Authors: Yongxin Yuan Hao Liu
Publish Date: 2013/04/23
Volume: 48, Issue: 9, Pages: 2245-2253
Abstract
The procedure of updating an existing but inaccurate model is an essential step toward establishing an effective model Updating damping and stiffness matrices simultaneously with measured modal data can be mathematically formulated as following two problems Problem 1 Let M a ∈SR n×n be the analytical mass matrix and Λ=diagλ 1…λ p ∈C p×p X=x 1…x p ∈C n×p be the measured eigenvalue and eigenvector matrices where rankX=p pn and both Λ and X are closed under complex conjugation in the sense that lambda 2j = barlambda 2j1 innobreakmathbfC x 2j = barx 2j1 inmathbfCn for j=1…l and λ k ∈R x k ∈R n for k=2l+1…p Find realvalued symmetric matrices D and K such that M a XΛ 2+DXΛ+KX=0 Problem 2 Let D a K a ∈SR n×n be the analytical damping and stiffness matrices Find hatD hatK inmathbfS mathbfE such that hatDD a 2+ hatKK a 2= min DK in mathbfS mathbfE DD a 2 +KK a 2 where S E is the solution set of Problem 1 and ∥⋅∥ is the Frobenius norm In this paper a gradient based iterative GI algorithm is constructed to solve Problems 1 and 2 A sufficient condition for the convergence of the iterative method is derived and the range of the convergence factor is given to guarantee that the iterative solutions consistently converge to the unique minimum Frobenius norm symmetric solution of Problem 2 when a suitable initial symmetric matrix pair is chosen The algorithm proposed requires less storage capacity than the existing numerical ones and is numerically reliable as only matrix manipulation is required Two numerical examples show that the introduced iterative algorithm is quite efficient
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