Search Results (1,182)

Large flange shafts are the core load-bearing and connecting components of high-end equipment, and their welding multi-physical fields directly affect the quality and service safety of the components. Traditional experiments and finite element methods suffer from long cycles and low efficiency, which can hardly meet the demand for rapid prediction. Aiming at the fast and accurate prediction of welding temperature, deformation and residual stress, this study combines thermal–mechanical coupled finite element simulation with machine learning to construct and compare a variety of prediction models. A dataset is built based on simulation data from 100 groups of process parameters. Overfitting is reduced through strategies including early stopping and dropout, and models such as MLP, RF, RBF-SVR, TabNet, XGBoost, and FT-Transformer are established and verified through 10-fold cross-validation. The results show that the MLP model performs best in the prediction of temperature, deformation and residual stress, and is in good agreement with the simulation values. The prediction errors of the peak temperature of the weld and base metal are below 5%, and the errors of deformation and residual stress are controlled within 10%. The average error of peak residual stress is about 6 MPa, and the deviation of most samples is less than 5 MPa. The RF model ranks second in accuracy, with an average error of about 6.5 MPa for peak residual stress, showing a satisfactory interpretability and engineering applicability. RBF-SVR and TabNet can meet basic prediction requirements. Under the small-sample condition in this work, XGBoost and FT-Transformer present relatively large errors and a weak generalization ability, making it difficult to achieve high-precision prediction. The MLP model established in this paper can effectively reproduce the evolution of welding multi-physical fields and supports the rapid prediction and process optimization of large flange shaft welding. The generalization ability and practical performance of the model can be further improved by expanding the dataset and experimental verification in the future. Full article

Accurately predicting the ultimate tensile strain of full-scale pipelines with unequal wall thickness containing cracked girth weld joints is essential for strain-based design, structural integrity assessment, and safe operation. However, many existing limit state prediction methods for full-scale girth welds are developed for equal wall thickness configurations or idealized geometries, and their applicability to unequal wall thickness conditions remains limited. To address this gap, this paper develops a limit state prediction model for the ultimate tensile strain of cracked girth welded joints in full-scale pipelines with unequal wall thickness. The model is established using a numerical database generated from finite element simulations, incorporating realistic pipe geometry, material properties, wall thickness mismatch, and representative crack defect characteristics. By considering the stress and strain concentration effects induced by geometric non-uniformity in the weld region, the proposed model provides a practical and efficient tool for limit state evaluation. During pipeline construction, it supports the formulation of quantitative requirements for key design and fabrication parameters, such as the strength matching level. During stable operation, it enables reliable prediction of the strain capacity of existing girth welds in pipelines with unequal wall thickness, thereby supporting integrity management and decision making for safe service. Full article

In the coarse grain heat-affected zone (CGHAZ) of welded pipe steel joints, hydrogen damage is a key factor limiting the high-pressure hydrogen transportation performance of the pipeline. This study employed multi-dimensional characterization methods (including microstructure, mechanical properties, and hydrogen distribution) to investigate the influence of welding heat input on the hydrogen embrittlement (HE) sensitivity of X60 pipeline steel in the CGHAZ. The results showed that as the heat input increased, the grains in the CGHAZ became coarser, and the microstructure changed from bainitic ferrite (BF) to granular bainite (GB) and polygonal ferrite (PF). Among them, the BF + GB composite structure had the best resistance to HE (HE sensitivity was 29.8%). At low heat input, the reversible hydrogen distribution occurred at the interfaces between the grain boundaries and the BF blocks, while at high heat input, it would accumulate around the martensite/austenite (M/A) constituents. For the 16 kJ/cm heat input experimental steel, the increase in Σ3 grain boundary density accelerated hydrogen diffusion and reduced its enrichment, thereby resulting in the lowest HE sensitivity. Full article

