应用于随机失谐叶盘振动分析的代理模型研究（英文）

Surrogate Models for Vibration Analysis of Randomly Mistuned Bladed Disk

蒙特卡洛方法常被用来获得随机失谐对叶盘振动响应的影响,但该方法计算负荷大。本文应用多项式响应面和Kriging代理模型预测失谐叶盘的幅值放大因子。为进一步提高预测精度,这里采用期望提高的Kriging方法来处理随机失谐与幅值放大因子之间复杂的非线性关系。采用失谐叶盘集中参数模型来验证文中代理模型的有效性。计算结果表明,期望提高的Kriging模型的失谐响应预测精度要远高于多项式响应面。

Analysis of the response statistics of randomly mistuned bladed disk usually is expensive due to the Monte Carlo simulations.The polynomial response surface method and Kriging metamodel are used to predict the amplification factor of the mistuned system in this paper.To improve the accuracy of the surrogate model,the expected improvement(EI)Kriging is proposed to handle the complex nonlinear relations between the random mistuning and the amplification factor.A lumped parameter bladed disk is used as example to show the effectiveness of the surrogate models.The results indicate that,Kriging model with EI criterion performs much better than polynomial response surface method in accuracy.