A Physics-Based Reduction with Monitoring Data Assimilation for Adaptive Representations in Structural Systems
Open access
Date
2023Type
- Conference Paper
ETH Bibliography
yes
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Abstract
Digital twin representations have become an indispensable tool for delivering data-informed virtualizations of operating systems, especially in structural health monitoring applications. In this context, challenges arise when the response often shifts beyond regular operating conditions due to extreme events such as earthquakes or structural damage. Our work proposes a reduced order modeling for adaptive digital twins, for systems undergoing damage, condition deterioration, or experiencing stochastic excitation. Our approach initiates by featuring a projection-based reduced order model (ROM), relying on proper orthogonal decomposition (POD) and local subspaces to form a low-cost surrogate of the parametrized high-fidelity system that retains a physical connotation. However, extreme events induce loading conditions and model states that challenge the accuracy of such representations. To this end, we propose adopting the derived ROM as a forward simulator and adapt the projection basis on-the-fly during operation via a Gaussian processes regressor (GPR) scheme. During operation, the ROM framework receives response monitoring information from a sparse number of nodes. It employs a suitable condition indicator to highlight the potential low precision of the initial surrogate. Subsequently, the GPR-based scheme utilizes the monitoring input to reconstruct the current deformed configuration of the whole system in an online manner. In turn, this approximation serves as a damaged mode that enriches the projection-based ROM and enables online adaptivity. This coupling yields a ROM equipped with critical features for health monitoring applications such as (near) real-time basis refinement, signaling potentially irreversible consequences, and estimation of the uncertainty in the enrichment mode and the adapted ROM prediction. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000574196Publication status
publishedExternal links
Editor
Book title
Model Validation and Uncertainty Quantification, Volume 3Journal / series
Conference Proceedings of the Society for Experimental Mechanics SeriesPages / Article No.
Publisher
SpringerEvent
Subject
Adaptive GPR-ROM; Monitoring data assimilationOrganisational unit
03890 - Chatzi, Eleni / Chatzi, Eleni
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ETH Bibliography
yes
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