Introduction to Metal Additive Manufacturing for Space Applications
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Additive Manufacturing↗
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Metal Additive Manufacturing to Enable Spaceflight
NASA has been involved in the development and maturation of metal additive manufacturing (AM) for spaceflight since the late 2000’s. This presentation will highlight some of the developments in understanding AM processes through material characterization and testing, standards development, and component fabrication to advance the technology for current and future spaceflight missions.
Additive Manufacturing↗
Nondiffractive beam shaping for enhanced optothermal control in metal additive manufacturing
High thermal gradients and complex melt pool instabilities involved in powder bed fusion–based metal additive manufacturing using focused Gaussian-shaped beams often lead to high porosity, poor morphological quality, and degraded mechanical performance. We show here that Bessel beams offer unprecedented control over the spatiotemporal evolution of the melt pool in stainless steel (SS 316L) in comparison to Gaussian beams. Notably, the nondiffractive nature of Bessel beams enables greater tolerance for focal plane positioning during 3D printing. We also demonstrate that Bessel beams significantly reduce the propensity for keyhole formation across a broad scan parameter space. High-speed imaging of the melt pool evolution and solidification dynamics reveals a unique mechanism where Bessel beams stabilize the melt pool turbulence and increase the time for melt pool solidification, owing to reduced thermal gradients. Consequently, we observe a distinctively improved combination of high density, reduced surface roughness, and robust tensile properties in 3D-printed test structures.
36 MATERIALS SCIENCE↗
Porosity Model Parameter Effects on Metal Additive Manufacturing Simulations
This work investigates the effects of model parameters on thermomechanical simulations of a metal additive manufacturing process. The first half of this work explores the sensitivity and effects of the two porosity parameters used in the evolving constitutive model of the simulation. Varying the two parameters of the model show that for the simulations conducted here, the linear coefficient drives the predicted residual stress results while the constant term has little impact. The second half of the work considers the size, order, and the number of element layers in the finite element mesh. The stress distribution plots show that second-order elements along with a dense mesh marginally improve mesh convergence at a significant cost.
Additive Manufacturing↗
Adaptation of Metal Additive Manufacturing Processes for the International Space Station
The In-Space Manufacturing (ISM) project at NASA Marshall Space Flight Center, in a partnership with the company, Made in Space, has previously investigated 3D printing of polymer materials on-orbit. In recent years, the project has begun exploring the potential for metal additive manufacturing (AM) on future space missions to reduce logistics and enable point-of-use manufacturing for sparing and repair. This presentation will provide an overview of constraints for demonstrating a manufacturing process on the International Space Station (ISS) as well as trades of available metal AM processes and their potential for in-space use. There are currently two processes in development as payloads for an ISS technology demonstration: wire+arc additive manufacturing (the Vulcan payload from Made in Space, Inc.) and bound metal deposition (the Fabrication Laboratory from Techshot, Inc). An update on both of these systems, results to date, and future development efforts will be presented. Relevant modeling work to evaluate operation of certain aspects of the processes in a microgravity environment will also be summarized.
manufacturing↗
Method for Rapid Modeling of Distortion in Laser Powder Bed Fusion Metal Additive Manufacturing Parts
The simulation and modeling of part-level distortion and residual stress in diverse metal additive manufacturing (AM) geometries has great potential to enable the rapid adoption of this technology in engineering design. Moreover, the use of additive manufacturing component libraries (CLs) offer a computationally efficient means of quantifying these part-level defects resultant from AM processing. We report on how the individual simulations of simple shapes, potential entries in a CL, can be superimposed to provide an indication of distortion and residual stresses in complex geometries. Laser powder bed fusion AM was used to construct test geometries of varied shapes and their combinations in the form of CLs in an effort to characterize location-dependent and feature-dependent distortion distributions. Blue light scanning was used to experimentally measure 3D distortions in order to investigate the interaction between the component shapes and local boundary conditions. Overall, part-level distortions were highly dependent on test component geometry, local boundary conditions, and shape combination. Commercial finite element software was used to verify experimental trends and to make predictions of distortion. The use of CLs resulted in over 20 times savings in computational cost while reproducing overall trends in distortion for test geometry assemblies. Therefore, it is anticipated that the use of CLs for L-PBF AM geometries has demonstrated potential to facilitate efficient simulations of full component AM assemblies, thereby reducing the need for costly trial-and-error-type experimental analysis.
36 MATERIALS SCIENCE↗
Geometric Sensitivity of Residual Fields in Metal Additive Manufacturing
The sensitivity of geometrical parameters on the residual stress and distortion as computed by a metal additive manufacturing simulation is presented. A nozzle-like geometry was chosen with its length, wall thickness, and outer radius varied. A Latin hypercube sampling of 300 specimens produced the combinations of the geometrical parameters. Full thermomechanical simulations predicted the residual fields. Statistical analysis including regression curves shows that there is a strong correlation between these residual fields and the geometry, hinting that it may be possible to predictably influence the residual displacements and residual stresses by varying the overall geometry.
