifies limitations, and outlines research directions to enhance SACOC efficiency in aerospace applications. Full article

The aim of this study was to determine the connection between oscillations in operating pressure values and the appearance of various irregularities on machined surfaces. Such oscillations are a consequence of the high water pressure generated during abrasive water jet machining. Oscillations in the operating pressure values are periodic, namely due to the cyclic operation of the intensifier and the physical characteristics of water. One of the most common means of reducing this phenomenon is installing an attenuator in the hydraulic system or a phased intensifier system. The main hypothesis of this study was that the topography of a machined surface is directly influenced by the inability of the pressure accumulator to fully absorb water pressure oscillations. In this study, we monitored changes in hydraulic oil pressure values at the intensifier entrance and their connection with irregularities on the machined surface—such as waviness—when cutting aluminum AlMg3 of different thicknesses. Experimental research was conducted in order to establish this connection. Aluminum AlMg3 of different thicknesses—from 6 mm to 12 mm—was cut with different traverse speeds while hydraulic oil pressure values were monitored. The pressure signals thus obtained were analyzed by applying the fast Fourier transform (FFT) algorithm. We identified a single-sided pressure signal amplitude spectrum. The frequency axis can be transformed by multiplying inverse frequency data with traverse speed; in this way, a single-sided amplitude spectrum can be obtained, examined against the period in which striations are expected to appear (in millimeters). In the lower zone of the analyzed samples, striations are observed at intervals determined by the dominant hydraulic oil pressure harmonics, which are transferred to the operating pressure. In other words, we demonstrate how the machined surface topography is directly induced by water jet pressure frequency characteristics. Full article

The acoustic performance of windows significantly influences evaluations of building quality, particularly in urban environments. This study presents the results of laboratory tests on the airborne sound insulation of windows with dimensions greater than those specified in ISO 10140-5:2021-10. The aim was to determine the impact of construction details and installation techniques on sound insulation, specifically R_w and R_w + C_tr values. The experimental variables included mounting methods (expansion tape versus low-pressure polyurethane foam), the presence or absence of a threshold in the lower frame, and the type of mullion (fixed versus movable). The tests involved two types of IGUs characterized by different acoustic properties. The findings indicate that the frame configuration, including threshold and mullion type, has a negligible influence on sound insulation. However, the standard method for estimating acoustic performance (EN 14351-1:2006 + A2:2017), which relies on IGU-based data, proved unreliable for modern window assemblies. The estimated values of R_w and R_w + C_tr were consistently lower than those obtained from direct laboratory measurements. These results highlight the need for verification through full-size window testing and suggest that reliance on simplified estimation procedures may lead to underperformance in real-world acoustic applications. Full article

Pyrolysis technology currently serves as a significant method for recycling and reducing waste tires. In this paper, in order to improve the heat transfer efficiency during the pyrolysis of waste tires in a horizontal rotary furnace and the yield of pyrolysis oil, the effect laws of tire particle size, rotary furnace rotation speed, enhanced heat transfer materials, and adding spiral fins on heat transfer performance and pyrolysis product distribution were studied, respectively. The innovation lies in two aspects: first, aiming at the problems of slow heat transfer and low pyrolysis efficiency in horizontal rotary furnaces, we identified technical measures through experiments to enhance heat transfer, thereby accelerating pyrolysis and reducing energy consumption; second, with the goal of increasing high-value pyrolysis oil yield, we determined optimal operating parameters to improve economic and sustainability outcomes. The results showed that powdered particles of waste tires were heated more evenly during the pyrolysis process, which increased the overall heat transfer coefficient and the proportion of liquid products. When the rotational speed of the rotary pyrolysis furnace exceeded 2 rpm, there was sufficient contact between the material and the furnace wall, which was beneficial to the improvement of heat transfer performance. Adding heat transfer enhancement materials such as carborundum and white alundum could improve the heat transfer performance between the pyrolysis furnace and the material. Notably, a rotational speed of 3 rpm and carborundum were used as a heat transfer enhancement material with powdered waste tire particles during the pyrolysis process; the overall heat transfer coefficient was the highest, which was 16.89 W/(m²·K), and the proportion of pyrolysis oil products was 46.1%. When spiral fins were installed, the comprehensive heat transfer coefficient was increased from 12.78 W/(m²·K) to 16.32 W/(m²·K). The experimental results show that by increasing the speed of the pyrolysis furnace, adding heat transfer enhancing materials with high thermal conductivity to waste tires, and appropriate particle size, the heat transfer performance and pyrolysis rate can be improved, and energy consumption can be reduced. Full article

