Abstract
In this research, the impact toughness of powder bed based additively manufactured 304L stainless steel was investigated. Charpy specimens were built in vertical, horizontal and inclined (45⁰) orientations to investigate the variation in toughness with build direction. These specimens were tested in as-built and machined conditions. A significant difference in toughness was observed with varying build directions. The lowest toughness values were recorded when the notch was oriented in line with the interlayer boundary. The highest toughness was recorded when the notch was perpendicular to the interlayer boundary. A significant scatter in toughness values was also observed. The variation and distribution among the toughness values were modeled by performing 3-parameter Weibull fits. The performance and variation of the additively manufactured 304L were also compared with the toughness values of wrought 304 stainless. The additively manufactured material was observed to be significantly less tough and more variant in comparison to wrought material.
Recommended Citation
S. Karnati et al., "Characterization of Impact Toughness of 304L Stainless Steel Fabricated through Laser Powder Bed Fusion Process," Proceedings of the 29th Annual International Solid Freeform Fabrication Symposium (2018, Austin, TX), pp. 1336 - 1346, University of Texas at Austin, Aug 2018.
Meeting Name
29th Annual International Solid Freeform Fabrication Symposium -- An Additive Manufacturing Conference, SFF 2018 (2018: Aug. 13-15, Austin, TX)
Department(s)
Mechanical and Aerospace Engineering
Second Department
Materials Science and Engineering
Research Center/Lab(s)
Intelligent Systems Center
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Publication Date
15 Aug 2018
Comments
This work has been funded by Honeywell Federal Manufacturing & Technologies under Contract No. DE-NA0002839 with the U.S. Department of Energy.
The supports from National Science Foundation Grants CMMI-1625736, and the Intelligent Systems Center (ISC) at Missouri S&T are greatly appreciated.