Second Order Arnoldi Reduction application to some engineering problems

Abstract

A standard approach to model reduction of second order linear dynamical systems is to rewrite the system as an equivalent first order system and then employ Krylov subspace techniques for model reduction. Recently the Second Order Arnoldi Reduction (SOAR) method was presented by Bai and Su which constructs the projection to a second order Krylov subspace thus preserving the structure of the underlying problem. In this paper we demonstrate the superior numerical behavior of the SOAR-algorithm upon the first order methods for four engineering problems from different areas.