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Eingeladener Vortrag
- nein (41)
Additive manufacturing (AM) of metallic alloys has gained momentum in the past decade for industrial applications. The microstructures of AM metallic alloys are complex and hierarchical from the macroscopic to the nanometer scale. When using laser-based powder bed fusion (L-PBF) process, two main microstructural features emerge at the nanoscale: the melt pool boundaries (MPB) and the solidification cellular substructure.
Here, details of the MPB are revealed to clearly show the three-dimensional nature of MPBs with changes of cell growth of direction and their relation to their surrounding cellular substructure, as investigated by transmission electron microscopy (TEM) for L-PBF 316L austenitic stainless steel (cf. Figure 1). A hitherto unknown modulated substructure with a period of 21 nm is further discovered within cells as the result of a partial Ga+-focused ion beam-induced ferritic transformation of the austenite. Cell cores and cell boundaries differ notably regarding the modulated substructure.
Ni alloys are generally classified as difficult-to-cut materials and cost intensive. Additive manufacturing (AM) offers economic advantages. However, machining of these AM components is mandatory to create the final contour or surface. The inhomogeneous and anisotropic microstructure and properties of AM components causes an unstable cutting process. Moreover, undesirable tensile residual stresses are generated due to subsequent machining. In this investigation, the initial alloy 36 is modified with Ti and Nb up to 1.6 wt.-% and build-up welded via gas metal arc welding (GMAW) and plasma-transferred-arc (PTA). Then, finish-milling tests are carried out to investigate the influence of the modification as well as the cutting parameters on the resulting cutting force and the surface integrity. In addition, the conventional milling process (CM) is compared with the ultrasonic-assisted milling process (US), which has a significant influence on the machinability as well as on the surface integrity.
Directed energy deposition is a metal additive manufacturing process that builds parts by joining material in a layer-by-layer fashion on a substrate. Those parts are exposed to rapid thermo-cycles which cause steep stress gradients and the layer-upon-layer manufacturing fosters an anisotropic microstructure, therefore stress relief heat treatment is necessary. The numerical simulation can be used to find suitable parameters for the heat treatment and to reduce the necessary efforts to perform an effective stress relieving. Suitable validation Experiments are necessary to verify the results of the numerical simulation.
In this paper, a 3D coupled thermo-mechanical model is used to simulate the heat treatment of an additive manufactured component to investigate the application of a C-ring geometry for the distortion-based validation of the numerical simulation.
Therefore, the C-ring samples were 3D scanned using a structured light 3D scanner to quantify the distortion after each process step.
The determination of mechanical properties of welded Steel structures such as strength or ductility is a subject of high interest for the majority of Companies in the area of metal Processing. The material Parameters can be obtained by performing the tensile test on the samples made from a part of a component. In some cases, it is highly expensive to produce the tensile specimens especially from the weld metal, which contains different type of microstructure such as weld seam or heat affected zone in an extremely small area. Therefore, a method is described in this paper to determine the material Parameters of high strength Steel structures and welded joints locally and without any additional effort to perform the tensile test. In this method, instrumented indentation technique (IIT), an indenter is pushed on the flat surface of a specimen in a certain period of time and simultaneously the applied force and the corresponding indentation path are measured. The data related to the force-indentation diagram is given as input to an artificial neural network (ANN) to obtain the material Parameters. The ANN can be trained by generating the large qualitative data sets with numerical Simulation of the IIT procedure. The Simulation must be run several times with the different material model parameter sets to generate the numerous
force-indentation diagrams as the inputs of ANN. Then, the trained ANN is validated by performing the IIT on the welded joints and comparing the obtained material Parameters from ANN with the tensile test.
Consequently, the mechanical properties of welded joints can be determined by performing the IIT and evaluating the resulting data by the ANN.
Virtual-lab-based determination of a macroscopic yield function for additively manufactured parts
(2018)
This work presents a method for the yield function determination of additively manufactured parts of S316L steel. A crystal plasticity model is calibrated with test results and used afterwards to perform so-called virtual experiments, that account for the specific process-related microstructure including crystallographic and morphological textures. These simulations are undertaken on a representative volume element (RVE), that is generated from EBSD/CT-Scans on in-house additively manufactured specimen, considering grain structure and crystal orientations. The results of the virtual experiments are used to determine an anisotropic Barlat yield function, that can be used in a macroscopical continuum-sense afterwards. This scale-bridging approach enables the calculation of large-scale parts, that would be numerically too expensive to be simulated by a crystal plasticity model.
While additive manufacturing (AM) is blossoming in nearly every industrial field, and the most different process are being used to produce components and materials, little attention is paid on the safety concerns around AM materials and processes.
Leveraging on our leading expertise in non-destructive testing (NDT) and materials characterization, we approach AM at BAM under two important viewpoints: first the on-line monitoring of the process and of the product, second the evolution of the (unstable) microstructure of AM materials under external loads.
These two subjects are the core of the two new-born internal projects ProMoAM and AGIL, respectively.
A detailed view of the goals and the organization of these two projects will be given, together with the expected output, and some preliminary results.
Additive manufacturing (AM) is a technology which has the potential not only to change the way of conventional industrial manufacturing processes, adding material instead of subtracting, but also to create entirely new production and business strategies. Since about three decades, AM technologies have been used to fabricate prototypes or models mostly from polymeric or metallic materials. Recently, products have been introduced into the market that cannot be produced in another way than additively. Ceramic materials are, however, not easy to process by AM technologies, as their processing requirements (in terms of feedstock and/or sintering) are very challenging. On the other hand, it can be expected that AM technologies, once successful, will have an extraordinary impact on the industrial production of ceramic components and, moreover, will open for ceramics new uses and new markets.
Ni alloys are generally classified as difficult-to-cut materials and cost intensive. Additive manufacturing (AM) offers economic advantages. However, machining of these AM components is mandatory to create the final contour or surface. The inhomogeneous and anisotropic microstructure and properties of AM components causes an unstable cutting process. Moreover, undesirable tensile residual stresses are generated due to subsequent machining. In this investigation, the initial alloy 36 is modified with Ti and Nb up to 1.6 wt.-% and build-up welded via gas metal arc welding (GMAW) and plasma-transferred-arc (PTA). Then, finish-milling tests are carried out to investigate the influence of the modification as well as the cutting parameters on the resulting cutting force and the surface integrity. In addition, the conventional milling process (CM) is compared with the ultrasonic-assisted milling process (US), which has a significant influence on the machinability as well as on the surface integrity.
This study provides insights into the properties of 316L stainless steel produced by additive manufacturing using fused filament fabrication (FFF). One key finding is particularly noteworthy: in significant contrast to cold-rolled 316L, FFF316L develops a pronounced martensite phase after fabrication. The comprehensive comparative analysis shows that FFF316L not only retains the ferrite volume content, but that this is also significantly influenced by the build-up direction. Despite the sintering process, which typically involves densification of the material, a pore volume fraction of 8.45 % remains, which influences the mechanical properties. Although FFF316L has lower elastic
modulus and tensile strength values compared to cold-rolled 316L, its ductility is still competitive. The study further reveals that deformation-induced martensite forms at the intersections of the deformation twins and ferrite islands form at the grain boundaries during the compression and sintering phases. These findings highlight the challenges associated with FFF316L in specific application fields and signal the need to continue to carefully evaluate and improve the development of manufacturing technologies.