Garboczi, E.
, Henry, T.
, Phillips, F.
, Cole, D.
, Haynes, R.
and Johnson, T.
(2020),
In situ fatigue monitoring investigation of additively manufactured maraging steel, International Journal of Advanced Manufacturing Technology, [online], https://doi.org/10.1007/s00170-020-05255-4, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=927278
(Accessed November 16, 2025)
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In situ fatigue monitoring investigation of additively manufactured maraging steel
Published
Author(s)
, Todd Henry, Francis Phillips, Daniel Cole, Robert Haynes, Terrence Johnson
Abstract
This work describes an experimental validation set for assessing the real-time fatigue behavior ofmetallic additive manufacturing (AM) maraging steel structures. Maraging steel AM beams were fabricated with laser powder bed fusion (LPBF) and characterized with ex situ studies of porosity through X-ray computed tomography (CT), nano-indentation, and atomic force microscopy, as well as quasi-static testing to evaluate the as-printed state. Microscale evaluation showed void content of 0.34–0.36% with hardness and stiffness variation through the build direction on the order of 5.1–5.6 GPa and 139–154 GPa, respectively. The microscale inhomogeneities created an as-printed state where the compression and tension plasticity behavior at the macroscale was unequal in quasi-static loading, leading to greater yielding in tension. Specimens were subjected to cyclic loads, while the structural behavior was characterized through in situ magnetic permeability, digital image correlation (DIC) strain, and structural compliance measurements. In the range of 3 × 103 to 3 × 104 cycles to failure, magnetic permeability measurements were able to capture the mechanical state as early as 60% of life depending on failure location. Results are discussed with an emphasis on material-property-structure relationships in terms of the multi-scale material state and fatigue validation data for improving the durability of AM parts.Citation
International Journal of Advanced Manufacturing Technology
Volume
107
Pub Type
Journals
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Keywords
additive manufacturing, digital image correlation, nano-indentation, x-ray computed tomography, maraging steel
Citation
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Created April 17, 2020, Updated September 29, 2025