Ingenieurwissenschaften und zugeordnete Tätigkeiten
Filtern
Dokumenttyp
- Posterpräsentation (9) (entfernen)
Sprache
- Englisch (9)
Referierte Publikation
- nein (9)
Schlagworte
- Additive Manufacturing (9) (entfernen)
Organisationseinheit der BAM
- 9 Komponentensicherheit (9) (entfernen)
The subsurface residual stress in laser powder bed fused 316L structures was analyzed using X-ray diffraction (XRD) and layer removal. The influence of varying structure thicknesses was investigated. In this study the importance of combining surface roughness measurements with XRD was shown. Moreover, a clear relation between the structure thickness and the subsurface residual stress profiles was observed.
Additively Manufactured (AM) parts are still far from being used in safety-relevant applications, mainly due to a lack of understanding of the feedstock-process-propertiesperformance relationship. This work aims at providing a characterization of the fatigue behavior of the additively manufactured AISI 316L austenitic stainless steel and a direct comparison with the fatigue performance of the wrought steel. A set of specimens has been produced by laser powder bed fusion (L-PBF) and a second set of specimens has been machined out of hot-rolled plates. The L-PBF material shows a higher fatigue limit and better finite life performance compared to the wrought material, accompanied by an extensive amount of cyclic softening.
The assessment of high cycle fatigue in additive manufactured (AM) components is a challenge due to complex microstructure, anisotropic material behavior, residual stresses and porosity / lack-of-fusion defects. Due to the statistical distribution of defects, a high scatter band of S-N-curves is expected. The fracture mechanics-based fatigue assessment of additive manufactured components must consider the propagation of short cracks emanating from defects.
In this work, the fatigue crack propagation resistance in the short and large crack regimes of additive and conventionally manufactured AISI 316L stainless steel is examined experimentally based on the cyclic R-curve. However, remaining residual stresses in the AM specimen lead to unexpected and dramatic crack-growth during the pre-cracking procedure.
Despite of the significant advances in additive manufacturing (AM) process optimization there is still a lack of experimental results and understanding regarding the mechanical behavior and its relationship with the microstructural features of AM-parts, especially in loading conditions typical for safety-relevant applications. Within the scope of the presented ongoing investigations, a basic microstructural characterization, tensile tests at room and elevated temperature (400°C) as well as a characterization of the fatigue behavior of additively manufactured Ti-6Al-4V in the low cycle fatigue regime are carried out in the as-built state. After failure, different techniques are used to describe the failure mechanisms of the specimens. The AM-Specimens are provided by the Fraunhofer institute for production systems and design technology and investigated at the BAM following the philosophy of the TF-Project AGIL.
The Influence of the Temperature Gradient on the Distribution of Residual Stresses in AM AISI 316L
(2019)
Steep temperature gradients and solidification shrinkage are the main contributors to the formation of residual stresses in additively manufactured metallic parts produced by laser beam melting. The aim of this work was to determine the influence of the temperature gradient.
Diffraction results show a similar pattern for both specimens, indicating the shrinkage to be more dominant for the distribution of residual stresses than the temperature gradient. Thermography results imply that a higher energy input result in higher compressive residual stresses in the bulk.
µCT is used to validate the capability of online monitoring for in-situ detection of defects during the L-PBF build process, which is a focus of the TF project ProMoAM.
Our first experiments show that online monitoring using thermography and optical tomography cameras are able to detect defects in the built part. But further research is needed to understand root cause of the correlation.