In-situ full-field mapping of melt flow dynamics in laser metal additive manufacturing
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36 MATERIALS SCIENCE↗
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Accelerating Large-Format Metal Additive Manufacturing: How Controls R&D is Driving Speed, Scale, and Efficiency
This article highlights work at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility to develop closed-loop, feedback control for laser-wire based Directed Energy Deposition, a form of metal Big Area Additive Manufacturing (m-BAAM), a process being developed in partnership with GKN Aerospace specifically for the production of Ti-6Al-4V pre-forms for aerospace components. A large-scale structural demonstrator component is presented as a case-study in which not just control, but the entire 3D printing workflow for m-BAAM is discussed in detail, including design principles for large-format metal AM, toolpath generation, parameter development, process control, and system operation, as well as post-print net-shape geometric analysis and finish machining. In terms of control, a multi-sensor approach has been utilized to measure both layer height and melt pool size, and multiple modes of closed-loop control have been developed to manipulate process parameters (laser power, print speed, deposition rate) to control these variables. Layer height control and melt pool size control have yielded excellent local (intralayer) and global (component-level) geometry control, and the impact of melt pool size control in particular on thermal gradients and material properties is the subject of continuing research. Further, these modes of control have allowed the process to advance to higher deposition rates (exceeding 7.5 lb/hr), larger parts (1-meter scale), shorter build times, and higher overall efficiency. The control modes are examined individually, highlighting their development, demonstration, and lessons learned, and it is shown how they operate concurrently to enable the printing of a large-scale, near net shape Ti-6Al-4V component.
Gibson, Brian↗
Perspectives on Computational Materials-informed Qualification and Certification of Additively Manufactured Metallic Materials
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Computational Materials↗
Successes and Failures of Metal Additive Manufacturing for Rocket Engines
NASA has been developing additive manufacturing (AM) for various technical and programmatic advantages for complex rocket engine and aerospace components. This maturation has focused on various AM processes, new alloys, characterizing material properties, developing standards, producing demonstrator parts, and integrating AM hardware in liquid rocket engines through test-fail-fix cycles, as well as application and dissemination of lessons learned of the AM lifecycle. The importance of proper AM processing was made evident in the failure of a Laser Powder Bed Fusion (L-PBF) copper-alloy combustion chamber during a hot-fire test due to a degraded material quality. The hot-fire test aimed to demonstrate high duty cycle under a risk-tolerant development project, where consequences of component failure would be minimal. However, the unintentional component failure emphasized the necessity of robust material characterization and rigorous process control procedures for the safe use of AM components in critical applications. This presentation provides an overview of the development failure, a discussion on the evaluation of the failed chamber and supplemental chambers produced at the same time, a representative material samples that included intentional build witness lines, and a summary of the key results and recommendations from the evaluations. NASA continues to approach AM processes and designs with a level of risk and acceptance of failures that is appropriate for the project objectives, with the overall goal of safe implementation of AM technology and transferring AM technology into commercial space applications. This presentation with provide critical awareness to the community lessons learned on proper implementation of AM.
Additive Manufacturing↗
Tailoring Corrosion Resistance of Additively Manufactured Metals with Atomic Layer Deposition
The goal of this work is to develop a scalable post-manufacturing capability at LANL that utilizes atomic layer deposition (ALD) for corrosion-resistant coatings onto additively manufactured (AM) metals. This will provide fundamentally new and essential capabilities towards the interchangeability of AM metals with traditionally wrought or machined material. This will be accomplished by (1) formulating novel ALD precursor doses and film thicknesses onto as-printed coupons of AM metals and (2) providing electrochemical characterization of corrosion susceptibility as a function of deposited film thickness. While ALD is well-established, the unique aspect (risk) of this work is application to rough AM surfaces. This risk is mitigated by repeating ALD deposition cycles, where thicker coatings laterally branch, resulting in a uniform coating. This risk will be assessed in the phase 1 feasibility study, wherein the application of ALD coatings to small AM coupon surfaces will be demonstrated using existing hardware and characterization tools at Sigma. This study alone will provide ground-breaking insight on the compatibility of ALD coating techniques with AM metals. Going beyond the phase 1 study, a standalone deposition chamber will be built, so full AM components can be coated and tested. While this MFR investment is focused on corrosion mitigation, it is critical to highlight external benefits of this technique outside the scope of this proposed study. ALD has extraordinary universality, whereby almost any material can be given almost any coating or graded density coating with atomic precision; and, the only limiting factors to scalability is the size of the dosing chamber. The self-limiting reactions intrinsic to ALD offers high conformity to part geometry and tolerance, even for internal surfaces where electroplating or conventional chemical vapor deposition falls short due to differential diffusion. This uniquely positions ALD at the forefront of post-manufacturing strategies for AM components, especially for those with complex geometry and internal surfaces.
