Search Results (148)

Laser powder bed fusion (LPBF) of high-strength aluminum alloy 7075 (AA7075) is severely limited by hot cracking. However, the underlying mechanisms, particularly the coupling between thermal fields, solidification microstructure, and cracking behavior, remain insufficiently clarified. This study elucidates these mechanisms by integrating experimental characterization with thermal simulation to investigate the temperature field, microstructure, and cracking relationships in both AA7075 and a crack-resistant 7075-Er-Zr alloy. Results show that coarse hot crack morphology is highly dependent on linear energy density E_L. In AA7075, E_L < 450 J/m promotes laterally inclined cracks (short, narrow cracks extending from the melt pool boundary toward the track center), whereas E_L higher than that value leads to the continuous centerline cracks (long, wide cracks along the track center). Fine microcracks are also observed at melt pool boundaries. The 7075-Er-Zr alloy demonstrates superior crack resistance. At E_L = 600 J/m, longitudinal centerline cracks still penetrate along the track, but the alloy achieves crack-free tracks at 200 W with scanning speeds above 1000 mm/s, otherwise exhibiting only short discontinuous cracks. Microcracks at melt pool boundaries are markedly suppressed in the modified alloy. The enhanced crack resistance is attributed to Er/Zr-induced grain refinement and a transition to an equiaxed grain structure, which disrupts intergranular gaps. Critically, thermal simulations identify an annular region with a peak temperature gradient. In AA7075, this region develops aligned columnar grains that facilitate both microcracks and centerline cracks. In the 7075-Er-Zr alloy, microcracks are fully eliminated within this region. However, a residual crystallographic texture persists in the annular region, which promotes the continued occurrence of centerline cracks under high energy density (e.g., E_L = 600 J/m). The annular region remains a critical weak link, and its microstructural control determines the prevailing crack type. This work provides a fundamental understanding of the thermal-microstructural origins of cracking and offers a theoretical foundation for developing crack-resistant aluminum alloys via LPBF. Full article

Lack of fusion (LOF) is a dominant defect in Laser Powder-Bed Fusion (PBF-LB/M) caused by insufficient overlapping between adjacent melt pools. This study introduces a rapid, first-principles model based on Rosenthal’s analytical solution for a moving point heat source to predict melt pool geometry. Using geometric criteria, the model evaluates whether the melt pool width exceeds the hatching distance and whether the melt pool depth exceeds the layer thickness. Based on these conditions, LOF-based process windows are constructed by plotting laser power against scanning speed and classifying each parameter combination as either LOF or no LOF. The process developed here for constructing LOF process windows can be applied to metallic PBF-LB/M systems. As PBF-LB/M of copper is commonly associated with LOF defects, the approach is examined for pure copper by evaluating a range of laser powers and scanning speeds for both near-infrared (NIR) (1064 nm) and green (515 nm) lasers using copper-specific absorptivity values. The resulting process windows are validated against literature-reported relative density data for pure copper, using high relative density values as indicators of full fusion and lower relative density values reported with LOF characteristics as indicators of lack of fusion. For a 30 µm layer thickness, the predicted LOF boundary agreed with 43 of 46 literature-reported copper PBF-LB/M data points when the data were classified using relative density and reported defect morphology. Sensitivity analysis showed that the agreement changed modestly when the relative-density threshold was reduced from 99% to 98.5% and 98% and that near-boundary classifications were sensitive to the selected absorptivity within the reported NIR range. The agreement supports the use of the framework as a preliminary screening tool for identifying LOF-prone parameter regions. By providing a fast, physics-based screening tool for LOF-limited process windows, this framework offers a computationally efficient alternative to high-fidelity numerical simulations commonly used in PBF-LB/M process development. Full article

