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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Correlation approach for quality assurance of additive manufactured parts based on optical metrology

Surface topography and surface finish are two significant factors for evaluating the quality of products in additive manufacturing (AM). AM parts are fabricated layer by layer, which is quite different from traditional formative or subtractive methods. Despite rapid progress in additive manufacturing and associated optical metrology for quality control and in-situ monitoring, limited research has been conducted to investigate the reliability of 3D surface measurement data. The surface topologies scanned by multiple optical systems demonstrated significant differences due to varying sampling mechanisms, resolutions, system noises, etc. The 3D datasets should be trustworthy in order to extract parameters for quality assurance or feedback control from 3D surface measurements. In this paper, we set up new standards to evaluate the reliability of 3D surface measurement data and analyze the variation in the topographical profile. In this study, two non-contact optical methods based on Focus Variation Microscopy (FVM) and Structured Light System (SLS) were adopted to measure the surface topography of the target components. The two optical metrology systems generated two entirely different point cloud datasets. Statistical methods were applied to test the difference between the data obtained from the two systems. By using a data analytics approach for comparison, it was found that the surface roughness estimated from the point cloud data sets of FVM and SLS has no significant difference, though the point cloud data sets were completely different. This paper provides standard validation approach to evaluate the plausibility of metrology data from in-situ real-time surface analysis for process planning of AM.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Evaluation of HCF strength of Alloy 625 with non-optimum additive manufacturing process parameters

An extensive experimental program was undertaken to generate the process-structure-HCF property data for additive-manufactured Alloy 625. Round tensile and flat dog-bone HCF specimens were fabricated using a laser powder bed fusion process. Several builds were fabricated with different processing parameters. The fatigue strengths were determined using a step-test method and fracture surfaces were characterized to identify the critical microstructure feature associated with the formation of the fatigue crack. Finally, a fracture mechanics-based methodology using fatigue crack growth data measured on a wrought alloy is shown to provide conservative estimates of the HCF lives for the additive-manufactured alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Additive Manufacturing of Corrosion Resistant UHTC Materials for Chloride Salt-to-sCO2 Brayton Cycle Heat Exchangers

The objectives of the project include: (1) screen high-purity, high density ultra-high-temperature ceramics (UHTCs) for chloride salt corrosion resistance, (2) develop binder-jet additive manufacturing and sintering for ZrB 2 -MoSi 2 blends using literature and experiments to demonstrate feasibility, and (3) evaluate chloride salt corrosion resistance of additively manufactured ZrB 2 -MoSi 2 . These initial objectives support the development of a durable and reliable ultra-compact high-efficiency salt-to-sCO 2 heat exchanger for closed-loop Brayton power cycles based on corrosion resistant, high-strength, thermally conductive UHTC materials and novel designs enabled by additive manufacturing. The UHTC materials are also abrasion resistant so that they could be applicable to all three thermal carrier media pathways identified in the CSP Gen3 Roadmap.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Development of a high-temperature Inconel 625 heat exchanger by model design and binder jetting additive manufacturing

A nickel-based Inconel 625 superalloy heat exchanger for high-temperature applications was developed via binder jetting additive manufacturing. The material properties were characterized first on printed and sintered parts. Two sintering temperatures were used to investigate the effects of the temperature on densification and microstructure. For channel geometry design, the heat transfer capabilities of the heat exchanger were optimized for the cross-section geometry of fluid flow channels in a counterflow configuration, and a stress analysis was conducted to investigate the effects of channel geometry. After headers were incorporated into the heat exchanger as a one-piece component, a prototype was printed. A complete depowdering was achieved via compressed air blowing, and sintering was performed with the developed profile. Ultimately, a one-piece heat exchanger with a nearly full density was obtained. Heat transfer tests were performed on this unit, and the results were compared with those from the simulations. In this study, systematic processes were developed for an additively manufactured Inconel-based heat exchanger for high-pressure, high-temperature heat transfer applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Impact of Additive Manufacturing on Internal Cooling Channels With Varying Diameters and Build Directions

Abstract The use of additive manufacturing (AM) processes, such as direct metal laser sintering, provides the design freedom required to incorporate complex cooling schemes in gas turbine components. Additively manufactured turbine components have a range of cooling feature sizes and, because of the inherent three-dimensionality, a wide range of build angles. Previous studies have shown that AM built directions influence internal channel surface roughness that, in turn, augment heat transfer and pressure loss. This study investigates the impact of AM on channel feature size and builds direction relative to tolerance, surface roughness, pressure losses, and convective cooling. Multiple AM coupons were built from Inconel 718 consisting of channels with different diameters and a variety of build directions. An experimental rig was used to measure pressure drop to calculate friction factor and was used to impose a constant surface temperature boundary condition to collect Nusselt number over a range of Reynolds numbers. Significant variations in surface roughness and geometric deviations from the design intent were observed for distinct build directions and channel sizes. These differences led to notable impacts in friction factor and Nusselt number augmentations, which were a strong function of build angle.