Multiscale Modeling↗
Advancement of Metal Additive Manufacturing Processes and Alloys for Rocket Propulsion Applications
NASA has been involved in the development and maturation of metal additive manufacturing (AM) for space applications since the 2000’s. Several efforts have focused on the understanding of AM processes through material characterization and testing, standards development, component fabrication, and infusion into development and flight applications. While many common aerospace alloys have been and continue to be a focus of ongoing development, the need for custom-alloy developments for high performance applications enabled by various AM processes has been realized. The applications being targeted are liquid rocket engines with high heat fluxes, high pressure, and that utilize propellants such as hydrogen, which can degrade the alloy. NASA has recently focused on the development and advancement of novel alloy advancement using AM for use in these harsh environments, such as GRCop-42, GRCop-84, NASA HR-1, and JBK-75. These alloys have been evaluated using powder bed fusion (PBF), directed energy deposition (DED), and solid-state AM processes. The results from these processes have demonstrated that AM can enable rapid development of new alloy systems that can yield higher performances across various metal AM processes. These alloys have undergone the fundamental metallurgical evaluations, heat treatment study, and microstructure characterization and mechanical testing campaign. This, combined with direct application-specific component fabrication and hot-fire testing, enabled the increase of the Technology Readiness Level (TRL). This presentation will provide a background and overview of various AM-enabled novel alloys, a comparison across the AM processes, and development including metallurgical and mechanical property studies. It will also cover the latest advancement in the parallel component development and testing and future developments. The goal of these alloy development and use of various AM processes is to allow for technology infusion into NASA and commercial spaceflight missions as well as to establish and sustain the needed commercial AM supply chain.
Additive Manufacturing↗
Enhancing Metal Additive Manufacturing Training with the Advanced Vision Language Model: A Pathway to Immersive Augmented Reality Training for Non-Experts
This paper introduces an innovative training system for the Renishaw AM400 metal printer, leveraging the synergy of the advanced Vision Language Model (VLM) with Augmented Reality (AR) within the Digital Twins (DT) framework. Aimed at overcoming the limitations of conventional training methods in metal additive manufacturing (AM), our system integrates AR to provide an immersive learning environment, enhancing the real-world experience with interactive digital overlays. The core of the system lies in its use of VLM, which, pre-trained on diverse datasets, excels in processing multi-modal data, thereby offering nuanced and contextually relevant guidance for trainees. Key experiments demonstrate the system’s effectiveness, particularly highlighting the usage of VLM as an Artificial Intelligence (AI) agent to integrate external tools like YOLO-v7 for valve state classification and CRAFT for control panel text recognition. This approach significantly improves recognition accuracy, operational understanding, and human–machine interaction, especially for non-expert users, making complex metal AM operations more accessible. The research not only showcases the potential of AR and VLM in industrial training but also sets a new standard for smart manufacturing practices, indicating broader applications in various industrial domains.
Metal additive manufacturing↗
Quality Control of Additively Manufactured Metallic Structures with Machine Learning of Thermography Images
Additive manufacturing (AM) of high-strength metals is currently based on the laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Quality control (QC) requires nondestructive evaluation of actual AM structures. Flash thermography is a potentially promising QC technique because it is scalable to arbitrary structure size. However, the detection sensitivity of this method is limited by noise. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatial–temporal blind source separation and spatial–temporal sparse dictionary learning methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced by the LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. Finally, the ML methods with higher accuracy require a longer runtime. However, this runtime is sufficiently short to perform QC within a realistic time frame.
36 MATERIALS SCIENCE↗
Multi-Task Learning of Scanning Electron Microscopy and Synthetic Thermal Tomography Images for Detection of Defects in Additively Manufactured Metals
One of the key challenges in laser powder bed fusion (LPBF) additive manufacturing of metals is the appearance of microscopic pores in 3D-printed metallic structures. Quality control in LPBF can be accomplished with non-destructive imaging of the actual 3D-printed structures. Thermal tomography (TT) is a promising non-contact, non-destructive imaging method, which allows for the visualization of subsurface defects in arbitrary-sized metallic structures. However, because imaging is based on heat diffusion, TT images suffer from blurring, which increases with depth. We have been investigating the enhancement of TT imaging capability using machine learning. In this work, we introduce a novel multi-task learning (MTL) approach, which simultaneously performs the classification of synthetic TT images, and segmentation of experimental scanning electron microscopy (SEM) images. Synthetic TT images are obtained from computer simulations of metallic structures with subsurface elliptical-shaped defects, while experimental SEM images are obtained from imaging of LPBF-printed stainless-steel coupons. MTL network is implemented as a shared U-net encoder between the classification and the segmentation tasks. Results of this study show that the MTL network performs better in both the classification of synthetic TT images and the segmentation of SEM images tasks, as compared to the conventional approach when the individual tasks are performed independently of each other.