Laser powder bed fusion (LPBF) poses significant simulation challenges due to its highly nonlinear thermo-fluid-solid coupling. To address this, we propose an adaptive framework coupling the edge-based smoothed finite element method (ES-FEM) and smoothed particle hydrodynamics (SPH) via a bidirectional element-particle transformation algorithm. This integration leverages ES-FEM for modeling solid thermo-mechanical responses and SPH for resolving melt pool dynamics, enabling fully coupled simulation of temperature, fluid flow, and stress within a unified model. The framework comprises three key components: a nodal mass normalization scheme ensuring conservation during transformations, a ghost particle algorithm for solid-fluid heat transfer and interaction, and a bidirectional finite-element-to-particle conversion mechanism. This work represents the first implementation of bidirectional coupling between mesh-free Lagrangian SPH and Lagrangian FEM. The validation against benchmark cases confirms the framework’s accuracy in capturing transient thermal, hydrodynamic, and mechanical behavior. It successfully reproduces key LPBF phenomena, including melt pool morphology, Marangoni flows, and residual stress evolution, demonstrating its suitability for high-fidelity LPBF process simulation. It should be noted that the current ES-FEM-SPH framework has not taken into account the recoil pressure, evaporation, and the interaction between the powder and the molten pool. The powder is regarded as a rigid body. Future work will focus on incorporating these neglected physical factors to further improve the predictive capability of the proposed framework. Full article

This study proposes a novel dynamic composite heat source combining discrete tracking and vapor heating, which can precisely capture the transient energy deposition at the keyhole wall, and further discusses the formation mechanism of weld defects by investigating keyhole evolution and melt pool flow behavior. The weld morphology and dimensions predicted by the simulation are in good agreement with the experimental data, revealing the coupled mechanism between keyhole instability and porosity formation, as well as the generation mechanism of process-type porosity mainly influenced by the keyhole dynamic characteristics and the melt pool flow field together; specifically, keyhole instability forms a vapor cavity that will generate bubbles to participate in melt pool flow if it cannot be re-fused with the keyhole, and the bubble trajectory is related to buoyancy, gravity and liquid flow in the melt pool, with larger bubbles less likely to escape due to greater liquid viscous force. In addition, this study finds that increasing weld power and weld speed helps improve keyhole stability, weaken melt pool circulation intensity and shorten bubble escape path, thereby fundamentally revealing the formation mechanism of porosity defects during electron beam welding (EBW) of aluminum alloy, providing an effective numerical tool for optimizing EBW process parameters, and proposing corresponding inhibition measures to improve weld quality. Full article

The segregation of brittle Laves phases remains a critical bottleneck limiting the performance of additive manufacturing (AM) nickel-based superalloys. While its evolution is governed by complex transient physical fields within the melt pool, a quantitative kinetic correlation between processing parameters and microstructural features is currently lacking. In this study, a high-fidelity multiphysics numerical model was developed to establish a cross-scale mapping logic of “Process-Physical Field-Microstructure” by dissecting the global distribution of temperature gradient (G) and solidification rate (R) along the quasi-steady-state melt pool boundary. It is revealed that increasing the scanning speed synergistically enhances R while compressing G. Beyond driving a transition from oriented columnar dendrites to refined mixed-dendritic structures, this shift effectively blocks the continuous enrichment channels of Nb and Mo elements by compressing the “kinetic time window” for solute redistribution. Consequently, the morphology of the Laves phase is forced to evolve from a continuous interconnected chain-like network into dispersed isolated particles. This research clarifies the kinetic essence of microstructural evolution under non-equilibrium solidification, providing critical physical criteria for the precise intervention of deleterious phases and the regulation of microstructural consistency in high-performance AM components. Full article

Arc-driven powder bed fusion represents a low-cost alternative to beam-based powder bed systems, yet the morphological stability regimes governing single-track formation and the relative influence of process parameters on regime transitions have not been systematically characterised. Manual visual assessment of track morphology is inherently subjective and cannot objectively quantify the parameter hierarchy governing stability boundaries. This study addresses both limitations through two complementary contributions. A deterministic two-stage image-based framework is developed to automatically classify single-track morphology from top-view images of solidified 316L stainless steel tracks, replacing subjective assessment with a reproducible, intervention-free procedure. A gap-based continuity criterion distinguishes discontinuous from continuous melt paths; for continuous tracks, the coefficient of variation in width (CV (coefficient of variation) < 0.15) further separates geometrically stable from transitional morphologies. Building on the image-derived regime labels, two interpretable classifiers—a depth-limited Decision Tree (DT) and a regularised Logistic Regression (LR)—are fitted using applied current, scanning speed, and electrode-to-powder-bed distance as predictors. The classifiers are employed not for predictive generalisation but to extract standardised coefficients and permutation-based feature importance rankings, yielding a model-agnostic, quantitative explanation of which process parameters govern regime transitions. Stable continuous tracks are obtained only within a restricted parameter window. Permutation importance consistently ranks applied current as the dominant predictor, followed by electrode distance and scanning speed, in agreement with the thermophysical interpretation. Logistic Regression coefficients confirm that reduced stand-off distance is a necessary condition for sufficient arc constriction. Supplementary linear regression models indicate that applied current governs melt pool depth, whereas scanning speed is the primary determinant of width variation. The combined framework establishes a reproducible basis for process parameter hierarchy analysis in arc-driven powder bed systems and provides a foundation for regression-based process optimisation. Full article

