CAREER: Unveiling the Governing Mechanisms of Fatigue Failure in Additively Manufactured Aluminum

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Additive manufacturing (AM), often referred to as 3D printing, is an exciting technology that can offer more flexibility and efficiency in the production of complex metal parts compared to conventional manufacturing. However, the path to AM as a viable and safe alternative in applications where structural components must carry loads (in some cases, where components must sustain repetitive loading over long periods of time) is at a critical junction. The widespread incorporation of this transformative manufacturing technology is hampered by the fact that it is currently not possible to predict when and why an additively manufactured metal component might fail, and to design the component accordingly to mitigate risk of failure. This presents a major problem for many industries that are looking to use AM to produce metal load-bearing components. This Faculty Early Career Development Program (CAREER) award supports fundamental research to address this pressing need and to enable the expanded, yet safe, use of metal AM in many industries, including aerospace, automotive, biomedical, manufacturing, and national defense. The research is closely integrated with a unique outreach program that will engage students across different age levels and backgrounds, including middle-school students from rural locations in Utah.The research supported by this CAREER award is a fundamental step toward expanding the use of AM to fatigue-critical applications through the discovery of 3D, microstructure-sensitive, fatigue-crack driving mechanisms in additively manufactured aluminum. Two parallel research thrusts will be carried out. One thrust will focus on experimentally characterizing the microstructural features in 3D neighborhoods of fatigue cracks observed in aluminum specimens produced by laser powder bed fusion. The second thrust will focus on numerically characterizing the local micromechanical fields that evolve in 3D as a function of underlying, manufacturing-induced microstructure and defect distribution, with particular focus on residual-stress incompatibility, porosity, and surface roughness. Data-driven approaches will be leveraged across the experimental and numerical data sets to provide new insights into the mechanisms responsible for fatigue failure among the specimens. While the research focuses on aluminum alloys, it is anticipated that the findings regarding the relative importance of geometrical defects, like pores and surface roughness, versus intrinsic material defects on fatigue failure of additively manufactured parts could be broadly applicable to other metals as well.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.