36 MATERIALS SCIENCE↗
Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment in the Area of Aluminum Powder Alloys
The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. A new aluminum (Al) alloy based on high entropy composition, enhanced powder production, and optimized AM build parameterization provided a critical step in widespread adoption of AM technology for automotive applications, in this case. The individual backgrounds and capabilities of the Parties are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and develop a close working relationship with the Participant in the area of aluminum powder alloys and their end use.
36 MATERIALS SCIENCE↗
Predicting phase transformation kinetics during metal additive manufacturing using non-isothermal Johnson-Mehl-Avrami models: Application to Inconel 718 and Ti-6Al-4V
Here, a computational model was developed to predict solid-state phase transformation kinetics within mechanical parts during metal additive manufacturing processes. This model is a modified version of the Johnson-Mehl-Avrami model for non-isothermal phase transformations that can be applied to various material systems undergoing solid-state phase transformations. Using the thermal history of an additive manufacturing fabricated mechanical part, along with the necessary thermodynamic data and kinetic information as inputs, the model outputs the history of phase fraction evolution during the build process. The model was applied to an Inconel 718 part built by powder bed fusion and a Ti-6Al-4V part built by directed energy deposition. Microstructure characterization and mechanical testing were performed for the validation of the model.
36 MATERIALS SCIENCE↗
Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment in the Area of Aluminum Alloys for AM Powder Production (Final Report)
The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. A new aluminum (Al) alloy based on an Al-Ce-X composition, enhanced powder production, and optimized AM build parameterization provided a critical step in widespread adoption of AM technology for automotive applications, in this case. The individual background and capabilities of the Party are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and developed a close working relationship with the Participant in the area of aluminum powder alloys and their end use.
36 MATERIALS SCIENCE↗
Science-Based Acceleration of the Full Value Stream for Metal Additive Manufacturing: Expedited Powder Development and Additive Manufacturing Deployment in the Areas of Ni-Base Superalloy and Custom Alloy Powders for AM
The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. Production of modified nickel-based superalloys and a Ni-containing alloy based on a high entropy composition, enhanced powder production methods, and optimized AM build parameterization provided critical steps in widespread adoption of AM technology for aerospace applications, in this case. The individual backgrounds and capabilities of the Parties are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and develop a close working relationship with the Participant in the areas of nickel-based powder superalloys and custom alloys and their end use.
36 MATERIALS SCIENCE↗
Science-Based Acceleration of the Full Value Stream for Metal Additive Manufacturing: Expedited Powder Development and Additive Manufacturing Deployment in the Areas of Ni-Base Superalloy and Custom Alloy Powders for AM
The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. Production of modified nickel-based superalloys and a Ni-containing alloy based on a high entropy composition, enhanced powder production methods, and optimized AM build parameterization provided critical steps in widespread adoption of AM technology for aerospace applications, in this case. The individual backgrounds and capabilities of the Parties are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and develop a close working relationship with the Participant in the areas of nickel-based powder superalloys and custom alloys and their end use.
36 MATERIALS SCIENCE↗
Review of internal and external surface finishing technologies for additively manufactured metallic alloys components and new frontiers
Surface finishing in additive manufacturing (AM) is a technological bottleneck. The field of surface finishing of AM parts is vast because it not only focuses on roughness reduction in the hard-to-access internal surfaces but also includes the scope of adding coatings and sensors. Even though metal AM component is reaching the density and bulk microstructure at par or even better than conventionally produced components, adverse impact of surface roughness and imperfections is becoming the major obstruction. It is observed that external and internal surface roughness of AM components is a high probability cause of many unavoidable issues such as corrosion, incorrect tolerance estimations during the build stage, and the fatigue failure of parts before the expected life cycle. At present, AM field mainly focuses on improving and enhancing the internal and external surface roughness to pass the stringent qualification requirements for actual applications. To address these challenges, researchers worldwide are conducting many experiments and developing different surface finishing techniques. This paper reviews the state-of-the-art knowledge and processes of different surface finishing technology that can be applied to AM metal components. This article mainly highlights several liquid-based surfaces finishing approaches to develop promising surface microstructures on interior and exterior surfaces as a micromachining tool. The future of making strong and self-monitoring AM component requires broadening of surface finishing field and including advanced topics such as coatings and adding sensor technology. We also discuss new frontiers and the scope of future work in the surface finishing field to bring attention to related concerns and possibilities associated with making smart and strong AM components for twenty-first-century integrated engineering systems.
36 MATERIALS SCIENCE↗
Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing: Expedited Powder Development in the Area of Aluminum Powder Alloys and their End Use (Final Report)
The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. A new aluminum (Al) alloy based on high entropy composition, enhanced powder production, and optimized AM build parameterization provided a critical step in widespread adoption of AM technology for automotive applications, in this case. The individual backgrounds and capabilities of the Parties are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and develop a close working relationship with the Participant in the area of aluminum powder alloys and their end use.
36 MATERIALS SCIENCE↗