Laser Powder Bed Fusion for metals (PBF-LB/M) is a complex additive manufacturing process in which metal powder is selectively melted layer-by-layer to fabricate 3D parts. Process parameters critically influence the resulting microstructure in nickel alloys, with features such as melt pool marks, grain size and orientation, porosity, and cracks serving as key process signatures. These features are typically analyzed post-process to identify suboptimal conditions. This research aims to develop automated post-process measurement and analysis techniques using image processing, pattern recognition, and statistical learning to correlate process parameters with part quality. Optical microscopy images of build surfaces are analyzed using machine learning algorithms to evaluate porosity, grain size, and relative density in fabricated test coupons. Effect plots are generated to identify trends related to increasing energy density. A novel deep learning approach based on Mask R-CNN is used to detect and segment melt pool regions in optical microscopy images. From the segmented regions, melt pool dimensions—such as width, depth, and area—are extracted using bounding geometry coordinates. Manually labeled images (Type I and Type II) are used to train the model. A comparison between ResNet-50 and ResNet-101 backbones shows that the ResNet-50-based model (Model 2) achieves superior performance, with lower training loss (0.1781 vs. 0.1907) and validation loss (8.6140 vs. 9.4228). Quantitative evaluation using the Jaccard index, precision, and recall metrics shows that the ResNet-101 backbone outperforms ResNet-50, achieving about 4% higher mean Intersection-over-Union, with values of 0.85 for Type I and 0.82 for Type II melt pools, where Type I is detected more accurately due to its more regular morphology and clearer boundaries. By extending Faster R-CNNs with a mask prediction branch, the method allows for precise melt pool measurements, providing valuable insights into process quality and dimensional accuracy, and aiding in the detection of defects in PBF-LB-fabricated parts. Full article

This study investigates the influence of varying positive–negative polarity ratios (EP:EN) on melt pool evolution during alternating current CMT (VP-CMT) arc additive manufacturing through a combined experimental and numerical approach. A multi-layer single-track droplet-melt pool coupling model was established, revealing the regulatory mechanisms governing melt pool flow, temperature distribution, and dimensional changes. These are driven by differences in arc morphology, heat input, and mechanical forces during EP and EN phases. Results indicate that molten pool flow is primarily governed by wire feed, retraction, and Marangoni forces. During the EP phase, arc divergence and elevated heat input result in significantly higher flow velocities than in the EN phase. Molten pool length increases with rising EP proportion, exhibiting periodic dynamic variations. Lateral flow intensity intensifies as EP ratio increases, directly influencing cladding layer morphology. This study provides theoretical basis for optimising additive manufacturing quality by adjusting the EP:EN ratio. Full article

In metal additive manufacturing, the molten pool directly influences the performance of the fabricated components. Therefore, a comprehensive understanding of the molten pool behavior is essential for improving the quality of the parts and mitigating the formation of defects. Selective arc melting (SAM) is a promising additive manufacturing method for fabricating metal matrix composites. However, the melting and solidification process of the powder layer under the arc heat source remains unrevealed. This study aims to elucidate the formation mechanisms of surface morphology during SAM processing and the influence of carbide addition on the melting and solidification behavior of Inconel 718 powder. In this study, thin-walled parts of Inconel 718 and TiC/Inconel 718 composite were fabricated and their microstructures were studied. The melting and solidification behavior of Inconel 718 and TiC/Inconel 718 composite during single-track single-layer deposition was investigated using high-speed photography. Focusing on the differences in the sidewall surface morphology of the Inconel 718 and TiC/Inconel 718 composite parts, the edge feature formation of the deposition track of both materials was studied. Furthermore, the formation mechanism of the differences in forming height at different positions of the deposition track was explored. The results indicate that the melted material in the molten pool of Inconel 718 mainly comes from the mass transport of the beads generated around the molten pool, while the liquid material in the molten pool of TiC/Inconel 718 composite mainly comes from the in situ powder melted under the arc center. During the melting process of Inconel 718 powder, beads at the edge of the heating area come into contact with the boundary of the molten pool and solidify in situ, forming protrusion features. The randomness in the bead size leads to different volumes of molten material at different positions within the same time, thereby causing variations in building height. Full article

