Size-dependent stochastic tensile properties in additively manufactured 316L stainless steel

Journal Article · 23 January 2020 · Additive Manufacturing

DOI: https://doi.org/10.1016/j.addma.2020.101090 · OSTI ID:1605718

Roach, Ashley M. ^[1]; White, Benjamin C ^[1]; Garland, Anthony ^[1]; Jared, Bradley Howell ^[1]; Carroll, Jay ^[1]; Boyce, Brad ^[1]

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1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Recent work in metal additive manufacturing (AM) suggests that mechanical properties may vary with feature size; however, these studies do not provide a statistically robust description of this phenomenon, nor do they provide a clear causal mechanism. Because of the huge design freedom afforded by 3D printing, AM parts typically contain a range of feature sizes, with particular interest in smaller features, so the size effect must be well understood in order to make informed design decisions. This work investigates the effect of feature size on the stochastic mechanical performance of laser powder bed fusion tensile specimens. A high-throughput tensile testing method was used to characterize the effect of specimen size on strength, elastic modulus and elongation in a statistically meaningful way. The effective yield strength, ultimate tensile strength and modulus decreased strongly with decreasing specimen size: all three properties were reduced by nearly a factor of two as feature dimensions were scaled down from 6.25 mm to 0.4 mm. Hardness and microstructural observations indicate that this size dependence was not due to an intrinsic change in material properties, but instead the effects of surface roughness on the geometry of the specimens. Finite element analysis using explicit representations of surface topography shows the critical role surface features play in creating stress concentrations that trigger deformation and subsequent fracture. The experimental and finite element results provide the tools needed to make corrections in the design process to more accurately predict the performance of AM components.

• Research Organization: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: USDOE; USDOE National Nuclear Security Administration (NNSA)
• Grant/Contract Number: AC04-94AL85000
• OSTI ID: 1605718
• Report Number(s): SAND--2020-2115J; 684055
• Journal Information: Additive Manufacturing, Journal Name: Additive Manufacturing Journal Issue: C Vol. 32; ISSN 2214-8604
• Publisher: ElsevierCopyright Statement
• Country of Publication: United States
• Language: English