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Search Results (2,157)

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23 pages, 9139 KiB  
Article
Experimental and Numerical Simulation Study on the Mechanical Properties of Integrated Sleeve Mortise and Tenon Steel–Wood Composite Joints
by Zhanguang Wang, Weihan Yang, Zhenyu Gao, Jianhua Shao and Dongmei Li
Buildings 2025, 15(1), 137; https://doi.org/10.3390/buildings15010137 (registering DOI) - 4 Jan 2025
Viewed by 396
Abstract
In view of the application status and technical challenges of steel–wood composite joints in architecture, this paper proposes an innovative connection technology to solve issues such as susceptibility to pry-out at beam–column joints and low load-bearing capacity and to provide various reinforcement methods [...] Read more.
In view of the application status and technical challenges of steel–wood composite joints in architecture, this paper proposes an innovative connection technology to solve issues such as susceptibility to pry-out at beam–column joints and low load-bearing capacity and to provide various reinforcement methods in order to meet the different structural requirements and economic benefits. By designing and manufacturing four groups of beam–column joint specimens with different reinforcement methods, including no reinforcement, structural adhesive and angle steel reinforcement, 4 mm thick steel sleeve reinforcement, and 6 mm thick steel sleeve reinforcement, monotonic loading tests and finite element simulations were carried out, respectively. This research found that unreinforced specimens and structural adhesive angle steel-reinforced joints exhibited obvious mortise and tenon compression deformation and, moreover, tenon pulling phenomena at load values of approximately 2 kN and 2.6 kN, respectively. However, the joint reinforced by a steel sleeve showed a significant improvement in the tenon pulling phenomenon and demonstrated excellent initial stiffness characteristics. The failure mode of the steel sleeve-reinforced joints is primarily characterized by the propagation of cracks at the edges of the steel plate and the tearing of the wood, but the overall structure remains intact. The initial rotational stiffness of the joints reinforced with angle steel and self-tapping screws, the joints reinforced with 4 mm thick steel sleeves, and the joints reinforced with 6 mm thick steel sleeves are 3.96, 6.99, and 13.62 times that of the pure wooden joints, while the ultimate bending moments are 1.97, 7.11, and 7.39 times, respectively. Using finite element software to simulate four groups of joints to observe their stress changes, the areas with high stress in the joints without sleeve reinforcement are mainly located at the upper and lower ends of the tenon, where the compressive stress at the upper edge of the tenon and the tensile stress at the lower flange are both distributed along the grain direction of the beam. The stress on the column sleeve of the joints reinforced with steel sleeves and bolts is relatively low, while the areas with high strain in the beam sleeve are mainly concentrated on the side with the welded stiffeners and its surroundings; the strain around the bolt holes is also quite noticeable. Full article
(This article belongs to the Section Building Structures)
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Figure 1

Figure 1
<p>Nodes J-1 to J-4. (<b>a</b>) J-1, (<b>b</b>) J-2, and (<b>c</b>) J-3 and J-4.</p>
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<p>Design drawings of node J-3 and node J-4. (<b>a</b>) Left view of the steel sleeve of the column, (<b>b</b>) front view of the steel sleeve of the column, (<b>c</b>) left view of the steel sleeve of the beam, and (<b>d</b>) front view of the steel sleeve of the beam. (<b>e</b>) Completed node assembly diagram.</p>
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<p>Three-dimensional view of the loading device.</p>
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<p>Loading regime.</p>
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<p>Layout drawing of measuring points. (<b>a</b>) J-1, (<b>b</b>) J-2, and (<b>c</b>) J-3 and J-4.</p>
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<p>Distribution diagram of displacement meters. (<b>a</b>) D1, D2, and D3; (<b>b</b>) D4 and D5.</p>
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<p>Deformation diagram of node J-1. (<b>a</b>) Overall view before the test, (<b>b</b>) tenon pulling diagram of the lower flange of the beam, and (<b>c</b>) deformation diagram of the specimen after failure.</p>
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<p>Deformation diagram of node J-2. (<b>a</b>) Deformation diagram with an increased degree of tenon pulling and (<b>b</b>) deformation diagram with a tenon pulling amount of 2.5 cm.</p>
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<p>Deformation diagram of node J-3. (<b>a</b>) Deformation diagram of the wooden beam under extrusion and tilting, (<b>b</b>) deformation diagram of the edge fracture of the upper flange, and (<b>c</b>) deformation diagram of the extrusion of the lower flange.</p>
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<p>Deformation diagram of the J-4 joint. (<b>a</b>) Squeezing deformation diagram of the upper flange, (<b>b</b>) fracture diagram of the upper flange of the wooden beam and the steel plate, and (<b>c</b>) deformation diagram of the wooden beam.</p>
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<p>Comparison of the node moment—rotation curves.</p>
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<p>Constitutive model of wood in terms of compression and tension along the grain.</p>
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<p>Constitutive model of wood in terms of compression across the grain.</p>
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<p>Constitutive model of steel.</p>
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<p>Schematic diagram of mesh generation.</p>
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<p>Distributed coupling constraints at the top and end of the column.</p>
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<p>Comparison between finite element analysis results and experimental results. (<b>a</b>) J-1, (<b>b</b>) J-2, (<b>c</b>) J-3, and (<b>d</b>) J-4.</p>
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<p>Stress nephogram of J-1 joint (unit: MPa). (<b>a</b>) Overall failure stress nephogram of the joint, (<b>b</b>) failure stress nephogram of the beam end, and (<b>c</b>) failure stress nephogram of the mortise hole at the column end.</p>
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<p>Stress nephogram of the J-2 joint (unit: MPa). (<b>a</b>) Failure stress nephogram of the column end; (<b>b</b>) failure nephogram of the beam end.</p>
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<p>Stress nephogram of the J-3 joint (unit: MPa). (<b>a</b>) Stress nephogram of overall joint failure, (<b>b</b>) stress nephogram of column end failure, (<b>c</b>) stress nephogram of beam end failure, (<b>d</b>) failure stress nephogram of the sleeve, and (<b>e</b>) failure stress nephogram of the bolt.</p>
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<p>Stress nephogram of the J-4 joint (unit: MPa). (<b>a</b>) Overall failure stress nephogram of the joint, (<b>b</b>) failure stress nephogram of the beam end, and (<b>c</b>) failure stress nephogram of the sleeve.</p>
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25 pages, 14571 KiB  
Article
Friction Stir Spot Welding of Aluminum Alloy to Carbon Fiber-Reinforced Thermosetting Resin Coated by Thermoplastic Resin Using Tools with Different Surface Shapes
by Kazuto Tanaka and Yuki Nagae
J. Compos. Sci. 2025, 9(1), 17; https://doi.org/10.3390/jcs9010017 - 2 Jan 2025
Viewed by 286
Abstract
To achieve carbon neutrality, a reduction in car body weight is essential. Multi-material structures that use lightweight materials such as carbon fiber-reinforced polymers (CFRP) and aluminum (Al) alloy are used to replace parts of steel components. This multi-material method requires specific joining techniques [...] Read more.
