Rub-in processes in turbines - experimental investigation and modeling

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Achieving high efficiency in gas turbines requires the minimization of clearances between rotor and stator. Clearances vary constantly during operation due to e.g. thermal expansion or dynamic loads. The lack of clearance control over the entire operation cycle leads to frequent rubbing, which can critically damage rotor and stator, e.g. in the form of wear or cracking. In order to guarantee high operation safety and efficiency of the entire engine, robust sealing systems are required which are able to tolerate even heavy rubbing processes. Labyrinth seals with special honeycomb liners on the stator are able to meet these requirements. However, rubbing processes in such seals are not completely understood yet, which still prevents the development of a reliable design. Therefore, during the first funding period, a test rig was set up and used to determine the influence of rubbing parameters on resulting contact forces, temperatures and wear. The results of the experimental investigation and the determination of thermo-physical material properties of the participating materials Haynes 214 and Hastelloy X enabled the development and validation of a multiscale modelling system for simulating a rubbing event. It could be shown that the manufacturing process has a significant influence on physical material properties and the rubbing process.The aim for the second funding period is to further develop the multiscale finite element model in order to predict the behavior of complex sealing systems. For this, it is necessary to integrate the influence of the soldering method of honeycomb liners into the physical description and to consider it in the experimental investigation. The obtained physical material properties and experimental results of the rub test rig will be incorporated into the multiscale finite element model. Thus, the model serves as an important tool to completely design labyrinth sealing systems for given specification profiles and to provide reliable performance and service life prognoses in the future.