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Experimental veriication of bridge seismic damage states quantiied
by calibrating analytical models with empirical ield data

Swagata Banerjee and Masanobu Shinozuka
Department of Civil and Environmental Engineering, University of California, Irvine, CA, USA

Abstract: Bridges are one of the most vulnerable components of a highway transportation network system subjected
to earthquake ground motions. Prediction of resilience and sustainability of bridge performance in a probabilistic manner
provides valuable information for pre-event system upgrading and post-event functional recovery of the network. The
current study integrates bridge seismic damageability information obtained through empirical, analytical and experimental
procedures and quantiies threshold limits of bridge damage states consistent with the physical damage description given in
HAZUS. Experimental data from a large-scale shaking table test are utilized for this purpose. This experiment was conducted
at the University of Nevada, Reno, where a research team from the University of California, Irvine, participated. Observed
experimental damage data are processed to identify and quantify bridge damage states in terms of rotational ductility at bridge
column ends. In parallel, a mechanistic model for fragility curves is developed in such a way that the model can be calibrated
against empirical fragility curves that have been constructed from damage data obtained during the 1994 Northridge
earthquake. This calibration quantiies threshold values of bridge damage states and makes the analytical study consistent
with damage data observed in past earthquakes. The mechanistic model is transportable and applicable to most types and
sizes of bridges. Finally, calibrated damage state deinitions are compared with that obtained using experimental indings.
Comparison shows excellent consistency among results from analytical, empirical and experimental observations.

Keywords: highway bridges; nonlinear time history analysis; fragility curves; threshold damage limits; mechanistic
model; calibration