36 MATERIALS SCIENCE↗
Scaling Up metal additive manufacturing process to fabricate molds for composite manufacturing
Direct Energy Deposition (DED) systems are currently used to repair and maintain existing parts in the aerospace and automotive industries. This paper discusses an effort to scale up the DED technique in order to Additively Manufacture (AM) molds and dies used in the composite manufacturing industry. The US molds and dies market has been in a rapid decline over the last decade due to outsourcing to non-US entities. Oak Ridge National Laboratory (ORNL), Wolf Robotics and Lincoln Electric have developed a Metal Big Area Additive Manufacturing (MBAAM) system that uses a high deposition rate and a low-cost wire feedstock material. In this work we used the MBAAM system with a mild steel wire, ER70S-6, to fabricate a compression molding mold for composite structures used in automotive and mass-transit applications. In addition, the mechanical properties of the AM structure were investigated, and it was found that the MBAAM process delivers parts with high planar isotropic behavior. The paper investigates the microstructure and grain of the printed articles to confirm the roots of the observed planar isotropic properties. Here, the manufactured AM mold was used to fabricate 50 composite parts with no observed mold deformations.
36 MATERIALS SCIENCE↗
Evaluation of Additively Manufactured Metals for Use in Oxygen Systems Project
Space Launch System, Commercial Resupply, and Commercial Crew programs have published intent to use additively manufactured (AM) components in propulsion systems and are likely to include various life support systems in the future. Parts produced by these types of additive manufacturing techniques have not been fully evaluated for use in oxygen systems and the inherent risks have not been fully identified. Some areas of primary concern in the SLS process with respect to oxygen compatibility may be the porosity of the printed parts, fundamental differences in microstructure of an AM part as compared to traditional materials, or increased risk of shed metal particulate into an oxygen system. If an ignition were to occur the printed material could be more flammable than components manufactured from a traditional billet of raw material and/or present a significant hazards if not identified and rigorously studied in advance of implementation into an oxygen system.
Tylka, Jonathan↗
Powder Bed Fusion Laser Beam Metals Additive Manufacturing: Process Monitoring Approaches for Qualification and Certification
The use of in-situ process monitoring is of interest to lower the cost of inspection for the qualification of powder bed fusion laser beam metal (PBF-LB/M) additively manufactured (AM) parts. Precise monitoring of the PBF-LB/M AM build process constitutes a multi-scale and multi-discipline task. There are several significant challenges to the in-situ approach: the synchronization of sensor signals to process steps; the physical interpretation and classification of sensor signals; managing very large datasets; and comparing the inputs with the observed monitoring signals. At NASA Langley Research Center, a configurable architecture additive testbed has been developed to monitor the build process with synchronized sensors. The philosophy and method adopted for the synchronization of the cameras with laser power and position throughout a complex PBF-LB/M AM build will be described. The synchronized in-situ monitoring signals are compared with ex-situ nondestructive inspection, x-ray computed tomography (XCT). Such comparisons permit a better understanding of how the sequential process actions of LPBF-AM can affect build quality. The multi-scale and complex process of printing additively manufactured (AM) parts can have unexpected, but predictable, build conditions that result in material microstructure variability. This presentation will describe an additive manufacturing model-based process metric (AM-PM) computational method that is a fully parallel reduced order modeling approach developed to evaluate the evolution of AM processes. This method couples the known sequence of the AM process with a physically informed nearest neighbors’ calculation to map the conditions of a part-scale build. The result is a map of the build that is derived directly from build files or in-situ process monitoring sensors. The methodology of the approach will be described and mapped to the porosity observed from XCT for a complex PBF-LB/M build. Such comparative results develop understanding of how the sequential process actions can affect the PBF-LB/M AM build quality and microstructure variability.
Laser Powder Bed Fusion↗
Attention-based 3D – convolutional neural network model for mechanical property predictions using visible light images in metal additive manufacturing
Additive manufacturing (AM), while commonly used for rapid prototyping and creating components with complex geometries, has not been widely adopted for critical applications across the aerospace, automotive, defense, energy, and medical industries. This is, in part, due to the challenges of controlling flaws and uncertainty in the mechanical behavior of additively manufactured components. In recent years, there has been an increase in research aimed at predicting the final mechanical properties of additively manufactured components during the printing process. To address these issues, a 3D-CNN model was trained using low-cost in situ visible-light camera data, anomaly classifications, and the chosen process parameters to predict the ultimate tensile strength (UTS), yield strength (YS), total elongation (TE), and uniform elongation (UE). The 3D-CNN layers of the model employed attention mechanisms to prioritize features in the data, thereby improving prediction accuracy. Furthermore, the effect of each process parameter and anomaly class is investigated using attention-based dynamic sigmoid weighted gates to interpret the influence each class has on the final prediction. Different combinations of the in situ data were fed into the 3D-CNN, with varying amounts of image layers, to determine the ideal combination for predicting mechanical properties in situ. Here, the 3D-CNN model achieved mean absolute percentage errors (MAPE) below 5% for both UTS and YS while using only a single camera input and under half of the available image layers.
