Full-Scale Bridge Finite-Element Model Calibration Using Measured Frequency-Response Functions
Publication: Journal of Bridge Engineering
Volume 20, Issue 9
Abstract
A frequency-response function–based parameter-estimation method was used for finite-element (FE) model calibration of a full-scale bridge using measured dynamic test data. Dynamic tests were performed on the bridge to obtain measured frequency-response functions. Data quality was ensured by comparing measured data with the FE model and removing erroneous data. A coherence data selector was developed to remove the noise-contaminated portions of the measured frequency-response functions. An unrefined FE model was created using design information for the geometry and structural parameters. This model was improved to a refined model by using concrete cylinder property data, as-built drawing geometry, and the addition of components that participate in the dynamic response of the bridge. Simulations were performed using the model to ensure both observability and identifiability of structural parameters. The model of the bridge was then calibrated successfully using measured frequency-response functions. An increase in the negative bending region concrete-deck rigidity was found during the calibration and verified by increased reinforcement in that area. Examining the second norm of the residual between the different models and the measured data resulted in an improvement from the unrefined to the calibrated FE model. The proposed method proved to be robust in the presence of modeling and measurement errors and computationally efficient for use with full-scale structures.
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Acknowledgments
The authors are grateful for the funding of this research made possible by National Science Foundation PFI Grant 0650258. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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© 2014 American Society of Civil Engineers.
History
Received: Mar 21, 2014
Accepted: Sep 10, 2014
Published online: Oct 6, 2014
Published in print: Sep 1, 2015
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