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Results for “Powder Bed Fusion”

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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Texture evolution during processing and post-processing of maraging steel fabricated by laser powder bed fusion

Abstract In this study, the evolution of solidification texture during LPBF of Ti-free grade 300 maraging steel, and its effect on texture development during subsequent post-fabrication heat treatments was characterized using Electron Backscatter Diffraction (EBSD). It was found that in the as-fabricated state, no texture was observed in the room temperature martensitic phase. However, the reconstructed parent austenite phase displayed a Cube texture with a minor fraction of Rotated Goss texture. During subsequent aging treatments involving two different routes, namely direct aging of the as-fabricated samples, and conventional solution treatment + aging of the as-fabricated samples, significant changes in the texture components of parent austenite were observed, whereas no changes in texture were observed in the room temperature martensitic phase. During direct aging, it was found that with an increase in the aging temperature up to 520 °C, the texture components of the parent austenite changed from Cube/Rotated Goss to Brass, whereas during the conventional solution treatment and aging cycle, interestingly a change in texture component to rotated copper was observed. The transitions in texture components have been discussed using the concepts of recrystallization and twinning in austenite during annealing and/or aging, and strain energy release maximization (SERM) theory. Furthermore, the importance of these preferred orientations on the mechanical properties was quantified using transformation potential diagrams.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Melt Pool characteristics on surface roughness and printability of 316L stainless steel in laser powder bed fusion

Purpose Surface quality and porosity significantly influence the structural and functional properties of the final product. This study aims to establish and explain the underlying relationships among processing parameters, top surface roughness and porosity level in additively manufactured 316L stainless steel. Design/methodology/approach A systematic variation of printing process parameters was conducted to print cubic samples based on laser power, speed and their combinations of energy density. Melt pool morphologies and dimensions, surface roughness quantified by arithmetic mean height (Sa) and porosity levels were characterized via optical confocal microscopy. Findings The study reveals that the laser power required to achieve optimal top surface quality increases with the volumetric energy density (VED) levels. A smooth top surface (Sa < 15 µm) or a rough surface with humps at high VEDs (VED > 133.3 J/mm 3 ) can serve as indicators for fully dense bulk samples, while rough top surfaces resulting from melt pool discontinuity correlate with high porosity levels. Under insufficient VED, melt pool discontinuity dominates the top surface. At high VEDs, surface quality improves with increased power as mitigation of melt pool discontinuity, followed by the deterioration with hump formation. Originality/value This study reveals and summarizes the formation mechanism of dominant features on top surface features and offers a potential method to predict the porosity by observing the top surface features with consideration of processing conditions.

Engineering↗
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 OSTI2024

Data for: Ultrasonic characterization of material heterogeneities in stainless steel parts fabricated by powder bed fusion

These are the raw ultrasonic waveform files and nanoindentation measurements for three additively manufactured 316L stainless steel components with different fabrication parameters. Each part's length is divided into four segmented regions where their fabrication energy densities change. Part V+ begins at 33 J/mm^3 and increases in energy density by 3 J/mm^3 with each segment. Part C remains at a constant 33 J/mm^3 throughout the part. Part V- begins at 33 J/mm^3 and decreases in energy density by 3 J/mm^3 with each segment. We have found that the ultrasonic waves in regions with higher energy densities will traverse more quickly, as shown by the shorter time of flight, and vice versa. Similarly, nanoindentation measurements of reduced modulus and hardness follow this trend. We have measured the direction in which the parts were fabricated (build direction) and the segmented regions that are perpendicular to the build direction (transverse directions). The build direction longitudinal wave velocity measurements are considerably lower than their transverse direction counterparts, indicating anisotropy between the two directions. In Part C, we have removed material from one of its surfaces and recorded its ultrasonic and nanoindentation measurements with each material removal iteration. Changes in the material properties are more prominent by nanoindentation, suggesting material heterogeneity between the part's surface and interior. The README.txt file has information on how to navigate the files and process the data.

Anisotropy↗
DOE OSTI2022

Porosity Determination and Classification of Laser Powder Bed Fusion AlSi10Mg Dogbones Using Machine Learning [Slides]

Angular pores (lack of fusion) pores are more detrimental to the health of the part due to induced stress concentrations. Three types of porosity found in AM parts: keyhole porosity, gas porosity, and lack of fusion porosity. In this research, we address the question, "Which machine learning and/or machine vision techniques work best to segment porosity and determine the type of porosity observed in the sample?"

42 ENGINEERING↗