Reduced order method based on an adaptive formulation and its application to fan blade system with dovetail joints

Yuan, Jie, Schwingshackl, Christoph, Salles, Loic, Wong, Chian and Patsias, Sophoclis (2021) Reduced order method based on an adaptive formulation and its application to fan blade system with dovetail joints. In Proceedings of the ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. (doi:10.1115/GT2020-14227).

Abstract

Localized nonlinearities due to the contact friction interfaces are widely present in the aero-engine structures. They can significantly reduce the vibration amplitudes and shift the resonance frequencies away from critical operating speeds, by exploiting the frictional energy dissipation at the contact interface. However, the modelling capability to predict the dynamics of such large-scale systems with these nonlinearities is often impeded by the high computational expense. Component mode synthesis (CMS) based reduced order modelling (ROM) are commonly used to overcome this problem in jointed structures. However, the computational efficiency of these classical ROMs are sometimes limited as their size is proportional to the DOFs of joint interfaces resulting in a full dense matrix. A new ROM based on an adaptive formulation is proposed in this paper to improve the CMS methods for reliable predictions of the dynamics in jointed structures. This new ROM approach is able to adaptively switch the sticking contact nodes off during the online computation leading to a significant size reduction comparing to the CMS based models. The large-scale high fidelity fan blade assembly is used as the case study. The forced response obtained from the novel ROM is compared to the state-of-the-art CMS based Craig-Bampton method. A parametric study is then carried out to assess the influence of the contact parameters on the dynamics of the fan assembly. The feasibility of using this proposed method for nonlinear modal analysis is also characterised.

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Contributors

Author: Jie Yuan

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