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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

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↗
DOE OSTI2021

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↗
DOE OSTI2022

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↗
DOE OSTI2022

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↗
DOE OSTI2023

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↗
DOE OSTI2024

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↗
DOE OSTI2024

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↗
DOE OSTI2025

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↗
DOE OSTI2025

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↗
DOE OSTI2020

Towards improved speed and accuracy of laser powder bed fusion simulations via multiscale spatial representations

Due to the growing popularity of laser powder bed fusion (LPBF) as a metal additive manufacturing technique, there is a strong need to be able to accurately predict build outcomes. Full fidelity simulations of this process are not feasible due to the vast range of length and time scales inherent to it. While part-scale codes for simulating residual stress and distortion have shown reasonable predictive capability, they often neglect many aspects of the process occurring over smaller length/time scales, and thus are unable to capture effects of process parameter adjustments or the behavior of fine features. One way of capturing aspects at more refined length scales is through the use of adaptive mesh refinement (AMR). AMR allows for the process to be simulated at scales approaching the physical spatial dimensions without drastically increasing the total degrees of freedom in the simulation. This manuscript describes the implementation of an AMR algorithm within a multiphysics, parallelized finite element code, and its application to the LPBF problem. In this work, part-scale examples are provided where the use of AMR has allowed for higher fidelity thermal and thermomechanical simulations, as compared to experimental measurements. Results from these higher resolution simulations show that while AMR is a necessary component for increased accuracy in a computationally efficient manner, other improvements are also necessary, including handling of the multiple time scales inherent to the problem and the need for improved AM-specific material models.

42 ENGINEERING↗
DOE OSTI2022

Predictive process mapping for laser powder bed fusion: A review of existing analytical solutions

One of the main challenges in the laser powder bed fusion (LPBF) process is making dense and defect-free components. These porosity defects are dependent upon the melt pool geometry and the processing conditions. Power-velocity (PV) processing maps can aid in visualizing the effects of LPBF processing variables and mapping different defect regimes such as lack-of-fusion, under-melting, balling, and keyholing. This work presents an assessment of existing analytical equations and models that provide an estimate of the melt pool geometry as a function of material properties. The melt pool equations are then combined with defect criteria to provide a quick approximation of the PV processing maps for a variety of materials. Finally, the predictions of these processing maps are compared with experimental data from the literature. Here, the predictive processing maps can be computed quickly and can be coupled with dimensionless numbers and high-throughput (HT) experiments for validation. The present work provides a boundary framework for designing the optimal processing parameters for new metals and alloys based on existing analytical solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Extreme variation in fatigue: Fatigue life prediction and dependence on build volume location in laser powder bed fusion of 17-4 stainless steel

Laser powder bed fusion (LPBF), a metal additive manufacturing technology, is well-suited for design optimization but fatigue life is limited by manufacturing defects. In this work, 17-4 stainless steel components were manufactured in densely populated build volumes, simulating at-scale LPBF production. Tests revealed extreme variability in fatigue life data, analyzed via rigorous statistical tools. The El-Haddad model, modified for finite-life, enabled defect-based life prediction. Specimen location within the build volume correlated to life, which was heteroscedastic. Investigating defect concentration over the build volume explained typical life and scatter. Finally, these findings argue for qualification approaches which acknowledge high material lot variability.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Microstructural effects on the rotating bending fatigue behavior of Ti–6Al–4V produced via laser powder bed fusion with novel heat treatments

