Search Results (433)

Accurate melt pool geometry prediction is essential for ensuring quality and reliability in Laser Powder Bed Fusion (L-PBF). However, small experimental datasets and limited physical interpretability often restrict the effectiveness of traditional machine learning (ML) models. This study proposes a hybrid framework that integrates an explicit thermal model with ML algorithms to improve prediction under sparse data conditions. The explicit model—calibrated for variable penetration depth and absorptivity—generates synthetic melt pool data, augmenting 36 experimental samples across conduction, transition, and keyhole regimes for 316 L stainless steel. Three ML methods—Multilayer Perceptron (MLP), Random Forest, and XGBoost—are trained using fivefold cross-validation. The hybrid approach significantly improves prediction accuracy, especially in unstable transition regions (D/W ≈ 0.5–1.2), where morphological fluctuations hinder experimental sampling. The best-performing model (MLP) achieves R² > 0.98, with notable reductions in MAE and RMSE. The results highlight the benefit of incorporating physically consistent, nonlinearly distributed synthetic data to enhance generalization and robustness. This physics-augmented learning strategy not only demonstrates scientific novelty by integrating mechanistic modeling into data-driven learning, but also provides a scalable solution for intelligent process optimization, in situ monitoring, and digital twin development in metal additive manufacturing. Full article

This study systematically investigates the homogenization-induced Laves phase dissolution kinetics and recrystallization mechanisms in laser powder bed fusion (L-PBF) processed IN718 superalloy. The as-built material exhibits a characteristic fine dendritic microstructure with interdendritic Laves phase segregation and high dislocation density, featuring directional sub-grain boundaries aligned with the build direction. Laves phase dissolution demonstrates dual-stage kinetics: initial rapid dissolution (0–15 min) governed by bulk atomic diffusion, followed by interface reaction-controlled deceleration (15–60 min) after 1 h at 1150 °C. Complete dissolution of the Laves phase is achieved after 3.7 h at 1150 °C. Recrystallization initiates preferentially at serrated grain boundaries through boundary bulging mechanisms, driven by localized orientation gradients and stored energy differentials. Grain growth kinetics obey a fourth-power time dependence, confirming Ostwald ripening-controlled boundary migration via grain boundary diffusion. Such a study is expected to be helpful in understanding the microstructural development of L-PBF-built IN718 under heat treatments. Full article

This study aims to determine the optimal low-temperature stress relieving heat treatment that minimizes residual stresses while preserving corrosion resistance in Laser Powder Bed Fusion (L-PBF) processed Ti6Al4V alloy. Specifically, it investigates the effects of stress relieving at 400 °C, 600 °C, and 800 °C on microstructure, residual stress, and electrochemical performance. Specimens were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), and electrochemical techniques. A novel microcapillary electrochemical method was employed to precisely assess passive layer stability and corrosion behaviour under simulated oral conditions, including fluoride contamination and tensile loading. Results show that heat treatments up to 600 °C effectively reduce residual stress with minimal impact on corrosion resistance. However, 800 °C treatment leads to a phase transformation from α′ martensite to a dual-phase α + β structure, significantly compromising passive film integrity. The findings establish 600 °C as the optimal stress-relieving temperature for balancing mechanical stability and electrochemical performance in biomedical and aerospace components. Full article

Laser beam powder bed fusion of metals (PBF-LB/M, or simply L-PBF) has emerged as one of the most competitive additive manufacturing technologies for producing complex metallic components with high precision, design freedom, and minimal material waste. Among the various categories of additive manufacturing processes, L-PBF stands out, paving the way for the execution of part designs with geometries previously considered unfeasible. Despite offering several advantages, parts with overhang features require the use of support structures to provide dimensional stability of the part. Support structures achieve this by resisting residual stresses generated during processing and assisting heat dissipation. Although the scientific community acknowledges the role of support structures in the success of L-PBF manufacturing, they have remained relatively underexplored in the literature. In this context, the present work investigated the impact of laser power and scanning speed on the dimensioning, integrity and tensile strength of single-walled block type support structures manufactured in AISI 316L stainless steel. The method proposed in this work is divided in two stages: processing parameter exploration, and mechanical characterization. The results indicated that support structures become more robust and resistant as laser power increases, and the opposite effect is observed with an increment in scanning speed. In addition, defects were detected at the interfaces between the bulk and support regions, which were crucial for the failure of the tensile test specimens. For a layer thickness corresponding to 0.060 mm, it was verified that the combination of laser power and scanning speed of 150 W and 500 mm/s resulted in the highest tensile resistance while respecting the dimensional deviation requirement. Full article