To achieve carbon neutrality, a reduction in car body weight is essential. Multi-material structures that use lightweight materials such as carbon fiber-reinforced polymers (CFRP) and aluminum (Al) alloy are used to replace parts of steel components. This multi-material method requires specific joining techniques for bonding dissimilar materials. Friction stir spot welding (FSSW) is one of the joining techniques used for joining dissimilar materials, enabling rapid and strong joints. FSSW for bonding A5052 Al alloy and carbon fiber-reinforced thermosetting resin (CFRTS) utilizing composite laminates with integrally molded thermoplastic resin in the outermost layer has been developed. However, joints using this method cause pyrolysis due to excessive frictional heating at the tool’s bottom, which may affect joint strength and promote corrosion in Al alloy. Therefore, this study developed new tools, a concave-shaped tool without a probe, a concave-shaped tool with a probe and a conventional FSSW tool, and investigated the influence of heat distribution and joint strength using the three new tools. The newly developed concave-shaped tool with a probe suppressed 7% of maximum heat input, decreased the pyrolysis area of epoxy resin by 47%, and increased joint strength by 4%. Finite element analysis also showed the suppression of heat input through the newly developed concave-shaped tool with a probe, achieved by reducing the contact area between the tool and Al alloy. Full article
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Figure 1
<p>CFRP laminates: (<b>a</b>) picture and (<b>b</b>) schematic drawing of composition.</p>
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<p>Curing temperature history of CFRP laminates.</p>
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<p>Surface treatment of Al alloy: (<b>a</b>) schematic drawing of treatment, (<b>b</b>) untreated, (<b>c</b>) electropolished and (<b>d</b>) phosphoric acid anodized.</p>
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<p>FSSW equipment: (<b>a</b>) picture of FSSW equipment (<b>b</b>) schematic drawing of FSSW equipment and (<b>c</b>) schematic drawing of FSSW including fixing and welding specimens.</p>
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<p>Schematic drawing of the tools used in the experiment: (<b>a</b>) Tool0: conventional tool with a probe, (<b>b</b>) Tool1: newly developed concave-shaped tool without a probe and (<b>c</b>) Tool2: newly developed concave-shaped tool with a probe.</p>
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<p>FSSW tool depth condition.</p>
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<p>Schematic drawing of the cross-section area of the joint for SEM observation.</p>
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<p>Schematic view of X-ray observation: (<b>a</b>) main components of the experiment set-up, (<b>b</b>) picture of sample and sample holder and (<b>c</b>) schematic drawing of X-ray observation.</p>
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<p>Schematic drawing of temperature observation during FSSW using thermography.</p>
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<p>Schematic drawing of specimen for tensile shear test.</p>
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<p>Schematic drawing of fracture surface of joint after tensile shear test.</p>
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<p>Schematic drawing of the heat sources for the FEA model: (<b>a</b>) Tool0 and (<b>b</b>) Tool2.</p>
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<p>Temperature dependence of the yield stress for Al alloy.</p>
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<p>Maximum temperature profiles for the three tools.</p>
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<p>Temperature distribution images: (<b>a</b>) Tool0 (<b>b</b>) Tool1 and (<b>c</b>) Tool2 (* indicates the point where the maximum temperature is observed in each image, with its corresponding maximum temperature displays in the bottom-left corner. (<b>i</b>) 0 s represents room temperature. Schematic drawings of the three tools are illustrated in infrared images at (<b>ii</b>) 0.8 s and (<b>iii</b>) 1.5 s).</p>
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<p>Temperature distribution images: (<b>a</b>) Tool0 (<b>b</b>) Tool1 and (<b>c</b>) Tool2 (* indicates the point where the maximum temperature is observed in each image, with its corresponding maximum temperature displays in the bottom-left corner. (<b>i</b>) 0 s represents room temperature. Schematic drawings of the three tools are illustrated in infrared images at (<b>ii</b>) 0.8 s and (<b>iii</b>) 1.5 s).</p>
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<p>Schematic drawing of the tool movement during FSSW: (<b>a</b>) Tool0, (<b>b</b>) Tool1 and (<b>c</b>) Tool2.</p>
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<p>Maximum temperature input during FSSW.</p>
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<p>Molten area of PA12 resin.</p>
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<p>Pyrolysis area of epoxy resin.</p>
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<p>Tensile shear test results: (<b>a</b>) maximum load and welding area results and (<b>b</b>) one example of the welded area on CFRP laminates (Welding area is outlined by red).</p>
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<p>Joint strength for the three tools.</p>
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<p>Fracture surfaces after the tensile shear test: (<b>a</b>) Tool0, (<b>b</b>) Tool1 and (<b>c</b>) Tool2.</p>
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<p>SEM images of the joint cross-section: (<b>a</b>) Tool0, (<b>b</b>) Tool1 and (<b>c</b>) Tool2 (Void areas are outlined by red boxes).</p>
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<p>Three-dimensional image obtained from the X-ray observation: (<b>a</b>) Tool0, (<b>b</b>) Tool1 and (<b>c</b>) Tool2.</p>
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<p>Schematic drawing of the validation line of the FEA model (Red square is temperature observation area using an thermography).</p>
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<p>Comparison between FEA predictions and experiment results: (<b>a</b>) Tool0 and (<b>b</b>) Tool2 (Schematic drawings of tool’s positions are illustrated as black shadow in the graph).</p>
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<p>Temperature distribution on Al alloy surface: (<b>a</b>) Tool0 and (<b>b</b>) Tool2.</p>
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<p>Temperature distribution across the cross-section area between Al alloy and CFRP laminates: (<b>a</b>) Tool0 and (<b>b</b>) Tool2.</p>
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<p>Temperature histories at the interface between Al alloy and CFRP laminates: (<b>a</b>) schematic drawing of the evaluated interface, (<b>b</b>) results of Tool0 and (<b>c</b>) results of Tool2 (Schematic drawings of tool’s positions are illustrated as a black shadow in the graph).</p>
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17 pages, 17836 KiB  
Article
Functionalization of Continuous Fiber-Reinforced Thermoplastic Pultrusion Profiles by Welding
by Calvin Ebert, Marcel Nick Dürr and Christian Bonten
J. Compos. Sci. 2025, 9(1), 6; https://doi.org/10.3390/jcs9010006 - 2 Jan 2025
Viewed by 462
Abstract
Highly filled thermoplastic profiles, produced by in situ pultrusion, offer excellent mechanical properties, but further processing is necessary to expand the range of their applications. Due to the thermoplastic matrix, these materials are particularly well-suited for thermal welding processes. However, the high fiber [...] Read more.
Highly filled thermoplastic profiles, produced by in situ pultrusion, offer excellent mechanical properties, but further processing is necessary to expand the range of their applications. Due to the thermoplastic matrix, these materials are particularly well-suited for thermal welding processes. However, the high fiber content of up to 70 vol.-% presents a significant challenge in welding, an aspect that has not yet been thoroughly investigated in the existing literature. This study focuses on the further processing of the highly-filled profiles by adapting the classic hot tool welding process with the aim of investigating the underlying welding mechanism. An IR line-emitter is used to melt the PA6 matrix of the fiber-reinforced plastic component while the second adherend (unfilled PA6) is melted with a classic heating element. Afterward, the joints are tested for tensile and bending strength. The results of these mechanical tests demonstrate that a strong bond can be formed between the adherends. The joint strength reached values of up to 39 MPa, which corresponds to a welding factor of 0.81. Optical examination of the weld seam reveals a reason for the mechanical performance. At high joining pressures, a form-fit is created between the continuous fibers in the profile and the welded-on unfilled PA6. Full article
(This article belongs to the Topic Advanced Composites Manufacturing and Plastics Processing)
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Figure 1
<p>Welding setup in the heating phase (top left corner) and the joining phase (bottom left corner). The diagrams on the right show the corresponding pressure curves of the two pneumatic cylinders of the sledges.</p>
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<p>Photographs of welded samples. A detailed view of the right-hand sample is shown on the right.</p>
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<p>(<b>a</b>) Test setups for mechanical characterization: testing under tensile load (<b>left</b>) and bending load (<b>right</b>); (<b>b</b>) photographs of the setups in the mechanical laboratory at IKT.</p>
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<p>(<b>a</b>) Tensile strength of the welded samples at <math display="inline"><semantics> <mrow> <mi>P</mi> </mrow> </semantics></math> = 75%; (<b>b</b>) tensile strength of the welded specimens at <math display="inline"><semantics> <mrow> <mi>P</mi> </mrow> </semantics></math> = 85%. Reference unfilled PA6.</p>
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<p>Bending strength of the welded samples plotted against the applied energy on the pultrudate plate.</p>
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<p>(<b>a</b>) Stress-deformation diagram under tensile load; (<b>b</b>) stress-deformation diagram under bending load. Reference unfilled PA6.</p>
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<p>Microscopy images of the weld seam in sectional view. Test samples welded with the parameters of sample No. 9. (<b>a</b>,<b>b</b>) before applying mechanical stress, (<b>c</b>–<b>e</b>) after the tensile test, (<b>f</b>–<b>h</b>) after the bending test.</p>
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<p>Microscopy images of the weld seam in sectional view. Test samples welded with the parameters of samples No. 1, 9, and 10. Heating time <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>t</mi> </mrow> <mrow> <mi>H</mi> </mrow> </msub> <mo>=</mo> </mrow> </semantics></math> 80 s for all samples.</p>
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18 pages, 14828 KiB  
Article
Effect of Beam Power on Intermetallic Compound Formation of Electron Beam-Welded Cu and Al6082-T6 Dissimilar Joints
by Darina Kaisheva, Georgi Kotlarski, Maria Ormanova, Borislav Stoyanov, Vladimir Dunchev, Angel Anchev and Stefan Valkov
Eng 2025, 6(1), 6; https://doi.org/10.3390/eng6010006 - 1 Jan 2025
Viewed by 461
Abstract
In this work, electron beam welds between Cu and Al plates were formed using different power modes, namely 1800 W, 2400 W, and 3000 W. The structure, microhardness, and tensile strength of the raw materials and the weld seams were studied. The low [...] Read more.
