Abstract
Nonlinear models for large/complex structures are hard to simulate for parametric studies of long-time dynamical behaviors. Reduced order models (ROMs) provide tools that both allow long-time dynamical simulations and reduce data storage requirements. In data-based model reduction, there is usually no consistent way to determine if the obtained ROM is robust to the variations in system parameters. Here, we use two concepts of “dynamical consistency” and “subspace robustness” to evaluate ROMs validity for parametric studies. The application of these concepts is demonstrated by reducing a nonlinear finite element model of a cantilever beam in a two well potential field. The resulting procedure can be used for developing and evaluating ROMs that are robust to the variations in the parameters or operating conditions.
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Notes
- 1.
As an example, POMs capturing maximal energy for a deterministic steady state motion will be generally different from POMs for a stochastically excited system.
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Acknowledgements
This paper is based upon work supported by the National Science Foundation under Grant No. 1100031.
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Chelidze, D. (2014). Identifying Robust Subspaces for Dynamically Consistent Reduced-Order Models. In: Kerschen, G. (eds) Nonlinear Dynamics, Volume 2. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-04522-1_11
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DOI: https://doi.org/10.1007/978-3-319-04522-1_11
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