SIAM Journal on Scientific Computing · 2005 · 270 citations · 22 references
EngineeringComputational EngineeringMechanical EngineeringComputational MechanicsDynamical SystemsStructural DynamicsDimension ReductionDynamic Response AnalysisMulti-degree-of-freedom SystemsNonlinear DynamicsVibration AnalysisModel ReductionNonlinear Dimension ReductionNonlinear Model ReductionProjection-based Model ReductionStructural Dynamics ModelingStructural Dynamics ResponseStructure-preserving Model Reduction
A structure-preserving dimension reduction algorithm for large-scale second-order dynamical systems is presented. It is a projection method based on a second-order Krylov subspace. A second-order Arnoldi (SOAR) method is used to generate an orthonormal basis of the projection subspace. The reduced system not only preserves the second-order structure but also has the same order of approximation as the standard Arnoldi-based Krylov subspace method via linearization. The superior numerical properties of the SOAR-based method are demonstrated by examples from structural dynamics and microelectromechanical systems.
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