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DOE OSTI · 1721600

Global System Reduction Order Modeling for Localized Feature Inclusion

Abstract

The development of reduced-order models remains an active research area, despite advances in computational resources. Here we develop a novel order-reduction approach that is designed to incorporate isolated regions that contain, for example, nonlinearitites or accumulating damage. The approach is designed to use global modes of the overall system response, which are then naturally coupled to the response in the isolated region of interest. Two examples are provided to demonstrate both the accuracy and the computational efficiency of the proposed approach. The performance of this approach is compared to the exact response corresponding to a finite element simulation for the chosen problems. In addition, the accuracy and computational efficiency are shown relative to a standard Galerkin reduction based on the linear normal modes. It is found that the proposed reduction offer computational efficiency comparable to a Galerkin reduction, but more accurately represents the response of the system when both are compared to the finite element simulation.

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BibTeXRIS

Quinn, D. Dane, Brink, Adam R.. 2020-11-19. Global System Reduction Order Modeling for Localized Feature Inclusion. https://doi.org/10.1115/1.4048890

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