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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 19 records

In-Situ Characterization of Pore Formation Dynamics in Pulsed Wave Laser Powder Bed Fusion

Laser powder bed fusion (LPBF) is an additive manufacturing technology with the capability of printing complex metal parts directly from digital models. Between two available emission modes employed in LPBF printing systems, pulsed wave (PW) emission provides more control over the heat input compared to continuous wave (CW) emission, which is highly beneficial for printing parts with intricate features. However, parts printed with pulsed wave LPBF (PW-LPBF) commonly contain pores, which degrade their mechanical properties. In this study, we reveal pore formation mechanisms during PW-LPBF in real time by using an in-situ high-speed synchrotron x-ray imaging technique. We found that vapor depression collapse proceeds when the laser irradiation stops within one pulse, resulting in occasional pore formation during PW-LPBF. We also revealed that the melt ejection and rapid melt pool solidification during pulsed-wave laser melting resulted in cavity formation and subsequent formation of a pore pattern in the melted track. The pore formation dynamics revealed here may provide guidance on developing pore elimination approaches.

36 MATERIALS SCIENCE↗

Combining Deep Learning and scatterControl for High-Throughput X-ray CT Based Non-Destructive Characterization of Large-Scale Casted Metallic Components

X-ray computed tomography (XCT) is essential for nondestructive evaluation and quality control of large-scale metal components. XCT imaging, however, faces significant challenges from metal artifacts, particularly those caused by Compton scattering, which degrade image quality and obscure critical details. Hardware-based solutions (e.g. scatterControl) offer advancements by intercepting scattered photons and reducing artifacts, but they can be time-consuming and require additional processing. Here, we propose modifying and leveraging a novel deep learning (DL) framework, Simurgh, to enhance and accelerate scatter correction in XCT. By combining scatterControl with DL-based artifact removal, we demonstrate significant reduction in scan time while producing high-quality reconstructions. Through extensive evaluation on industrial XCT data, we show that our methods reduce scan time by up to more than 10 x while preserving flaw detectability. Quantitative analysis across multiple segmentation techniques confirms that Simurgh-based reconstructions consistently outperform traditional Feldkamp-Davis-Kress, model-based iterative reconstruction, and commercial DL models in both pixel-level and task-specific evaluations, enabling scalable, high-throughput XCT workflows for characterization of large scale components in applications such as casting and metal additive manufacturing.

Complex metal parts↗

Island scanning pattern optimization for residual deformation mitigation in laser powder bed fusion via sequential inherent strain method and sensitivity analysis

Laser powder bed fusion (L-PBF) has emerged as one of the mainstream additive manufacturing approaches for fabricating metal parts with complex geometries and intricate internal structures. However, large deformation associated with rapid heating and cooling can lead to build failure and requires post-processing which may increase manufacturing cost and prolong the production period. Here in this work, an island scanning pattern design method is proposed to optimize the scanning direction of each island in order to reduce part deformation after cutting off the build platform. The objective of this optimization is to minimize the upward bending of the part after sectioning, which allows the part deformation to satisfy the tolerance requirement or reduce the post heat treatment time. Inherent strain method is employed in the sequential finite element analysis consisting of layer-by-layer activations and sectioning for fast residual distortion prediction. Full sequential sensitivity analysis for the formulated optimization is provided to update the island scanning directions. To show the feasibility and effectiveness of the proposed method, the scanning patterns of a block structure and a connecting rod were designed and parts were fabricated using an open architecture L-PBF machine. The fabrication experiments demonstrated that the residual deformation of both parts fabricated by optimized scanning pattern can be reduced by over 50% compared to the initial scanning patterns, which demonstrate the effectiveness of the proposed method.

36 MATERIALS SCIENCE↗

Defects and anomalies in powder bed fusion metal additive manufacturing

Metal additive manufacturing is a disruptive technology that is revolutionizing the manufacturing industry. Despite its unrivaled capability for directly fabricating metal parts with complex geometries, the wide realization of the technology is currently limited by microstructural defects and anomalies, which could significantly degrade the structural integrity and service performance of the product. Accurate detection, characterization, and prediction of these defects and anomalies have an important and immediate impact in manufacturing fully-dense and defect-free builds. As such, this review seeks to elucidate common defects/anomalies and their formation mechanisms in powder bed fusion additive manufacturing processes. They could arise from raw materials, processing conditions, and post-processing. While defects/anomalies in laser welding have been studied extensively, their formation and evolution remain unclear. Additionally, the existence of powder in powder bed fusion techniques may generate new types of defects, e.g., porosity transferring from powder to builds. Practical strategies to mitigate defects are also addressed through fundamental understanding of their formation. Such explorations enable the validation and calibration of models and ease the process qualification without costly trial-and-error experimentation.

