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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

In Situ X-ray Radiography and Computational Modeling to Predict Grain Morphology in $\beta$-Titanium during Simulated Additive Manufacturing

The continued development of metal additive manufacturing (AM) has expanded the engineering metallic alloys for which these processes may be applied, including beta-titanium alloys with desirable strength-to-density ratios. To understand the response of beta-titanium alloys to AM processing, solidification and microstructure evolution needs to be investigated. In particular, thermal gradients (Gs) and solidification velocities (Vs) experienced during AM are needed to link processing to microstructure development, including the columnar-to-equiaxed transition (CET). In this work, in situ synchrotron X-ray radiography of the beta-titanium alloy Ti-10V-2Fe-3Al (wt.%) (Ti-1023) during simulated laser-powder bed fusion (L-PBF) was performed at the Advanced Photon Source at Argonne National Laboratory, allowing for direct determination of Vs. Two different computational modeling tools, SYSWELD and FLOW-3D, were utilized to investigate the solidification conditions of spot and raster melt scenarios. The predicted Vs obtained from both pieces of computational software exhibited good agreement with those obtained from in situ synchrotron X-ray radiography measurements. The model that accounted for fluid flow also showed the ability to predict trends unobservable in the in situ synchrotron X-ray radiography, but are known to occur during rapid solidification. A CET model for Ti-1023 was also developed using the Kurz–Giovanola–Trivedi model, which allowed modeled Gs and Vs to be compared in the context of predicted grain morphologies. Both pieces of software were in agreement for morphology predictions of spot-melts, but drastically differed for raster predictions. The discrepancy is attributable to the difference in accounting for fluid flow, resulting in magnitude-different values of Gs for similar Vs.

36 MATERIALS SCIENCE↗
NASA NTRS2014

Additive Manufacturing Infrared Inspection

Additive manufacturing is a rapid prototyping technology that allows parts to be built in a series of thin layers from plastic, ceramics, and metallics. Metallic additive manufacturing is an emerging form of rapid prototyping that allows complex structures to be built using various metallic powders. Significant time and cost savings have also been observed using the metallic additive manufacturing compared with traditional techniques. Development of the metallic additive manufacturing technology has advanced significantly over the last decade, although many of the techniques to inspect parts made from these processes have not advanced significantly or have limitations. Several external geometry inspection techniques exist such as Coordinate Measurement Machines (CMM), Laser Scanners, Structured Light Scanning Systems, or even traditional calipers and gages. All of the aforementioned techniques are limited to external geometry and contours or must use a contact probe to inspect limited internal dimensions. This presentation will document the development of a process for real-time dimensional inspection technique and digital quality record of the additive manufacturing process using Infrared camera imaging and processing techniques.

Gaddy, Darrell↗
DOE OSTI2020

Mitigating Scatter in Mechanical Properties in AISI 410 Fabricated via Arc-Based Additive Manufacturing Process

Wire-based metal additive manufacturing utilizes the ability of additive manufacturing to fabricate complex geometries with high deposition rates (above 7 kg/h), thus finding applications in the fabrication of large-scale components, such as stamping dies. Traditionally, the workhorse materials for stamping dies have been martensitic steels. However, the complex thermal gyrations induced during additive manufacturing can cause the evolution of an inhomogeneous microstructure, which leads to a significant scatter in the mechanical properties, especially the toughness. Therefore, to understand these phenomena, arc-based additive AISI 410 samples were fabricated using robotic gas metal arc welding (GMAW) and were subjected to a detailed characterization campaign. The results show significant scatter in the tensile properties as well as Charpy V-notch impact toughness data, which was then correlated to the microstructural heterogeneity and delta (δ) ferrite formation. Post-processing (austenitizing and tempering) treatments were developed and an ~70% reduction in the scatter of tensile data and a four-times improvement in the toughness were obtained. The changes in mechanical properties were rationalized based on the microstructure evolution during additive manufacturing. Based on these, an outline to tailor the composition of “printable” steels for tooling with isotropic and uniform mechanical properties is presented and discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Assessment of Additive Manufacturing of Particle Accelerator [Slides]

