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At least 721 records · Page 40

Effects of spatial energy distribution-induced porosity on mechanical properties of laser powder bed fusion 316L stainless steel

Laser powder bed fusion (LPBF) additive manufacturing (AM) offers a variety of advantages over traditional manufacturing, however its usefulness for manufacturing of high-performance components is currently hampered by internal defects (porosity) created during the LPBF process that have an unknown impact on global mechanical performance. By inducing porosity distributions through variations in print energy density and inspecting the resulting tensile samples using computed tomography, nearly 50,000 pores across 75 samples were identified. Porosity characteristics were quantitatively extracted from inspection data and compared with mechanical properties to understand the strength of relationships between porosity and global tensile performance. Useful porosity characteristics were identified for prediction of part performance. Results indicate that ductility and strain at ultimate tensile strength are the global tensile properties most significantly impacted by porosity and can be predicted with reasonable accuracy using simple porosity shape descriptors such as volume, diameter, and surface area. Moreover, it was found that the largest pores influenced behavior most significantly. Specifically, pores in excess of 125 µm in diameter were found to be a sufficient threshold for property estimation. These results establish an initial understanding of the complex defect-performance relationship in AM 316L stainless steel and can be leveraged to develop certification standards and improve confidence in part quality and reliability for the broader set of engineering alloys.

36 MATERIALS SCIENCE↗

Deformation and fracture behavior of a laser powder bed fusion processed stainless steel: In situ synchrotron x-ray computed microtomography study

Tensile plastic deformation and fracture behavior of a laser powder bed fusion processed 316L stainless steel alloy was investigated in situ using high-resolution synchrotron x-ray computed microtomography (sXCT). Three different cases were studied: (1) specimen A1, near full-density with initial porosity of 0.04%, (2) specimen B1, initial lack-of-fusion (LOF) porosity of about 3% with the major axis of defects aligned nearly perpendicular to the tensile loading direction (LD), and (3) specimen B, similar to B1 but with the major axis of LOF defects aligned nearly parallel to LD. The effects of type, density, and orientation of defects in as-printed samples on plastic deformation and failure modes were studied by analyzing sXCT image sequences and quantitative defect properties. Specifically, the evolutions of porosity, size, aspect ratio, and angle of gas pores and LOF defects were characterized as a function of applied strain. Moreover, interactions between as-printed defects and deformation-induced crack propagation were investigated. The tensile behavior of specimen A1 was comparable to that of a commercial wrought plate. Furthermore, the quantitative in-situ sXCT results showed a void-growth phenomenon in A1 but without noticeable coalescence, resulting in a ductile cup-cone failure. Specimen B1 showed damage-driven brittle failure with limited plasticity due to early and rapid propagation of open voids. On the other hand, specimen B, with a similar amount of LOF defects as B1, showed deceivingly strong and ductile tensile behavior similar to A1 without any major crack propagations due to the favorable orientation relationship between LOF defects and the LD.

36 MATERIALS SCIENCE↗

Effect of processing parameters and strut dimensions on the microstructures and hardness of stainless steel 316L lattice-emulating structures made by powder bed fusion

In this study, we present the effects of input processing parameters and strut thickness (in square struts) on microstructure and properties in laser powder bed fusion additively manufactured stainless steel 316L lattice-emulating structures. Lattice-emulating X-structures with square cross-sections of 1.5, 1.0, and 0.5 mm were fabricated using three different parameter sets with varying power, speed, and therefore, linear energy density. Grain size and morphology were shown to be dictated by epitaxial growth, which was dependent on weld pool morphology. Additionally, grain size and morphology were shown to change across the thickness direction of the struts (from the bottom inclined surface to the top inclined surface). The spatial variation in grain size was reflected by changes in hardness through the thickness of each strut. The 0.5 mm struts exhibited more significant grain elongation in the strut direction and larger sub-grain solidification cell diameters than their thicker counterparts. The larger sub-grain solidification cell diameters in the 0.5 mm samples resulted in correspondingly lower hardness values when compared to samples of higher thicknesses.