The study investigates the influence of microstructures on fatigue behavior and failure mechanisms of the α-β titanium alloy Ti6246, fabricated via Powder Bed Fusion-Laser Beam (PBF-LB). In particular, the investigation assesses the effect of two post-processing heat treatments, namely α-β annealing at 875 °C (AN875) and solution treatment at 825 °C followed by aging at 500 °C (STA825), on the alloy’s rotating and bending fatigue behavior. The results indicate that the STA825 condition provides superior fatigue resistance (+25%) compared to AN875, due to the presence of a finer bilamellar microstructure, characterized by thinner primary α lamellae (α_p) and a more homogeneous distribution of secondary α lamellae (α_s) within the β matrix. Additionally, an investigation conducted using the Kitagawa–Takahashi (KT) approach and the El-Haddad model, based on the relationship between the fatigue limit and defect sensitivity, revealed improved crack propagation resistance from pre-existing defects (ΔK_th) for the STA825 condition compared to AN875. Notably, the presence of fine α_s after aging for STA825 is effective in delaying crack nucleation and propagation at early stages, while refined α_p contributes to hindering macrocrack growth. The fatigue behavior of the STA825-treated Ti6246 alloy was even superior to that of the PBF-LB-processed Ti64, representing a viable alternative for the production of high-performance components in the automotive and aerospace sectors. Full article

This study investigates the influence of process parameters on the fabrication and mechanical performance of Scalmalloy^® lattice structures produced via laser powder bed fusion (PBF-LB) and their mechanical responses at different cell size. A full-factorial design of experiments was employed to evaluate the effect of scan speed, hatch distance, and downskin power on internal porosity and dimensional accuracy. Regression models revealed significant relationships, with optimised parameters identified at a scan speed of 700 mm/s, hatch distance of 0.13 mm, and downskin power of 80 W. Mechanical characterisation through tensile tests of bulk samples and compression tests of lattice structures highlighted the strengthening effects of the heat treatment. Experimental data on quasi-elastic gradient and yield strength were compared to predictions from the Ashby–Gibson model, revealing a partial agreement but noticeable deviations attributed to cell geometry and manufacturing defects. The scaling laws observed differed from the classical model, particularly in the yield strength exponent, indicating the need for empirical models tailored to metallic lattices. This work provides key insights into the optimisation of PBF-LB parameters for Scalmalloy^® and underlines the complex interplay between process parameters, structural design, and mechanical behaviour. Full article

Additive manufacturing (AM), particularly laser powder bed fusion (L-PBF), provides unmatched design flexibility for creating intricate steel structures with minimal post-processing. However, adopting L-PBF for high-performance applications is difficult due to the challenge of predicting microstructure evolution. This is because the process is sensitive to many parameters and has a complex thermal history. Thin-walled geometries present an added challenge because their dimensions often approach the scale of individual grains. Thus, microstructure becomes a critical factor in the overall integrity of the component. This study focuses on applying cellular automata (CA) modeling to establish robust and efficient process–structure relationships in L-PBF of 316L stainless steel. The CA framework simulates solidification-driven grain evolution and texture development across various processing conditions. Model predictions are evaluated against experimental electron backscatter diffraction (EBSD) data, with additional quantitative comparisons based on texture and morphology metrics. The results demonstrate that CA simulations calibrated with relevant process parameters can effectively reproduce key microstructural features, including grain size distributions, aspect ratios, and texture components, observed in thin-walled L-PBF structures. This work highlights the strengths and limitations of CA-based modeling and supports its role in reliably designing and optimizing complex L-PBF components. Full article

Multi-laser processing is increasingly adopted in laser powder bed fusion (L-PBF) to improve productivity and enable the fabrication of larger components, but its impact on part quality and performance remains a critical concern. This study investigates the microstructure, tensile properties, and fatigue performance of components fabricated by L-PBF using single- and multiple-laser configurations. Both strategies were evaluated under varying layer thicknesses and gas flow conditions with optimized process parameters. Microstructural analysis revealed defects such as lack-of-fusion, porosity and microcracks in multiple-laser builds with reduced gas flow. However, the density and microhardness results showed negligible differences between single and multiple-laser builds. Tensile testing indicated that single-laser builds exhibited superior strength and ductility, whereas multiple-laser builds demonstrated reduced performance due to localized defects such as lack-of-fusion and microcracks. Low-cycle fatigue testing results showed that optimized multiple-laser strategies could achieve performance comparable to that of single-laser builds while improving productivity. The results also revealed that the gas flow becomes more pronounced with multiple-laser processing, where more spatter is generated due to the interactions of the lasers in a small scan area, and that reduced gas flow leads to fatigue degradation due to increased defect density. The results from this study clearly highlight the importance of gas flow, laser overlap, border optimization, and defect mitigation strategies in producing multiple-laser produced components with mechanical properties and fatigue performance comparable to those of single-laser produced L-PBF components. Full article