36 MATERIALS SCIENCE↗
Modeling Nondestructive Defect Detection in Additively Manufactured Metallic Structures for Nuclear Applications
The future of quickly, economically produced metallic nuclear reactor parts with minimal supply-chain dependence lies in Laser Powder Bed Fusion (LPBF) Additive Manufacturing (AM): a 3D printing method involving laser melting and net shaping stainless steel and Inconel metallic powder into a solid structure. However, intrinsic features in LPBF frequently leads to the formation of materials defects, such as pores, within 3D printed structures. As safe long-term use in energy applications requires knowledge of all relevant defects before deployment in a reactor, we must develop methods for nondestructive detection of these defects. We are investigating Pulsed Thermal Tomography (PTT), which is a non-contact nondestructive imaging method scalable to arbitrary structure size. Thermal tomography (TT) is a computational method for 3D spatial reconstruction of material thermal effusivity from flash or pulsed thermography temperature data cube. Thermography data cube consists of 2D surface temperature measurements at different times. The objective of the present work is to investigate limits on defect detection in AM metallic structures with PTT. To this effect, we modeled PTT with COMSOL heat transfer computer simulations. We developed a layered media COMSOL simulation consisting of a Stainless Steel 316 (SS316) plate with an internal layer of un-sintered SS316 powder. Thermophysical properties of the powder layer were modeled with equivalent volume mixing model. To account for partial sintering at the boundary of the defect, the transition between solid and powder layers was modeled as a Gaussian. Using data from COMSOL simulations, we reconstructed depth-dependent thermal effusivity, which allowed defect visibility estimation. A series of parametric studies determined that at 1mm depth, 50µm is the smallest detectable defect. In addition, classification of the defects which can lead to early fatigue of the metallic structure in a reactor is briefly discussed.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Equation of State Properties of Additively Manufactured Metals
Report of FY 2019 activities for SDRD project.
36 MATERIALS SCIENCE↗
Analysis of Defects in Metal Additive Manufacturing with Augmented Data Generation
Laser powder bed fusion (LPBF) is a method of additive manufacturing (AM) that selectively melts and fuses together microscopic metallic powder. LPBF offers the benefit of producing custom structures out of high strength metals that can be difficult to fabricate with conventional methods. The challenge of LPBF is that 3D printed structures often have internal pores due to process flaws. Pulsed thermal tomography (PTT) is a method for reconstructing the depth profile of materials, allowing the visualization internal voids in solids. In prior work, we developed a convolutional neural network (CNN) which, having been trained on simulated 2D PTT images of subsurface elliptical defects, was able to classify the semi-major radii, semi-minor radii, and angular orientation of the best-fit ellipses in previously unseen PTT images. The unseen PTT images contained subsurface irregular defect shapes imported from scanning electron microscopy (SEM) images of metallic LPBF-printed specimens. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN.
36 MATERIALS SCIENCE↗
Systems and Methods for Designing and Fabricating Contact-Free Support Structures for Overhang Geometries of Parts in Powder-Bed Metal Additive Manufacturing
Systems and methods are provided for designing and fabricating contact-free support structures for overhang geometries of parts fabricated using electron beam additive manufacturing. One or more layers of un-melted metallic powder are disposed in an elongate gap between an upper horizontal surface of the support structure and a lower surface of the overhang geometry. The powder conducts heat from the overhang geometry to the support structure. The support structure acts as a heat sink to enhance heat transfer and reduce the temperature and severe thermal gradients due to poor thermal conductivity of metallic powders underneath the overhang. Because the support structure is not connected to the part, the support structure can be removed freely without any post-processing step.