36 MATERIALS SCIENCE↗

Design of heterogeneous structured Al alloys with wide processing window for laser-powder bed fusion additive manufacturing

Required microstructural attributes of an alloy vary with structural applications. The microstructural fine-tuning capability of laser-powder bed fusion (L-PBF) additive manufacturing (AM) enables application specific manufacture of the components. Such manufacture with L-PBF AM requires alloys that exhibit wide processing window and are amenable to multiple deformation mechanisms. However, high hot cracking susceptibility of Al alloys poses a barrier to such printability-performance synergy. In this work we show that an integration of, a) grain refinement through heterogeneous nucleation, and b) eutectic solidification, leads to crack-free parts at wide range of process parameters, microstructural heterogeneity, and hierarchy in the Al-Ni-Ti-Zr alloy. Such an integration targets hot cracking at multiple stages of solidification in L-PBF as opposed to the contemporary alloy design strategies that target hot-cracking at only specific stages of solidification. The Al-Ni-Ti-Zr alloy exhibits excellent printability and a high as-built tensile performance. Due to the wide processing window and amenability to multiple deformation mechanisms, the alloy microstructure and subsequently the performance, can be fine-tuned. Here, such strategy opens the gateway for application-specific manufacture of Al alloys with L-PBF AM and establishes a fundamental shift in current methodologies for design of these alloys for L-PBF AM.

36 MATERIALS SCIENCE↗

Solidification texture, variant selection, and phase fraction in a spot-melt electron-beam powder bed fusion processed Ti-6Al-4V

The effect of a spot melt strategy on the solidification texture, variant selection, phase fraction, and their variations along the build height was investigated in comparison to a conventional linear melt strategy. Ti-6Al-4V alloy samples were manufactured by an electron-beam powder bed fusion process using two different melt strategies and characterized using high-energy synchrotron x-ray diffraction. The linear and spot melt cases resulted in β<100> cube and fiber textures, respectively, with the cube/fiber axis nearly parallel to the build direction. The α phase exhibited Burgers orientation relationship (BOR) with the parent β phase for both melt strategies. Although all of the key texture components and the BOR between the α and β phases were consistently observed in both cases along the build height, there were several measurable differences between the two. At the top of the build height, the β<100> build texture intensity was stronger in the linear case. However, the texture intensity in the linear case decreased gradually from the top to near the substrate, whereas the spot melt case did not show this trend. Moreover, the BOR was examined along the build height and the results showed that there is a distinct variant selection in the spot melt case, unlike the linear case. Specifically, the planar variants sharing ($\bar101$) β || (0002) α with [$\bar2\bar2\bar2$]β and [$2\bar22$]β were the most prominent in the spot melt, but no preference was identified in the directional variants. The β phase fraction was slightly lower in the spot melt case compared to the linear case. In both the cases, the β phase fraction decreased moving towards the substrate but remained significantly higher than that of the powder feedstock. Overall, the novel spot melt strategy produced a more homogeneous microstructure in terms of both the phase fraction and texture across the build height.

36 MATERIALS SCIENCE↗

A new procedure for implementing the modified inherent strain method with improved accuracy in predicting both residual stress and deformation for laser powder bed fusion

As a metal additive manufacturing (AM) process, laser powder bed fusion (L-PBF) has been widely used to produce parts with complex geometries. The large thermal gradient caused by the fast, intense, and repeated laser scanning induces significant residual deformation and stress to the as-built parts, which increase manufacturing difficulty and geometrical inaccuracy as a result. The modified inherent strain (MIS) method exploiting multiscale process simulations was developed to simulate residual deformation accurately and efficiently. However, the existing procedure of implementing the MIS method is found to give inaccurate residual stress prediction. Here in this work, a new implementation procedure for the MIS method is proposed to improve the simulation accuracy of residual stress without degrading the residual deformation prediction. The new procedure concerns the application of inherent strains to the part-scale layer-by-layer finite element model to obtain residual stress and deformation field. While the existing implementation of the part-scale MIS model involves only mechanical properties at ambient temperature, the new procedure adds one more solution step employing mechanical properties at an elevated temperature determined from the inherent strain extraction step. Both numerical and experimental studies are conducted to validate the proposed new implementation procedure. It shows that by using the new procedure, the MIS-based simulation can predict both residual stress and deformation of as-built L-PBF metal parts with good accuracy.

