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A‐priori pole selection for reduced models in vibro‐acoustics
Author(s) -
Aumann Quirin,
Müller Gerhard
Publication year - 2019
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.201900205
Subject(s) - a priori and a posteriori , convergence (economics) , range (aeronautics) , reduction (mathematics) , mathematics , model order reduction , set (abstract data type) , mode (computer interface) , algorithm , iterative method , mathematical optimization , selection (genetic algorithm) , computer science , geometry , projection (relational algebra) , philosophy , materials science , epistemology , artificial intelligence , economics , composite material , programming language , economic growth , operating system
Large 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.