Search Results (1,460)

Cup rupture failures in strip steel welds can lead to strip breakage, resulting in unplanned downtime of high-speed continuous rolling mills and scrap steel losses. Manual visual inspection suffers from a high false positive rate and cannot meet the production cycle time requirements. This paper proposes a lightweight online cup rupture visual inspection method based on an improved YOLOv10 algorithm. The backbone feature extraction network is replaced with ShuffleNetV2 to reduce the model’s parameter count and computational complexity. An ECA attention mechanism is incorporated into the backbone network to enhance the model’s focus on cup rupture micro-cracks. A Slim-Neck design is adopted, utilizing a dual optimization with GSConv and VoV-GSCSP, significantly improving the balance between real-time performance and accuracy. Based on the results, the optimized model achieves a precision of 98.8% and a recall of 99.2%, with a mean average precision (mAP) of 99.5%—an improvement of 0.2 percentage points over the baseline. The model has a computational load of 4.4 GFLOPs and a compact size of only 3.24 MB, approximately half that of the original model. On embedded devices, it achieves a real-time inference speed of 122 FPS, which is about 2.5, 11, and 1.8 times faster than SSD, Faster R-CNN, and YOLOv10n, respectively. Therefore, the lightweight model based on the improved YOLOv10 not only enhances detection accuracy but also significantly reduces computational cost and model size, enabling efficient real-time cup rupture detection in industrial production environments on embedded platforms. Full article

In this paper, the influence of the novel design of a ladle shroud (LS) on the liquid steel flow structure inside the working volume of a two-strand slab tundish was assessed, determining the best solutions for LS use to achieve the optimal level of active flow zones and protect the tundish lining. A 0.33 scale water model was used for physical experiments. Numerical simulations were carried out in the Ansys-Fluent 12.1 software for a 1:1 scale tundish. The effect of the influence of LS type, LS immersion depth, LS side ports position, LS misalignment and casting speed was examined. Finally, the use of the “umbrella” ladle shroud allows stable hydrodynamics to be maintained even with shroud misalignment. Moreover, the “umbrella” ladle shroud effectively decreases the average velocity of liquid steel inside the tundish and significantly decreases shear stresses and dynamic pressure at the tundish lining in the tundish pouring area. Full article

This study investigated the degradation of aluminum-based sacrificial anodes caused by sulfate-reducing bacteria (SRB) in marine mud. Through self-discharge tests simulating real cathodic protection conditions, alongside macroscopic observations, electrochemical analysis, and microscopic characterization, we systematically elucidated the corrosion behavior and mechanisms of the anodes with and without SRB. The results showed that the electrochemical capacity of anodes in SRB-inoculated mud was only 1281.28 Ah·kg⁻¹ (efficiency: 44.82%), failing to meet the design requirement of ≥1500 Ah·kg⁻¹. In contrast, in sterile mud, the capacity was 1972.84 Ah·kg⁻¹ (efficiency: 69.01%), which met the standard. SRB promoted the formation of discrete corrosion pits with depths reaching up to 0.43 mm, 3.07 times deeper than those observed under sterile conditions. The local pH within the pits dropped to 3–4, accelerating the selective dissolution of active elements such as Al and Zn. Mechanistic analysis revealed that the sulfides produced by SRB not only disrupt the passive film but also exacerbate the inefficient consumption of the anode through a positive feedback loop involving “acidic corrosion and electron consumption”. This led to a reduction in the protective current density, accompanied by significant fluctuations. This study provides the underlying mechanisms by which SRB degrade the performance of sacrificial anodes and valuable insights for optimizing the design of cathodic protection systems for steel structures in marine mud environments. Full article

The continuous advancement of modern weaponry has intensified the pursuit of next-generation ballistic protection systems that integrate lightweight architectures, superior flexibility, and high energy absorption efficiency. This review provides a technological overview of current trends in the design, processing, and performance optimization of metallic, ceramic, polymeric, and composite materials for ballistic applications. Particular emphasis is placed on the role of advanced surface coatings and nanostructured interfaces as enabling technologies for improved impact resistance and multifunctionality. Conventional materials such as high-strength steels, alumina, silicon carbide, boron carbide, Kevlar^®, and ultra-high-molecular-weight polyethylene (UHMWPE) continue to dominate the field due to their outstanding mechanical properties; however, their intrinsic limitations have prompted a transition toward nanotechnology-assisted solutions. Functional coatings incorporating nanosilica, graphene and graphene oxide, carbon nanotubes (CNTs), and zinc oxide nanowires (ZnO NWs) have demonstrated significant enhancement in interfacial adhesion, inter-yarn friction, and energy dissipation. Moreover, multifunctional coatings such as CNT- and laser-induced graphene (LIG)-based layers integrate sensing capability, electromagnetic interference (EMI) shielding, and thermal stability, supporting the development of smart and adaptive protection platforms. By combining experimental evidence with computational modeling and materials informatics, this review highlights the technological impact of coating-assisted strategies in the evolution of lightweight, high-performance, and multifunctional ballistic armor systems for defense and civil protection. Full article