36 MATERIALS SCIENCE↗

Nanoparticle-enhanced absorptivity of copper during laser powder bed fusion

We report laser powder bed fusion (LPBF) of pure copper for thermal and electrical applications is hampered by its low near-infrared absorptivity and high thermal diffusivity. These material properties make it very difficult to localize the thermal energy needed to produce high density 3D printed parts. Modification of metal powders via nanoparticle additives is a promising approach to increasing absorptivity, but the effect of nanoparticles on absorptivity and melting behavior during LPBF is not well understood. In this study, we developed an in situ calorimetry system to measure effective absorptivity during LPBF on copper substrates. We decorated copper substrates using three nanoparticle systems (CuS, TiB 2 , multilayer graphene flakes) and demonstrated an enhanced absorptivity of the decorated substrates relative to pure copper. Graphene nanoflakes resulted in the highest improved absorption relative to pure copper from 0.09 to 0.48, due to their stability at high laser scanning powers. A thermomechanical model with convective heat transfer provided confidence in the measurements by reproducing the experimental melt pool traces. Full 3D cylindrical prints demonstrated an improvement in relative density of the copper-graphene powder prints (in the range of 0.930–0.992), relative to that of as-purchased copper powder prints (in the range of 0.854–0.972). This work provides a fundamental study of nanoparticle-enabled LPBF of highly reflective metals and demonstrates a viable route for expanding the library of reliably printable metals.

36 MATERIALS SCIENCE↗

Developing ductile and isotropic Ti alloy with tailored composition for laser powder bed fusion

Laser powder bed fusion (LPBF) is an advanced technology to create metallic components with complex geometry. Ti-6Al-4V (Ti64) is one of the most frequently used materials for LPBF. The intrinsic high cooling rates and ultra-high directional thermal gradient of melt, however, lead to a hierarchical structure composed of fine martensitic alpha' within columnar prior-beta grains in LPBF Ti64. This microstructure results in poor ductility and strong mechanical anisotropy in as-built Ti64 components, which largely limit their applications. Here, we report that the above shortcomings can be overcome by tailoring the alloy composition. Specifically, by reducing the aluminum content from 6 wt% to 4 wt%, the resultant LPBF Ti-4Al-4V (Ti44) alloy exhibits substantially improved ductility and mechanical isotropy. These improvements are attributed to grain refinement during solidification and the activation of multiple slip modes and twinning in the as-built material during deformation. This work offers a simple strategy to design new titanium alloys for LPBF with significantly improved ductility and isotropy.

36 MATERIALS SCIENCE↗

Optimization of stochastic feature properties in laser powder bed fusion

Process parameter selection in laser powder bed fusion (LPBF) controls the as-printed dimensional tolerances, pore formation, surface quality and microstructure of printed metallic structures. Measuring the stochastic mechanical performance for a wide range of process parameters is cumbersome both in time and cost. As such, in this study, we overcome these hurdles by using high-throughput tensile (HTT) testing of over 250 dogbone samples to examine process-driven performance of strut-like small features, ~1 mm 2 in austenitic stainless steel (316 L). The output mechanical properties, porosity, surface roughness and dimensional accuracy were mapped across the printable range of laser powers and scan speeds using a continuous wave laser LPBF machine. Tradeoffs between ductility and strength are shown across the process space and their implications are discussed. While volumetric energy density deposited onto a substrate to create a melt-pool can be a useful metric for determining bulk properties, it was not found to directly correlate with output small feature performance.

