Structural model updating of an in-service bridge using dynamic data

Recent developments in instrumentation, modeling, and data collection have advanced the state of the art in structural health monitoring in many engineering areas. However, the application of these developments in civil engineering infrastructure still presents some challenges. With approximately 11% of the bridges in the USA classified as structural deficient and billions of dollars required for either replacement or rehabilitation, transportation authorities require more efficient methods for condition assessment of existing bridges and funding allocation. In this article, a frequency response function-based, two-step model updating technique is applied to the Powder Mill Bridge. The Powder Mill Bridge is a typical overpass bridge constructed in 2009 and located in the town of Barre, Massachusetts. The goal of this research is to obtain a baseline finite element model that captures the bridge’s behavior in its healthy condition using experimentally collected data from testing performed in 2010. The proposed two-step protocol successfully identified stiffness, mass, and damping parameters in simulated scenarios with contamination from measurement errors. Likewise, experimental validation using field collected dynamic data produced parameters that were reflective of the field-observed structural condition of the tested bridge. If the model updating protocol is repeated using collected data at standard intervals, the baseline could be eventually used to identify changes in structural parameters that are indicative of damage. Copyright © 2015 John Wiley & Sons, Ltd.