Search Results (269)

In the context of the rapid popularization of clean energy, the precise identification of surface defects on photovoltaic modules has become a core technical bottleneck limiting the operational efficiency of power stations. In response to the shortcomings of existing detection methods in identifying tiny defects and model efficiency, this study innovatively constructed the EER-DETR detection framework: firstly, a feature reconstruction module WDBB with a differentiable branch structure was introduced to significantly enhance the feature retention ability for fine cracks and other small targets; secondly, an adaptive feature pyramid network EHFPN was innovatively designed, which achieved efficient integration of multi-level features through a dynamic weight allocation mechanism, reducing the model complexity by 9.7% while maintaining detection accuracy, solving the industry problem of “precision—efficiency imbalance” in traditional feature pyramid networks; finally, an enhanced upsampling component was introduced to effectively address the problem of detail loss that occurs in traditional methods during image resolution enhancement. Experimental verification shows that the improved algorithm increased the average precision (mAP@0.5) on the panel dataset by 1.9%, and its comprehensive performance also exceeded RT-DETR. Based on the industry standard PVEL-AD, the detection rate of typical defects significantly improved compared to the baseline model. The core innovation of this research lies in the combination of differentiable architecture design and dynamic feature management, providing a detection tool for the intelligent operation and maintenance of photovoltaic power stations that possesses both high precision and lightweight characteristics. It has significant engineering application value and academic reference significance. Full article

Magnetic pulse welding (MPW) is a promising solid-state joining process that utilizes electromagnetic forces to create high-speed, impact-like collisions between two metal components. This welding technique is widely known for its ability to join dissimilar metals, including aluminum, steel, and copper, without the need for additional filler materials or fluxes. MPW offers several advantages, such as minimal heat input, no distortion or warping, and excellent joint strength and integrity. The process is highly efficient, with welding times typically ranging from microseconds to milliseconds, making it suitable for high-volume production applications in sectors including automotive, aerospace, electronics, and various other industries where strong and reliable joints are required. It provides a cost-effective solution for joining lightweight materials, reducing weight and improving fuel efficiency in transportation systems. This contribution concerns an application for the automotive sector (body-in-white) and specifically examines the welding of AA6082-T6 aluminum alloy with HC420LA cold-rolled micro-alloyed steel. One of the main aspects for MPW optimization is the determination of the process window that does not depend on the equipment used but rather on the parameters associated with the physical mechanisms of the process. It was demonstrated that process windows based on contact angle versus output voltage diagrams can be of interest for production use for a given component (shock absorbers, suspension struts, chassis components, instrument panel beams, next-generation crash boxes, etc.). The process window based on impact pressures versus impact velocity for different impact angles, in addition to not depending on the equipment, allows highlighting other factors such as the pressure welding threshold for different temperatures in the impact zone, critical transition speeds for straight or wavy interface formation, and the jetting/no jetting effect transition. Experimental results demonstrated that optimal welding conditions are achieved with impact velocities between 900 and 1200 m/s, impact pressures of 3000–4000 MPa, and impact angles ranging from 18–35°. These conditions correspond to optimal technological parameters including gaps of 1.5–2 mm and output voltages between 7.5 and 8.5 kV. Successful welds require mean energy values above 20 kJ and weld specific energy values exceeding 150 kJ/m². The study establishes critical failure thresholds: welds consistently failed when gap distances exceeded 3 mm, output voltage dropped below 5.5 kV, or impact pressures fell below 2000 MPa. To determine these impact parameters, relationships based on Buckingham’s π theorem provide a viable solution closely aligned with experimental reality. Additionally, shear tests were conducted to determine weld cohesion, enabling the integration of mechanical resistance isovalues into the process window. The findings reveal an inverse relationship between impact angle and weld specific energy, with higher impact velocities producing thicker intermetallic compounds (IMCs), emphasizing the need for careful parameter optimization to balance weld strength and IMC formation. Full article

