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Model Order Reduction for Parametric Non‐linear Mechanical Systems: State of the Art and Future Research
Author(s) -
Meyer Christian H.,
Lerch Christopher,
Lohmann Boris,
Rixen Daniel J.
Publication year - 2017
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.201710011
Subject(s) - reduction (mathematics) , parametric statistics , computer science , model order reduction , matching (statistics) , linear system , state (computer science) , modal , mathematical optimization , industrial engineering , algorithm , engineering , mathematics , materials science , polymer chemistry , projection (relational algebra) , mathematical analysis , statistics , geometry
One research objective in the Priority Program 1897 “Calm, Smooth and Smart” of the German Research Foundation (DFG – SPP 1897) is the development of model order reduction techniques for parametric non‐linear mechanical systems to enable efficient design, simulation, analysis, optimization and control of those. As a starting point for our research, this contribution provides an overview of the main challenges and well‐established reduction techniques in this research area, at that stage, neglecting parameter dependencies. This includes simulation‐based as well as simulation‐free reduction bases generation and hyperreduction of the non‐linear force terms. An extension of the Krylov directions in moment matching based on the concept of modal derivatives is also sketched. (© 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)