The rotating bending fatigue (RBF) behavior (fully reversed, R = -1) of additively manufactured (AM) Ti–6Al–4V alloy produced via laser powder bed fusion (PBF-L) was investigated with respect to different microstructures achieved through novel heat treatments. The investigation herein seeks to elucidate the effect of microstructure by controlling variables that can affect fatigue behavior in Ti–6Al–4V, such as chemistry, porosity, and surface roughness. In order to control these variables, different hot isostatic pressing (HIP) treatments at 800 °C, 920 °C, and 1050 °C with a 920 °C temper were applied to three sets of Ti–6Al–4V cylinders that originated from the same PBF-L build, such that there were 30 tests per condition. After HIP treatment, the specimens were machined and tested. The highest runout stress was achieved after sub-β transus HIP at 800 °C for 2 h at 200 MPa of pressure. A significant drop in fatigue strength was attributed to large prior-β grains and grain boundary α resulting from super-β transus HIP treated specimens. In conclusion, for the sub-β transus HIP specimens, differences in fatigue strength were attributed to α lath thickness, relative dislocation density, and dislocation boundary strengthening.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Very high cycle fatigue characteristics of laser beam powder bed fused AlSi10Mg: A systematic evaluation of part geometry

This study explores the influence of geometry and part size on defect distribution, melt pool size, and mechanical characteristics in laser beam powder bed fused (LB-PBF) AlSi10Mg. Five distinct geometries—hourglass, small rod, small block, large block, and large rod—were fabricated under identical process parameters. Fully reversed ultrasonic fatigue testing, operating at a frequency of 20 kHz, was conducted to assess the very high cycle fatigue properties. The findings indicated that part geometry had a major impact on the fatigue properties of the material in the very high cycle fatigue regime. Specimens machined from large rods and large blocks had the lowest porosity and highest fatigue resistance. Microstructural analysis indicated that hourglass, small rod, and small block specimens had shallower melt pools and overlap depths compared to other geometries. This observation suggests a higher cooling rate in specimens with smaller cross-sectional areas, leading to the increased presence of entrapped gas pores and a lack of fusion defects. Understanding the relationship between part geometry and fatigue properties in LB-PBF components offers insights for optimizing design and manufacturing processes in additive manufacturing applications.

AlSi10Mg↗
DOE OSTI2025

Simulated effect of defect volume and location on very high cycle fatigue of laser beam powder bed fused AlSi10Mg

This study quantifies the interaction between volumetric defect location and size on the very high cycle fatigue (VHCF) of laser beam powder bed fused (LB-PBF) AlSi10Mg. Crystal plasticity finite element method (CPFEM) simulations were used to investigate the effects of defect location and size on the driving force for crack initiation. The CPFEM model was calibrated against uniaxial and cyclic experimental data of LB-PBF AlSi10Mg. Defect characteristics were informed by experimental data from the specimens produced in various geometries to create realistic representative volume elements (RVEs) with equivalent volume fractions of defects. By embedding defects of varying sizes and locations within the RVEs, fatigue indicator parameters (FIPs) were calculated to analyze the impact of defects’ characteristics on fatigue performance. Different combinations of defect volume and locations were generated for various microstructure instantiations, providing insight into extreme value fatigue responses. Larger defect volumes located on free surfaces consistently generated the highest FIPs, suggesting defect size and boundary proximity intensify stress concentration effects. RVEs with multiple smaller defects produced lower FIPs than those with single large critical defects. These findings underscore the critical role of defect characteristics on fatigue life, providing a foundation for future predictive modeling in fatigue-sensitive AM applications.

AlSi10Mg↗
DOE OSTI2022

Melt pool temperature measurement and monitoring during laser powder bed fusion based additive manufacturing via single-camera two-wavelength imaging pyrometry (STWIP)

Melt pool (MP) temperature is one of the determining factors and a key signature for evaluating the properties of printed components in metal additive manufacturing (AM). The state-of-the-art measurement systems are hindered, primarily by the large-scale data acquisition and processing demands. In this work, we introduce a novel coaxial, high-speed, single-camera two-wavelength imaging pyrometer (STWIP) system as opposed to the typical utilization of multiple cameras for measuring MP temperature profiles in laser powder bed fusion (LPBF) processes. Developed on a commercial LPBF machine (EOS M290), the STWIP system demonstrated its ability to quantitatively monitor the MP temperature and its variation for 50 layers at high framerates (>30,000 fps) for a real-world application (standard fatigue specimens) print. High performance computing is employed to analyze the acquired big data (MP images), for determining each MP's average temperature and 2D temperature profile. The MP temperature evolution in the gage section of a fatigue specimen is also examined at a temporal resolution of 1 ms, by evaluating the MP temperatures in the samples' first, middle, and last layers. This report is the first of its kind on monitoring MP temperature distribution and evolution at such a large, detailed scale for longer durations in practical applications.