The construction sector faces growing pressure to adopt sustainable alternatives amid the global plastic-waste crisis. This study presents a novel use of mechanically recycled high-density polyethylene (HDPE) and polypropylene (PP) to manufacture full-scale plastic rebars for mortar-free, light-load construction applications. A total of 48 samples, plain and ribbed, across three diameters (12 mm, 19 mm, and 25 mm) were fabricated and tested. Due to the absence of standardized protocols for recycled plastic rebars, tensile testing was conducted in reference to ASTM A615. Characterization techniques such as X-ray diffraction (XRD), and Scanning Electron Microscopy (SEM) confirmed the material’s structural features and polymer integrity. XRD confirmed the crystalline phases of HDPE and PP, while SEM revealed ductile fracture in HDPE and brittle failure in PP. The 25 mm ribbed PP rebars demonstrated superior performance, achieving a maximum load capacity of 12.2 ± 0.6 kN, a toughness index of 19.3 ± 1.0, and energy absorption of 101.6 ± 5.0 N-m × 10. These results affirm their suitability for lightweight structural components such as boundary walls, partition panels, and mortar-free interlocking systems. Unlike prior studies that confined recycled plastics to filler roles in composites, this work validates their direct application as full-section, load-bearing members. Additionally, a polynomial-based empirical model was formulated to predict the tensile behavior of the recycled rebars. The findings underscore the potential of mechanical extrusion as a low-emission, scalable solution to convert plastic waste into durable construction materials that support circular economic principles. Full article

In this study, to optimize the lightweight design of power battery cases for new energy vehicles and meet impact resistance requirements, the mechanical properties of honeycomb sandwich composites were experimentally investigated by varying carbon/glass fiber hybrid ratios. Carbon fiber and glass fiber hybrid laminates were used as the panel, and the aluminum honeycomb was used as the core layer to prepare sandwich composite materials through vacuum-assisted resin infusion (VARI). Then, the flexural and impact properties of honeycomb sandwich composites with different hybrid ratios were tested, respectively. The damage morphology and the damage mechanism of the hybrid composites were analyzed by 3D profile scanning. The results demonstrated that compared to glass fiber-reinforced panels, hybrid panels significantly enhanced the flexural load-bearing capacity of the sandwich composites, exhibiting maximum increases of 26.5% and 34.38% in the L direction and W direction, respectively. Carbon fiber effectively improved the impact resistance of specimens, with the maximum impact load increasing by 53.09% and energy absorption showing measurable enhancement, while glass fiber improves toughness and reduces the severity of damage. This study includes damage analysis and mechanical behavior change analysis of composite materials, which can provide a reference for the application of composite materials in the battery box shell. Full article

The development of lightweight construction is of crucial importance for the development of sustainable technologies and for the reduction in carbon dioxide emissions, especially in the automotive industry. This study aims to address the challenges associated with manufacturing plant fibre-based polymer composites. The investigation focused on two novel formulations of bio-based unsaturated polyester resins, assessing their viability as a matrix in plant fibre-reinforced composites within the context of automotive applications. The study addresses the challenges related to the preparation and processing of the system, leading to the necessity of diluting the resin with (hydroxymethyl)methacrylate (HEMA) to achieve an applicable viscosity. Two different flax fibre textiles, in the form of a short fibre mat and a woven fabric, were used as reinforcement. The composite panels were manufactured using the vacuum-assisted resin infusion (VARI) process. The most efficacious material combination, comprising Bcomp^® ampliTex™ 5040 and STRUKTOL^® POLYVERTEC^® 3831, with viscosity modified by 39% HEMA, exhibited a consistent fibre volume fraction of 40% and a glass transition temperature of 70 °C. In addition, the mechanical behaviour in the 0°-direction demonstrated tensile strength and modulus values of approximately 99 MPa and 9 GPa, respectively, accompanied by an elongation at break of 2%. The flexural modulus was found to be 7 GPa, and the flexural strength 94 MPa. Full article