Metal additive manufacturing of copper components has been commercialized on multiple printing modalities; including Bound Metal Deposition (BMD), Laser Powder Bed Fusion (LPBF), and Electron Beam Melting (EBM). BMD was selected at the primary printing modality for this TED because of the availability of the Markforged Metal X machine within the LANL E-2 AM research lab. Linear accelerator (LINAC) structures are similarly demonstrated technology. Accelerator structures are typically made of high purity oxygen-free electronic copper owing to the material’s high electrical and thermal conductivity. Conventionally machined and brazed, welded, or bolted designs are difficult to manufacture and require long lead times.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Analysis of Pitting Corrosion on Wrought and Additively Manufactured 316L Stainless Steel in Atmospheric Environments

Additive manufacturing of metal components enables rapid fabrication of complex geometries. However, metal additive manufacturing also introduces new morphological and microstructural characteristics which might be detrimental to component performance. Here we report the pitting corrosion properties of wrought and additively manufactured 316L stainless steel after atmospheric exposure to coastal environments and laboratory-created environments. Qualitative visualization in combination with quantitative analysis of resulting pits provided an in-depth understanding of pitting differences between wrought and additively manufactured 316L stainless steel and between coastal and laboratory-based exposure. Optical and scanning electron microscopy were utilized for visualization, while white light interferometry measured pits across approximately 5mm x 5mm areas on each sample. Post-processing of the interferometry data enables quantification of pitting attack for each sample in terms of both pit depth and pit volume. The pitting analysis introduced herein offers a new technique to compare pitting attack between different manufacturing processes and materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

High absorptivity nanotextured powders for additive manufacturing

The widespread application of metal additive manufacturing (AM) is limited by the ability to control the complex interactions between the energy source and the feedstock material. Here, we develop a generalizable process to introduce nanoscale grooves to the surface of metal powders which increases the powder absorptivity by up to 70% during laser powder bed fusion. Absorptivity enhancements in copper, copper-silver, and tungsten enable energy-efficient manufacturing, with printing of pure copper at relative densities up to 92% using laser energy densities as low as 83 joules per cubic millimeter. Simulations show that the enhanced powder absorptivity results from plasmon-enabled light concentration in nanoscale grooves combined with multiple scattering events. The approach taken here demonstrates a general method to enhance the absorptivity and printability of reflective and refractory metal powders by changing the surface morphology of the feedstock without altering its composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A scalable framework for efficient coupling of thermal and microstructural simulations in additive manufacturing

Predicting microstructure evolution in metal additive manufacturing (AM) is important for process optimization, but spatiotemporal scale disparities between thermal transport and microstructure evolution create significant challenges for efficient data transfer between simulation codes. To address this, we present Stork, a scalable framework for coupling thermal and microstructural simulations. Stork uses a sparse data representation to identify and store active solidification sub-volumes, enabling highly parallel quad-linear interpolation from coarse thermal grids to fine microstructure grids without large intermediate storage. We demonstrate the framework by coupling the semi-analytic heat transfer code 3DThesis with the time-parallel cellular automata code Toucan. This approach achieves over two orders of magnitude reduction in data generation time and file size compared to prior workflows. Numerical studies show that quad-linear interpolation preserves grain morphology and crystallographic texture in laser powder bed fusion (LPBF) simulations for coarsening ratios up to 16. Overall, Stork provides a scalable pathway for high-throughput, component-scale AM simulations on modern high-performance computing systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Flow in additively manufactured super-rough channels

Metal additive manufacturing has enabled geometrically complex internal cooling channels for turbine and heat exchanger applications, but the process gives rise to large-scale roughness whose size is comparable to the channel height (which is 500 $\mathrm {\mu }$ m). These super-rough channels pose previously unseen challenges for experimental measurements, data interpretation and roughness modelling. First, it is not clear if measurements at a particular streamwise and spanwise location still provide accurate representation of the mean (time- and plane-averaged) flow. Second, we do not know if the logarithmic layer survives. Third, it is unknown how well previously developed rough-wall models work for these large-scale roughnesses. To answer the above practical questions, we conduct direct numerical simulations of flow in additively manufactured super-rough channels. Three rough surfaces are considered, all of which are obtained from computed tomography scans of additively manufactured surfaces. The roughness’ trough to peak sizes are 0.1 $h$ , 0.3 $h$ and 0.8 $h$ , respectively, where $h$ is the intended half-channel height. Each rough surface is placed opposite a smooth wall and the other two rough surfaces, leading to six rough-wall channel configurations. Two Reynolds numbers are considered, namely $Re_\tau =180$ and $Re_\tau =395$ . We show first that measurements at one streamwise and spanwise location are insufficient due to strong mean flow inhomogeneity across the entire channel, second that the logarithmic law of the wall survives despite the mean flow inhomogeneity and third that the established roughness sheltering model remains accurate.

