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3D characterization of defects in deep-powder-bed manufactured Ti-6Al-4V and their influence on tensile properties

journal contribution
posted on 2024-11-01, 11:35 authored by Joe ElambasserilJoe Elambasseril, S Lu, Y Ning, Nan Liu, Jian Wang, Milan BrandtMilan Brandt, Huiping Tang, Ma QianMa Qian
Deep-powder-bed additive manufacturing (AM) can lead to distinctive microstructural features. In this study, 300-mm long cylindrical rods (12-mm diameter) of Ti–6Al–4V were vertically built to the limit height of a commercial selective electron beam melting (SEBM) system for quantitative three-dimensional (3D) characterization of the defects by X-ray micro-computed tomography (μ-CT). Detailed μ-CT data from 18,337 consecutive slices revealed a strong dependence of defect characteristics on build height, including defect volume, population, sphericity, major axis length, depth and orientation angle. The first 100-mm build exhibited the worst presence of defects by each measurement, while the middle and last 100-mm builds contained much fewer defects, especially the last 100-mm build, which was free of lack-of-fusion defects (sphericity < 0.5). As a result, the first 100-mm build displayed 50% lower reduction of area and 20% lower strain-to-fracture than the last 100-mm build, while the tensile strengths varied within just ±3%. An outer 3-mm thick ring and a central 1.5-mm diameter region were found to contain substantially less defects along the 300-mm build height. The dependence of defect features on build height was attributed to the existence of an upward temperature gradient during SEBM. The 3D defect features revealed by μ-CT along the build height provide important implications for deep-powder-bed AM by SEBM.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1016/j.msea.2019.138031
  2. 2.
    ISSN - Is published in 09215093

Journal

Materials Science and Engineering A

Volume

761

Number

138031

Start page

1

End page

10

Total pages

10

Publisher

Elsevier B.V.

Place published

Netherlands

Language

English

Copyright

© 2019 Elsevier B.V. All rights reserved.

Former Identifier

2006092867

Esploro creation date

2020-06-22

Fedora creation date

2019-08-06

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