The formation of hard/brittle layers (HBLs) forming in proximity to the transition-layer interface during the welding process of stainless steel clad plates constitutes a pivotal element in determining the limitations on joint homogeneity and toughness. In order to elucidate their formation mechanisms and develop viable suppression routes, S31603/Q420qENH clad plates were utilised to fabricate five butt joints. This was achieved by varying the carbon content of the welding consumables and the heat input in the transition layer. A programme was conducted that combined microstructural and microhardness characterisation, mechanical testing, and numerical welding simulations. The findings indicate that base-layer consumables with comparatively elevated carbon content (w(C) ≥ 0.06%) expeditiously engender a constricted, localised hardened band in close proximity to the transition-layer interface. This is characterised by the predominance of martensite and Cr-rich compounds of the M_xCr_y type, which function as the principal genesis of bending cracks. Conversely, the utilisation of low-carbon welding consumables has been shown to markedly reduce interfacial carbon activity and C-Cr segregation, thereby suppressing the precipitation of M_xCr_y phases and effectively decreasing the overall thickness of the HBLs. Further numerical analysis shows that moderately increasing the transition-layer heat input lowers the T_8/5 cooling rate and shifts the cooling path away from the martensite region. This transforms the interfacial microstructure from a localised hardened band into a more uniform, graded structure. These findings provide an engineerable process-control strategy for enhancing both microstructural uniformity and toughness in stainless steel clad joints. Full article

Reliable ultrasonic inspection of welded structures requires a quantitative understanding of how defect morphology and depth influence detectability. In this study, a simulation-based signal-response Probability of Detection (POD) framework is developed to investigate ultrasonic wave interaction with representative planar and volumetric weld defects. Two-dimensional finite-element shear-wave simulations were conducted to model wave propagation and scattering from planar flaws (toe and root cracks) and volumetric flaws (porosity) across defined inspection depth zones. Peak terminal voltage was used as a continuous response metric for regression-based POD analysis. The results demonstrate that defect morphology dominates the influence on ultrasonic detectability. Planar defects produced systematically higher signal responses than volumetric defects of comparable size, resulting in lower characteristic detection limits. The estimated a₉₀ value for planar flaws was 2.96 mm, compared to 5.64 mm for volumetric flaws under identical threshold conditions. Depth-dependent analyses further revealed morphology-specific behavior: planar defects exhibited consistently high detection probabilities across depth zones (POD > 0.98), whereas volumetric defects showed a reduction in detectability with depth, with POD decreasing from approximately 0.32 in shallow zones to 0.16 in deeper regions. The resulting POD trends are interpreted as comparative, trend-based indicators of morphology and depth-dependent ultrasonic detectability under idealized inspection conditions. These findings quantitatively demonstrate how ultrasonic detectability is governed by wave-defect interaction mechanisms associated with defect morphology and inspection depth. Full article

Ultrasonic Impact Treatment (UIT), a prevalent surface-strengthening technology for welded structures, combines mechanical shock and ultrasonic vibration to induce plastic deformation and beneficial residual compressive stress at weld toes, effectively enhancing welded joint fatigue performance. This study adopts a full-process numerical simulation approach, integrating the finite element software ABAQUS and FE-SAFE fatigue-life prediction platform to investigate QSTE700TM high-strength automotive steel butt joints. Considering welding-induced initial residual stress, ABAQUS simulates the welding and subsequent UIT processes; explicit dynamic analysis reveals residual stress evolution, with pre- and post-UIT stress-distribution comparisons. The post-UIT residual stress field is input into a static tensile model to obtain load-stress distributions, which are then imported into FE-SAFE with S-N curves for fatigue-life prediction. Simulation results align well with experimental data: UIT improves the fatigue limit of welded specimens by 31.3% and unwelded ones by 42.9%. Additionally, optical and scanning electron microscopes observe fatigue fracture morphologies to further clarify UIT’s fatigue-enhancement mechanism. Full article