Altland, Samuel↗
DOE OSTI2025

Feature Based Qualification of 17-4PH Stainless Steel to Evaluate Location-Specific Variability in Wire Arc Additive Manufacturing

Qualifying large-scale metal additive manufacturing (M-AM) technologies such as wire arc additive manufacturing (WAAM) can be challenging. This is especially significant in precipitation hardened martensitic stainless steels like SS 17-4PH, where thermal histories induce location-specific microstructural variability and property anisotropy. The Department of Defense (DOD) and the United States Army Combat Capabilities Development Command Ground Vehicle Systems Center (GVSC) Ground Vehicle Materials Engineering (GVME) aim to build robust and qualified large-scale M-AM workflows that could reduce the time and cost through quick and informed evaluation, testing, and development of feedstock, processes, and parts. The report presents the findings from the collaborative efforts between Oak Ridge National Laboratory (ORNL) and the U.S. Army GVSC GVME. The aim of this project was to develop a geometric feature-based qualification framework for WAAM of SS 17-4PH components. This report outlines selection methodology of representative build geometries, optimization of WAAM process parameters, in-situ monitoring, microstructure-property evaluation, thermal simulations, as well as data visualization techniques incorporated in this project. The results from this project demonstrate a clear understanding of thermal history dependent phase evolution and consequent location-specific property variations in WAAM of SS 17-4PH. These results in conjunction with the data-driven methodologies used in this project are expected to reduce qualification timelines, improve predictability, and accelerate the development of reliable feature-based qualification strategies for part production via large-scale M-AM technologies.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Additive Manufacturing for Rocket Propulsion Applications

Metal Additive manufacturing (AM) is changing how components are being fabricated for current and next generation spaceflights. AM provides many advantages including cost and schedule reduction, enhanced complexity for light-weighting, consolidation of parts, and improved performance using novel alloys and improved designs. This presentation will highlight some of the use cases of AM in rocket propulsion applications, the various processes and attributes for proper selection, and the integrated lifecycle for proper AM use. As AM evolves, there is a need to better understand these lifecycle design constraints such as geometry, microstructure and resulting properties, and surface texture for proper implementation. Ongoing research is being conducted on integral channel heat exchangers, such as combustion chambers and nozzles, using some of the AM processes. The presentation will conclude with a focus on this AM heat exchanger research and how it may be applied for future spaceflight.

Additive Manufacturing↗
DOE OSTI2022

Schmid factor crack propagation and tracking crystallographic texture markers of microstructural condition in direct energy deposition additive manufacturing of Ti-6Al-4V

Metallic additive manufacturing (AM) provides a customizable and tailorable manufacturing process for new engineering designs and technologies. The greatest challenge currently facing metallic AM is maintaining control of microstructural evolution during solidification and any solid state phase transformations during the build process. Ti-6Al-4V has been extensively surveyed in this regard, with the potential solid state and solidification microstructures explored at length. In this study, we evaluate the applicability of previously determined crystallo- graphic markers of microstructural condition observed in electron beam melting powder bed fusion (PBF-EB) builds of Ti-6Al-4V in a directed energy deposition (DED) build process. The aim of this effort is to elucidate whether or not these specific crystallographic textures are useful tools for indicating microstructural conditions in AM variants beyond PBF-EB. Parent β-Ti grain size was determined to be directly related to α-Ti textures in the DED build process, and the solid state microstructural condition could be inferred from the intensity of specific α-Ti orientations. Qualitative trends on the as-solidified β-Ti grain size were also determined to be related to the presence of a fiber texture, and proposed as a marker for as-solidified grain size in any cubic metal melted by AM. Analysis of the DED Ti-6Al-4V build also demonstrated a near complete fracture of the build volume, suspected to originate from accumulated thermal stresses in the solid state. Crack propagation was found to only appreciably occur in regions of slow cooling with large α +β colonies. Schmid factors for the basal and prismatic α-Ti systems explained the observed crack pathway, including slower bifurcation in colonies with lower Schmid factors of both slip systems. Colony morphologies and localized equiaxed β-Ti solidification were also found to originate from build pauses during production and uneven heating of the build edges during deposition. Tailoring of DED Ti-6Al-4V microstructures with the insight gained here is proposed, along with cautionary insight on preventing unplanned build pauses to maintain an informed and controlled thermal environment for microstructural control.

