Search Results (1,777)

Magnesium alloys, characterized by high specific strength and low density, have high potential for applications in transportation and aerospace. Nevertheless, ensuring the reliable joining of thin-walled components remains a major technical challenge. This study examines how rotational speed affects the microstructure and mechanical properties of friction stir welded AZ61 magnesium alloy hollow profiles (3 mm thick), with particular focus on the underlying mechanisms. The results show that higher rotational speed during friction stir welding promotes dynamic recrystallization and weakens the basal texture. It also affects microstructural homogeneity, where an optimal rotational speed produces a relatively uniform hybrid microstructure consisting of refined recrystallized and un-recrystallized regions. This balance enhances both texture strengthening and microstructural optimization. The weld joint fabricated at a rotational speed of 1500 rpm showed the best overall mechanical properties, with ultimate tensile strength, yield strength, and elongation reaching peak values of 286.7 MPa, 154.7 MPa, and 9.7%, respectively. At this speed, the average grain size in the weld nugget zone was 4.92 μm, and the volume fraction of second-phase particles was 0.67%. This study establishes a critical process foundation for the reliable joining of thin-walled magnesium alloy structures. The optimized parameters serve as valuable guidelines for engineering applications in lightweight transportation equipment and aerospace manufacturing. Full article

Steel structures that support machines and industrial process installations should ideally be flexible, adaptable, and easily reconfigurable. However, in current practice, new profiles are frequently used and discarded whenever layout modifications are required, leading to considerable material waste, increased costs, and environmental burdens. Such practices conflict with the principles of the circular economy, in which reusability is preferable to recycling. This paper presents a life cycle sustainability assessment (life cycle cost, LCC, and life cycle assessment, LCA) applied to six structural typologies: (a) welded IPE profiles, (b) bolted IPE profiles, (c) welded tubular profiles, (d) bolted tubular profiles, (e) clamped IPE profiles with demountable joints, and (f) flanged tubular profiles with demountable joints. The assessment integrates structural calculations with an updatable database of costs, operation times, and service lives, providing a systematic framework for evaluating both economic and environmental performance in medium-load industrial structures (0.5–9.8 kN/m²). Application to nine representative case studies demonstrated that demountable clamped and flanged joints become economically competitive after three life cycles, and after only two life cycles under high-load conditions (9.8 kN/m²). The findings indicate relative cost savings of up to 75% in optimized configurations and carbon-footprint reductions of approximately 50% after three cycles. These results provide quantitative evidence of the long-term advantages of demountable and reconfigurable steel structures. Their capacity for repeated reuse without loss of performance supports sustainable design strategies, reduces environmental impacts, and advances circular economy principles, making them an attractive option for modern industrial facilities subject to frequent modifications. Full article

Structural applications that use High-Strength Low-Alloy (HSLA) steels require detailed microstructural analysis to manufacture welded components that combine strength and weldability. The balance of these properties depends on both the chemical composition and the welding parameters. Moreover, in multi-pass welds, thermal cycling results in a complex Heat-Affected Zone (HAZ), characterized by sub-regions with a multitude of microstructural constituents, including brittle phases. This study investigates the influence of Vanadium addition on the microstructure and performance of the HAZ. Multi-pass welded joints were manufactured on 15 mm thick S355 steels with different Vanadium contents using a robotic GMAW process. A steel variant containing both Vanadium and Niobium was also considered, and the results were compared to those of standard S355 steel. Moving through the different sub-regions of the welded joints, the results show a heterogeneous microstructure characterized by ferrite, bainite and martensite/austenite (M/A) islands. The presence of Vanadium reduces carbon solubility during the phase transformations involved in the welding process. This results in the formation of very fine (average size 11 ± 4 nm) and dispersed precipitates, as well as a lower percentage of the brittle M/A phase, in the variant with a high Vanadium content (0.1 wt.%), compared to the standard S355 steel. Despite the presence of the brittle phase, the micro-alloyed variants exhibit strengthening without loss of ductility. The combined presence of both hard and soft phases in the HAZ provides stress-damping behavior, which, together with the very fine precipitates, promises improved resistance to crack propagation under different loading conditions. Full article

