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At least 37 records · Page 2

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↗

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↗

Correlations Between Porosity, Spatter, and Process Metrics for Powder Bed Fusion Laser Beam Metallic Additive Manufacturing

Components fabricated using the powder bed fusion laser beam metallic (PBF-LB/M)additive manufacturing process are the result of a multitude of weld passes conducted sequentially. Qualifying components for aerospace applications requires a thorough understanding of the process-structure-properties relationships. Porosity defects are known to have a strong adverse effect on the mechanical properties of a component. In particular, porosity defects created by lack of fusion have high aspect ratio morphologies leading to stress concentrations that become crack initiation sites. In the present work, the occurrence of spatter induced lack of fusion porosity was studied using synchronized in-situ process monitoring, additive manufacturing model-based process metrics, and high-resolution X-ray computed tomography. The results show that lack of fusion porosity is statistically correlated with unremoved welding spatter ejecta of the PBF-LB/M process and process metrics related to the hatching strategy.

Qualification↗

Development of Computational Materials Workflows for Additively Manufactured Metallic Materials to Enable Accelerated Prediction of Fatigue Performance

The maturation of computational materials approaches for fatigue performance prediction in a qualification and certification process is stifled by the ability to validate complex, microstructure-based simulations. Such a validation strategy bears immediate challenges including generating accurate virtual microstructures, efficiently solving physics-based mechanical simulations over relevant spatial and temporal scales, and acquiring high-fidelity calibration and validation data at the appropriate length scale. This presentation will overview these common challenges and present a case study to demonstrate a computational materials workflow for additively manufactured metallic materials. In this study, process-specific defects are characterized using segmented X-Ray micro-computed tomography measurements and overlaid on virtual microstructures. Accelerated crystal plasticity-based fatigue simulations are performed to demonstrate cyclic evolution and localization of mechanical fields in the vicinity of defects in response to their precise spatial configuration. An example of how this computational materials workflow may support next-generation qualification is discussed.

computational materials↗

Introduction to Metal Additive Manufacturing for Propulsion Applications: Part I and II

Additive Manufacturing (AM) has become a prominent technology of interest for manufacturing propulsion components and gaining attention across the aerospace industry. AM is maturing at a rapid pace and providing new design opportunities, novel materials, new industries and supply chains resulting in programmatic and technical performance improvements. The successful use of AM requires a methodical and intentional approach to understanding the concept to utilization lifecycle for AM. This course will provide an overview of the various steps in AM process trades, design, build process, post-processing, certification and infusion of AM. This will provide various lessons learned and experiences that were captured in a recent AIAA textbook titled "Metal Additive Manufacturing for Propulsion Applications" by the session chairs and industry colleagues. This course will include propulsion examples and that went through the AM lifecycle including hot-fire testing.

Additive Manufacturing↗

Uncertainty Reduction With Multi-Model Monte Carlo for Crystal Plasticity Simulations of Additively Manufactured Metals

In this work, multi-model Monte Carlo estimators are developed to reduce uncertainty in quantities of interest (QoIs) extracted from crystal plasticity simulations of additively manufactured (AM) metals. A significant concern in AM parts is uncertainty in mechanical properties caused in part by complex microstructures that arise from the AM process. Quantifying uncertainty in microstructure-sensitive behavior using experiments alone is costly, especially when mechanical allowables must be established. Quantitative relationships among microstructure, micromechanical metrics like slip accumulation, crack initiation, and failure are also difficult to capture with limited experiments. Crystal plasticity material models instead enable computational prediction of micromechanical stress and strain fields given a discretized microstructure. However, high-fidelity finely discretized crystal plasticity simulations are computationally expensive, while lower-fidelity models are less accurate and generally biased, making uncertainty quantification and reduction computationally difficult as well. Multi-model Monte Carlo methods leverage correlations between high- and low-fidelity models to produce unbiased estimators for QoIs with reduced uncertainty relative to standard Monte Carlo. Crystal plasticity QoIs considered in this work include yield strength and the mean and extreme values of micromechanical fields that are relevant to crack initiation. Multi-model Monte Carlo estimators are developed for each individual QoI and several groups of QoIs. The results of this work establish relationships among model correlations, sample allocation, and uncertainty reduction for different combinations of QoIs and demonstrate a trend of less uncertainty reduction as QoIs become more sensitive to local microstructure. Limitations from using pilot samples to estimate model covariances and train low-fidelity models are also addressed. The uncertainty reduction achieved by multi-model Monte Carlo is an important step toward using computational mechanics models to predict microstructure-sensitive crack initiation and failure in AM parts.

uncertainty quantification↗

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↗

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↗

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↗

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↗