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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