In this work, electron beam welds between Cu and Al plates were formed using different power modes, namely 1800 W, 2400 W, and 3000 W. The structure, microhardness, and tensile strength of the raw materials and the weld seams were studied. The low power of the electron beam resulted in the improper penetration and insufficient depth of the weld seam. The low power resulted in high cooling rates, which hindered the nucleation of the copper and aluminum particles. A number of intermetallic compounds (IMCs) were formed, including the metastable Cu9Al4 one. An increase in the power of the electron beam reduced the cooling rate and increased the miscibility between the materials. This resulted in the formation of a mostly homogeneous structure comprising an αAl solid solution and dendritic eutectic CuAl2 intermetallic compounds. A preferred crystallographic orientation of the aluminum phase was detected regarding the sample prepared using a power of 3000 W, forming a specific texture towards the {111} family of crystallographic planes, which is the closest-packed structure. This plane characterizes the highest chemical activity and the highest plasticity. As a result, this sample exhibited the best chemical bonding between the IMCs and the aluminum matrix and the best microhardness and tensile test values. Full article
(This article belongs to the Section Materials Engineering)
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Figure 1
<p>Technological conditions (<b>a</b>) and a schematic of the EBW process of Cu and Al6082-T6 (<b>b</b>).</p>
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<p>X-ray diffraction-analyzed areas.</p>
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<p>Shape and size of the tensile test samples.</p>
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<p>X-ray diffraction patterns of the (<b>a</b>) aluminum plate and (<b>b</b>) the copper plate.</p>
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<p>Pole density of the detected families of crystallographic planes of the (<b>a</b>) untreated Al6082-T6 plate, and (<b>b</b>) the untreated Cu plate.</p>
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<p>Optical images of the copper plate (<b>a</b>) before and (<b>b</b>) after the preheating process, and microhardness indentation (<b>c</b>) before and (<b>d</b>) after the preheating process.</p>
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<p>Optical images of the aluminum plate (<b>a</b>) before and (<b>b</b>) after the preheating process, and microhardness indentation (<b>c</b>) before and (<b>d</b>) after the preheating process.</p>
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<p>Additional microscopic images of the aluminum plate (<b>a</b>) before and (<b>b</b>) after the preheating process.</p>
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<p>X-ray diffraction patterns of the joints formed using a beam power of (<b>a</b>) 1800 W, (<b>b</b>) 2400 W, and (<b>c</b>) 3000 W.</p>
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<p>Pole density of the detected families of crystallographic planes of the aluminum phase corresponding to the obtained samples with a power of the electron beam of (<b>a</b>) 1800 W, (<b>b</b>) 2400 W, and (<b>c</b>) 3000 W.</p>
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<p>SEM images of the sample prepared using a beam power of 1800 W: (<b>a</b>) the border between the Cu plate and the fusion zone (FZ), (<b>b</b>) the fusion zone (FZ), (<b>c</b>) the border between the fusion zone (FZ) and the aluminum alloy plate.</p>
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<p>SEM images of the sample prepared using a beam power of 2400 W: (<b>a</b>) the border between the Cu plate and the fusion zone (FZ), (<b>b</b>) the fusion zone (FZ), (<b>c</b>) the border between the fusion zone (FZ) and the aluminum alloy plate.</p>
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<p>SEM images of the sample prepared using a beam power of 3000 W: (<b>a</b>) the border between the Cu plate and the fusion zone (FZ), (<b>b</b>) the fusion zone (FZ), (<b>c</b>) the border between the fusion zone (FZ) and the aluminum alloy plate.</p>
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<p>SEM images of the formed specimens using a beam power of (<b>a</b>,<b>b</b>) 1800 W, (<b>c</b>,<b>d</b>) 2400 W, and (<b>e</b>,<b>f</b>) 3000 W, and their corresponding chemical compositions.</p>
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<p>Microhardness of the specimen welded using a beam power of (<b>a</b>) 1800 W, (<b>b</b>) 2400 W, and (<b>c</b>) 3000 W.</p>
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28 pages, 4725 KiB  
Review
High Energy Density Welding of Ni-Based Superalloys: An Overview
by Riccardo Donnini, Alessandra Varone, Alessandra Palombi, Saveria Spiller, Paolo Ferro and Giuliano Angella
Metals 2025, 15(1), 30; https://doi.org/10.3390/met15010030 - 1 Jan 2025
Viewed by 277
Abstract
High energy density technologies for welding processes provide opportune solutions to joint metal materials and repair components in several industrial applications. Their high-performance levels are related to the high penetration depth and welding speed achievable. Moreover, the localized thermal input helps in reducing [...] Read more.
High energy density technologies for welding processes provide opportune solutions to joint metal materials and repair components in several industrial applications. Their high-performance levels are related to the high penetration depth and welding speed achievable. Moreover, the localized thermal input helps in reducing distortion and residual stresses in the welds, minimizing the extension of the fusion zone and heat-affected zone. The use of these welding technologies can be decisive in the employment of sophisticated alloys such as Ni-based superalloys, which are notoriously excellent candidates for industrial components subjected to high temperatures and corrosive work conditions. Nonetheless, the peculiar crystallographic and chemical complexity of Ni-based superalloys (whether characterized by polycrystalline, directionally solidified, or single-crystal microstructure) leads to high susceptibility to welding processes and, in general, challenging issues related to the microstructural features of the welded joints. The present review highlights the advantages and drawbacks of high energy density (Laser Beam and Electron Beam) welding techniques applied to Ni-based superalloy. The effects of process parameters on cracking susceptibility have been analyzed to better understand the correlation between them and the microstructure-mechanical properties of the welds. The weldability of three different polycrystalline Ni superalloys, one solid solution-strengthened alloy, Inconel 625, and two precipitation-strengthen alloys, Nimonic 263 and Inconel 718, is reviewed in detail. In addition, a variant of the latter, the AF955 alloy, is also presented for its great potential in terms of weldability. Full article
(This article belongs to the Special Issue Advanced Welding Technology in Metals III)
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Figure 1
<p>Weldability reference diagram for Ni-based superalloys depending on chemical composition (%wt.) Reprinted from ref. [<a href="#B33-metals-15-00030" class="html-bibr">33</a>]. Copyright 2002 Sage Publications.</p>
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<p>Schematic of the weld width with different welding techniques. Reprinted from Ref. [<a href="#B48-metals-15-00030" class="html-bibr">48</a>].</p>
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<p>(<b>a</b>) Sketches of Laser Beam Welding, and (<b>b</b>) Electron Beam Welding processes. Reprinted from Ref. [<a href="#B54-metals-15-00030" class="html-bibr">54</a>].</p>
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<p>Influence of G and R parameters on the possible resulting solidified microstructure. Reprinted from Refs. [<a href="#B52-metals-15-00030" class="html-bibr">52</a>,<a href="#B53-metals-15-00030" class="html-bibr">53</a>].</p>
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<p>Representation of the solidification processes and constituents formation in FZ (equivalent to melted zone MZ) and HAZ of GH909 Ni-based superalloy. Reprinted from Ref. [<a href="#B86-metals-15-00030" class="html-bibr">86</a>].</p>
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<p>Constituents formation in the fusion zone in an IN738 Ni-based superalloy by Nd:YAG pulsed laser welding process. Reprinted from Ref. [<a href="#B31-metals-15-00030" class="html-bibr">31</a>]. HAZ liquation cracks associated with: (<b>a</b>) Ni-Zr intermetallic, (<b>b</b>) γ-γ′ eutectic and Cr–Mo boride (<b>c</b>) Cr rich Carbides and (<b>d</b>) Ta rich MC carbides.</p>
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<p>Details by scanning electron micrograph for the microstructure of the FZ in a Haynes282 welded by CO<sub>2</sub> laser beam. Reprinted from Ref. [<a href="#B89-metals-15-00030" class="html-bibr">89</a>].</p>
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<p>Schematic of solidification cracking formation. Reprinted from Ref. [<a href="#B58-metals-15-00030" class="html-bibr">58</a>].</p>
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<p>Pulsed laser weld on PWA 1480 single crystal Ni-based superalloy showing large regions of epitaxial growth as well as abundant stray grains and cracking along stray-grain high angle boundaries. Reprinted from Ref. [<a href="#B94-metals-15-00030" class="html-bibr">94</a>]. Copyright 2004 The Minerals, Metals &amp; Materials Society.</p>
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<p>Comparison between the cross-sections obtained by GTAW (first row) and EBW (second row) varying the process parameters. Reprinted from Ref. [<a href="#B53-metals-15-00030" class="html-bibr">53</a>].</p>
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<p>Typical microstructure of an EB weld. Reprinted from Ref. [<a href="#B107-metals-15-00030" class="html-bibr">107</a>].</p>
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<p>Schematic of the solidification process of GDT-111 nickel-based superalloy. Reprinted from Ref. [<a href="#B112-metals-15-00030" class="html-bibr">112</a>]. Schematic of GTD-111 superalloy solidification steps, (<b>a</b>) Liquid metal, (<b>b</b>) Formed dendrite structure (γ1), (<b>c</b>) The residual liquid in IDR, (<b>e</b>) Precipitation of MC carbides, (<b>f</b>) Formation of γ-γ′ eutectic, (<b>g</b>) precipitation of ordered γ′ phase.</p>
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14 pages, 11933 KiB  
Article
Effect of the Electrogalvanized and Galvannealed Zn Coatings on the Liquid Metal Embrittlement Susceptibility of High Si and Mn Advanced High-Strength Steel
by Jiayi Zhou, Rongxun Hu, Yu Sun, Ming Lei and Yulai Gao
Coatings 2025, 15(1), 28; https://doi.org/10.3390/coatings15010028 - 1 Jan 2025
Viewed by 365
Abstract
The advanced high-strength steels (AHSSs) with high Si and Mn contents are extensively applied in the automobile manufacturing industry. To improve the corrosion resistance, Zn coatings are generally applied to the steel substrate. However, heat input and tensile stress occur during the resistance [...] Read more.