316 L stainless steel↗

A framework for forming thermoset polymer networks during laser powder bed fusion additive manufacturing

It is commonly reported that the limited availability of material types is a major barrier to widespread adoption for polymer laser powder bed fusion (PBF/L) additive manufacturing (AM). A deeper understanding of the physico-chemical relationships between AM process stimuli and polymer responsive behavior is needed to make data-driven decisions for PBF/L specific material development and formulation. Many researchers have cumulatively built the current state of PBF/L “science-based manufacturing” framework where an initial guess for process parameter values can be determined from measured polymer properties and the first-principles of physics. However, published literature has focused on developing this framework for thermoplastic processing of polymers omitting many specific concerns unique to processing thermosetting materials. The authors consider in the present work the implications of many specific aspects unique to thermosetting polymers during PBF/L manufacturing. These aspects are contextually discussed according to the five sub-functions of PBF/L and are described mathematically where appropriate alongside example data from thermosetting materials commercially available in powder form. Further, this expansion of the prevailing material development framework to include thermosetting polymers paves the way for the unique performance properties offered by that class to be manifest through AM’s geometric freedom.

36 MATERIALS SCIENCE↗

Localized keyhole pore prediction during laser powder bed fusion via multimodal process monitoring and X-ray radiography

Systematic fault detection and control during laser powder bed fusion (L-PBF) has been a long-standing objective for system manufacturers and researchers in the additive manufacturing (AM) industry. This manuscript investigates a data fusion approach for detection of keyhole porosity formation during laser irradiation of Ti-6Al-4V substrates by concurrent recording of thermally induced optical emission measured using both off-axis and coaxial photodiode sensors, and acoustic emission. Subsurface defect formation was monitored via high-speed synchrotron X-ray imaging at 20,000 frames per second, enabling temporal registration of keyhole pore formation events to the monitoring signals at a resolution of 50 µs. We developed data fusion machine learning (ML) models for localized prediction of keyhole pore formation at various time scales ranging from 0.5 ms to 2 ms. The signal segments were featurized using two independent approaches: (1) power spectral density (PSD) and (2) highly comparative time series analysis (HCTSA) framework. The extracted features from different sensor modalities were fused together to construct a multimodal feature space and sequential feature selection was used to determine the most informative features for training the ML models. The predictive performance was evaluated for three classifying algorithms: Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Gaussian Naive Bayes (GNB). As a result, pore formation events were predicted with up to 0.95 F1-score, 1.0 recall and 0.94 accuracy. The most heavily weighted features indicate that model performance is chiefly governed by the acoustic monitoring signal, with a secondary contribution from the optical emission sensors.

36 MATERIALS SCIENCE↗

Hypereutectic Al-Ce-X (X=Mn, Cr, V, Mo, W) alloys fabricated by laser powder-bed fusion

Here, we characterize the microstructures and high-temperature mechanical properties of Al-2Ce and ternary Al-2Ce-1X (at.%) alloys fabricated by laser powder-bed fusion (LPBF), where X = Mn, Cr, V, Mo, and W are slow-diffusing transition metals. All ternary alloys show a hypereutectic microstructure in the as-LPBF state, containing an interconnected network of eutectic Al 11 Ce 3 phases (~10 vol.%) and an additional population of submicron, equiaxed Al 20 CeX 2 primary precipitates (~10 vol.%) which are isomorphous among these five alloys. Similar microstructures are present in arc-melted rods and atomized powders but are coarser due to the slower cooling rates in these processes. The hardness of the as-LPBF ternary Al-Ce-X alloys (1300–1400 MPa) is higher than that of the binary Al-Ce alloy (~1100 MPa) due to the higher volume fraction of strengthening phases. Furthermore, during exposure at 400 °C for up to three months, greater hardness retention is achieved in the ternary Al-Ce-X alloys (65–75%) than in the binary Al-Ce alloy (~55%), which is attributed to the extreme coarsening resistance of the Al 20 CeX 2 precipitates imparted by the very slow-diffusing ternary solute. These coarsening-resistant Al 20 CeX 2 precipitates also substantially improve alloy creep resistance, increasing the threshold stress for dislocation creep at 300°C from ~32 MPa for the binary Al-Ce alloy to ~77–100 MPa for the ternary Al-Ce-X alloys, and at 400°C from <10 MPa for the binary Al-Ce alloy to >40 MPa for the ternary Al-Ce-V alloy.