42 ENGINEERING↗

Heat-treatment of metal parts facilitated by sand embedment

Embedding metal parts of complex shape in sand contained in a steel box prevents strains and warping during heat treatment. The sand not only provides a simple, inexpensive support for the parts but also ensures more uniform distribution of heat to the parts.

Briscoe, C. C.↗

Use of diffusive gradients in thin films (DGT) to measure potentially bioavailable metals in southeastern USA blackwater streams

Here, we used diffusive gradients in thin films (DGT) to measure potentially bioavailable metals in coastal plain streams in the southeastern USA that exhibited strong to moderate blackwater characteristics. Metals were partitioned into particulate metals, DGT-inert metals (i.e., colloidal and refractory organic complexes not accumulated by DGT), and DGT-labile metals (i.e., free metal ions, small inorganic complexes, and labile organic complexes). We also examined the influence of different DGT deployment times using data collected from the field and a follow-up laboratory study. The DGT-measured fraction of dissolved metals in the streams was 15% for Cd, 21% for Zn, 33% for Cu, 37% for Pb, and 98% for Mn. Metals bound to particulates predominated only for Pb. Most of the Cd, Pb, Zn, and Cu were associated with colloids, refractory organic complexes, or particles. Relatively small amounts were in free ion or labile complexes likely to be bioavailable through respiratory surfaces. Modeled concentrations of free and inorganically bound Cu and Pb were lower than the DGT fraction indicating that DGT accumulated some organically bound Cu and Pb that might not have been bioavailable. DGT-exposure times in excess of 5 days may have contributed to the accumulation of partly labile organic–metal complexes and were associated with substantial biofouling that caused metal uptake by DGT to depart from linearity.

54 ENVIRONMENTAL SCIENCES↗

Vector-level feedforward control of LPBF melt pool area using a physics-based thermal model

Laser powder bed fusion (LPBF) is an additive manufacturing technique that has gained popularity thanks to its ability to produce geometrically complex, fully dense metal parts. However, these parts are prone to internal defects and geometric inaccuracies, stemming in part from variations in the melt pool. Here, this paper proposes a novel vector-level feedforward control framework for regulating melt pool area in LPBF. By decoupling part-scale thermal behavior from small-scale melt pool physics, the controller provides a scale-agnostic prediction of melt pool area and efficient optimization over it. This is done by operating on two coupled lightweight models: a finite-difference thermal model that efficiently captures vector-level temperature fields and a reduced-order, analytical melt pool model. Each model is calibrated separately with minimal single-track and 2D experiments, and the framework is validated on a complex 3D geometry in both Inconel 718 and 316L stainless steel. Results showed that feedforward vector-level laser power scheduling reduced geometric inaccuracy in key dimensions by 62%, overall porosity by 16.5%, and photodiode root-mean-squared deviation by 38.5% on average. Overall, this modular, data-efficient approach demonstrates that proactively compensating for known thermal effects can significantly improve part quality while remaining computationally efficient and readily extensible to other materials and machines.

Additive manufacturing↗

A process optimization framework for laser direct energy deposition: Densification, microstructure, and mechanical properties of an Fe-Cr alloy

Laser Direct Energy Deposition (DED) is a metal additive manufacturing technique with the ability to fabricate large and complex parts through deposition of metal powders. However, achieving high-density parts and targeted build heights using DED can be challenging due to the large number of highly sensitive process variables. This work proposes a robust fabrication parameter optimization framework to generate process maps for primary parameters in DED, including laser power, scan speed, mass flow rate, hatch spacing, and layer height. Simple single-track experiments were utilized to map out the parameter space, and a combination of geometric criteria for hatch spacing and layer height were proposed to determine parameter sets that achieve both targeted build heights and mitigate porosity formation. Using this framework, specimens with >99 % density and consistent mechanical properties were successfully fabricated over a wide range of process parameters for an Fe-9wt.%Cr (Fe9Cr) alloy, a surrogate for radiation damage-resistant reduced activation ferritic/martensitic (RAFM) steels. Processing these materials using DED is of particular interest in the development of plasma facing components for nuclear fusion applications. The microstructure and mechanical properties of as-printed Fe9Cr were characterized using optical and electron microscopy, X-ray diffraction, and uniaxial tensile tests. As-printed Fe9Cr displayed ~25 % elongation and ultimate tensile strengths of up to 475 MPa which is comparable to similar wrought alloys. Finally, the proposed framework will allow for accelerated DED parameter optimization for novel alloy systems, as well as open the possibility for local microstructure control while simultaneously mitigating defect formation.