The advanced high-strength steels (AHSSs) with high Si and Mn contents are extensively applied in the automobile manufacturing industry. To improve the corrosion resistance, Zn coatings are generally applied to the steel substrate. However, heat input and tensile stress occur during the resistance spot welding (RSW) process; thus, Zn-induced liquid metal embrittlement (LME) can be produced due to the existence of liquid Zn. Unfortunately, the LME occurrence can trigger the premature failure of welded joints, seriously affecting the service life of vehicle components. In this study, the LME behaviors in high Si and Mn RSW joints with electrogalvanized (EG) and galvannealed (GA) Zn coatings were comparatively investigated. Based on the Auto/Steel Partnership (A/SP) criterion, 16 groups of different welding currents were designed. In particular, four typical groups of RSW joints were selected to reveal the characteristics of the LME behaviors. Moreover, these four typical groups of EG and GA high Si and Mn RSW joints were, respectively, etched to measure their nugget sizes. The results indicated that with the increase in the welding current, more severe LME cracks tended form. As determined during the comprehensive evaluation of the 16 groups of EG and GA welded joints, higher LME susceptibility occurred in the EG high Si and Mn steels. It was concluded that the formation of Fe-Zn intermetallic compounds (IMCs) and internal oxide layers during the annealing process could account for the lower LME susceptibility in the GA welded joints. Full article
(This article belongs to the Special Issue Advances in Deposition and Characterization of Hard Coatings)
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<p>Schematic of the welding process and four types of liquid metal embrittlement (LME) cracks: (<b>a</b>) resistance spot welding (RSW) process; (<b>b</b>) type A, B, C, and D LME cracks possibly occurring in an RSW joint.</p>
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<p>The engineering stress–strain curves of the as-prepared electrogalvanized (EG) and galvannealed (GA) steel plates.</p>
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<p>Surface morphology of the RSW joints after pickling: (<b>a</b>–<b>d</b>) the electrogalvanized (EG) welded joints at welding currents of 8.0 kA, 10.0 kA, 12.0 kA, and 14.5 kA, respectively, and (<b>e</b>–<b>h</b>) the galvannealed (GA) welded joints at welding currents of 8.0 kA, 10.0 kA, 12.0 kA, and 14.5 kA, respectively.</p>
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<p>Metallographic images of the LME cracks in the cross-section of the EG specimen at a welding current of 8.0 kA: (<b>a</b>) the overall microstructure of the EG welded joint with the chemical etching, (<b>b</b>) microstructure of the type A crack in zone I, indicated by the yellow rectangle in (<b>a</b>), (<b>c</b>) microstructure of the type C crack in zone II, indicated by the yellow rectangle in (<b>a</b>), and (<b>d</b>) microstructure of the type D crack in zone III, indicated by the yellow rectangle in (<b>a</b>).</p>
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<p>Metallographic images of the LME cracks in the cross-section of the EG specimen at a welding current of 10.0 kA: (<b>a</b>) the overall microstructure of the EG welded joint with the chemical etching, (<b>b</b>) microstructure of the type A crack in zone, I indicated by the yellow rectangle in (<b>a</b>), (<b>c</b>) microstructure of the type D crack in zone II, indicated by the yellow rectangle in (<b>a</b>), and (<b>d</b>) microstructure of the type D crack in zone III, indicated by the yellow rectangle in (<b>a</b>).</p>
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<p>Metallographic images of the LME cracks in the cross-section of the EG specimen at a welding current of 12.0 kA: (<b>a</b>) the overall microstructure of the EG welded joint with the chemical etching, (<b>b</b>) microstructure of the type A crack in zone I, indicated by the yellow rectangle in (<b>a</b>), (<b>c</b>) microstructure of the type D crack in zone II, indicated by the yellow rectangle in (<b>a</b>), and (<b>d</b>) microstructure of the type D crack in zone III, indicated by the yellow rectangle in (<b>a</b>).</p>
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<p>Metallographic images of the LME cracks in the cross-section of the EG specimen at a welding current of 14.5 kA: (<b>a</b>) the overall microstructure of the EG welded joint with the chemical etching, (<b>b</b>) microstructure of the type A crack in zone I, indicated by the yellow rectangle in (<b>a</b>), (<b>c</b>) microstructure of the type C crack in zone II, indicated by the yellow rectangle in (<b>a</b>), and (<b>d</b>) microstructure of the type D crack in zone III, indicated by the yellow rectangle in (<b>a</b>).</p>
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<p>Metallographic images of the LME cracks in the cross-section of the GA specimen at a welding current of 8.0 kA: (<b>a</b>) the overall microstructure of the GA welded joint with chemical etching, (<b>b</b>) microstructure of zone I, indicated by the yellow rectangle in (<b>a</b>), and (<b>c</b>) microstructure of zone II, indicated by the yellow rectangle in (<b>a</b>).</p>
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<p>Metallographic images of the LME cracks in the cross-section of the GA specimen at a welding current of 10.0 kA: (<b>a</b>) the overall microstructure of the GA welded joint with the chemical etching, (<b>b</b>) microstructure of the type A crack in zone I, indicated by the yellow rectangle in (<b>a</b>), and (<b>c</b>) microstructure of the type D crack in zone II, indicated by the yellow rectangle in (<b>a</b>).</p>
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<p>Metallographic images of the LME cracks in the cross-section of the GA specimen at a welding current of 12.0 kA: (<b>a</b>) the overall microstructure of the GA welded joint with the chemical etching, (<b>b</b>) microstructure of the type D crack in zone I, indicated by the yellow rectangle in (<b>a</b>), and (<b>c</b>) microstructure of the type D crack in zone II, indicated by the yellow rectangle in (<b>a</b>).</p>
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<p>Metallographic images of the LME cracks in the cross-section of the GA specimen at a welding current of 14.5 kA: (<b>a</b>) the overall microstructure of the GA welded joint with the chemical etching, (<b>b</b>) microstructure of the type A crack in zone I, indicated by the yellow rectangle in (<b>a</b>), and (<b>c</b>) microstructure of the type D crack in zone II, indicated by the yellow rectangle in (<b>a</b>).</p>
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<p>Statistical results of the number of the 4 types of LME cracks for the 16 groups of different welding currents: the number of LME cracks in (<b>a</b>) the EG welded joints and (<b>b</b>) the GA welded joints.</p>
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<p>Statistical results of the maximum length of the 4 types of LME cracks for the 16 groups of different welding currents: the maximum length of the LME cracks in (<b>a</b>) the EG welded joints, and (<b>b</b>) the GA welded joints.</p>
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<p>Metallographic images of the Zn coatings on the EG and GA steel substrates: (<b>a</b>) EG steel, (<b>b</b>) microstructure of EG coating in zone I, indicated by the yellow rectangle in (<b>a</b>), (<b>c</b>) GA steel, and (<b>d</b>) microstructure of GA coating in zone II, indicated by the yellow rectangle in (<b>c</b>).</p>
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17 pages, 10666 KiB  
Article
Prediction of Mechanical Properties and Fracture Behavior of TC17 Linear Friction Welded Joint Based on Finite Element Simulation
by Xuan Xiao, Yue Mao and Li Fu
Materials 2025, 18(1), 128; https://doi.org/10.3390/ma18010128 - 31 Dec 2024
Viewed by 288
Abstract
TC17 titanium alloy is widely used in the aviation industry for dual-performance blades, and linear friction welding (LFW) is a key technology for its manufacturing and repair. However, accurate evaluation of the mechanical properties of TC17−LFW joints and research on their joint fracture [...] Read more.
