Abstract This work studies the use of laser shock peening (LSP) to improve back stress in additively manufactured (AM) 316L parts. Unusual hardening behavior in AM metal due to tortuous microstructure and strong texture poses additional design challenges. Anisotropic mechanical behavior complicates application for mechanical design because 3D printed parts will behave differently than traditionally manufactured parts under the same loading conditions. The prevalence of back-stress hardening or the Bauschinger effect causes reduced fatigue life under random loading and dissipates beneficial compressive residual stresses that prevent crack propagation. LSP is known to improve fatigue life by inducing compressive residual stress and has been applied with promising results to AM metal parts. It is here demonstrated that LSP may also be used as a tool for mitigating tensile back-stress hardening in AM parts, thereby reducing anisotropic hardening behavior and improving design use. It is also shown that the method of application of LSP to additively manufactured parts is key for achieving effective back-stress reduction. Back stress is extracted from additively manufactured dog bone samples built in both XY and XZ directions using hysteresis tensile. Both LSPed and as-built conditions are tested and compared, showing that LSPed samples exhibit a significant reduction to back stress when the laser processing is applied to the sample along the build direction. Electron backscatter diffraction (EBSD) performed under these conditions elucidates how grain morphologies and texture contribute to the observed improvement. Crystal plasticity finite element (CPFE) modeling develops insights as to the mechanisms by which this reduction is achieved in comparison with EBSD results. In particular, the difference in plastic behavior across build orientations of identified crystal planes and grain families are shown to impact the degree of LSP-induced back-stress reduction that is sustained through tensile loading.
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Life Prediction for Directed Energy Deposition‐Manufactured 316L Stainless Steel using a Coupled Crystal Plasticity–Machine Learning Framework
Additively manufactured stainless steels have become increasingly popular due to their desirable properties, but their mechanical behavior in structural parts is not yet fully understood. Specifically, the impact of columnar microstructures on fatigue behavior is still unclear. A typical directed energy deposition (DED)‐fabricated 316L stainless steel microstructure consists of distinct zones with equiaxed and columnar grains. To answer the question of how these zones of a DED‐fabricated 316L stainless steel microstructure affect the local mechanical behavior individually, such as the fatigue strength, stress/strain distribution, and fatigue life, crystal plasticity simulations are conducted to investigate the influence of microstructure on local mechanical behavior such as fatigue strength, stress/strain distribution, and fatigue life. The simulations find that columnar microstructures exhibit better fatigue strength than equiaxed structures when the load is parallel to the major axis of the columnar grains, but the strength decreases when the load is perpendicular. This study also uses machine learning to predict fatigue life, which shows good agreement with crystal plasticity modeling. The study suggests that the combined crystal plasticity–machine learning approach is an effective way to predict the fatigue behavior of additively manufactured components.
- Award ID(s):
- 2152369
- NSF-PAR ID:
- 10402225
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Engineering Materials
- Volume:
- 25
- Issue:
- 10
- ISSN:
- 1438-1656
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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