Engineering↗
DOE OSTI2022

Processing and Archiving Camera Data Effectively for Operando Neutron Measurement of Metal Additive Manufacturing

As the name suggests, The Operando Neutron Measurement of Metal Additive Manufacturing project conducted by ORNL’s Manufacturing Demonstration Facility (MDF) is experimenting with advanced additive metal manufacturing techniques while analyzing the process using the Spallation Neutron Source’s (SNS) beamline. As part of this experiment, the MDF is seeking to employ 2 XIMEA visible light cameras and a single infrared camera to analyze and correct manufacturing in real-time. The MDF requires a solution for capturing the high-resolution data feed from the cameras with compression while preserving enough detail for their software to detect and correct errors in real time. Our solution was to develop a Robot Operating System (ROS) driver to feed the camera data into ROS. From ROS, the feed is compressed and temporarily stored locally to a stripped 4 NVMe SSD RAID array. Post-experiment, the data is transitioned to long-term storage for archival purposes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Phase stability in cast and additively manufactured Al-rich Al-Cu-Ce alloys

Additively manufactured (AM) eutectic Al alloy systems have been studied extensively for advantageous thermal stability and mechanical properties due to their refined microstructures. Al-Cu-Ce alloys are one subset of these AM eutectic alloys. Here we studied phase stability in AM Al-Cu-Ce alloys and compared it to that of conventionally cast ones. A new phase, Al 8 Cu 3 Ce, was identified in the microstructures of both AM and cast Al-Cu-Ce alloys. This Al 8 Cu 3 Ce phase was not previously included on experimental or thermodynamically calculated phase diagrams of the Al-Cu-Ce system. Therefore, we performed additional thermodynamic modeling of the system. These models were experimentally validated with cast and subsequently heat-treated Al-Cu-Ce alloys. We found that despite the refined microstructure of the AM alloys, the phases formed were consistent with the cast alloys, suggesting that AM processing did not significantly alter the formation and stability of phases from that in the conventional alloys. In conclusion, this work has resolved inconsistent previous descriptions of the Al-Cu-Ce ternary phase diagram in the Al-rich region and resulted in the addition of the Al 8 Cu 3 Ce as an equilibrium phase above 500 °C.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Using pyrometry to identify porosity in additively manufactured structures

A method and apparatus for identifying porosity in a structure made by an additive manufacturing process in which a laser is scanned across layers of material to form the structure. Pyrometry data comprising images of the layers acquired during additive manufacturing of the structure is received. The pyrometry data is used to generate temperature data comprising estimated temperatures of points in the layers in the images of the layers. The temperature data is used to identify shapes fit to high temperature areas in the images of the layers. Conditions of the shapes fit to the high temperature areas in the images of the layers are identified. Outlier shapes are identified in the shapes fit to the high temperature areas in the images of the layers using the conditions of the shapes.

Mitchell, John A.↗
DOE OSTI2021

Geometrical defect detection for additive manufacturing with machine learning models

This study proposed a scheme based on Machine Learning (ML) models to detect geometric defects of additively manufactured objects. The ML models are trained with synthetic 3D point clouds with defects and then applied to detect defects in actual production. Using synthetic 3D point clouds rather than experimental data could save a huge amount of training time and costs associated with many prints for each design. Besides distance differences of individual points between source and target point clouds, this scheme uses a new concept called “patch” to capture macro-level information about nearby points for ML training and implementation. Numerical comparisons of prediction results on experimental data with different shapes showed that the proposed scheme outperformed the existing Z-difference method in the literature. Five ML methods (Bagging of Trees, Gradient Boosting, Random Forest, K-nearest Neighbors and Linear Supported Vector Machine) were compared under various conditions, such as different point cloud densities and defect sizes. Bagging and Random Forest were found the two best models regarding predictability; and the right patch size was found to be at 20. The proposed ML-based scheme is applicable to in-situ defect detection during additive manufacturing with the aid of a proper 3D data acquisition system.