TC17 titanium alloy is widely used in the aviation industry for dual-performance blades, and linear friction welding (LFW) is a key technology for its manufacturing and repair. However, accurate evaluation of the mechanical properties of TC17−LFW joints and research on their joint fracture behavior are still not clear. Therefore, this paper used the finite element numerical simulation method (FEM) to investigate the mechanical behavior of the TC17−LFW joint with a complex micro−structure during the tensile processing, and predicted its mechanical properties and fracture behavior. The results indicate that the simulated elastic modulus of the joint is 108.5 GPa, the yield strength is 1023.2 MPa, the tensile strength is 1067.5 MPa, and the elongation is 1.98%. The deviations from measured results between simulated results are less than 2%. The stress and strain field studies during the processing show that the material located at the upper and lower edges of the joint in the WZ experiences stress and strain concentration, followed by the extending of the stress and strain concentration zone toward the center of the WZ. And finally, the strain concentration zone covered the entire WZ. The fracture behavior studies show that the material necking occurs in the TMAZ of TC17(α + β) and WZ, while cracks first appear in the WZ. Subsequently, joint cracks propagate along the TC17(α + β) side of the WZ until fracture occurs. There are obvious tearing edges formed by the partial tearing of the WZ structure in the simulated fracture surface, and there are fracture surfaces with different height differences at the center of the joint crack, indicating that the joint has mixed fracture characteristics. Full article
(This article belongs to the Special Issue Advanced Materials Joining and Manufacturing Techniques)
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<p>Diagram flow of the methodology and investigation steps.</p>
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<p>LFW machine setup and joint sample: (<b>a</b>) machine; (<b>b</b>) operation mode; (<b>c</b>) TC17−LFW joint.</p>
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<p>Morphology of TC17−LFW Joint.</p>
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<p>Schematic diagram of tensile specimen.</p>
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<p>Geometric model and mesh of tensile processing in TC17−LFW joint: (<b>a</b>) geometric model; (<b>b</b>) mesh.</p>
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<p>Stress–strain curves of different areas of TC17−LFW joint obtained by inverse material parameters using nanoindentation load displacement curves.</p>
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<p>Material parameter settings of tensile processing model in TC17−LFW joint.</p>
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<p>Boundary conditions of tensile processing model in TC17−LFW joint.</p>
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<p>Boundary conditions of tensile processing model in TC17−LFW joint.</p>
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<p>Stress field during tensile processing of TC17−LFW joint: (<b>a</b>) after yielding; (<b>b</b>) deformed 45%; (<b>c</b>) deformed 60%; (<b>d</b>) Deformed 90%.</p>
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<p>Strain field during tensile processing of TC17−LFW joint: (<b>a</b>) after yielding; (<b>b</b>) deformed 45%; (<b>c</b>) deformed 60%; (<b>d</b>) deformed 90%.</p>
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<p>Stress field during tensile processing of surface XOY of TC17−LFW joint: (<b>a</b>) deformed 45%; (<b>b</b>) deformed 60%; (<b>c</b>) deformed 90%.</p>
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<p>Strain field during tensile processing of surface XOY of TC17−LFW joint: (<b>a</b>) deformed 45%; (<b>b</b>) deformed 60%; (<b>c</b>) deformed 90%.</p>
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<p>DIC full-field strain during tensile processing of TC17−LFW joint: (<b>a</b>) deformed 45%; (<b>b</b>) deformed 60%; (<b>c</b>) deformed 90%.</p>
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<p>Neck shrinkage deformation and fracture behavior during tensile processing of TC17−LFW joint: (<b>a</b>) initiation; (<b>b</b>) neck shrinkage; (<b>c</b>) cracking; (<b>d</b>) fracture.</p>
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<p>Simulation fracture morphology of TC17−LFW joint.</p>
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<p>Fracture morphology of TC17−LFW joint: (<b>a</b>) overall morphology; (<b>b</b>–<b>d</b>) local fracture morphology.</p>
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19 pages, 9493 KiB  
Article
Numerical Simulation and Process Optimization of Laser Welding in 6056 Aluminum Alloy T-Joints
by Jin Peng, Shihua Xie, Tiejun Chen, Xingxing Wang, Xiaokai Yu, Luqiang Yang, Zenglei Ni, Zicheng Ling, Zhipeng Yuan, Jianjun Shi and Zhibin Yang
Crystals 2025, 15(1), 35; https://doi.org/10.3390/cryst15010035 - 30 Dec 2024
Viewed by 304
Abstract
This paper conducts a numerical simulation of the laser welding process for 6056 aluminum alloy stringers and skin T-joints using Simufact Welding. Initially, the accuracy of the finite element simulation is validated, followed by an exploration of the impact of bilateral asynchronous and [...] Read more.
This paper conducts a numerical simulation of the laser welding process for 6056 aluminum alloy stringers and skin T-joints using Simufact Welding. Initially, the accuracy of the finite element simulation is validated, followed by an exploration of the impact of bilateral asynchronous and bilateral synchronous laser welding on molten pool stability. Process parameters, including laser power, welding speed, fixture clamping force, and preheat temperature, are optimized through orthogonal testing. Furthermore, the influence of welding sequences on post-weld equivalent stress and deformation in three stringers’ T-joints is analyzed. The numerical simulation results indicate that the stability of the molten pool is superior in bilateral synchronous welding compared to asynchronous welding. Optimized process parameters were obtained through orthogonal testing, and subsequent experiments demonstrated that the welding sequence of welding both sides first, followed by the middle, produced lower post-weld equivalent stress and reduced overall joint deformation. Full article
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<p>Dimensions of the stringer T-joints. (<b>a</b>) Stringer; (<b>b</b>) base plate; (<b>c</b>) joint.</p>
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<p>Model of three stringer T-joints. (<b>a</b>) Base plate; (<b>b</b>) joint.</p>
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<p>Mesh generation. (<b>a</b>) Stringer; (<b>b</b>) base plate; (<b>c</b>) base plate for the three stringer T-joints.</p>
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<p>Schematic of the laser welding heat source model.</p>
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<p>Comparison between experimental and simulated weld seam cross-section.</p>
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<p>Comparison between experimental and simulated melt pool.</p>
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<p>Melt pool at different time instances during double-sided synchronous laser welding. (<b>a</b>) t = 0.1078 s; (<b>b</b>) t = 0.5286 s; (<b>c</b>) t = 0.8451 s; (<b>d</b>) t = 1.266 s.</p>
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<p>Double-sided synchronous laser welding. (<b>a</b>) Schematic of weld penetration, (<b>b</b>) penetration depth variation curve.</p>
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<p>Double-sided synchronous laser welding. (<b>a</b>) Schematic of weld penetration, (<b>b</b>) penetration depth variation curve.</p>
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<p>Melt pool at different time instances during double-sided asynchronous laser welding. (<b>a</b>) t = 0.1078 s; (<b>b</b>) t = 0.4243 s; (<b>c</b>) t = 1.266 s; (<b>d</b>) t = 1.475 s.</p>
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<p>Penetration depth variation curve of double-sided asynchronous laser welding.</p>
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<p>Trends of various factors with equivalent stress.</p>
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<p>Trends of various factors with deformation.</p>
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<p>Melt pool morphology of orthogonal test schemes. Figures (<b>a</b>–<b>i</b>) correspond to case 1 to case 9.</p>
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<p>Melt pool morphology of orthogonal test schemes. Figures (<b>a</b>–<b>i</b>) correspond to case 1 to case 9.</p>
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<p>Cross-sectional morphology of the molten pool with optimized parameter combinations.</p>
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<p>Variation curves of equivalent force and deformation at welded joints. (<b>a</b>) Equivalent force (<b>b</b>) deformation.</p>
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<p>Simulation model of three stringer T-joints.</p>
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<p>Cloud plot of equivalent stress distribution.</p>
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<p>Cloud plot of total deformation distribution.</p>
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30 pages, 10080 KiB  
Article
Design, Development, and Testing of Machine Learning Models to Estimate Properties of Friction Stir Welded Joints
by Sajjad Arif, Abdul Samad, Muhammed Muaz, Anwar Ulla Khan, Mohammad Ehtisham Khan, Wahid Ali and Farooque Ahmad
Materials 2025, 18(1), 94; https://doi.org/10.3390/ma18010094 - 29 Dec 2024
Viewed by 433
Abstract
This paper estimates friction stir welded joints’ ultimate tensile strength (UTS) and hardness using six supervised machine learning models (viz., linear regression, support vector regression, decision tree regression, random forest regression, K-nearest neighbour, and artificial neural network). Tool traverse speed, tool rotational speed, [...] Read more.
