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Results for “additively manufactured components”

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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Build plate conduction cooling for thermal management of wire arc additive manufactured components

Wire arc additive manufacturing (WAAM) allows for quick, large component manufacturing with fast deposition rates while leveraging readily available wire feedstock that is significantly cheaper than metal powder. However, the increased deposition rate of this process requires enhanced thermal management as failures can occur due to overheating. A common strategy to mitigate overheating is to dwell, or pause, between individual layers; however, this can significantly increase build times and eliminate the advantage of additive manufacturing being able to manufacture components quickly. To help mitigate this issue, this study explores the use of active cooling to maintain process control and to decrease overall build time. In this work, conductive cooling applied to either the bottom or side of the print substrate was explored. Results from this study showed that bottom build plate active cooling can be used to decrease dwell times by up to 50% and decrease cool-down to room temperature after the building process by up to 75%. Results from this study demonstrate that the use of active cooling strategies for WAAM can be used for better thermal control over the process and should be further investigated.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Scientific Foundations and Approaches for Qualification of Additively Manufactured Structural Components

Additive manufacturing (AM) maintains a wide process window that enables complex designs otherwise unattainable via conventional production technologies. However, the lack of confidence in qualifying AM parts that leverage AM process–structure–property–performance (PSPP) relationships stymies design optimization and adoption of AM. While continuing efforts to map fundamental PSPP relationships that cover the potential design space, we first need pragmatic and then long-term solutions that overcome challenges associated with qualifying AM-designed parts. Two pragmatic solutions include: (1) AM material specifications to substantiate process reproducibility, and (2) component risk categorization to associate system risk relative to part performance and required part quality. A novel qualification paradigm under development involves efficient prediction of part performance over wide-ranging PSPP relationships through targeted testing and computational simulation. Here this paper describes projects at Sandia National Laboratories on PSPP relationship discovery, these pragmatic approaches, and the novel qualification approach.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ductile coatings on additive manufactured components

A method of forming a coated component using an additive manufacturing system including building a body portion of the component on a build plate. An outer surface of the body portion can include an indentation resulting from the additive manufacturing system. The method further includes performing at least one post-build process on the body portion. The method yet further includes forming a coating layer on an outer surface of the processed body portion. The coating layer may surround a portion of the body component and may impregnate the indentation. A thickness of the coating layer may be a function of at least one of surface roughness, size of the indentation, or a diameter of particles used to build the additive manufactured bracket.

Racca, Stephen D.↗
DOE OSTI2025

DETERMINATION OF THE SOLID-STATE RESISTANCE-WELDABILITY OF ADDITIVELY MANUFACTURED 304L STAINLESS STEEL

Additive manufacturing of pressure-containing boundaries is of interest to numerous industries, so a project was initiated to develop several different methods to join and weld additively manufactured materials. The approach investigated in this study was a low energy, solid state spot weld. This general approach has been routinely used for conventionally prepared tubing and is now being expanded to additively manufactured components. Additively manufactured 304L stainless steel sheets, semi-tubes, and tubes were resistance spot welded and compared to comparable welds in conventionally manufactured tubing. Radiographic computed tomography and metallography were used to evaluate the suitability of the welds using three criteria: weld closure length, thickness, and width. All additively manufactured test welds closely matched the conventional tubing for these criteria

additive manufacturing↗
DOE OSTI2024

Ultrasonic Characterization of Material Properties in Metal Components Additively Manufactured by Powder Bed Fusion

We present the methodology for using pulsed-echo ultrasound to characterize the properties of additively manufactured (AM) metal components and their response to changes in the fabrication settings. We show how to accurately characterize anisotropy in these properties and when such characterization can be performed noninvasively. Our approach, when applied to 3D-printed stainless steel samples, reveals a significant heterogeneity between the surface and internal properties of the AM part and the anisotropy in material properties in the build and transverse directions.

Walton, Kenneth↗
DOE OSTI2022

Alternating chempolishing and electropolishing for interior and exterior surface finishing of additively manufactured (AM) metal components

Additively manufactured (AM) components’ surface finishing is crucial in adopting them for intended applications in challenging environments involving fatigue, corrosion, high temperature, and nuclear radiation. In our prior research, chempolishing (C) was utilized as an electroless etching process that uniformly smoothens complex AM components’ accessible interior and exterior surfaces (Tyagi et al. Additive Manufacturing, 25:32–38, 22). A wide range of electropolishing (E) has been demonstrated for AM surface finishing. However, electropolishing can impact a surface that can be juxtaposed to counter electrode and can yield a very smooth surface to sub-micrometer level roughness. However, a knowledge gap exists about the impact of applying both approaches on the same surface one after another and what new advantages may arise because of combining two methods. This paper uses dual-stage liquid-based surface finishing strategies produced by alternating the chempolishing (C) and electropolishing (E) steps. Two dual-stage surface finishing approaches, i.e., chempolishing followed by electropolishing (CE) and electropolishing followed by chempolishing (EC), were performed on the 316 stainless AM steel component. Impacts of EC and CE approaches were compared with single-stage C and E surface finishing approaches. An optical microscope and mechanical profilometer were utilized to investigate the wide range of surface roughness parameters. CE and EC produced Ra ~ 1.4 µm and ~ 1.6 µm, respectively. Surface roughness on CE- and EC-treated AM samples was lower than those individually treated by C and E approaches. Scanning electron microscopy provided further insights into the microstructural difference between CE- and EC-treated AM samples. This paper reports a liquid contact angle study on CE- and EC-treated AM samples to provide insights into the relative difference in surface energy that is crucial for making coatings on AM parts. A spectroscopic reflectance study was also employed to register the difference in physical properties of AM components treated with CE and EC approaches. Further, this study reveals industrially practicable interior and exterior surface finishing approaches for complex AM metal components that require minimum tooling and real-time process monitoring.