Wireless sensor networks provide a solution for structural health monitoring of aviation pipelines. In the installation environment of aviation pipelines, widespread vibrations can be utilized to extract energy through vibration energy harvesting technology to achieve self-powering of sensors. This study analyzed the vibration characteristics of aviation pipeline structures. The vibration characteristics and influencing factors of typical aviation pipeline structures were obtained through simulations and experiments. An N-shaped symmetric vibration energy harvester was designed considering the limited space in aviation pipeline structures. To improve the efficiency of electrical energy extraction from the vibration energy harvester, expand its operating frequency band, and achieve efficient vibration energy harvesting, this study first analyzed its natural frequency characteristics through theoretical analysis. Finite element simulation software was then used to analyze the effects of the external excitation acceleration direction, mass and combination of counterweights, piezoelectric sheet length, and piezoelectric material placement on the output power of the energy harvester. The structural parameters of the vibration energy harvester were optimized, and the optimal working conditions were determined. The experimental results indicate that the N-shaped symmetric vibration energy harvester designed and optimized in this study improves the efficiency of vibration energy harvesting and can be arranged in the limited space of aviation pipeline structures. It achieves efficient energy harvesting under multi-modal conditions, different excitation directions, and a wide operating frequency band, thus meeting the practical application requirement and engineering feasibility of aircraft design. Full article

Foreign Object Debris (FOD) detection is paramount for airport operations. The precise identification and removal of FOD are critical for ensuring airplane flight safety. This study collected FOD images using optical imaging sensors installed at Urumqi Airport and created a custom FOD dataset based on these images. To address the challenges of small targets and complex backgrounds in the dataset, this paper proposes optimizations and improvements based on the advanced detection network Dab-Deformable. First, this paper introduces a Lightweight Deep-Shallow Feature Fusion algorithm (LDSFF), which integrates a hotspot sensing network and a spatial mapping enhancer aimed at focusing the model on significant regions. Second, we devise a Multi-Directional Deformable Channel Attention (MDDCA) module for rational feature weight allocation. Furthermore, a feedback mechanism is incorporated into the encoder structure, enhancing the model’s capacity to capture complex dependencies within sequential data. Additionally, when combined with a Threshold Selection (TS) algorithm, the model effectively mitigates the distraction caused by the serialization of multi-layer feature maps in the Transformer architecture. Experimental results on the optical small FOD dataset show that the proposed network achieves a robust performance and improved accuracy in FOD detection. Full article

This study focuses on the optimization of valve assemblies in downhole rod pumping units (DRPUs), which remain the predominant artificial lift technology in oil production worldwide. The research addresses the critical issue of premature failures in DRPUs caused by leakage in valve pairs, i.e., a problem that accounts for approximately 15% of all failures, as identified in a statistical analysis of the 2022 operational data from the Uzen oilfield in Kazakhstan. The leakage is primarily attributed to the accumulation of mechanical impurities and paraffin deposits between the valve ball and seat, leading to concentrated surface wear and compromised sealing. To mitigate this issue, a novel valve assembly design was developed featuring a flow turbulizer positioned beneath the valve seat. The turbulizer generates controlled vortex motion in the fluid flow, which increases the rotational frequency of the valve ball during operation. This motion promotes more uniform wear across the contact surfaces and reduces the risk of localized degradation. The turbulizers were manufactured using additive FDM technology, and several design variants were tested in a full-scale laboratory setup simulating downhole conditions. Experimental results revealed that the most effective configuration was a spiral plate turbulizer with a 7.5 mm width, installed without axis deviation from the vertical, which achieved the highest ball rotation frequency and enhanced lapping effect between the ball and the seat. Subsequent field trials using valves with duralumin-based turbulizers demonstrated increased operational lifespans compared to standard valves, confirming the viability of the proposed solution. However, cases of abrasive wear were observed under conditions of high mechanical impurity concentration, indicating the need for more durable materials. To address this, the study recommends transitioning to 316 L stainless steel for turbulizer fabrication due to its superior tensile strength, corrosion resistance, and wear resistance. Implementing this design improvement can significantly reduce maintenance intervals, improve pump reliability, and lower operating costs in mature oilfields with high water cut and solid content. The findings of this research contribute to the broader efforts in petroleum engineering to enhance the longevity and performance of artificial lift systems through targeted mechanical design improvements and material innovation. Full article