The lack of new materials with desired processability and functional characteristics remains a challenge for metal additive manufacturing (AM). Therefore, in this work, a new promising AISI 316L-based alloy with better performance compared to the commercially available one is developed via the laser powder bed fusion (L-PBF) process. Moreover, establishing process–structure–properties linkages is a critical point that should be evaluated carefully before adding newly developed alloys into the AM market. Hence, the current study investigates the influences of various process parameters on the as-built quality and microstructure of the newly developed alloy. The results revealed that increasing laser energy density led to reduced porosity and surface roughness, likely due to enhanced melting and solidification. Microstructural analysis revealed a uniform distribution of copper within the austenite phase without forming any agglomeration or secondary phases. Electron backscatter diffraction analysis indicated a strong texture along the build direction with a gradual increase in Goss texture at higher energy densities. Grain boundary regions exhibited higher local misorientation and dislocation density. These findings suggest that changing the process parameters of the L-PBF process is a promising method for developing tailored microstructures and chemical compositions of commercially available AISI 316L stainless steel. Full article

This work presents a multiscale, microstructure-aware framework for predicting fatigue strength distributions in additively manufactured (AM) alloys—specifically, laser powder bed fusion (L-PBF) AlSi10Mg and Ti-6Al-4V—by integrating density functional theory (DFT), instrumented indentation, and Bayesian inference. The methodology leverages principles common to all 3D printing (additive manufacturing) processes: layer-wise material deposition, process-induced defect formation (such as porosity and residual stress), and microstructural tailoring through parameter control, which collectively differentiate AM from conventional manufacturing. By linking DFT-derived cohesive energies with indentation-based modulus measurements and a MAP-based statistical model, we quantify the effect of additive-manufactured microstructural heterogeneity on fatigue performance. Quantitative validation demonstrates that the predicted fatigue strength distributions agree with experimental high-cycle and very-high-cycle fatigue (HCF/VHCF) data, with posterior modes and 95 % credible intervals of ${\widehat{\sigma }}_f^{\mathrm{AlSi}10\mathrm{Mg}}={86}_{-7}^{+8}\mathrm{MPa}$ and ${\widehat{\sigma }}_f^{\mathrm{Ti}–6\mathrm{Al}–4\mathrm{V}}={115}_{-9}^{+10}\mathrm{MPa}$, respectively. The resulting Woehler (S–N) curves and Paris crack-growth parameters envelop more than 92 % of the measured coupon data, confirming both accuracy and robustness. Furthermore, global sensitivity analysis reveals that volumetric porosity and residual stress account for over 70 % of the fatigue strength variance, highlighting the central role of process–structure relationships unique to AM. The presented framework thus provides a predictive, physically interpretable, and data-efficient pathway for microstructure-informed fatigue design in additively manufactured metals, and is readily extensible to other AM alloys and process variants. Full article

Thermomechanical processing has a significant impact on the porosity and mechanical properties of AISI 316L stainless steel produced by laser powder bed fusion (L-PBF). This work evaluated the effect of three heat treatment conditions: as-built (HT0), annealed at 650 °C for 3 h with air cooling (HT1), and annealed at 1050 °C for 1 h followed by water quenching (HT2), combined with cold and hot rolling at different strain levels. The most pronounced improvement was observed after 20% hot rolling followed by water quenching (HR + WQ), which reduced porosity to 0.05% and yielded the most spherical pores, with a circularity factor ($f_{circle}$) of 0.90 and an aspect ratio (AsR) of 1.57. At elevated temperatures, the matrix becomes more pliable, which promotes pore closure and helps reduce stress concentrations. On the other hand, applying heat treatment without causing deformation resulted in the pores growing and increasing porosity in the build direction. The fractography supported these findings, showing a transition from brittle to more ductile fracture surfaces. Heat treatment combined with plastic deformation effectively reduced internal defects and improved both structural integrity and strength. Full article

