The health monitoring of structures and infrastructures exposed to aging and/or extreme loading conditions is increasingly recognized as a timely issue, not only in civil engineering. To move towards real-time structural health monitoring (SHM) procedures, the adoption of reduced-order models (ROMs) obtained through proper orthogonal decomposition (POD) was proposed in . In the case of a changing structural health, the ROM would need to be continuously re-trained so as to prevent the results to be affected by biases. In  a procedure was offered to avoid such time consuming re-training stages; in this work, we further discuss the proposed framework. The chance to attain even larger speedups through a coupling of such reduced-order modeling procedure and adaptive domain decomposition strategies, see e.g. , will be also commented during the Conference.
|Titolo:||Adaptive POD-based reduced order modeling and identification of nonlinear structural systems|
|Autori interni:||MARIANI, STEFANO|
|Data di pubblicazione:||2016|
|Appare nelle tipologie:||04.1 Contributo in Atti di convegno|
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