Chou, Yuag-Shan↗
Phased array-based nonlinear wave mixing technique: Application to lack-of-fusion porosity characterization in additively manufactured metals
The objective of this research is to demonstrate the effectiveness of a phased array-based nonlinear wave mixing technique to characterize internal, localized microscale damage in an additively manufactured (AM) component. By using phased arrays for the generation of the incident waves, it is possible to produce a nonlinear wave mixing scanning technique without the need for immersion or changing coupling conditions. The phased arrays can be configured to generate incident waves in multiple directions that meet the resonance conditions required for nonlinear wave mixing at a variety of internal locations. This allows for the scanning of a specimen without the removal and re-coupling of the source transducers, leading to greater scanning speed and repeatability. To demonstrate the accuracy of this phased array wave mixing approach, measurements of acoustic nonlinearity in an AM component are first made with a bulk wave second harmonic generation through thickness measurement. Next, nonlinear wave mixing measurements are made with single element transducers to confirm the sensitivity of the proposed nonlinear wave mixing approach to lack-of-fusion porosity in AM metals. Finally, phased arrays are used to highlight the effectiveness of the proposed nonlinear wave mixing technique in these same AM components.
Acoustics↗
Microscale Metal Additive Manufacturing by Solid‐State Impact Bonding of Shaped Thin Films
The deposition of device-grade inorganic materials is one key challenge toward the implementation of additive manufacturing (AM) in microfabrication, and to that end, a broad range of physico-chemical principles has been explored for 3D fabrication with micro- and nanoscale resolution. Yet, for metals, a process that achieves material quality rivalling that of established thin-film deposition methods, and at the same time, has the potential to combine high throughput production with a broad palette of processable materials, is still lacking. Here, the kinetic, solid-state bonding of metal thin films for the additive assembly of high-purity, high-density metals with micrometer-scale precision is introduced. Indirect laser ablation accelerates micrometer-thick gold films to hundreds of meters per second without their heating or ablation. Their subsequent impact on the substrate above a critical velocity forms a permanent, metallic bond in the solid state. Stacked layers are of high density (>99%). By defining thin-film layers with established lithographic methods prior to launch, a variable feature size (2–50 µm), arbitrary shape of bonded layers, and parallel transfer of up to 36 independent film units in a single shot, is demonstrated. Thus, the solid-state kinetic bonding principle as a viable and potentially versatile route for micro-scale AM of metals is established.
3D printing↗
In situ/operando synchrotron x-ray studies of metal additive manufacturing
Additive manufacturing (AM) comprises a group of transformative technologies that are likely to revolutionize manufacturing. In particular, laser-based metal AM techniques can not only fabricate parts with extreme complexity, but also provide innovative means for designing and processing new metallic systems. However, there are still several technical barriers that constrain metal AM. Overcoming these barriers requires a better understanding of the physics underlying the complex and dynamic laser–metal interaction at the heart of many AM processes. Furthermore, this article briefly describes the state of the art of in situ/operando synchrotron x-ray imaging and diffraction for studying metal AM, mostly the laser powder-bed fusion process. It highlights the immediate impact of operando synchrotron studies on the advancement of AM technologies, and presents future research challenges and opportunities.
36 MATERIALS SCIENCE↗
Roughness measurements across topographically varied additively manufactured metal surfaces
Not Available
36 MATERIALS SCIENCE↗
Optimization of Rocket Engine Components using Multi-Metallic Additive Manufacturing
Additive manufacturing (AM) is advancing many applications of component design for liquid rocket engines. AM has been demonstrated in various rocket component applications using a variety of monolithic metal alloys, many of which are traditional alloys for extreme environments. NASA and industry partners have focused in recent years to advance processing to create bimetallic and multicomponent AM processes and materials. The role of multi-metallic AM offers advantages since it can further optimize weight, optimize reliability and performance by increasing the strength to weight ratio of a component, and can optimize materials for various engineering requirements. NASA’s Rapid Analysis and Manufacturing Propulsion Technology (RAMPT) project has designed and manufactured a series of additively manufactured (AM) coupled combustion chambers, nozzles, and other engine components to advance new AM processes and materials with the goal of reducing cost and schedule for engine manufacturing. These designs incorporated multimetallic AM, which further enabled carbon-fiber composite overwrap to reduce overall thrust chamber assembly (TCA) mass. Various AM processes were demonstrated on these components using a copper-based alloy/superalloy bimetallic solution. The AM processes being explored individually and in combination for bimetallic applications include Laser Powder Bed Fusion (L-PBF), Laser Powder Directed Energy Deposition (LP-DED), and cold spray. The combination of bimetallic material combinations explored in this research include GRCop-based alloys and superalloys, Inconel 625 or NASA HR-1. One unique development that will be presented is the combustion chamber and nozzle as a single component by using freeform integrated DED to build the nozzle directly onto the aft end of the chamber. The various aspects of the additive manufacturing processes and challenges, materials characterization and mechanical testing, and hot-fire testing of bimetallic components in a relevant rocket engine environment will be discussed.
Additive Manufacturing↗