A novel closed loop visual positioning system, termed YOLO–LaserGalvo (YLGS), is proposed for precise localization of welding torch tips in industrial welding automation. The proposed system integrates a monocular camera, an infrared laser distance sensor with a galvanometer scanner, and a customized deep learning detector based on an improved YOLOv11 model. In operation, the vision subsystem first detects the approximate image location of the torch tip using the YOLOv11-based model. Guided by this detection, the galvanometer steers the IR laser beam to that point and measures the distance to the torch tip. The distance feedback is then fused with the vision coordinates to compute the precise 3D position of the torch tip in real-time. Under complex illumination, the proposed YLGS system exhibits superior robustness compared with color-marker and ArUco baselines. Experimental evaluation shows that the system outperforms traditional color-marker and ArUco-based methods in terms of accuracy, robustness, and processing speed. This marker-free method provides high-precision torch positioning without requiring structured lighting or artificial markers. Its pedagogical implications in engineering education are also discussed. Potential future work includes extending the method to full 6-DOF pose estimation and integrating additional sensors for enhanced performance. Full article

Fatigue fracture is the predominant failure mode in welded joints, where complex stress distributions and stress gradient effects at critical joint regions present major challenges for fatigue design. In civil engineering, the diversity of welded joint configurations, large structural spans, and complex loading conditions make it essential to investigate the influence of geometrical size effects on fatigue performance to ensure structural safety. This study focuses on welded T-joints and examines how variations in web plate thickness, weld toe size, and welding angle affect their fatigue behavior through experimental testing. The results show that fatigue life curves fitted using the Mises stress amplitude exhibit higher accuracy than those based on the normal stress amplitude used in current design codes. Pearson correlation analysis indicates that the influences of the geometrical parameters on fatigue life are mutually independent. Furthermore, analysis of the coefficient of variation reveals that welding angle has the greatest effect on fatigue life, whereas weld toe size exerts the least influence. Full article

Short fibre-reinforced polymers (SFRPs) are increasingly used in structural applications where mechanical integrity under complex loading is critical. However, conventional modelling approaches often fail to accurately predict mechanical behaviour in weldline regions formed during injection moulding, where microstructural anomalies and pre-existing damage significantly degrade performance. This study addresses these limitations by extending a hybrid micro–macromechanical constitutive framework to incorporate localised initial damage at weldlines. Calibration and validation of the model were conducted using directional tensile tests on dumbbell-shaped polyamide 66 specimens reinforced with 25 wt% glass fibres, featuring controlled weldline geometry. Digital image correlation (DIC) was employed to capture strain fields, while injection moulding simulations provided fibre orientation distributions and weldline positioning. Results demonstrate that incorporating initial damage and its independent evolution for the cold weld region significantly improves prediction accuracy in weldline zones without compromising model efficiency. The proposed approach can be integrated seamlessly with existing finite element framework and offers a robust solution for simulating SFRP components with weldlines, enhancing reliability in safety-critical applications. Full article

This study investigates the fatigue performance of 3D-printed metal shafts fabricated via Wire Arc Additive Manufacturing (WAAM) with stacked steel ring substrates under rotating bending (ISO 1143:2021). A Taguchi L25 orthogonal array was used to analyze five process parameters: ring diameter, current intensity, torch speed, ring thickness, and contact tip to workpiece distance (CTWD). Analysis of Variance (ANOVA) identified ring diameter as the dominant factor, significantly enhancing fatigue life at 14.0 mm by reducing stress concentrations. Current intensity (125 A) and torch speed (550 mm/min) further improve weld quality and microstructure, while ring thickness (1.0 mm) and CTWD (1.5 mm) have minor effects. A linear regression model (R² = 0.9603) accurately predicts fatigue life, with optimal settings yielding 299,730 cycles. The stacked-ring configuration enables intricate structures like cooling channels, ideal for aerospace and automotive applications. The 3.5% unexplained variance suggests parameter interactions, warranting further investigation into shielding gas effects and multiaxial loading to broaden material and loading applicability. Full article

The high-strength aluminum alloy 7B04 used in aircraft structures poses challenges in welding. In this study, 7075 aluminum alloy powder is used as an interlayer to strengthen the vacuum diffusion bonding (DB) joint of 7B04 aluminum alloy. Surface treatments with plasma activation before DB can effectively increase the bonding rate and lap shear strength (LSS) of the joint. The effects of DB temperature, pressure, and holding time on the joint LSS were analyzed by developing a quadratic regression model based on the response surface method (RSM). The model’s determination coefficient reached 99.52%, with a relative error of about 5%, making it suitable for 7B04 aluminum alloy DB process parameters optimization and joint performance prediction. Two sets of process parameters (505 °C-5.7 h-4.5 MPa and 515 °C-7.5 h-4.4 MPa) were acquired using the satisfaction function optimization method. Experimental results confirmed that the error between measured and predicted LSS is approximately 5%, and a higher LSS of 174 MPa was achieved at 515 °C-7.5 h-4.4 MPa. Full article

