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Damage initiation and localization in uniaxial tension tests of an Al6061‐T6 alloy are evaluated and quantified using in situ X‐ray computed tomography and a neural network segmentation strategy. This segmentation strategy offers significant advantages over traditional thresholding in quantifying microstructural and damage evolution metrics. Void nucleation was observed to occur throughout the deformation process, whereas void volume did not grow significantly until later stages of deformation. Localized analysis determined that void nucleation begins in and around the necked region during the early stages of deformation, whereas limited damage nucleation occurs outside of the neck until late stages of deformation. Lastly, inhomogeneities in void and particle spacing in the initial undeformed state of the material are observed to correlate well with the location of damage localization and necking during deformation. These results provide new insights into the ductile failure of Al alloys and how preexisting defects influence damage and rupture. Highlights: Void nucleation occurs throughout the deformation process.Void volume is constant until later stages of deformation.Void nucleation is concentrated in the neck region during early stages of deformation.Void and particle spacing in the undeformed state correlate with damage localization. [ABSTRACT FROM AUTHOR]

Purpose: There is recent emphasis on designing new materials and alloys specifically for metal additive manufacturing (AM) processes, in contrast to AM of existing alloys that were developed for other traditional manufacturing methods involving considerably different physics. Process optimization to determine processing recipes for newly developed materials is expensive and time-consuming. The purpose of the current work is to use a systematic printability assessment framework developed by the co-authors to determine windows of processing parameters to print defect-free parts from a binary nickel-niobium alloy (NiNb5) using laser powder bed fusion (LPBF) metal AM. Design/methodology/approach: The printability assessment framework integrates analytical thermal modeling, uncertainty quantification and experimental characterization to determine processing windows for NiNb5 in an accelerated fashion. Test coupons and mechanical test samples were fabricated on a ProX 200 commercial LPBF system. A series of density, microstructure and mechanical property characterization was conducted to validate the proposed framework. Findings: Near fully-dense parts with more than 99% density were successfully printed using the proposed framework. Furthermore, the mechanical properties of as-printed parts showed low variability, good tensile strength of up to 662 MPa and tensile ductility 51% higher than what has been reported in the literature. Originality/value: Although many literature studies investigate process optimization for metal AM, there is a lack of a systematic printability assessment framework to determine manufacturing process parameters for newly designed AM materials in an accelerated fashion. Moreover, the majority of existing process optimization approaches involve either time- and cost-intensive experimental campaigns or require the use of proprietary computational materials codes. Through the use of a readily accessible analytical thermal model coupled with statistical calibration and uncertainty quantification techniques, the proposed framework achieves both efficiency and accessibility to the user. Furthermore, this study demonstrates that following this framework results in printed parts with low degrees of variability in their mechanical properties. [ABSTRACT FROM AUTHOR]

Laser powder-bed fusion solidification of Ni–Nb alloys often results in cellular morphology in which the solute microsegregation was determined using experiments and simulations, and the data obtained were utilised to explore the predictive capability of microsegregation models. The experimental 'ground truth' was compared with high-fidelity phase-field simulations as well as with analytical model predictions. Supervised statistical analyses, including linear regression, polynomial regression, and model reification were employed to understand the merit of these approaches toward microsegregation estimation. The bias-variance and accuracy-interpretability trade-off limits were considered in the data analysis that was consistent with our experimental findings. [ABSTRACT FROM AUTHOR]

Martensitic steels have gained renewed interest recently for their use in automotive, aerospace, and defense applications due to their ultra-high yield strengths and reasonable ductility. A recently discovered low alloy martensitic steel, AF9628, has been shown to exhibit strengths greater than 1.5 GPa with more than 10% tensile ductility, due to the formation of ε-carbide phase. In an effort to produce high strength parts with a high degree of control over geometry, the work herein presents the effects of selective laser melting (SLM) parameters on the microstructure and mechanical properties of this new steel. An optimization framework to determine the process parameters for building porosity-free parts is introduced. This framework utilizes the computationally inexpensive Eagar-Tsai model, calibrated with single track experiments, to predict the melt pool geometry. A geometric criterion for determining maximum allowable hatch spacing is also developed in order to avoid lack of fusion induced porosity in the as-printed parts. Using this framework, fully dense samples were successfully fabricated over a wide range of process parameters, allowing the construction of an SLM processing map for AF9628. The as-printed samples displayed tensile strengths of up to 1.4 GPa, the highest reported to date for any 3D printed alloy, with up to 11% elongation. The demonstrated flexibility in process parameter selection, while maintaining full density, opens up the possibility of local microstructural refinement and parameter optimization for improved mechanical properties in as-printed parts. The process optimization framework introduced here is expected to allow successful printing of new materials in an accelerated fashion. Image, graphical abstract [ABSTRACT FROM AUTHOR]

The solidification microstructure of a melt pool under additive manufacturing conditions is highly heterogeneous due to the heterogeneity in the thermal spatio-temporal fields. This work combines a finite element (FE)-based thermal model with a phase field model (PFM) to predict microstructure distribution among the process parameter span in LPBF, which is strongly controlled by local thermal histories. The segregation distribution across the parameter space can be classified into four different microstructure distribution types: (i) fully planar, (ii) bottom dendritic, (iii) top dendritic, and (iv) fully dendritic. Also, the relationship between the thermal histories (the temperature gradient (G) and the growth rate (R)) variation induced by P and V → and the microstructure distribution is clearly analyzed in the paper. For a Ni-20 at.%Cu alloy, the predicted microstructural distribution is verified experimentally. The parameter space is further divided into homogeneous and heterogeneous regions using the predicted area fraction of cellular–dendritic segregation across the melt pools. The process map is then used to build AM parts with homogeneous microstructures, where only planar microstructure is found experimentally. This methodology will aid in the exploitation of the alloy and processing space to identify alloy-process combinations that yield microstructurally-homogeneous, defect-free parts, provided an unconditionally printable regime can be identified. [Display omitted] [ABSTRACT FROM AUTHOR]