In this study, with the rapid development of the field of rail vehicles, the laser welding process with high energy and small thermal deformation is selected, which reduces the working hours of post-welding grinding, repainting, and other processes, and ensures the industrial design requirements of the beautiful body after welding. The welding process for the non-penetration laser lap welding of SUS301L stainless-steel plates was optimized to address the problem of welding marks on the outer surface of railway vehicle car bodies. The impact of laser power, welding speed, and defocusing amount on weld penetration and tensile shear load was investigated using the response surface methodology. The results showed that the optimal response model for tensile shear load was the linear model, while the optimal response model for weld penetration was the 2FI model. The defocusing amount had the greatest influence on tensile shear load and weld penetration. When the laser power was 1.44 kW, the welding speed was 15 mm/s, and the defocusing amount was −4 mm, the tensile shear load reached its maximum by prediction. The actual tensile shear load of welded joints using these parameters was 4293 N with an error of merely 0.31% relative to the predicted value. The shear strength of laser-welded joints was measured at 429.3 N/mm, meeting the criteria established by the relevant standards. The tensile fracture shows characteristics of brittle fracture. The surface of the welded joints was bright white and well-formed, while the back side of the lower plate exhibited no signs of melting or welding marks. The microstructure of the weld zone (WZ) exhibited irregular columnar austenite and plate-like ferrite, while the heat-affected zone (HAZ) comprised columnar austenite and elongated bars or networks of δ-ferrite. The small-angle grain in welded joints can reduce grain boundary defects and mitigate stress concentration. After welding, angular deformation occurred, resulting in a residual stress distribution that shows tensile stress near the weld and compressive stress at a distance from the weld. Full article

This study investigates the interlayer properties and sustainability of 3D-printed ultra-high-performance concrete (UHPC) modified with antimony tailings (ATs). The different AT ratios considered were 2.7, 5.4, 8.1, 10.8, and 13.5 wt% additions. The mechanical experiments show the optimal concentration resulting in compressive and flexural strength of 11.2% and 17.2% enhancement at 28 days, respectively. SEM analysis revealed that AT enhances the interlayer strength of 3D-printed UHPC and influences the anisotropic behavior of the matrix around steel fibers. X-CT demonstrated that increasing the AT from the compared group to 13.5% reduced the pore volume from 2.02% to 0.30%. Furthermore, an environmental impact assessment of the 10.8 wt% AT exhibited a 32.5% reduction in key indicators including abiotic depletion (ADP), acidification potential (AP), global warming potential (GWP), and ozone depletion potential (ODP). Consequently, UHPC incorporating AT offers superior environmental sustainability in the practical construction of 3D-printed concrete. This research provides practical guidance in optimizing 3D-printed UHPC engineering, further facilitating the integrated design and manufacturing of multi-layer structures. Full article

This study optimized the punch-assisted demolding technique for the separation of contact lenses, incorporating finite-element analysis to evaluate the effects of punch geometry (punch material: 304L stainless steel) on the stress and strain distributions of polypropylene lens molds. The simulation results revealed that the punch surface featured a flat base with a central arc-shaped groove (groove diameter: 7 mm, depth: 0.75 mm), which exhibited optimal stress dispersion characteristics during the demolding process, effectively reducing mold deformation. Experimental validation over 100 demolding cycles confirmed that the use of the aforementioned punch resulted in the manufactured lens having high central stability and reduced van der Waals forces during demolding, allowing smoother lens release and facilitating improved demolding performance. Comprehensive evaluation based on defect inspection and centering stability indicated that a yield of 82% was achieved with the optimized punch, with this yield being 13% higher than that obtained with a flat punch lacking an arc groove (69%). These results indicate that the optimized punch design not only reduces development costs but also enhances manufacturing yield and throughput, demonstrating strong potential for application in contact lens production. Full article