42 ENGINEERING↗

The interplay between vapour, liquid, and solid phases in laser powder bed fusion

The capability of producing complex, high performance metal parts on demand has established laser powder bed fusion (LPBF) as a promising additive manufacturing technology, yet deeper understanding of the laser-material interaction is crucial to exploit the potential of the process. By simultaneous in-situ synchrotron x-ray and schlieren imaging, we probe directly the interconnected fluid dynamics of the vapour jet formed by the laser and the depression it produces in the melt pool. The combined imaging shows the formation of a stable plume over stable surface depressions, which becomes chaotic following transition to a full keyhole. We quantify process instability across several parameter sets by analysing keyhole and plume morphologies, and identify a previously unreported threshold of the energy input required for stable line scans. The effect of the powder layer and its impact on process stability is explored. These high-speed visualisations of the fluid mechanics governing LPBF enable us to identify unfavourable process dynamics associated with unwanted porosity, aiding the design of process windows at higher power and speed, and providing the potential for in-process monitoring of process stability.

36 MATERIALS SCIENCE↗

Exploratory Studies of Mechanical Properties, Residual Stress, and Grain Evolution at the Local Regions near Pores in Additively Manufactured Metals

Directed energy deposition (DED) is gaining widespread acceptance in various industrial applications since its unique manufacturing features allow the DED to print metallic parts with very complex geometries. However, DED inevitably generates a lot of internal pores which can limit the widespread applications of the DED technique. The current studies on DED porosity are mostly focused on analyzing pores’ bulk-scale influences on mechanical properties and performances. Since DED pores have a micro-scale existence, with dimensions ranging from a few microns to several hundred microns, it is fundamental to explore the pores’ influences on the micro-scale, including local mechanical properties, residual stress, and grains near pores. However, this important research direction has been neglected. The objective of this work is to fill the above gap in DED porosity research and acquire a fundamental understanding of the role of porosity on a microscopic scale. The authors used nanoindentation approaches to investigate internal pores’ effects on mechanical properties and residual stress in local regions surrounding the pores. In addition, the grains near pores were observed through EBSD, and simulated with the Kinetic Monte Carlo model. The research findings can be provided for DED researchers and industrial practitioners as technical guidance. Most importantly, the research results can work as a good reference for tracing the source of bulk-scale mechanical performances and properties of DED parts with internal pores.

36 MATERIALS SCIENCE↗

Pressurized Shell Molds For Metal-Matrix Composites

Balanced-pressure molds used to make parts in complex shapes from fiber-reinforced metal-matrix composite materials. In single step, molding process makes parts in nearly final shapes; only minor finishing needed. Because molding pressure same on inside and outside, mold does not have to be especially strong and can be made of cheap, nonstructural material like glass or graphite. Fibers do not have to be cut to conform to molds. Method produces parts with high content of continuous fibers. Parts stiff but light in weight, and coefficients of thermal expansion adjusted. Parts resistant to mechanical and thermal fatigue superior to similar parts made by prior fabrication methods.

Kashalikar, Uday K.↗

Laser powder bed fusion parameter estimation with k-NN

Abstract Laser powder bed fusion (L-PBF) is a technique within additive manufacturing that uses a high power density laser to build parts from fused powdered metal alloy. This technology is well equipped to produce complex parts with otherwise impossible features, such as hidden voids or lattice structures. Alongside capability, reliability and quality are key characteristics considered when choosing a manufacturing method, and these are gaining attention as this method becomes more prevalent in industry. One main indicator of a stable L-PBF process is consistent melt pool geometry, and the properties of which are likely to determine the quality of the part produced. As computing power and sensing technologies become more advanced, this melt pool geometry could be studied in real time. This work addresses the challenge by leveraging a k-nearest neighbor (k-NN) model to identify key features within melt pool imagery and predict the energy density. The k-NN model was trained on data provided by the National Institute of Standards and Technology (NIST). Data preprocessing was performed on the images to extract features that were used in the k-NN model. This approach was used to accurately infer the energy density of unseen layers within the same part. The algorithm was subsequently tested with unique scan strategies and found to reasonably estimate the energy density of different parts. A fivefold cross validation found the algorithm to be consistently predicting the class of 91.4% of the in situ melt pool images.

