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Kriging-Based Surrogate Modeling for Rotordynamics Prediction in Rotor-Bearing System

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Proceedings of the 10th International Conference on Rotor Dynamics – IFToMM (IFToMM 2018)

Part of the book series: Mechanisms and Machine Science ((Mechan. Machine Science,volume 62))

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Abstract

In this work, it was proposed to use Kriging surrogate models for rotordynamics prediction in rotor-bearing systems. The motivation is to significantly reduce computation effort when evaluating the design space. First, fundamentals of rotordynamics are reviewed and the rotor-bearing system is modeled using the Finite Element (FE) method. Modal analysis is used to determine whirl frequencies and critical speeds while system dynamic behavior is evaluated in terms of the unbalance response. Subsequently, approximations of the input/output relationships created by the FE simulations are obtained by applying the Kriging interpolating method. The derived models work as fast-running surrogates for the full model. Comparison of the results from Kriging surrogates obtained using different training samples shows that the proposed methodology provides a computationally efficient and low-dimension mathematical relationship that can accurately predict rotor-bearing system outputs with considerably low training effort.

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Correspondence to Mateus P. F. Barbosa or William M. Alves .

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Barbosa, M.P.F., Alves, W.M. (2019). Kriging-Based Surrogate Modeling for Rotordynamics Prediction in Rotor-Bearing System. In: Cavalca, K., Weber, H. (eds) Proceedings of the 10th International Conference on Rotor Dynamics – IFToMM . IFToMM 2018. Mechanisms and Machine Science, vol 62. Springer, Cham. https://doi.org/10.1007/978-3-319-99270-9_22

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  • DOI: https://doi.org/10.1007/978-3-319-99270-9_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99269-3

  • Online ISBN: 978-3-319-99270-9

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