Visual inspection remains a cornerstone of quality control in welded structures, yet manual evaluations are inherently constrained by subjectivity, inconsistency, and limited scalability. This study presents WeldVGG, a deep learning-based visual inspection model designed to automate weld defect classification using radiographic imagery. The proposed model is trained on the RIAWELC dataset, a publicly available collection of X-ray weld images acquired in real manufacturing environments and annotated across four defect conditions: cracking, porosity, lack of penetration, and no defect. RIAWELC offers high-resolution imagery and standardized class labels, making it a valuable benchmark for defect classification under realistic conditions. To improve trust and explainability, Grad-CAM++ is employed to generate class-discriminative saliency maps, enabling visual validation of predictions. The model is rigorously evaluated through stratified cross-validation and benchmarked against traditional machine learning baselines, including SVC, Random Forest, and a state-of-the-art architecture, MobileNetV3. The proposed model achieves high classification accuracy and interpretability, offering a practical and scalable solution for intelligent weld inspection. Furthermore, to prove the model’s ability to generalize, a test on the GDXray was performed, yielding positive results. Additionally, a Wilcoxon signed-rank test was conducted separately to assess statistical significance between model performances. Full article

Creating complex structures using multiple materials in additive manufacturing comes with a unique set of challenges, particularly when it comes to how the materials transition and bond together. This research looks at a new powder binning method for combining metal powders to create multi-material components in a single build, all produced on a standard Laser Powder Bed Fusion EOS M 290 machine. The study focuses on the size and quality of the resulting multi-material interfaces and how different scan strategies used affect the interface strength. The strength of the interface between different material pairings is evaluated for combinations of 316 stainless steel bonded to Inconel 718, Inconel 718 bonded to Inconel 625, and Inconel 625 bonded to 316 stainless steel. The Ultimate Tensile Strength (UTS) and interface region lengths were calculated to be 675 MPa and 1250 µm for 316L–IN718, 1004 MPa and 2500 µm for IN718–IN625, and 687 MPa and 2000 µm for IN625–316L, respectively. The findings show that the laser powder bed fusion material binning method is comparable to traditional methods, such as welding or directed energy deposition. This suggests that the new material binning method offers clear advantages when it comes to enabling complex geometry multi-material components while maintaining the strength and durability of the bonds between different metal materials found in traditional means. Further, optimization of scan strategies in the interface zones could play a significant role in improving the overall performance of these multi-material components, which is particularly important for industries such as aerospace, automotive, and energy production. Full article

This paper presents a comprehensive study on automated defect detection in complex structures using phased array ultrasonic testing data, focusing on both traditional signal processing and advanced deep learning methods. As a non-AI baseline, the well-known signal-to-noise ratio algorithm was improved by introducing automatic depth gate calculation using derivative analysis and eliminated the need for manual parameter tuning. Even though this method demonstrates robust flaw indication, it faces difficulties for automatic defect detection in highly noisy data or in cases with large pore zones. Considering this, multiple DL architectures—including fully connected networks, convolutional neural networks, and a novel Convolutional Attention Temporal Transformer for Sequences—are developed and trained on diverse datasets comprising simulated CIVA data and real-world data files from welded and composite specimens. Experimental results show that while the FCN architecture is limited in its ability to model dependencies, the CNN achieves a strong performance with a test accuracy of 94.9%, effectively capturing local features from PAUT signals. The CATT-S model, which integrates a convolutional feature extractor with a self-attention mechanism, consistently outperforms the other baselines by effectively modeling both fine-grained signal morphology and long-range inter-beam dependencies. Achieving a remarkable accuracy of 99.4% and a strong F1-score of 0.905 on experimental data, this integrated approach demonstrates significant practical potential for improving the reliability and efficiency of NDT in complex, heterogeneous materials. Full article

