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ABSTRACT
Hot gas components such as gas turbine blades are loaded with constant centrifugal stress at high temperatures and thus the formation of creep cavitation on grain boundaries is expedited. Conventionally cast polycrystalline Nickel-base superalloys used as blade materials are prone to creep cavitation as unfavourably orientated grain boundaries exist. This research presents a diffusion-based probabilistic creep model which describes the creep cavitation process on grain boundaries. It includes the three mechanisms: pore nucleation, growth, and coalescence. The calibration of the model has been carried out by analysing Alloy 247 as-received specimens and specimens with pre-strain. For the evaluation of the pore numbers and sizes, a deep learning model for pore detection was trained on light microscopic and scanning electron microscopy images. Electron backscatter diffraction images are analysed for further investigations regarding grain orientations and grain boundary angles to the loading direction. The calibrated model allows predictions of pore size distributions over time.
Acknowledgments
The investigations were conducted as part of the joint research program OptiSysKom in the frame of AG Turbo. The work was funded by the Federal Ministry for Economic Affairs and Climate Action as per resolution of the German Federal Parliament under grant number 03EE5034B. We thank Dr. Markus Vöse for his support and providing the creep pore model, as well as Thomas Bouchenot and the Siemens Energy Casselberry Test Lab Team for providing us the experimental data.
Disclosure statement
The author(s) declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.