36 MATERIALS SCIENCE↗

Efficient sensitivity analysis of the thermal profile in powder bed fusion of metals using hypercomplex automatic differentiation finite element method

Rapid cyclic temperature fluctuation occurring in powder bed fusion of metals using a laser beam (PBF-LB/M) influences the formation of flaws in printed parts. Consequently, there is a pressing need to enhance the quality of printed parts by developing innovative methodologies that can predict thermal histories and help uncover the intricate relationships between process parameters and thermal profiles. Sensitivity Analysis (SA) emerges as an essential tool for this, offering the potential for process optimization and enhanced quality control. Nonetheless, conventional SA methodologies often incur in excessive computational costs and potential numerical approximation errors. Here, to address this technical challenge, we present a novel method for SA that integrates the HYPercomplex-based Automatic Differentiation (HYPAD) technique with transient thermal simulations conducted via the finite element method (FEM). Leveraging this methodology, we efficiently and accurately perform SA for PBF-LB/M processes in a post-processing step. Compared to traditional methods like Finite Differences (FD), HYPAD-FEM required 96 % less computational time for obtaining sensitivities for 22 process parameters, under a comparative study conducted within the context of the 2018–02 AM benchmark of the National Institute of Standards and Technology. In summary, HYPAD-FEM offers superior efficiency and accuracy in SA over conventional methods, delivering the best sensitivity of a model without the need for step-size selection and problem or parameter-based implementations.

36 MATERIALS SCIENCE↗

Gas pore correlations in laser powder bed fusion of Al6061

Additive manufacturing (AM) of metal materials based on powder bed fusion technology is widely used now in many industries. A known limitation of this type of manufacturing is the formation of gas pores in the bulk material. Here we present a combined X-ray imaging and mid-infrared pyrometry study of pore formation in side-by-side tracks of Al6061 for different processing conditions using both in-situ and post-processing analysis. By carefully quantifying the distributions and correlations of pore positions, we show that an existing pore in one track often catalyzes the formation of another pore in an adjacent track. In a raster scan strategy commonly used to construct bulk material, this phenomenon has the result of forming subsurface perforations, or lines of pores transverse to the scanning direction in a rastered patch. If controlled, this effect can be eliminated to improve the yield strength of the build, or exploited to create programmable failures for specific purposes.

36 MATERIALS SCIENCE↗

Formation mechanisms of Sn-rich δ phase and its role in strengthening Cu-10Sn manufactured by laser powder bed fusion

Cu-Sn alloys produced via laser powder bed fusion (L-PBF) additive manufacturing (AM) have gained significant attention because they combine the advantages of AM relevant to intricate component design with outstanding combinations of strength, ductility, and resistance to wear and corrosion. However, a detailed understanding of the microstructure that contributes to the enhancement of the mechanical properties of L-PBF Cu-10Sn alloys remains unclear. In particular, there is a lack of understanding of the formation mechanisms of the Sn-rich δ phase commonly observed in Cu-10Sn. This study reveals two distinct variants of the δ phase possessing unique morphological characteristics. These characteristics are attributed to the local solidification conditions inherent to the melt pool boundaries versus those at the interiors of melt pools. A phase transformation pathway that elucidates the origin of the morphological variants of the δ phase from the Sn-rich metastable phases during the cyclic heating of the AM process is proposed. We report superior mechanical properties in L-PBF Cu-10Sn compared to those of conventionally manufactured counterparts due to the synergistic contributions from grain boundaries, dislocations, and the δ phase. Notably, the δ phase alone contributes approximately 22 % to the overall strength observed in the L-PBF Cu-10Sn alloy. The discovery of two types of distinct Sn-rich δ phase offers key insights into precise microstructural control in AM Cu-Sn alloys to enhance mechanical properties, providing practical strategies for improving material performance for diverse applications in automotive, aerospace, and machinery industries.

