Predicting the Usefulness of Monitoring for Identifying the Behavior of Structures
Publication: Journal of Structural Engineering
Volume 139, Issue 10
Abstract
Structures can be better understood when measurement data are used to improve the modeling of structural behavior. Our capacity to interpret data depends on aspects such as the choice of model class, model parameters (and their range of possible values), and the extent of uncertainties influencing models and measurements. The objective of this paper is to determine probabilistically to what degree measurements are useful for structural identification with respect to these aspects. A metric, expected identifiability, is proposed to be used prior to monitoring. The new methodology is based on three performance indexes: the expected number of candidate models, the expected prediction ranges, and a combination of the two. Because it does not require intervention on the structure, the method can be used as a tool to support prioritization of decisions related to full-scale testing. These features are illustrated through the study of the Langensand Bridge (Switzerland). In this example, the methodology shows that increases in modeling uncertainties significantly hinder the usefulness of measurements for identifying model parameter values. The predictive capability of the method proposed is verified by agreement with observations made during a recent structural identification exercise. Quantifying the expected identifiability provides a tool to support infrastructure decision making, such as determining to what extent certain structural monitoring plans are useful.
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Acknowledgments
Collaboration with the designers of the Langensand Bridge, G. Guscetti and Dr. C. Pirazzi, was important for successful completion of the load tests. The authors also acknowledge input from Dr. R. Cantieni and the help we received from his team when taking the measurements. Finally, the authors thank Dr. I. Laory and P. Gallay for their help during load testing. The city of Lucerne provided logistical support, the trucks for the load tests, and the deformation sensors. The authors also thank the reviewers for their thoughtful comments. This research is funded by the Swiss National Science Foundation under contract No. 200020-117670/1.
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Information & Authors
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Published In
Journal of Structural Engineering
Volume 139 • Issue 10 • October 2013
Pages: 1716 - 1727
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Apr 28, 2011
Accepted: Feb 7, 2012
Published online: Feb 10, 2012
Published in print: Oct 1, 2013
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