Bridge System Performance Assessment from Structural Health Monitoring: A Case Study
Publication: Journal of Structural Engineering
Volume 135, Issue 6
Abstract
Based on the long-term monitored strain data induced by heavy vehicle traffic on an existing bridge, this paper presents an efficient approach to assessing the bridge system performance through a series-parallel system model consisting of bridge component reliabilities. The correlations among the bridge component safety margins are obtained by using actual traffic and strain data from structural health monitoring (SHM). The prediction of bridge system reliability in the future is dependent on the performance functions of components. Sensitivity studies with respect to system modeling, correlations, extreme value probability distributions, measurement errors, and number of observations are carried out. A case study of the proposed approach is provided on an existing highway bridge in Wisconsin, which was monitored in 2004 by the Advanced Technology for Large Structural Systems Center, a National Engineering Research Center at Lehigh University, Bethlehem, Pa, USA. This study provides a solid basis for integrating SHM data into practical assessment of bridge system performance.
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Acknowledgments
The support from the National Science Foundation through Grant No. NSFCMS-0639428, the Commonwealth of Pennsylvania, Department of Community and Economic Development, through the Pennsylvania Infrastructure Technology Alliance (PITA), and the U.S. Federal Highway Administration Cooperative Agreement Award UNSPECIFIEDDTFH61-07-H-00040 is gratefully acknowledged. The writers want to express their profound thanks to Mr. Ian Hodgson, Lehigh University, for his constructive comments and access to the data obtained during the long-term monitoring of the Wisconsin River Bridge I-39. The opinions and conclusions presented in this paper are those of the writers and do not necessarily reflect the views of the sponsoring organizations.
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© 2009 ASCE.
History
Received: Mar 24, 2008
Accepted: Dec 19, 2008
Published online: May 15, 2009
Published in print: Jun 2009
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