Additive manufacturing↗
DOE OSTI2021

Enhanced biomechanical performance of additively manufactured Ti-6Al-4V bone plates

As the global trauma fixation devices market expands rapidly, it is imperative to improve the production of fixation devices through enhanced design accuracy and fit for best performance and maximum patient comfort. Selective laser melting (SLM) is one of the mature additive manufacturing methods, which provides a viable route for the rapid production of such devices. In this work, the ability of SLM to produce near-net-shape parts, as desired for medical implants, was utilized for the fabrication of bone plates from Ti-6Al-4V alloy powder. Martensitic microstructure obtained after the printing of alloy resulted in poor ductility, limiting its application in the field of orthopedics. A specially designed repeated cyclic heating and cooling close to but below the β-transus was used to transform from acicular to a bimodal microstructure without the need for plastic deformation prior to heat treatment for improving the ductility. Bone plates subjected to this heat treatment were mechanically tested by means of tensile and 3-point bend tests and demonstrated large improvement in ductility, and the values were comparable to those similar plates prepared from wrought alloy. Other important properties required for implants were assessed, such as corrosion resistance in simulated body fluid and cytocompatibility in vitro using MC3T3-E1 cells. These results for the bone plate after heat treatment were excellent and similar to those of the additively manufactured and wrought plates. Taken together, the performance of the additively manufactured bone plates after subjecting to heat treatment was similar to those of bone plate manufactured using wrought alloy. These results have important implications for the fabrication of patient-specific metallic orthopedic devices using SLM without compromising their biomechanical performance by subjecting them to a tailored heat treatment.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Additive manufacturing of soft magnetic high entropy alloys: A review

Additive manufacturing (AM) offers unique advantages in fabricating soft magnetic high-entropy alloys (HEAs), enabling precise control over material properties and the development of advanced components for applications such as magnetic cores, electric motors, and transformers. These HEAs exhibit superior magnetic performance, mechanical strength, and thermal stability, making them highly suitable for modern electronics applications. Here, this review explores the advancements in AM-processed soft magnetic HEAs, including ongoing research on process optimization, tailored microstructures, and enhanced magnetic properties. It emphasizes the importance of understanding the correlations between AM process parameters, resulting microstructures, and the soft magnetic properties of HEAs. By summarizing the state of the field, we provide insights into current progress and highlight future research trends, focusing on the potential for industrial adoption and advancements in this emerging area.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Accurate additive manufacturing of lightweight and elastic carbons using plastic precursors

Despite groundbreaking advances in the additive manufacturing of polymers, metals, and ceramics, scaled and accurate production of structured carbons remains largely underdeveloped. This work reports a simple method to produce complex carbon materials with very low dimensional shrinkage from printed to carbonized state (less than 4%), using commercially available polypropylene precursors and a fused filament fabrication-based process. The control of macrostructural retention is enabled by the inclusion of fiber fillers regardless of the crosslinking degree of the polypropylene matrix, providing a significant advantage to directly control the density, porosity, and mechanical properties of 3D printed carbons. Using the same printed plastic precursors, different mechanical responses of derived carbons can be obtained, notably from stiff to highly compressible. This report harnesses the power of additive manufacturing for producing carbons with accurately controlled structure and properties, while enabling great opportunities for various applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

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↗
NASA NTRSDate not supplied

Robust Metal Additive Manufacturing Process Selection and Development for Aerospace Components

Metal additive manufacturing (AM) is a generic term that captures a variety of fabrication techniques. Each of these manufacturing process has unique advantages, applications for use, and challenges. The most common AM processes in use include Powder Bed Fusion (PBF) and Directed Energy Deposition (DED) as well as many solid state processes. While detailed research has been conducted among many of the processes including parameters and material properties, navigating which processes are best to select is difficult as it is based on component requirements. The focus of this presentation is to provide an overview of considerations for each of metal AM process selection for aerospace components based on various attributes. These attributes include geometric considerations, metallurgical characteristics, cost basis, post-processing and maturity of the processes. The data for these trade selections are based on studies that NASA as performed internally and with academic and industry partners. These studies include multiple AM build experiments to evaluate (1) geometric variations and constraints within the processes, (2) alloy characterization and mechanical testing, (3) pathfinder component development and hotfire evaluations, and (4) certification approaches. This presentation summarizes these results and meant to introduce various considerations when designing a metal AM component.

