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

With increasing design demands of turbomachinery, stochastic flutter behavior has become more prominent and even appears a hazard to reliability safety. Stochastic assessment is an effective measure quantify the failure risk improve aeroelastic stability. However, for complex turbomachinery with multiple dynamic influencing factors (i.e., aeroengine compressor time-variant loads), hard be achieved effectively, since large deviations inefficient computing will incurred no matter considering at certain instant or whole time domain. To assessing efficiency accuracy behavior, meta-modeling approach (termed BA-DWTR) presented integration bat algorithm (BA) wavelet tube regression (DWTR). The typical blade considered as one case evaluate proposed respect condition variabilities load fluctuations. evaluation results reveal that 0.95% probability induce when operating 100% rotative rate t = 170 s. total temperature rotor inlet loads (vibrating frequency rate) are primary sensitive parameters on probability. By method comparisons, validated possess high-accuracy highefficiency in turbomachinery.