A‐priori pole selection for reduced models in vibro‐acoustics

Abstract

AbstractLarge models of complex dynamic systems can be evaluated efficiently using model order reduction methods. Many techniques, for example the iterative rational Krylov algorithm (IRKA), rely on a set of expansion points chosen before the reduction procedure. The number and location of the expansion points has a major impact on the quality of the resulting reduced model and the convergence of the algorithm. Based on the system's geometry and material, the number of modes in a certain frequency range can be computed using wave equations. This mode count allows the choice of both a reasonable size for the reduced model as well as a reasonable distribution of initial expansion points, which improves the convergence of IRKA. Using the mode count in a specific frequency range, a reduced model approximating the full model only in this frequency range can be generated.