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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