The integral welded panel represents a highly promising aircraft structural component, owing to its lightweight design and reduced connector requirements. However, the complexity of its welded structure results in the formation of cross-welded joints. This study systematically investigated the mechanical properties of the cross-welded joints through tensile tests across different welded regions, which were complemented by fracture morphology examination via scanning electron microscopy (SEM). The residual stress distribution was characterized using X-ray diffraction, while electron backscatter diffraction (EBSD) analysis was used to elucidate the relationship between residual stress and microstructure. Key findings revealed that the cross-welded zone exhibited lower yield strength and ductility than the single-welded zone, and the advancing heat-affected zone demonstrated superior tensile properties relative to the retreating side. Residual stress analysis showed that the cross-welded joint lacked the “double peak” profile characteristic and displayed lower maximum residual stress than the single-welded joint. EBSD analysis indicated significant grain elongation in the cross-welded zone due to mechanical forces during the welding process, resulting in higher dislocation density and deformation, corresponding with elevated residual stress levels. Full article

Bamboo is a fast-growing biomass material with excellent performance, making it a preferred choice for the development of green and low-carbon building materials. However, challenges such as combustibility and difficulties in processing and utilization persist. In this study, bamboo chips are wrapped in fiberglass cloth and cemented with magnesium oxychloride cement (MOC) to develop green, environmentally friendly, flame-retardant, and carbon-storing bamboo-based composite panels. Firstly, the optimal ratio of the inorganic adhesive MOC was systematically investigated, and flue gas desulfurization gypsum (FG) was added to enhance its water resistance. The flexural strengths of the composite board in the direction of the bamboo fiber and that perpendicular to it were found to be 15.71 MPa and 34.64 MPa, respectively. Secondly, numerical simulations were conducted alongside plate experiments, analyzing the floor and wall made from the boards. The results indicate that since the fiber-reinforced bamboo board as a lightweight wall can meet the requirements for a two-story building, it does not satisfy safety standards as a floor slab due to the higher loads. Despite this limitation, the fiber-reinforced bamboo board shows promising application prospects as a green and low-carbon alternative. Full article

This study investigates the impact failure behavior of aluminum-composite sandwich panels, aluminum sheets, and composite laminates. Aluminum alloy sheets possess excellent ductility and plasticity, while carbon fiber composite sheets exhibit high strength, high rigidity, and superior heat resistance. The sandwich panel structure, composed of two layers of aluminum alloy sheets and a central carbon fiber composite sheet, offers the advantages of being lightweight and high strength. These three types of specimens were subjected to impact energies of 15 J, 25 J, and 50 J. The numerical simulations employ LS-DYNA finite element software, with additional investigations into the energy absorption characteristics, which were employed and compared with the experiment. The experimental results indicate that aluminum alloy sheets only exhibit indentation under all three impact energies. Carbon fiber composite sheets sustain damage without penetration at 15 J but experience penetration failure at 25 J and 50 J. Aluminum-composite sandwich panels exhibit greater resistance to failure as compared to carbon fiber composites. At 15 J and 25 J, the top aluminum layer shows indentation, while the bottom aluminum layer develops cracks. At 50 J, complete penetration occurs. A comparison of damage morphology and force–time curves shows good agreement between the experimental and simulation results. While the carbon fiber composite plate exhibits the highest SEA, it also has the largest damage diameter, indicating more severe damage. In contrast, the aluminum alloy panel has the lowest specific energy absorption (SEA) due to its high weight. The aluminum-composite sandwich panel demonstrates intermediate performance in both damage diameter and SEA, striking a balance between the other two specimens. Full article

Forming hybrid structures into complex shapes is key to address lightweighting of automotive parts. Recently, an innovative joining technique between aluminium and Carbon Fibre-Reinforced Polymer (CFRP) based on mechanical interlocking through sheet punching has been developed. However, scaling up the solution requires the assessment of challenges, such as multi-material forming and joint integrity, after forming operations. Therefore, this work proves the feasibility of forming aluminium–CFRP prepreg panels into complex omega-shaped profiles following a conventional cold-stamping process. Forming without defects was possible even in specimens featuring mechanical joints generated through punching. The effect of the CFRP position (in the inner or the outer side of the formed profile), the number of mechanical joints, the addition of a Glass Fibre-Reinforced Polymer (GFRP) intermediate layer to prevent galvanic corrosion and adequate lubrication on necking, cracking, springback behaviour and the final geometry after curing were studied. Compression tests were performed to assess the mechanical response of the hybrid profile, and the results showed that the addition of CFRP in the aluminium omega profile changed the buckling behaviour from global bending to axial folding, increasing the maximum compression load. Additionally, the presence of mechanical interlocking joints further improved the mechanical performance and led to a more controlled failure due to buckling localization in the geometric discontinuity. Full article