L-shaped concrete-filled steel tubular (CFST) columns have attracted increasing attention in recent years due to their favorable seismic performance and their ability to reduce column protrusions into interior wall surfaces. Existing studies on L-shaped CFST columns have mainly focused on a specific cross-section form, and the mechanical behavior of L-shaped CFST columns with different limb length ratios and inter-limb angles has not yet been sufficiently investigated. To further examine the axial compressive performance of L-shaped CFST columns, this study designed and tested eight L-shaped CFST columns by considering the cross-section form, limb-length ratio, and inter-limb angle as key parameters. In addition, a simplified formula for predicting the axial load capacity of L-shaped CFST columns was proposed based on the unified theory. The test results indicated that the cross-section form significantly affects both load-carrying capacity and ductility. For the equal-limb specimens, the peak load of the C-type specimen was 8% and 9% higher than that of the A-type and B-type specimens, respectively, whereas the displacement ductility coefficient of the A-type specimen was 48% and 47% higher than that of the B-type and C-type specimens, respectively. Compared with the unequal limb specimens, the equal limb specimens exhibited an increase in peak load of more than 20%; moreover, the displacement ductility coefficients of the A-type and B-type specimens increased by 48% and 61%, respectively. Increasing the inter-limb angle enhanced the peak load but reduced the ductility, and it led to a gradual shift in the failure mode from local buckling of the steel tube to overall bending. The findings of this study contribute to a more comprehensive understanding of the mechanical behavior of L-shaped CFST columns and can provide reference for their design and optimization. Full article

Optimizing end mill geometry is critical for improving performance and reducing costs in the high-volume manufacturing of tools, dies and molds. This study demonstrates a successful optimization framework for solid end mills machining 1.2379 cold-work tool steel, integrating Finite Element Analysis (FEA), Artificial Neural Networks (ANN), and Genetic Algorithms (GA). The optimized tool geometry, derived from four key design parameters, delivered substantial performance gains over an industrial reference (parent) tool. Our ANN-GA model achieved a remarkable predictive accuracy (R = 0.75–0.98) over the RSM model (R = 0.17–0.63) and identified an optimal design that reduced the resultant cutting force by approximately 11% (to 142.8 N) and improved surface roughness by 21% (to 0.1637 µm) compared to experimental baselines. Crucially, the new geometry halved the tool breakage rate from 50% to ~25%. Parameter analysis revealed the width of the land as the most influential geometric factor. This work provides a validated, high-performance tool design and a powerful modeling framework for advancing machining efficiency in tool, mold and die manufacturing. Full article

The joining of dissimilar steels is crucial for designing lightweight, high-performance structures but poses significant challenges due to uneven material properties. This study optimizes the butt-welding process for a dissimilar pair of S355J2 and Strenx 700E steels. Cold Metal Transfer welding was employed, and the effects of surface preparation, linear energy, and joint gap on joint integrity were systematically investigated via tensile testing, digital image correlation, fractography, and microhardness analysis. The results demonstrate that mechanical surface cleaning combined with a low linear energy of 0.334 kJ/mm and a 0.5 mm gap yields optimal performance. This parameter set produced a joint with a tensile strength of 616 MPa, representing a 32% increase compared to uncleaned samples, and promoted uniform plastic deformation across the joint. Microstructural analysis confirmed a narrower heat-affected zone and the absence of significant softening in the high-strength steel. Full article

This study investigates the seismic retrofit of historic single-nave churches through the optimization of roof diaphragms designed to enhance energy dissipation. The proposed strategy introduces a deformable box-type diaphragm above the existing roof, composed of timber panels and steel connectors with a cover of steel stripes, where energy dissipation is concentrated in the connections. The retrofit design is guided by the estimation of Equivalent Damping Ratio (EDR) instead of the usually adopted resistance criterion, considering an energy-based approach to improve global seismic performance while preserving architectural integrity. In this way, the retrofitted configuration of the roof can be considered a damper. Three numerical phases are presented to assess the effectiveness of the equivalent damping-based intervention. In the first one, the seismic response of the initial non-retrofitted configuration is implemented using a 3D linear finite element model subjected to a response spectrum. Subsequently, nonlinear equivalent models subjected to spectrum-compatible accelerograms are implemented, simulating the possible retrofitted configurations of the roofs to detect the optimum damping and finding the corresponding roof diaphragm configuration. In the third one, the response of the detected retrofitted configuration is also evaluated by nonlinear 3D model subjected to accelerograms. The three phases with the relative numerical approaches are here applied to a case study, located in a high seismic hazard area. The results demonstrate that the EDR-based methodology can optimize the retrofitted roof diaphragm configuration; the nave transverse response is improved in comparison with that designed with the traditional approach, considering only the over-strength of the interventions. Comparisons about the approaches based on the EDR and the strength criteria are presented in terms of lateral displacements, in-plane shear acting on the roof diaphragm, and in-plane stresses on the façade. Full article