36 MATERIALS SCIENCE↗
DOE OSTI2022

In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learning

Abstract In droplet-on-demand liquid metal jetting (DoD-LMJ) additive manufacturing, complex physical interactions govern the droplet characteristics, such as size, velocity, and shape. These droplet characteristics, in turn, determine the functional quality of the printed parts. Hence, to ensure repeatable and reliable part quality it is necessary to monitor and control the droplet characteristics. Existing approaches for in-situ monitoring of droplet behavior in DoD-LMJ rely on high-speed imaging sensors. The resulting high volume of droplet images acquired is computationally demanding to analyze and hinders real-time control of the process. To overcome this challenge, the objective of this work is to use time series data acquired from an in-process millimeter-wave sensor for predicting the size, velocity, and shape characteristics of droplets in DoD-LMJ process. As opposed to high-speed imaging, this sensor produces data-efficient time series signatures that allows rapid, real-time process monitoring. We devise machine learning models that use the millimeter-wave sensor data to predict the droplet characteristics. Specifically, we developed multilayer perceptron-based non-linear autoregressive models to predict the size and velocity of droplets. Likewise, a supervised machine learning model was trained to classify the droplet shape using the frequency spectrum information contained in the millimeter-wave sensor signatures. High-speed imaging data served as ground truth for model training and validation. These models captured the droplet characteristics with a statistical fidelity exceeding 90%, and vastly outperformed conventional statistical modeling approaches. Thus, this work achieves a practically viable sensing approach for real-time quality monitoring of the DoD-LMJ process, in lieu of the existing data-intensive image-based techniques.

Gaikwad, Aniruddha (ORCID:0000000285642621)↗
DOE OSTI2021

Electron Beam Powder Bed Fusion Additive Manufacturing of Refractory Metals

The processing of refractory metals via additive manufacturing (AM) presents an opportunity to fabricatecomponents not possible through traditional powder metallurgy techniques. However, processing via AM isextremely challenging and there exist a host of technological limitations still unaddressed. Molybdenumand tungsten are two materials of particular interest for nuclear energy generation applications. Themajority of existing work on the processing of these materials is focused on laser powder bed fusion whereasa smaller body of work exists for electron beam melting AM. In general, material with acceptable densitycan be obtained via both routes however cracking is much more difficult to mitigate against. Strongcrystallographic fiber textures have been observed across a range of refractory systems. In this work wepresent our recent findings on electron beam melting AM of pure tungsten and molybdenum. Wedemonstrate that defect-free material can be obtained in both systems with appropriate processing. Strongbuild direction crystallographic texture fibers are observed in both systems. In molybdenum the fibertexture has direct impact on the resulting tensile behavior. These results demonstrate that electron beamAM is a suitable technology for processing these difficult to fabricate materials.

Fernandez-Zelaia, Patxi↗
NASA NTRS2016

Photon Doppler Velocimeter to Measure Entrained Additive Manufactured Bulk Metal Powders in Hot Subsonic and Supersonic Oxygen Gas

Parts produced by additive manufacturing, particularly selective laser melting (SLM), have been shown to silt metal particulate even after undergoing stringent precision aerospace cleaning processes (Lowrey 2016). As printed parts are used in oxygen systems with increased pressures, temperatures, and gas velocity, the risk of ignition by particle impact, the most common direct ignition source of metals in oxygen, substantially increases. The White Sands Test Facility (WSTF), in collaboration with Marshall Space Flight Center (MSFC), desires to test the ignitability of SLM metals by particle impact in heated oxygen. The existing test systems rely on gas velocity calculations to infer particle velocity in both subsonic and supersonic particle impact systems. Until now, it was not possible to directly measure particle velocity. To increase the fidelity of planned SLM ignition studies, it is necessary to validate that the Photon Doppler Velocimetry(PDV) test system can accurately measure particle velocity.