Additive manufacturing techniques, such as laser-based powder bed fusion of metals (PBF-LB/M), have now gained high industrial and academic interest. Despite its design flexibility and the ability to fabricate intricate components, LPBF has not yet reached its full potential, partly due to the challenges associated with microstructure control. The precise manipulation of the microstructure in LPBF is a formidable yet highly rewarding endeavor, offering the capability to engineer components at a local level. This work introduces an innovative parallelized Cellular Automaton (CA) framework for modeling the evolution of the microstructure during the LPBF process. LPBF involves remelting and subsequent nucleation followed by crystal growth during solidification, which complicates and burdens microstructure simulations. In this research, a novel approach to nucleation seeding and crystal growth is implemented, focusing exclusively on the final stages of melting and solidification, enhancing the computational efficiency by 30%. This approach streamlines the simulation process, making it more efficient and effective. The developed model was employed to simulate the microstructure of an austenitic advanced high-strength steel (AHSS). The model was validated by comparing the simulation results qualitatively and quantitatively with the experimental data obtained under the same process parameters. The predicted microstructure closely aligned with the experimental findings. Simulations were also conducted at varying resolutions of CA cells, enabling a comprehensive study of their impact on microstructure evolution. Furthermore, the computational efficiency was critically evaluated. Full article

Laser-based powder bed fusion of metals (PBF-LB/M) is one of the most promising additive manufacturing technologies to fabricate complex-structured metal parts. However, its corresponding applications have been limited by technical bottlenecks and increasingly strict industrial requirements. Process optimization, a scientific issue, urgently needs to be solved. In this paper, a three-phase transient model based on the level-set method is established to examine the heat transfer and melt pool behavior in PBF-LB/M. Surface tension, the Marangoni effect, and recoil pressure are implemented in the model, and evaporation-induced mass and thermal loss are fully considered in the computing element. The results show that the surface roughness and density of metal parts induced by heat transfer and melt pool behavior are closely related to process parameters such as laser power, layer thickness, scanning speed, etc. When the volumetric energy density is low, the insufficient fusion of metal particles leads to pore defects. When the line energy density is high, the melt track is smooth with low porosity, resulting in the high density of the products. Additionally, the partial melting of powder particles at the beginning and end of the melting track usually contributes to pore formation. These findings provide valuable insights for improving the quality and reliability of metal additive manufacturing. Full article

316L stainless steel (316L SS) exhibits excellent corrosion resistance, mechanical properties, and biocompatibility, but the rapid melting and solidification of the laser powder bed fusion (PBF-LB/M) process reduce the properties of the newly formed parts. This study aims to enhance the mechanical properties of PBF-LB/M PBF-LB/M-formed 316L SS parts by investigating the effects of various heat treatment temperatures. The results show that an appropriate heat treatment temperature can improve the microstructure and mechanical properties of the formed parts. Lower temperatures have minimal effects on performance; however, at 1100 °C, recrystallization occurs, resulting in more uniform grain structures, improved densification, and substantial stress relief. The residual stress is reduced by 85.59% compared to the untreated PBF-LB/M samples, while the ferrite content is significantly decreased, making the phase structure more homogeneous. Although both yield strength and tensile strength decrease, plasticity improves by 21.11%. Full article

Titanium alloys, especially Ti6Al4V, are widely used in biomedical implants due to their biocompatibility and mechanical strength. However, their high elastic modulus (>100 GPa), compared to that of human bone (10–30 GPa), often causes stress shielding, reducing implant lifespan. To address this, titanium alloys with lower elastic modulus are under development. In this study, Ti-based multi-element alloy with 16 wt.% Nb samples were fabricated using laser powder bed fusion (L-PBF) from a premixed powder blend of Ti6Al4V and Nb-Hf-Ti. Processing high-melting Nb-based alloys via L-PBF poses challenges, which were mitigated through optimized parameters, including a maximum laser power of 100 W. Eleven parameter sets were employed to evaluate printability, microstructure, and mechanical properties. Microstructural analysis revealed Widmanstätten structures composed of α and β phases, along with isolated spherical pores. Reduced hatch spacing and slower laser speed led to increased hardness. The highest hardness (~43 HRC) was observed at the highest energy density (266 J/mm³), while the lowest (~28 HRC) corresponded to 44 J/mm³. Elastic modulus values ranged from 30 to 35 GPa, closely matching that of bone. These results demonstrate the potential of the developed Ti-based alloy containing 16 wt.% Nb as a promising candidate for load-bearing biomedical implants. Full article