Multimodel Structural Performance Monitoring
Publication: Journal of Structural Engineering
Volume 136, Issue 10
Abstract
Measurements from load tests may lead to numerical models that better reflect structural behavior. This kind of system identification is not straightforward due to important uncertainties in measurement and models. Moreover, since system identification is an inverse engineering task, many models may fit measured behavior. Traditional model updating methods may not provide the correct behavioral model due to uncertainty and parameter compensation. In this paper, a multimodel approach that explicitly incorporates uncertainties and modeling assumptions is described. The approach samples thousands of models starting from a general parametrized finite-element model. The population of selected candidate models may be used to understand and predict behavior, thereby improving structural management decision making. This approach is applied to measurements from structural performance monitoring of the Langensand Bridge in Lucerne, Switzerland. Predictions from the set of candidate models are homogenous and show an average discrepancy of 4–7% from the displacement measurements. The tests demonstrate the applicability of the multimodel approach for the structural identification and performance monitoring of real structures. The multimodel approach reveals that the Langensand Bridge has a reserve capacity of 30% with respect to serviceability requirements.
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Acknowledgments
Collaboration with the designers of the Langensand Bridge, Gabriele Guscetti and Claudio Pirazzi (Guscetti and Tournier), 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 would like to thank I. Laory and P. Gallay for their help during load testing. The city of Lucerne provided logistics support, the trucks for the load tests and the deformation sensors. This research is funded by the Swiss National Science Foundation under Contract No. NSF-CH200020-117670/1.
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© 2010 ASCE.
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Received: Jun 24, 2009
Accepted: Apr 5, 2010
Published online: Apr 13, 2010
Published in print: Oct 2010
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