Effects of changing ambient temperature on finite element model updating of the Dowling Hall Footbridge

In this paper, effects of changing ambient temperatures on finite element (FE) model updating of the Dowling Hall Footbridge are investigated. The Dowling Hall Footbridge is located on the Tufts University campus in Medford, Massachusetts. The footbridge is equipped with a continuous monitoring system that records vibration and temperature of the bridge once an hour or when triggered by large vibrations. Natural frequencies, mode shapes, and modal damping ratios of the structure are extracted from measured ambient vibration data using an automated data-driven stochastic subspace identification algorithm. The identified natural frequencies and mode shapes are then used for calibration/updating of an initial FE model of the bridge. However, the identified natural frequencies show significant variability with changing ambient temperature. This variability propagates through the FE model updating process and therefore yields uncertainty in the FE model updating results. A static polynomial model is estimated to represent the relationship between identified natural frequencies and measured temperatures. This model is then used to “remove” the temperature effects from the identified natural frequencies. Two sets of FE models are updated in this study based on 17 weeks of hourly-identified modal parameters, before and after removing the temperature effects. The proposed approach is successful in minimizing the effects of changing ambient temperature on FE model updating of the Dowling Hall Footbridge. Accounting for the temperature effects in the FE model updating process reduces the variability of temperature-sensitive updating parameters and therefore decreases the probability of missed identification of damage.

► Effects of changing ambient temperatures on FE model updating of a footbridge are studied.
► Two sets of FE models are updated based on 17 weeks of data, before and after removing temperature effects.
► The variations of updating parameters are quantified after the temperature effects are removed.
► More accurate damage identification results are obtained when accounting for temperature effects.