Tylka, Jonathan↗
DOE OSTI2020

In Situ Analysis of Laser Powder Bed Fusion Using Simultaneous High-Speed Infrared and X-ray Imaging

Laser powder bed fusion is a metal additive manufacturing technique that has received significant scientific and industrial attention over the past decades. However, the quality and reproducibility of parts manufactured by this technique is still a problem. Overcoming this issue requires an understanding of multiple complex physical phenomena which occur simultaneously during the process. Here, we illustrate a powerful new technique which synchronizes high-speed x-ray imaging with high-speed infrared imaging to study laser powder bed fusion processes in real time. Using this technique, we demonstrate the simultaneous observation of multiple phenomena including three-dimensional melt pool visualization, vapor plume dynamics, spatter formation, thermal history, and point cooling rates. The paired observation of these dynamic phenomena is critical to understanding the fundamentals of laser powder bed fusion, and the overall impact of process parameters on print quality.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Dendritic deformation modes in additive manufacturing revealed by operando x-ray diffraction

Abstract Dynamic solidification behavior during metal additive manufacturing directly influences the as-built microstructure, defects, and mechanical properties of printed parts. How the formation of these features is driven by temperature variation (e.g., thermal gradient magnitude and solidification front velocity) has been studied extensively in metal additive manufacturing, with synchrotron x-ray imaging becoming a critical tool to monitor these processes. Here, we extend these efforts to monitoring full thermomechanical deformation during solidification through the use of operando x-ray diffraction during laser melting. With operando diffraction, we analyze thermomechanical deformation modes such as torsion, bending, fragmentation, assimilation, oscillation, and interdendritic growth. Understanding such phenomena can aid the optimization of printing strategies to obtain specific microstructural features, including localized misorientations, dislocation substructure, and grain boundary character. The interpretation of operando diffraction results is supported by post-mortem electron backscatter diffraction analyses.

Dass, Adrita (ORCID:000000019100635X)↗
DOE OSTI2025

Electromagnetic Modeling of Lattice Structures in Additively Manufactured Electric Machines

Recent advancements in metal additive manufacturing (AM) show great potential to revolutionize the design and manufacturing of electromagnetic components used in the field of electrical engineering. Lattice structures directly printed by AM processes typically offer better structural performance with reduced weight, such as high stiffness, surface area, elongation, energy absorption, and porosity, than the solid counterpart. This paper aims to study the electromagnetic modeling of lattice structures used in additively manufactured magnetic cores or windings for electric machines. Three dimensional (3D) electromagnetic finite element (FE) analysis with high performance computing (HPC) shows the highest fidelity in predicting the electromagnetic performance of designs with lattice structures by preserving complex geometry details. FE-based homogenization methods have also been explored to potentially speed up concept design. A case study based on an additively manufactured axial-flux permanent magnet machine with a Hilbert pattern stator validates the discussed electromagnetic modeling approaches.

Chung, Shi-Uk [ANSYS, Inc.]↗
NASA NTRSDate not supplied

Three-Dimensional Reconstruction of Defects and Structures in Additively Manufactured Parts with Automated Serial Sectioning

Metal additive manufacturing (AM) processes have been demonstrated to be effective at reducing costs and lead times associated with complex components for space flight applications. Laser powderbed fusion (L-PBF) is a commonly used AM technology due to the ability to produce complex parts with fine feature resolution in a wide variety of alloys and applications. L-PBF, like many other manufacturing processes, can produce minor flaws in parts when in nominal operation as well as process-escape defects when process abnormalities occur. The effects of the flaws and methods of detecting the flaws are a subject of interest to understand the difficulties in detecting these flaws with current technology and how much risk the flaws or defects pose to potential flight parts. Using a RoboMet.3D automated serial sectioning system, seeded defects as well as minor process flaws can be imaged and reconstructed in three dimensions to compare to non-destructive evaluation (NDE) techniques, such as x-ray computed tomography (CT), neutron CT, and in-situ monitoring. The RoboMet automates the metallography process by automatically grinding, polishing, and imaging samples in a single system and providing the control data for NDE comparisons to know the real size of defects built into coupons. These comparisons provide an understanding behind the technological limitations of the NDE techniques for different alloys. The same serial sectioning methods have also been utilized to characterize the surfaces of parts to reconstruct the surfaces and take measurements of internal features not easily examined with non-destructive methods. Using the RoboMet, fine lattice structures built with L-PBF have been characterized to determine the actual thicknesses of struts and density of the lattice structures. These structures have been used as finer build supports for the L-PBF process, designs for fine catalysts, and other design considerations for small components. The RoboMet data helps to inform the modeling and design efforts around these fine components.

additive manufacturing↗