Probabilistic damage identification of the Dowling Hall footbridge through Hierarchical Bayesian model updating Behmanesh, Iman; Moaveni, Babak
In this paper, a Hierarchical Bayesian finite element model updating framework is applied for probabilistic identification of simulated damage on the Dowling Hall Footbridge. The footbridge is located at Tufts campus and is equipped with a continuous monitoring system, including 12 accelerometers. Structural damage is simulated by the addition of mass on a small segment of the footbridge, and the Hierarchical framework is used to identify the location and extent of the damage (added mass), and to quantify the prediction uncertainties. This framework is well suited for applications to civil structures, where the structural properties (stiffness, mass) can be considered time-variant due to changing environmental conditions such as temperature, wind speed, or traffic.
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Attribution-NonCommercial-NoDerivs 2.5 Canada