The aim of this study is to investigate the potential of wood composites as sustainable acoustic materials and to explore their integration with advanced manufacturing techniques for improved performance. Using a comprehensive review methodology, the paper analyzes recent innovations in wood composites, focusing on the combination with other sustainable materials such as expanded polystyrene (EPS) and natural fibers. The results show that wood composites can achieve sound absorption coefficients (α) of up to 0.9, with oak panels showing transmission losses of up to 11 dB. In addition, advanced designs, including biodegradable panels and lightweight honeycomb structures, significantly improve sound transmission loss, with an average sound transmission loss (TLeq) of up to 28.3 dB reported for composite panels made from waste tire rubber. In addition, the study highlights the environmental benefits achieved through the use of agricultural byproducts and industrial waste in the development of these materials, confirming the role of wood composites as a carbon-neutral alternative in the quest for green building solutions. This study provides valuable insights into the transformative potential of wood composites for sustainable acoustic applications. Full article

The development of sustainable and energy-efficient construction materials is crucial for mitigating the growing environmental impact of the building sector. This study introduces a new lightweight sandwich panel, featuring a core made of lightweight concrete with rice husk bio-aggregate (RHB) and faces constructed from foamed cementitious composites. The innovative design aims to promote sustainability by utilizing agro-industrial waste while maintaining satisfactory mechanical performance. Composites were produced with 4% short sisal fibers and matrices containing 15%, 20%, and 30% foaming agent. These composites were evaluated for density, direct compression, and four-point bending. It was found that the mixture with 20% foam volume demonstrated the highest efficiency for use in the production of sandwich panels. Concrete mixtures containing 50%, 60%, and 70% rice husk bio-aggregates were tested for density and compressive strength and used in the production of lightweight sandwich panels with densities ranging from 670 to 1000 kg/m³. Mechanical evaluation under flexion and shear indicated that the presence of fibers inhibited crack propagation in the face, enabling the creation of lightweight sandwich panels with deflection-hardening behavior. On the other hand, the increase in RHB content led to a reduction in the ultimate stress on the face, the core shear ultimate stress, and the toughness of the sandwich panels. Full article

Modularised wall panels are increasingly used in building and construction. A new double-skin composite (DSC) wall system technology uses clinch seams to combine two roll-formed open section profiles into a hollow steel shell that is then filled with a light-weight concrete foam and can provide a fire-rated DSC solution for use in commercial and high-rise buildings. One important material parameter for the application is the panel performance in wind loading. This study presents a first fundamental analysis of the structural behaviour of the new DSC wall panel relevant to wind loading. For this, 3-point and 4-point bending tests combined with in situ camera analysis are performed and complimented with the analysis of seam strength and the concrete material parameters. The experimental results provide the first experimental evidence that the aerated concrete core material of the DSC panel only has a minor effect on the wall performance in bending. Most of the bending loads are absorbed by the tensile and compressive deformation of the steel outer shell and the shear deformation near the clinch seam. In this way, failure at maximum load is not initiated by concrete cracking but by steel sheet buckling or a mixed failure mode that combines steel buckling and seam opening. Full article