Powder-bed arc additive manufacturing (PBAAM) may reduce the cost of powder-bed metal additive manufacturing and enable thicker layers than laser powder bed fusion (LPBF), but melt-track stability limits are not well established. Here, 316L stainless steel powder (15–53 µm) was melted by a TIG-based arc in a custom powder-bed system while varying current, travel speed, layer thickness and hatch distance. Single tracks on an inclined bed (≈0–0.4 mm thickness) were used to identify continuity loss and melt-pool width, quantified from top-view images via width profiles, a gap-based continuity metric and the coefficient of variation. Parallel-track tests at 0.15, 0.20 and 0.25 mm layer thickness with hatch distances set to 25%, 50% and 75% of the measured melt-pool width assessed inter-track bonding and lack of fusion, and selected parameters were validated in five-layer builds. Higher current with low-to-moderate travel speeds produced wider, more stable melt pools on the inclined bed. Hatch ratios of 25–50% were the most effective for sustaining fusion in single layers and multi-layer builds, whereas 75% promoted unbonded regions and narrow-track morphologies. Overall, PBAAM can process substantially thicker layers with relatively simple equipment, but requires a narrow, carefully tuned window to balance continuity, fusion and heat accumulation. Full article

This study utilized oscillating laser cladding technology to fabricate nickel-based composite coatings, systematically investigating the influence of varying laser powers on their morphology, microstructure, and properties. The results indicate that as laser power increases from 800 W to 1400 W, the dilution rate of the coating exhibits a non-monotonic change, reaching a maximum at an intermediate laser power due to the competing effects of enhanced substrate melting and melt-pool instability. The microstructure of the coatings is primarily composed of dendritic and equiaxed crystals. Elemental analysis revealed that Ni is predominantly enriched within the dendritic regions, whereas Cr segregates toward the grain boundary areas. Furthermore, the microhardness of the coating, as well as its anti-wear and anti-corrosion properties, are positively correlated with the laser power. When the power reaches the maximum value of 1400 W studied, the performance of the coating significantly improves. The average hardness is 482 HV, and the relative wear resistance is approximately 1.8 times that of the coating when the power is 800 W. The corrosion current density is 9.04 × 10⁻⁷ A/cm². Full article

To address surface defects and enhance the wear resistance of 316L stainless steel parts fabricated by Selective Laser Melting (SLM), this study applied shot peening (SP) surface treatment to the SLM-processed samples. Ball-on-disk tribological tests were systematically conducted under water-lubricated conditions to investigate the evolution of surface morphology, microstructure, microhardness, and tribological performance before and after SP. The results indicate that SP induced severe plastic deformation in the surface layer, effectively refining the coarse columnar crystals and melt pool structures characteristic of SLM, and forming a crystalline hardened layer with a depth of 70–80 μm. Consequently, the surface microhardness increased by 21.97% compared to the un-peened samples. Under loads of 20 N and 30 N, the coefficient of friction (COF) of the SP-treated samples decreased by 16.36% and 12.4%, while the wear rate was reduced by 17.09% and 14.9%, respectively. In this load range, the samples primarily exhibited uniform plowing and localized adhesive wear, demonstrating significantly improved resistance to plastic deformation and crack initiation. However, when the load increased to 40 N, intense stress and thermal effects diminished the strengthening benefits of SP, resulting in no significant difference in tribological performance between the SP-treated and untreated samples. At this stage, the dominant wear mechanism transitioned to severe plastic deformation, extensive delamination, and thermally induced adhesion. Full article