36 MATERIALS SCIENCE↗

Real-time tracking and analysis of gas bubble dynamics in laser powder bed fusion using in-situ X-ray characterization and machine learning

Porosity defects remain a significant challenge in the laser powder bed fusion (LPBF) process, adversely affecting the mechanical properties and reliability of additively manufactured components. Here, this study investigates the real-time formation and trajectory of gas bubbles during LPBF of Al6061 alloy using advanced in-situ X-ray characterization and machine learning. The unsupervised Gaussian mixture model and particle tracking algorithm developed are able to precisely track and quantify the properties of gas bubbles and keyhole pores. Our analysis identified five distinct types of gas bubble formation and movement patterns, emphasizing the diverse origins and behaviors of these defects. It enables precise quantification of trajectories, velocities, and morphological changes of gas bubbles, offering a granular view of the subsurface dynamics within the melt pool. Additionally, we explored keyhole-induced pore dynamics, revealing the critical role of keyhole oscillation and collapse for the formation of both large and small gas pores. It defines four different regions of gas bubble movement within the melt pool, providing a clearer understanding of how local fluid dynamics affect pore behavior. The results underscore the importance of integrating in-situ experimental observation and automated machine learning to develop a more robust predictive model for defect formation in LPBF.

In-situ X-ray imaging↗

Discrete element simulation of Pebble Bed Reactors on graphics processing units

Prediction of pebble positions in a Pebble Bed Reactor (PBR) is necessary for both reactor physics and thermal hydraulics simulations as the arrangement of pebbles has a significant impact on the resulting core power, coolant flow, and fuel temperature. Knowledge of pebble movement as the fuel is cycled through the core is also critical for predicting the fuel residence time and subsequently, the fuel burnup. Simulation with the Discrete Element Method (DEM) can provide knowledge of both the fuel packing and the fuel movement during cycling. Previous works that have performed 3D full-core DEM simulation of PBRs have used simplified models that neglect reflector wall features. This work employs a graphics processing unit (GPU)-enabled DEM code, Project Chrono, to analyze the differences in pebble packing and pebble velocities between a simplified smooth PBR reflector and a more realistic reflector that includes circular wall features. Additionally, a sensitivity study is performed on the depth of the wall features to ensure that crystallization is prevented. Project Chrono is also validated for PBR cycling applications using experimental data. It is found that wall features with a depth of at least 0.5 pebble diameters significantly reduce crystallization in the near-wall region, leading to discrepancies in both packing fraction and pebble velocity in this region compared to the simplified reflector models. These discrepancies are found to lead to roughly a 5–10% difference in the prediction of the near-wall porosity and a 10% difference in the prediction of the velocity of pebbles near the wall. As a result of these discrepancies, it is suggested that future DEM simulations of PBRs include wall features to reduce modeling errors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

High-fidelity simulations of the run-in process for a pebble-bed reactor

Pebble-bed reactors (PBRs) rely on a continual feed of fuel pebbles being cycled through the core. As a result, they require a “run-in” period in order to reach an equilibrium state. The run-in period for a PBR is a complex, time-dependent problem that requires the injection of new fuel, different types of fuel, and power increases. This complexity in the run-in makes it important to capture the physical processes in order to generate an accurate representation. The present work details the creation of a high-fidelity Monte Carlo methodology for analyzing the run-in and subsequent approach to equilibrium for PBRs. The methodology entails a Python module wrapped around Serpent so as to perform neutronics calculations, move pebbles, refuel the core, and discharge pebbles, thereby modeling the explicit behavior of the PBR run-in. Further, three run-in simulations (a constant temperature profile, a linear temperature profile, and a constant temperature profile using control rods) were examined in order to identify the key physical phenomena present in the run-in process. Utilizing kugelpy, we found the inclusion of a temperature profile to be important for accurately capturing a discharge burnup (around 141 MWd/kg), a consistent k-eff (around 1.005), and an average pebble power (around 2.5 kW/pebble) that all fall within acceptable limits.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