Laser-based manufacturing processes—including marking, hardening, cutting, and welding—demand the precise selection of processing parameters, as the resulting surface state is critically dependent on the delivered power density and beam–material interaction time. This study presents a unified predictive framework for estimating the critical surface power density thresholds for melting q_scm and evaporation q_scv as functions of scanning speed v for the following four technologically important metallic materials: titanium, C26000 brass, SS304 stainless steel, and 42CrMo4 alloy steel. The principal novelty of this work is twofold. First, it provides the first directly comparative analysis of these four materials under identical, standardized laser conditions (λ = 1064 nm, d = 40 μm, constant absorptivity A = 0.4), eliminating the confounding effects of variable beam geometries and optical assumptions that hinder cross-study comparisons. Second, it translates fundamental thermophysical principles into a practical engineering tool, such as a validated spreadsheet calculator that outputs material-specific threshold curves in real time, enabling rapid, physics-based parameter estimation without recourse to complex numerical simulations. The computed threshold curves exhibit a consistent non-linear increase with scanning speed for all materials, governed by the inverse relationship between interaction time and required power density. The following clear material hierarchy emerges: C26000 brass exhibits the highest thresholds (e.g., q_scm = 0.94 × 10¹⁰ W/m², q_scv = 10.74 × 10¹⁰ W/m² at v = 100 mm/s) due to its high thermal conductivity, while titanium shows the lowest (q_scm = 0.19 × 10¹⁰ W/m², q_scv = 0.48 × 10¹⁰ W/m² at v = 100 mm/s) as a consequence of strong heat confinement. SS304 and 42CrMo4 occupy intermediate positions, with 42CrMo4 demonstrating notably higher evaporation resistance than SS304 despite similar melting thresholds. The resulting dual-threshold framework delineates three distinct process regimes—sub-melting heating, melting-dominant processing, and evaporation—providing a quantitative basis for parameter selection in applications ranging from surface hardening to micromachining. By bridging the gap between theoretical material science and applied manufacturing, this work offers a robust, first-order reference for process design and establishes a methodological template for future comparative studies of laser–material interactions. Full article

Large-diameter longitudinal submerged arc welded (LSAW) pipes represent a critical component of long-distance oil and gas transmission pipelines. To enhance the forming efficiency of the JCO (J-shape to C-shape to O-shape) forming process for LSAW pipes, and to reduce residual straight segment in order to minimize the ovality of the formed pipes, an asymmetric four-point air bending (AFB) process was proposed. In this process, one end of the sheet contacts the dies with a straight segment, while the other end contacts a circular arc segment. The distribution of bending moments and mechanical model under different bending stages were analyzed, and analytical formulas for the main forming indexes before and after springback were derived. Experimental and finite element simulation verification were conducted for the AFB process. The results indicated that the error between the experimental and simulation results and the theoretical results was small, and the variation trends were consistent. Furthermore, the ellipticity of the pipes formed by the AFB process was less than 0.66%, which is obviously lower than that of the pipe formed by the symmetric four-point air bending (SFB) process. The forming quality and production efficiency of the pipe is improved, thereby proving the feasibility and reliability of the AFB process and promoting the development of LSAW pipe JCO forming processes. Full article

Electrical Discharge Machining (EDM) enables precision post-weld finishing of AISI 304 stainless steel, but stochastic spark overlaps make the fatigue-critical maximum peak-to-valley height (R_max) difficult to predict. This study develops a validated physics-based framework quantifying how crater overlap governs R_max evolution. Experiments on unwelded AISI 304 cylinders—proxying weld metal while excluding heat-affected zone (HAZ) effects—used Central Composite Design (20 trials, 900–9380 μJ discharge energies). Profilometry and scanning electron microscopy (SEM) correlated the crater size, overlap intensity, micro-cracking, and R_max escalation from 18 to 85 μm. Primary and secondary crater formation under minimum and maximum overlap configurations were simulated using a 2D axisymmetric finite element model with Gaussian heat flux and temperature-dependent thermophysical properties. The predictive metric R_max,num = (d_initial + d_secondary)/2 achieved 11–19% average error against the experimental R_max,exp, with complementary valley depth (R_v) validation at 13% error. The Specimen 7 outlier (~50% error) reveals the limitations of deterministic modelling under stochastic debris accumulation and plasma instability at intermediate energies. Crater overlap generates secondary dimples, sharp inter-crater peaks, and rim micro-crack networks, driving the 4.7-fold R_max increase—approaching International Institute of Welding (IIW) fatigue thresholds (<25 μm for high-cycle categories). The framework explicitly links the discharge energy, plasma channel radius (R_pc), and overlap geometry to surface topography, enabling process optimization (I·t_on < 60 A·s maintains R_max < 25 μm). Mesh independence (<2.5% convergence) and six centre-point replicates (CV = 4.2%) confirm robustness. This validated upper-bound R_max predictor supports the digital co-optimization of welding and EDM parameters for aerospace/energy applications, with planned extensions to stochastic 3D models incorporating adaptive remeshing and real weld topographies. Full article

