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The eigenvalue and eigenvector errors using model reduction techniques

机译:使用模型归约技术的特征值和特征向量误差

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Methods of reduced order model are widely applied in reduction of degree of freedom of large finite element models, the static condensation method used for fast computation of natural frequencies and mode shapes exactly in low frequency. The improve reduce system (IRS) method produces a reduced model which more accurate estimated the modal model of the full system, Rayleigh Ritz vector is a most general technique for finding approximations to the lowest eigenvalue and corresponding eigenvectors. In this paper a comparison between IRS, Ritz and condensation is presented, numerical example applied for three methods, IRS is strongly has agreement with FEM.
机译:降阶模型的方法被广泛应用于降低大型有限元模型的自由度,而静态压缩方法则用于快速计算固有频率和精确地在低频下的振型。改进的减少系统(IRS)方法产生了一个减少的模型,该模型可以更准确地估计整个系统的模态模型。RayleighRitz向量是用于找到最低特征值和相应特征向量的近似值的最通用技术。本文对IRS,Ritz和凝结进行了比较,数值算例应用于三种方法,IRS与FEM有很强的一致性。

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