Untersuchung, Modellierung und Simulation der Freckle-Bildung an Superlegierungsbauteilen
Mechanical Properties of Metallic Materials and their Microstructural Origins
Final Report Abstract
Despite extensive research, freckles represent a defect which is still not fully understood, especially regarding the investment casting of single-crystal Ni-based alloys. As result of a density inversion of the melt and the associated thermo-solutal convection, freckle formation is mainly determined by the chemical composition, the casting size and the process parameters. Despite extensive research, however, there is still a lack of an exact understanding of the various factors influencing the freckle risk. The aim of the project therefore was to improve the basic understanding and description of freckle formation on a physical basis in a multiscale approach. The aim was to bring together the different length scales, namely the macroscale (entire casting + furnace), the mesoscale (selected semi-liquid areas with their convection patterns) and the microscale (individual dendrites) with their respective freckle-relevant phenomena. The approach was experimentally supported by the production of cylindrical and star-shaped cast freckle samples in order to systematically investigate the influence of shading and edges. To simulate the Bridgman casting process on the macroscale, the STAR-CCM+ software was used, addressing, among other things, the effect of shading on the radial temperature gradient. The simulated temperature fields were handed over as temperature gradients to the microstructure simulation and as heat flux boundary conditions to the mesoscale simulation. On the mesoscale, a fundamental further development of the existing model was first necessary in order to correctly reproduce the behaviour of multi-component alloys. Further, a columnar growth model for directional solidification was implemented. Using the melt permeabilities determined on the microscale, flow-mechanical solidification simulations could be carried out, which showed, among other things, the development of an upward flow field on the shadow side of the cylinder samples with subsequent remelting of dendrites. Finally, extensive multicomponent and multi-phase 3D-calculations of the dendrite morphology were performed on the microscale. It could be shown that with the help of the MICRESS® software and through high-performance implementation and coupling to thermodynamic databases, a simulation of the fundamental processes at the microstructure level as well as the prediction of temperaturedependent thermophysical quantities can be achieved. It was further possible to directly simulate the remelting of a dendrite when considering an ascending melt flow. Overall, it could be demonstrated that the procedure of scale and phenomenon integration makes it possible to map the mechanisms of freckles formation in the interaction of the software packages and also to determine valuable parameters about the solidification process.
Publications
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Calphad coupled phase-field model with mechano-chemical contributions and its application to rafting of γ’ in CMSX-4. Computational Materials Science, 184, 109909.
Böttger, B.; Apel, M.; Budnitzki, M.; Eiken, J.; Laschet, G. & Zhou, B.
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Freckles-Bildung bei unterschiedlichen Kantenwinkeln. Giesserei. 110(12): p. 58-61.
Pustal, B., T. Wittenzellner & A. Bührig-Polaczek
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Integrative Simulation der Freckle-Bildung in Ni-Basis Superlegierungen. Giesserei Special – Forschung und Innovation. 110(11): p. 58-67.
Pustal, B., R. Berger, H. Behnken, B. Böttger & A. Bührig-Polaczek
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Experimental Analysis and Simulation of Freckle Formation at Different Edge Angles During Directional Solidification of Ni-Base Superalloys. Metallurgical and Materials Transactions B, 55(4), 2732-2738.
Pustal, Björn; Wittenzellner, Tobias; Behnken, Herfried; Böttger, Bernd & Bührig-Polaczek, Andreas
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Numerical prediction of primary dendrite arm spacing (PDAS), properties of the mushy zone, and freckle risk for various multicomponent Ni-base superalloys using the 3D-phase-field method. Computational Materials Science, 236, 112854.
Böttger, B.; Seiz, A.; Sowa, R.; Berger, R. & Apel, M.