This paper estimates friction stir welded joints’ ultimate tensile strength (UTS) and hardness using six supervised machine learning models (viz., linear regression, support vector regression, decision tree regression, random forest regression, K-nearest neighbour, and artificial neural network). Tool traverse speed, tool rotational speed, pin diameter, shoulder diameter, tool offset, and tool tilt are the six input parameters in the 200 datasets for training and testing the models. Deep learning artificial neural networks (ANN) exhibited the highest accuracy. Therefore, the ANN approach was used successfully to estimate the UTS and the hardness of friction stir welded joints. Additionally, the relationship of pin diameter, tool offset, and tool rotation speed over UTS and hardness were extracted over the collected data points. Furthermore, experimental results, such as UTS and hardness of steel–magnesium-based welded joints and model estimated results, were compared to cross-check model generalization capability. It was noted that ANN estimates and experimental results at desired processing conditions are consistent with sufficiently high accuracy. Full article
(This article belongs to the Special Issue Advances in Welding Process and Materials (2nd Edition))
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<p>Procedure of machine learning modelling.</p>
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<p>Various input and output parameters.</p>
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<p>Different machine learning models used.</p>
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<p>Correlation between the features of a dataset through a heat map.</p>
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<p>Correlation between the features of the dataset through scatterplot matrices.</p>
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<p>Schematic illustrations of the friction stir welding process.</p>
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<p>Surface appearance of dissimilar FSW joints between the AZ61 magnesium alloy and mild steel at a welding speed of (<b>a</b>) 15 mm/min, (<b>b</b>) 30 mm/min, and (<b>c</b>) 50 mm/min.</p>
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<p>OM images of the interfaces of welded joints at a welding speed of (<b>a</b>) 30 mm/min and (<b>b</b>) 50 mm/min.</p>
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<p>SEM image and EDS mappings of the interfaces on the cross-section of the specimen at 1500 rpm, 30 mm/min, offset 0.5 mm. (<b>a</b>) Point EDS at Mg side near-adjacent to interface. (<b>b</b>) EDS mapping of interface.</p>
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<p>Training performance of LR, SVR, KNN, RF, DT, and ANN for hardness.</p>
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<p>Training performance of LR, SVR, KNN, RF, DT, and ANN for UTS.</p>
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<p>Training performance of LR, SVR, KNN, RF, DT, and ANN for UTS.</p>
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<p>MSE and MAE for all six models under consideration.</p>
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<p>Correlation coefficient (R<sup>2</sup>) for all six models under consideration.</p>
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<p>ANN architecture used for prediction of UTS and hardness.</p>
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<p>Variation in MSE with the number of neurons.</p>
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<p>Graph between normalized test and predicted values of (<b>a</b>) hardness and (<b>b</b>) UTS.</p>
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<p>Variation in predicted UTS and hardness with tool rotational speed.</p>
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<p>Variation in predicted UTS and hardness with tool offset.</p>
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<p>Variation in predicted UTS w.r.t. tool pin diameter.</p>
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<p>Comparison between experimental and modelling results for hardness by machine learning.</p>
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<p>Comparison between experimental and modelling results for UTS by machine learning.</p>
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15 pages, 8336 KiB  
Article
A Novel Vibration Suppression Method for Welding Robots Based on Welding Pool Instability Evaluation and Trajectory Optimization
by Mingtian Ma, Hong Lu, Yongquan Zhang, Zidong Wu, He Huang, Xujie Yuan, Xu Feng, Zhi Liu and Zhangjie Li
Technologies 2025, 13(1), 12; https://doi.org/10.3390/technologies13010012 - 28 Dec 2024
Viewed by 396
Abstract
Industrial robots are widely used in welding operations because of their high production efficiency. The structure of the robot and the complex stress conditions during welding operations lead to the vibration of the end of robot, which leads to welding defects. However, current [...] Read more.
Industrial robots are widely used in welding operations because of their high production efficiency. The structure of the robot and the complex stress conditions during welding operations lead to the vibration of the end of robot, which leads to welding defects. However, current vibration suppression techniques for welding robots usually only consider the robotic performance while overlooking their impact on the welding metal forming process. Therefore, based on the influence of robot vibration on welding pool stability during the welding process, a new welding robot vibration suppression method is proposed in this paper, along with the establishment of a welding pool stability assessment model. The proposed vibration suppression algorithm is based on the optimization of the welding trajectory. To enhance the performance of the method, the Particle Swarm Optimization (PSO) algorithm is applied to optimize the joint angular velocity and angular acceleration. Finally, robot welding experiments are designed and conducted. By comparing vibration measurement data and welding quality before and after the vibration suppression, the effectiveness and stability of the proposed method are validated. Full article
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<p>(<b>a</b>) Robot picture; (<b>b</b>) Robot render picture.</p>
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<p>Control flow chart of vibration suppression method based on joint trajectory optimization; Y represents yes, and N represents no.</p>
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<p>Track correction vibration suppression block diagram.</p>
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<p>Welding robot experimental platform.</p>
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<p>Optimized joint trajectory.</p>
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<p>The current information of each joint is acquired for the same path.</p>
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<p>Welding current and voltage using the original trajectory and optimized trajectory; (<b>a</b>) current data; (<b>b</b>) voltage data.</p>
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<p>Welding experiment results. The application of the proposed vibration suppression method results in the enhanced stability of welding formation quality.</p>
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17 pages, 8254 KiB  
Article
Characteristics of Microstructure and Fracture Toughness According to the Groove Shape of Submerged Arc Welding
by Yong-Taek Shin, Chang-Ju Jung, Seong-Han Bae, Gyubaek An, Myungrak Son and Young-Il Park
Metals 2025, 15(1), 10; https://doi.org/10.3390/met15010010 - 27 Dec 2024
Viewed by 292
Abstract
This study investigates the effects of heat input on the microstructure and fracture toughness of SAW (Submerged Arc Welding) joints with K-groove and X-groove weld preparations using S460NL steel. Microstructural analysis focused on acicular ferrite, grain boundary ferrite, and MA (Martensite–Austenite) constituents to [...] Read more.
This study investigates the effects of heat input on the microstructure and fracture toughness of SAW (Submerged Arc Welding) joints with K-groove and X-groove weld preparations using S460NL steel. Microstructural analysis focused on acicular ferrite, grain boundary ferrite, and MA (Martensite–Austenite) constituents to assess their influence on CTOD (Crack Tip Opening Displacement). The results indicate that the K-groove achieved a higher CTOD value of 0.82 mm compared to 0.13 mm for the X-groove, attributed to differences in microstructural composition and cooling rates. The findings highlight the impact of groove geometry and heat input on weld performance. Full article
(This article belongs to the Special Issue Fracture Mechanics of Metals (2nd Edition))
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<p>Details of welding profiles: (<b>a</b>) K-groove; (<b>b</b>) X-groove.</p>
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<p>Measuring position of microstructure: (<b>a</b>) K-groove; (<b>b</b>) X-groove (unit: mm).</p>
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<p>Generation of heat source for measuring cooling rate: (<b>a</b>) K-groove; (<b>b</b>) X-groove.</p>
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<p>Thermal properties according to temperature change for thermal analysis.</p>
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<p>Fracture surface of CTOD specimen: (<b>a</b>) K-groove; (<b>b</b>) X-groove.</p>
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<p>Microstructure of each specimen’s weld metal: (<b>a</b>) K-groove; (<b>b</b>) X-groove.</p>
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<p>M–A constituents of the K-groove specimen at LBZ and weld metal.</p>
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<p>M-A constituents of the X-groove specimen at LBZ and weld metal.</p>
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<p>Comparison of microstructure and CTOD value: (<b>a</b>) AF and CTOD; (<b>b</b>) GBF and CTOD.</p>
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<p>Comparison of the M–A constituent area fraction and CTOD value.</p>
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<p>Change in the fraction of M–A according to the increase in interpass temperature of the K-groove specimen.</p>
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<p>Change in the fraction of M–A according to the increase in interpass temperature of the X-groove specimen.</p>
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<p>Change in the fraction of M–A according to the increase in heat input of the X-groove specimen.</p>
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<p>Comparison of the No. 7 pass of K-groove and No. 5 pass of X-groove: the red line is X-groove, and the blue line is K-groove.</p>
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<p>Comparison of the No. 23 pass of K-groove and No. 28 pass of X-groove: the red line is X-groove, and the blue line is K-groove.</p>
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18 pages, 12799 KiB  
Article
Development of Application Customization Toolkit (ACT) for 3D Thermal Elastic-Plastic Welding Analysis
by Jaeyong Lee, Dong Hee Park, Juhyeon Park and Do Kyun Kim
Materials 2025, 18(1), 57; https://doi.org/10.3390/ma18010057 - 26 Dec 2024
Viewed by 325
Abstract
A 3D thermal elastic-plastic welding analysis ACT (Application Customization Toolkit) was developed in ANSYS, making welding analysis more accessible. The welding analysis was performed using a decoupled method, separated into thermal and structural analyses. To validate the results, comparisons were made with previous [...] Read more.