This study conducts a numerical simulation of the working performance of a single horizontal shaft forced mixer using the Discrete Element Method (DEM). It systematically investigates the effects of blade installation angle, feeding method, mixing speed, and coarse aggregate particle size on the mixing uniformity. A 1:2 scale model was developed, incorporating Newton’s laws of motion and a soft-sphere contact model to simulate the particle trajectories and interactions during mixing. The results indicate that top–bottom feeding enhances mixing efficiency significantly by forming vertical convective circulation, achieving a mixing uniformity above 0.9. A moderate rotation speed of 30 rpm provides the best balance between energy consumption and mixing performance. As the coarse aggregate size increases (from 9 mm to 15 mm), the enhanced particle inertia leads to a decrease in mixing uniformity (from 0.9 to 0.6). Additionally, the discrepancy between simulation and experimental results is less than 0.1, validating the reliability of the model. This research offers theoretical guidance for the structural optimization and parameter selection of single-shaft mixers, contributing to improved mixing efficiency and concrete quality in engineering applications. Full article

Deep-sea oil and gas pipelines undergo significant plastic strain during reel-lay installation. Additionally, the static strain aging phenomenon that occurs during service can further deteriorate the mechanical properties of the pipelines. This study investigates the plastic deformation mechanism of reel-lay pipeline steel by subjecting the test steel to 5% pre-strain followed by aging treatment at 250 °C for 1 h. The present study systematically correlates the evolution of mechanical properties with microstructural changes through microstructural characterization techniques such as EBSD, TEM, and XRD. The results demonstrate that after pre-straining, the yield strength of the experimental steel increases due to dislocation strengthening and residual stress generation, while its uniform elongation decreases. Although no significant changes in grain size are observed macroscopically, microstructural characterization reveals a substantial increase in dislocation density within the matrix, forming dislocation cells and walls. These substructures lead to a deterioration of the material’s work hardening capacity. Following aging treatment, the tested steel exhibits further increased yield strength and reduced uniform elongation. After aging treatment, although the dislocation density in the matrix slightly decreases and dislocation tangles are somewhat reduced, the Cottrell atmosphere pinning effect leads to a further decline in work hardening capability, ultimately resulting in the deterioration of plasticity in reel-lay pipeline steel. The instantaneous hardening exponent curve shows that the work hardening phenomenon becomes more pronounced in the tested steel after strain aging as the tempering temperature increases. Full article

The use of short cylinders of recycled aggregate concrete (RAC) reinforced with basalt fiber-reinforced polymer (BFRP) circumferential strips and polyvinyl chloride (PVC) tubes has been proven effective in previous studies. However, BFRP circumferential strips are cumbersome to install and do not ensure the integrity of the BFRP strips. Therefore, this study investigates axial compression experiments on RAC short cylinders reinforced with BFRP spiral strips and PVC tubes. A combination of experimental studies, finite element simulations, and theoretical analyses revealed that the winding angle and spacing of BFRP strips significantly affect the load-bearing capacity and ductility of the restrained specimens. Additionally, an improved strength model was developed based on an existing model. When evaluated using both computational and experimental results, the equations generated in this study showed an average error of less than 10%. The findings indicate that the composite structure provides effective reinforcement and offers valuable reference information for practical applications. Full article