36 MATERIALS SCIENCE↗
DOE OSTI2022

In-process, layer-by-layer non-destructive testing of additive manufactured components using linear and nonlinear vibrational resonance

Provided is an additive manufacturing system capable of performing in-process, layer-by-layer non-destructive testing, the additive manufacturing system including: a plate for producing a part thereon; a transducer attached to the plate and configured to induce vibrations in the part; and a laser vibrometer configured to detect a vibrational response of the part to determine whether defect and/or anisotropy exists within the part.

Remillieux, Marcel↗
DOE OSTI2025

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗
DOE OSTI2023

Scalable in situ non-destructive evaluation of additively manufactured components using process monitoring, sensor fusion, and machine learning

Laser Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) is among the metal 3D printing technologies most broadly adopted by the manufacturing industry. However, the current industry qualification paradigm for critical-application L-PBF parts relies heavily on expensive non-destructive inspection techniques, which significantly limits the use-cases of L-PBF. In situ monitoring of the process promises a less expensive alternative to ex situ testing, but existing sensor technologies and data analysis techniques struggle to detect sub-surface flaws (e.g., porosity and cracking) on production-scale L-PBF printers. In this work, an in situ NDE (INDE) system was engineered to detect subsurface flaws detected in X-Ray Computed Tomography (XCT) directly from process monitoring data. A multilayer, multimodal data input allowed the INDE system to detect numerous subsurface flaws in the size range of 200–1000µm using a novel human-in-the-loop annotation procedure. Furthermore, a framework was established for generating probability-of-detection (POD) and probability-of-false-alarm (PFA) curves compliant with NDE standards by systematically comparing instances of detected subsurface flaws to post-build XCT data. Here, we also introduce for the first time in the AM in situ sensing literature the a 90/95 – the flaw size corresponding to a 90% detection rate on the lower 95% confidence interval of the POD curve. The INDE system successfully demonstrated POD capabilities commensurate with traditional NDE methods. Traditional ML performance metrics were also shown to be inadequate for assessing the ability of the INDE system’s flaw detection performance. It is the hope of the authors that future studies will adopt the POD and PFA approach outlined here to provide better insight into the utility of process monitoring for AM.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Model-Based Ultrasonic Signal Processing for the Nondestructive Evaluation of Additive Manufacturing Components

Ultrasonic testing (UT) for nondestructive evaluation (NDE) is a critical entity necessary to resolve both the quality and precision questions of complex parts evolving from the innovative additive manufacturing (AM) process. This modality provides the essential quantitative information for acceptance and potential flaw detectionof the part under investigation. A primary ingredient in UT besides the required precision robotic hardware for theacquisition of high quality measurement data is the underlying signal processing. It is here that much of the system performance capability resides. In this report,we discuss the basic steps in UT signal processing along with current and future capabilities that must be achieved in order to satisfy the critical demands created by the AM process.

42 ENGINEERING↗
DOE OSTI2024

Improving Additive Manufactured Component Performance through Multi-Scale Microstructure Simulation and Process Optimization

The purpose of this project was to utilize computational tools to understand the relationships between processing, microstructure, and properties for additively manufactured (AM) aluminum alloys for automotive applications, and to provide an engineering solution for helping to optimize process conditions. The project leverages ORNL developments in computational modeling, including AM process modeling, phase-field based microstructure evolution predictions, and data analytics techniques for mapping process conditions to material outcomes. The project utilized an Al-Cu-Mn-Zr alloy as a model material for studying formation of defects and microstructural features in response to variations in process conditions. Based on both pre-existing experimental data and simulation results, statistical process maps were constructed to identify regions of process space with minimal defect formation and advantageous microstructures and properties. The software tools used for this purpose were successful disseminated to GM, who were able to successful compile the relevant HPC codes within their own computing ecosystem and perform initial calculations to reproduce ORNL results.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Fabricating and Testing Additively Manufactured Components for Tritium Service Consideration

This SRTE PDRD sponsored project produced test articles, tooling, and training articles for evaluation. In addition, the hydrogen compatibility of the alloys that can be readily produced by the Arcam A2X was tested. During the evaluation it was determined that the mechanical properties were more sensitive to build plate location than hydrogen exposure. Hydrogen pressure – volume-temperature experiments showed that the as-fabricated samples did not absorb hydrogen readily, but activated samples did.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Electrical-Discharge-Machining Contamination Removal from Metal Additively Manufactured Components

The use of an electrochemical dissolution process is shown to remove the recast layer contamination from the surfaces of electrical-discharge-machining cut components, as well as the interior exposed surfaces of the structure. The solution chemistry, cell potential, and exposure time are all relevant interdependent variables. Optimization of the electrode geometry should be made for each type of component. For the case of Cu-Zn recast contamination of 300-series alloy components, surface composition analysis indicates that complete electrochemical dissolution is achieved using a dilute solution of nitric acid (HNO 3 ). For example, electrochemical dissolution of the Cu-Zn recast is accomplished at 1.2 V cell potential using a 20% nitric solution and an exposure time of 4 h. The use of a nitric acid bath was specifically chosen since it’s chemically compatible and will not degrade the host alloy or the component. In sum, an electrochemically driven dissolution process can be tailored to remove of the recast contamination without affecting the integrity of the host component structure and its dimensional tolerances.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