3D-Kagome lattice sandwich panels are mainly composed of upper and lower panels and a series of symmetrically and periodically arranged lattices, known for their excellent high specific stiffness, high specific strength, and energy absorption capacity. The inherent geometrical symmetry of the 3D-Kagome lattice plays a crucial role in achieving superior mechanical stability and load distribution efficiency. This structural symmetry enhances the uniformity of stress distribution, making it highly suitable for automotive vibration suppression, such as battery protection for electric vehicles. In this study, a polyurethane foam-filled, symmetry-enhanced 3D-Kagome sandwich panel is designed following an optimization of the lattice structure. A novel fabrication method combining precision wire-cutting, interlocking core assembly, and in situ foam filling is employed to ensure a high degree of integration and manufacturability of the composite structure. Its mechanical properties and energy absorption characteristics are systematically evaluated through a series of experimental tests, including quasi-static compression, three-point bending, and low-speed impact. The study analyzes the effects of core height on the structural stiffness, strength, and energy absorption capacity under varying loads, elucidating the failure mechanisms inherent to the symmetrical lattice sandwich configurations. The results show that the foam-filled sandwich panels exhibit significant improvements in mechanical performance compared to the unfilled ones. Specifically, the panels with core heights of 15 mm, 20 mm, and 25 mm demonstrate increases in bending stiffness of 47.3%, 53.5%, and 51.3%, respectively, along with corresponding increases in bending strength of 45.5%, 53.1%, and 50.9%. The experimental findings provide a fundamental understanding of foam-filled lattice sandwich structures, offering insights into their structural optimization for lightweight energy-absorbing applications. This study establishes a foundation for the development of advanced crash-resistant materials for automotive, aerospace, and protective engineering applications. This work highlights the structural advantages and crashworthiness potential of foam-filled Kagome sandwich panels, providing a promising foundation for their application in electric vehicle battery enclosures, aerospace impact shields, and advanced protective systems. Full article

Snow accumulation on solar panels presents a significant challenge to energy generation in snowy regions, reducing the efficiency of solar photovoltaic (PV) systems and impacting economic viability. While prior studies have explored snow detection using fixed-camera setups, these methods suffer from scalability limitations, stationary viewpoints, and the need for reference images. This study introduces an automated deep-learning framework that leverages drone-captured imagery to detect and quantify snow coverage on solar panels, aiming to enhance power forecasting and optimize snow removal strategies in winter conditions. We developed and evaluated two approaches using YOLO-based models: Approach 1, a high-precision method utilizing a two-class detection model, and Approach 2, a real-time single-class detection model optimized for fast inference. While Approach 1 demonstrated superior accuracy, achieving an overall precision of 89% and recall of 82%, it is computationally expensive, making it more suitable for strategic decision making. Approach 2, with a precision of 93% and a recall of 75%, provides a lightweight and efficient alternative for real-time monitoring but is sensitive to lighting variations. The proposed framework calculates snow coverage percentages (SCP) to support snow removal planning, minimize downtime, and optimize power generation. Compared to fixed-camera-based snow detection models, our approach leverages drone imagery to improve detection precision while offering greater scalability to be adopted for large solar farms. Qualitative and quantitative analysis of both approaches is presented in this paper, highlighting their strengths and weaknesses in different environmental conditions. Full article

The rapid growth of solar photovoltaic (PV) installations worldwide has increased the need for the effective monitoring and maintenance of these vital renewable energy assets. PV systems are crucial in reducing greenhouse gas emissions and diversifying electricity generation. However, they often experience faults and damage during manufacturing or operation, significantly impacting their performance, while thermal infrared imaging provides a promising non-invasive method for detecting common defects such as hotspots, cracks, and bypass diode failures, current deep learning approaches for fault classification generally rely on computationally intensive architectures or closed-source solutions, constraining their practical use in real-time situations involving low-resolution thermal data. To tackle these challenges, we introduce SlantNet, a lightweight neural network crafted to classify thermal PV defects efficiently and accurately. At its core, SlantNet incorporates an innovative Slant Convolution (SC) layer that utilizes slant transformation to enhance directional feature extraction and capture subtle thermal gradient variations essential for fault detection. We complement this architectural advancement with a thermal-specific image enhancement augmentation strategy that employs adaptive contrast adjustments to bolster model robustness under the noisy and class-imbalanced conditions typically encountered in field applications. Extensive experimental validation on a comprehensive solar panel defect detection benchmark dataset showcases SlantNet’s exceptional performance. Our method achieves a 95.1% classification accuracy while reducing computational overhead by approximately 60% compared to leading models. Full article