Additive Manufacturing↗
DOE OSTI2022

Anisotropic thermal behavior of extrusion-based large scale additively manufactured carbon-fiber reinforced thermoplastic structures

Large format additive manufacturing (AM) enables rapid manufacturing of large parts and structures with minimum waste in material and energy. Extrusion-based AM deposition processes provide parts with highly anisotropic thermal properties, which are not typically reflected in textbook values for these materials. In order to develop accurate models that describe the directionally dependent thermal behavior of these materials in processing and service, accurate measurements of specific heat capacity and thermal conductivity are required. Here, this work characterizes, documents, and analyzes the effect of the anisotropic nature of the extrusion-based deposition process on the specific heat capacity and thermal conductivity of the resulting AM products. All measurements were made over a temperature range of 20–180°C using the transient plane source technique, also referred to as the hot disk technique. Three of the most commonly used large format AM feedstock materials that utilize carbon fiber reinforcement were examined in this work: acrylonitrile butadiene styrene, polyphenylene sulfide and polyphenylsulfone. Finally, these findings can serve as a thermal design/process guideline for future large format AM applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Corrosion Testing Needs and Considerations for Additively Manufactured Materials in Nuclear Reactors

The Advanced Materials and Manufacturing Technologies (AMMT) program within the Department of Energy, Office of Nuclear Energy (DOE-NE) has developed its current recommendation for its corrosion testing strategy to deploy additively manufactured (AM) materials in advanced nuclear reactors. Additive manufacturing technologies have developed rapidly in recent years, creating new opportunities and challenges for the nuclear industry. To adopt AM technologies, the corrosion performance of AM materials needs to be adequately evaluated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Dynamic Scaling Analysis of Accelerated Irradiation Testing on Additive Manufacturing Materials by Positron Annihilation

The timely applications of Additive Manufacturing (AM) materials in nuclear environments require accelerated irradiation tests, mainly ion irradiation to enable rapid prototyping. Low dose ion irradiation would cause sub-nanostructure changes by generation of lattice defects, vacancies, vacancy clusters and voids and void swelling caused by cellular dislocations. Positron Annihilation Lifetime (PAL), a novel technology, sensitive towards sub-nanostructure morphology with high accuracy (about 10-7 vacancy per atom), supported by Transition Electron Microscope (TEM) would be applied to identify the type and total size of the defects. The subsequent PAL measurements and TEM surface studies would be followed by PAL analysis that includes sophisticated trapping model. The PAS results would become an input to dynamic scaling analysis (that predicts radiation effects from low dose studies for high dose effects), which incorporate mean-field theory model. The final effect is an in-depth understanding of the microstructure evolution of AM materials under ion irradiation which can be extrapolated to the studies of neutron irradiation, since ion-irradiation takes less time and do not cause the irradiation hazard. The working hypothesis is that PAL technology, that have excellent sensitivity to low-defect concentration would help to identify ion-induced material damage on the atomic and nano-scale level, which then could be extrapolated to understand the neutron damage better.

accelerated irradiation testing↗
DOE OSTI2020

Sensitivity of Thermal Predictions to Uncertain Surface Tension Data in Laser Additive Manufacturing

To understand the process-microstructure relationships in additive manufacturing (AM), it is necessary to predict the solidification characteristics in the melt pool. This study investigates the influence of Marangoni driven fluid flow on the predicted melt pool geometry and solidification conditions using a continuum finite volume model. A calibrated laser absorptivity was determined by comparing the model predictions (neglecting fluid flow) against melt pool dimensions obtained from single laser melt experiments on a nickel super alloy 625 (IN625) plate. Using this calibrated efficiency, predicted melt pool geometries agree well with experiments across a range of process conditions. When fluid mechanics is considered, a surface tension gradient recommended for IN625 tends to overpredict the influence of convective heat transfer, but the use of an intermediate value reported from experimental measurements of a similar nickel super alloy produces excellent experimental agreement. Despite its significant effect on the melt pool geometry predictions, fluid flow was found to have a small effect on the predicted solidification conditions compared to processing conditions. We find that this result suggests that under certain circumstances, a model only considering conductive heat transfer is sufficient for approximating process-microstructure relationships in laser AM. Extending the model to multiple laser passes further showed that fluid flow also has a small effect on the solidification conditions compared to the transient variations in the process. Furthermore, limitations of the current model and areas of improvement, including uncertainties associated with the phenomenological model inputs are discussed.

36 MATERIALS SCIENCE↗