Existing macroscopic finite element models for electron beam welding (EBW) typically assume isotropic material behavior, often failing to accurately predict residual stresses induced by strong crystallographic textures. To address this limitation, this study established a sequential dual-scale coupled numerical model bridging micro-texture to macro-mechanics by combining the crystal plasticity finite element method (CPFEM) with thermal-elastic-plastic theory. Representative volume elements (RVEs) incorporating α and β dual-phase characteristics were constructed based on electron backscatter diffraction (EBSD) data from the TA15 weld cross-section. Through simulated tensile and shear calculations on the RVEs, homogenized orthotropic stiffness matrices and Hill yield constitutive parameters were derived and mapped onto the macroscopic model. Simulation results indicate that the proposed model maintains the prediction error for molten pool morphology within 16.3%, while effectively correcting the stress overestimation inherent in isotropic models. Specifically, it adjusts the peak longitudinal residual stress at the weld center from 800 MPa to approximately 350 MPa, significantly reducing the anomalous “M-shaped” stress distribution. By successfully capturing shear stress components, this work provides a high-fidelity computational approach for predicting complex stress states in welded joints, offering critical insights for structural integrity assessment. Full article

Efficient on-site connection of power cable conductors is critical for ensuring the safe operation of the power grid. Traditional thermite welding methods pose significant safety risks, including open flames and fumes. Meanwhile, induction heating, when applied to cable conductors, faces challenges of severe magnetic field dispersion, low heating efficiency, and a high risk of damaging adjacent insulation layers. This paper proposes a novel magnetic flux control system based on gradient permeability ceramics to address these issues. The core of this system is the synergistic utilization of a gradient permeability composite ceramic mold and a high-permeability shielding shell. A 2D axisymmetric multiphysics coupled model was established to compare the performance of the optimized system with a conventional case and single control components. Simulation results demonstrate that the optimized system increases the magnetic flux density at the weld seam to 3.7 times that of the conventional setup (0.263 T). Consequently, the weld seam of the 240 mm² copper conductor is rapidly heated to the melting point of copper (1083 °C) within 7.78 s. Due to the high heating rate, upon completion of the welding process, the temperatures of the inner shielding and insulation layers are only 48.8 °C and 24.3 °C, respectively, well below the materials’ safety thresholds. These findings suggest that the proposed magnetic flux control strategy achieves rapid and precise heating, offering a theoretical foundation for the development of high-performance on-site equipment for fabricating cable joints. Full article

A spherical-cylindrical pressure hull is a new form of pressure-resistant structure that is distinguished from traditional large deep-sea equipment. The residual stresses and deformations introduced by out-of-tolerance welded joints pose a great threat to structural safety under deep-sea service conditions. In this paper, the angular joint of the spherical-cylindrical structure is optimized as a skirted butt joint, and the simulation method is employed to focus on the changes in stress and deformation in the two structural models before and after applying 20 MPa external pressure. The results identify that under hydrostatic pressure, the stress level in the skirt model decreases significantly compared to the residual stress of welding, while the stress in the fillet model increases slightly at the local location. After unloading, the structural stress and deformation return to the post-weld state. The effect of heat treatment on stress relief is very significant and can improve the bearing capacity of the structure. Full article