This study examines the joining characteristics of Cu foil stacks to lead tabs using green-laser welding in the main-welding step of a sequential welding process for lithium-ion pouch cells. The influence of lap configuration, line and wobble seam strategies, and process parameters was systematically investigated in terms of bead morphology, mechanical performance, metallurgical characteristics, and electrical resistance. Under the present line-welding parameter window (2.0 kW, 100–200 mm/s), humping, pinholes, and porosity were observed, particularly in the upper lead-tab configuration, which is attributed to melt-pool/keyhole instability under the applied conditions. Wobble welding effectively suppressed these defects in the foil-stack configuration by promoting stable melt flow and efficient bubble expulsion. Mechanical tests revealed that the wobble-based seam strategy achieved a maximum tensile–shear load of approximately 1.28 kN at a wobble amplitude of 0.8 mm. Fracture analysis confirmed a transition from seam-type interfacial failure in line welding to ductile tearing in the heat-affected zone with wobble welding. In electrical performance, wobble welding reduced resistance to as low as 45 µΩ at a wobble amplitude of 1.2 mm, while line welding yielded higher and scattered values. These results should be interpreted as the combined outcome of the wobble-based seam strategy (beam oscillation together with overlapped stitch welding at a lower travel speed) under the present processing windows. A strictly matched A/B comparison at identical linear energy density and seam layout will be investigated in future work to isolate the effect of oscillation. Full article

To address the limitations in the corrosion resistance of 316L stainless steel, ceramic reinforcements are increasingly utilized in additive manufacturing. However, their influence on corrosion behavior varies significantly. Via laser powder bed fusion (LPBF), 316L stainless steel composites reinforced with, respectively, 1 wt.% ceramic particles (TiC, SiC, SiO₂, WC, Y₂O₃) were fabricated, and the comparing microstructure and corrosion performance was investigated in this work. The results indicated that ceramic particle addition increased porosity (0.24% to 1.40%) due to the thermal expansion coefficient mismatch between particles and matrix and defects from incompletely melted particles. Microstructural analysis revealed that LPBF-processed 316L exhibited cellular sub-grain boundaries with distinct melt pool boundaries. Ceramic particle addition refined sub-grain boundaries to varying degrees across composites, accompanied by increased sub-grain boundary density. Interfacial reactions and thermal stresses induced crack formation in SiC/316L and SiO₂/316L composites. Electrochemical testing demonstrated that Y₂O₃/316L exhibited the highest corrosion resistance, followed by TiC/316L and WC/316L. The corrosion resistance of the as-built L-BPF 316L matrix was inferior to that of these three composites. Conversely, SiC/316L and SiO₂/316L exhibited the poorest corrosion resistance. The optimized corrosion resistance of Y₂O₃/316L is hypothesized to result from pronounced grain refinement and the highest sub-grain boundary density, which provided abundant nucleation sites for passive film formation. Conversely, SiC/316L and SiO₂/316L showed lower corrosion resistance than the as-built L-BPF 316L matrix due to elevated defect density. Corrosion morphology analysis indicated preferential corrosion propagation along melt pool boundaries in 316L, TiC/316L, WC/316L, and Y₂O₃/316L. In contrast, pores and microcracks in SiC/316L and SiO₂/316L accelerated pit nucleation, indicating failure dominated by localized corrosion mechanisms. Full article

Selective Laser Melting (SLM), as a common metal additive manufacturing (AM) technology, achieves high-precision complex part formation by layer-by-layer melting of metal powder using a laser. However, the dynamic behavior of the melt pool during the SLM process is influenced by the heat source model, which is crucial for suppressing porosity defects and optimizing process parameters, directly determining the reliability of numerical simulations. To address the issue of traditional surface heat source models overestimating the melt pool width and volume heat source models underestimating the melt pool depth, this study constructs a three-dimensional transient heat conduction finite element model based on ANSYS Parametric Design Language (APDL) to simulate the evolution of the temperature field and melt pool geometry under different laser parameters. First, the temperature fields and melt pool morphology and dimensions of four heat source models—Gaussian surface heat source, volumetric heat source models (rotating Gaussian volumetric heat source, double ellipsoid heat source), and a combined heat source model—were investigated. Subsequently, a dynamic heat source model was proposed, combining a Gaussian surface heat source with a rotating volumetric heat source. By dynamically allocating the laser energy absorption ratio between the powder surface layer and the substrate depth, the influence of this heat source model on melt pool size was explored and compared with other heat source models. The results show that under the dynamic heat source, the melt pool width and depth are 128.6 μm and 63.13 μm, respectively. The melt pool width is significantly larger compared to other heat source models, and the melt pool depth is about 17% greater than that of the combined heat source model. At the same time, the predicted melt pool width and depth under this heat source model have relative errors of 1.0% and 5.5% compared to the experimental measurements, indicating that this heat source model has high accuracy in predicting the melt pool’s lateral dimensions and can effectively reflect the actual melt pool morphology during processing. Full article