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    Dynamic Meta-Modeling Method to Assess Stochastic Flutter Behavior in Turbomachinery

    Bowei Wang1, Wenzhong Tang1, Lukai Song2,3,*, Guangchen Bai3

    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.1, pp. 171-193, 2022, DOI:10.32604/cmes.2022.021123

    Abstract With increasing design demands of turbomachinery, stochastic flutter behavior has become more prominent and even appears a hazard to reliability and safety. Stochastic flutter assessment is an effective measure to quantify the failure risk and improve aeroelastic stability. However, for complex turbomachinery with multiple dynamic influencing factors (i.e., aeroengine compressor with time-variant loads), the stochastic flutter assessment is hard to be achieved effectively, since large deviations and inefficient computing will be incurred no matter considering influencing factors at a certain instant or the whole time domain. To improve the assessing efficiency and accuracy of stochastic flutter behavior, a dynamic meta-modeling… More >

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