Currently, the non-uniformity of girth weld positions makes their limit state a crucial determinant of pipeline safety. The design method based on the limit state is pivotal in ensuring the integrity and reliability of the pipeline system. Challenges often emerge when determining the limit states of girth welds using semi-empirical formula methods, primarily due to difficulties in accurately identifying influential factors. The quantitative impact of each influence parameter on the crack driving force and the results determined by the semi-empirical formula remain unclear. This study utilizes numerical simulation methods to systematically analyze the quantitative sensitivity laws of critical factors such as crack depth on the crack driving force to address this challenge. The findings revealed that the strength matching coefficient, crack depth, and misalignment are the most significant factors influencing the crack driving force, followed by crack length, softening rate, yield-to-strength ratio, internal pressure, and wall thickness. The effects of tensile strength and outer diameter are relatively minor. A comprehensive database of crack driving forces is constructed using a parameter matrix approach. Combined with the LightGBM machine learning algorithm, a full-scale prediction model for the strain capacity of pipeline girth welds is developed. Predictions for 18 sets of wide-plate test results from the literature confirm the high accuracy of the prediction model, with a prediction accuracy of 6.48%. This research provides a robust reference for accurately determining the limit state of pipeline girth welds and effectively meets the demands of rapidly advancing welding technologies and increasingly complex service environments. Full article

Conventional subtractive manufacturing methods, such as cutting, often result in material waste and limitations in geometric complexity. To address these challenges, Wire Arc Additive Manufacturing (WAAM), in which components are built through successive weld bead deposition, has attracted increasing attention across various industrial fields. However, WAAM-fabricated components typically exhibit significant surface irregularities, necessitating additional post-processing that reduces overall productivity. Improving productivity therefore requires effective control and optimization of deposition parameters. This task is particularly challenging in multilayer WAAM processes, as the geometry of previously deposited layers varies with operating conditions. To address this challenge, this study proposes an AI-based framework for controlling surface roughness by rapidly identifying near-optimal process parameters in response to evolving bead geometry. A large-scale simulation dataset was generated by applying a pre-trained deep neural network (DNN) surface roughness predictor to one million bead geometry variations under 72 process parameter combinations. The resulting optimal parameter labels were used to train a classification model that recommends process conditions based on the current bead geometry. Model performance was evaluated using predictor-estimated surface roughness values, achieving Weighted Precision, Recall, and F1-score of 0.98, with an average AUC of 0.977. Five previously generated WAAM specimens were used for comparative analysis between AI-recommended and conventional process conditions using the previously developed and validated surface roughness prediction model, rather than direct physical measurements. This predictor-based feasibility analysis showed that AI-recommended conditions consistently reduced the predicted surface roughness, indicating the potential of AI-driven process optimization to improve surface quality in WAAM and reduce reliance on post-processing. Full article

This study employed a Gleeble-3800TM thermal simulator to conduct thermal cycle experiments on the coarse-grained heat-affected zone (CGHAZ) of Nb-Ti-La microalloyed steel under welding heat inputs of 50, 80, 100, and 120 kJ/cm. A systematic analysis was carried out to investigate the influence of heat input on the microstructure and impact toughness of the CGHAZ. The results indicate that the microstructure of the CGHAZ across different heat inputs consists of acicular ferrite (AF), granular bainite ferrite (GBF), polygonal ferrite (PF), as well as hard phases such as M/A constituents and degenerated pearlite (DP). With increasing heat input, the content of GBF decreases monotonically, while the content of PF increases monotonically, and the amount of hard phases rises continuously. In contrast, the content of AF initially increases and then decreases, reaching its peak at 100 kJ/cm. The microstructural changes induced by higher heat input lead to increased inhomogeneity in the local microstrain, thereby causing a monotonic reduction in crack initiation energy. Regarding crack propagation energy, the optimal performance is achieved at 100 kJ/cm due to the formation of a high proportion of AF, which heterogeneously nucleates on La-rich inclusions. This structure provides a high density of high-angle grain boundaries that effectively hinder crack propagation. Consequently, under the combined influence of crack initiation and propagation behaviors, the CGHAZ exhibits the best impact toughness at a heat input of 100 kJ/cm. Full article