Abstract
In aero engines, rotating labyrinth seals are widely used to suppress the flow leakage between static and rotating components. These seals are usually designed with light weight to further enhance the engine performance. Hence, they are susceptible to flutter vibration due to their low stiffness. In this study, the ways to optimize both seal leakage performance and flutter margin are investigated using fluid-structure interaction (FSI) simulation and machine learning. Through this study, it is found that by optimizing sub cavity geometries between seal fins, both the leakage performance and flutter margin can be effectively improved.