Efficient detection of road surface defects is vital for timely maintenance and traffic safety. This study introduces a novel AI-powered web framework, TriRoad AI, that integrates multiple versions of the You Only Look Once (YOLO) object detection algorithms—specifically YOLOv8 and YOLOv11—for automated detection of potholes and cracks. A user-friendly browser interface was developed to enable real-time image analysis, confidence-based prediction filtering, and severity-based geolocation mapping using OpenStreetMap. Experimental evaluation was conducted using two datasets: one from online sources and another from field-collected images in Ankara, Turkey. YOLOv8 achieved a mean accuracy of 88.43% on internet-sourced images, while YOLOv11-B demonstrated higher robustness in challenging field environments with a detection accuracy of 46.15%, and YOLOv8 followed closely with 44.92% on mixed field images. The Gemini AI model, although highly effective in controlled environments (97.64% detection accuracy), exhibited a significant performance drop of up to 80% in complex field scenarios, with its accuracy falling to 18.50%. The proposed platform’s uniqueness lies in its fully integrated, browser-based design, requiring no device-specific installation, and its incorporation of severity classification with interactive geospatial visualization. These contributions address current gaps in generalization, accessibility, and practical deployment, offering a scalable solution for smart infrastructure monitoring and preventive maintenance planning in urban environments. Full article

Precision irrigation plays a crucial role in managing crop production in a sustainable and environmentally friendly manner. This study builds on the results of the GreenWaterDrone project, aiming to estimate, in real time, the actual water requirements of crop fields using the crop water stress index, integrating infrared canopy temperature, air temperature, relative humidity, and thermal and near-infrared imagery. To achieve this, a state-of-the-art aerial micrometeorological station (AMMS), equipped with an infrared thermal sensor, temperature–humidity sensor, and advanced multispectral and thermal cameras is mounted on an unmanned aerial system (UAS), thus minimizing crop field intervention and permanently installed equipment maintenance. Additionally, data from satellite systems and ground micrometeorological stations (GMMS) are integrated to enhance and upscale system results from the local field to the regional level. The research was conducted over two years of pilot testing in the municipality of Trifilia (Peloponnese, Greece) on pilot potato and watermelon crops, which are primary cultivations in the region. Results revealed that empirical irrigation applied to the rhizosphere significantly exceeded crop water needs, with over-irrigation exceeding by 390% the maximum requirement in the case of potato. Furthermore, correlations between high-resolution remote and proximal sensors were strong, while associations with coarser Landsat 8 satellite data, to upscale the local pilot field experimental results, were moderate. By applying a comprehensive model for upscaling pilot field results, to the overall Trifilia region, project findings proved adequate for supporting sustainable irrigation planning through simulation scenarios. The results of this study, in the context of the overall services introduced by the project, provide valuable insights for farmers, agricultural scientists, and local/regional authorities and stakeholders, facilitating improved regional water management and sustainable agricultural policies. Full article

As global electricity demand increases and concerns over fossil fuel usage intensify, renewable energy sources have gained significant attention. Solar energy stands out due to its low installation costs and suitability for deployment. However, solar power generation remains difficult to predict because of its dependence on weather conditions and decentralized infrastructure. To address this challenge, this study proposes a flexible hybrid ensemble (FHE) framework that dynamically selects the most appropriate base model based on prediction error patterns. Unlike traditional ensemble methods that aggregate all base model outputs, the FHE employs a meta-model to leverage the strengths of individual models while mitigating their weaknesses. The FHE is evaluated using data from four solar power plants and is benchmarked against several state-of-the-art models and conventional hybrid ensemble techniques. Experimental results demonstrate that the FHE framework achieves superior predictive performance, improving the Mean Absolute Percentage Error by 30% compared to the SVR model. Moreover, the FHE model maintains high accuracy across diverse weather conditions and eliminates the need for preliminary validation of base and ensemble models, streamlining the deployment process. These findings highlight the FHE framework’s potential as a robust and scalable solution for forecasting in small-scale distributed solar power systems. Full article