Reducing the carbon footprint of the construction sector is a growing priority. This study explores the potential of using submerged arc welding (SAW) slag as a precursor in the development of low-carbon geopolymeric materials for 3D printing. The influence of potassium hydroxide (KOH) molarity, partial replacement of ground granulated blast furnace slag (GGBFS) with SAW slag, and water-to-binder (w/b) ratio was evaluated in terms of fresh and hardened properties. Increasing KOH molarity delayed setting times, with the longest delays at 10 M and 12 M. The highest compressive strength (48.5 MPa at 28 days) was achieved at 8 M; higher molarities led to strength losses due to excessive precursor dissolution and increased porosity. GGBFS replacement increased setting times due to its higher Al₂O₃ and MgO content, which slowed geopolymerization. The optimized formulation, containing 20% SAW slag and activated with 8 M KOH at a w/b ratio of 0.29, exhibited good workability, extrudability, and shape retention. This mixture also performed best in 3D printing trials, strong layer adhesion and no segregation, although minor edge irregularities were observed. These results suggest that SAW slag is a promising sustainable material showing for 3D-printed geopolymers, with further optimization of printing parameters needed to enhance surface quality. Full article

This study systematically investigates the effects of welding current on the macro-morphology, microstructure, mechanical properties, and corrosion resistance of Cu-Mn-Al alloy coatings deposited on 27SiMn steel substrates using Cold Metal Transfer (CMT) technology. The 27SiMn steel is widely applied in coal mining, geology, and engineering equipment due to its high strength and toughness, but its poor corrosion and wear resistance significantly limits service life. To address this issue, a Cu-Mn-Al alloy (high-manganese aluminum bronze) was selected as a cladding material because of its superior combination of mechanical strength, toughness, and excellent corrosion resistance in saline and marine environments. Compared with conventional cladding processes, CMT technology enables low-heat-input deposition, reduces dilution from the substrate, and promotes defect-free coating formation. To the best of our knowledge, this is the first report on the fabrication of Cu-Mn-Al coatings on 27SiMn steel using CMT, aiming to optimize process parameters and establish the relationship between welding current, phase evolution, and coating performance. The experimental results demonstrate that the cladding layer width increases progressively with welding current, whereas the layer height remains relatively stable at approximately 3 mm. At welding currents of 120 A and 150 A, the cladding layer primarily consists of α-Cu, κII, β-Cu₃Al, and α-Cu + κIII phases. At higher welding currents (180 A and 210 A), the α-Cu + κIII phase disappears, accompanied by the formation of petal-shaped κI phase. The peak shear strength (509.49 MPa) is achieved at 120 A, while the maximum average hardness (253 HV) is obtained at 150 A. The 120 A cladding layer demonstrates optimal corrosion resistance. These findings provide new insights into the application of CMT in fabricating Cu-Mn-Al protective coatings on steel and offer theoretical guidance for extending the service life of 27SiMn steel components in aggressive environments. Full article

The widespread application of WE43 (Mg-4Y-2Nd-1Gd-0.5Zr) alloy castings in aerospace components is hindered by the frequent formation of defects such as cracks, pores, and especially yttria inclusions. These defects necessitate subsequent welding. However, using homologous WE43 filler wires often exacerbates these issues, leading to high crack susceptibility and reintroduction of inclusions. Herein, we propose a novel strategy of tailoring Y content in filler wires to achieve high-quality welded joint of WE43 sand castings. Systematic investigations reveal that reducing Y content to 2 wt.% (WE23) effectively suppresses oxide inclusion formation and significantly enhances the integrity of the joint. The fusion zone microstructure evolves distinctly with varying Y levels: grain size initially increases, peaking at 24 μm with WE43 wire, then decreases with further Y addition. Moreover, eutectic compounds transition from a semi-continuous to a continuous network structure with increasing Y content, deteriorating mechanical performance. Notably, joints welded with WE23 filler exhibit minimal performance loss, with ultimate tensile strength, yield strength, and elongation reaching 93.0%, 98.0%, and 97.4% of the sand-cast base metal, respectively. The underlying strengthening mechanisms and solute-second phase relationships are elucidated, highlighting the efficacy of optimizing Y content in welding wire design. This study provides valuable insights toward defect-free welding of high-performance Mg-RE alloy castings. Full article

Environmental factors significantly affect the fatigue performance of weathering steel welded components in high-altitude, low-temperature corrosive environments. This study conducted multi-factor-coupled constant-amplitude fatigue tests on Q500qENH weathering steel V-groove welded joints and built an equivalent finite element model using test data to explore key influencing factors under multi-condition coupling. Results show that stress level most significantly affects fatigue performance, followed by corrosion duration, then ambient temperature, with influences decreasing in turn. Analyzing 18-day cyclic immersion corrosion morphology predicts 21-year outdoor corrosion in plateau regions, providing a reliable method for long-term exposure prediction. Finite element simulations confirm that low temperatures improve slightly corroded specimens’ fatigue performance by 20%, but damage accumulates before optimal service. This study offers key parameters for safe design of high-altitude weathering steel welded components. Full article