A 3D thermal elastic-plastic welding analysis ACT (Application Customization Toolkit) was developed in ANSYS, making welding analysis more accessible. The welding analysis was performed using a decoupled method, separated into thermal and structural analyses. To validate the results, comparisons were made with previous studies for two types of welding: T-joint fillet welding and butt welding. Subsequently, the residual stress and deformation obtained from the welding analysis were applied as initial imperfections in a compression analysis to evaluate the ultimate compressive strength with conventional compression analysis. This comparison allowed for a more realistic assessment of the effects of deformation and residual stress distribution on the structural behaviours. Full article
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<p>Options of welding direction and order.</p>
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<p>Details of setting welding direction.</p>
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<p>The geometry of the T-joint fillet welding model.</p>
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<p>Thermal properties of S355J2.</p>
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<p>Mechanical properties of S355J2.</p>
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<p>Mesh of the T-joint fillet welding model.</p>
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<p>Boundary conditions of the T-joint fillet welding model.</p>
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<p>Deflection Comparison of NoE 2 and 4.</p>
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<p>Welding path and geometry of simplified heat source.</p>
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<p>Geometrical features and mesh of the butt-welding model. (<b>a</b>) Geometry of the butt-welding model (<b>b</b>) Mesh of the butt-welding model.</p>
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<p>Thermal properties of st37.</p>
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<p>Mechanical properties of st37.</p>
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<p>Temperature–time history of TC-101 (T-joint fillet welding) [<a href="#B6-materials-18-00057" class="html-bibr">6</a>].</p>
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<p>Temperature–time history of TC-102 (T-joint fillet welding) [<a href="#B6-materials-18-00057" class="html-bibr">6</a>].</p>
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<p>Thermal analysis results of the typical cases: (<b>a</b>) thermal analysis at 31 s, (<b>b</b>) thermal analysis at 431 s.</p>
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<p>Temperature–time history of TC 1, 2, 3 (Butt welding) [<a href="#B25-materials-18-00057" class="html-bibr">25</a>].</p>
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<p>Deformation (<b>a</b>) and residual stress distributions (<b>b</b>) (T-joint fillet welding).</p>
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<p>Deflection curve at middle section (T-joint fillet welding) [<a href="#B6-materials-18-00057" class="html-bibr">6</a>].</p>
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<p>Longitudinal residual stress distribution at middle section (T-joint fillet welding) [<a href="#B6-materials-18-00057" class="html-bibr">6</a>].</p>
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<p>Deflection curve at edge (butt-welding) [<a href="#B25-materials-18-00057" class="html-bibr">25</a>].</p>
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<p>Equivalent stress and six stress components.</p>
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<p>Analysis results for the typical cases: (<b>a</b>) Eigenmode buckling shape, (<b>b</b>) Idealised residual stress.</p>
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<p>Boundary conditions and load conditions of compression analysis.</p>
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<p>Ultimate compressive strength among three analysis cases.</p>
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19 pages, 2965 KiB  
Article
Integrated Prediction of Gas Metal Arc Welding Multi-Layer Welding Heat Cycle, Ferrite Fraction, and Joint Hardness of X80 Pipeline Steel
by Chen Yan, Haonan Li, Die Yang, Yanan Gao, Jun Deng, Zhihang Zhang and Zhibo Dong
Crystals 2025, 15(1), 14; https://doi.org/10.3390/cryst15010014 - 26 Dec 2024
Viewed by 373
Abstract
X80 pipeline steel is widely used in oil and gas pipelines because of its excellent strength, toughness, and corrosion resistance. It is welded via gas metal arc welding (GMAW), risking high cold crack sensitivities. There is a certain relationship between the joint hardness [...] Read more.
X80 pipeline steel is widely used in oil and gas pipelines because of its excellent strength, toughness, and corrosion resistance. It is welded via gas metal arc welding (GMAW), risking high cold crack sensitivities. There is a certain relationship between the joint hardness and cold crack sensitivity of welded joints; thus, predicting the joint hardness is necessary. Considering the inefficiency of welding experiments and the complexity of welding parameters, we designed a set of processes from temperature field analysis to microstructure prediction and finally hardness prediction. Firstly, we calculated the thermal cycle curve during welding through multi-layer welding numerical simulation using the finite element method (FEM). Afterwards, BP neural networks were used to predict the cooling rates in the temperature interval that ferrite nuclears and grows. Introducing the cooling rates to the Leblond function, the ferrite fraction of the joint was given. Based on the predicted ferrite fraction, mapping relationships between joint hardness and the joint ferrite fraction were built using BP neural networks. The results shows that the error during phase fraction prediction is less than 8%, and during joint hardness prediction, it is less than 5%. Full article
(This article belongs to the Special Issue Advanced High-Strength Steel)
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<p>Hardness prediction flow chart of X80 pipeline steel.</p>
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<p>A schematic diagram of the typical structure of a BP neural network.</p>
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<p>Schematic diagram of the weld groove morphology, welding sequence, and measurement points of the welding thermal cycle curve: (<b>a</b>) weld groove morphology, (<b>b</b>) welding sequence, (<b>c</b>) measurement points of the welding thermal cycle curve.</p>
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<p>Phase fraction statistics and hardness testing process.</p>
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<p>Simulated welding temperature field and its proofread: (<b>a</b>) simulated welding temperature field using the finite element method, (<b>b</b>) validation of the computational model based on molten pool morphology, (<b>c</b>) simulated thermal cycle curve using the finite element method, (<b>d</b>) comparison of simulated and measured thermal cycle curves.</p>
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<p>Prediction results of the cooling section of the welding thermal cycle curve: (<b>a</b>) Comparison of neural network prediction results with FEM calculation results, (<b>b</b>) simplified results of the cooling curve in the phase transformation interval.</p>
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<p>Joint microstructure morphologies and their phase fractions in: (<b>a</b>) root welding, (<b>b</b>) hot welding, (<b>c</b>) filling 1, (<b>d</b>) filling 2, (<b>e</b>) filling 3, (<b>f</b>) filling 4, (<b>g</b>) filling 5, (<b>h</b>) cover welding 1, (<b>i</b>) cover welding 2.</p>
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<p>CCT curve measurement results and the relationship between ferrite fraction and cooling rate: (<b>a</b>) CCT curve, (<b>b</b>) relationship between ferrite fraction and <math display="inline"><semantics> <msub> <mi>t</mi> <mrow> <mn>8</mn> <mo>/</mo> <mn>5</mn> </mrow> </msub> </semantics></math>.</p>
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<p>Ferrite fraction prediction results of the joint.</p>
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<p>The relationship between joint hardness and ferrite fraction, the training process MSE curve, and the prediction results of joint hardness: (<b>a</b>) the relationship between joint hardness and ferrite fraction, (<b>b</b>) MSE curve, (<b>c</b>) hardness prediction results.</p>
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20 pages, 8329 KiB  
Article
Selection of Processing Methods and Parameters for Composite Inserts in Window Profiles with Regard to the Strength of Their Welds
by Marek Kozielczyk, Kinga Mencel, Jakub Kowalczyk and Marta Paczkowska
Materials 2025, 18(1), 44; https://doi.org/10.3390/ma18010044 - 26 Dec 2024
Viewed by 327
Abstract
In the study of structural materials, the analysis of fracture and deformation resistance plays an important role, particularly in materials widely used in the construction industry, such as poly(vinyl chloride) (PVC). PVC is a popular material used, among others, in the manufacture of [...] Read more.
