Influence of Porosity on the Thermal, Electrical, and Mechanical Performance of Selective Laser Melted Stainless Steel
Abstract
This study verifies a novel approach to determine the thermal conductivity developed by the first two authors (Tomanek and Stutts) [1] as applied to additively manufactured selective laser melted stainless steel 304L specimens having a range of 1.4 to seven percent porosity. The selective laser melting technique is highly dependent on the process parameters used, unlike traditionally manufactured materials, and can cause the thermal, electrical, and mechanical properties to vary considerably from the bulk alloy. For this study, the thermal conductivity and several auxiliary parameters were estimated using a Levenberg-Marquardt nonlinear least squares algorithm. The parameter estimation used a model of a one-dimensional transient heat diffusion PDE with a closed-form solution of a slender rod under forced convection. In addition to the thermal conductivity's dependency on porosity, the correlated porosity dependency on electrical conductivity was examined. The results were corroborated by mechanical tensile tests as well. The stainless steel 304L selective laser melted specimens saw a degradation of mechanical, thermal, and electrical performance with increasing porosity.
Recommended Citation
L. B. Tomanek et al., "Influence of Porosity on the Thermal, Electrical, and Mechanical Performance of Selective Laser Melted Stainless Steel," Additive Manufacturing, vol. 39, article no. 101886, Elsevier, Mar 2021.
The definitive version is available at https://doi.org/10.1016/j.addma.2021.101886
Department(s)
Mechanical and Aerospace Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Additive manufacturing; Analytical model; Electrical conductivity; Parameter estimation; Part performance; Thermal conductivity
International Standard Serial Number (ISSN)
2214-8604; 2214-8604
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2021 Elsevier, All rights reserved.
Publication Date
01 Mar 2021
Comments
National Science Foundation, Grant CMMI 1625736