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Proceedings Paper

Reduced-order model design for nonlinear smart system models
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Paper Abstract

The use of finite element or finite difference techniques to discretize nonlinear smart material system models can yield full-order numerical models that accurately characterize the system dynamics but do so at significant computational cost. This can preclude the use of these full-order models for uncertainty analysis, sensitivity analysis, system design, or real-time control implementation. In this paper, we discuss the construction of reduced-order system models using proper orthogonal decompositions (POD) with updates. Through the use of snapshots constructed from the full-order models, fundamental physics is retained while significantly improving efficiency for high-speed implementation.

Paper Details

Date Published: 3 April 2009
PDF: 8 pages
Proc. SPIE 7286, Modeling, Signal Processing, and Control for Smart Structures 2009, 72860B (3 April 2009); doi: 10.1117/12.815773
Show Author Affiliations
Stephen F. May, North Carolina State Univ. (United States)
Ralph C. Smith, North Carolina State Univ. (United States)

Published in SPIE Proceedings Vol. 7286:
Modeling, Signal Processing, and Control for Smart Structures 2009
Douglas K. Lindner, Editor(s)

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