Jung, Patrick (ORCID:0000000267890859)↗

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↗

The Application of Convolutional Neural Networks (CNNs) to Recognize Defects in 3D-Printed Parts

Cracks and pores are two common defects in metallic additive manufacturing (AM) parts. In this paper, deep learning-based image analysis is performed for defect (cracks and pores) classification/detection based on SEM images of metallic AM parts. Three different levels of complexities, namely, defect classification, defect detection and defect image segmentation, are successfully achieved using a simple CNN model, the YOLOv4 model and the Detectron2 object detection library, respectively. The tuned CNN model can classify any single defect as either a crack or pore at almost 100% accuracy. The other two models can identify more than 90% of the cracks and pores in the testing images. In addition to the application of static image analysis, defect detection is also successfully applied on a video which mimics the AM process control images. The trained Detectron2 model can identify almost all the pores and cracks that exist in the original video. This study lays a foundation for future in situ process monitoring of the 3D printing process.

36 MATERIALS SCIENCE↗

Using Innovative Technologies for Manufacturing and Evaluating Rocket Engine Hardware

Many of the manufacturing and evaluation techniques that are currently used for rocket engine component production are traditional methods that have been proven through years of experience and historical precedence. As we enter into a new space age where new launch vehicles are being designed and propulsion systems are being improved upon, it is sometimes necessary to adopt new and innovative techniques for manufacturing and evaluating hardware. With a heavy emphasis on cost reduction and improvements in manufacturing time, manufacturing techniques such as Direct Metal Laser Sintering (DMLS) and white light scanning are being adopted and evaluated for their use on J-2X, with hopes of employing both technologies on a wide variety of future projects. DMLS has the potential to significantly reduce the processing time and cost of engine hardware, while achieving desirable material properties by using a layered powdered metal manufacturing process in order to produce complex part geometries. The white light technique is a non-invasive method that can be used to inspect for geometric feature alignment. Both the DMLS manufacturing method and the white light scanning technique have proven to be viable options for manufacturing and evaluating rocket engine hardware, and further development and use of these techniques is recommended.

Betts, Erin M.↗

Using Innovative Techniques for Manufacturing Rocket Engine Hardware

Many of the manufacturing techniques that are currently used for rocket engine component production are traditional methods that have been proven through years of experience and historical precedence. As we enter into a new space age where new launch vehicles are being designed and propulsion systems are being improved upon, it is sometimes necessary to adopt new and innovative techniques for manufacturing hardware. With a heavy emphasis on cost reduction and improvements in manufacturing time, manufacturing techniques such as Direct Metal Laser Sintering (DMLS) are being adopted and evaluated for their use on J-2X, with hopes of employing this technology on a wide variety of future projects. DMLS has the potential to significantly reduce the processing time and cost of engine hardware, while achieving desirable material properties by using a layered powder metal manufacturing process in order to produce complex part geometries. Marshall Space Flight Center (MSFC) has recently hot-fire tested a J-2X gas generator discharge duct that was manufactured using DMLS. The duct was inspected and proof tested prior to the hot-fire test. Using the Workhorse Gas Generator (WHGG) test setup at MSFC?s East Test Area test stand 116, the duct was subject to extreme J-2X gas generator environments and endured a total of 538 seconds of hot-fire time. The duct survived the testing and was inspected after the test. DMLS manufacturing has proven to be a viable option for manufacturing rocket engine hardware, and further development and use of this manufacturing method is recommended.

Betts, Erin M.↗

Using Innovative Technologies for Manufacturing Rocket Engine Hardware

Many of the manufacturing techniques that are currently used for rocket engine component production are traditional methods that have been proven through years of experience and historical precedence. As the United States enters into the next space age where new launch vehicles are being designed and propulsion systems are being improved upon, it is sometimes necessary to adopt innovative techniques for manufacturing hardware. With a heavy emphasis on cost reduction and improvements in manufacturing time, rapid manufacturing techniques such as Direct Metal Laser Sintering (DMLS) are being adopted and evaluated for their use on NASA s Space Launch System (SLS) upper stage engine, J-2X, with hopes of employing this technology on a wide variety of future projects. DMLS has the potential to significantly reduce the processing time and cost of engine hardware, while achieving desirable material properties by using a layered powder metal manufacturing process in order to produce complex part geometries. Marshall Space Flight Center (MSFC) has recently hot-fire tested a J-2X gas generator (GG) discharge duct that was manufactured using DMLS. The duct was inspected and proof tested prior to the hot-fire test. Using a workhorse gas generator (WHGG) test fixture at MSFC's East Test Area, the duct was subjected to extreme J-2X hot gas environments during 7 tests for a total of 537 seconds of hot-fire time. The duct underwent extensive post-test evaluation and showed no signs of degradation. DMLS manufacturing has proven to be a viable option for manufacturing rocket engine hardware, and further development and use of this manufacturing method is recommended.

Betts, E. M.↗

Forming complex cavities in clear plastic

Metal casting "lost wax" process is used to mold plastic parts. Highly economical technique produces optically-clear components of complex shapes, which can be used in complex combustion and manifold systems.

Riley, T.↗