Abstract
The aim of this study was to assess the capabilities of different simulation approaches to predict the flutter stability of a steam turbine rotor. The focus here was on linear and nonlinear frequency domain solvers in combination with the energy method, which is widely used for the prediction of flutter onset. Whereas a GMRES solver was used for the linear problem, the nonlinear methods employed a time-marching procedure. The solvers were applied to the flutter analysis of the first rotor bending mode of the open Durham Steam Turbine test case. This test case is representative of the last stage of modern industrial steam turbines. We compared our results to those published by other researchers in terms of aerodynamic damping and local work per cycle coefficients. Time-domain, harmonic balance, and time-linearised methods were compared to each other in terms of CPU efficiency and accuracy.
Highlights
The efficient and accurate prediction of turbine flutter during the design phase is vital since flutter stability and aerodynamic efficiency are often competing goals
The relative error was computed with respect to the reference solution after a residual drop of 10−4
Time-linearised, harmonic balance and time-integration methods were applied to the flutter analysis of a steam turbine rotor
Summary
The efficient and accurate prediction of turbine flutter during the design phase is vital since flutter stability and aerodynamic efficiency are often competing goals. For transonic test cases, shock boundary layer interactions may result in local nonlinear responses of the unsteady flow, even if the overall work per cycle depends almost linearly on the vibration amplitude. For cases with periodic shock oscillations, linear solvers may produce unphysically high pressure amplitudes which depend strongly on the mesh resolution and the spatial discretisation. In this case, the CFD result can be a good approximation in terms of the overall aerodynamic damping [2], it is very difficult to compare local unsteady pressures with experimental data, for instance from pressure transducers [3,4]
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