In the study of structural materials, the analysis of fracture and deformation resistance plays an important role, particularly in materials widely used in the construction industry, such as poly(vinyl chloride) (PVC). PVC is a popular material used, among others, in the manufacture of window profiles, doors, pipes, and many other structural components. The aim of this research was to define the influence of the degree of milling of the glass-fibre-reinforced composite on the strength of the window frame welds, and in the next step, to propose new welding parameters to obtain sufficient strength properties that allow reducing the cost of the technological welding operation. During the tests, it was found that the average failure load of the composite samples was highest at a milling depth of 1 mm and lowest at 6 mm. Up to a depth of 1 mm, the values of destructive loads show an increasing trend, while above this depth, a decreasing trend. A clear reduction in strength was observed when milling to a depth of 1.5 mm, which is related to material discontinuity and the lack of a visible weld joint caused by milling too deep. The differences in average failure loads between the samples of 0 mm, 0.5 mm, and 1 mm milling are minimal. Full article
(This article belongs to the Special Issue Fusion Bonding/Welding of Metal and Non-Metallic Materials)
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<p>Research plan.</p>
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<p>Cross-section of the tested profiles (<b>a</b>) and view of the composite inserts (<b>b</b>).</p>
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<p>Profile machining; (<b>a</b>)—cutting; (<b>b</b>)—milling.</p>
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<p>A 4-head welder was used in the tests.</p>
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<p>LN2000 corner breaker; (<b>a</b>)—sample view; (<b>b</b>)—diagram; F—pressure force.</p>
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<p>Average failure load values of individual reconnaissance test samples.</p>
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<p>Average values of failure loads for individual reconnaissance test heads.</p>
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<p>Two sample welds of reconnaissance test samples; (<b>a</b>)—for the first head, (<b>b</b>)—for the second head.</p>
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<p>Average failure load values of individual test specimens using milling of the composite to a depth of 6 mm.</p>
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<p>Average failure loads for individual heads using milling of the composite to a depth of 6 mm.</p>
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<p>Two selected welds of test specimens using composite milling to a depth of 6 mm; (<b>a</b>)—for head one, (<b>b</b>)—for head four.</p>
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<p>Average failure load values of individual test specimens using milling of the composite to a depth of 3 mm.</p>
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<p>Average failure loads for individual heads using milling of the composite to a depth of 3 mm.</p>
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<p>Two selected welds of test specimens using composite milling to a depth of 3 mm; (<b>a</b>)—for head one, (<b>b</b>)—for head three.</p>
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<p>Average failure load values of individual test specimens using milling of the composite to a depth of 2 mm.</p>
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<p>Average failure loads for individual heads using milling of the composite to a depth of 2 mm.</p>
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<p>Two selected welds of test specimens using 2 mm deep composite milling; (<b>a</b>)—for head one, (<b>b</b>)—for head four.</p>
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<p>Average failure load values of individual test specimens using milling of the composite to a depth of 1.5 mm.</p>
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<p>Average failure loads for individual heads using milling of the composite to a depth of 1.5 mm.</p>
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<p>Two different selected welds of test specimens using composite milling to a depth of 1.5 mm; (<b>a</b>)—for head one, (<b>b</b>)—for head one.</p>
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<p>Average failure load values of individual test specimens using milling of the composite to a depth of 1 mm.</p>
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<p>Average failure loads for individual heads using milling of the composite to a depth of 1 mm.</p>
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<p>Two selected welds of test specimens using composite milling to a depth of 1 mm; (<b>a</b>)—for head one, (<b>b</b>)—for head two.</p>
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<p>Average failure load values of individual test specimens using milling of the composite to a depth of 0.5 mm.</p>
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<p>Average failure loads for individual heads using milling of the composite to a depth of 0.5 mm.</p>
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<p>Two selected welds of test specimens using milling of the composite at a depth of 0.5 mm; (<b>a</b>)—for head one, (<b>b</b>)—for head three.</p>
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<p>Average values of breaking loads of individual sets of samples with different degrees of composite milling.</p>
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20 pages, 9045 KiB  
Article
Effects of Vibratory Stress Relief on Microstructure and Mechanical Properties of Marine Welded Structures
by Liqiang Gao, Qinan Yao, Yuchen Yang, Dejian Sun, Guanhua Xu, Bangping Gu, Cong Yang and Shuaizhen Li
J. Mar. Sci. Eng. 2025, 13(1), 11; https://doi.org/10.3390/jmse13010011 - 25 Dec 2024
Viewed by 390
Abstract
Dissimilar steel welded structures are commonly used in the marine engineering field. Owing to the scarcity of in-depth investigation into the intricate pattern of residual stress distribution in welding within 316L/Q345 dissimilar steel welded joints and methods for reducing this stress, a platform-based [...] Read more.
Dissimilar steel welded structures are commonly used in the marine engineering field. Owing to the scarcity of in-depth investigation into the intricate pattern of residual stress distribution in welding within 316L/Q345 dissimilar steel welded joints and methods for reducing this stress, a platform-based vibratory stress relief (VSR) experimental system was established to comprehensively study the effects of VSR on the mechanical properties and microstructure of 316L/Q345 welded structures. Scanning electron microscopy (SEM) was used to examine the fracture morphology and explore the intrinsic mechanisms by which VSR enhances the mechanical properties of welded joints. The findings suggest that VSR is capable of significantly homogenizing and diminishing the welding residual stress within the heat-affected area of 316L/Q345 mismatched steel welded specimens. The significant reduction in residual stress after VSR can primarily be attributed to the combination of alternating stress applied by the VSR platform and the welding residual stress, which exceeded the yield limit of the metal materials. Furthermore, the significant reduction in residual stress, refinement of second-phase particles, and changes in fracture mechanisms are the main reasons for the increased strength observed after VSR. This study has significant engineering application value, providing a theoretical basis for the use of VSR treatment to enhance the reliability of the safe operation of marine engineering equipment. Full article
(This article belongs to the Section Ocean Engineering)
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<p>Welding diagram.</p>
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<p>Self-built platform VSR system.</p>
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<p>Seventh-order free mode of vibration platform.</p>
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<p>Dynamic model of VSR.</p>
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<p>Residual stress test system. (<b>a</b>) Hole-drilling equipment. (<b>b</b>) Measurement point distribution.</p>
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<p>Microstructure observation system.</p>
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<p>Hardness testing equipment.</p>
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<p>Tensile test system. (<b>a</b>) Tensile specimen size. (<b>b</b>) Tensile equipment.</p>
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<p>Residual stress in the 316L/Q345 heat-affected zone [<a href="#B37-jmse-13-00011" class="html-bibr">37</a>]. (<b>a</b>) Longitudinal residual stress in the Q345 heat-affected zone. (<b>b</b>) Transverse residual stress in the Q345 heat-affected zone. (<b>c</b>) Longitudinal residual stress in the 316L heat-affected zone. (<b>d</b>) Transverse residual stress in the 316L heat-affected zone. (<b>e</b>) Stress release value in the Q345 heat-affected zone. (<b>f</b>) Stress release value in the 316L heat-affected zone.</p>
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<p>Microstructure of Q345/316L dissimilar steel parts. (<b>a</b>) Q345 heat-affected zone. (<b>b</b>) 316L heat-affected zone. (<b>c</b>) Q345 base metal region. (<b>d</b>) 316L base metal region. (<b>e</b>) Q345 heat-affected zone after VSR. (<b>f</b>) 316L heat-affected zone after VSR. (<b>g</b>) Q345 base metal region after VSR. (<b>h</b>) 316L base metal region after VSR.</p>
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<p>Microhardness data. (<b>a</b>) Average microhardness values. (<b>b</b>) Microhardness distribution.</p>
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<p>Stress–strain curves of welded joints of Q345/316L dissimilar steel.</p>
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<p>Macroscopic morphology of fracture. (<b>a</b>) Untreated. (<b>b</b>) After VSR.</p>
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<p>Microscopic morphology of fracture. (<b>a</b>) Fiber region. (<b>b</b>) Radiation region. (<b>c</b>) Shear lip. (<b>d</b>) Fiber region after VSR. (<b>e</b>) Radiation region after VSR. (<b>f</b>) Shear lip after VSR.</p>
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