[en] High-cycle fatigue caused by large resonance stresses remains one of the most common causes of turbine blade failures. Friction dampers are one of the most effective and practical solutions to limit the vibration amplitudes, and shift the resonance frequencies of the turbine assemblies far from operating speeds. However, predicting the effects of underplatform dampers on the dynamics of the blades with good accuracy still represents a major challenge today, due to the complex nature of the nonlinear forces at the interface, characterised by transitions between stick, slip, and separation conditions. The most common modelling approaches developed recently are based on the explicit FE model for the damper, and on a dense grid of 3D contact elements comprised of Jenkins elements, or on a single 2D microslip element on each surface. In this paper, a combination of the two approaches is proposed. A 3D microslip element, based on a modified Valanis model is proposed and a series of these elements are used to describe the contact interface. This new approach allows to implicitly account for the microscale energy dissipation as well as the pressure-dependent contact stiffness caused by the roughness of the contact surface. The proposed model and its predicting capabilities are then evaluated against a simplified blade-damper model, based on an underplatform damper test rig recently developed by the authors. A semi-analytical contact solver is used to tune the parameters of the contact element starting from the profilometer measurements of the real damper surface. A comparison with a more simplistic modelling approach based on macroslip contact elements, highlights the improved accuracy of the new model to predict the experimental nonlinear response, when information about the surface roughness is available.
The authors are grateful to Innovate UK and Rolls-Royce plc for providing the financial support for this work and for giving permission to publish it. This work is part of a collaborative R&T project SILOET II P19.6 which is co-funded by Innovate UK and Rolls-Royce plc and carried out by Rolls-Royce plc and the Vibration UTC at Imperial College London.The authors are grateful to Innovate UK and Rolls-Royce plc for providing the financial support for this work and for giving permission to publish it. This work is part of a collaborative R&T project SILOET II P19.6 which is co-funded by Innovate UK and Rolls-Royce plc and carried out by Rolls-Royce plc and the Vibration UTC at Imperial College London.
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