42 ENGINEERING↗
DOE OSTI2023

Data-driven prediction of geometry- and toolpath sequence-dependent intra-layer process conditions variations in laser powder bed fusion

Geometrical features and toolpath sequence are two important factors that cause process condition variations, such as variations in the meltpool temperature or meltpool size, that might lead to undesired material properties in the laser powder bed fusion (LPBF) process. Due to the high dynamics and complex physics of the LPBF process, it is difficult to predict variations in process conditions with simulations alone. Advances in measurement technology and computational technologies open up new possibilities for smart manufacturing. In this paper, a data-driven method to predict intra-layer variations in the processing conditions that source from the toolpath sequence and part geometry is presented. The approach is demonstrated using two-color on-axis pyrometer measurements. Three demonstration cases are presented in which it is demonstrated (1) how the trained predictive model can be used as a filter to ease the interpretation of process variations and discover patterns related to toolpath and part geometry, and (2) how to generate predictions that can be used for feedforward control, i.e., for adjusting laser power or scanning speed along the toolpath using a meltpool temperature prediction model generated based on on-axis measurements. Results show that the developed prediction model is able to meaningfully predict process variations resulted from toolpath sequence and geometry. Predictions are aligned with the results from the related work of others and for the case of 180° laser path turnarounds in our high-speed X-ray imaging experiments. In conclusion, the potential issues related to the current maturity status of the process and measuring equipment that could in practice affect the performance of the proposed solutions are also discussed.

42 ENGINEERING↗
DOE OSTI2025

Impact of lead on an axisymmetric, single bead blown powder DED overhung geometry

Metal additive manufacturing can be utilized for the near net-shape manufacture of components in a layer wise technique. Traditionally, the buildup process is conducted in the direction of gravity or bottom to top in the vertical orientation; however, with the availability of commercial systems with additive heads or fixturing that can index from vertical, and the need to manufacture larger parts without modifying available systems, the limitation of manufacturing from bottom to top is removed enabling the buildup of larger components printed at an angle from vertical. The effect of gravity on the melt pool and as-deposited component quality when printing off vertical is unknown in literature, especially for axisymmetric components. This understanding is critical for the advancement of manufacturing components of increased size in 4 and 5-axis additive systems. This investigation utilizes blown powder directed energy deposition to evaluate the change in as-printed geometry when the start point is altered in relation to gravity while the part rotates to manufacture an axisymmetric component. The objectives of this work are to determine the impact of the deposition location on the geometric variability on axisymmetric components. This investigation tests the hypothesis that differences in layer height exist due to a change in catchment efficiency when the deposition location is moved to a tangent of the round geometry due to a change in the melt pool dynamics. It was found the ideal deposition location when printing at 26.6-degrees from vertical was at −90-degrees from the top center point of the component, along the tangent, where gravity was pushing the melt pool down, but the rotation of the part was pulling the deposited material towards the top center of the component. This work provides an understanding of layer height stability and catchment efficiency to guide print orientation strategy for high-aspect ratio components. It was found the −90-degree lead deposition had the best layer height stability at 0.6 % as compared to the top-center at 6.3 % and +90-degree deposition location at 9.2 % for the nominal programmed layer height. The change in layer height also effected the final diameter the greatest for the top center deposition location where the diameter diverged by 2.5 % during the overbuild condition and converged by 0.6 %. In conclusion, this finding will increase the manufacturing efficiency of axisymmetric components by increasing the passive stability of the printing process for the successful manufacture of parts without the need for perfectly calibrated manufacturing parameters.

36 MATERIALS SCIENCE↗