Platinum coatings produced by magnetron sputtering are highly valued due to their exceptional properties, including excellent electrical conductivity, high catalytic activity, and superior corrosion resistance. The quality of these coatings, however, is strongly dependent on the sputtering parameters. This study performs optimization of platinum thin film deposition on stainless steel substrates by systematically varying magnetron sputtering parameters. Experimental data were obtained under different conditions of discharge current, pressure, and deposition time. The results were analyzed using both classical regression techniques and advanced machine learning approaches to assess the influence of process parameters on deposition rate and coating thickness. Among the tested models, Gaussian Process Regression (GPR) demonstrated the highest accuracy and stability. The findings indicate that deposition time is the dominant factor influencing coating thickness, while discharge current primarily governs the deposition rate. Furthermore, multi-objective optimization and active learning approaches highlighted the potential of combining artificial intelligence methods with experimental design to reduce the number of required trials and improve process efficiency. Full article

In practical applications, steel storage racks include a wide range of beam-to-column connections (BCCs), which have a significant impact on their structural stability, particularly under various loading conditions. This systematic review focuses on the application of the finite element method (FEM) as a complementary tool to evaluate the mechanical behavior of these connections. Key parameters that influence connection performance include the connector’s class and hook configuration, column thickness, beam height and weld position on the connector. Although the Eurocode 3 standard provides design guidelines for connections, experimental testing remains the most reliable method due to the complexity of semi-rigid connections, particularly in the context of pallet racks. Validated FEM analysis emerges as a dependable and cost-effective alternative to experiments, enabling more detailed parametric studies and improving the prediction of structural response. This review focuses on the advantages of FEM integration into design workflows via quantitative synthesis, while also emphasizing the role of contact formulations in modeling accuracy. To establish FEM as an independent predictive tool for the design and optimization of steel storage racks, future research should focus on cohesive zone modeling, ductile damage criteria, advanced contact strategies and additional machine learning (ML) techniques. Full article

As research on new, lightweight energy vehicles continues to develop, the application of high-strength steel sheets with tensile strength greater than 1 GPa and their mechanical clinching technology, which is associated with aluminum alloys, has emerged as a new research focus. However, due to the challenges associated with the cold deformation of high-strength steel, conventional mechanical clinching processes often fail to establish effective joint interlocking, resulting in weak connections. This study proposes a center-punching mechanical clinching process for connecting DP980 high-strength steel to AL5052 aluminum alloy. The mechanical evolution during the forming process was analyzed via finite element simulation. An orthogonal experimental design was employed to optimize key geometric parameters of the punch and die, yielding the optimal configuration for the mold. Mechanical testing of the joint demonstrated average pull-out force and pull-shear forces of 1124 N and 2179 N, respectively, confirming the proposed process’s ability to successfully connect high-strength steel and aluminum alloy. Full article

Improving the energy efficiency of advanced ultra-supercritical (USC) power plants by increasing steam operating temperature up to 700 °C can be achieved, at reduced cost, by using novel engineering design concepts, such as coated steam pipe systems manufactured from high temperature materials commonly used in current operational power plants. The durability of thermal barrier coatings (TBC) in advanced USC coal power systems is critically influenced by thermally grown oxide (TGO) evolution and interfacial stress under thermo-chemo-mechanical coupling. This study investigates a novel dual-pipe coating system comprising an inner P91 steel pipe with dual coatings and external cooling, designed to mitigate thermal mismatch stresses while operating at 700 °C. A finite element framework integrating thermo-chemo-mechanical coupling theory is developed to analyze TGO growth kinetics, oxygen diffusion, and interfacial stress evolution. Results reveal significant thermal gradients across the coating, reducing the inner pipe surface temperature to 560 °C under steady-state conditions. Oxygen diffusion and interfacial curvature drive non-uniform TGO thickening, with peak regions exhibiting 23% greater thickness than troughs after 500 h of oxidation. Stress analysis identifies axial stress dominance at top coat/TGO and TGO/bond coat interfaces, increasing from 570 MPa to 850 MPa due to constrained volumetric changes and incompatible growth strains. The parabolic TGO growth kinetics and stress redistribution mechanisms underscore the critical role of thermo-chemo-mechanical interactions in interfacial degradation. These research findings will facilitate the optimization of coating architectures and the enhancement of structural integrity in high-temperature energy systems. Meanwhile, clarifying the stress evolution within the coating can improve the ability to predict failures in USC coal power technology. Full article