Abstract
Rotating machines have a remarkable importance on industry and understanding their behavior may be crucial for the production. Rotors supported by journal bearings are subjected to fluid-induced instability and the occurrence of this phenomenon is influenced by parameters that may vary randomly, so the problem of the identification of the stability threshold is stochastic. This paper applies the Stochastic Collocation method to solve this problem for a given rotor system. The validation of the method is made by the comparison of the results to the results of Monte Carlo simulations for the same problem. The Monte Carlo method requires a great number of simulations for a proper convergence of the results, while the Stochastic Collocation method requires fewer simulations. This difference implies on a considerable processing time difference for the two methods, several hours for the Monte Carlo against some minutes for the Stochastic Collocation. The results of the methods differ on some features: the probability density function generated by the Stochastic Collocation doesn’t fit the normalized histogram generated by the Monte Carlo and the variance of the stability threshold present a considerable difference on the methods. However, the lower and upper limits of the stability threshold on both methods is nearly the same, as well as the mean value for the stability threshold.
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Acknowledgements
The authors gratefully acknowledge CAPES and São Paulo Research Foundation FAPESP (grant #2015/20363-6 and #2016/13059-1) for providing financial support for this work.
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Visnadi, L.B., Garoli, G.Y., de Castro, H.F. (2019). Application of Stochastic Collocation on Eigenfrequencies Analysis of a 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 63. Springer, Cham. https://doi.org/10.1007/978-3-319-99272-3_29
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DOI: https://doi.org/10.1007/978-3-319-99272-3_29
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