Lightweight Fe–Mn–Al–C steels have become a topic of significant interest for the defense and automotive industries. These alloys can maintain high strength and ductility while also reducing weight in structural applications. Conventionally processed Fe–Mn–Al–C austenitic steels with high Al content (∼9 wt%) demonstrate greater than 1.5 GPa strength with 35% elongation. Several recent studies have demonstrated success in fabricating steel parts using laser powder bed fusion (L-PBF) additive manufacturing (AM), which can generate near-net-shape components with complex geometries and is capable of local microstructural control. However, studies on L-PBF processing of Fe–Mn–Al–C alloys have focused on low Al content (<5 wt%) compositional regimes representing alloys that undergo transformation-induced plasticity (TRIP) and twinning-induced plasticity (TWIP). Here, we present the effects of L-PBF processing on the microstructure and mechanical properties of an Fe–30Mn–9Al–1Si-0.5Mo-0.9C austenitic steel. A process optimization framework is employed to determine an ideal L-PBF processing space that will result in >99% density parts. Implementing this framework resulted in near-fully dense specimens fabricated over a broad range of process parameters. Additionally, two bi-directional scan rotation strategies (90° and 67°) were applied to understand their effects on texture and anisotropy in this material. As-printed specimens displayed considerable work-hardening characteristics with average strengths of up to 1.3 GPa and 36% elongation in the build direction. However, solidification microcracks oriented in the build direction resulted in anisotropy in tensile strength and ductility resulting in average strengths of 1.1 GPa and 20% elongation perpendicular to the build direction. The successful L-PBF fabrication of Fe–30Mn–9Al–1Si-0.5Mo-0.9C presented here is expected to open new avenues for weight reduction in structural applications with a high degree of control over part topology. [ABSTRACT FROM AUTHOR]

This work presents a methodology for predicting a hybrid microstructure and defect processing map for laser powder bed fusion (LPBF) additive manufacturing (AM). A finite element (FE) analysis based thermal model is coupled with a phase field model (PFM) in order to predict both defect formation and microstructure across the LPBF process parameter space. The parameter space is first categorized into defect regions such as keyholing, balling, and lack of fusion. These regions are predicted using the FE thermal model, allowing a defect map to be generated based on the geometries of the melt pools for a defined powder layer thickness. A region of the parameter space that leads to successful AM of defect-free parts is then identified. Segregation across the parameter space is predicted by an integrated computational model, which couples a finite interface dissipation PFM and the aforementioned FE thermal model. The parameter space is then separated into regions that result in cellular or planar microstructures based on the area fraction of cellular-dendritic segregation predicted within the melt pools. By merging the microstructure and defect maps, a hybrid microstructure-defect printability map is generated that distinguishes a process parameter region for fabricating defect-free parts with homogeneous microstructures. This hybrid map is validated with experimental observations for a Ni-5wt.%Nb alloy. The hybrid printability map can be used in the rapid selection and optimization of process parameters for additively manufacturing any alloy (provided models and their parameterization are available, and the alloy is printable), and can potentially help design alloys best suited for AM. [Display omitted] [ABSTRACT FROM AUTHOR]

During laser powder bed fusion (L-PBF) parts undergo multiple rapid heating-cooling cycles, leading to complex microstructures with nonuniform properties. In the present work, a computational framework which weakly couples a finite element thermal model to a non-equilibrium PF model was developed to investigate the rapid solidification microstructure of a Ni–Nb alloy during L-PBF. The framework is utilized to predict the spatial variation of the morphology and size of cellular segregation structures as well as the differences in melt pool microstructures obtained under different process conditions. A solidification map demonstrating the variation of microstructural features as a function of the temperature gradient and growth rate is presented. A planar to cellular transition is predicted in the majority of keyhole mode melt pools, while a planar interface is predominant in conduction mode melt pools. The predicted morphology and size of the cellular segregation structure agree well with experimental measurements. [ABSTRACT FROM AUTHOR]

We propose a methodology for predicting the printability of an alloy, subject to laser powder bed fusion additive manufacturing. Regions in the process space associated with keyhole formation, balling, and lack of fusion are assumed to be strong functions of the geometry of the melt pool, which in turn is calculated for various combinations of laser power and scan speed via a Finite Element thermal model that incorporates a novel vaporization-based transition from surface to volumetric heating upon keyhole formation. Process maps established from the Finite Element simulations agree with experiments for a Ni-5wt.%Nb alloy and an equiatomic CoCrFeMnNi High Entropy Alloy and suggest a strong effect of chemistry on alloy printability. The printability maps resulting from the use of the simpler Eagar-Tsai model, on the other hand, are found to be in disagreement with experiments due to the oversimplification of this approach. Uncertainties in the printability maps were quantified via Monte Carlo sampling of a multivariate Gaussian Processes surrogate model trained on simulation outputs. The printability maps generated with the proposed method can be used in the selection—and potentially the design—of alloys best suited for Additive Manufacturing. Image 1 [ABSTRACT FROM AUTHOR]